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Objective To study the efficacy and safety of secukinumab in the treatment of moderate and severe plaque psoriasis in children. Methods A total of 10 children with psoriasis were enrolled at Yongcheng Central Hospital from November 2021 to November 2022. All patients were treated with subcutaneous injection of secukinumab and followed up for 52 weeks. The psoriasis area and severity index (PASI) and childrens' dermatology life quality index(CDLQI) were evaluated, and adverse reactions were observed. Results After 4 weeks of the treatment, 8 patients achieved PASI 75, among which 7 patients achieved PASI 90 and PASI 100 was observed in 5 patients. After 8 weeks of the treatment, all 10 patients reached PASI 75, including 8 patients with PASI 100. After 12 weeks, all 10 patients achieved PASI 100. By 52 weeks, 9 patients reached PASI 75, including 8 patients with PASI 90 and 7 patients with PASI 100. After 4 weeks of the treatment, CDLQI scores were significantly decreased and declined to 0 by 52 weeks. No adverse reactions were observed in all patients. Conclusions Secukinumab can rapidly improve moderate to severe plaque psoriasis in children and exhibits long-lasting benefit. It is safe and can quickly improve the quality of life of the children.

The timely repair of high-density polyethylene (HDPE) membrane leakage in landfills is an important means of environmental risk control, which is critical for preventing leachate from polluting groundwater and soil. Electric repair technology is expected to become a hot spot in the leakage repair of HDPE films, because it can solve the issues of complex operation, high costs, and security risks during the operation and closure of landfills. To explore the influence law of various technical factors on the electric repair process, we carried out single factor experiments on the main influencing factors such as the operation time, bentonite concentration and dispersant/bentonite dosage ratio, leakage size, and calcium concentration. We then explored the best technological conditions. The results showed that accumulation at the leakage site possessed a good repair effect with a permeability coefficient of 4.22 × 10−6 cm/s. Furthermore, we observed that the Zeta potential played an important role in the electric repair technology, where the higher the absolute value of the Zeta potential, the faster the electrophoretic migration rate of the bentonite particles, and the lower the permeability coefficient of accumulation. This study may serve as a theoretical basis and offer scientific guidance for the directional electric repair of HDPE membrane leakage during the operating period and after the closure of landfills.

Abstract The aim of this study was to develop a medical imaging and comprehensive stacked learning-based method for predicting high- and low-risk thymoma. A total of 126 patients with thymomas and 5 patients with thymic carcinoma treated at our institution, including 65 low-risk patients and 66 high-risk patients, were retrospectively recruited. Among them, 78 patients composed the training cohort, while the remaining 53 patients formed the validation cohort. We extracted 1702 features each from the patients’ arterial-, venous-, and plain-phase images. Pairwise subtraction of these features yielded 1702 arterial-venous, arterial-plain, and venous-plain difference features each. The Mann‒Whitney U test and least absolute shrinkage and selection operator (LASSO) and SelectKBest methods were employed to select the best features from the training set. Six models were built with a stacked learning algorithm. By applying stacked ensemble learning, three machine learning algorithms (XGBoost, multilayer perceptron (MLP), and random forest) were combined by XGBoost to produce the the six basic imaging models. Then, the XGBoost algorithm was applied to the six basic imaging models to construct a combined radiomic model. Finally, the radiomic model was combined with clinical information to create a nomogram that could easily be used in clinical practice to predict the thymoma risk category. The areas under the curve (AUCs) of the combined radiomic model in the training and validation cohorts were 0.999 (95% CI 0.988–1.000) and 0.967 (95% CI 0.916–1.000), respectively, while those of the nomogram were 0.999 (95% CI 0.996–1.000) and 0.983 (95% CI 0.990–1.000). This study describes the application of CT-based radiomics in thymoma patients and proposes a nomogram for predicting the risk category for this disease, which could be advantageous for clinical decision-making for affected patients.

Abstract Background The progression of non-small cell lung cancer (NSCLC) is significantly influenced by circular RNAs (circRNAs), especially in tumor hypoxia microenvironment. However, the precise functions and underlying mechanisms of dysregulated circRNAs in NSCLC remain largely unexplored. Methods Differentially expressed circRNAs in NSCLC tissues were identified through high-throughput RNA sequencing. The characteristics of circ_0007386 were rigorously confirmed via Sanger sequencing, RNase R treatment and actinomycin D treatment. The effects of circ_0007386 on proliferation and apoptosis were investigated using CCK8, cloning formation assays, TUNEL staining, and flow cytometry assays in vitro. In vivo, xenograft tumor models were used to evaluate its impact on proliferation. Mechanistically, the regulatory relationships of circ_0007386, miR-383-5p and CIRBP were examined through dual luciferase reporter assays and rescue experiments. Additionally, we detected the binding of EIF4A3 to CRIM1 pre-mRNA by RNA immunoprecipitation and the interaction between YAP1 and EIF4A3 under hypoxic conditions by co-immunoprecipitation. Results Our investigation revealed a novel circRNA, designated as circ_0007386, that was upregulated in NSCLC tissues and cell lines. Circ_0007386 modulated proliferation and apoptosis in NSCLC both in vitro and in vivo. Functionally, circ_0007386 acted as a sponge for miR-383-5p, targeting CIRBP, which influenced NSCLC cell proliferation and apoptosis via the PI3K/AKT signaling pathway. Furthermore, under hypoxic conditions, the interaction between YAP1 and EIF4A3 was enhanced, leading to the displacement of EIF4A4 from binding to CRIM1 pre-mRNA. This facilitated the back-splicing of CRIM1 pre-mRNA, increasing the formation of circ_0007386. The circ_0007386/miR-383-5p/CIRBP axis was significantly associated with the clinical features and prognosis of NSCLC patients. Conclusions Circ_0007386, regulated by YAP1-EIF4A3 interaction under hypoxia conditions, plays an oncogenic role in NSCLC progression via the miR-383-5p/CIRBP axis.

The micaceous weathered granitic soil (WGS) is frequently encountered in civil engineering worldwide, unfortunately little information is available regarding how mica affects the physico-mechanical behaviors of WGS. This study prepares reconstituted WGS with different mica contents by removing natural mica in the WGS, and then mixes it with commercial mica powders. The geotechnical behavior as well as the microstructures of the mixtures are characterized. The addition of mica enables the physical indices of WGS to be specific combinations of coarser gradation and high permeability but high Atterberg limits. However, high mica content in WGS was found to be associated with undesirable mechanical properties, including increased compressibility, disintegration, and swelling potential, as well as poor compactability and low effective frictional angle. Microstructural analysis indicates that the influence of mica on the responses of mixtures originates from the intrinsic nature of mica as well as the particle packing being formed within WGS. Mica exists in the mixture as stacks of plates that form a spongy structure with high compressibility and swelling potential. Pores among the plates give the soil high water retention and high Atterberg limits. Large pores are also generated by soil particles with bridging packing, which enhances the permeability and water-soil interactions upon immersion. This study provides a micro-level understanding of how mica dominates the behavior of WGS and provides new insights into the effective stabilization and improvement of micaceous soils.

