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Abstract Background Fritillaria ussuriensis is an endangered medicinal plant known for its notable therapeutic properties. Unfortunately, its population has drastically declined due to the destruction of forest habitats. Thus, effectively protecting F. ussuriensis from extinction poses a significant challenge. A profound understanding of its genetic foundation is crucial. To date, research on the complete mitochondrial genome of F. ussuriensis has not yet been reported. Results The complete mitochondrial genome of F. ussuriensis was sequenced and assembled by integrating PacBio and Illumina sequencing technologies, revealing 13 circular chromosomes totaling 737,569 bp with an average GC content of 45.41%. A total of 55 genes were annotated in this mitogenome, including 2 rRNA genes, 12 tRNA genes, and 41 PCGs. The mitochondrial genome of F. ussuriensis contained 192 SSRs and 4,027 dispersed repeats. In the PCGs of F. ussuriensis mitogenome, 90.00% of the RSCU values exceeding 1 exhibited a preference for A-ended or U-ended codons. In addition, 505 RNA editing sites were predicted across these PCGs. Selective pressure analysis suggested negative selection on most PCGs to preserve mitochondrial functionality, as the notable exception of the gene nad3 showed positive selection. Comparison between the mitochondrial and chloroplast genomes of F. ussuriensis revealed 20 homologous fragments totaling 8,954 bp. Nucleotide diversity analysis revealed the variation among genes, and gene atp9 was the most notable. Despite the conservation of GC content, mitogenome sizes varied significantly among six closely related species, and colinear analysis confirmed the lack of conservation in their genomic structures. Phylogenetic analysis indicated a close relationship between F. ussuriensis and Lilium tsingtauense. Conclusions In this study, we sequenced and annotated the mitogenome of F. ussuriensis and compared it with the mitogenomes of other closely related species. In addition to genomic features and evolutionary position, this study also provides valuable genomic resources to further understand and utilize this medicinal plant.

Objective: Jinbei oral liquid (JBOL), which is derived from a traditional hospital preparation, is frequently utilized to treat idiopathic pulmonary fibrosis (IPF) and has shown efficacy in clinical therapy. However, there are now several obstacles facing the mechanism inquiry, including target proteins, active components, and the binding affinity between crucial compounds and target proteins. To gain additional insight into the mechanisms underlying JBOL in anti-IPF, this study used bioinformation technologies, including network pharmacology, molecular docking, and molecular dynamic simulation, with a substantial amount of data based on realistic constituents. Methods: Using network pharmacology, we loaded 118 realistic compounds into the SwissTargetPrediction and SwissADME databases and screened the active compounds and target proteins. IPF-related targets were collected from the OMIM, DisGeNET, and GeneCards databases, and the network of IPF-active constituents was built with Cytoscape 3.10.1. The GO and KEGG pathway enrichment analyses were carried out using Metascape, and the protein-protein interaction (PPI) network was constructed to screen the key targets with the STRING database. Finally, the reciprocal affinity between the active molecules and the crucial targets was assessed through the use of molecular docking and molecular dynamics simulation. Results: A total of 122 targets and 34 tested active compounds were summarized in this investigation. Among these, kaempferol, apigenin, baicalein were present in high degree. PPI networks topological analysis identified eight key target proteins. AGE-RAGE, EGFR, and PI3K-Akt signaling pathways were found to be regulated during the phases of cell senescence, inflammatory response, autophagy, and immunological response in anti-IPF of JBOL. It was verified by molecular docking and molecular dynamics simulation that the combining way and binding energy between active ingredients and selected targets. Conclusions: This work forecasts the prospective core ingredients, targets, and signal pathways of JBOL in anti-IPF, which has confirmed the multiple targets and pathways of JBOL in anti-IPF and provided the first comprehensive assessment with bioinformatic approaches. With empirical backing and an innovative approach to the molecular mechanism, JBOL is being considered as a potential new medication.

Our previous study using 41 tree rings of one Abies alba Mill. disc indicated that the superellipse equation can accurately fit its tree-ring shape. This study further used the superellipse equation (xan+yβn=1 ) to model the geometries of 1090 tree rings of A. alba discs collected from five sites in Denmark. The adjusted root-mean-square-error (RMSEadj) was calculated to assess the goodness of fit between observed and predicted tree-ring boundaries. The results showed that RMSEadj ranged between 0.0038 and 0.0591, with a mean value of 0.0141. This verified that the superellipse equation sufficiently describes the A. alba tree-ring shape. In the polar coordinate system, the superellipse equation can be expressed as r=a(cosφn+sinφ/kn)−1/n. Where r and φ are the polar radius and polar angle, respectively. k=β/a, where a and β are the major and minor semi-axes of the superellipse. The mean value of k was 0.95, 94% of tree rings had k-values between 0.90 and 1.00, and only 67 tree rings had k-values between 0.71 and 0.90. n-value ranged from 1.62 to 2.81, with an average value of 2.04. 59% of the tree rings had n-values between 1.90 and 2.10, and 62% showed n-values greater than 2.0. This means that most tree rings are a hyperellipse approached to an ellipse. Sites with different soil moisture conditions influenced the size but not the shape of tree rings. This study verified that the tree-ring shape of A. alba tends to be bilaterally symmetric and hyperellipse approached ellipse. Its variation was reflected more in inter-annual differences in k- and n-values.

