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Amomum villosum Lour. (A. villosum) is a valuable herbaceous plant that produces the famous traditional Chinese medicine Amori Fructus. Identifying molecular markers associated with the growth of A. villosum can facilitate molecular marker-assisted breeding of the plant. This study employed 75 A. villosum accessions as the test material and utilized 71 pairs of polymorphic simple sequence repeat (SSR) molecular markers to genotype the population. The study analyzed the association between SSR markers and phenotypic traits through the linkage imbalance and population structure analysis. Candidate genes associated with the molecular markers were also identified. The results showed that the phenotypic diversity index range of the 12 agronomic traits was 4.081–4.312 and conformed to a normal distribution. Moreover, 293 allelic variations were detected in the 75 accessions, with an average of 5.32 amplified alleles per loci, ranging from 3 to 8. The maximum number of amplified alleles for AVL12 was 8. The population structure and cluster analysis indicated that the accessions could be divided into two subgroups. Using the mixed linear model (MLM) model of population structure (Q)+kinship matrix (K) for association analysis, three SSR molecular markers significantly associated with the agronomic traits were detected. Fluorescence quantification was used to analyze the expression levels of six candidate genes, and it was found that three of the genes were differentially expressed in phenotypically different accessions. This study is the first to use SSR markers for genome-wide association study (GWAS) mapping and identification of the associated agronomic traits in A. villosum. The results of this study provide a basis for identifying genetic markers for growth traits for marker-assisted breeding in A. villosum. [ABSTRACT FROM AUTHOR]

[Display omitted] VO 2 (B) is recognized as a promising cathode material for aqueous zinc metal batteries (AZMBs) owing to its remarkable specific capacity and its unique, expansive tunnel structure, which facilitates the reversible insertion and extraction of Zn2+. Nonetheless, challenges such as the inherent instability of the VO 2 structure, poor ion/electron transport and a limited capacity due to the low redox potential of the V3+/V4+ couple have hindered its wider application. In this study, we present a strategy to replace vanadium ions by doping Al3+ in VO 2. This approach activates the multi-electron reaction (V4+/V5+), to increase the specific capacity and improve the structural stability by forming robust V5+ O and Al3+ O bonds. It also induces a local electric field by altering the local electron arrangement, which significantly accelerates the ion/electron transport process. As a result, Al-doped VO 2 exhibits superior specific capacity, improved cycling stability, and accelerated electronic transport kinetics compared to undoped VO 2. The beneficial effects of heterogeneous atomic doping observed here may provide valuable insights into the improvement electrode materials in metal-ion battery systems other than those based on Zn. [ABSTRACT FROM AUTHOR]

[Display omitted] Vanadium-based materials are widely recognized as the primary candidate cathode materials for aqueous Zn-ion batteries (AZIBs). However, slow kinetics and poor stability pose significant challenges for widespread application. Herein, to address these issues, alkali metal ions and polyaniline (PANI) are introduced into layered hydrated V 2 O 5 (VO). Density functional theory calculations reveal that the synthesized (C 6 H 4 NH) 0.27 K 0.24 V 2 O 5 ·0.92H 2 O (KPVO), with K+ and PANI co-intercalation, exhibits a robust interlayer structure and a continuous three-dimensional (3D) electron transfer network. These properties facilitate the reversible diffusion of Zn2+ with a low migration potential barrier and rapid response kinetics. The KPVO cathode exhibits a discharge specific capacity of 418.3 mAh/g at 100 mA/g and excellent cycling stability with 89.5 % retention after 3000 cycles at 5 A/g. This work provides a general strategy for integrating cathode materials to achieve high specific capacity and excellent kinetic performance. [ABSTRACT FROM AUTHOR]

