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Abstract This paper presents a novel approach to the phase space reconstruction technique, fractional-order phase space reconstruction (FOSS), which generalizes the traditional integer-order derivative-based method. By leveraging fractional derivatives, FOSS offers a novel perspective for understanding complex time series, revealing unique properties not captured by conventional methods. We further develop the multi-span transition entropy component method (MTECM-FOSS), an advanced complexity measurement technique that builds upon FOSS. MTECM-FOSS decomposes complexity into intra-sample and inter-sample components, providing a more comprehensive understanding of the dynamics in multivariate data. In simulated data, we observe that lower fractional orders can effectively filter out random noise. Time series with diverse long- and short-term memory patterns exhibit distinct extremities at different fractional orders. In practical applications, MTECM-FOSS exhibits competitive or superior classification performance compared to state-of-the-art algorithms when using fewer features, indicating its potential for engineering tasks.

Abstract. Background:. Early detection of esophageal squamous cell carcinoma (ESCC) can considerably improve the prognosis of patients. Aberrant cell-free DNA (cfDNA) methylation signatures are a promising tool for detecting ESCC. However, available markers based on cell-free DNA methylation are still inadequate. This study aimed to identify ESCC-specific cfDNA methylation markers and evaluate the diagnostic performance in the early detection of ESCC. Methods:. We performed whole-genome bisulfite sequencing (WGBS) for 24 ESCC tissues and their normal adjacent tissues. Based on the WGBS data, we identified 21,469,837 eligible CpG sites (CpGs). By integrating several methylation datasets, we identified several promising ESCC-specific cell-free DNA methylation markers. Finally, we developed a dual-marker panel based on methylated KCNA3 and OTOP2, and then, we evaluated its performance in our training and validation cohorts. Results:. The ESCC diagnostic model constructed based on KCNA3 and OTOP2 had an AUC of 0.91 [95% CI: 0.85–0.95], and an optimal sensitivity and specificity of 84.91% and 94.32%, respectively, in the training cohort. In the independent validation cohort, the AUC was 0.88 [95% CI: 0.83–0.92], along with an optimal sensitivity of 81.5% and specificity of 92.9%. The model sensitivity for stage I–II ESCC was 78.4%, which was slightly lower than the sensitivity of the model (85.7%) for stage III–IV ESCC. Conclusion:. The dual-target panel based on cfDNA showed excellent performance for detecting ESCC and might be an alternative strategy for screening ESCC.

Abstract Ethylene regulates plant growth, development, and stress adaptation. However, the early signaling events following ethylene perception, particularly in the regulation of ethylene receptor/CTRs (CONSTITUTIVE TRIPLE RESPONSE) complex, remains less understood. Here, utilizing the rapid phospho-shift of rice OsCTR2 in response to ethylene as a sensitive readout for signal activation, we revealed that MHZ3, previously identified as a stabilizer of ETHYLENE INSENSITIVE 2 (OsEIN2), is crucial for maintaining OsCTR2 phosphorylation. Genetically, both functional MHZ3 and ethylene receptors prove essential for OsCTR2 phosphorylation. MHZ3 physically interacts with both subfamily I and II ethylene receptors, e.g., OsERS2 and OsETR2 respectively, stabilizing their association with OsCTR2 and thereby maintaining OsCTR2 activity. Ethylene treatment disrupts the interactions within the protein complex MHZ3/receptors/OsCTR2, reducing OsCTR2 phosphorylation and initiating downstream signaling. Our study unveils the dual role of MHZ3 in fine-tuning ethylene signaling activation, providing insights into the initial stages of the ethylene signaling cascade.

Abstract Measurement of the cervical range of motion (CROM) is significant for early diagnosis of cervical spondylosis and determination of the severity of the disease. Aiming at the problem of convenient and continuous measurement of CROM and the reduction of the impact of data fluctuations, this paper proposes a low‐cost method for testing and analyzing CROM. This paper analyzes the correspondence between smartphone orientation sensor angle and CROM, obtains smartphone orientation sensing data, and uses the extreme‐point symmetric mode decomposition method by calculating the energy of the difference value to extract the adaptive global mean curve of the CROM data, and calculates the cervical ROM. The statistical analysis of the CROM test results is carried out. Results show that the method proposed can obtain the CROM including flexion and extension, lateral flexion, and rotation in a single measurement, which has the advantages of continuous measurement and low cost.

Abstract As an emerging cancer treatment strategy, reactive oxygen species-based tumor catalytic therapies face enormous challenges due to hypoxia and the overexpression of glutathione (GSH) in the tumor microenvironment. Herein, a self-assembled copper-based nanoplatform, TCCHA, was designed for enzyme-like catalysis-enhanced chemodynamic/photodynamic/antiangiogenic tritherapy against hepatocellular carcinoma. TCCHA was fabricated from Cu2+, 3,3′-dithiobis (propionohydrazide), and photosensitizer chlorine e6 via a facile one-pot self-assembly strategy, after which an aldehyde hyaluronic acid was coated, followed by loading of the antivascular drug AL3818. The obtained TCCHA nanoparticles exhibited pH/GSH dual-responsive drug release behaviors and multienzymatic activities, including Fenton, glutathione peroxidase-, and catalase-like activities. TCCHA, a redox homeostasis disruptor, promotes ⋅OH generation and GSH depletion, thus increasing the efficacy of chemodynamic therapy. TCCHA, which has catalase-like activity, can also reinforce the efficacy of photodynamic therapy by amplifying O2 production. In vivo, TCCHA efficiently inhibited tumor angiogenesis and suppressed tumor growth without apparent systemic toxicity. Overall, this study presents a facile strategy for the preparation of multienzyme-like nanoparticles, and TCCHA nanoparticles display great potential for enzyme catalysis-enhanced chemodynamic/photodynamic/antiangiogenic triple therapy against cancer. Graphical Abstract

Abstract Background Previous studies have largely neglected the role of sulfur metabolism in LUAD, and no study has combine iron, copper, and sulfur-metabolism associated genes together to create prognostic signatures. Methods This study encompasses 1564 LUAD patients, 1249 NSCLC patients, and over 10,000 patients with various cancer types from diverse cohorts. We employed the R package ConsensusClusterPlus to separate patients into different ICSM (Iron, Copper, and Sulfur-Metabolism) subtypes. Various machine-learning methods were utilized to develop the ICSMI. Enrichment analyses were conducted using ClusterProfiler and GSVA, while IOBR quantified immune cell infiltration. GISTIC2.0 and maftools were utilized for CNV and SNV data analysis. The Oncopredict package predicted drug information based on GDSC1. TIDE algorithm and cohorts GSE91061 and IMvigor210 evaluated patient response to immunotherapy. Single-cell data was processed using the Seurat package, AUCell package calculated cells geneset activity scores, and the Scissor algorithm identified ICSMI-associated cells. In vitro experiments was conducted to explore the role of ICSMRGs in LUAD. Results Unsupervised clustering identified two distinct ICSM subtypes of LUAD, each with unique clinical characteristics. The ICSMI, comprising 10 genes, was constructed using integrated machine-learning methods. Its prognostic power was validated in 10 independent datasets, revealing that LUAD patients with higher ICSMI levels had poorer prognoses. Furthermore, ICSMI demonstrated superior predictive abilities compared to 102 previously published signatures. A nomogram incorporating ICSMI and clinical features exhibited high predictive performance. ICSMI positively correlated with patients gene mutations, and integrated analysis of bulk and single-cell transcriptome data revealed its association with TME modulators. Cells representing the high-ICSMI phenotype exhibited more malignant features. LUAD patients with high ICSMI levels exhibited sensitivity to chemotherapy and targeted therapy but displayed resistance to immunotherapy. In a comprehensive analysis across various cancers, ICSMI retained significant prognostic value and emerged as a risk factor for the majority of cancer patients. Conclusions ICSMI provides critical prognostic insights for LUAD patients, offering valuable insights into the tumor microenvironment and predicting treatment responsiveness.