A viable pathway towards achieving shared prosperity is made possible by the growth of tourism, which encourages the movement of urban and rural elements. This harmonious alignment of tourism development and urban–rural integration also helps to narrow the gap between urban and rural areas. This study uses a set of panel regression models to investigate whether tourism growth promotes urban–rural integration within 41 cities in the Yangtze River Delta Region of China from 2010 to 2020. The findings show that the effect of tourism development on urban–rural integration is significantly positive, displaying significant heterogeneity across various times and city sizes. Furthermore, tourism development exhibits a threshold effect and city-type heterogeneity concerning urban–rural integration. The effect demonstrates significant continuous growth along with the expansion of economic growth. However, the impact of tourism development on urban–rural integration demonstrates a distinct promotional threshold effect, and its positive effect appears to be weakened.

In this study, the co-combustion characteristics of coal and biomass blends (20, 40, 60, 80, and 100 wt%) were investigated by thermogravimetric analysis. All the samples were operated under an oxidative atmosphere, with a heating rate of 20 C/min. The reaction stages, ignition and burnout temperature, maximum weight loss rate, and different combustion indices were determined. When the percentage of biomass in the blends was increased, the maximum mass loss rate was enhanced in the second region, and the ignition and burnout temperature was lowered, indicating the higher reactivity and better combustion performance of the samples. The comprehensive performance index presented an N shape with the increasing biomass blending ratio. Based on various combustion indices, 20% was an optimum percentage for the co-utilization of coal-biomass blends. A significant promoting interaction was observed between corn straw and rice straw blends, while inhibiting effects occurred between rice husk and coal. The kinetic parameters of the blends were evaluated by the Coats and Redfern method using the nth-order reaction model. The value of activation energy and the pre-exponential factor increased with the decreasing biomass percentage in the blends.

The Chinese water bureaucracy increasingly utilises information and communications technology (ICT) in order to strengthen interaction with the population, which is severely affected by industrial pollution. Government webpages, mailboxes, and online interviews with officers have become prevalent tools for environmental governance, including information disclosure, and a virtual communication forum between the state and its citizens. The present study employs a mixed methods approach with a qualitative emphasis to explore the process of communication and interaction between government agencies and local residents in Dongying, Shandong Province. The results show that information disclosure of pollution data remains far from being transparent, despite the fact that the local government has implemented digital environmental governance, as encouraged by the central Chinese state. Internet technologies empower resource-poor environmental activists in Dongying to strengthen their social network and build communication with the authorities. The application of bureaucratic techniques, however, is key for them to enter the communication interface with government agencies in order to influence political decisions. Results suggest that local cadres tend to send mixed signals to activists and display wariness towards them. They also tend to take preventive measures to keep the situation under control when environmental disputes arise. The proposed communication interface approach sheds a clearer light on the complexity among the emergent ICTs, environmental activism, and digital governance.

The Sanjiangyuan region is located on the Qinghai-Tibetan Plateau in western China and encompasses the headwaters of the Yangtze, Yellow and Mekong rivers. It is also home to 300,000 Tibetan pastoralists. The area is characterized by its significant ecological service, unique culture, and fragile ecosystems, and has undergone a rapid degradation over the past several decades. Traditional Tibetan culture offers alternative knowledge and perspectives that facilitate the environmental conservation throughout the region, but have yet to be recognized or adopted by the Chinese government. Beginning in 2007, the local environmental NGO, Shanshui Conservation Center, has initiated a journey to bridge Tibetan communities with the outside scientific community, mainstream society and policy-makers with the aim of advocating integrating traditional Tibetan practices in conservation actions in the Sanjiangyuan region. Through the conservation concession program initiated and facilitated by Shanshui Conservation Center in collaboration with Conservation International, the Sanjiangyuan nature reserve turned over the management of some reserve lands to local communities after a conservation agreement with clear management plans and monitoring indictors was made between the two parties. The trial and demonstration of the conservation concession program successfully led to the adoption of community-based conservation models in state level conservation policy in 2011. We demonstrate as a bridging organization, Shanshui Conservation Center plays the role of cultural translator to promote the understanding and appreciation of traditional Tibetan culture in conservation in western China.