Background: Ovarian cancer (OV) is regarded as one of the most lethal malignancies affecting the female reproductive system, with individuals diagnosed with OV often facing a dismal prognosis due to resistance to chemotherapy and the presence of an immunosuppressive environment. T cells serve as a crucial mediator for immune surveillance and cancer elimination. This study aims to analyze the mechanism of T cell-associated markers in OV and create a prognostic model for clinical use in enhancing outcomes for OV patients. Methods: Based on the single-cell dataset GSE184880, this study used single-cell data analysis to identify characteristic T cell subsets. Analysis of high dimensional weighted gene co-expression network analysis (hdWGCNA) is utilized to identify crucial gene modules along with their corresponding hub genes. A grand total of 113 predictive models were formed utilizing ten distinct machine learning algorithms along with the combination of the cancer genome atlas (TCGA)-OV dataset and the GSE140082 dataset. The most dependable clinical prognostic model was created utilizing the leave one out cross validation (LOOCV) framework. The validation process for the models was achieved by conducting survival curve analysis and receiver operating characteristic (ROC) analysis. The relationship between risk scores and immune cells was explored through the utilization of the Cibersort algorithm. Additionally, an analysis of drug sensitivity was carried out to anticipate chemotherapy responses across various risk groups. The genes implicated in the model were authenticated utilizing qRT-PCR, cell viability experiments, and EdU assay. Results: This study developed a clinical prognostic model that includes ten risk genes. The results obtained from the training set of the study indicate that patients classified in the low-risk group experience a significant survival advantage compared to those in the high-risk group. The ROC analysis demonstrates that the model holds significant clinical utility. These results were verified using an independent dataset, strengthening the model's precision and dependability. The risk assessment provided by the model also serves as an independent prognostic factor for OV patients. The study also unveiled a noteworthy relationship between the risk scores calculated by the model and various immune cells, suggesting that the model may potentially serve as a valuable tool in forecasting responses to both immune therapy and chemotherapy in ovarian cancer patients. Notably, experimental evidence suggests that PFN1, one of the genes included in the model, is upregulated in human OV cell lines and has the capacity to promote cancer progression in in vitro models. Conclusion: We have created an accurate and dependable clinical prognostic model for OV capable of predicting clinical outcomes and categorizing patients. This model effectively forecasts responses to both immune therapy and chemotherapy. By regulating the immune microenvironment and targeting the key gene PFN1, it may improve the prognosis for high-risk patients.

Abstract The gut microbiota plays a critical role in the progression of human diseases, especially cancer. In recent decades, there has been accumulating evidence of the connections between the gut microbiota and cancer immunotherapy. Therefore, understanding the functional role of the gut microbiota in regulating immune responses to cancer immunotherapy is crucial for developing precision medicine. In this review, we extract insights from state-of-the-art research to decipher the complicated crosstalk among the gut microbiota, the systemic immune system, and immunotherapy in the context of cancer. Additionally, as the gut microbiota can account for immune-related adverse events, we discuss potential interventions to minimize these adverse effects and discuss the clinical application of five microbiota-targeted strategies that precisely increase the efficacy of cancer immunotherapy. Finally, as the gut microbiota holds promising potential as a target for precision cancer immunotherapeutics, we summarize current challenges and provide a general outlook on future directions in this field.

Abstract Immune checkpoint inhibitors targeting the programmed cell death-1 (PD-1) protein significantly improve survival in patients with advanced non-small-cell lung cancer (NSCLC), but its impact on early-stage ground-glass opacity (GGO) lesions remains unclear. This is a single-arm, phase II trial (NCT04026841) using Simon’s optimal two-stage design, of which 4 doses of sintilimab (200 mg per 3 weeks) were administrated in 36 enrolled multiple primary lung cancer (MPLC) patients with persistent high-risk (Lung-RADS category 4 or had progressed within 6 months) GGOs. The primary endpoint was objective response rate (ORR). T/B/NK-cell subpopulations, TCR-seq, cytokines, exosomal RNA, and multiplexed immunohistochemistry (mIHC) were monitored and compared between responders and non-responders. Finally, two intent-to-treat (ITT) lesions (pure-GGO or GGO-predominant) showed responses (ORR: 5.6%, 2/36), and no patients had progressive disease (PD). No grade 3–5 TRAEs occurred. The total response rate considering two ITT lesions and three non-intent-to-treat (NITT) lesions (pure-solid or solid-predominant) was 13.9% (5/36). The proportion of CD8+ T cells, the ratio of CD8+/CD4+, and the TCR clonality value were significantly higher in the peripheral blood of responders before treatment and decreased over time. Correspondingly, the mIHC analysis showed more CD8+ T cells infiltrated in responders. Besides, responders’ cytokine concentrations of EGF and CTLA-4 increased during treatment. The exosomal expression of fatty acid metabolism and oxidative phosphorylation gene signatures were down-regulated among responders. Collectively, PD-1 inhibitor showed certain activity on high-risk pulmonary GGO lesions without safety concerns. Such effects were associated with specific T-cell re-distribution, EGF/CTLA-4 cytokine compensation, and regulation of metabolism pathways.

Abstract Radiofrequency ablation (RFA) comparative efficacy of treatments using video-assisted thoracoscopic sympathectomy (VATS) in the long term remains uncertain in patients with palmar hyperhidrosis (PHH). This study aimed to compare the efficacy and safety of RFA and VATS in patients with PHH. We recruited patients aged ≥ 14 years with diagnosed PHH from 14 centres in China. The treatment options of RFA or VATS were assigned to two cohort in patients with PHH. The primary outcome was the efficacy at 1-year. A total of 807 patients were enrolled. After propensity score matching, the rate of complete remission was lower in RFA group than VATS group (95% CI 0.21–0.57; p

Summary: The NLRP3 inflammasome is a key multi-protein complex controlling inflammation, particularly interleukin-1β (IL-1β) production. Here, we present a protocol to profile spatially resolved NLRP3 inflammasome complexes using ascorbic peroxidase 2 (APEX2)-based proximity labeling combined with liquid chromatography-tandem mass spectrometry (LC-MS/MS). We describe steps for design and generation of the fusion construct, characterization of the stable FLAG-NLRP3-APEX2 expression cell line by western blotting/imaging, biotinylated proteome enrichment, and mass spectrometry analysis.For complete details on the use and execution of this protocol, please refer to Liang et al.1 : Publisher’s note: Undertaking any experimental protocol requires adherence to local institutional guidelines for laboratory safety and ethics.

FeCoCrNiAlx (x=0, 0.5, 1.0, mole ratio, the same below) coatings were prepared on the surface of TC4 titanium alloy by electric explosion spraying technology. The effects of Al content on the phase structure, surface morphology, microhardness and wear resistance of high-entropy alloy coatings were studied by means of XRD, SEM, EDS, microhardness tester and friction and wear test. The results show that the grain size of the coatings is nano-scale, and simple FCC, BCC and FCC+BCC solid solutions are formed. With the increase of Al element, the phase structure is gradually changed from FCC phase to BCC phase. The surface of the coatings is smooth and dense, without obvious cracks, and the elements are evenly distributed on the surface of the coatings, and no obvious segregation of elements is found. The scratch test shows that the average critical load for the failure of the FeCoCrNiAl1.0 coatings is 37.2 N. The coating is metallurgically bonded to the substrate. The hardness and wear resistance of the coatings are positively correlated with the Al content. When x is 1.0, the average microhardness reaches the maximum value of 531.8HV, which is about 1.62 times that of the substrate. The FeCoCrNiAl1.0 coatings have the smallest amount of wear, and the wear resistance is about 3.9 times that of the substrate. The wear mechanism is mainly abrasive wear.