Abstract To explore the spontaneous combustion characteristics and hazards of the low-temperature oxidation (LTO) stage in the process of spontaneous combustion of coal and mudstone, the pore structure, spontaneous combustion characteristic parameters, and exothermic characteristics of coal and mudstone were tested and studied, and the oxidation kinetic parameters were calculated. The results show that mudstone has a larger specific surface area and pore volume than coal. From the fractal characteristics, the pore structure of mudstone is more complex than that of coal. According to the comparison of theoretical and actual gas generation and oxygen consumption rate curves, it is found that there is an interaction between coal and mudstone in the LTO process. With the increase of mudstone mass ratio, gas production, and its oxygen consumption rate increase. Among them, CM-4 (Coal:Mudstone = 1:1) has the highest exothermic intensity and the exothermic factor (A) and fire coefficient (K) increase with the increase of mudstone content. The apparent activation energy of the mudstone sample is lower than that of the raw coal, indicating that the sample after adding mudstone is more likely to have spontaneous combustion in the LTO stage.

Abstract We aimed to identify the druggable cell-intrinsic vulnerabilities and target-based drug therapies for PitNETs using the high-throughput drug screening (HTS) and genomic sequencing methods. We examined 9 patient-derived PitNET primary cells in HTS. Based on the screening results, the potential target genes were analyzed with genomic sequencing from a total of 180 PitNETs. We identified and verified one of the most potentially effective drugs, which targeted the Histone deacetylases (HDACs) both in in vitro and in vivo PitNET models. Further RNA sequencing revealed underlying molecular mechanisms following treatment with the representative HDACs inhibitor, Panobinostat. The HTS generated a total of 20,736 single-agent dose responses which were enriched among multiple inhibitors for various oncogenic targets, including HDACs, PI3K, mTOR, and proteasome. Among these drugs, HDAC inhibitors (HDACIs) were, on average, the most potent drug class. Further studies using in vitro, in vivo, and isolated PitNET primary cell models validated HDACIs, especially Panobinostat, as a promising therapeutic agent. Transcriptional surveys revealed substantial alterations to the Nrf2 signaling following Panobinostat treatment. Moreover, Nrf2 is highly expressed in PitNETs. The combination of Panobinostat and Nrf2 inhibitor ML385 had a synergistic effect on PitNET suppression. The current study revealed a class of effective anti-PitNET drugs, HDACIs, based on the HTS and genomic sequencing. One of the representative compounds, Panobinostat, may be a potential drug for PitNET treatment via Nrf2-mediated redox modulation. Combination of Panobinostat and ML385 further enhance the effectiveness for PitNET treatment.

Abstract In order to study the effect of temperature on the structure and mechanical properties of coal with different metamorphic degree. Three coal samples with varying degrees of metamorphism were chosen for analysis. The discrete element software PFC2D is used to simulate the heat treatment and compression of coal. The findings indicate that during the heating process, low-order coal exhibits noticeable thermal cracks at an early stage, while thermal crack development in middle-order coal is concentrated in the later stages. In contrast, high-order coal demonstrates a more stable macroscopic structure. The strength and stiffness of low rank coal show the lowest value and decrease significantly within 135 °C. However, the strength and stiffness of medium rank coal decrease significantly after 135 °C. The changes of mechanical properties and damage modes of coal caused by thermal damage are often ignored, which may lead to the deviation of design and research results from the actual situation. Therefore, this study is of great significance to the prevention and control of coal mine disasters.

To investigate the mechanism of inhibition of spontaneous combustion of coal by degradation of white-rot fungus, the changes of macroscopic oxidizing characteristics and microstructure of the degraded coal were investigated by the programmed temperature-raising test and the in situ Fourier-transform infrared spectroscopy experiments. The difference in gas production between the degraded coal and the blank samples indicated that the degradation inhibited the oxidation process of coal, and the intensity of the inhibition effect was different at different oxidation stages. The strongest inhibition effect was found in the accelerated oxidation stage, i.e. 80–140 °C. To further analyze the micro-mechanism of the degradation of Phanerochaete chrysosporium affecting the spontaneous combustion of coal, the relative contents of active functional groups in coal samples were compared. The results showed that the degradation affected the relative contents of hydroxyl, aliphatic hydrocarbon, and oxygenated functional groups in coal. Among them, the most significant changes of –OH and –CO- were observed at 80–140 °C. Thus, it was analyzed that Phanerochaete chrysosporium could degrade the macromolecular structure of coal by generating biological enzymes to reduce the number of oxidizable functional groups such as –OH, –CH2, –CH3, –CO-, and so on, thus reducing the risk of spontaneous combustion of coal.

Background and objective Computed tomography guided percutaneous lung biopsy (CT-PLB) is a widely used method for the diagnosis of lung lesions. However, it is invasive, and the most common complications are pneumothorax and pulmonary hemorrhage, which can be life-threatening in severe cases. Therefore, the aim of this study is to analyze the independent risk factors affecting the occurrence of different complications of CT-PLB, so as to reduce the incidence of complications. Methods The 605 patients with complete clinical data who underwent CT-PLB in our hospital from May 2018 to December 2019 were retrospectively analyzed. According to the location of the lesions, they were divided into subpleural group and non-subpleural group. The patients were divided into pneumothorax group, pulmonary hemorrhage group, pneumothorax with pulmonary hemorrhage group and non-pneumothorax/pulmonary hemorrhage group according to the complications. The risk factors affecting the incidence of different complications and the independent risk factors of each complication were analyzed. Results The incidence of pneumothorax was 34.1%, the incidence of pulmonary hemorrhage was 28.1%, and the incidence of pneumothorax complicated with pulmonary hemorrhage was 10.8% (63 cases). The independent risk factor affecting the incidence of subpleural pneumothorax was lesion size (P=0.002). The independent risk factors affecting the occurrence of pneumothorax in the non-subpleural group were plain scan CT value (P=0.035), length of needle through lung tissue (P=0.003), and thickness of needle through chest wall (P=0.020). Independent risk factors affecting the occurrence of pulmonary hemorrhage in the non-subpleural group were length of needle through lung tissue (P

Abstract Exonucleases serve as efficient tools for signal processing and play an important role in biochemical reactions. Here, we identify the mechanism of cooperative exonuclease hydrolysis, offering a method to regulate the cooperative hydrolysis driven by exonucleases through the modulation of the number of bases in gap region. A signal transmission strategy capable of producing amplified orthogonal DNA signal is proposed to resolve the polarity of signals and byproducts, which provides a solution to overcome the signal attenuation. The gap-regulated mechanism combined with DNA strand displacement (DSD) reduces the unpredictable secondary structures, allowing for the coexistence of similar structures in hierarchical molecular networks. For the application of the strategy, a molecular computing model is constructed to solve the maximum weight clique problems (MWCP). This work enhances for our knowledge of these important enzymes and promises application prospects in molecular computing, signal detection, and nanomachines.

