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Abstract Background Ferroptosis can be used as a powerful predictor of cancer prognosis. HPV persistent infection is the main cause of cervical cancer, so it is very important to improve the prognosis of patients. Therefore, it is necessary to explore the value of HPV-ferroptosis related genes as prognostic biomarkers of cervical cancer patients. Methods In this study, differentially expressed HPV-ferroptosis related genes were obtained from GSE7410, HPV gene set crossed with iron death genes. Five HPV-ferroptosis related genes with prognostic features were finally identified: CYBB, VEGFA, CKB, EFNA1 and HELLS. Multifactorial Cox regression was applied to establish and validate the prognostic model, and drug susceptibility and immune infiltration analyses were also performed. Results The prognostic model was validated in the training set (TCGA) and validation set (GSE44001). Kaplan–Meier curves reveal significant differences in overall survival (OS) between high-risk and low-risk groups. Receiver operating characteristic (ROC) curve reflects the stability and accuracy of the prognostic model established in this study. In terms of immune function, T cell costimulation was better in the low-risk group than in the high-risk group (P

Abstract Background Enhancing social participation is not only the main goal of stroke survivors' community rehabilitation but also a protective factor affecting their physical and emotional health. The current state of stroke survivors' social participation is not encouraging due to the high disability incidence of stroke. Spouses may play a facilitating role in the social participation of patients by providing them with support and assistance. However, there remains a lack of evidence specifically regarding dyadic coping interventions of social participation for stroke survivors, and the intervention strategies are still underdeveloped without clear theoretical frameworks. Therefore, this proposed study aims to develop and evaluate the effectiveness of the Dyadic Coping Intervention of Social Participation (DCISP) for survivors of first-episode homebound stroke. Methods A single-blind (assessor-blinded), randomized controlled trial will be conducted to verify the effectiveness of DCISP. The randomized controlled trial will be preceded by a feasibility study (N = 20) of DCISP in stroke survivors. Stroke survivors will be randomly classified (1:1) into either a control (N = 50) or an experimental group (N = 50). In addition to routine care, participants in the experimental group will receive six 40 ~ 45 min sessions of guidance, once every two weeks. The primary outcome is social participation of stroke survivors, measured using Impact on Participation and Autonomy Questionnaire (IPA) and Utrecht Scale for Evaluation of Rehabilitation-Participation (USER-P), and the secondary outcomes will be measured by Knowledge Questionnaire for Stroke Patients (SPKQ), Stroke-specific Quality of Life Scale (SS-QOL), Dyadic Coping Inventory (DCI), Modified Rankin Scale (mRS) and Zarit Caregiver Burden Interview (ZBI-22). These will be measured at baseline(T0), during the intervention (T1 = 1 month), and after intervention completion (T2 = 3 months, T3 = 6 months). Discussion Findings from the study will provide evidence of the effects of DCISP on improving the social participation of first-episode homebound stroke survivors. The results of this study may support the implementation of survivor–spouse dyads care support in stroke survivors and provide a reference for clinical rehabilitation nursing practice, offering new insights into nursing interventions for stroke patients. Trial registration Chinese Clinical Trial Registry (ChiCTR) ChiCTR2400083072. Registered on 20 July 2023.

Abstract Background Nursing interns encounter numerous professional pressures during clinical practice. Assessing adversity quotient levels and understanding the influencing factors are crucial for supporting students’ seamless transition to professional nurses. Purpose This study examined the adversity quotient subtypes of nursing interns and explored the relationships between adversity quotient and depression, coping styles, positive psychological capital, and professional adaptability. Methods This study employed a cross-sectional research design, involving a survey of 287 nursing interns in five general hospitals in Shanghai, China. Latent profile analysis was conducted to explore the subtypes of adversity quotient with the four domains as input variables. Multinomial logistic regression models and multiple correspondence analysis were used for subsequent data analysis. Results The average adversity quotient score of the nursing interns was 116.63 ± 32.22. A three-profile solution was obtained based on the latent profile analysis results. Three distinct subtypes emerged: a high-adversity quotient subtype (n = 50, 17.4%), a medium-adversity quotient subtype (n = 189, 65.9%), and a relatively low-adversity quotient subtype (n = 48, 16.7%). Multinomial logistic regression revealed that nursing interns in the high-adversity quotient subtype tended to be male, and had higher scores for positive psychological capital, negative coping style, and professional adaptability (p

The ongoing high occurrence of harmful infectious diseases significantly threatens human health. Existing methods used to control such diseases primarily involve targeting the pathogens, usually neglecting the vital role of host factors in disease advancement. Gamma delta (γδ) T cells act as a bridge between innate and adaptive immunity, playing a crucial role in combating pathogen invasion. Among these γδT cell subsets, which are categorized based on T cell receptor delta variable expression patterns, V delta (δ) 1+ T cells possess unique recognition abilities and regulatory characteristics and actively engage in various immune responses. The differentiation, development, and immune reactivity of Vδ1+ T cells are closely associated with the initial and progressive stages of infectious diseases. This article provides an overview of the classification, distribution, differentiation, and development of Vδ1+ T cells and their mechanisms in combating pathogenic infections, offering new insights for disease diagnosis and treatment.

Background and objective Lung squamous cell carcinoma (LUSC) is a subtypes of non-small cell lung cancer (NSCLC). It has been reported that members of the protocadherin γ family can regulate tumor cell growth by inhibiting the Wnt signaling pathway. Protocadherin-gamma subfamily B4 (PCDHGB4) as a family member in LUSC was rarely reported. The aim of this study was to investigate the role and potential prognostic value of PCDHGB4 in the development of LUSC using bioinformatics methods. Methods The Cancer Genome Atlas (TCGA), cBioPortal and UALCAN databases were used to analyze the expression, prognosis, clinicopathological features, immune cell infiltration, immune regulatory genes, immune checkpoint inhibitors (ICIs), and methyltransferases of PCDHGB4 in LUSC. At the single cell level, we analyzed the clustering results of cell subtypes and the expression of PCDHGB4 in different immune cell subpopulations. In addition, we compared the promoter methylation levels of PCDHGB4 in LUSC tissues and normal tissues and performed protein-protein interaction and mutation analysis. Finally, enrichment analysis was performed based on the differentially expressed genes. Results Bioinformatics analysis results showed that the expression level of PCDHGB4 in LUSC tissues was lower than that in normal tissues. Survival analysis showed that increased PCDHGB4 expression was associated with poor prognosis. Single-cell sequencing analysis showed that PCDHGB4 was expressed in T cells, monocytes or macrophages, and dendritic cells. It was further found that PCDHGB4 played an important role in tumor immunity and confirmed that PCDHGB4 was associated with immune checkpoints, immune regulatory genes, and methyltransferases. Besides, enrichment analysis revealed that PCDHGB4 was involved in multiple cancer-related pathways. Conclusion The expression of PCDHGB4 was low in LUSC. PCDHGB4 was related to the poor prognosis of patients, and PCDHGB4 was closely related to the infiltration and pathway of tumor immune cells. PCDHGB4 may be a potential prognostic marker and a new target for immunotherapy in LUSC.

Abstract Background To explore the efficacy of a prediction model based on diffusion‐weighted imaging (DWI) features extracted from deep learning (DL) and radiomics combined with clinical parameters and apparent diffusion coefficient (ADC) values to identify microsatellite instability (MSI) in endometrial cancer (EC). Methods This study included a cohort of 116 patients with EC, who were subsequently divided into training (n = 81) and test (n = 35) sets. From DWI, conventional radiomics features and convolutional neural network‐based DL features were extracted. Random forest (RF) and logistic regression were adopted as classifiers. DL features, radiomics features, clinical variables, ADC values, and their combinations were applied to establish DL, radiomics, clinical, ADC, and combined models, respectively. The predictive performance was evaluated through the area under the receiver operating characteristic curve (AUC), total integrated discrimination index (IDI), net reclassification index (NRI), calibration curves, and decision curve analysis (DCA). Results The optimal predictive model, based on an RF classifier, comprised four DL features, three radiomics features, two clinical variables, and an ADC value. In the training and test sets, this model exhibited AUC values of 0.989 (95% CI: 0.935–1.000) and 0.885 (95% CI: 0.731–0.967), respectively, demonstrating different degrees of improvement compared with the clinical, DL, radiomics, and ADC models (AUC‐training = 0.671, 0.873, 0.833, and 0.814, AUC‐test = 0.685, 0.783, 0.708, and 0.713, respectively). The NRI and IDI analyses revealed that the combined model resulted in improved risk reclassification of the MSI status compared to the clinical, radiomics, DL, and ADC models. The calibration curves and DCA indicated good consistency and clinical utility of this model, respectively. Conclusions The predictive model based on DWI features extracted from DL and radiomics combined with clinical parameters and ADC values could effectively assess the MSI status in EC.