Summary: Activation of the NACHT, LRR, and PYD domains-containing protein 3 (NLRP3) inflammasome complex is an essential innate immune signaling mechanism. To reveal how human NLRP3 inflammasome assembly and activation are controlled, in particular by components of the ubiquitin system, proximity labeling, affinity purification, and RNAi screening approaches were performed. Our study provides an intricate time-resolved molecular map of different phases of NLRP3 inflammasome activation. Also, we show that ubiquitin C-terminal hydrolase 1 (UCH-L1) interacts with the NACHT domain of NLRP3. Downregulation of UCH-L1 decreases pro-interleukin-1β (IL-1β) levels. UCH-L1 chemical inhibition with small molecules interfered with NLRP3 puncta formation and ASC oligomerization, leading to altered IL-1β cleavage and secretion, particularly in microglia cells, which exhibited elevated UCH-L1 expression as compared to monocytes/macrophages. Altogether, we profiled NLRP3 inflammasome activation dynamics and highlight UCH-L1 as an important modulator of NLRP3-mediated IL-1β production, suggesting that a pharmacological inhibitor of UCH-L1 may decrease inflammation-associated pathologies.

Abstract Chronic obstructive pulmonary disease (COPD) is a serious chronic lung disease. Schisandrin A (SchA) is one of the most important active ingredients in Schisandra chinensis and has been used to treat various lung diseases in several countries. Here, we studied the pharmacological effect of SchA on airway inflammation induced by cigarette smoke (CS) and explored the therapeutic mechanism of SchA in COPD model mice. Our results showed that SchA treatment significantly improved the lung function of CS-induced COPD model mice and reduced the recruitment of leukocytes and hypersecretion of interleukin-6 (IL-6), interleukin-1β (IL-1β) and tumor necrosis factor α (TNF-α) in bronchoalveolar lavage fluid (BALF). H&E staining showed that SchA treatment could effectively reduce emphysema, immune cell infiltration and airway wall destruction. In addition, we found that SchA treatment can stimulate the expression of heme oxygenase-1 (HO-1) through the nuclear factor-erythroid 2-related factor (Nrf2) pathway, significantly reduce oxidative stress, increase catalase (CAT) and superoxide dismutase (SOD) levels, and suppress the level of malondialdehyde (MDA) in COPD model mice. Moreover, SchA treatment suppressed the generation of the NLRP3/ASC/Caspase1 inflammasome complex to inhibit the inflammatory response caused by IL-1β and IL-18 and pyroptosis caused by GSDMD. In conclusion, our study shows that SchA treatment can inhibit the production of ROS and the activation of the NLRP3 inflammasome by upregulating Nrf-2, thereby producing anti-inflammatory effects and reducing lung injury in COPD model mice. More importantly, SchA exhibited similar anti-inflammatory effects to dexamethasone in COPD model mice, and we did not observe substantial side effects of SchA treatment. The high safety of SchA makes it a potential candidate drug for the treatment of COPD.

Abstract The transcription factor family activator protein 2 (TFAP2) is vital for regulating both embryonic and oncogenic development. The TFAP2 family consists of five DNA-binding proteins, including TFAP2A, TFAP2B, TFAP2C, TFAP2D and TFAP2E. The importance of TFAP2 in tumor biology is becoming more widely recognized. While TFAP2D is not well studied, here, we mainly focus on the other four TFAP2 members. As a transcription factor, TFAP2 regulates the downstream targets directly by binding to their regulatory region. In addition, the regulation of downstream targets by epigenetic modification, posttranslational regulation, and interaction with noncoding RNA have also been identified. According to the pathways in which the downstream targets are involved in, the regulatory effects of TFAP2 on tumorigenesis are generally summarized as follows: stemness and EMT, interaction between TFAP2 and tumor microenvironment, cell cycle and DNA damage repair, ER- and ERBB2-related signaling pathway, ferroptosis and therapeutic response. Moreover, the factors that affect TFAP2 expression in oncogenesis are also summarized. Here, we review and discuss the most recent studies on TFAP2 and its effects on carcinogenesis and regulatory mechanisms.

Abstract Objectives Aberrantly expressed circular RNAs (circRNAs) have been detected in many types of tumors. Hence, they are currently investigated as candidate biomarkers for diagnostic and potential targets for therapy in cancers. The objective of this study was to assess the expression profile of circRNA in lung adenocarcinoma (LUAD). Methods This study included 14 pairs of postoperative lung adenocarcinoma specimens, including cancer tissues and matched adjacent tissues. Second‐generation sequencing was applied to the specimens to determine the circRNA expression in them among the 5242 distinct circRNAs detected. Results We identified a total of 18 significantly dysregulated circRNAs in the LUAD tissues: upregulation in four and downregulation in 14. ROC (The receiver operating characteristic curve) further suggested that hsa_circ_0120106, has_circ_0007342, has_circ_0005937, and circRNA_0000826 could potentially be used as biomarkers in the diagnosis of LUAD. Furthermore, study of the circRNA–microRNA (miRNA)–messenger RNA (mRNA) revealed interactions between the 18 dysregulated circRNA and several cancer‐related miRNAs. Finally, a further Kyoto Encyclopedia of Genes and Genomes analysis showed that the cell cycle phase transition, p53 signaling pathway, AMP‐activated protein kinase (AMPK) relative signaling pathway, and so on were key putative pathways in the process of LUAD. Conclusions These findings demonstrated the correlation between abnormality in circRNA expression and LUAD, which lays the foundation of making CircRNAs candidate biomarkers in the diagnosis of LUAD.

The key to implementing the fundamental task of establishing moral education is how the abstract and broad physical education and health curriculum core literacy is translated into concrete and visible physical education and health subject curriculum and teaching practice. This paper firstly explains the framework for the realization of core literacy in PE and health curriculum in teaching and learning, specifically from three perspectives: context, health behavior, and physical virtue. Secondly, the abstract core literacy of physical education and health curriculum is transformed into a side problem of ordinary differential equation with unknown parameter initial values by using the method of ordinary differential error approximation, which can obtain the parametric expressions of the approximation of function values at the nodes and realize the concretization. The experimental results show that there is a significant difference between the core literacy of physical education and health curriculum based on the ordinary differential error approximation method before and after the application of the core literacy in teaching, in which the comprehensive improvement of motor ability is 23.7%, the comprehensive improvement of health behavior is 19.2%, and the comprehensive improvement of physical morality is 26.6%. This paper successfully visualized the core literacy issues of physical education and health curriculum based on the ordinary differential error approximation method, which provided a reference for physical education teaching, improved the professional competence and quality of school physical education teachers, and formed the characteristics of school physical education and health curriculum.