The legs of insects play an important role in their daily behaviour, especially reproduction. Entomologists have performed much research on the role of the leg in different behaviours of beetles, an important group in the insect family, but relatively little has been done to study the ultrastructure and transcriptome of their legs. Hence, we systematically studied the ultrastructure and gene expression of the leg of G. cantor, a polygynous beetle, and compared its male and female diversity. In this study, we found the fore-leg, mid-leg and hind-leg of the female were significantly longer than those of the male. From the perspective of intuitive structural differences, we also compared the ultrastructures of the adhesion structure (tarsal) of males and females. The tarsal functional structure of the adult leg mainly includes sensilla and an adhesion structure. The sensilla on the tarsal joint mainly include sensilla chaetica (SCh II, SCh III) and sensilla trichodea (ST II). The adhesion structure includes disc-shaped bristles (di), lanceolate bristles (la), serrated bristles (se), spatula-shaped bristles (spl) and mushroom-shaped bristles (mus). Although there was no significant difference in sensillum distribution or type between males and females, there were significant differences in the distribution and species of adhesion structures between the fore-leg, mid-leg, and hind-leg of the same sex and between males and females. Therefore, different adhesion structures play different roles in various behaviours of beetles. On the other hand, the transcriptome results of male and female legs were screened for a subset of olfaction- and mechanics-related genes. We discovered that the male leg showed upregulation of 1 odorant binding protein (OBP), 2 Olfactory receptors (ORs) and 2 Chemosensory proteins (CSPs). Meanwhile, the female leg showed upregulation of 3 OBPs, 1 OR, 1 Gustatory receptor (GR) and 3 Mechanosensitive proteins (MSPs). An in-depth examination of the ultrastructure and molecular composition of the legs can elucidate its function in the reproductive behavior of G. cantor. Moremore, this investigation will serve as a cornerstone for subsequent research into the underlying behavioral mechanisms. [ABSTRACT FROM AUTHOR]

N 6-methyladenosine (m6A) is a dynamic and reversible epigenetic modification that is important in RNA translation, degradation, folding, splicing, and export. m6A levels and methylation patterns are changed in nonalcoholic fatty liver disease (NAFLD). m6A modification significantly promotes the development of NAFLD in terms of adipogenesis, lipid metabolism, inflammation, and insulin resistance. Novel m6A modification inhibitors may be a therapeutic strategy for the treatment of NAFLD. Nonalcoholic fatty liver disease (NAFLD) is the most common chronic liver disease worldwide, influencing numerous regulatory axes and extrahepatic vital organs. The molecular mechanisms that lead to the progression of NAFLD remain unclear and knowledge on the pathways causing hepatocellular damage followed by lipid accumulation is limited. Recently, a number of studies have shown that mRNA N 6-methyladenosine (m6A) modification contributes to the progression of NAFLD. In this review, we summarize current knowledge on m6A modification in the metabolic processes associated with NAFLD and discuss the challenges of and prospects for therapeutic avenues based on m6A regulation for the treatment of liver disease. [ABSTRACT FROM AUTHOR]

Computational modeling and investigation have become increasingly useful in assessing the hemodynamic and structural factors that contribute to aneurysm rupture, particularly when conventional clinical tools are inadequate. To this end, we conduct a study of a realistic internal carotid artery (ICA) under various working conditions using computational fluid dynamics. We analyze nine specific real ICA geometries in terms of coiling porosity and blood hematocrit, using a response surface model to evaluate 25 runs across selected geometrical parameters and treatment factors. The computational domain is created using computed tomography data from an actual patient, and we apply proposed boundary conditions to solve three-dimensional transient Navier–Stokes equations. By analyzing these cases, we try to understand how the sac section area, mean radius of the parent vessel, hematocrit, and coiling porosity interact and affect the risk of ICA rupture. We conduct an extensive study of the effects of sac section area and mean radius of the parent vessel on blood hemodynamics, examining several factors and comparing them at the peak systolic time instant, including wall shear stress (WSS), oscillatory shear index (OSI), pressure distributions, and velocity. Our results show that a 12% increase in the mean radius of the parent vessel reduced the maximum OSI value by approximately 50%, while a 120% increase in the sac section area decreases WSS on the aneurysm wall by up to 300%. These findings demonstrate the potential of computational modeling to provide valuable insight into the complex factors that influence aneurysm rupture, especially in cases where traditional clinical tools may be insufficient. [ABSTRACT FROM AUTHOR]

