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The thermal transport properties of Ga _2 O _3 in different phases remain inadequately explored. We employ first-principles calculations and the phonon Boltzmann equation to systematically study the lattice thermal conductivity of β -, α - and κ -Ga _2 O _3 . Our results reveal that κ -Ga _2 O _3 exhibits pronounced phonon anharmonicity due to its complex polyhedral configurations and weak bonding, resulting in significantly lower lattice thermal conductivity compared to β - and α -Ga _2 O _3 . This work provides critical knowledge of the fundamental phonon thermal transport properties of different-phase Ga _2 O _3 , as well as helpful guidance for the thermal design of Ga _2 O _3 -based high-power devices.

Abstract Oral Squamous Cell Carcinoma (OSCC) is the most common malignant cancer affecting oral cavity. Recent studies have demonstrated that Ubiquitin-specific protease 7 (USP7) was upregulated in several types of cancers. USP7 expression was associated with various proto-oncogenes and tumor suppressor genes. However, USP7 expression level and its functional role in OSCC is unclear. In the current study, we showed that USP7 expression in OSCC tissues was generally upregulated compared to normal adjacent tissues by using IHC. Furthermore, statistical analysis uncovered that USP7 expression was positively correlated with Ki-67, MMP2, VEGF in OSCC tissues. Importantly, high USP7 expression was significantly correlated with lymph node metastasis and histological differentiation in OSCC patients. So, our hypothesis is that USP7 plays a tumor-promoting role in OSCC. Knocking down of USP7 in tumor cells not only suppressed HSC3 cells proliferation, migration and invasion, but also promoted cell apoptosis. Moreover, USP7 siRNA blocked the activation of Akt/ERK signaling pathway. In conclusion, data presented here suggests that USP7 promotes the progression of OSCC. USP7 may be used as a new therapeutic target for OSCC diagnosis and treatment.

Arbuscular mycorrhizal fungi (AMF) play vital roles in the growth and development of plants, ecosystem sustainability, and stability in agroecosystem, such as transporting nutrients to host plants, improving soil physical structure, and enhancing the stress resistance of host plants. However, the effects of fertilization on AMF diversity and community in brown soil areas are still unclear. The purpose of this study is to explore changes in AMF diversity and community structures and finding out the factors that influenced the changes after 41 years of fertilization in brown soil. Samples were collected from five treatments of the long-term fertilization experiment in June 2019, including CK (no fertilizer), N (mineral nitrogen fertilizer), NP (mineral nitrogen and phosphate fertilizer), M (pig manure), and MNP (pig manure, mineral nitrogen, and phosphate fertilizer). Illumina HiSeq sequencing was used to determine AMF diversity and community structure. The relationship between AMF communities in soil and roots and environmental factors was analyzed by redundancy analysis. The results showed that the soil nutrient content of manure treatments was generally higher than that of chemical fertilizer treatments and no fertilizer treatment. Long-term fertilization increased AMF spore density, which increased with the increase of soil fertility. The moderate content of soil available phosphorus was beneficial to the colonization of AMF. AMF diversity in soil decreased with soil fertility, but AMF diversity in roots was influenced only by soil nitrate–nitrogen and pH. Glomus was the dominant genus in both soil and root samples. AMF community structure in soil and roots had a different response to long-term fertilization. Application of manure had a greater impact on AMF community structure in soil, whereas application of exogenous phosphate fertilizer had a greater impact on that in roots. Soil ammonium nitrogen, nitrate–nitrogen, total nitrogen, organic carbon, total potassium, and available potassium were the most important factors that influenced taxa of AMF in soil, whereas soil ammonium nitrogen, nitrate–nitrogen, total nitrogen, organic carbon, total potassium, available potassium, available phosphorus, and plant phosphorus and potassium content were the most important factors influencing taxa of AMF in maize roots under long-term fertilization in brown soil.

Recognizing prohibited items in X-ray security checking images automatically based on Convolutional Neural Networks (CNNs) has attracted attention increasingly. However, there are no suitable X-ray security checking image databases to train a reliable CNN model. Therefore, we propose a data augmentation method for X-ray security checking images. First, a lot of new X-ray prohibited item images are generated using the improved Self-Attention Generative Adversarial Network (SAGAN). Next, a Cycle GAN based method is proposed to transform the item natural images into the X-ray images. It can enrich the diversity of the new images, including item shape and pose. Then, we combine the prohibited item images with background images to synthesize the new X-ray security checking images. Finally, two single shot multi-box detector (SSD) models are applied to verify whether the enlarged database has achieved data augmentation. Experimental results show that the performance of SSD model trained by the enlarged database is better than the SSD model trained by the original database. It implies that our method can achieve data augmentation for X-ray security checking images effectively.

ABSTRACTThe seroprevalenc of autoimmune hepatitis (AIH)-related antibodies in patients, particularly Asians, with acute hepatitis E (AHE) is unclear. In this study, we investigated whether acute hepatitis E virus (HEV) infection is associated with the seroprevalence of AIH-related autoantibodies and assessed their impact on the disease characteristics. AIH-related autoantibodies were detected by indirect immunofluorescence in 198 AHE patients and 50 type 1 AIH patients. The positivity rates of against nuclear antigen (ANA) and smooth muscles antibody (SMA) in AHE patients were 37.4% and 22.7%, and the total positivity rate was 50%. Compared to those in AIH patients, the positivity rates of ANA-H and SMA-AA were significantly lower (35.1% vs. 82.1% and 4.4% vs. 88.4%). Female gender and the ALT level, but not immunosuppressive or antiviral drugs, were independently predictive of the presence of AIH-related autoantibodies in AHE patients. Fifty-two patients positive for AIH-related autoantibodies were followed up for 12 months. During this period, 33 of them became negative and 19 remained positive, albeit with significantly decreased titres. In conclusions, the seroprevalence of AIH-related autoantibodies in AHE patients was elevated, particularly in females, but their subspecificities and titres differed from those of type 1 AIH. Acute HEV infection may be related to AIH.Abbreviations: AIH: autoimmune hepatitis; AHE: acute hepatitis E; ANA: against nuclear antigen; SMA: smooth muscles antibody; ANA-H: ANA with homogeneous pattern; SMA-AA: SMA with anti-actin pattern; Anti-LKM1: anti- liver-kidney microsomes-1 antibody; ANCA: anti-neutrophil cytoplasmic antibody; AMA: anti-mitochondrial antibody; Anti-SLA: anti-soluble liver antigen; Anti-LC1: anti-liver cytoplasmic type 1 antibody; pANCA: perinuclear antineutrophil cytoplasmic antibody