The substance here is to workshop the current problems of physical education in higher learning institutions and construct a reform and innovation machinery of sports learning style in institutions of higher learning. This paper researches the teaching system of college sports learning style based on BP nervous enlist the services, proposes a majorization network foundation hereditary compute mode for the shortcoming that BP nervous enlist the services to be prone to land oneself in the optimal regional solution, and takes 10 influence element the results of academy sports learning style as the sample features of the data set, uses the optimized GA-BP nervous enlist the services for discipline and compares the test results with the practice price and the dispatch of other algorithms. The average error of the detection of GA-BP nervous enlist the services was 1.23, and the average error rate was 1.85%, which performed better compared with other neural networks. In terms of the poundage of the influencing factors in the export multiple, the diversity of curriculum, the advancement of teaching philosophy and the science of sports skill instruction have significant effects on the amount of sports learning style in institutions of higher learning, with the weights reaching 0.1212, 0.1387 and 0.1453, respectively. The reform and innovation of sports learning style in institutions of higher learning should develop diversified physical education courses according to students’ constitution bases and sports levels and impart scientific methods of the constitution and sports values of enjoying sports.

To produce the porous coating on the inner wall of the pipe is an effective way to enhance heat transfer performance and improve heat exchange efficiency. The electric explosion spraying method was employed to produce the porous coating on the inner wall of the pipe. The surface morphology, roughness and pore distribution of the coating under different initial voltages were studied. The mechanism for the formation of the coating was investigated by the deposition energy and explosive products explained. The results indicate that the initial voltage of the electric explosion spraying influences the microstructure of coating. The optimal porous coating can be obtained when the initial voltage of the electric explosion spraying is 14.0 kV. The optimal porous coating is formed by the accumulation of the small particles. Moreover, the optimal porous coating is obtained, the surface area is 4.47 times that of the uncoated pipe and the porosity of the ideal coating is 57.8%. The uniform round porous coating is formed, when the initial voltage of the electric explosion spraying is 15.2 kV. The porosity of those coating is 40.3%. The formation of the coating depends on the energy deposited on the copper wire during the explosion. The energy deposited on the copper wire acts as the thermodynamic condition for the sprayed particles, determines the energy and particle size of the sprayed particles and the states of the sprayed particles collide with the surface of the base tube or the particles accumulate or form a molten pool. Finally, it influences the microscopic morphology of the coating.

Background/Aims Disrupted bile acid regulation and accumulation in the liver can contribute to progressive liver damage and fibrosis. However, the effects of bile acids on the activation of hepatic stellate cells (HSCs) remain unclear. This study investigated the effects of bile acids on HSC activation during liver fibrosis, and examined the underlying mechanisms. Methods The immortalized HSCs, LX-2 and JS-1cells were used for the in vitro study. in vitro, the adeno-associated viruses adeno-associated virus-sh-S1PR2 and JTE-013 were used to pharmacologically inhibit the activity of S1PR2 in a murine model of fibrosis induced by a 3,5-diethoxycarbonyl-1,4-dihydrocollidine (DDC) diet. Histological and biochemical analyses were performed to study the involvement of S1PR2 in the regulation of fibrogenic factors as well as the activation properties of HSCs. Results S1PR2 was the predominant S1PR expressed in HSCs and was upregulated during taurocholic acid (TCA) stimulation and in cholestatic liver fibrosis mice. TCA-induced HSC proliferation, migration and contraction and extracellular matrix protein secretion were inhibited by JTE-013 and a specific shRNA targeting S1PR2 in LX-2 and JS-1 cells. Meanwhile, treatment with JTE-013 or S1PR2 deficiency significantly attenuated liver histopathological injury, collagen accumulation, and the expression of fibrogenesis-associated genes in mice fed a DDC diet. Furthermore, TCA-mediated activation of HSCs through S1PR2 was closely related to the yes-associated protein (YAP) signaling pathway via p38 mitogen-activated protein kinase (p38 MAPK). Conclusions TCA-induced activation of the S1PR2/p38 MAPK/YAP signaling pathways plays a vital role in regulating HSC activation, which might be therapeutically relevant for targeting cholestatic liver fibrosis.

The invasiveness of ground-glass nodules (GGNs) is difficult to characterize through morphological examination. Multiple studies have independently detected a close relationship between mean computed tomography value and invasiveness of GGNs, however, their relative diagnostic accuracy is uncertain. Here, we performed a meta-analysis to validate whether the mean computed tomography value can predict the invasiveness of GGNs. Briefly, we searched the Web of Science, Embase, PubMed, Cochrane, Google Scholar, CNKI, VIP, Wanfang and SinoMed databases. The sensitivity, specificity, 95% confidence interval (CI), symmetric receiver operating characteristic curve (SROC curve) and the area under curve (AUC) were obtained using STATA 16.0 to evaluate the predictive value of the mean computed tomography value for GGNs. The presence of heterogeneity was assessed using fixed effects sensitivity analysis and I2 statistics. We used the Deek's funnel plot to evaluate the possibility of publication bias. Thirteen studies encompassing 1564 GGNs were included in our meta-analysis. Six of these studies revealed that using the mean computed tomography value for the diagnosis of pre-invasive and invasive lesions had a sensitivity and specificity of 0.75 (95% CI: 0.61–0.85) and 0.81 (95% CI: 0.74–0.86), respectively. The optimal critical value was −557 Hu. Later, eight studies were examined for the use of the mean CT value for patients with minimally invasive adenocarcinoma (MIA) and invasive adenocarcinoma (IAC); the results showed that the sensitivity was 0.78 (95% CI: 0.66–0.86) and the specificity was 0.81 (95% CI: 0.68–0.89), and the optimal critical value was −484 Hu. Therefore, the mean computed tomography value assessed via CT scan could be a significant predictor of the invasiveness of GGNs as well as a good surgical treatment guide in patients diagnosed with lung cancer. Prospero registration number: CRD42020177125.

A brain-computer interface (BCI) measures and analyzes brain activity and converts it into computer commands to control external devices. Traditional BCIs usually require full calibration, which is time-consuming and makes BCI systems inconvenient to use. In this study, we propose an online P300 BCI spelling system with zero or shortened calibration based on a convolutional neural network (CNN) and big electroencephalography (EEG) data. Specifically, three methods are proposed to train CNNs for the online detection of P300 potentials: (i) training a subject-independent CNN with data collected from 150 subjects; (ii) adapting the CNN online via a semisupervised learning/self-training method based on unlabeled data collected during the user’s online operation; and (iii) fine-tuning the CNN with a transfer learning method based on a small quantity of labeled data collected before the user’s online operation. Note that the calibration process is eliminated in the first two methods and dramatically shortened in the third method. Based on these methods, an online P300 spelling system is developed. Twenty subjects participated in our online experiments. Average accuracies of 89.38%, 94.00% and 93.50% were obtained by the subject-independent CNN, the self-training-based CNN and the transfer learning-based CNN, respectively. These results demonstrate the effectiveness of our methods, and thus, the convenience of the online P300-based BCI system is substantially improved.