Background: Dihydromyricetin (DMY) is a natural flavonoid with anti-nonalcoholic steatohepatitis (NASH) activity. However, the effects of DMY on the composition of lipids and bile acids (BAs) in serum, and gut microbiota (GM) in ileum of mice with NASH are not clear. Methods: After male C57BL/6 mice was fed with methionine and choline deficiency (MCD) diet and simultaneously administered with DMY (300 mg/kg/day) by gavage for 8 weeks, the pathological changes of liver tissue were observed by Oil Red O, hematoxylin eosin and Masson staining, the levels of serum alaninea minotransferase, aspartate aminotransferase and liver triglyceride, malonic dialdehyde were detected by the detection kits, the composition and contents of serum lipids and BAs were detected by Liquid Chromatograph-Mass Spectrometry, the mRNA levels of hepatic BAs homeostasis-related genes were detected by RT-qPCR, and microbiological diversity in ileum was analyzed by 16S rDNA sequencing. Results: The results showed that the significant changes including 29 lipids, 4 BAs (23-nor-deoxycholic acid, ursodeoxycholic acid, 7-ketodeoxycholic acid and cholic acid), 2 BA transporters (Mrp2 and Oatp1b2) and 8 GMs between MCD and DMY groups. Among them, DMY treatment significantly down-regulated 21 lipids, 4 BAs mentioned above, the ratio of Firmicutes/Bacteroidota and the abundance of Erysipelotrichaceae, Faecalibacuium, significantly up-regulated 8 lipids and 5 GMs (Verrucomicrobiota, Bacteroidota, Actinobacteria, Akkermansiaceae and Akkermansia). Conclusions: The results suggested that DMY may alleviate MCD diet-induced NASH through decreasing the serum levels of toxic BAs which regulated by liver Oatp1b2 and Mrp2, regulating the metabolism of related lipids, and up-regulating intestinal probiotics (Actinobacteria and Verrucomicrobiota at the phylum level; Akkermansiaceae at the family level; Akkermansiaat at the genus level) and inhibiting intestinal harmful bacteria (Firmicutes at the phylum level; Erysipelotrichaceae at the family level; Faecalibaculum at the genus level). [ABSTRACT FROM AUTHOR]

To elucidate the relationship between different isothermal processes and toughness of 20Mn2Si2Cr bainite high‐strength steel, conventional austempering (AT), multistep austempering (MAT), and inverse multistep austempering (IMAT) heat treatment processes at different temperatures are conducted. The changes of properties with different processes are analyzed according to microstructure characteristics. The results indicate that the fraction of retained austenite is changed slightly for all processes, while the carbon content in retained austenite is from 1.03 wt% (AT‐1) to 1.24 wt% (IMAT‐2). Toughness is improved significantly by adjusting process parameters, but strength is not greatly affected at the same time. The toughness of AT‐1 specimens is only 98 J cm−2, and it increases to 123 J cm−2 (AT‐2 specimens) by reducing isothermal temperature. Compared with AT‐1 specimens, toughness of MAT‐2 and IMAT‐2 specimens is increased by about ≈40% (138 J cm−2) and ≈65% (162 J cm−2), respectively. It is also noteworthy that the tensile strength varies in a small range from 998 to 1080 MPa. The improvement in properties is severely related to modification of microstructure. [ABSTRACT FROM AUTHOR]

FOXP1, known as a Forkhead-box (FOX) family protein, plays an important role in human tumorigenesis. However, the function and molecular mechanism of FOXP1 in pancreatic cancer (PC) remain unclear. Here, we report that PC patients with FOXP1 overexpression had a higher survival rate compared to patients with low- FOXP1 expression. Additionally, high expression of FOXP1 can markedly inhibit the growth of pancreatic cancer in vivo and in vitro, whereas low expression of FOXP1 effectively promoted the tumorigenesis. Mechanistically, FOXP1 could directly bind the IRF1 promoter, which triggered the transcriptional activity of IRF1. Taken together, FOXP1 suppressed PC growth via IRF1-dependent manner, serving as a potential prognostic biomarker for patients with PC. [ABSTRACT FROM AUTHOR]