Water depth measurement requires the establishment of one or more tidal stations in the survey area for synchronous water level observation, and finally the water depth is estimated to the depth datum. The non-tidal observation measuring has high efficiency and avoids the water level correction error caused by tidal observation in traditional sounding. Therefore, non-tidal observation measuring has become an effective water depth measurement method in offshore and inland water. However, datum conversion in non-tide operation is mostly based on the polynomial fitting method. The accuracy of this method is influenced by the distribution of datum control points, topographic relief and operation ranges. In this paper, we present a method to construct a depth datum geodesic height model, which can directly obtain a bathymetric database of depth data in a GNSS bathymetric survey. The model incorporates the continuous depth datum and the mean sea level of geodetic height in the same area. Through the numerical simulation of tidal wave motion in regional water, the tidal model is obtained. Based on the grid model, the tidal level is extracted from the tidal model for harmonic analysis, and a continuous depth datum model is established. Mean sea level geodetic height is from the CNES-CLS2015 Average Sea Surface Model. In this paper, the model is confirmed in the South Yellow Sea area. The results show that the accuracy of the depth datum model, and the depth datum geodetic height model meets the accuracy requirements of the datum.

Anxiety disorders are common mental disorders that often result in disability. Recently, large-scale genome-wide association studies (GWASs) have identified several novel risk variants and loci for anxiety disorders (or anxiety traits). Nevertheless, how the reported risk variants confer risk of anxiety remains unknown. To identify genes whose cis-regulated expression levels are associated with risk of anxiety traits, we conducted a transcriptome-wide association study (TWAS) by integrating genome-wide associations from a large-scale GWAS (N = 175,163) (which evaluated anxiety traits based on Generalized Anxiety Disorder 2-item scale (GAD-2) score) and brain expression quantitative trait loci (eQTL) data (from the PsychENCODE and GTEx). We identified 19 and 17 transcriptome-wide significant (TWS) genes in the PsychENCODE and GTEx, respectively. Intriguingly, 10 genes showed significant associations with anxiety in both datasets, strongly suggesting that genetic risk variants may confer risk of anxiety traits by regulating the expression of these genes. Top TWS genes included RNF123, KANSL1-AS1, GLYCTK, CRHR1, DND1P1, MAPT and ARHGAP27. Of note, 25 TWS genes were not implicated in the original GWAS. Our TWAS identified 26 risk genes whose cis-regulated expression were significantly associated with anxiety, providing important insights into the genetic component of gene expression in anxiety disorders/traits and new clues for future drug development.

It is well known that cancer incidence and death rates have been growing, but the development of cancer theranostics and therapeutics has been a challenging work. Recently, nucleic acid probe–based fluorescent sensing and imaging have achieved remarkable improvements in a variety of cancer management techniques, credited to their high sensitivity, good tolerance to interference, fast detection, and high versatility. Herein, nucleic acid probe–based fluorescent sensing and imaging are labeled with advanced fluorophores, which are essential for fast and sensitive detection of aberrant nucleic acids and other cancer-relevant molecules, consequently performing cancer early diagnosis and targeted treatment. In this review, we introduce the characteristics of nucleic acid probes, summarize the development of nucleic acid probe–based fluorescent sensing and imaging, and prominently elaborate their applications in cancer diagnosis and treatment. In discussion, some challenges and perspectives are elaborated in the field of nucleic acid probe–based fluorescent sensing and imaging.

Objectives: Evidence has shown that angiotensin-converting enzyme 2 (ACE2), which can be upregulated after angiotensin-converting enzyme inhibitor (ACEi) and angiotensin receptor blocker (ARB) treatment, may play a dual role in the pathogenesis and progression of coronavirus disease 2019 (COVID-19). We aimed to assess the association between the use of ACEi/ARB and the outcome of COVID-19 patients with preexisting hypertension in non-endemic areas.Methods: From January 17, 2020, to February 19, 2020, 286 patients with hypertension were enrolled in this retrospective study out of 1,437 COVID-19 patients from 47 centers in Zhejiang and Jiangsu Province. The composite endpoints consisted of mechanical ventilation, intensive care unit (ICU) admission, or death. Cox proportional hazards analysis was performed to assess the association between ACEi/ARB and clinical outcomes of COVID-19 patients with hypertension.Results: In the main analysis, 103 patients receiving ACEi/ARB were compared with 173 patients receiving other regimens. Overall, 44 patients (15.94%) had an endpoint event. The risk probability of crude endpoints in the ACEi/ARB group (12.62%) was lower than that in the non-ACEi/ARB group (17.92%). After adjusting for confounding factors by inverse probability weighting, the results showed that the use of ACEi/ARB reduced the occurrence of end events by 47% [hazard ratio (HR) = 0.53; 95% CI, 0.34–0.83]. Similar results were obtained in multiple sensitivity analyses.Conclusions: In this retrospective study, among COVID-19 patients with hypertension, the use of ACEi/ARB is not associated with an increased risk of disease severity compared with patients without ACEi/ARB. The trends of beneficial effects of ACEi/ARB need to be further evaluated in randomized clinical trials.