Accurate reconstruction of the brain activities from electroencephalography and magnetoencephalography (E/MEG) remains a long-standing challenge for the intrinsic ill-posedness in the inverse problem. In this study, to address this issue, we propose a novel data-driven source imaging framework based on sparse Bayesian learning and deep neural network (SI-SBLNN). Within this framework, the variational inference in conventional algorithm, which is built upon sparse Bayesian learning, is compressed via constructing a straightforward mapping from measurements to latent sparseness encoding parameters using deep neural network. The network is trained with synthesized data derived from the probabilistic graphical model embedded in the conventional algorithm. We achieved a realization of this framework with the algorithm, source imaging based on spatio-temporal basis function (SI-STBF), as backbone. In numerical simulations, the proposed algorithm validated its availability for different head models and robustness against distinct intensities of the noise. Meanwhile, it acquired superior performance compared to SI-STBF and several benchmarks in a variety of source configurations. Additionally, in real data experiments, it obtained the concordant results with the prior studies.

Mangroves are one of the most important wetland ecosystems. The development of fisheries in tropical and subtropical bays or estuaries is closely associated with mangroves since the high heterogeneity of the mangrove ecosystem provides a suitable habitat for marine organisms. However, multiple factors have led to a significant reduction in mangroves, such as water pollution, disease, insect pests, invasive alien species, and climate change. It is crucial to understand the relationships among organisms, as well as the interactions between organisms and their environment, by studying the ecological niche width and overlap of species. Therefore, two new perspectives of ecological niche width and ecological niche overlap were used to understand the interspecific ecological relationships, competition mechanisms, and resource utilization status of fish communities in mangrove forests. Based on the data collected during seasonal sampling in July 2019 (summer), October 2019 (autumn), January 2020 (winter), and May 2020 (spring) in the Nanliujiang Estuary, the index of relative importance (IRI), Shannon index, and Pianka index were employed to analyze the temporal and spatial niche of the main fish species in the mangrove creeks and to study niche differentiation among the main fish species by redundancy analysis. A total of 17,680 individual fish were collected in this study, belonging to 12 orders, 23 families, 37 genera, and 45 species. Ten main fish species with IRI>100 were identified. Among the main fish species, the temporal niche breadth ranged from 0.46 to 1.78, with the highest of which belonging to Butis butis (1.78) and the lowest belonging to Pseudogobius javanicus (0.46). The spatial niche breadth ranged from 0.81 to 2.05, with the highest of which belonging to Synechogobius ommaturus (2.05) and the lowest belonging to P. javanicus (0.81). The spatiotemporal niche breadth of six species was greater than 2 (wide-niche species) that included Mugil cephalus, Coptodon zillii, Bostrychus sinensis, S. ommaturus, B. butis, and Pisodonophis boro. With regard to overlap, the temporal niche overlap between M. cephalus and P. javanicus was the highest (0.928), whereas that between Ambassis urotaenia and Terapon jarbua (0.001) was the lowest. The spatial niche overlap between A. urotaenia and Gambusia affinis was the highest (0.979), whereas that between M. cephalus and P. javanicus (0.178) was the lowest. Finally, the spatiotemporal niche overlap between C. zillii and P. javanicus was the highest (0.822), whereas that between A. urotaenia and Terapon jarbua (0.001) was the lowest. The two-dimensional temporal and spatial niche pairs in the mangrove creeks of the Nanliujiang River Estuary significantly overlapped (Qik > 0.6), accounting for 6.7% of the total species pairs, indicating that the temporal and spatial distributions of species were quite different and the temporal and spatial niche overlap was affected by seasonal changes. Redundancy analysis revealed that the main factors affecting spatiotemporal niche differentiation of the main fish species in the mangrove creeks of the Nanliujiang Estuary were water temperature, salinity, and Chlorophyll a. And the main fish biomass in winter was positively correlated with salinity; the main fish biomass in spring was positively correlated with dissolved oxygen, pH and Chlorophyll a; the main fish biomass in summer was positively correlated with total organic carbon, water temperature and Chlorophyll a; the main fish biomass in autumn was positively correlated with total nitrogen, turbidity and total phosphorus.

Abstract Background Lung adenocarcinoma (LUAD) is a leading cause of cancer-related death worldwide. Ferroptosis, a form of cell death characterized by iron-dependent lipid peroxidation. However, the involvement of ferroptosis in the regulation of immune cell infiltration and its immunotherapeutic efficacy in LUAD remain unclear. Methods The Cancer Genome Atlas (TCGA) LUAD cohort was used to assess the survival prognosis of FRGs and construct a seven-gene risk signature. Correlation tests, difference tests, and a cluster analysis were performed to explore the role of FRGs in the immune microenvironment and their immunotherapeutic efficacy in LUAD. The effects of FRGs on LUAD cells were assessed by Western blot, iron assay, and lipid peroxidation assay. Results The seven-gene risk signatures of patients with LUAD were established and validated. FRG clustering based on 70 differentially expressed FRGs was associated with the immune microenvironment and indicated potential immune subtypes of LUAD. The seven-gene risk signature was an independent prognostic factor for LUAD and was used to divide the LUAD cohort into a high-risk and a low-risk group. Immunocyte infiltration levels, immune checkpoints, and immunotherapy response rates were significantly different between the two groups. Patients with high risk scores had lower overall levels of immunocyte infiltration but higher immunotherapy response rates. The key gene ribonucleotide reductase subunit M2 (RRM2) was associated with LUAD prognosis, which may be related to its ability to regulate the infiltration levels of activated mast cells and activated CD4 memory T cells. In addition, RRM2 was involved in ferroptosis, and its expression was up regulated in lung cancer tissues and the LUAD cell lines. Silencing RRM2 can inhibit the proliferation and induce ferroptosis of H1975 cells suggesting that silencing RRM2 could promote ferroptosis in H1975 cells. Conclusion Our results revealed RRM2 as a promising biomarker and therapeutic target associated with tumor immune infiltration in patients with LUAD.

ObjectiveAlthough previous studies have reported an association between thyroid function and anti-Müllerian hormone (AMH) levels, which is considered a reliable marker of ovarian reserve, the causal relationship between them remains uncertain. This study aims to investigate whether thyrotropin (TSH), free thyroxine (fT4), hypo- and hyperthyroidism are causally linked to AMH levels.MethodsWe obtained summary statistics from three sources: the ThyroidOmics Consortium (N = 54,288), HUNT + MGI + ThyroidOmics meta-analysis (N = 119,715), and the most recent AMH genome-wide association meta-analysis (N = 7,049). Two-sample MR analyses were conducted using instrumental variables representing TSH and fT4 levels within the normal range. Additionally, we conducted secondary analyses to explore the effects of hypo- and hyperthyroidism. Subgroup analyses for TSH were also performed.ResultsMR analyses did not show any causality relationship between thyroid function and AMH levels, using normal range TSH, normal range fT4, subclinical hypothyroidism, subclinical hyperthyroidism and overt hypothyroidism as exposure, respectively. In addition, neither full range TSH nor TSH with individuals