Abstract The aberrant upregulation of Yes-associated protein 1 (YAP1) in a variety of solid cancers contributes to tumor progression and poor clinical outcomes, rendering it an appealing therapeutic target. However, effective therapies to directly target YAP1 remain challenging. In this study, we perform a high-throughput screening and identify Casein kinase II (CK2) as an uncharacterized upstream regulator of YAP1 turnover in cancer cells of ovarian cancer and several other cancer types. Pharmacological inhibition of Casein kinase II by Silmitasertib or genetic depletion of the catalytic subunit of Casein kinase II (CK2α) markedly destabilizes YAP1 and consequently suppresses its oncogenic functions in vitro and in vivo. Moreover, we reveal that DUB3 as a bona fide deubiquitinase of YAP1, which functionally links CK2 and YAP1 stability in a variety of human cancers. Mechanistically, CK2α directly phosphorylates DUB3 at Thr495, thereby facilitating DUB3-mediated deubiquitination process of YAP1. On the contrary, the loss of Thr495 phosphorylation by the phosphorylation-defective mutant DUB3 T495A, the cancer-related mutant DUB3 D496H and CK2 inhibition failed to deubiquitinate and stabilize YAP1 effectively. Notably, upregulated expressions of CK2α and DUB3 in ovarian cancer positively correlate with YAP1 overexpression. Collectively, our findings demonstrate the functional significance of the CK2α-DUB3 axis in YAP1 stabilization and YAP1-driven tumor progression, highlighting that strategies to target this axis might be of benefit in the clinical management of ovarian cancer and several other lethal cancers with aberrantly upregulated YAP1.

Abstract The welding of titanium alloys is an important topic in today’s industrial field, and the interaction between the solder and the base material is crucial for the quality of the welded parts. The structural, elastic, electronic, and thermal properties of Ti-Al-Me (Me = Cu, Fe and Ni) alloys (TAMs) with the face-centered cubic structures were investigated using plane-wave pseudo potential method in the framework of density functional theory. Based on the calculated elastic constants combined with empirical and semi-empirical formulas, physical properties including ductility/brittleness, hardness and anisotropy were calculated. Moreover, thermodynamic information such as entropy, enthalpy, free energy, heat capacity and heat transfer coefficient were calculated. The results showed that TiAlFe2 had the highest thermal conductivity coefficient, and the heat capacities of all phases gradually approached the Dulong-Petit limit at high temperatures, while they conformed to the Debye’s temperature law at low temperatures. Furthermore, the electronic structure calculation results indicate that all compounds are metallic and the d orbital plays an important role in the hybridization process. These calculation results are of great practical importance for understanding the basic physical and chemical properties of TAMs, clarifying their applications in the welding of aerospace and aircraft structural components to make sensible material selection.

Abstract Background Smoking has been identified as a standalone risk factor for coronary heart disease (CHD) and myocardial infarction (MI), but the precise underlying mechanisms remain incompletely elucidated. Results In this study, we conducted a two-sample Mendelian randomization analysis to examine the impact of smoking behaviors (including smoking initiation, age of smoking initiation, cigarettes per day, and smoking cessation) and smoking-related DNA methylation at CpG sites on CHD and MI based on the UK Biobank dataset. Additionally, we included the FinnGen and Biobank Japan datasets as replications and performed a meta-analysis to combine the results from different data sources. We further validated our results using genetic colocalization analysis. In genomic analysis, we provided compelling evidence on the association between genetically predicted smoking initiation and increased susceptibility to CHD and MI. In epigenetic analysis, we identified 11 smoking-related CpG sites linked to CHD risk and 10 smoking-related CpG sites associated with the risk of MI based on the UK Biobank dataset. Subsequently, some of these CpG sites were further replicated using the FinnGen or BBJ datasets. Ultimately, a meta-analysis was conducted to integrate findings from various data sources (3 for CHD, and 2 for MI), revealing that 7 of 11 CpG sites were linked to CHD risk; whereas, 7 of 10 CpG sites were associated with MI risk. Furthermore, we performed genetic colocalization analysis and found that cg19744173 (FBLN7), cg00395063 (ARHGEF12), and cg16822035 (MCF2L) exhibited robust evidence of colocalization with coronary heart disease; whereas, cg19529732 (DIABLO), cg26405020 (FES), and cg08940075 (CNN3) demonstrated strong colocalization evidence with the risk of myocardial infarction. Conclusions Our research offers a novel insight into the impact of smoking on the susceptibility to CHD and MI through the lens of epigenetic DNA methylation.

Summary: The population history of the northern coastal Chinese is largely unknown due to the lack of ancient human genomes from the Neolithic to historical periods. In this study, we reported 14 newly generated ancient genomes from Linzi, one of China’s densely populated and economically prosperous cities from the Zhou to Han Dynasties. The ancient samples in this study were dated to the Warring States period to the Eastern Han Dynasty (∼2,000 BP). We found the samples derived all their ancestry from Late Bronze Age to Iron Age Middle Yellow River farmers rather than local Neolithic populations. They were genetically homogeneous with present-day Han Chinese of Shandong, suggesting 2,000 years of genetic stability. Our results highlight the role of the eastward migration of Yellow River farmers in the Central Plain to northern coastal China in forming the present-day genetic structure of Han Chinese.