The objective of this study was to find out changes in ammonia oxidation microorganisms with respect to fertilizer as investigated by real-time polymerase chain reaction and high-throughput sequencing. The treatments included control (CK); chemical fertilizer nitrogen low (N) and high (N2); nitrogen and phosphorus (NP); nitrogen phosphorus and potassium (NPK) and organic manure fertilizer (M); MN; MN2; MNPK. The results showed that long-term fertilization influenced soil fertility and affected the abundance and community of ammonia-oxidizing microorganisms by changing the physical and chemical properties of the soil. The abundance and community structure of ammonia-oxidizing archaea (AOA) and ammonia-oxidizing bacteria (AOB) was influenced by soil organic carbon, total nitrogen, total soil phosphorus, available phosphorus, available potassium, and soil nitrate. Soil environmental factors affected the nitrification potential by affecting the structure of ammonia-oxidizing microorganisms; specific and rare AOA and AOB rather than the whole AOA or AOB community played dominant role in nitrification.

This study aims to examine the neural correlates of cognitive shifting during the Dimensional Change Card Sort Task (DCCS) task with functional near-infrared spectroscopy. Altogether 49 children completed the DCCS tasks, and 25 children (Mage = 68.66, SD = 5.3) passing all items were classified into the Switch group. Twenty children (Mage = 62.05, SD = 8.13) committing more than one perseverative errors were grouped into the Perseverate group. The Switch group had Brodmann Area (BA) 9 and 10 activated in the pre-switch period and BA 6, 9, 10, 40, and 44 in the post-switch period. In contrast, the Perseverate group had BA 9 and 10 activated in the pre-switch period and BA 8, 9, 10 in the post-switch period. The general linear model results afford strong support to the “V-shape curve” hypothesis by identifying a significant decrease–increase cycle in BA 9 and 44, the neural correlations of cognitive shifting.

This study explored the differentiated neural correlates of mental rotation (MR) in preschoolers with high and low working memory capacity using functional near-infrared spectroscopy (fNIRS). Altogether 38 Chinese preschoolers (M = 5.0 years, SD = 0.69 years) completed the Working Memory Capacity (WMC) test, the Mental Rotation (MR), and its Control tasks (without MR). They were divided into High-WMC (N1 = 9) and Low-WMC (N2 = 18) groups based on the WMC scores. The behavioral and fNIRS results indicated that: (1) there were no significant differences in MR task performance between the High-WMC (Mmr = 23.44, SD = 0.88) and Low-WMC group (Mmr = 23.67, SD = 0.59); (2) the Low-WMC group activated BA6, BA8, BA 9, and BA 44, whereas the High-WMC group activated BA8, BA10 and BA 44 during mental rotation; (3) significant differences were found in the activation of BA44 and BA9 between the High-WMC and Low-WMC groups during mental rotation; and (4) the High-WMC and Low-WMC groups differed significantly in the activation of BA 9 and BA10 during the control tasks, indicating that both areas might be responsible for the group differences in working memory.

Recognizing prohibited items automatically is of great significance for intelligent X-ray baggage security screening. Convolutional neural networks (CNNs), with the support of big training data, have been verified as the powerful models capable of reliably detecting the expected objects in images. Therefore, building a specific CNN model working reliably on prohibited item detection also requires large amounts of labeled item image data. Unfortunately, the current X-ray baggage image database is not big enough in count and diversity for CNN model training. In this paper, we propose a novel method for X-ray prohibited item data augmentation using generative adversarial networks (GANs). The prohibited items are first extracted from X-ray baggage images using a K-nearest neighbor matting scheme. Then, the poses of the obtained item images are estimated using a space rectangular coordinate system and categorized into four or eight classes for constructing a training database. For generating the realistic samples reliably, different GAN models are evaluated using Frechet Inception Distance scores, and some important tips of handling GAN training in X-ray prohibited item image generation are reported. Finally, to verify whether the generated images belong to its corresponding class or not, a cross-validation scheme based on a CNN model is implemented. The experimental results show that most of the generated images can be classified correctly by the CNN model. This implies that the generated prohibited item images can be used as the extended samples to augment an X-ray image database.

In terms of biometrics, a human finger itself is with trimodal traits including fingerprint, finger-vein, and finger-knuckle-print, which provides convenience and practicality for finger trimodal fusion recognition. The scale inconsistency of finger trimodal images is an important reason affecting effective fusion. It is therefore very important to developing a theory of giving a unified expression of finger trimodal features. In this paper, a graph-based feature extraction method for finger biometric images is proposed. The feature expression based on graph structure can well solve the problem of feature space mismatch for the finger three modalities. We provide two fusion frameworks to integrate the finger trimodal graph features together, the serial fusion and coding fusion. The research results can not only promote the advancement of finger multimodal biometrics technology but also provide a scientific solution framework for other multimodal feature fusion problems. The experimental results show that the proposed graph fusion recognition approach obtains a better and more effective recognition performance in finger biometrics.

Allogeneic hematopoietic cell transplantation (HCT) remains the only curative therapy for many hematological malignant and non-malignant disorders. However, key obstacles to the success of HCT include graft-versus-host disease (GVHD) and disease relapse due to absence of graft-versus-tumor (GVT) effect. Over the last decade, advances in “omics” technologies and systems biology analysis, have allowed for the discovery and validation of blood biomarkers that can be used as diagnostic test and prognostic test (that risk-stratify patients before disease occurrence) for acute and chronic GVHD and recently GVT. There are also predictive biomarkers that categorize patients based on their likely to respond to therapy. Newer mathematical analysis such as machine learning is able to identify different predictors of GVHD using clinical characteristics pre-transplant and possibly in the future combined with other biomarkers. Biomarkers are not only useful to identify patients with higher risk of disease progression, but also help guide treatment decisions and/or provide a basis for specific therapeutic interventions. This review summarizes biomarkers definition, omics technologies, acute, chronic GVHD and GVT biomarkers currently used in clinic or with potential as targets for existing or new drugs focusing on novel published work.