The transformation of aldose to ketose or common sugars into rare saccharides, including rare ketoses and aldoses, is of great value and interest to the food industry and for saccharidic biomass utilization, medicine, and the synthesis of drugs. Nowadays, high-fructose corn syrup (HFCS) is industrially produced in more than 10 million tons annually using immobilized glucose isomerase. Some low-calorie saccharides such as tagatose and psicose, which are becoming popular sweeteners, have also been produced on a pilot scale in order to replace sucrose and HFCS. However, current catalysts and catalytic processes are still difficult to utilize in biomass conversion and also have strong substrate dependence in producing high-value, rare sugars. Considering the specific reaction properties of saccharides and catalysts, since the pioneering discovery by Fischer, various catalysts and catalytic systems have been discovered or developed in attempts to extend the reaction pathways, improve the reaction efficiency, and to potentially produce commercial products. In this review, we trace the history of sugar isomerization/epimerization reactions and summarize the important breakthroughs for each reaction as well as the difficulties that remain unresolved to date.

Abstract Ethylene/α-olefin copolymers are produced in huge scale and widely used, but their after-use disposal has caused plastic pollution problems. Their chemical inertness made chemical re/upcycling difficult. Ideally, PE materials should be made de novo to have a circular closed-loop lifecycle. However, synthesis of circular ethylene/α-olefin copolymers, including high-volume, linear low-density PE as well as high-value olefin elastomers and block copolymers, presents a particular challenge due to difficulties in introducing branches while simultaneously installing chemical recyclability and directly using industrial ethylene and α-olefin feedstocks. Here we show that coupling of industrial coordination copolymerization of ethylene and α-olefins with a designed functionalized chain-transfer agent, followed by modular assembly of the resulting AB telechelic polyolefin building blocks by polycondensation, affords a series of ester-linked PE-based copolymers. These new materials not only retain thermomechanical properties of PE-based materials but also exhibit full chemical circularity via simple transesterification and markedly enhanced adhesion to polar surfaces.

Abstract Radionuclides internal radiotherapy (RIT) is a clinically powerful method for cancer treatment, but still poses unsatisfactory therapeutic outcomes due to the hypoxic characteristic of tumor microenvironment (TME). Catalase (CAT) or CAT-like nanomaterials can be used to enzymatically decompose TME endogenous H2O2 to boost TME oxygenation and thus alleviate the hypoxic level within tumors, but their effectiveness is still hindered by the short-lasting of hypoxia relief owing to their poor stability or degradability, thereby failing to match the long therapeutic duration of RIT. Herein, we proposed an innovative strategy of using facet-dependent CAT-like Pd-based two-dimensional (2D) nanoplatforms to continuously enhance RIT. Specifically, rationally designed 2D Pd@Au nanosheets (NSs) enable consistent enzymatic conversion of endogenous H2O2 into O2 to overcome hypoxia-induced RIT resistance. Furthermore, partially coated Au layer afford NIR-II responsiveness and moderate photothermal treatment that augmenting their enzymatic functionality. This approach with dual-effect paves the way for reshaping TME and consequently facilitating the brachytherapy ablation of cancer. Our work offers a significant advancement in the integration of catalytic nanomedicine and nuclear medicine, with the overarching goal of amplifying the clinical benefits of RIT-treated patients. Graphical abstract

Abstract Severe mental health problems with the representation of negative affect symptoms (NAS) have been increasingly reported during the coronavirus disease 2019 (COVID-19) pandemic. This study aimed to explore the multivariate patterns of brain functional connectome predicting COVID-19-related NAS. This cohort study encompassed a group of university students to undergo neuroimaging scans before the pandemic, and we re-contacted participants for 1-year follow-up COVID-related NAS evaluations during the pandemic. Regularized canonical correlation analysis was used to identify connectome-based dimensions of NAS to compute pairs of canonical variates. The predictive ability of identified functional connectome to NAS dimensional scores was examined with a nested cross-validation. Two dimensions (i.e. mode stress and mode anxiety) were related to distinct patterns of brain functional connectome (r 2 = 0.911, P FDR = 0.048; r 2 = 0.901, P FDR = 0.037, respectively). Mode anxiety was characterized by high loadings in connectivity between affective network (AFN) and visual network (VN), while connectivity of the default mode network with dorsal attention network (DAN) were remarkably prominent in mode stress. Connectivity patterns within the DAN and between DAN and VN, ventral attention network, and AFN was common for both dimensions. The identified functional connectome can reliably predict mode stress (r = 0.37, MAE = 5.1, p

Abstract Background Extensive local invasion of glioblastoma (GBM) cells within the central nervous system (CNS) is one factor that severely limits current treatments. The aim of this study was to uncover genes involved in the invasion process, which could also serve as therapeutic targets. For the isolation of invasive GBM cells from non-invasive cells, we used a three-dimensional organotypic co-culture system where glioma stem cell (GSC) spheres were confronted with brain organoids (BOs). Using ultra-low input RNA sequencing (ui-RNA Seq), an invasive gene signature was obtained that was exploited in a therapeutic context. Methods GFP-labeled tumor cells were sorted from invasive and non-invasive regions within co-cultures. Ui-RNA sequencing analysis was performed to find a gene cluster up-regulated in the invasive compartment. This gene cluster was further analyzed using the Connectivity MAP (CMap) database. This led to the identification of SKF83566, an antagonist of the D1 dopamine receptor (DRD1), as a candidate therapeutic molecule. Knockdown and overexpression experiments were performed to find molecular pathways responsible for the therapeutic effects of SKF83566. Finally, the effects of SKF83566 were validated in orthotopic xenograft models in vivo. Results Ui-RNA seq analysis of three GSC cell models (P3, BG5 and BG7) yielded a set of 27 differentially expressed genes between invasive and non-invasive cells. Using CMap analysis, SKF83566 was identified as a selective inhibitor targeting both DRD1 and DRD5. In vitro studies demonstrated that SKF83566 inhibited tumor cell proliferation, GSC sphere formation, and invasion. RNA sequencing analysis of SKF83566-treated P3, BG5, BG7, and control cell populations yielded a total of 32 differentially expressed genes, that were predicted to be regulated by c-Myc. Of these, the UHRF1 gene emerged as the most downregulated gene following treatment, and ChIP experiments revealed that c-Myc binds to its promoter region. Finally, SKF83566, or stable DRD1 knockdown, inhibited the growth of orthotopic GSC (BG5) derived xenografts in nude mice. Conclusions DRD1 contributes to GBM invasion and progression by regulating c-Myc entry into the nucleus that affects the transcription of the UHRF1 gene. SKF83566 inhibits the transmembrane protein DRD1, and as such represents a candidate small therapeutic molecule for GBMs.