Objectives Identifying the specific biomarkers and molecular signatures of MM might provide novel evidence for MM prognosis and targeted therapy.Methods Bioinformatic analyses were performed through GEO and TCGA datasets. The differential expression of HIST1H2BH in MM sample was validated by the qRT-PCR. And the CCK-8 assay was performed to detect the proliferation activity of HIST1H2BH on MM cell lines.Results A total of 793 DEGs were identified between bone marrow plasma cells from newly diagnosed myeloma and normal donors in GSE6477. Among them, four vital genes (HIST1H2AC, HIST1H2BH, CCND1 and TCF7L2) modeling were constructed. The increased HIST1H2BH expression was correlated with worse survival of MM based on TCGA datasets. The transcriptional expression of HIST1H2BH was significantly up-regulated in primary MM patients. And knockdown HIST1H2BH decreased the proliferation of MM cell lines.Conclusions We have identified up-regulated HIST1H2BH in MM patients associated with poor prognosis using integrated bioinformatical methods.

Objective: Periventricular-intraventricular hemorrhage is the most common type of intracranial bleeding in newborns, especially in the first 3 days after birth. Severe periventricular-intraventricular hemorrhage is considered a progression from mild periventricular-intraventricular hemorrhage and is often closely associated with severe neurological sequelae. However, no specific indicators are available to predict the progression from mild to severe periventricular-intraventricular in early admission. This study aims to establish an early diagnostic prediction model for severe PIVH. Method: This study was a retrospective cohort study with data collected from the MIMIC-III (v1.4) database. Laboratory and clinical data collected within the first 24 h of NICU admission have been used as variables for both univariate and multivariate logistic regression analyses to construct a nomogram-based early prediction model for severe periventricular-intraventricular hemorrhage and subsequently validated. Results: A predictive model was established and represented by a nomogram, it comprised three variables: output, lowest platelet count and use of vasoactive drugs within 24 h of NICU admission. The model's predictive performance showed by the calculated area under the curve was 0.792, indicating good discriminatory power. The calibration plot demonstrated good calibration between observed and predicted outcomes, and the Hosmer-Lemeshow test showed high consistency (p = 0.990). Internal validation showed the calculated area under a curve of 0.788. Conclusions: This severe PIVH predictive model, established by three easily obtainable indicators within the NICU, demonstrated good predictive ability. It offered a more user-friendly and convenient option for neonatologists.

Abstract Siderophore-dependent iron uptake is a mechanism by which microorganisms scavenge and utilize iron for their survival, growth, and many specialized activities, such as pathogenicity. The siderophore biosynthetic system PubABC in Shewanella can synthesize a series of distinct siderophores, yet how it is regulated in response to iron availability remains largely unexplored. Here, by whole genome screening we identify TCS components histidine kinase (HK) BarA and response regulator (RR) SsoR as positive regulators of siderophore biosynthesis. While BarA partners with UvrY to mediate expression of pubABC post-transcriptionally via the Csr regulatory cascade, SsoR is an atypical orphan RR of the OmpR/PhoB subfamily that activates transcription in a phosphorylation-independent manner. By combining structural analysis and molecular dynamics simulations, we observe conformational changes in OmpR/PhoB-like RRs that illustrate the impact of phosphorylation on dynamic properties, and that SsoR is locked in the ‘phosphorylated’ state found in phosphorylation-dependent counterparts of the same subfamily. Furthermore, we show that iron homeostasis global regulator Fur, in addition to mediating transcription of its own regulon, acts as the sensor of iron starvation to increase SsoR production when needed. Overall, this study delineates an intricate, multi-tiered transcriptional and post-transcriptional regulatory network that governs siderophore biosynthesis.

Abstract The filamentous fungus Trichoderma reesei (teleomorph Hypocrea jecorina, Ascomycota) is a well-known lignocellulolytic enzymes-producing strain in industry. To increase the fermentation titer of lignocellulolytic enzymes, random mutagenesis and rational genetic engineering in T. reesei were carried out since it was initially found in the Solomon Islands during the Second World War. Especially the continuous exploration of the underlying regulatory network during (hemi)cellulase gene expression in the post-genome era provided various strategies to develop an efficient fungal cell factory for these enzymes’ production. Meanwhile, T. reesei emerges competitiveness potential as a filamentous fungal chassis to produce proteins from other species (e.g., human albumin and interferon α-2b, SARS-CoV-2 N antigen) in virtue of the excellent expression and secretion system acquired during the studies about (hemi)cellulase production. However, all the achievements in high yield of (hemi)cellulases are impossible to finish without high-efficiency genetic strategies to analyze the proper functions of those genes involved in (hemi)cellulase gene expression or secretion. Here, we in detail summarize the current strategies employed to investigate gene functions in T. reesei. These strategies are supposed to be beneficial for extending the potential of T. reesei in prospective strain engineering.