Abstract Background Electronic Medical Record (EMR) comprises patients’ medical information gathered by medical stuff for providing better health care. Named Entity Recognition (NER) is a sub-field of information extraction aimed at identifying specific entity terms such as disease, test, symptom, genes etc. NER can be a relief for healthcare providers and medical specialists to extract useful information automatically and avoid unnecessary and unrelated information in EMR. However, limited resources of available EMR pose a great challenge for mining entity terms. Therefore, a multitask bi-directional RNN model is proposed here as a potential solution of data augmentation to enhance NER performance with limited data. Methods A multitask bi-directional RNN model is proposed for extracting entity terms from Chinese EMR. The proposed model can be divided into a shared layer and a task specific layer. Firstly, vector representation of each word is obtained as a concatenation of word embedding and character embedding. Then Bi-directional RNN is used to extract context information from sentence. After that, all these layers are shared by two different task layers, namely the parts-of-speech tagging task layer and the named entity recognition task layer. These two tasks layers are trained alternatively so that the knowledge learned from named entity recognition task can be enhanced by the knowledge gained from parts-of-speech tagging task. Results The performance of our proposed model has been evaluated in terms of micro average F-score, macro average F-score and accuracy. It is observed that the proposed model outperforms the baseline model in all cases. For instance, experimental results conducted on the discharge summaries show that the micro average F-score and the macro average F-score are improved by 2.41% point and 4.16% point, respectively, and the overall accuracy is improved by 5.66% point. Conclusions In this paper, a novel multitask bi-directional RNN model is proposed for improving the performance of named entity recognition in EMR. Evaluation results using real datasets demonstrate the effectiveness of the proposed model.

Abstract Background Recent studies have indicated that deubiquitinating enzymes (DUBs) are related to the stem-cell pathway network and chemo-resistance in cancer. Ubiquitin-specific peptidase 37 (USP37), a novel DUB, was identified to be a potential factor associated with tumor progression. However, the biological functions of USP37 in breast cancer remain unclear. Methods The distribution of USP37 expression in breast cancer and the correlation between USP37 expression and the overall survival rate were detected by The Cancer Genome Atlas (TCGA) database. Gene set enrichment analysis (GSEA) was utilized to evaluate potential mechanism of USP37 in breast cancer. The USP37 expression in breast cancer tissues and breast cancer cell lines were detected by immunohistochemistry and western blotting. Sorting of breast cancer stem cells (BCSCs) were by using MACS assay. In vitro and in vivo assays were performed to examine the biological functions of USP37 in breast cancer cells. MG132, CHX chase, immunofluorescence staining and co-immunoprecipitation assays were used to test the interaction between USP37 and Gli-1. Results Bioinformatics analysis demonstrated that USP37 gene was elevated in breast cancer tissues and its overexpression was strongly correlated with the increased mortality rate. GSEA analysis showed that USP37 expression was positively associated with cell growth and metastasis while negatively related to cell apoptosis in the TCGA breast cancer samples. USP37 expression was elevated in breast cancer tissues and breast cancer cell lines. Moreover, we also detected that USP37 was overexpressed in BCSCs. USP37 regulated the ability of cell invasion, epithelial-mesenchymal transition (EMT), stemness and cisplatin sensitivity in breast cancer cell lines. Additionally, USP37 knockdown inhibited tumorigenicity and increased anticancer effect of cisplatin in vivo. Knockdown of USP37 significantly decreased hedgehog (Hh) pathway components Smo and Gli-1. Gli-1 was stabilized by USP37 and they interacted with each other. Further studies indicated that USP37 knockdown could inhibit the stemness, cell invasion and EMT in breast cancer via downregulation of Hh pathway. Conclusions These findings reveal that USP37 is highly expressed in BCSCs and is correlated with poor prognosis in breast cancer patients. USP37 can regulate the stemness, cell invasion and EMT via Hh pathway, and decreased USP37 confers sensitivity to cisplatin in breast cancer cells. USP37 is required for the regulation of breast cancer progression, as well as a critical target for clinical treatment of breast cancer.

Key technologies in empty bottle inspection systems are studied in this paper to solve detecting error and poor adaptability problems. Those technologies have two different approaches: the ones in the first group locate and track bottle mouth, bottle bottom and walls while the other group technologies involve defect detecting. Such vision inspection systems are required to perform with high accuracy and adaptability under high speed and mechanical vibration working conditions. This study proposes distinctive algorithms for bottle locating, tracking and defect detecting based on inspection requirements and images of bottle mouth, bottom and walls. On the premise of satisfying the inspecting requirements, the simplicity, ease of implementation and universality of the algorithms are considered to improve the detection speed and the adaptability of the system to different kinds of bottles. Experiments showed that the system proposed in this paper can improve the detection accuracy and speed.

Abstract Background Cardiovascular disease (CVD) has become the leading cause of death in China, and most of the cases can be prevented by controlling risk factors. The goal of this study was to build a corpus of CVD risk factor annotations based on Chinese electronic medical records (CEMRs). This corpus is intended to be used to develop a risk factor information extraction system that, in turn, can be applied as a foundation for the further study of the progress of risk factors and CVD. Results We designed a light annotation task to capture CVD risk factors with indicators, temporal attributes and assertions that were explicitly or implicitly displayed in the records. The task included: 1) preparing data; 2) creating guidelines for capturing annotations (these were created with the help of clinicians); 3) proposing an annotation method including building the guidelines draft, training the annotators and updating the guidelines, and corpus construction. Meanwhile, we proposed some creative annotation guidelines: (1) the under-threshold medical examination values were annotated for our purpose of studying the progress of risk factors and CVD; (2) possible and negative risk factors were concerned for the same reason, and we created assertions for annotations; (3) we added four temporal attributes to CVD risk factors in CEMRs for constructing long term variations. Then, a risk factor annotated corpus based on de-identified discharge summaries and progress notes from 600 patients was developed. Built with the help of clinicians, this corpus has an inter-annotator agreement (IAA) F1-measure of 0.968, indicating a high reliability. Conclusion To the best of our knowledge, this is the first annotated corpus concerning CVD risk factors in CEMRs and the guidelines for capturing CVD risk factor annotations from CEMRs were proposed. The obtained document-level annotations can be applied in future studies to monitor risk factors and CVD over the long term.