BackgroundAlzheimer's disease (AD) is a progressive and irreversible neurodegenerative disorder that has become one of the major health concerns for the elderly. Computer-aided AD diagnosis can assist doctors in quickly and accurately determining patients' severity and affected regions.MethodsIn this paper, we propose a method called MADNet for computer-aided AD diagnosis using multimodal datasets. The method selects ResNet-10 as the backbone network, with dual-branch parallel extraction of discriminative features for AD classification. It incorporates long-range dependencies modeling using attention scores in the decision-making layer and fuses the features based on their importance across modalities. To validate the effectiveness of our proposed multimodal classification method, we construct a multimodal dataset based on the publicly available ADNI dataset and a collected XWNI dataset, which includes examples of AD, Mild Cognitive Impairment (MCI), and Cognitively Normal (CN).ResultsOn this dataset, we conduct binary classification experiments of AD vs. CN and MCI vs. CN, and demonstrate that our proposed method outperforms other traditional single-modal deep learning models. Furthermore, this conclusion also confirms the necessity of using multimodal sMRI and DTI data for computer-aided AD diagnosis, as these two modalities complement and convey information to each other. We visualize the feature maps extracted by MADNet using Grad-CAM, generating heatmaps that guide doctors' attention to important regions in patients' sMRI, which play a crucial role in the development of AD, establishing trust between human experts and machine learning models.ConclusionWe propose a simple yet effective multimodal deep convolutional neural network model MADNet that outperforms traditional deep learning methods that use a single-modality dataset for AD diagnosis.

Abstract Background RNA modifications have been proven to play fundamental roles in regulating cellular biology process. Recently, maladjusted N7-methylguanosine (m7G) modification and its modifiers METTL1/WDR4 have been confirmed an oncogene role in multiple cancers. However, the functions and molecular mechanisms of METTL1/WDR4 in acute myeloid leukemia (AML) remain to be determined. Methods METTL1/WDR4 expression levels were quantified using qRT-PCR, western blot analysis on AML clinical samples, and bioinformatics analysis on publicly available AML datasets. CCK-8 assays and cell count assays were performed to determine cell proliferation. Flow cytometry assays were conducted to assess cell cycle and apoptosis rates. Multiple techniques were used for mechanism studies in vitro assays, such as northern blotting, liquid chromatography-coupled mass spectrometry (LC–MS/MS), tRNA stability analysis, transcriptome sequencing, small non-coding RNA sequencing, quantitative proteomics, and protein synthesis measurements. Results METTL1/WDR4 are significantly elevated in AML patients and associated with poor prognosis. METTL1 knockdown resulted in reduced cell proliferation and increased apoptosis in AML cells. Mechanically, METTL1 knockdown leads to significant decrease of m7G modification abundance on tRNA, which further destabilizes tRNAs and facilitates the biogenesis of tsRNAs in AML cells. In addition, profiling of nascent proteins revealed that METTL1 knockdown and transfection of total tRNAs that were isolated from METTL1 knockdown AML cells decreased global translation efficiency in AML cells. Conclusions Taken together, our study demonstrates the important role of METTL1/WDR4 in AML leukaemogenesis, which provides a promising target candidate for AML therapy.

Combining with the characteristics of Fe3O4 and activated carbon, magnetic granular activated carbon (GAC–Fe3O4) was prepared by chemical coprecipitation. With GAC–Fe3O4 as the adsorbent, the effects of GAC–Fe3O4 dosage, the initial pH of wastewater temperature, and the initial concentration of copper (II) and chromium (Ⅵ) on the removal performance were explored. The adsorption process of copper (II) and chromium (VI) on magnetic GAC was studied using adsorption kinetics, adsorption isotherms, scanning electron microscopy, and infrared spectroscopy. The experimental results indicate that among these influencing factors, the pH value of wastewater plays a vital role in the removal efficiency. When the pH value was 6 and 2, the initial concentration of copper (II) and chromium (VI) ions was 5 ppm, the optimum removal efficiencies of copper (II) and chromium (VI) were 99.98 and 96.39%, respectively. As to the adsorption mechanism of GAC–Fe3O4, the adsorption of copper (II) and chromium (VI) in wastewater was more consistent with the Langmuir model. The adsorption process in this study can be well explained by the pseudo-second-order kinetic model. HIGHLIGHTS The preparation of a magnetically activated carbon particles loaded with ferric oxide.; Magnetic granular activated carbon (GAC) has good recoverability.; Magnetic GAC has a good treatment effect on wastewater containing copper (II) and chromium (VI).;

In this study, a turn-on fluorescence sensor for the detection of adenosine 5′-triphosphate (ATP) was developed and tested using ATP-DNA2-Ag NCs. The results showed that the fluorescence of ATP-DNA2-Ag NCs was significantly enhanced with the addition of ATP. The fluorescence enhancement was a result of the specific binding activity of the ATP aptamer and ATP, which caused G-rich sequences to approach the dark DNA-Ag NCs, owing to the alteration in ATP aptamer conformation. The proposed sensor demonstrated a good linear range of 18–42 mM and a limit of detection (LOD) of 2.8 μM. The sensor’s features include sensitivity, selectivity, and simple operation. In addition, the proposed sensor successfully measured ATP in 100-fold diluted fetal bovine serum.

Abstract Objective Thyroid cancer is one of the most frequently reported endocrine system malignancies. It is difficult to distinguish follicular thyroid cancer (FTC) from follicular thyroid adenoma (FTA) during pathological diagnosis in patients without lymph nodes or distant metastases. Therefore, we conducted a retrospective study to investigate the significance of SLC5A8 methylation and expression in the diagnosis and prognosis of FTC. Methods We used 165 tissue samples, including FTC (n = 58), thyroid tumors of uncertain malignant potential (TT-UMP, n = 40), and FTA (n = 67), to explore the differences in SLC5A8 methylation and mRNA transcription in different pathological types. Survival analysis was conducted to evaluate the recurrence rate at a 5-year follow-up. Results The SLC5A8 methylation positive rate was higher in patients with thyroglobulin ≥ 40 μg/l and Chol ≥ 5.17 mmol/l, and it was higher in patients with FTC (n = 42, 72.4%) than those with FTA (n = 27, 40.3%) and TT-UMP (n = 23, 57.5%). The relative concentration of SLC5A8 mRNA was lower in patients with FTC than in those with FTA (p

Abstract Background Intramuscular fat (IMF) and intramuscular connective tissue (IMC) are often seen in human myopathies and are central to beef quality. The mechanisms regulating their accumulation remain poorly understood. Here, we explored the possibility of using beef cattle as a novel model for mechanistic studies of intramuscular adipogenesis and fibrogenesis. Methods Skeletal muscle single‐cell RNAseq was performed on three cattle breeds, including Wagyu (high IMF), Brahman (abundant IMC but scarce IMF), and Wagyu/Brahman cross. Sophisticated bioinformatics analyses, including clustering analysis, gene set enrichment analyses, gene regulatory network construction, RNA velocity, pseudotime analysis, and cell–cell communication analysis, were performed to elucidate heterogeneities and differentiation processes of individual cell types and differences between cattle breeds. Experiments were conducted to validate the function and specificity of identified key regulatory and marker genes. Integrated analysis with multiple published human and non‐human primate datasets was performed to identify common mechanisms. Results A total of 32 708 cells and 21 clusters were identified, including fibro/adipogenic progenitor (FAP) and other resident and infiltrating cell types. We identified an endomysial adipogenic FAP subpopulation enriched for COL4A1 and CFD (log2FC = 3.19 and 1.92, respectively; P