This paper proposes a high-sensitivity microstrip differential sensor for measuring the complex permittivity of liquids. The prototype of the differential sensor was formed by cascading two LC resonators on a microstrip transmission line based on stepped impedance. A strong electric field was found to be distributed in the circular patch of the LC resonator; therefore, a cylindrical micropore was set in the center of the circular LC resonator to measure the dielectric sample, which maximized the disturbance of the dielectric sample on the sensor. By optimizing the size of the circular LC resonator, a high-sensitivity sensor circuit was designed and manufactured. The complex permittivity of the test sample was calculated by measuring the transmission coefficient of different molar concentrations of ethanol–water solutions. The experimental results show that the designed differential sensor can accurately measure the complex permittivity of liquid materials with an average sensitivity of 0.76%.

IntroductionEmotional eating not only contributes to physical obesity but also leads to the experience of guilt and shame, exacerbating emotional problems. Increasing physical activity, adopting a balanced diet, and seeking psychological support help improve emotional eating issues in overweight or obese young adults, enhancing overall mental and physical well-being.MethodsThis study investigates the correlation between physical activity, self-identity, social anxiety, and emotional eating among 373 overweight and obese college students aged 18–26 in central China. By utilizing AMOS v.26, a structural equation model was constructed to examine the hypotheses.ResultsThe findings reveal that physical activity significantly influences self-identity and social anxiety, which, in turn, significantly impact emotional eating. Moreover, self-identity and social anxiety serve as mediators in the relationship between physical activity and emotional eating. These results emphasize the role of physical activity in mitigating emotional eating among young individuals struggling with overweight and obesity.DiscussionConsequently, the government and relevant agencies are urged to address the issue of obesity among young adults and provide support for their engagement in physical activity.

IntroductionIn the highly competitive field of sports, impulsive behavior by athletes not only threatens personal and team harmony but also poses significant risks to their careers and public image. Despite these behaviors often becoming the focus of public attention, their underlying causes and prevention strategies remain relatively unknown. This study delves deep into the impact of mindfulness on athletes’ impulsive behavior, revealing the mediating roles of self-reflection and coping effectiveness.MethodsUsing a combination of snowball and convenience sampling, a sample of 403 athletes from high-level sports teams in the Central China region participated in a questionnaire survey. The data were analyzed using Amos v.23 software.ResultsThe findings indicate a positive correlation between mindfulness and coping effectiveness (standardized coefficient = 0.336, p

Abstract Long noncoding RNAs (lncRNAs) in eukaryotic transcripts have long been believed to regulate various aspects of cellular processes, including carcinogenesis. Herein, it is found that lncRNA AFAP1‐AS1 encodes a conserved 90‐amino acid peptide located on mitochondria, named lncRNA AFAP1‐AS1 translated mitochondrial‐localized peptide (ATMLP), and it is not the lncRNA but the peptide that promotes the malignancy of nonsmall cell lung cancer (NSCLC). As the tumor progresses, the serum level of ATMLP increases. NSCLC patients with high levels of ATMLP display poorer prognosis. Translation of ATMLP is controlled by m6A methylation at the 1313 adenine locus of AFAP1‐AS1. Mechanistically, ATMLP binds to the 4‐nitrophenylphosphatase domain and non‐neuronal SNAP25‐like protein homolog 1 (NIPSNAP1) and inhibits its transport from the inner to the outer mitochondrial membrane, which antagonizes the NIPSNAP1‐mediated regulation of cell autolysosome formation. The findings uncover a complex regulatory mechanism of NSCLC malignancy orchestrated by a peptide encoded by a lncRNA. A comprehensive judgment of the application prospects of ATMLP as an early diagnostic biomarker for NSCLC is also made.

Abstract Triple‐negative breast cancer (TNBC) is a highly lethal malignancy with limited therapy options. TWIST1, a key transcriptional factor of epithelial‐mesenchymal transition (EMT), contributes to self‐renewal of cancer stem‐like cells (CSCs), chemo‐resistance, metastasis, and TNBC‐related death. However, the mechanism by which TWIST1 is deregulated in TNBC remains elusive. Here, USP29 is identified as a bona fide deubiquitinase of TWIST1. The deubiquitination of TWIST1 catalyzed by USP29 is required for its stabilization and subsequent EMT and CSC functions in TNBC, thereby conferring chemotherapeutic resistance and metastasis. Furthermore, the results unexpectedly reveal that CDK1 functions as the direct USP29 activator. Mechanistically, CDK1‐mediated phosphorylation of USP29 is essential for its deubiquitinase activity toward TWIST1 and TWIST1 driven‐malignant phenotypes in TNBC, which could be markedly mitigated by the genetic ablation or pharmacological inhibition of CDK1. Moreover, the histological analyses show that CDK1 and USP29 are highly upregulated in TNBC samples, which positively correlate with the expression of TWIST1. Taken together, the findings reveal a previously unrecognized tumor‐promoting function and clinical significance of the CDK1‐USP29 axis through stabilizing TWIST1 and provide the preclinical evidence that targeting this axis is an appealing therapeutic strategy to conquer chemo‐resistance and metastasis in TNBC.