Abstract A novel LiNbO3 (lithium niobate, LN) electro-optic (EO) Q-switch that can independently operate in the pulse-on regime without the assistance of a quarter-wave plate (QWP) or analyzer was designed and demonstrated. By theoretical analysis and calculations, the proper orientation of the LN was determined to be θ = 1.7° and φ = ±45°, and the quarter-wave voltage was identical to that of a conventional LN EO Q-switch. Additionally, the possible influences caused by the small angular variation between the wave normal and optic axis were found to be negligible. To the best of our knowledge, this is the first time that a LN crystal has been (xztw)-1.2°/1.2°-cut and used successfully in a pulse-on cavity without using a QWP or analyzer. The performance of the novel Q-switched laser and its temperature dependence were verified to be almost identical to those of a conventional pulse-on LN EO Q-switched laser, which strongly demonstrates the practicability of our novel Q-switch. This novel Q-switch design enables a more compact, lossless and stable laser cavity, which is of great concern for engineering applications.

Background and Aims. The involvement of cellular immunity in the development of hepatitis E virus (HEV) infection is rare. We aimed to study the roles of viral load and Th cell responses in acute hepatitis E (AHE) and HEV-related acute liver failure (HEV-ALF). Methods. We evaluated viral load and Th1/Th2 cytokine levels in 34 patients with HEV infection, including 17 each with AHE or HEV-ALF. Seventeen healthy controls (HCs) were also included who were negative for anti-HEV IgM and IgG. Results. There was no significant difference in viral load and HEV RNA in the AHE and HEV-ALF groups (both P>0.05). The Th lymphocyte levels (CD3+, CD4+) in the AHE and HEV-ALF groups were significantly higher than those in the HC group (both P0.05). Both IFN-γ and IL-10 showed gradual upward trend from the HC group to the AHE (both P0.05). Th2 bias was observed from the AHE (ratio=58.65) to HEV-ALF (ratio=1.20) groups. The level of IFN-γ was associated with the outcome of HEV-ALF patients. Conclusions. HEV viral load was not associated with aggravation of AHE, and the HEV-ALF patients showed significant Th2 bias, which may be involved in the aggravation of AHE.

Colorectal cancer (CRC) ranks second in cancer-associated mortality and third in the incidence worldwide. Most of CRC follow adenoma-carcinoma sequence, and have more than 90% chance of survival if diagnosed at early stage. But the recommended screening by colonoscopy is invasive, expensive, and poorly adhered to. Recently, several studies reported that the fecal bacteria might provide non-invasive biomarkers for CRC and precancerous tumors. Therefore, we collected and uniformly re-analyzed these published fecal 16S rDNA sequencing datasets to verify the association and identify biomarkers to classify and predict colorectal tumors by random forest method. A total of 1674 samples (330 CRC, 357 advanced adenoma, 141 adenoma, and 846 control) from 7 studies were analyzed in this study. By random effects model and fixed effects model, we observed significant differences in alpha-diversity and beta-diversity between individuals with CRC and the normal colon, but not between adenoma and the normal. We identified various bacterial genera with significant odds ratios for colorectal tumors at different stages. Through building random forest model with 10-fold cross-validation as well as new test datasets, we classified individuals with CRC, advanced adenoma, adenoma and normal colon. All approaches obtained comparable performance at entire OTU level, entire genus level, and the common genus level as measured using AUC. When combined all samples, the AUC of random forest model based on 12 common genera reached 0.846 for CRC, although the predication performed poorly for advance adenoma and adenoma.

This study aims to examine the impact of heavy use of tablets on preschoolers’ executive function during the Dimensional Change Card Sort (DCCS) task using the functional near-infrared spectroscopy (fNIRS). Altogether, 38 Chinese preschoolers (Mage = 5.0 years, SD = 0.69 years, 17 girls) completed the tasks before the COVID-19 lockdown. Eight children never used tablets, while 16 children were diagnosed as the ‘heavy-user’. The results indicated that: (1) the ‘non-user’ outperformed the ‘heavy-user’ with a significantly higher correct rate in the DCCS task; (2) the two groups differed significantly in the activation of the prefrontal cortex (BA 9): the ‘non-user’ pattern is normal and healthy, whereas the ‘heavy-user’ pattern is not normal and needs further exploration.

Specific entity terms such as disease, test, symptom, and genes in Electronic Medical Record (EMR) can be extracted by Named Entity Recognition (NER). However, limited resources of labeled EMR pose a great challenge for mining medical entity terms. In this study, a novel multitask bi-directional RNN model combined with deep transfer learning is proposed as a potential solution of transferring knowledge and data augmentation to enhance NER performance with limited data. The proposed model has been evaluated using micro average F-score, macro average F-score and accuracy. It is observed that the proposed model outperforms the baseline model in the case of discharge datasets. For instance, for the case of discharge summary, the micro average F-score is improved by 2.55% and the overall accuracy is improved by 7.53%. For the case of progress notes, the micro average F-score and the overall accuracy are improved by 1.63% and 5.63%, respectively.

We report on a single-shot diffraction imaging methodology using relativistic femtosecond electron pulses generated by a radio-frequency acceleration-based photoemission gun. The electron pulses exhibit excellent characteristics, including a root-mean-square (rms) illumination convergence of 31 ± 2 μrad, a spatial coherence length of 5.6 ± 0.4 nm, and a pulse duration of approximately 100 fs with (6.3 ± 0.6) × 106 electrons per pulse at 3.1 MeV energy. These pulses facilitate high-quality diffraction images of gold single crystals with a single shot. The rms spot width of the diffracted beams was obtained as 0.018 ± 0.001 Å−1, indicating excellent spatial resolution.