The action of freeze–thaw (F–T) cycles of claystone exerts a profound impact on the slope stability of open-pit mines in water-rich regions. Microstructural changes are observed as a crucial factor in determining the hydraulic characteristics and mechanical behaviors of claystone. The present work integrates a micro-X-ray computed tomography (Micro-CT) scanner, equipped with image processing and three-dimensional (3D) reconstruction capabilities, employed to observe the microstructure of claystone under varying numbers of F–T cycles (0, 10, 20, 30, and 50). Furthermore, seepage numerical simulations based on Micro-CT measurements are conducted to evaluate the hydraulic characteristics. Through meticulous microscopic observation and mechanical analysis, the damage mechanism induced by F–T cycles is revealed and the evolutionary characteristics are analyzed. The two-dimensional (2D) images of 3D reconstructed models unveil the gradual initiation propagation and coalescence of an intricate fissuring network in claystone during the F–T cycles. As the number of F–T cycles increases from 0 to 50, the 3D porosity exhibits exponential growth. Additionally, the influence of F–T cycles substantially enhances the connectivity of fissures. The seepage numerical simulations demonstrate that the evolutionary progression of fissures substantially augments the number of flow paths and enhances permeability. The increase in permeability follows an exponential trend, reflecting the distribution and evolution of fissures under F–T cycles. The impact on permeability arises from a combination of micromechanical properties and the microstructure of claystones. The present research tries to elucidate the microscopic evolution of fissures and their corresponding hydraulic properties in water-saturated claystone, offering significant insights for investigating the slope stability of open-pit mines in regions.

Summary: Cancer is a leading cause of mortality worldwide. Over 50% of cancers are diagnosed late, rendering many treatments ineffective. Existing liquid biopsy studies demonstrate a minimally invasive and inexpensive approach for disease detection but lack parsimonious biomarker selection, exhibit poor cancer detection performance and lack appropriate validation and testing. We established a tailored machine learning pipeline, DEcancer, for liquid biopsy analysis that addresses these limitations and improved performance. In a test set from a published cohort of 1,005 patients including 8 cancer types and 812 cancer-free individuals, DEcancer increased stage 1 cancer detection sensitivity across cancer types from 48 to 90%. In addition, with a test set cohort of patients from a high dimensional proteomics dataset of 61 lung cancer patients and 80 cancer-free individuals, DEcancer’s performance using a 14-43 protein panel was comparable to 1,000 original proteins. DEcancer is a promising tool which may facilitate improved cancer detection and management.

Abstract Background Circular RNAs (circRNAs) play an important role in the progression of non-small cell lung cancer (NSCLC), especially under tumor hypoxia. However, the precise functions and underlying mechanisms of dysregulated circRNAs in NSCLC are largely unknown. Methods High-throughput RNA sequencing was performed to identify significantly expressed circRNAs in NSCLC tissues. The functions of circ-0001875 in NSCLC cells were investigated in vitro and in vivo. The regulatory relationships of circ-0001875, miR-31-5p and SP1 were examined by dual luciferase reporter assays and rescue experiments. The signal pathway of epithelial-to-mesenchymal transition and the formation of filopodia were analyzed by western blot and immunofluorescence staining. The binding of SP1 to Alu elements was evaluated by RNA immunoprecipitation, and the HIF1α and SP1 interaction was detected by co-immunoprecipitation. Results We identified the novel Has_circ_0001875 as a significantly upregulated circRNA in NSCLC tissues and cell lines. circ-0001875 promoted the proliferation and metastasis of NSCLC both in vitro and in vivo, and induced NSCLC cells to extend filopodia. Mechanistically, circ-0001875 sponged miR-31-5p to regulate SP1, influencing epithelial-to-mesenchymal transition via the TGFβ/Smad2 signal pathway. SP1 negatively regulated circ-0001875 formation through an AluSq-dependent feedback loop, which was disrupted by competitive binding of HIF1α to SP1 under hypoxia condition. The circ-0001875/miR-31-5p/SP1 axis was associated with the clinical features and prognosis of NSCLC patients. Conclusions Our results revealed that the circ-0001875/miR-31-5p/SP1 axis and the complex regulatory loops influence NSCLC progression. These findings provide new insights into the regulation of circRNA formation under tumor hypoxia.

In order to study the influence of tunnel volume loss on adjacent framed buildings with different shallow foundations, this paper carried out physical model experiments with two common types of footings (isolated and strip footings) under different working conditions based on the digital image correlation (DIC) technique. The main finding of the present paper is that the increase in formation loss rate will aggravate the deformation and damage of the structure, and the strip foundation shows stronger integrity and stability compared with the isolated foundation in this process. With the increase in the eccentricity of the frames with respect to the tunnel, the overall tilt and damage degree of structural elements increases first and then decreases for both foundations, reaching the maximum value with the eccentric distance of one multiple of the tunnel diameter. Interestingly, when the isolated footings are located directly above the tunnel, the damage in the inner panels is the most severe and gradually decreases with eccentricity, changing from a sagging mode to a hogging mode for the frame form. While the strip footings always maintain slight hogging, and the trend of the damage degree of panels is similar to that of elements, with the eccentric distance reaching two times the tunnel diameter, the strip foundation structure tends to be stable, while the isolated one still needs attention for its potential possibility of damage in panels. The research results have reference value for the impact assessment of adjacent shallow-foundation framed buildings in subway tunnel construction.

Recently, there has been a focus on drawing progress on representation learning to obtain more identifiable and interpretable latent representations for spike trains, which helps analyze neural population activity and understand neural mechanisms. Most existing deep generative models adopt carefully designed constraints to capture meaningful latent representations. For neural data involving navigation in cognitive space, based on insights from studies on cognitive maps, we argue that the good representations should reflect such directional nature. Due to manifold mismatch, models utilizing the Euclidean space learn a distorted geometric structure that is difficult to interpret. In the present work, we explore capturing the directional nature in a simpler yet more efficient way by introducing hyperspherical neural latent variable models (SNLVM). SNLVM is an improved deep latent variable model modeling neural activity and behavioral variables simultaneously with hyperspherical latent space. It bridges cognitive maps and latent variable models. We conduct experiments on modeling a static unidirectional task. The results show that while SNLVM has competitive performance, a hyperspherical prior naturally provides more informative and significantly better latent structures that can be interpreted as spatial cognitive maps.

Accurate reconstruction of cortical activation from electroencephalography and magnetoencephalography (E/MEG) is a long-standing challenge because of the inherently ill-posed inverse problem. In this paper, a novel algorithm under the empirical Bayesian framework, source imaging with smoothness in spatial and temporal domains (SI-SST), is proposed to address this issue. In SI-SST, current sources are decomposed into the product of spatial smoothing kernel, sparseness encoding coefficients, and temporal basis functions (TBFs). Further smoothness is integrated in the temporal domain with the employment of an underlying autoregressive model. Because sparseness encoding coefficients are constructed depending on overlapped clusters over cortex in this model, we derived a novel update rule based on fixed-point criterion instead of the convexity based approach which becomes invalid in this scenario. Entire variables and hyper parameters are updated alternatively in the variational inference procedure. SI-SST was assessed by multiple metrics with both simulated and experimental datasets. In practice, SI-SST had the superior reconstruction performance in both spatial extents and temporal profiles compared to the benchmarks.