BackgroundImmunohistochemical microvessel density (MVD) is an early indicator of angiogenesis and it could be used to evaluate the therapeutic efficacy of non-small cell lung cancer (NSCLC). We sought to identify the ability of contrast-enhanced ultrasound (CEUS) in evaluating MVD of subpleural NSCLC.MethodsWe prospectively collected CEUS data of NSCLC confirmed by ultrasound-guided transthoracic needle biopsy from October 2019 to February 2021, The MVD of NSCLC counted by CD34-positive vessels of immunohistochemical staining. Microflow enhancement (MFE) of CEUS was divided into “dead wood”, “cotton”, and “vascular” patterns. Pathology subgroup and MVD between different MFE patterns were analyzed, respectively. The arrival time, time to peak, peak intensity (PI), and area under curve (AUC) derivefrom time-intensity curve of CEUS with MVD in NSCLC and its pathological subgroups (adenocarcinoma and squamous cell carcinoma) were subjected to correlation analysis.ResultsA total of 87 patients were included in this study, consisting of 53 cases of adenocarcinoma and 34 cases of squamous cell carcinoma with a mean MVD of 27.8 ± 12.2 mm–1. There was a significant statistical difference in MFE patterns between two pathological subgroups (p < 0.05). Besides, the MVD of “cotton” and “vascular” patterns were significantly higher than that of “dead wood” pattern (both of p < 0.05), whereas there was no significant difference in MVD between “cotton” pattern and “vascular” pattern. PI and AUC of CEUS were positively correlated with the MVD of NSCLC (r = 0.497, p < 0.001, and r = 0.367, p < 0.001, respectively). Besides, PI and AUC of CEUS were positively correlated with the MVD of squamous cell carcinoma (r = 0.802, and r = 0.663, respectively; both of p < 0.001). Only the PI was positively correlated with the MVD of lung adenocarcinoma (r = 0.288, p = 0.037).ConclusionsMFE patterns and quantitative parameters of CEUS had good correlation with MVD of NSCLC, especially in squamous cell carcinoma.

Synthetic aperture radar automatic target recognition (SAR ATR) uses computer processing capabilities to infer the classes of the targets without human intervention. For SAR ATR, deep learning gradually emerges as a powerful tool and achieves promising performance. However, it faces serious challenges of how to deal with incremental recognition scenarios. The existing deep learning-based SAR ATR methods usually predefine the total number of recognition classes. In realistic applications, the new tasks/classes will be added continuously. If all old data are stored and mixed with newly added data to update the model, the storage pressure and time consumption make the application infeasible. In this article, the high plastic error correction incremental learning (HPecIL) is proposed to address the model degradation and plasticity decline in the incremental scenario. Multiple optimal models trained on old tasks are used to correct accumulative errors and alleviate model degradation. Moreover, the sharp data distribution shift due to newly added data can also result in the model underperforming. A class-balanced training batch is constructed to deal with the issue of unbalanced data distribution. To make a tradeoff between model stability and model plasticity, low-effect nodes in the model are removed to boost the efficiency of model update. The proposed HPecIL outperforms the other state-of-the-art methods in incremental recognition scenarios. The experimental results demonstrate the effectiveness of the proposed method.

BackgroundMalignant pleural mesothelioma (MPM) is a highly invasive malignant tumor. Ultrasound guidance has the advantages of real-time, convenience and nonradiative. We sought to identify diagnostic value and its influenced factors of ultrasound-guided percutaneous pleural needle biopsy (US-PPNB) for MPM.MethodsPatients who underwent US-PPNB between March 2014 and March 2020 and were finally diagnosed with MPM were retrospectively analyzed. We retrospectively analyzed the US-PPNBs pathological results of all patients clinically confirmed as MPM, and divided US-PPNBs into correctly and incorrectly diagnosed groups. Patient, thoracic, and biopsy variables that affected diagnostic accuracy were assessed. All variables significant on univariate analyses were subjected to multivariate logistic regression to identify significant predictors of diagnostic accuracy. We derived cutoffs for all significant continuous variables and used the Mantel–Haenszel test to determine whether the diagnostic accuracy of US-PPNB for MPM increased with pleural thickness.ResultsIn total, 49 patients with clinically confirmed MPM underwent US-PPNB; 37 diagnoses were correct and 12 were incorrect (accuracy = 75.5%). The pleura was significantly thicker in the correctly diagnosed group (p