Background and objective Lung cancer is the most common malignant tumor in China, lung adenocarcinoma (LUAD) is the main type of lung cancer, which is a serious threat to people's life and health. At present, there are fewer studies on the role of Dikkopf1 (DKK1) in lung adenocarcinoma. The aim of this study was to investigate the role and potential prognostic value of DKK1 in the development of lung adenocarcinoma by bioinformatics methods. Methods Several databases, such as genotype-tissue expression (GTEx), The Cancer Genome Atlas (TCGA) and tumor-immune system interactions database (TISIDB), were used to analyze the expression, clinicopathological features, immune cell infiltration, prognosis and methylation of DKK1 in lung adenocarcinoma. Then, linked immune cell infiltration Omics database was used to analyze the co-expressed genes of DKK1 and their functional enrichment. Finally, 59 pathological samples of paraffin-embedded lung adenocarcinoma patients who underwent surgery at the Affiliated Cancer Hospital of Xinjiang Medical University between 2016 and 2017 were collected for the validation of the prognostic value of expression by immunohistochemistry (IHC) test. Results The results of bioconfidence analysis showed that the expression level of DKK1 in lung adenocarcinoma tissues was higher than that in normal tissues, the expression in advanced cancers was higher than that in early stages, and the experimental validation revealed that among 59 cases of lung adenocarcinoma, there were 15 cases of negative expression (25.4%), 18 cases of weakly positive expression (30.5%), and 26 cases of strongly positive expression (44.1%). The different expression of DKK1 is related to methylation, prognosis and the activities of various immune cells. Functional enrichment shows that DKK1 may be involved in skin development and cell-substrate junction, and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis shows that DKK1 is related to ABC transporters. Bioinformatics analysis and clinical case specimens showed that high DKK1 expression was associated with poorer prognosis in patients with lung adenocarcinoma. Conclusion High expression of DKK1 in lung adenocarcinoma is associated with poor prognosis. DKK1 is closely associated with tumor immune cell infiltration and pathways. DKK1 can be considered as a potential prognostic marker and a novel target for immunotherapy of lung adenocarcinoma.

Objective: To explore the effect of Poria cocos polysaccharides (Poria cocos polysaccharide, PPS) on anxiety and depression-like behaviors induced by lipopolysaccharide (LPS) and analyze its mechanism. Methods: BV-2 cells were divided into control group, LPS group, LPS+fluoxetine group and LPS+PPS (PPS of 4, 8, 16 μmol/L, respectively). After 24 h treatment, the level of intracellular reactive oxygen species (ROS) was detected by dichlorodihydrofluorescein dihydroacetate (DCFH-DA) fluorescence probe, the level of NO in culture supernatant was detected by griess method, and the levels of TNF-α and IL-1β in cell supernatant were detected by enzyme linked immunosorbent assay (ELISA). The levels of CD206, CD16/32 and NF-κB p65 were detected by western blot. In animal experiment, mice were divided into control group, model group, LPS+fluoxetine group, LPS+PPS low dose group (20 mg/kg) and LPS+PPS high dose group (80 mg/kg). Depression-like behavior test was performed, and the concentration of TNF-α, IL-1β and IL-18 in hippocampus was detected. The protein levels of CD206, CD16/32, NF-κB p65, NLRP3, ASC and Cleaved caspase-1 in hippocampus were analyzed. Results: Compared with LPS group, 4,8,16 μmol/L PPS significantly decreased the relative fluorescence intensity of ROS (P

IntroductionFerula is a traditional, edible, and important medicinal plant with high economic value. The distinction between edible and non-edible Ferula remains unclear.MethodsIn this study, headspace solid-phase microextraction coupled to gas chromatography-mass spectrometry (HS-SPME/GC-MS) and ultra-high performance liquid chromatography-tandem mass spectrometry (UHPLC-MS/MS) non-targeted metabolomics techniques were used to systematically and comprehensively analyse secondary metabolites in the leaves and roots of four species of Ferula, considering their edibility.ResultsA total of 166 leaf volatile organic compounds (VOCs) and 1,079 root metabolites were identified. Additionally, 42 potential VOCs and 62 differential root metabolites were screened to distinguish between edible and non-edible Ferula. Twelve volatile metabolites were specific to F. feurlaeoides, and eight compounds were specific to the three edible Ferula species. The results showed that compounds containing sulphur, aldehydes, and ketones, which produce pungent odours, were the primary sources of the strong odour of Ferula. The root differential metabolites include 13 categories, among which the high concentration group is organic acids, amino acids, terpenoids and fatty acids. The bioactive metabolites and VOCs in the roots exhibited species-specific characteristics. VOCs with various odors were linked to the distribution of root metabolites in both edible and non-edible Ferula plants. The screened root markers may contribute to the formation of characteristic VOCs.DiscussionThis study identified the difference in flavour between edible and non-edible Ferula plants and, for the first time, demonstrated the contribution of the efficacy of Ferula root to the unique flavour of the above-ground parts of Ferula. These results provide a theoretical basis for selecting Ferula for consumption and help evaluate the quality of different species of Ferula. Our findings may facilitate food processing and the further development of Ferula.

Summary: Here, we present a protocol to isolate progenitor cells from mouse epididymal visceral adipose tissue and construct bulk RNA and assay for transposase-accessible chromatin with sequencing (ATAC-seq) libraries. We describe steps for adipose tissue collection, cell isolation, and cell staining and sorting. We then detail procedures for both ATAC-seq and RNA sequencing library construction. This protocol can also be applied to other tissues and cell types directly or with minor modifications.For complete details on the use and execution of this protocol, please refer to Liu et al. (2023).1 : Publisher’s note: Undertaking any experimental protocol requires adherence to local institutional guidelines for laboratory safety and ethics.

Abstract. Alzheimer's disease (AD) is a neurodegenerative disease that gradually impairs cognitive functions. Recently, there has been a conceptual shift toward AD to view the disease as a continuum. Since AD is currently incurable, effective intervention to delay or prevent pathological cognitive decline may best target the early stages of symptomatic disease, such as subjective cognitive decline (SCD), in which cognitive function remains relatively intact. Diagnostic methods for identifying AD, such as cerebrospinal fluid biomarkers and positron emission tomography, are invasive and expensive. Therefore, it is imperative to develop blood biomarkers that are sensitive, less invasive, easier to access, and more cost effective for AD diagnosis. This review aimed to summarize the current data on whether individuals with SCD differ reliably and effectively in subjective and objective performances compared to cognitively normal elderly individuals, and to find one or more convenient and accessible blood biomarkers so that researchers can identify SCD patients with preclinical AD in the population as soon as possible. Owing to the heterogeneity and complicated pathogenesis of AD, it is difficult to make reliable diagnoses using only a single blood marker. This review provides an overview of the progress achieved to date with the use of SCD blood biomarkers in patients with preclinical AD, highlighting the key areas of application and current challenges.

In this study, Cu2+ modulated silver nanoclusters were constructed for the turn-on, label-free detection of L-histidine. Six Ag NCs protected by oligonucleotides (DNA-Ag NCs) were tested in a series of experiments. Finally, A-DAN-Ag NCs were chosen as the best candidate due to their excellent fluorescent properties. The fluorescence of A-DAN-Ag NCs was quenched using Cu2+ through energy or electron transfer. However, quenched fluorescence could be restored dramatically in the presence of L-histidine due to Cu2+ liberation from A-DAN-Ag NCs and because of the chelation between the imidazole group of L-histidine and Cu2+. The proposed sensor exhibited high selectivity towards L-histidine over other amino acids, with a limit of detection (LOD) of 0.096 μM ranging from 0 to 8 μM. The proposed sensor succeeded in detecting L-histidine in diluted human urine. Therefore, the sensor has promising practical applications in biological systems.

In current times, reconstruction of remote sensing images using super-resolution is a prominent topic of study. Remote sensing data have a complex spatial distribution. Compared with natural pictures, remote sensing pictures often contain subtler and more complicated information. Most super-resolution reconstruction algorithms cannot restore all the information contained in remote sensing images when reconstructing them. The content of some areas in the reconstructed images may be too smooth, and some areas may even have color changes, resulting in lower quality reconstructed images. In response to the problems presenting in current reconstruction algorithms about super-resolution, this article proposes the SRGAN-MSAM-DRC model (SRGAN model with multi-scale attention mechanism and dense residual connection). This model roots in generative adversarial networks and incorporates multi-scale attention mechanisms and dense residual connections into the generator. Furthermore, residual blocks are incorporated into the discriminator. We use some remote sensing image datasets of real-world data to evaluate this model, and the results indicate the SRGAN-MSAM-DRC model has shown enhancements in three evaluation metrics for reconstructed images about super-resolution. Compared to the basic SRGAN model, the SSIM (structural similarity), PSNR (peak signal-to-noise ratio), and IE (image entropy) increase by 5.0%, 4.0%, and 4.1%, respectively. From the results, we know the quality of the reconstructed images of remote sensing using the SRGAN-MSAM-DRC model is better than basic SRGAN model, and verifies that the model has good applicability and performance in reconstruction of remote sensing images using super-resolution.