Background. The mechanisms of mesenchymal stem cell (MSC) transplantation to protect against acute liver injury have been well studied within the liver. However, the associated changes in the intestinal microbiota during this process are poorly understood. Methods. In this study, compact bone-derived MSCs were injected into mice after carbon tetrachloride (CCl4) administration. Potential curative effect of MSC was evaluated by survival rate and biochemical and pathological results. Overall structural changes of microbial communities and alterations in the intestinal microbiota were assessed by sequenced 16S rRNA amplicon libraries from the contents of the cecum and colon. Results. MSCs significantly reduced the serum levels of aspartate transaminase and alanine transaminase and improved the histopathology and survival rate. Lower expression and discontinuous staining of zonula occludens, as well as disrupted tight junctions, were observed in CCl4-treated mice at 48 h compared with MSC-transplanted mice. Moreover, MSC transplantation to the liver leads to intestinal microbiota changes that were reflected in the decreased abundance of Bacteroidetes S24-7 and Bacteroidaceae and increased abundance of Firmicutes Clostridiales, Ruminococcaceae, and Lactobacillus at the initial time point compared with that in CCl4-treated mice. In addition, phylogenetic investigation of communities by the reconstruction of unobserved states (PICRUSt) based on the Greengenes database revealed functional biomarkers of MSC-transplanted mice involved in cell motility, signal transduction, membrane transport, transcription, and metabolism of lipids, cofactors, vitamins, terpenoids, and polyketides, as well as xenobiotics. Conclusion. The initial alterations in the Firmicutes/Bacteroidetes ratio, which resulted from MSC infusion to the liver, maintain intestinal mucosal biology and homeostasis that may be beneficial to liver repair.

Lepisorus thunbergianus (Kaulf.) (LET) is an evergreen fern found on rocks and tree trunks that is distributed in East and Southeast Asia. Our previous study showed that the methanol extract from LET had significant anti-oxidant activity, but the active components of LET are still unclear. In the present study, isovitexin, orientin, isoorientin and chlorogenic acid were isolated from LET under the guidance of antioxidant activity. In addition, the structure of isovitexin, orientin, isoorientin and chlorogenic acid was characterized using matrix-assisted laser desorption/ionization time of flight mass spectrometry (MALDI-TOF-MS) and nuclear magnetic resonance spectroscopy (NMR). Orientin and isoorientin presented similar activities toward the DPPH, with half maximal inhibitory concentrations (IC50) of 15–17 μmol, and inhibition of reactive oxygen species (ROS) production by 50% at 100 μmol. Chlorogenic acid significantly inhibited intracellular ROS and nitric oxide (NO) production and had a strong effect toward DPPH. Furthermore, chlorogenic acid demonstrated decreased iNOS, COX-2, IFN-β and TNF-α gene expression. These findings demonstrate the potential anti-inflammatory effects of chlorogenic acid. Isoorientin, at a concentration of 100 μmol, showed 50% inhibition of human liver cancer cells (Huh7 and HepG2). These results suggest that compounds isolated from LET have potential to prevent liver cancer cell lines.

Background: Stem cell-based therapy in liver diseases has received increasing interest over the past decade, but direct evidence of the homing and implantation of transplanted cells is conflicting. Reliable labeling and tracking techniques are essential but lacking. The purpose of this study was to establish human placenta-derived mesenchymal stem cells (hPMSCs) expressing green fluorescent protein (GFP) and to assay their hepatic functional differentiation in vitro. Methods: The GFP gene was transduced into hPMSCs using a lentivirus to establish GFP+ hPMSCs. GFP+ hPMSCs were analyzed for their phenotypic profile, viability and adipogenic, osteogenic and hepatic differentiation. The derived GFP+ hepatocyte-like cells were evaluated for their metabolic, synthetic and secretory functions, respectively. Results: GFP+ hPMSCs expressed high levels of HLA I, CD13, CD105, CD73, CD90, CD44 and CD29, but were negative for HLA II, CD45, CD31, CD34, CD133, CD271 and CD79. They possessed adipogenic, osteogenic and hepatic differentiation potential. Hepatocyte-like cells derived from GFP+ hPMSCs showed typical hepatic phenotypes. Conclusions: GFP gene transduction has no adverse influences on the cellular or biochemical properties of hPMSCs or markers. GFP gene transduction using lentiviral vectors is a reliable labeling and tracking method. GFP+ hPMSCs can therefore serve as a tool to investigate the mechanisms of MSC-based therapy, including hepatic disease therapy.

Abstract Due to its high theoretical energy density (2600 Wh kg−1), low cost, and environmental benignity, the lithium–sulfur (Li‐S) battery is attracting strong interest among the various electrochemical energy storage systems. However, its practical application is seriously hampered by the so‐called shuttle effect of the highly soluble polysulfides. Herein, a novel design of multifunctional sandwich‐structured polymer electrolyte (polymer/cellulose nonwoven/nanocarbon) for high‐performance Li‐S batteries is demonstrated. It is verified that Li‐S battery with this sandwich‐structured polymer electrolyte delivers excellent cycling stability (only 0.039% capacity decay cycle−1 on average exceeding 1500 cycles at 0.5 C) and rate capability (with a reversible capacity of 594 mA h g−1 at 4 C). These electrochemical performances are attributed to the synergistic effect of each layer in this unique sandwich‐structured polymer electrolyte including steady lithium stripping/plating, strong polysulfide absorption ability, and increased redox reaction sites. More importantly, even with high sulfur loading of 4.9 mg cm−2, Li‐S battery with this sandwich‐structured polymer electrolyte can deliver high initial areal capacity of 5.1 mA h cm−2. This demonstrated strategy here may open up a new era of designing hierarchical structured polymer electrolytes for high‐performance Li‐S batteries.