In this article, a novel infrared maritime small target detection method, called local dissimilarity measure with anti-interference based on global graph clustering (LDMGGC), is proposed. The Wasserstein distance is introduced to calculate the dissimilarity of gray level distribution between a central region and its neighborhoods. These dissimilarities construct the feature of a region. With this feature, detection for recalling all suspected targets is achieved. As the maritime interferences among suspected targets are able to be clustered, relaxing mutual k nearest neighbor graph is introduced in global graph clustering for filtering interferences. With this method, real targets are detected and maritime interferences are filtered out. Experiments are conducted on three maritime datasets and a nonmaritime dataset for comparison. On three datasets, the proposed method achieves the best Receiver Operating Characteristic curves and Area Under Curve (0.99529, 0.99945, 0.99573, and 0.9906) values, meaning that the proposed method has high detection probability and low false-alarm ratio. Target Hit Rate (98.04%, 97.96%, 100%, and 99.24%) and Intersection of Union (0.8170, 0.7542, 0.5824, 0.7707) on four datasets of the proposed method show it has a strong ability to suppress the interferences.

The human gastrointestinal tract, boasting the most diverse microbial community, harbors approximately 100 trillion microorganisms comprising viruses, bacteria, fungi, and archaea. The profound genetic and metabolic capabilities of the gut microbiome underlie its involvement in nearly every facet of human biology, from health maintenance and development to aging and disease. Recent recognition of microbiota – gut – brain axis, referring to the bidirectional communication network between gut microbes and their host, has led to a surge in interdisciplinary research. This review begins with an overview of the current understandings regarding the influence of gut microbes on intestinal and blood-brain barrier integrity. Subsequently, we discuss the mechanisms of the microbiota – gut – brain axis, examining the role of gut microbiota-related neural transmission, metabolites, gut hormones and immunity. We propose the concept of microbiota-mediated multi-barrier modulation in the potential treatment in gastrointestinal and neurological disorders. Furthermore, the role of lymphatic network in the development and maintenance of barrier function is discussed, providing insights into lesser-known conduits of communication between the microbial ecosystem within the gut and the brain. In the final section, we conclude by describing the ongoing frontiers in understanding of the microbiota – gut – brain axis’s impact on human health and disease.

Autolysins are endogenous cell wall degrading enzymes (CWDEs) in bacteria that remodel the peptidoglycan layer of its own cell wall. In the Bacillus subtilis genome, at least 35 autolysin genes have been identified. However, the study of their roles in bacterial physiology has been hampered by their complexity and functional redundancy. B. subtilis GLB191 is an effective biocontrol strain against grape downy mildew disease, the biocontrol effect of which results from both direct effect against the pathogen and stimulation of the plant defense. In this study, we show that the autolysin N-acetylglucosaminidase LytD, a major autolysin of vegetative growth in B. subtilis, plays an important role in its biocontrol activity against grape downy mildew. Disruption of lytD resulted in reduced suppression of the pathogen Plasmopara viticola and stimulation of the plant defense. LytD is also shown to affect the biofilm formation and colonization of B. subtilis on grape leaves. This is the first report that demonstrates the role of an endogenous CWDE in suppressing plant disease infection of a biological control microorganism. These findings not only expand our knowledge on the biological function of autolysins but also provide a new target to promote the biocontrol activity of B. subtilis.

Nitroamino is an ideal high-energy group for constructing energetic compounds. The skeletal isomerization of nitroamino to nitroimino forms intramolecular HBs, thus resulting in better density, thermal stability and sensitivity. However, it is difficult to find nitroamino and nitroimino in the same environment for comparative analysis. A new compound, 5-Nitroamino-8-nitroimino-1,4-dihydropyrazino [2,3-d]pyridazine-2,3-dione (3), was designed and synthesized. The symmetric skeleton of pyrazino [2,3-d]pyridazine provides the same environment for both nitroamino and nitroimino groups. By using a variety of computational and graphical methods, a theoretical support for nitroamino-based energetic materials was produced by thoroughly examining the influence between nitroamino and nitroimino.

Abstract Objective To investigate the expression of TTC7B and its prognostic significance, biological roles, and impact on the immune system in patients with head and neck squamous cell carcinoma (HNSCC). Materials and Methods Clinical and genomic data were obtained from TCGA (The Cancer Genome Atlas), GEO (Gene Expression Omnibus), GEPIA2 (Gene Expression Profiling Interactive Analysis 2.0), and TIMER2.0 (Tumor Immune Estimation Resource 2.0) databases. R software was utilized to process the retrieved data. qPCR and immunohistochemical assays were performed to validate the findings obtained from the databases. Results High expression of TTC7B was observed in HNSCC, and this heightened expression is significantly associated with reduced overall survival (OS) in patients, making it an independent risk factor impacting OS. TTC7B is correlated with focal adhesions and cell migration pathways based on functional enrichment analysis. CIBERSORT analysis and TIMER2.0 show a positive link between TTC7B and multiple immune cells, particularly macrophages. Pearson's analysis reveals a significant correlation between TTC7B and ferroptosis‐related genes. Conclusion In all, TTC7B could serve as a promising prognostic indicator of HNSCC, and is closely associated with focal adhesions, immune infiltration, and ferroptosis.

Abstract The presence of different types of coal at room temperature can lead to self-heating of coal, potentially resulting in spontaneous combustion. To investigate the effect of ambient temperature pre-oxidation (BL) time on the self-combustion characteristics of different coal types, synchronous thermal analysis (STA) and Fourier-transform infrared spectroscopy (FTIR) experiments were conducted. The results of the synchronous thermal analysis experiments indicate that ambient temperature pre-oxidation for 3 months (BL3), BL6, and BL9 coals exhibit faster oxidation reactions compared to the original coal, while BL12 coal shows slower oxidation than the original coal. Among these, BL9 coal demonstrates the most significant changes in oxidation reaction characteristics, with the fastest oxidation reaction time being 35.36 min, which is 1.38 min faster than the original coal. To support this observation, a comparison was made between the relative content of active functional groups in the original coal and BL coal. The study revealed that the BL process affects the relative content of hydroxyl groups, aromatic hydrocarbons, aliphatic hydrocarbons, and oxygen-containing functional groups, thereby influencing the coal-oxygen reaction process. This suggests that pre-oxidized coal, compared to the original coal, has a larger pore structure, which plays a dominant role in promoting coal self-combustion in the first 9 months of the BL process. As BL time continues to increase, the continuous reaction of active functional groups at room temperature leads to excessive consumption, resulting in a more significant role in inhibiting coal self-combustion. The research results provide valuable insights for predicting the spontaneous combustion risk of oxidized coal.