Yongxing Island (about 1.85 km2) is the largest island of the Xisha Islands. It is located in the Western South China Sea, and belongs to the tropical ocean monsoon climate zone. Yongxing island is quite rich in biological resources, for example, plants and birds have been well documented. However, there are limited reports on spider resources in Yongxing Island.A preliminary checklist of spiders of the Yongxing Island is provided here based on a short term study undertaken in January 2008. A total of 23 species belonging to 21 genera and 11 families were recorded from the area, which forms baseline information of spiders of the Yongxing Island. Among these, Onopidae, Pholcidae, Araneidae and Salticidae were found to be dominant in the area. Brignolia parumpunctata (Simon, 1893), Opopaea apicalis (Simon, 1893), Opopaea deserticola Simon, 1891 and Xyphinus baehrae Kranz-Baltensperger, 2014 were first reported from China during the study, for which we provide taxonomic description in this paper.

In this paper, we propose a user-friendly integral inequality to study the coupled parabolic chemotaxis system with singular sensitivity under the Neumann boundary condition. Under a low diffusion rate, the classical solution of this system is uniformly bounded. Our proof replies on the construction of the energy functional containing ∫Ω|v|4v2 with v>0. It is noteworthy that the inequality used in the paper may be applied to study other chemotaxis systems.

The plant hormone auxin plays pivotal roles in many aspects of plant growth and development. The auxin/indole-3-acetic acid (Aux/IAA) gene family encodes short-lived nuclear proteins acting on auxin perception and signaling, but the evolutionary history of this gene family remains to be elucidated. In this study, the Aux/IAA gene family in 17 plant species covering all major lineages of plants is identified and analyzed by using multiple bioinformatics methods. A total of 434 Aux/IAA genes was found among these plant species, and the gene copy number ranges from three (Physcomitrella patens) to 63 (Glycine max). The phylogenetic analysis shows that the canonical Aux/IAA proteins can be generally divided into five major clades, and the origin of Aux/IAA proteins could be traced back to the common ancestor of land plants and green algae. Many truncated Aux/IAA proteins were found, and some of these truncated Aux/IAA proteins may be generated from the C-terminal truncation of auxin response factor (ARF) proteins. Our results indicate that tandem and segmental duplications play dominant roles for the expansion of the Aux/IAA gene family mainly under purifying selection. The putative nuclear localization signals (NLSs) in Aux/IAA proteins are conservative, and two kinds of new primordial bipartite NLSs in P. patens and Selaginella moellendorffii were discovered. Our findings not only give insights into the origin and expansion of the Aux/IAA gene family, but also provide a basis for understanding their functions during the course of evolution. [ABSTRACT FROM AUTHOR]

Pancreatic cancer has a five-year overall survival rate <5%, a situation that has not improved since for 40 years. Diabetes mellitus including type 2 diabetes mellitus (T2D) is a suspected risk factor for the development of pancreatic cancer and nearly 45% of the pancreatic cancer cases are likely to present as new onset diabetes cases; however, the nature of association between T2D and pancreatic cancer is still controversial. In this meta-analysis, we examined the association specifically of T2D with pancreatic cancer and the influence of insulin therapy. PubMed, EMBASE, Scholar, Web of Science and Scopus databases were searched to identify clinical and patient oriented studies that examined the incidence of diabetes in pancreatic cancer patients and vice versa, over the last 10 years. All the authors independently screened the articles, and a collective decision was reached about the studies included in the meta-analysis. Parameters analyzed included, the Incidence of diabetes in pancreatic cancer patients; duration history of T2D in pancreatic cancer patients; influence of insulin therapy in T2D patients on pancreatic cancer incidence. Eleven studies with a total of 14,399 patients, of whom 4,080 were T2D-positive and 9,721 were non-diabetic were included in this meta-analysis. T2D duration history was significantly related to pancreatic cancer incidence and insulin therapy effects. In conclusion, recent-onset T2D is probably a manifestation of pancreatic cancer whereas long-term T2D is likely a risk factor for this cancer. Insulin therapy appears to decrease the incidence of pancreatic cancer. [ABSTRACT FROM AUTHOR]