Interplanting is an efficient method of improving nutrient utilization. However, the impact of intraspecific interplanting on rhizosphere microbial nitrogen cycling needs to be studied further. In this study, two corn cultivars were selected as the materials: Zhengdan958 (ZD958, high nitrogen use efficiency) and Denghai3622 (DH3622, low nitrogen use efficiency). Three planting patterns (interplanting, ZD958 monocropping, and DH3622 monocropping) were set up to study the effects of interplanting on crop growth and rhizosphere microbial nitrogen cycle function under two nitrogen levels: low nitrogen (140 kg N ha−1) and normal nitrogen (280 kg N ha−1). The results showed that the grain yield and nitrogen content in interplanting were significantly increased due to an enhanced leaf area index and root dry weight. The nitrogen accumulation and nitrogen use efficiency were enhanced by 8.14% and 19.38% in interplanting, which resulted in reductions in NH4+ and NO3− content in the rhizosphere. Interplanting enhanced rhizosphere nitrogen cycling processes; nitrification, denitrification, and nitrate reduction were increased. This study demonstrated that interplanting promotes corn nitrogen acquisition from the soil and indirectly regulates rhizosphere microbial function. These findings imply that the intraspecific interplanting of crops with appropriate functional traits is a promising approach to establishing diversified, productive, and efficient resource utilization ecosystems.

Intestinal diseases caused by opportunistic pathogens seriously threaten the health and survival of giant pandas. However, our understanding of gut pathogens in different populations of giant pandas, especially in the wild populations, is still limited. Here, we conducted a study based on 52 giant panda metagenomes to investigate the composition and distribution of gut pathogens and virulence factors (VFs) in five geographic populations (captive: GPCD and GPYA; wild: GPQIN, GPQIO, and GPXXL). The results of the beta-diversity analyzes revealed a close relationship and high similarity in pathogen and VF compositions within the two captive groups. Among all groups, Proteobacteria, Firmicutes, and Bacteroidetes emerged as the top three abundant phyla. By using the linear discriminant analysis effect size method, we identified pathogenic bacteria unique to different populations, such as Klebsiella in GPCD, Salmonella in GPYA, Hafnia in GPQIO, Pedobacter in GPXXL, and Lactococcus in GPQIN. In addition, we identified 12 VFs that play a role in the intestinal diseases of giant pandas, including flagella, CsrA, enterobactin, type IV pili, alginate, AcrAB, capsule, T6SS, urease, type 1 fimbriae, polar flagella, allantoin utilization, and ClpP. These VFs influence pathogen motility, adhesion, iron uptake, acid resistance, and protein regulation, thereby contributing to pathogen infection and pathogenicity. Notably, we also found a difference in virulence of Pseudomonas aeruginosa between GPQIN and non-GPQIN wild populations, in which the relative abundance of VFs (0.42%) of P. aeruginosa was the lowest in GPQIN and the highest in non-GPQIN wild populations (GPXXL: 23.55% and GPQIO: 10.47%). In addition to enhancing our understanding of gut pathogens and VFs in different geographic populations of giant pandas, the results of this study provide a specific theoretical basis and data support for the development of effective conservation measures for giant pandas.

Abstract The roadway in coal mine is prone to deformation of the surrounding rock under the influence of complex disturbance, which induces the imbalance of support attitude matching between roadway surrounding rock and advanced coupling support equipment, breaks the mechanical balance of the original coupling support system, and causes safety accidents. The postures and offsets of the various working spaces of the advanced hydraulic supports under the influence of complex disturbances are systematically analyzed. The D–H parameter matrix transformation method is used to establish the spatial posture kinematic model of a single/group of advanced hydraulic supports. The posture parameters of each key node are obtained through global coordinate transformation. Based on the comparison of the working attitude parameters of the support obtained through simulation analysis and model calculation, the average absolute error of the support height calculation results of the single group of advanced hydraulic support attitude model is 3.92 mm, and that of the coordinate calculation results of the advanced hydraulic support group is (3.26 mm, 1.99 mm), which meet the accuracy requirements of the advanced hydraulic support attitude monitoring. Finally, the spatial attitude kinematic model of a single/group of advanced hydraulic supports is verified and analyzed by using the advanced hydraulic support attitude monitoring test bench. The maximum error value of the experimental results is 4.9 mm, which verifies the accuracy of the established spatial attitude kinematic model of the advanced hydraulic support. The research results can provide theoretical and technical support for the intelligentization of the advanced coupling support system and the safe and efficient mining of coal mine.

After myocardial infarction, the massive death of cardiomyocytes leads to cardiac fibroblast proliferation and myofibroblast differentiation, which contributes to the extracellular matrix remodelling of the infarcted myocardium. We recently found that myofibroblasts further differentiate into matrifibrocytes, a newly identified cardiac fibroblast differentiation state. Cardiac fibroblasts of different states have distinct gene expression profiles closely related to their functions. However, the mechanism responsible for the gene expression changes during these activation and differentiation events is still not clear. In this study, the gene expression profiling and genome-wide accessible chromatin mapping of mouse cardiac fibroblasts isolated from the uninjured myocardium and the infarct at multiple time points corresponding to different differentiation states were performed by RNA sequencing (RNA-seq) and the assay for transposase-accessible chromatin with high-throughput sequencing (ATAC-seq), respectively. ATAC-seq peaks were highly enriched in the promoter area and the distal area where the enhancers are located. A positive correlation was identified between the expression and promoter accessibility for many dynamically expressed genes, even though evidence showed that mechanisms independent of chromatin accessibility may also contribute to the gene expression changes in cardiac fibroblasts after MI. Moreover, motif enrichment analysis and gene regulatory network construction identified transcription factors that possibly contributed to the differential gene expression between cardiac fibroblasts of different states.

BackgroundMeasurements of IgG antibodies to wild-type SARS-CoV-2 antigens can assess vaccine efficacy, but the absolute risk of Omicron symptomatic infection at different IgG levels for children and adolescents remains uncertain, as well as the minimum effective antibody level. We sought to determine the relationship between the tertiles of IgG antibodies to wild-type SARS-CoV-2 antigens and children with symptomatic infection of the pandemic and duration to negative conversion in China for the first time.MethodsA retrospective study was conducted, including 168 participants under 18 years old from the No.2 People’s Hospital of Lanzhou, China, diagnosed with Omicron variant BA.2.38 between July 8, 2022, and August 2, 2022. We calculated odds ratios (OR) in univariate and multivariate regression to assess the association of symptomatic infection with the tertiles of IgG, respectively. Kaplan–Meier curves and Cox proportional hazards regression were used to evaluate the relationship between IgG level and negative conversion time.ResultsThe average age of the 168 children included in this study was 7.2 (4.7) years old, 133 (79.2%) were symptomatic patients, and the average negative conversion time was 12.2 (3.5) days. The participants with high IgG levels were less likely to become symptomatic, had a shorter turnaround time, and had higher values of IgM and nucleic acid CT. Compared to those with the lowest tertile of IgG, patients with the highest tertile had a 91% lower risk of developing a symptomatic infection after fully adjusting for confounders (OR = 0.09, 95% CI, 0.02-0.36, p = 0.001). There’s no robust relationship between IgG level and negative conversion time in multivariate Cox regression.ConclusionThe risk of developing a symptomatic infection can be predicted independently by tertiles of IgG antibodies to wild-type SARS-CoV-2 antigens. High IgG levels can inhibit viral replication, vastly reduce the risk of symptomatic infections and promote a virus-negative conversion, especially when IgG quantitative detection was ≥3.44 S/CO, a potential threshold for protection and booster strategy in the future. More data and research are needed in the future to validate the predictive models.

Omicron variants of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is a health concern for both unvaccinated and vaccinated individuals against coronavirus disease 2019 (COVID-19). To date, the humoral immune response following vaccination and natural infection remains uncharacterized in children ages 17 years and younger. To address this concern, we performed clinical and immunological analyses of IgM and IgG antibody responses to SARS-CoV-2 Omicron BA.2.38 infection in 64 pediatric patients. COVID-19 symptom severity decreased with age in pediatric patients, from 70.8% (17/24) in patients 0–2 years of age to 50% (6/12) and 50% (14/28) in patients 3–5 years and 6–17 years of age, respectively. Furthermore, fewer patients experienced symptoms when vaccinated with the CoronaVac or BBIBP-CorV vaccine (50%, 13/26) than unvaccinated patients (71%, 22/31). Using a protein array, we found that the Omicron BA.2.38 infection induced antibody responses to other Omicron variants (Omicron BA.1-BA.5), which increased with vaccination. Notably, non-Omicron and Omicron variants showed distinct serotypes. Altogether, our results provide insight into the clinical and immunological characteristics of pediatric patients with COVID-19 Omicron BA.2.38 who have and have not been vaccinated against COVID-19. These data may help develop more effective diagnostic tests and vaccines in the future.