We have developed a compact relativistic femtosecond electron diffractometer with a radio-frequency photocathode electron gun and an electron lens system. The electron gun generated 2.5-MeV-energy electron pulses with a duration of 55 ± 5 fs containing 6.3 × 104 electrons per pulse. Using these pulses, we successfully detected high-contrast electron diffraction images of single crystalline, polycrystalline, and amorphous materials. An excellent spatial resolution of diffraction images was obtained as 0.027 ± 0.001 Å−1. In the time-resolved electron diffraction measurement, a laser-excited ultrafast electronically driven phase transition in single-crystalline silicon was observed with a temporal resolution of 100 fs. The results demonstrate the advantages of the compact relativistic femtosecond electron diffractometer, including access to high-order Bragg reflections, single shot imaging with the relativistic femtosecond electron pulse, and the feasibility of time-resolved electron diffraction to study ultrafast structural dynamics.

Recently, finger-based biometrics, including fingerprint (FP), finger-vein (FV) and finger-knuckle-print (FKP) with high convenience and user friendliness, have attracted much attention for personal identification. The features expression which is insensitive to illumination and pose variation are beneficial for finger trimodal recognition performance improvement. Therefore, exploring suitable method of reliable feature description is of great significance for developing finger-based biometric recognition system. In this paper, we first propose a correction approach for dealing with the pose inconsistency among the finger trimodal images, and then introduce a novel local coding-based feature expression method to further implement feature fusion of FP, FV, and FKP traits. First, for the coding scheme a bank of oriented Gabor filters is used for direction feature enhancement in finger images. Then, a generalized symmetric local graph structure (GSLGS) is developed to fully express the position and orientation relationships among neighborhood pixels. Experimental results on our own-built finger trimodal database show that the proposed coding-based approach achieves excellent performance in improving the matching accuracy and recognition efficiency.

Introduction. Green fluorescent protein (GFP) is widely used as a reporter gene in regenerative medicine research to label and track stem cells. Here, we examined whether expressing GFP gene may impact the metabolism of human placental mesenchymal stem cells (hPMSCs). Methods. The GFP gene was transduced into hPMSCs using lentiviral-based infection to establish GFP+hPMSCs. A sensitive 13C/12C-dansyl labeling LC-MS method targeting the amine/phenol submetabolome was used for in-depth cell metabolome profiling. Results. A total of 1151 peak pairs or metabolites were detected from 12 LC-MS runs. Principal component analysis and partial least squares discriminant analysis showed poor separation, and the volcano plots demonstrated that most of the metabolites were not significantly changed when hPMSCs were tagged with GFP. Overall, 739 metabolites were positively or putatively identified. Only 11 metabolites showed significant changes. Metabolic pathway analyses indicated that three of the identified metabolites were involved in nine pathways. However, these metabolites are unlikely to have a large impact on the metabolic pathways due to their nonessential roles and limited hits in pathway analysis. Conclusion. This study indicated that the expression of ectopic GFP reporter gene did not significantly alter the metabolomics pathways covered by the amine/phenol submetabolome.

This paper presents recent development on magnetostrictive linear position sensors (MLPS). A new compensation coil structure improves the EMI suppression and accuracy considerably. Furthermore, experimental results indicate that the new structure can improve the accuracy to ±0.13 mm nearly double the ±0.2 mm obtained with traditional structures. As another design continuation after the differential waveguide structure, this new structure is a practical and reliable implementation technique for the commercialization of MLPS.

Finger-vein recognition has received increased attention recently. However, the finger-vein images are always captured in poor quality. This certainly makes finger-vein feature representation unreliable, and further impairs the accuracy of finger-vein recognition. In this paper, we first give an analysis of the intrinsic factors causing finger-vein image degradation, and then propose a simple but effective image restoration method based on scattering removal. To give a proper description of finger-vein image degradation, a biological optical model (BOM) specific to finger-vein imaging is proposed according to the principle of light propagation in biological tissues. Based on BOM, the light scattering component is sensibly estimated and properly removed for finger-vein image restoration. Finally, experimental results demonstrate that the proposed method is powerful in enhancing the finger-vein image contrast and in improving the finger-vein image matching accuracy.

Railway inspection is an important task in railway maintenance to ensure safety. The fastener is a major part of the railway which fastens the tracks to the ground. The current article presents an efficient method to detect fasteners on the basis of image processing and pattern recognition techniques, which can be used to detect the absence of fasteners on the corresponding track in high-speed(up to 400 km/h). The Direction Field is extracted as the feature descriptor for recognition. In addition, the appropriate weight coefficient matrix is presented for robust and rapid matching in a complex environment. Experimental results are presented to show that the proposed method is computation efficient and robust for the detection of fasteners in a complex environment. Through the practical device fixed on the track inspection train, enough fastener samples are obtained, and the feasibility of the method is verified at 400 km/h.

Magnetostrictive linear position sensors (MLPS) are high-precision sensors used in the industrial field for measuring the propagation time of ultrasonic signals in a waveguide. To date, MLPS have attracted widespread attention for their accuracy, reliability, and cost-efficiency in performing non-contact, multiple measurements. However, the sensor, with its traditional structure, is susceptible to electromagnetic interference, which affects accuracy. In the present study, we propose a novel structure of MLPS that relies on two differential waveguides to improve the signal-to-noise ratio, common-mode rejection ratio, and accuracy of MLPS. The proposed sensor model can depict sensor performance and the relationship of sensor parameters. Experimental results with the new sensor indicate that the new structure can improve accuracy to ±0.1 mm higher than ±0.2 mm with a traditional structure. In addition, the proposed sensor shows a considerable improvement in temperature characteristics.