Abstract. Background:. Hypertensive heart disease (HHD) poses a public health challenge, but data on its burden and trends among older adults are scarce. This study aimed to identify trends in the burden of HHD among older adults between 1990 and 2019 at the global, regional, and national levels. Methods:. Using the Global Burden of Diseases study 2019 data, we assessed HHD prevalence, death, and disability-adjusted life-year (DALY) rates for individuals aged 60-89 years at the global, regional, and national levels and estimated their average annual percentage changes (AAPCs) between 1990 and 2019 using joinpoint regression analysis. Results:. In 2019, there were 14.35 million HHD prevalent cases, 0.85 million deaths, and 14.56 million DALYs in older adults. Between 1990 and 2019, the prevalence of HHD increased globally {AAPC, 0.38 (95% confidence interval [CI], 0.36, 0.41)} with decreases observed in mortality (AAPC, -0.83 [95% CI, -0.99, -0.66]) and the DALY rate (AAPC, -1.03 [95% CI, -1.19, -0.87]). This overall global trend pattern was essentially maintained for sex, age group, and sociodemographic index (SDI) quintile except for non-significant changes in the prevalence of HHD in those aged 70-74 years and in the middle SDI quintile. Notably, males had a higher HHD prevalence rate. However, HHD-related mortality and the DALY rate were higher in females. The middle SDI quintile experienced the largest decreases in mortality and the DALY rate, with a non-significant decline in prevalence between 1990 and 2019. There were significant discrepancies in the HHD burden and its trends across regions and countries. Conclusions:. In the past three decades, there has been an overall increasing trend in the prevalence of HHD among older adults worldwide despite decreasing trends in mortality and the DALY rate. Better management of hypertension, and prevention and control of HHD are needed in older adults.

Abstract Skeletal disorders are commonly diagnosed by X-ray imaging, but the radiation limits its use. Optical imaging through the near-infrared-II window (NIR-II, 1000–1700 nm) can penetrate deep tissues without radiation risk, but the targeting of contrast agent is non-specific. Here, we report that lanthanide-doped nanocrystals can passively target the bone marrow, which can be effective for over two months. We therefore develop the high-resolution NIR-II imaging method for bone disease diagnosis, including the 3D bone imaging instrumentation to show the intravital bone morphology. We demonstrate the monitoring of 1 mm bone defects with spatial resolution comparable to the X-ray imaging result. Moreover, NIR-II imaging can reveal the early onset inflammation as the synovitis in the early stage of rheumatoid arthritis, comparable to micro computed tomography (μCT) in diagnosis of osteoarthritis, including the symptoms of osteophyte and hyperostosis in the knee joint.

In saline environments, it is difficult for reinforced concrete structures to meet normal durability requirements, which in turn affects the mechanical properties of the members. In this context, this paper proposes a reinforcement method that involves wrapping corroded reinforced concrete columns with CFRP (carbon fiber reinforced polymer) cloth. By conducting axial compression tests on four specimens, key mechanical performance indicators such as failure mode, ductility, and bearing capacity during the entire stress process of the specimens were analyzed, revealing the failure mechanism of CFRP-confined corroded reinforced concrete columns. A refined finite element model of CFRP-confined corroded reinforced concrete columns was established using ABAQUS software. The influence of key parameters such as the number of CFRP wrapping layers, longitudinal reinforcement corrosion rate, and axial compression ratio on the mechanical properties of the specimens was studied, and the influence of each parameter was determined. Furthermore, a formula for the axial compression bearing capacity of CFRP-confined corroded reinforced concrete columns was proposed. The results indicate that in the presence of corroded steel reinforcement, specimens confined with CFRP undergo substantial lateral constraints during the mid to late stages of loading. This approach effectively alleviates the transverse deformation of the concrete. The specimen demonstrated yield bearing capacities and peak loads of 1441 KN and 1934 KN, respectively, representing a 2.2-fold and 2.5-fold increase compared to the non-reinforced specimen. With the increase in the transverse strain of concrete, CFRP begins to play a restraint role, and a more obvious restraint role in the failure stage of members. It is recommended to apply 1–3 layers of CFRP wrapping for a longitudinal reinforcement corrosion rate of 5%, 3–5 layers for a rate of 10%, and 6–8 layers for an overall corrosion rate of 15%. This paper establishes a theoretical framework for investigating the performance characteristics of such columns and offers technical assistance for practical engineering purposes.

Based on the first principles, the structural stability, mechanical characteristics, electronic structure, and thermodynamic properties of AlCu2M (M = Ti, Cr, Zr, Sc, Hf, Mn, Pa, Lu, Pm) are investigated. The calculated results indicate that the AlCu2Pa crystal structure is more stable and that AlCu2Pa should be easier to form. All of the AlCu2M compounds have structural stability in the ground state. Elastic constants are used to characterize the mechanical stability and elastic modulus, while the B/G values and Poisson ratio demonstrate the brittleness and ductility of AlCu2M compounds. It is demonstrated that all computed AlCu2M compounds are ductile and mechanically stable, with AlCu2Hf having the highest bulk modulus and AlCu2Mn having the highest Young’s modulus. AlCu2Mn has the highest intrinsic hardness among AlCu2M compounds, according to calculations of their intrinsic hardness. The electronic densities of states are discussed in detail; it was discovered that all AlCu2M compounds form Al-Cu and Al-M covalent bonds. Additionally, we observe that the Debye temperature and minimum thermal conductivity of AlCu2Mn and AlCu2Sc are both larger than those of others, indicating stronger chemical bonds and higher thermal conductivities, which is consistent with the elastic modulus results.

Seismic design principles advocate for simple and regular structures to minimize earthquake damage. However, this frequently does not lead to unique and aesthetically pleasing designs, leading some engineers to select irregular structures despite the potential risks. The primary aim of this investigation is to achieve the optimal design of torsional irregularity coefficients for planar irregular reinforced concrete (RC) frames under static and dynamic loads, utilizing a 3D 6-layer model. Structural ground vibration analysis was conducted using the ETABS software. By imposing limits on the torsional irregularity coefficients for each layer of the frame layout, we subsequently applied the combination of artificial neural networks (ANN) with the particle swarm optimization (PSO) algorithm, namely ANN-PSO, to address the size distribution issue across the structure. The design variables included the dimensions of the columns located in each layer of the layout. The results demonstrate that the ANN-PSO algorithm optimizes the cross-sectional area of columns with significant variations. The coefficients of the torsion inequality rule in the optimized solution closely approach the minimum values. The dimensions and orientations of the optimized columns slightly differ from the pre-optimized scheme. In the optimized scheme, the coefficients of the torsional irregularity in the Y-direction meet the requirements, preventing any torsional irregularities from occurring. The research presented an effective method, including an innovative combination of ANN-PSO and the finite element method (FEM), for designing RC structures. The findings of the research provided a practical solution to fulfill torsional regularity criteria, indicating the proposed approach is an effective method for the economical and safe design of RC structures in earthquake-prone areas. The outcomes of the present study highlighted the innovative framework to achieve optimal and safe designs for irregular RC structures while minimizing torsional damage during earthquakes.