BackgroundVaccine hesitancy was found in couples seeking artificial reproductive technology (ART) services. As the main vaccine used in China, investigations into the influence of inactivated coronavirus disease 2019 (COVID-19) vaccines on human fertility is needed.MethodsThis retrospective cohort study included data on COVID-19 vaccination, clinical characteristics, and reproductive outcome of 1,000 intrauterine insemination (IUI) cycles in 653 couples from March 2021 to March 2022 in a single university hospital-based center for reproductive medicine. The IUI cycles were divided into two categories based on sperm source, including 725 cycles in 492 women undergoing artificial insemination with their husband's sperm (AIH) and 275 cycles in 161 women undergoing artificial insemination with donor sperm (AID). Women were then divided into two groups. The vaccine exposed group included women vaccinated prior to insemination and the unexposed group included women who were not vaccinated or vaccinated after insemination. Reproductive outcomes including ongoing pregnancy rate, clinical pregnancy rate, and miscarriage rate were assessed.ResultsInactivated COVID-19 vaccinated women prior to intrauterine insemination in AIH cycles have comparable ongoing pregnancy rate (11.1 vs. 10.3%, P = 0.73), clinical pregnancy rate (12.5 vs. 11.3%, P = 0.60) as compared with unvaccinated counterparts. Similarly, there were no significant differences in ongoing pregnancy rate (20.9 vs. 28.1%, P = 0.17), clinical pregnancy rate (21.7 vs. 28.8%, P = 0.19) between vaccine exposed and unexposed groups in AID cycles. Multivariable logistic regression analyses showed that inactivated COVID-19 vaccination status cannot independently influence the reproductive outcomes of AIH and AID cycles. Subgroup analysis of vaccine exposed cycles showed that doses of vaccination and Interval between the last dose of vaccination and insemination have no influence on the reproductive outcomes of AIH cycles.ConclusionsNo negative effects were found on female fertility in IUI cycles following exposure to the inactivated COVID-19 vaccine. These findings indirectly reflect the safety of inactivated COVID-19 vaccine toward reproductive health and help to mitigate vaccine hesitancy among people planning to conceive.

Shallow landslides pose serious threats to human existence and economic development, especially in the Himalayan areas. Landslide susceptibility mapping (LSM) is a proven way for minimizing the hazard and risk of landslides. Modeling as an essential step, various algorithms have been applied to LSM, but no consensus exists on which model is most suitable or best. In this study, information value (IV) and logistic regression (LR) were selected as representatives of the conventional algorithms, categorical boosting (CatBoost), and conventional neural networks (CNN) as the advanced algorithms, for LSM in Yadong County, and their performance was compared. To begin with, 496 historical landslide events were compiled into a landslide inventory map, followed by a list of 11 conditioning factors, forming a data set. Secondly, the data set was randomly divided into two parts, 80% of which was used for modeling and 20% for validation. Finally, the area under the curve (AUC) and statistical metrics were applied to validate and compare the performance of the models. The results showed that the CNN model performed the best (sensitivity = 79.38%, specificity = 91.00%, accuracy = 85.28%, and AUC = 0.908), while the LR model performed the worst (sensitivity = 79.38%, specificity = 76.00%, accuracy = 77.66%, and AUC = 0.838) and the CatBoost model performed better (sensitivity = 76.28%, specificity = 85.00%, accuracy = 80.81%, and AUC = 0.893). Moreover, the LSM constructed by the CNN model did a more reasonable prediction of the distribution of susceptible areas. As for feature selection, a more detailed analysis of conditioning factors was conducted, but the results were uncertain. The result analyzed by GI may be more reliable but fluctuates with the amount of data. The conclusion reveals that the accuracy of LSM can be further improved with the advancement of algorithms, by determining more representative features, which serve as a more effective guide for land use planning in the study area or other highlands where landslides are frequent.

Recently, motor imagery brain-computer interfaces (MI-BCIs) with stimulation systems have been developed in the field of motor function assistance and rehabilitation engineering. An efficient stimulation paradigm and Electroencephalogram (EEG) decoding method have been designed to enhance the performance of MI-BCI systems. Therefore, in this study, a multimodal dual-level stimulation paradigm is designed for lower-limb rehabilitation training, whereby visual and auditory stimulations act on the sensory organ while proprioceptive and functional electrical stimulations are provided to the lower limb. In addition, upper triangle filter bank sparse spatial pattern (UTFB-SSP) is proposed to automatically select the optimal frequency sub-bands related to desynchronization rhythm during enhanced imaginary movement to improve the decoding performance. The effectiveness of the proposed MI-BCI system is demonstrated on an the in-house experimental dataset and the BCI competition IV IIa dataset. The experimental results show that the proposed system can effectively enhance the MI performance by inducing the α, β and γ rhythms in lower-limb movement imagery tasks.

As machine learning (ML) methods continue to be applied to a broad scope of problems in the physical sciences, uncertainty quantification is becoming correspondingly more important for their robust application. Uncertainty-aware machine learning methods have been used in select applications, but largely for scalar properties. In this work, we showcase an exemplary study in which neural network ensembles are used to predict the x-ray absorption spectra of small molecules, as well as their pointwise uncertainty, from local atomic environments. The performance of the resulting surrogate clearly demonstrates quantitative correlation between errors relative to ground truth and the predicted uncertainty estimates. Significantly, the model provides an upper bound on the expected error. Specifically, an important quality of this uncertainty-aware model is that it can indicate when the model is predicting on out-of-sample data. This allows for its integration with large-scale sampling of structures together with active learning or other techniques for structure refinement. Additionally, our models can be generalized to larger molecules than those used for training, and also successfully track uncertainty due to random distortions in test molecules. While we demonstrate this workflow on a specific example, ensemble learning is completely general. We believe it could have significant impact on ML-enabled forward modeling of a broad array of molecular and materials properties.

Abstract Controlling the activation of the NLRP3 inflammasome by post-translational modifications (PTMs) of critical protein subunits has emerged as a key determinant in inflammatory processes as well as in pathophysiology. In this review, we put into context the kinases, ubiquitin processing and other PTM enzymes that modify NLRP3, ASC/PYCARD and caspase-1, leading to inflammasome regulation, activation and signal termination. Potential target therapeutic entry points for a number of inflammatory diseases focussed on PTM enzyme readers, writers and erasers, leading to the regulation of inflammasome function, are discussed. Video Abstract

ObjectiveTo investigate the associations between sleep behaviors and female infertility.MethodsWe conducted a cross-sectional study composed of 2175 U.S. women 18-44 years of age from the National Health and Nutrition Examination Survey (NHANES) (2015-2018). Bedtime/waketime and sleep duration were extracted from the sleep disorder questionnaire. Self-reported infertility was defined as a binary variable based on the participants’ response to the question, “Have you ever attempted to become pregnant over a period of at least a year without becoming pregnant?”. Multivariate logistic regression analyses were done to explore the relationship between sleep behaviors and female infertility.ResultsBedtime (OR=1.24; 95% CI, 1.10-1.40, P = 0.001) and waketime (OR=1.14; 95% CI, 1.01-1.28, P = 0.037) were associated with infertility. Waketime of 08:00 was the inflection point, above which the probability of infertility increased rapidly (OR=1.41; 95% CI, 1.11-1.79, P = 0.004). Sleep-wake behavior was significantly associated with infertility (OR=1.34; 95% CI, 1.16-1.53, P < 0.001) and participants with early-bed/early-rise behavior had the lowest risk.ConclusionsAmong U.S. women 18-44 years of age, bedtime and waketime were significantly linearly and non-linearly correlated with infertility, respectively. Early-bed/early-rise behavior was associated with the lowest infertility rate. Further study is needed because the timing of sleep behaviors are modifiable factors and could be a novel strategy to cope with infertility.