Abstract Background Osteoarthritis (OA) is a common degenerative disease of synovial joints caused by inflammation. Acteoside (ACT), a major component and lipase inhibitor from the Chinese tea Ligustrum purpurascens kudingcha, has been reported to regulate the inflammation and immune response. The study aims to investigate the effects of ACT on inflammatory responses and joint protection in OA rats. Methods Cell proliferation was examined by MTT and colony formation assay. Apoptosis was analyzed using flow cytometry with Annexin V/PI staining. ELISA was employed to examine the concentration of inflammatory cytokines. OA rat model was established by surgery stimulation. Results ACT treatment significantly inhibited the upregulation of inflammatory cytokines induced by IL-1β in primary chondrocytes, including IL-6, IL-12, TNF-α and IFN-γ. ACT stimulation also enhanced the cell proliferation, while inhibited cell apoptosis in IL-1β-treated chondrocytes. Consistently, ACT treatment led to downregulation of cleaved-caspase-3 and apoptosis regulator Bax, and upregulation of Bcl-2. Furthermore, ACT treatment inhibited IL-1β-induced activation of JAK/STAT pathway. The results were confirmed in surgery-induced OA rat model. Moreover, ACT treatment significantly inhibited synovial inflammation and articular chondrocyte apoptosis in OA rats. Conclusion Our findings indicate that ACT has the potential therapeutic effect on OA through inhibiting the inflammatory responses via inactivating JAK/STAT signaling pathway.

While the detection of offshore ships in synthetic aperture radar (SAR) images has been widely studied, inshore ship detection remains a challenging task. Due to the influence of speckle noise and the high similarity between onshore buildings and inshore ships, the traditional methods are unable to achieve effective detection for inshore ships. To improve the detection performance of inshore ships, we propose a novel saliency enhancement algorithm based on the difference of anisotropic pyramid (DoAP). Considering the limitations of IoU in small-target detection, we design a detection framework based on the proposed Bhattacharyya-like distance (BLD). First, the anisotropic pyramid of the SAR image is constructed by a bilateral filter (BF). Then, the differences between the finest two scales and the coarsest two scales are used to generate the saliency map, which can be used to enhance ship pixels and suppress background clutter. Finally, the BLD is used to replace IoU in label assignment and non-maximum suppression to overcome the limitations of IoU for small-target detection. We embed the DoAP into the BLD-based detection framework to detect inshore ships in large-scale SAR images. The experimental results on the LS-SSDD-v1.0 dataset indicate that the proposed method outperforms the basic state-of-the-art detection methods.

Abstract Background Acinetobacter baumannii is ubiquitous, facultative intracellular, and opportunistic bacterial pathogen. Its unique abilities allow it to survive in a diverse range of environments, including health care settings, leading to nosocomial infections. And its exceptional ability to develop resistance to multiple antibiotics leaves few drug options for treatment. It has been recognized as a leading cause of nosocomial pneumonia and bacteremia over the world. Case presentation In this case, a 73-year-old woman presented with a Neer Group VI proximal humeral fracture. Six hours after a successfully performed hemiarthroplasty, she developed continuous fever. Clinical examination revealed that the vitals were regular. Laboratory and radiographic examinations revealed only elevated procalcitonin levels. Blood culture revealed no bacterial or fungal growth. Cooling treatment and empirical broad-spectrum antibiotic therapy showed no apparent effect. Conclusions We report a postoperative infection caused by Acinetobacter baumannii. The infectious pathogen was identified via molecular DNA sequencing and was initially misidentified as a free-living amoeba species upon microscopic examinations. The patient was mistreated with antiamebic combination therapy. Her symptoms persisted for over 4 months and were eventually followed by her death.

Synthetic aperture radar (SAR) target recognition can provide effective target category information and becomes the key part of SAR image application. Machine learning and deep learning are two main methods of target recognition. Normally, through the massive image features learning, the trained model can be used to infer the possible categories for various new target images, but the overfitting problem caused by limited data samples always makes the trained model unusable. In order to solve this case, the authors introduce a dual-input Siamese convolution neural network to the small samples oriented SAR target recognition. The training method looks like a kind of data enhancement method, but there are some differences between them. In the experiments, only 15 training samples are used to complete a three-class tank classification task. It means each category has just five samples while the number of corresponding testing data is 195. As a result, the recognition accuracy of the authors’ method outperforms the support vector machine, A-ConvNet, and 18-layers ResNet by 31, 13 and 16%, respectively. Siamese network has a good performance in small samples classification and the results prove the validity of the network.

Google Scholar has been a widely used platform for academic performance evaluation and citation analysis. The issue about the mis-configuration of author profiles may seriously damage the reliability of the data, and thus affect the accuracy of analysis. Therefore, it is important to detect the mis-configured author profiles. Dealing with this issue is challenging because the scale of the dataset is large and manual annotation is time-consuming and relatively subjective. In this paper, we first collect a dataset of Google Scholar’s author profiles in the field of computer science and compare the mis-configured author profiles with the reliable ones. Then, we propose an integrated model that utilizes machine learning and node embedding to automatically detect mis-configured author profiles. Additionally, we conduct two application case studies based on the data of Google Scholar, i.e., outstanding scholar searching and university ranking, to demonstrate how the improved dataset after filtering out the mis-configured author profiles will change the results. The two case studies validate the importance and meaningfulness of the detection of mis-configured author profiles.