This study addressed the scarcity of NH3 measurements in urban Europe and the diverse monitoring protocols, hindering direct data comparison. Sixty-nine datasets from Finland, France, Italy, Spain, and the UK across various site types, including industrial (IND, 8), traffic (TR, 12), urban (UB, 22), suburban (SUB, 12), and regional background (RB, 15), are analyzed to this study. Among these, 26 sites provided 5, or more, years of data for time series analysis. Despite varied protocols, necessitating future harmonization, the average NH3 concentration across sites reached 8.0 ± 8.9 μg/m3. Excluding farming/agricultural hotspots (FAHs), IND and TR sites had the highest concentrations (4.7 ± 3.2 and 4.5 ± 1.0 μg/m3), followed by UB, SUB, and RB sites (3.3 ± 1.5, 2.7 ± 1.3, and 1.0 ± 0.3 μg/m3, respectively) indicating that industrial, traffic, and other urban sources were primary contributors to NH3 outside FAH regions. When referring exclusively to the FAHs, concentrations ranged from 10.0 ± 2.3 to 15.6 ± 17.2 μg/m3, with the highest concentrations being reached in RB sites close to the farming and agricultural sources, and that, on average for FAHs there is a decreasing NH3 concentration gradient towards the city. Time trends showed that over half of the sites (18/26) observed statistically significant trends. Approximately 50 % of UB and TR sites showed a decreasing trend, while 30 % an increasing one. Meta-analysis revealed a small insignificant decreasing trend for non-FAH RB sites. In FAHs, there was a significant upward trend at a rate of 3.51[0.45,6.57]%/yr. Seasonal patterns of NH3 concentrations varied, with urban areas experiencing fluctuations influenced by surrounding emissions, particularly in FAHs. Diel variation showed differing patterns at urban monitoring sites, all with higher daytime concentrations, but with variations in peak times depending on major emission sources and meteorological patterns. These results offer valuable insights into the spatio-temporal patterns of gas-phase NH3 concentrations in urban Europe, contributing to future efforts in benchmarking NH3 pollution control in urban areas.

Summary: DNA tweezers, with their elegant simplicity and flexibility, have been pivotal in biosensing and DNA computing. However, conventional tweezers are confined to a binary transformation pre/post target signal recognition, limiting them to presence/absence judgments. This study introduces bubble DNA tweezers (BDT), capable of three distinct conformations based on variable target signal ratios. In contrast to traditional compact tweezers, BDT features a looser structure centered around a non-complementary bubble domain located between the tweezer arms' connecting axis and target signal recognition jaws. This bubble triggers toehold-free DNA strand displacement, leading to three conformational changes at different target signal concentrations. BDT detects presence/absence and true concentration with remarkable specificity and sensitivity. This adaptability is not confined to ideal scenarios, proving valuable in complex, noisy environments. Our method facilitates target DNA/miRNA signal quantification within a specific length range, promising applications in clinical research and environmental detection, while inspiring future biological assay innovations.

Abstract Polyesters with both cyclic topology and chemical recyclability are attractive. Here, the alternating copolymerization of cyclic anhydride and o‐phthalaldehyde to synthesize a series of cyclic and recyclable polyesters are reported for the first time. Besides readily available monomers, the copolymerization is carried out at 25 °C, uses common Lewis/Brønsted acids as catalysts, and achieves high yields within 1 h. The resulting polyesters possess well‐defined alternating sequences, high‐purity cyclic topology, and tunable structures using distinct two monomer sets. Of interest, the copolymerization manifests obvious chemical reversibility as revealed by kinetic and thermodynamic studies, making the unprecedented polyesters easy to recycle to their distinct two monomers in a closed loop at high temperatures. This work furnishes a facile and efficient method to synthesize cyclic polyesters with closed‐loop recyclability.

Objective: The progression of brain-computer interfaces (BCIs) has been propelled by breakthroughs in neuroscience, signal processing, and machine learning, marking it as a dynamic field of study over the past few decades. Nevertheless, the nonlinear and non-stationary characteristics of steady-state visual evoked potentials (SSVEPs), coupled with the incongruity between frequently employed linear techniques and nonlinear signal attributes, resulted in the subpar performance of mainstream non-training algorithms like canonical correlation analysis (CCA), multivariate synchronization index (MSI), and filter bank CCA (FBCCA) in short-term SSVEP detection. Methods: To tackle this problem, the novel fusions of common filter bank analysis, CCA dimensionality reduction methods, USSR models, and MSI recognition models are used in SSVEP signal recognition. Results: Unlike conventional linear techniques such as CCA, MSI, and FBCCA, the filter bank second-order underdamped stochastic resonance (FBUSSR) analysis demonstrates superior efficacy in the detection of short-term high-speed SSVEPs. Conclusion: This research enlists 32 subjects and uses a public dataset to assess the proposed approach, and the experimental outcomes indicate that the non-training method can attain greater recognition precision and stability. Furthermore, under the conditions of the newly proposed fusion method and light stimulation, the USSR model exhibits the most optimal enhancement effect. Significance: The findings of this study underscore the expansive potential for the application of BCI systems in the realm of neuroscience and signal processing.

Abstract Our society is pursuing chemically recyclable polymers to accelerate the green revolution in plastics. Here, we develop a recyclable polyester library from the alternating copolymerization of aldehyde and cyclic anhydride. Although these two monomer sets have little or no thermodynamic driving force for homopolymerization, their copolymerization demonstrates the unexpected alternating characteristics. In addition to readily available monomers, the method is performed under mild conditions, uses common Lewis/Brønsted acids as catalysts, achieves the facile tuning of polyester structure using two distinct monomer sets, and yields 60 polyesters. Interestingly, the copolymerization exhibits the chemical reversibility attributed to its relatively low enthalpy, which makes the resulting polyesters perform closed-loop recycling to monomers at high temperatures. This study provides a modular, efficient, and facile synthesis of recyclable polyesters using sustainable monomers.

Abstract Background Histone methyltransferases are crucial regulators in non‐small cell lung cancer (NSCLC) development. This study explored the mechanism of histone methyltransferase SET domain containing 1A (SETD1A)‐mediated H3K4me2 methylation in NSCLC cell ferroptosis and provides novel targets for NSCLC treatment. Methods Upon downregulation of SETD1A in NSCLC cell lines, cell proliferation potential, malondialdehyde (MDA), superoxide dismutase (SOD) and glutathione (GSH) activities, iron content, and SETD1A, long noncoding RNA HOXC cluster antisense RNA 3 (lncRNA HOXC‐AS3), E1A binding protein p300 (EP300), glutathione peroxidase 4 (GPX4) expressions were determined via cell counting kit‐8, ELISA, iron assay kits, RT‐qPCR, and western blot. Enrichment levels of SETD1A and H3K4me3 in the HOXC‐AS3 promotor were measured via chromatin immunoprecipitation, and the binding of HOXC‐AS3 and EP300 was analyzed via RNA immunoprecipitation. Rescue experiments were performed to confirm their roles in NSCLC cell ferroptosis. Xenograft tumor models were established to validate the role of SETD1A in vivo. Results SETD1A, H3K4me3, HOXC‐AS3, and EP300 were highly‐expressed in NSCLC cells. Silencing SETD1A inhibited NSCLC cell proliferation, increased MDA and iron levels, and decreased SOD, GSH, and GPX4 levels. SETD1A downregulation reduced H3K4me3 level, HOXC‐AS3 expression, the binding of HOXC‐AS3 to EP300, and EP300 stability. Overexpression of HOXC‐AS3 or EP300 reversed the promotion of silencing SETD1A on NSCLC cell ferroptosis. Silencing SETD1A reduced tumor volume and weight and positive rate of ki67 and increased ferroptosis through the HOXC‐AS3/EP300 axis. Conclusion SETD1A‐mediated H3K4me2 methylation promoted HOXC‐AS3 expression, binding of HOXC‐AS3 to EP300, and EP300 stability, thereby suppressing NSCLC cell ferroptosis.