Finger-based personal identification has become an active research topic in recent years because of its high user acceptance and convenience. How to reliably and effectively fuse the multimodal finger features together, however, has still been a challenging problem in practice. In this paper, viewing the finger trait as the combination of a fingerprint, finger vein, and finger-knuckle-print, a new multimodal finger feature recognition scheme is proposed based on granular computing. First, the ridge texture features of FP, FV, and FKP are extracted using Gabor Ordinal Measures (GOM). Second, combining the three-modal GOM feature maps in a color-based manner, we then constitute the original feature object set of a finger. To represent finger features effectively, they are granulated at three levels of feature granules (FGs) in a bottom-up manner based on spatial circular granulation. In order to test the performance of the multilevel FGs, a top-down matching method is proposed. Experimental results show that the proposed method achieves higher accuracy recognition rate in finger feature recognition.

Diabetic neuropathic pain is reduced with tight glycemic control. However, strict control increases the risk of hypoglycemic episodes, which are themselves linked to painful neuropathy. This study explored the effects of hypoglycemia-related painful neuropathy. Pretreatment with coenzyme Q10 (CoQ10) was performed to explore the preventive effect of CoQ10 on hypoglycemia-related acute neuropathic pain. Two strains of mice were used and 1 unit/kg of insulin was given to induce hypoglycemia. Mechanical sensitivity of hindpaw withdrawal thresholds was measured using von Frey filaments. Blood glucose levels were clamped at normal levels by joint insulin and glucose injection to test whether insulin itself induced hypersensitivity. Results suggest that the increased mechanical sensitivity after insulin injection is related to decreased blood glucose levels. When blood glucose levels remained at a normal level by the linked administration of insulin and glucose, mice demonstrated no significant change in mechanical sensitivity. Pretreatment with CoQ10 prevented neuropathic pain and the expression of the stress factor c-Fos. These results support the concept that pain in the diabetic scenario can be the result of hypoglycemia and not insulin itself. Additionally, pretreatment with CoQ10 may be a potent preventive method for the development of neuropathic pain.

OBJECTIVE:To characterize the significance of correlated autoantibodies in systemic lupus erythematosus (SLE) and its complication lupus nephritis (LN) in a large cohort of patients. METHODS:Clinical data were statistically analyzed in 1699 SLE patients with or without nephritis who were diagnosed and treated during 2002-2013 in the northeast region of China. Reactivity to a list of 16 autoantibodies was detected by the serum test Euroline ANA profile (IgG). Serum titers of the anti-nucleosome autoantibodies were measured by ELISA assays. Kidney biopsies were examined by pathologists. Immune complex deposition was identified by immunohistochemistry stain. RESULTS:Simultaneous positivity of anti-dsDNA, -nucleosome and -histone antibodies (3-pos) was prevalent in SLE patients with LN compared to Non-renal SLE patients (41% vs 11%, p< 0.001). Significant correlations were found between any two of the above three anti-nucleosome antibodies in LN patients. In comparison to non-3-pos cohorts, 3-pos patients with LN had significantly higher serum levels of the three antibodies and more active disease; was associated with type IV disease; suffered from more severe renal damages; received more intensive treatment and had worse disease outcome. The serum levels of these three autoantibodies in 3-pos LN patients were significantly decreased when they underwent clinical recovery. CONCLUSIONS:Simultaneous reactivity to anti-dsDNA, -nucleosome and -histone antibodies by Euroline ANA profile (IgG) may indicate severe nephropathy in patients with SLE.

Human uveitis is a type of T cell-mediated autoimmune disease that often shows relapse-remitting courses affecting multiple biological processes. As a cytoplasmic process, autophagy has been seen as an adaptive response to cell death and survival, yet the link between autophagy and T cell-mediated autoimmunity is not certain. In this study, based on the differentially expressed genes (GSE19652) between the recurrent versus monophasic T cell lines, whose adoptive transfer to susceptible animals may result in respective recurrent or monophasic uveitis, we proposed grouping annotations on a subcellular layered interactome framework to analyze the specific bioprocesses that are linked to the recurrence of T cell autoimmunity. That is, the subcellular layered interactome was established by the Cytoscape and Cerebral plugin based on differential expression, global interactome, and subcellular localization information. Then, the layered interactomes were grouping annotated by the ClueGO plugin based on Gene Ontology and Kyoto Encyclopedia of Genes and Genomes databases. The analysis showed that significant bioprocesses with autophagy were orchestrated in the cytoplasmic layered interactome and that mTOR may have a regulatory role in it. Furthermore, by setting up recurrent and monophasic uveitis in Lewis rats, we confirmed by transmission electron microscopy that, in comparison to the monophasic disease, recurrent uveitis in vivo showed significantly increased autophagy activity and extended lymphocyte infiltration to the affected retina. In summary, our framework methodology is a useful tool to disclose specific bioprocesses and molecular targets that can be attributed to a certain disease. Our results indicated that targeted inhibition of autophagy pathways may perturb the recurrence of uveitis.

Previously, we demonstrated that electroacupuncture (EA) decreased lymphocyte infiltration into the spinal cords of rats presenting with experimental autoimmune encephalomyelitis (EAE), a disease model used in the study of multiple sclerosis (MS). The aim of this study was to characterize the effects of EA on the EAE. Female Lewis rats were divided into either CFA, EAE, EA, or injection with naloxone after electroacupuncture (NAL) groups. Electroacupuncture was administered every day for 21 days. To evaluate proliferation and apoptosis, lymphocytes from rats presenting with EAE were collected and cultured with β-endorphin. Immunohistochemisty, flow cytometry and radio-immunity methods were applied to detect the expression of β-endorphin. Results presented in this report demonstrate that the beneficial anti-inflammatory effects of EA on EAE were related to β-endorphin production that balances the Thl/Th2 and Th17/Treg responses. These results suggest that β-endorphin could be an important component in the development of EA-based therapies used for the treatment of EAE.