Tobacco is a critical cash crop in China, so its growing status has received more and more attention. How to acquire accurate plant area, row spacing, and plant spacing at the same time have been key points for its grow status monitoring and yield prediction. However, accurately detecting small and densely arranged tobacco plants during the rosette stage poses a significant challenge. In Sichuan Province, the contours of scattered tobacco fields with different shapes are not well-extracted. Additionally, there is a lack of simultaneous methods for extracting crucial tobacco planting information, including area, row spacing, and plant spacing. In view of the above scientific problems, we proposed a method to extract the planting information of tobacco at the rosette stage with Unmanned Aerial Vehicle (UAV) remote sensing images. A detection model, YOLOv8s-EFF, was constructed for the small and weak tobacco in the rosette stage. We proposed an extraction algorithm for tobacco field area based on extended contours for different-shaped fields. Meanwhile, a planting distance extraction algorithm based on tobacco coordinates was presented. Further, four experimental areas were selected in Sichuan Province, and image processing and sample label production were carried out. Four isolated tobacco fields with different shapes in four experimental areas were used to preliminarily verify the effectiveness of the model and algorithm proposed. The results show that the precision ranges of tobacco field area, row spacing, and plant spacing were 96.51~99.04%, 90.08~99.74%, and 94.69~99.15%, respectively. And another two experimental areas, Jiange County, Guangyuan, and Dazhai County, Gulin County, and Luzhou, were selected to evaluate the accuracy of the method proposed in the research in practical application. The results indicate that the average accuracy of tobacco field area, row spacing, and plant spacing extracted by this method reached 97.99%, 97.98%, and 98.31%, respectively, which proved the extraction method of plant information is valuable.

Abstract The advanced hydraulic support group combined with bolts (cables) constitutes the advanced coupling support system, which can ensure the stability of coal mine roadway safely and effectively. To explore the influence of the initial bearing capacity of the advanced hydraulic support on roadway roof deformation under anchor bar (cable) action. According to the actual geological conditions and roadway support of the 15106 working faces in Pingshuo Coal Mine, Yangquan, and Shanxi. Based on the change in the stress and displacement of the half‐space body under normal force in elastic theory and combined with the linear superposition principle, the contact mechanics model of the advanced hydraulic support group and roadway roof under anchorage is established. Selecting the measured anchor bar (cable) preload in the coal mine as the input load of the model, the stress and displacement distribution of the roadway roof under different initial bearing capacities are calculated. The calculation results show that the stress and displacement of the roadway roof along the axis exhibit a “symmetrical distribution” and the whole roadway exhibits a “saddle surface” gradient distribution during the active support of advanced hydraulic support under anchorage. The increase in the initial bearing capacity of the advanced hydraulic support has a great influence on the support effect in the middle area of the roadway and has a relatively small influence on the support effect in the surrounding area of the roof. With an increase in an initial support capacity, the stress gradient changes violently but substantially less than it would under the crushing strength of the surrounding rock. Using the similar simulation experiment theory, a similar simulation experiment roadway was established at 1:40, and the simulation experiment of an advanced hydraulic support coupling active support under anchor protection was carried out. The maximum error percentage of the theoretical calculation and experimental results of roof deformation under different initial bearing capacities is 19.51%, and the maximum error percentage of stress is 13.77%. The accuracy of the distribution law of roof stress and displacement under the initial bearing capacity in the process of active support obtained by theoretical calculation is verified. The research results provide a theoretical basis for advanced coupling adaptive support and the control of fully mechanized mining faces.

Colorectal cancer (CRC) is the third most common cancer in the world. Other than adenocarcinomas, exceptional tumors of the colon and rectum represent a neglected clinical issue due to their rarity. Signet ring cell carcinoma (SRCC) is a rare subtype of CRC and has an extremely poor prognosis due to its advanced stage at diagnosis. Here we report a rare case of colorectal SRCC manifested as recurrent intestinal obstruction with a negative colonoscopy. Finally, he was diagnosed with signet ring cell carcinoma of the colon by postoperative pathology. It emphasized the special feature of intramural tumor growth without penetrating the mucosa in SRCC, which requires timely surgical intervention to avoid delay in diagnosis and treatment.

Summary: Distinct locations of different white adipose depots suggest anatomy-specific developmental regulation, a relatively understudied concept. Here, we report a population of Tcf21 lineage cells (Tcf21 LCs) present exclusively in visceral adipose tissue (VAT) that dynamically contributes to VAT development and expansion. During development, the Tcf21 lineage gives rise to adipocytes. In adult mice, Tcf21 LCs transform into a fibrotic or quiescent state. Multiomics analyses show consistent gene expression and chromatin accessibility changes in Tcf21 LC, based on which we constructed a gene-regulatory network governing Tcf21 LC activities. Furthermore, single-cell RNA sequencing (scRNA-seq) identifies the heterogeneity of Tcf21 LCs. Loss of Tcf21 promotes the adipogenesis and developmental progress of Tcf21 LCs, leading to improved metabolic health in the context of diet-induced obesity. Mechanistic studies show that the inhibitory effect of Tcf21 on adipogenesis is at least partially mediated via Dlk1 expression accentuation.

As a crucial computer vision task, multi-objective semantic segmentation has attracted widespread attention and research in the field of remote sensing image analysis. This technology has important application value in fields such as land resource surveys, global change monitoring, urban planning, and environmental monitoring. However, multi-target semantic segmentation of remote sensing images faces challenges such as complex surface features, complex spectral features, and a wide spatial range, resulting in differences in spatial and spectral dimensions among target features. To fully exploit and utilize spectral feature information, focusing on the information contained in spatial and spectral dimensions of multi-spectral images, and integrating external information, this paper constructs the CD-MQANet network structure, where C represents the Channel Creator module and D represents the Dual-Path Encoder. The Channel Creator module (CCM) mainly includes two parts: a generator block and a spectral attention module. The generator block aims to generate spectral channels that can expand different ground target types, while the spectral attention module can enhance useful spectral information. Dual-Path Encoders include channel encoders and spatial encoders, intended to fully utilize spectrally enhanced images while maintaining the spatial information of the original feature map. The decoder of CD-MQANet is a multitasking decoder composed of four types of attention, enhancing decoding capabilities. The loss function used in the CD-MQANet consists of three parts, which are generated by the intermediate results of the CCM, the intermediate results of the decoder, and the final segmentation results and label calculation. We performed experiments on the Potsdam dataset and the Vaihingen dataset. Compared to the baseline MQANet model, the CD-MQANet network improved mean F1 and OA by 2.03% and 2.49%, respectively, on the Potsdam dataset, and improved mean F1 and OA by 1.42% and 1.25%, respectively, on the Vaihingen dataset. The effectiveness of CD-MQANet was also proven by comparative experiments with other studies. We also conducted a thermographic analysis of the attention mechanism used in CD-MQANet and analyzed the intermediate results generated by CCM and LAM. Both modules generated intermediate results that had a significant positive impact on segmentation.

Abstract This brief focuses on the local Mittag–Leffler stabilisation of fractional‐order neural networks via quantised control with input saturation. First, a refined sector condition is put forward, which can deal with the problem of the simultaneous existence of quantiser effect and actuator constraint. With the aid of refined sector condition, theoretical analysis on the local Mittag–Leffler stabilisation of the resulting closed‐loop systems is carried out by using some inequality techniques on Mittag–Leffler function and fractional‐order Lyapunov theory. In addition, two convex optimisation schemes are respectively developed to minimise the cost of actuators and to enlarge the admissible initial region. Finally, a three‐neurons fractional‐order neural networks is applied to illustrate the effectiveness of the derived results.