Abstract Triple-negative breast cancer (TNBC) is a relatively aggressive breast cancer subtype due to tumor relapse, drug resistance, and multi-organ metastatic properties. Identifying reliable biomarkers to predict prognosis and precisely guide TNBC immunotherapy is still an unmet clinical need. To address this issue, we successfully constructed a novel 25 machine learning (ML) algorithms-based immune infiltrating cell (IIC) associated signature of TNBC (MLIIC), achieved by multiple transcriptome data of purified immune cells, TNBC cell lines, and TNBC entities. The TSI index was employed to determine IIC-RNAs that were accompanied by an expression pattern of upregulation in immune cells and downregulation in TNBC cells. LassoLR, Boruta, Xgboost, SVM, RF, and Pamr were utilized for further obtaining the optimal IIC-RNAs. Following univariate Cox regression analysis, LassoCox, CoxBoost, and RSF were utilized for the dimensionality reduction of IIC-RNAs from a prognostic perspective. RSF, Ranger, ObliqueRSF, Rpart, CoxPH, SurvivalSVM, CoxBoost, GlmBoost, SuperPC, StepwiseCox, Enet, LassoCox, CForest, Akritas, BlackBoost, PlsRcox, SurvReg, GBM, and CTree were used for determining the most potent MLIIC signature. Consequently, this MLIIC signature was correlated significantly with survival status validated by four independent TNBC cohorts. Also, the MLIIC signature had a superior predictive capability for TNBC prognosis, compared with 148 previously reported signatures. In addition, MLIIC signature scores developed by immunofluorescent staining of tissue arrays from TNBC patients showed a substantial prognostic value. In TNBC immunotherapy, the low MLIIC profile demonstrated significant immune-responsive efficacy in a dataset of multiple cancer types. MLIIC signature could also predict m6A epigenetic regulation which controls T cell homeostasis. Therefore, this well-established MLIIC signature is a robust predictive indicator for TNBC prognosis and the benefit of immunotherapy, thus providing an efficient tool for combating TNBC.

Abstract Ethylene plays essential roles in rice growth, development and stress adaptation. Translational control of ethylene signaling remains unclear in rice. Here, through analysis of an ethylene-response mutant mhz9, we identified a glycine-tyrosine-phenylalanine (GYF) domain protein MHZ9, which positively regulates ethylene signaling at translational level in rice. MHZ9 is localized in RNA processing bodies. The C-terminal domain of MHZ9 interacts with OsEIN2, a central regulator of rice ethylene signaling, and the N-terminal domain directly binds to the OsEBF1/2 mRNAs for translational inhibition, allowing accumulation of transcription factor OsEIL1 to activate the downstream signaling. RNA-IP seq and CLIP-seq analyses reveal that MHZ9 associates with hundreds of RNAs. Ribo-seq analysis indicates that MHZ9 is required for the regulation of ~ 90% of genes translationally affected by ethylene. Our study identifies a translational regulator MHZ9, which mediates translational regulation of genes in response to ethylene, facilitating stress adaptation and trait improvement in rice.

Objective: To develop a novel diagnostic modality to identify and diagnose stroke in daily life scenarios for improving the therapeutic effects and prognoses of patients. Methods: In this study, 16 stroke patients and 24 age-matched healthy participants as controls were recruited for comparative analysis. Leveraging a portable eye-tracking device and integrating traditional Chinese medicine theory with modern color psychology principles, we recorded the eye movement signals and calculated eye movement features. Meanwhile, the stroke recognition models based on eye movement features were further trained by using random forest (RF), k-nearest neighbors (KNN), decision tree (DT), gradient boosting classifier (GBC), XGBoost, and CatBoost. Results: The stroke group and the healthy group showed significant differences in some eye movement features (P

Recently, due to physical aging, diseases, accidents, and other factors, the population with lower limb disabilities has been increasing, and there is consequently a growing demand for wheelchair products. Modern product design tends to be more intelligent and multi-functional than in the past, with the popularization of intelligent concepts. This supports the design of a new, fully functional, intelligent wheelchair that can assist people with lower limb disabilities in their day-to-day life. Based on the UCD (user-centered design) concept, this study focused on the needs of people with lower limb disabilities. Accordingly, the demand for different functions of intelligent wheelchair products was studied through a questionnaire survey, interview survey, literature review, expert consultation, etc., and the function and appearance of the intelligent wheelchair were then defined. A brain–machine interface system was developed for controlling the motion of the intelligent wheelchair, catering to the needs of disabled individuals. Furthermore, ergonomics theory was used as a guide to determine the size of the intelligent wheelchair seat, and eventually, a new intelligent wheelchair with the features of climbing stairs, posture adjustment, seat elevation, easy interaction, etc., was developed. This paper provides a reference for the design upgrade of the subsequently developed intelligent wheelchair products.

Road traffic transportation has flourished in the process of urbanization due to its advantages, but concurrently it generates harmful environmental vibrations. This vibration issue becomes particularly crucial in production workshops housing precision instruments. However, limited research has been undertaken on this matter. This study aimed to investigate the influence of road traffic-induced vibration on micro-vibrations within a workshop housing precision instruments. A field test was conducted to assess the vibration levels originating from both machinery operation and vehicular traffic. The results indicated that ground-borne vibrations caused by road vehicles decrease with increasing propagation distance, peaking around 10 Hz. Machinery operation vibrations were primarily concentrated above 20 Hz, while vehicular traffic vibrations were more prominent below 20 Hz. Notably, the passage of heavy trucks significantly impacted both ground and workshop vibrations, with vertical vibrations being particularly significant. Within the workshop, the second floor experienced higher vibrations above 20 Hz due to the presence of installed instruments. Importantly, the micro-vibration levels on both floors exceeded the VC-C limit (12.5 µm/s), highlighting the need to account for road traffic and machinery vibrations in workshop design. These data can be utilized to validate numerical models for predicting road traffic-induced vibrations, aiding in vibration assessment during road planning and design.

To address the dilemma of the stiffness and toughness properties of high-density polyethylene (HDPE) composites, titanate coupling agent-treated CaCO3 nanoparticles (nano-CaCO3) and ethylene–octene copolymer (POE) were utilized to blend with HDPE to prepare ternary nanocomposites via a two-sequence-step process. Meanwhile, a one-step process was also studied as a control. The obtained ternary nanocomposites were characterized by scanning electron microscopy (SEM), Advanced Rheometrics Expansion System (ARES), Dynamic Mechanical Analysis (DMA), wide-angle X-ray diffraction analysis (WXRD), and mechanical test. The SEM results showed one or two CaCO3 nanoparticles were well-encapsulated by POE and were uniformly dispersed into the HDPE matrix to form a core–shell structure of 100–200 nm in size by the two-step process, while CaCO3 nanoparticles were aggregated in the HDPE matrix by the one-step method. The result of the XRD showed that the nano-CaCO3 particle played a role in promoting crystallization in HDPE nanocomposites. Mechanical tests showed that the synergistic effect of both the POE elastomer and CaCO3 nanoparticles should account for the balanced performance of the ternary composites. In comparison with neat HDPE, the notched impact toughness of the ternary nanocomposites of HDPE/POE/nano-CaCO3 was significantly increased. In addition, the core–shell structure absorbed the fracture impact energy and prevent further propagation of micro-cracks, thus obtaining a higher notched Izod impact strength.