Identification of forest gaps is a prerequisite for quantification of their size, shape, and dynamics, and for clarification of both complex structural forest species regeneration and understory species diversity. Although airborne LiDAR and digital orthophoto maps (DOM) have been used separately to identify forest gaps, few studies have considered integration of the two data sources for forest gap segmentation and classification. True color DOM (20 cm) and airborne LiDAR (3.7 points/m2) data were used to study object-oriented gap identification in the typical natural secondary forest of the Maoershan Experimental Forest Farm (China). Three segmentation schemes based on DOM only data, LiDAR data, and integrated DOM & LiDAR were adopted when processing the object-oriented classification. Based on the segmentation results, the support vector machine classifier was used with DOM spectral features, LiDAR height features, and integrated features from both data sources to identify forest gaps. The Modified Euclidean Distance 3 (ED3Modified) index was selected to assess segmentation quality. Comparison of the three segmentation schemes revealed that segmentation based on LiDAR was the best and the classification accuracy using integrated spectral and height features was the highest (OA = 87%, Kappa = 0.81). Those results could provide technical support for the quantitative analysis of forest gap features.

Abstract Corydalis yanhusuo W.T. Wang alkaloids are mainly divided into three categories: protoberberine, prototropine and aporphine alkaloids. Therefore, we have taken into account these three alkaloid contents when extracting and purifying crude drugs, which is essential for the quality control of C. yanhusuo and its derivative products. Herein, we investigated the feasibility of the Q-marker uniform design method in the optimization of the extraction and purification of C. yanhusuo. In this study, Q-marker-based comprehensive scoring (CS) and uniform design methods were used to optimize the extraction and purification of C. yanhusuo. The inspective factors included the solvent concentration, pH, liquid–solid ratio, extraction time and frequency. Then 8 Q-markers, the total alkaloid extraction and the extraction rate were considered as the evaluating indicators during the process. The results indicated that the optimal reflux extraction process of C. yanhusuo was as follows: a total amount of 20 times 70% ethanol (pH = 10 of diluted ammonia), heating and refluxing twice, and extracting each time for 60 min. The results of nine-resin screening exhibited that NKA-9 macroporous adsorption resin had the best separation and purification effect on 8 kinds of C. yanhusuo alkaloids with stronger enrichment. During the optimal enrichment process and elution conditions, the water-soluble impurities were washed off with 5 BV distilled water at a volume flow rate of 2 BV/h, and the elution solvent was 70% ethanol with an elution volume flow rate of 1.5 BV/h and an elution dosage of 12 BV. Additionally, the total alkaloids of the obtained product were over 50%, of which eight quality markers were (+)-corydaline 3.55%, tetrahydropalmatine 3.13%, coptisine 2.79%, palmatine hydrochloride 2.24%, dehydrocorydaline 13.11%, (R)-(+)-corypalmine 2.37%, protopine 2.71% and glaucine 14.03%. Our data demonstrated that the optimal extraction and purification process was stable and feasible, which was expected to provide an experimental basis and reference for the industrial production of C. yanhusuo.

ABSTRACT Ectomycorrhizal (EcM) fungi play important roles in forest ecosystems, and their richness and composition can change along with elevation and season changes. However, no study has estimated the relative importance of altitudinal and seasonal heterogeneity in predicting the distribution of EcM fungal communities by simultaneously considering different sample types (root versus soil). In this study, we collected root and soil samples along a > 1,500-m elevation gradient during wet and dry seasons from Baima Snow Mountain, located in “the Mountains of Southwest China,” one of the 34 biodiversity hot spots, and we analyzed them using next-generation sequencing. Regardless of the sample type, similar EcM fungal richness pattern with increasing elevation (decline in the forest zone, and an increase at the alpine meadow zone) and strong community turnovers among different elevational zones and between two seasons were detected, and changes of EcM fungal community similarity on 400-m altitude gradient were equivalent to the community turnover between dry and wet seasons. Elevation and edaphic factors were shown to have the largest effects on EcM fungal community. The heterogeneity of richness and community composition was stronger among different elevational zones than across different seasons, mainly because the elevation variations in the EcM fungal community were shaped by the combined effects of different environmental factors, while seasonal changes were mainly controlled by temperature and fast-changing soil nutrients. IMPORTANCE Altitude and season represent two important environmental gradients that shape the structure of biome, including the heterogeneity of EcM fungi. Previous studies have separately considered the influences of altitude and season on EcM fungal communities, but the relative importance of altitude and season is still unknown. The present study revealed that elevation influences the heterogeneity of EcM fungal community more than season; this may be because the variability of environmental factors is higher across different elevations than that across seasons.

Achieving high classification performance is challenging due to non-stationarity and low signal-to-noise ratio (low SNR) characteristics of EEG signals. Spatial filtering is commonly used to improve the SNR yet the individual differences in the underlying temporal or frequency information is often ignored. This paper investigates motor imagery signals via orthogonal wavelet decomposition, by which the raw signals are decomposed into multiple unrelated sub-band components. Furthermore, channel-wise spectral filtering via weighting the sub-band components are implemented jointly with spatial filtering to improve the discriminability of EEG signals, with an l2-norm regularization term embedded in the objective function to address the underlying over-fitting issue. Finally, sparse Bayesian learning with Gaussian prior is applied to the extracted power features, yielding an RVM classifier. The classification performance of SEOWADE is significantly better than those of several competing algorithms (CSP, FBCSP, CSSP, CSSSP, and shallow ConvNet). Moreover, scalp weight maps of the spatial filters optimized by SEOWADE are more neurophysiologically meaningful. In summary, these results demonstrate the effectiveness of SEOWADE in extracting relevant spatio-temporal information for single-trial EEG classification.

Scanning electron microscope (SEM) was used to study the morphologies of 3 kinds of domestic T800 carbon fiber (CCF800). Infrared spectrogram was used to analyse the structure of CCF800 sizing agent. In order to study the hygrothermal properties of domestic CCF800/epoxy composites, moisture absorption behavior and interlaminar shear property under hygrothermal environment were tested. Furthermore, SEM was used to study the interface between carbon fiber and epoxy after hygrothermal treatment. The results show that the morphologies of the 3 kinds of CCF800 are similar, while the chemical structures of sizing agent have a difference. The three kinds of CCF800/epoxy composite share the similar saturated moisture absorption period, that is about 54 days. And 95% saturated moisture absorption period is also the same, that is about 30 days. However, there is a obvious difference in saturated moisture absorption. In CCF800-3 sizing agent, the highest content of hydroxy leads to the highest moisture absorption rate of its epoxy resin matrix composite, and the interlaminar shear strength decreases most obviously under the action of high temperature and high humidity.