Abstract Background Diabetic peripheral neuropathy (DPN) is the most common chronic neurological complication. It is the main cause of disability in diabetes mellitus (DM) patients and seriously affects the quality of life of patients. Pharmacological treatments always associate with limited efficacy and adverse effects. Moxibustion has been recommended to treat DPN as an adjuvant therapy to conventional medical treatment to accelerate alleviation of the symptoms of DPN. 10.6-μm laser moxibustion (LM), whose wavelength is close to the peak of infrared radiation spectrum of the traditional moxibustion as well as human acupoints, produces the thermal effect similar with moxibustion but with no smoke or smell. The purpose of this sham controlled clinical trial is to determine the effect and safety of 10.6-μm LM as adjuvant therapy in patients with DPN. Methods This is a protocol for a randomized, double-blind, sham-controlled trial. One hundred fourteen patients meeting the inclusion and exclusion criteria will be recruited and randomly assigned to the LM group or the sham LM group with a 1:1 allocation ratio. Patients in both groups will receive a basic integrated treatment of Chinese and Western medicine and a total of 12 sessions of true or sham LM treatments over 4 weeks with 3 sessions a week. The primary outcome is nerve conduction velocity (NCV), and the secondary outcomes include Michigan Neuropathy Screening Instrument (MNSI) scores, Diabetes-Specific Quality of Life (DSQL) scores, blood rheology parameters, and assessments of safety and blinding. Outcome measures will be collected at baseline, 2 weeks after treatment, the end of LM treatments (4 weeks), and 4, 8 weeks after the end of LM treatment (8, 12weeks). Discussion This study will be conducted to compare the efficacy of LM versus sham LM combined with medical treatment. 10.6-μm LM may alleviate symptoms, improve quality of life, and reduce the dosage of drugs as well as avoid causing serious side effects. Trial registration Chinese Clinical Trial Registry ChiCTR2000029329 . Registered on 25 January 2020.

The etiology of severe acute hepatitis (SAH) in children is various. We describe the first Chinese case of severe acute hepatitis in a 22-month-old boy with the mild illness of Omicron sub-variant BA.2.38. With the application of Compound Glycyrrhizin Injection (CGI), the patient gradually recovered from acute liver injury (ALI). This case highlights the possibility of severe ALI in children with the non-critical illness of SARS-CoV-2. The management of SAH associated with the pandemic presents challenges for clinicians, and follow-up is in need. The method of differential diagnosis using limited laboratory results is of great value to the clinicians.

Background: Recent studies have reported that the incidence of sensitive skin is increasing. Skin sensitivity and skin barrier functions were related to many skin diseases including atopic dermatitis, psoriasis, rosacea, and so on. Mesenchymal stem cell (MSC)-derived exosomes (hMSC) might be considered as a new effective therapeutic scheme.Aims: This study aims to investigate the safety and efficacy of hMSC exosomes as a novel topical treatment for sensitive skin.Patients/Methods: Exosomes were extracted from primary hMSC via ultracentrifugation method. The morphology of hMSC exosomes was studied via transmission electron microscope. Expression of exosome specific surface marker was detected via Western blot. 22 subjects (female, aged 18–55) diagnosed with sensitive skin were enrolled. Follow-up was conducted before, 7-day, 14-day, and 28-day after hMSC exosomes use. Transepidermal water loss (TEWL), surface hydration, sebum secretion, and L*a*b* value were simultaneously tested at the same time point in an environment-controlled room.Results: Under transmission electron microscopy, the extracted hMSC exosomes were circular or elliptical with intact membrane structure, and their diameters ranged mainly from 40 to 80 nm. Western blot showed that the expression of markers CD63, CD9, and Tsg101 was positive. Brownian motion based nanoparticle trajectory analysis (NTA) showed that the main peak of particle size distribution occurred around 96 nm, the average particle size was 122 nm, and the main peak accounted for 96.7%. All this conformed to the biological characteristics of exosomes standardized by the International Society for Extracellular Vesicles. In the clinical trial, scores of objective symptoms including roughness, scales, erythema, and subjective symptoms including tension, burning, or itching, were improved after 7-, 14-, and 28- day using hMSC-exosomes. TEWL, hydration, sebum, pH, and a* values were tended to return to the level of healthy skin.Conclusion: The hMSC-exosomes, with the advantages of biocompatibility and biodegradability, could improve clinical symptoms and eruptions in sensitive skin patients, and might be as an MSC cell-free novel therapy in sensitive skin-related disease treatment.

Limonium bicolor is a dicotyledonous recretohalophyte with several multicellular salt glands on the leaves. The plant can directly secrete excess salt onto the leaf surface through the salt glands to maintain ion homeostasis under salt stress. Therefore, it is of great significance to study the functions of genes related to salt gland development and salt tolerance. In this study, an R1-type MYB transcription factor gene was screened from L. bicolor, named LbMYB48, and its expression was strongly induced by salt stress. Subcellular localization analysis showed that LbMYB48 was localized in the nucleus. LbMYB48 protein has transcriptional activation activity shown by transcriptional activation experiments. The density of salt glands in the leaves and the salt secretion capacity of LbMYB48-silenced lines were decremented, as demonstrated by the leaf disc method to detect sodium ion secretion. Furthermore, salt stress index experiments revealed that the ability of LbMYB48-silenced lines to resist salt stress was significantly reduced. LbMYB48 regulates salt gland development and salt tolerance in L. bicolor mainly by regulating the expression of epidermal cell development related genes such as LbCPC-like and LbDIS3 and salt stress-related genes (LbSOSs, LbRLKs, and LbGSTs) as demonstrated by RNA-seq analysis of LbMYB48-silenced lines. The heterologous over-expression of LbMYB48 in Arabidopsis thaliana improves salt tolerance of plants by stabilizing ion and osmotic balance and is likely to be involved in the abscisic acid signaling pathway. Therefore, LbMYB48, a transcriptional activator regulates the salt gland development of L. bicolor and salt tolerance of L. bicolor and A. thaliana.

BackgroundPlasma neurofilament light chain (pNFL) represents one of the scaffolding proteins of central nervous system axonal injury. The aim of this study was to evaluate pNFL as a predictive biomarker for early neurological deterioration (END) in medically managed patients with large vessel occlusion (LVO) and mild presentation (NIHSS < 6).MethodsThis retrospective study was developed from a prospectively collected stroke database, which was conducted at a large academic comprehensive stroke center in western China. Patients who first presented with acute ischemic stroke (AIS) within 24 h of symptom onset were continuously included. Stroke severity was analyzed at admission using the NIHSS score. The pNFL drawn on admission was analyzed with a novel ultrasensitive single-molecule array.ResultsThirty-nine consecutive patients were included in the analysis, and 19 (48.72%) patients experienced END. Patients who experienced END had significantly higher pNFL levels (mean, 65.20 vs. 48.28 pg/mL; P < 0.001) and larger infarct volume (mean, 15.46 vs. 9.56 mL; P < 0.001). pNFL was valuable for the prediction of END (OR, 1.170; 95% CI, 1.049–1.306; P = 0.005), even after adjusted for age and sex (OR, 1.178; 95% CI, 1.038–1.323; P = 0.006), blood sampling time, baseline NIHSS, TOAST classification, and infarct volume (OR, 1.168; 95% CI, 1.034–1.320; P = 0.012). The area under the ROC curve was 85.0% (95% CI, 0.731–0.970; P < 0.001). The sensitivity was 73.7%, and the specificity was 80%.ConclusionEND in minor stroke with LVO was distinguishable from those without END following the determination of pNFL in the blood samples within 24 h of onset. The pNFL is a promising biomarker of END in minor stroke with LVO.Clinical trial registrationChiCTR1800020330.

Homeodomain leucine zipper (HD-ZIP) proteins are plant-specific transcription factors that contain a homeodomain (HD) and a leucine zipper (LZ) domain. The highly conserved HD binds specifically to DNA and the LZ mediates homodimer or heterodimer formation. HD-ZIP transcription factors control plant growth, development, and responses to abiotic stress by regulating downstream target genes and hormone regulatory pathways. HD-ZIP proteins are divided into four subclasses (I–IV) according to their sequence conservation and function. The genome-wide identification and expression profile analysis of HD-ZIP proteins in model plants such as Arabidopsis (Arabidopsis thaliana) and rice (Oryza sativa) have improved our understanding of the functions of the different subclasses. In this review, we mainly summarize and discuss the roles of HD-ZIP proteins in plant response to abiotic stresses such as drought, salinity, low temperature, and harmful metals. HD-ZIP proteins mainly mediate plant stress tolerance by regulating the expression of downstream stress-related genes through abscisic acid (ABA) mediated signaling pathways, and also by regulating plant growth and development. This review provides a basis for understanding the roles of HD-ZIP proteins and potential targets for breeding abiotic stress tolerance in plants.