Three seismic stations in Chongqing area have been reconstructed. And the type of station base is changed from deep pit observation to surface observation. The PSD and PDF of the three stations before and after reconstruction were calculated respectively, and the noise power spectrum is used to average the noise curve to evaluate the background noise variation of the three stations. The calculation results show that, the environmental noise level of the three reconstructed stations still increased, especially for frequency bands above 2 Hz. The maximum increase of PSD is 9 dB at YUM station, 10 dB at LIJ station, and 4 dB at SHG station. But the overall environmental noise level between 1—20 Hz bands of the three stations still meets the requirements of the observation specifications. However, after changing the observation mode of the station base, the components of the noise signal received by the station change significantly, especially the human activity related noise. So when we carry out the construction and reconstruction of seismic stations, it is necessary to carefully change the observation mode of the station base.

Abstract Vicarious traumatization (VT), a negative reaction to witnessing others’ trauma, has been experienced by some people during the COVID-19 pandemic, and can lead to mental health problems. This study aimed to identify functional brain markers of COVID-specific VT and explore the psychological mechanism underlying the brain-VT link. One hundred healthy participants underwent resting-state functional magnetic resonance imaging before the pandemic (October 2019–January 2020) and completed VT measurement during the pandemic (February–April 2020). Whole-brain correlation analysis based on global functional connectivity density (FCD) mapping revealed that VT was negatively correlated with FCD in the right inferior temporal gyrus (ITG) (i.e., the lower FCD in ITG, the worse the VT), identified by mapping onto known large-scale networks as part of the default-mode network (DMN). Resting-state functional connectivity (RSFC) analysis using ITG as seed found that VT was predicted by lower functional connectivity between ITG and other DMN regions including left medial prefrontal cortex, left orbitofrontal cortex, right superior frontal gyrus, right inferior parietal lobule and bilateral precuneus (i.e., the lower the ITG-DMN connectivity, the worse the VT). Mediation analyses suggested that psychological resilience served as a mediator in these associations of ITG FCD and ITG-DMN RSFC with VT. Our results provide novel evidence on the brain basis of VT and emphasize psychological resilience as an important link from DMN functional connectivity to COVID-specific-VT. This may facilitate public health interventions by helping identify individuals at risk of stress- and trauma-related psychopathologies.

Abstract Background The causal role of high-risk Human papillomavirus (HR-HPV) in the pathogenesis of anogenital cancers is well established. In contrast, information on HR-HPV distribution of continuous anatomic sites within the female genital tract is limited, and the impact of sample type on the clinical performance in HPV-based cervical cancer screening warrants investigation. Methods A total of 2,646 Chinese women were enrolled in the study from May 2006 to April 2007. We analyzed the infection features by infection status and pathological diagnoses of 489 women with complete HR-HPV type and viral load data on the cervix, upper vagina, lower vagina, and perineum samples. Additionally, we assessed the clinical performance for detecting high-grade cervical intraepithelial neoplasia of grade two or worse (≥ CIN2) among these four types of samples. Results HR-HPV positivity rate was lower in the cervix (51.53%) and perineum (55.83%), higher in the upper (65.64%) and lower vagina (64.42%), and increased with the severity of cervical histological lesions (all P

Abstract In deep coal mining, the high temperature and humidity environment are one of the main disasters threatening workers and equipment. To predict the temperature and humidity of airflow in the airway accurately, this study establishes a numerical calculation model of the surrounding rock temperature, airflow temperature, and humidity under the conditions of considering the moisture evaporation and heat absorption of the airway wall, the condensation and heat release of supersaturated water vapor in the airflow, and the influence of air compression or expansion. Combined with the two‐dimensional (2D) heat conduction model (considering the influence of the axial surrounding rock heat conduction of the airway), the axial strip partial moisture calculation model of the airway is proposed, and then the uniform moist wall model and the axial strip partial moist wall model are established. The influence of different parameters on the temperature and humidity of airflow is discussed by analyzing the results of numerical simulation of the uniform wet surface model (UWSM) and partly wet surface model (PWSM) of the airway wall. The results show that the surrounding rock temperature, especially the temperature distribution of the airway wall, calculated by using the 2D heat conduction model under the local humid airway conditions, is more realistic. The increment of airflow temperature decreases with the increase of wet area ratio, airflow temperature at the entrance and airway radius, and increases with relative humidity at the entrance. The calculation accuracy of temperature and humidity prediction for large ventilation networks can be further improved by using the equivalent humidity of the UWSM to replace the correction coefficient of the wet area ratio of the PWSM.

Abstract Most of the shape classification methods are based on a single closed contour. However, practical shapes always have complex contours, for example, a combination of multiple open contours. How to accurately identify complex shapes is an unsolved problem. In this research, a novel method is proposed to classify complex shapes. The proposed method firstly encodes a complex shape to an angle code and a sparsity code, then input these codes to a 1‐D CNN for extracting features and classification. Experiments on two datasets show this novel method is superior in terms of classification accuracy. These two datasets are practical shape dataset collected by this paper on internet and MPEG‐7 CE‐1 Part B. The proposed method achieves higher classification accuracy than compared methods. In order to show the performance of the proposed method on each class, the accuracy on each class is analyzed. Ablation experiment is conducted to show the contribution of each module in the network. The result shows that each module is meaningful in the network, because without any module the accuracy drops.

Fluorescence imaging through the second near-infrared window (NIR-II,1000–1700 nm) allows in-depth imaging. However, current imaging systems use wide-field illumination and can only provide low-contrast 2D information, without depth resolution. Here, we systematically apply a light-sheet illumination, a time-gated detection, and a deep-learning algorithm to yield high-contrast high-resolution volumetric images. To achieve a large FoV (field of view) and minimize the scattering effect, we generate a light sheet as thin as 100.5 μm with a Rayleigh length of 8 mm to yield an axial resolution of 220 µm. To further suppress the background, we time-gate to only detect long lifetime luminescence achieving a high contrast of up to 0.45 Ιcontrast. To enhance the resolution, we develop an algorithm based on profile protrusions detection and a deep neural network and distinguish vasculature from a low-contrast area of 0.07 Ιcontrast to resolve the 100 μm small vessels. The system can rapidly scan a volume of view of 75 × 55 × 20 mm3 and collect 750 images within 6 mins. By adding a scattering-based modality to acquire the 3D surface profile of the mice skin, we reveal the whole volumetric vasculature network with clear depth resolution within more than 1 mm from the skin. High-contrast large-scale 3D animal imaging helps us expand a new dimension in NIR-II imaging.