Previous studies have documented cotton boll weight reductions under drought, but the relative importance of the subtending leaf, bracts and capsule wall in driving drought-induced reductions in boll mass has received limited attention. To investigate the role of carbon metabolism in driving organ-specific differences in contribution to boll weight formation, under drought conditions. Controlled experiments were carried out under soil relative water content (SRWC) (75 ± 5)% (well-watered conditions, control), (60 ± 5)% (moderate drought) and (45 ± 5)% (severe drought) in 2018 and 2019 with two cultivars Yuzaomian 9110 and Dexiamian 1. Under severe drought, the decreases of photosynthetic rate (Pn) and carbon isotope composition (δ13C) were observed in the subtending leaf, bract and capsule wall, suggesting that carbon assimilation of three organs was restricted and the limitation was most pronounced in the subtending leaf. Changes in the activities of sucrose phosphate synthase (SPS), sucrose synthase (SuSy), invertases as well as the reduction in expression of sucrose transporter (GhSUT1) led to variabilities in the sucrose content of three organs. Moreover, photosynthate distribution from subtending leaf to seeds plus fibers (the components of boll weight) was significantly restricted and the photosynthetic contribution rate of subtending leaf to boll weight was decreased, while contributions of bracts and capsule wall were increased by drought. This, in conjunction with the observed decreases in boll weight, indicated that the subtending leaf was the most sensitive photosynthetic organ to drought and was a dominant driver of boll weight loss under drought. Therefore, the subtending leaf governs boll weight loss under drought due to limitations in carbon assimilation, perturbations in sucrose metabolism and inhibition of sucrose transport.

This paper is concerned with electric–acoustic/acoustic–electric conversions of thin-wafer piezoelectric transducers polarized in the thickness direction. By introducing two mechanical components with frequency-dependent values, i.e., radiation resistance and radiation mass, into the equivalent circuit of the thin-wafer piezoelectric transducer, we established a frequency-dependent dynamic mechanic-electric equivalent network with four terminals for an arbitrary given frequency, an enhancement from the conventional circuit networks. We derived the analytic expressions of its electric–acoustic and acoustic–electric conversion impulse responses using the four-terminal equivalent circuit to replace the traditional six-terminal equivalent circuit for a thin-wafer transducer with harmonic vibrational motion. For multifrequency electrical/acoustic signals acting on the transducer, we established parallel electric–acoustic/acoustic–electric conversion transmission networks. These two transmission network models have simple structures and clear physical and mathematical descriptions of thin-wafer transducers for electric–acoustic/acoustic–electric conversion when excited by a multifrequency electric/acoustic signal wavelet. The calculated results showed that the transducer’s center frequency shift relates to its mechanical load and vibration state. The method reported in this paper can be applied to conventional-sized and small-sized piezoelectric transducers with universal applicability.

Droughts are natural disasters that have significant implications for agricultural production and human livelihood. Under climate change, the drought process is accelerating, such as the intensification of flash droughts. The efficient and quick monitoring of droughts has increasingly become a crucial measure in responding to extreme drought events. We utilized multi-imagery data from the geostationary meteorological satellite FY-4A within one day; implemented the daily Maximum Value Composite (MVC) method to minimize interference from the clouds, atmosphere, and anomalies; and developed a method for calculating the daily-scale Temperature Vegetation Drought Index (TVDI), which is a dryness index. Three representative drought events (Yunnan Province, Guangdong Province, and the Huanghuai region) from 2021 to 2022 were selected for validation, respectively. We evaluated the spatial and temporal effects of the TVDI with the Soil Relative Humidity Index (SRHI) and the Meteorological Drought Composite Index (MCI). The results show that the TVDI has stronger negative correlations with the MCI and SRHI in moderate and severe drought events. Meanwhile, the TVDI and SRHI exhibited similar trends. The trends of drought areas identified by the TVDI, SRHI, and MCI were consistent, while the drought area identified by the TVDI was slightly higher than the SRHI. Yunnan Province has the most concentrated distribution, which is mostly between 16.93 and 25.22%. The spatial distribution of the TVDI by FY-4A and MODIS is generally consistent, and the differences in severe drought areas may be attributed to disparities in the NDVI. Furthermore, the TVDI based on FY-4A provides a higher number of valid pixels (437 more pixels in the Huanghuai region) than that based on MODIS, yielding better overall drought detection. The spatial distribution of the TVDI between FY-4A and Landsat-8 is also consistent. FY-4A has the advantage of acquiring a complete image on a daily basis, and lower computational cost in regional drought monitoring. The results indicate the effectiveness of the FY-4A TVDI in achieving daily-scale drought monitoring, with a larger number of valid pixels and better spatial consistency with station indices. This study provides a new solution for drought monitoring using a geostationary meteorological satellite from different spatial–temporal perspectives to facilitate comprehensive drought monitoring.

With their unique geographical characteristics, semi-closed narrow bays are important places for human survival but vulnerable to pollution. Because pollutants (polycyclic aromatic hydrocarbons, PAHs) migrate and undergo transformation through a dynamic mechanism in bays of this type, environmental authorities have formulated a series of effective measures for pollution prevention and control, but these are difficult to realize. Based on monitoring and historical data, a multiphase-coupled hydrodynamic model combined with a carcinogenic risk-assessment model was able to solve the challenging environmental problem. Results showed that the hydrodynamic condition in the semi-closed narrow bay was very complex. A weaker hydrodynamic force had an adverse influence on the diffusion of pollutants, further amplified in part by the head of the semi-closed narrow bay, resulting in a higher ecological risk. The prediction results indicated that the total amount of PAHs transported from seawater to sediments was about 4.7 × 1013 ng/year, which might cause serious threats to aquaculture or human health.

Host plants influence rhizosphere microorganism composition through root secretions, and rhizosphere associated microorganisms influence Cistanche seeds germination. At present, little is known about effects of different host plants on soil bacteria and fungi in the rhizosphere of Cistanche salsa. High-throughput sequencing was used here to reveal the similarities and differences in the structural composition of the soil microbial community of C. salsa from six host plants (i.e., Halocnemum strobilaceum, Atriplex patens, Kalidium foliatum, Caroxylon passerinum, Anabasis aphylla, Krascheninnikovia ceratoides). We discovered that Krascheninnikovia ceratoides-parasitizing C. salsa (YRCR6) had the highest diversity of rhizosphere bacterial communities, and Anabasis aphylla -parasitizing C. salsa (YRCR5) had the highest diversity of rhizosphere fungal communities. Fungal communities were more influenced by the host plant than bacterial communities. In addition, we discovered certain rhizosphere microorganisms that may be associated with Cistanche seeds germination, including Mortierella, Aspergillus alliaceus, and Cladosporium, which are account for a relatively high proportion in Halocnemum strobilaceum, Atriplex patens and Anabasis aphylla -parasitizing C. salsa. Redundancy analysis results also revealed that AP, HCO3–, pH, Ca2+, SO42–, and K+ had a highly significant impact on the bacterial community structure (P < 0.01), while pH and SO42– had a significant impact on the fungal community structure (P < 0.05). Conclusively, differences were noted in the structure of rhizosphere bacterial and fungal communities of C. salsa parasitizing different plants in the same habit and the difference may be related to the host plant. This result can provide a new ideas for the selection of host plants and the cultivation of C. salsa.

ObjectiveThis study aimed to investigate the association of altered cortical thickness and functional connectivity (FC) with depression in Parkinson’s disease (PD).Materials and methodsA total of 26 non-depressed PD patients (PD-ND), 30 PD patients with minor depression (PD-MnD), 32 PD patients with major depression (PD-MDD), and 30 healthy controls (HC) were enrolled. Differences in cortical thickness among the four groups were assessed, and the results were used to analyze FC differences in regions of cortical atrophy. Binary logistic regression and receiver operating characteristic (ROC) curve analyses were also performed to identify clinical features and neuroimaging biomarkers that might help in the prediction of PD-MDD.ResultsPatients with PD-MDD showed decreased cortical thickness compared to patients with PD-ND in the left superior temporal and right rostral middle frontal gyri (RMFG), as well as weak FC between the left superior temporal gyrus and right cerebellum posterior lobe and between right RMFG and right inferior frontal gyrus and insula. The combination of cortical thickness, FC, and basic clinical features showed strong potential for predicting PD-MDD based on the area under the ROC curve (0.927, 95% CI 0.854–0.999, p < 0.001).ConclusionPatients with PD-MDD show extensive cortical atrophy and FC alterations, suggesting that cortical thickness and FC may be neuroimaging-based diagnostic biomarkers for PD-MDD.

Plant trichomes, protrusions formed from specialized aboveground epidermal cells, provide protection against various biotic and abiotic stresses. Trichomes can be unicellular, bicellular or multicellular, with multiple branches or no branches at all. Unicellular trichomes are generally not secretory, whereas multicellular trichomes include both secretory and non-secretory hairs. The secretory trichomes release secondary metabolites such as artemisinin, which is valuable as an antimalarial agent. Cotton trichomes, also known as cotton fibers, are an important natural product for the textile industry. In recent years, much progress has been made in unraveling the molecular mechanisms of trichome formation in Arabidopsis thaliana, Gossypium hirsutum, Oryza sativa, Cucumis sativus, Solanum lycopersicum, Nicotiana tabacum, and Artemisia annua. Here, we review current knowledge of the molecular mechanisms underlying fate determination and initiation, elongation, and maturation of unicellular, bicellular and multicellular trichomes in several representative plants. We emphasize the regulatory roles of plant hormones, transcription factors, the cell cycle and epigenetic modifications in different stages of trichome development. Finally, we identify the obstacles and key points for future research on plant trichome development, and speculated the development relationship between the salt glands of halophytes and the trichomes of non-halophytes, which provides a reference for future studying the development of plant epidermal cells.

Abstract Background Diabetic peripheral neuropathy (DPN) is one of the most common chronic complications of diabetes mellitus. The main symptoms of DPN include numbness or pain in both extremities and paresthesia (such as formication or burning sensations), which greatly affect patients’ quality of life. Pharmacological treatments for DPN are associated with both uncertain therapeutic effects and adverse effects, as well as with high costs. Some clinical studies have reported that low-level laser therapy (LLLT) relieves clinical symptoms and improves nerve function in patients with DPN. We intend to conduct a systematic review and meta-analysis to further evaluate the effectiveness and safety of LLLT for DPN. Methods The following electronic databases will be searched to retrieve literature from their inception until December 2020: MEDLINE (PubMed), Embase, Cochrane Central Register of Controlled Trials, Web of Science (the Science and Social Science Citation Index), CNKI, VIP, WanFang, and SinoMed. Simultaneously, clinical registration tests and gray literature will also be retrieved. Randomized controlled trials (RCTs) comparing LLLT with either sham LLLT, no (specific) treatment, or active conventional medical treatments will be included. The primary outcomes will be nerve conduction velocity as well as clinical scores that assess neurological function and related symptoms. The risk of bias of each study and quality of evidence will be assessed using the updated Cochrane Risk of Bias 2.0 tool and GRADE approach, respectively. A meta-analysis will then be conducted using Review Manager software version 5.3. Discussion This study will integrate RCTs and analyze data to provide a detailed summary of the evidence relating to the effects and safety of LLLT in patients with DPN. LLLT will be compared with sham LLLT, no (specific) treatment, or active conventional medical treatments, especially in terms of neurological function, quality of life, and adverse events. In conclusion, this systematic review will generate evidence regarding the use of LLLT to treat DPN, in terms of both its efficacy and safety. Systematic review registration This protocol was registered with the International Prospective Register of Systematic Reviews on April 2020 (registration number: CRD42020170625 ).

With the development of deep learning and remote sensing technologies in recent years, many semantic segmentation methods based on convolutional neural networks (CNNs) have been applied to road extraction. However, previous deep learning-based road extraction methods primarily used RGB imagery as an input and did not take advantage of the spectral information contained in hyperspectral imagery. These methods can produce discontinuous outputs caused by objects with similar spectral signatures to roads. In addition, the images obtained from different Earth remote sensing sensors may have different spatial resolutions, enhancing the difficulty of the joint analysis. This work proposes the Multiscale Fusion Attention Network (MSFANet) to overcome these problems. Compared to traditional road extraction frameworks, the proposed MSFANet fuses information from different spectra at multiple scales. In MSFANet, multispectral remote sensing data is used as an additional input to the network, in addition to RGB remote sensing data, to obtain richer spectral information. The Cross-source Feature Fusion Module (CFFM) is used to calibrate and fuse spectral features at different scales, reducing the impact of noise and redundant features from different inputs. The Multiscale Semantic Aggregation Decoder (MSAD) fuses multiscale features and global context information from the upsampling process layer by layer, reducing information loss during the multiscale feature fusion. The proposed MSFANet network was applied to the SpaceNet dataset and self-annotated images from Chongzhou, a representative city in China. Our MSFANet performs better over the baseline HRNet by a large margin of +6.38 IoU and +5.11 F1-score on the SpaceNet dataset, +3.61 IoU and +2.32 F1-score on the self-annotated dataset (Chongzhou dataset). Moreover, the effectiveness of MSFANet was also proven by comparative experiments with other studies.

Abstract Background Saussurea involucrata survives in extreme arctic conditions and is very cold-resistant. This species grows in rocky, mountainous areas with elevations of 2400–4100 m, which are snow-covered year-round and are subject to freezing temperatures. S. involucrata’s ability to survive in an extreme low-temperature environment suggests that it has particularly high photosynthetic efficiency, providing a magnificent model, and rich gene pool, for the analysis of plant cold stress response. Fructose-1, 6-bisphosphate aldolase (FBA) is a key enzyme in the photosynthesis process and also mediates the conversion of fructose 1, 6-bisphosphate (FBP) into dihydroxyacetone phosphate (DHAP) and glycerol triphosphate (GAP) during glycolysis and gluconeogenesis. The molecular mechanisms underlying S. involucrata’s cold tolerance are still unclear; therefore, our work aims to investigate the role of FBA in plant cold-stress response. Results In this study, we identified a cold-responsive gene, SiFBA5, based on a preliminary low-temperature, genome-wide transcriptional profiling of S. involucrata. Expression analysis indicated that cold temperatures rapidly induced transcriptional expression of SiFBA5, suggesting that SiFBA5 participates in the initial stress response. Subcellular localization analysis revealed that SiFBA5 is localized to the chloroplast. Transgenic tomato plants that overexpressed SiFBA5 were generated using a CaMV 35S promoter. Phenotypic observation suggested that the transgenic plants displayed increased cold tolerance and photosynthetic efficiency in comparison with wild-type plants. Conclusion Cold stress has a detrimental impact on crop yield. Our results demonstrated that SiFBA5 positively regulates plant response to cold stress, which is of great significance for increasing crop yield under cold stress conditions.

Soil moisture (SM) is a key parameter of the hydrological process, which affects exchanges of water and heat at the land/atmosphere interface. The “trapezoid” (or “triangle”) method has been widely applied to SM monitoring based on the pixel distribution within the thermal and optical remote sensing observations. However, the trapezoid method is a linear empirical model highly related to the retrieval accuracy of the surface temperature. In the article, the moderate-resolution imaging spectroradiometer (MODIS) data were applied to retrieve SM through an improved method over the Tibetan Plateau. The improved method is integrated with the “trapezoid” model and multiple learning techniques, Random Forest (RF) and Extreme Gradient Boosting (XGBoost). Meanwhile, RF and XGBoost were both trained with SM target data (the scale of SM and soil temperature) derived from the Tibetan Plateau observations, and the input variables were derived from MODIS observations. Compared with the SM measured, the results showed the root mean square error, the mean absolute error, and the correlation coefficient of the ensemble retrievals were 0.046-0.081 m3m-3, 0.030-0.065 m3m-3, and 0.60-0.87, respectively, which is better than that of the separate model. The ideas to implement the combination of traditional inversion algorithms and machine learning methods are helpful for researches in remote sensing fields.

RING zinc finger proteins have a conserved RING domain, mainly function as E3 ubiquitin ligases, and play important roles in plant growth, development, and the responses to abiotic stresses such as drought, salt, temperature, reactive oxygen species, and harmful metals. RING zinc finger proteins act in abiotic stress responses mainly by modifying and degrading stress-related proteins. Here, we review the latest progress in research on RING zinc finger proteins, including their structural characteristics, classification, subcellular localization, and physiological functions, with an emphasis on abiotic stress tolerance. Under abiotic stress, RING zinc finger proteins on the plasma membrane may function as sensors or abscisic acid (ABA) receptors in abiotic stress signaling. Some RING zinc finger proteins accumulate in the nucleus may act like transcription factors to regulate the expression of downstream abiotic stress marker genes through direct or indirect ways. Most RING zinc finger proteins usually accumulate in the cytoplasm or nucleus and act as E3 ubiquitin ligases in the abiotic stress response through ABA, mitogen-activated protein kinase (MAPK), and ethylene signaling pathways. We also highlight areas where further research on RING zinc finger proteins in plants is needed.