Single-cell RNA sequencing (scRNA-seq) clustering and labelling methods are used to determine precise cellular composition of tissue samples. Automated labelling methods rely on either unsupervised, cluster-based approaches or supervised, cell-based approaches to identify cell types. The high complexity of cancer poses a unique challenge, as tumor microenvironments are often composed of diverse cell subpopulations with unique functional effects that may lead to disease progression, metastasis and treatment resistance. Here, we assess 17 cell-based and 9 cluster-based scRNA-seq labelling algorithms using 8 cancer datasets, providing a comprehensive large-scale assessment of such methods in a cancer-specific context. Using several performance metrics, we show that cell-based methods generally achieved higher performance and were faster compared to cluster-based methods. Cluster-based methods more successfully labelled non-malignant cell types, likely because of a lack of gene signatures for relevant malignant cell subpopulations. Larger cell numbers present in some cell types in training data positively impacted prediction scores for cell-based methods. Finally, we examined which methods performed favorably when trained and tested on separate patient cohorts in scenarios similar to clinical applications, and which were able to accurately label particularly small or under-represented cell populations in the given datasets. We conclude that scPred and SVM show the best overall performances with cancer-specific data and provide further suggestions for algorithm selection. Our analysis pipeline for assessing the performance of cell type labelling algorithms is available in https://github.com/shooshtarilab/scRNAseq-Automated-Cell-Type-Labelling. [ABSTRACT FROM AUTHOR]

Background: Gestational diabetes mellitus (GDM) is the most common complication during pregnancy, occurring under the combined action of environmental and genetic factors. Genetic variants of glucagon-like peptide-1 receptor (GLP-1R) have been reported to affect insulin secretion and susceptibility to type 2 diabetes. This study aimed to explore the role of GLP-1R polymorphisms in GDM and glucose metabolism. Methods: A two-center nested case‒control study was designed, including 200 pregnant women with GDM and 200 pregnant women without GDM genotyped for five tag SNPs of GLP-1R using Sanger sequencing. Logistic regression was used to evaluate the relationship between GLP-1R polymorphisms and GDM risk. Glucose and insulin concentrations were measured based upon the 75 g oral glucose tolerance test (OGTT). Beta cell function of different genotypes was estimated with the 60 min insulinogenic index (IGI60) and OGTT-derived disposition index (DI). Results: Mutant genotype AG + GG of tag SNP rs6458093 nominally increased GDM risk (p = 0.049), especially among subjects younger than 35 years (p = 0.024) and with BMI no less than 24 (p = 0.041), after adjusting for confounders. Meanwhile, compared with subjects with wild genotype AA, subjects with genotype AG + GG of rs6458093 also showed nominally significantly lower IGI60 (p = 0.032) and DI (p = 0.029), as well as significantly higher 75 g OGTT-based 1 h glucose load plasma glucose levels (p = 0.045). Moreover, the mutant heterozygous genotype GA of tag SNP rs3765467 nominally decreased GDM risk among subjects older than 35 years (p = 0.037) but showed no association with insulin secretion and glucose homeostasis. Conclusions: Tag SNP rs6458093 of GLP-1R was nominally associated with increased GDM risk and affected beta cell function and postprandial glucose metabolism, while tag SNP rs3765467 of GLP-1R was nominally associated with decreased GDM risk, providing evidence for molecular markers and etiological study of GDM. [ABSTRACT FROM AUTHOR]

Besides the traditional roles of HBA1 and HBB, recent findings suggest that hemoglobin genes may have roles in other contexts. In the present study, we aim to investigate a possible tumor-suppressor role of HBA1 and HBB in acute myeloid leukemia. Quantitative real-time PCR (RT-qPCR) was performed to detect the expression levels of HBA1 and HBB in acute myeloid leukemia patients and AML cell lines. The transfected cells were analyzed for Cell Counting Kit-8 (CCK-8), apoptosis, and cell cycle assay. HBA1 and HBB genes were significantly decreased in acute myeloid leukemia patients and AML cell lines. Furthermore, in vitro approaches showed that overexpression of HBA1 and HBB inhibited proliferation, induced cell apoptosis, and blocked cell cycle process at the G2/M phase in K562 cells. Our data indicated that HBA1 and HBB genes may be potential tumor-suppressor genes in acute myeloid leukemia. [ABSTRACT FROM AUTHOR]

Omeprazole is commonly prescribed to obese patients and patients after laparoscopic sleeve gastrectomy (LSG). The pharmacokinetics of oral omeprazole after LSG are still unknown. Therefore, the aim of this study was to investigate the pharmacokinetics of oral omeprazole in obese patients before and after LSG. A total of 331 blood samples were collected from 62 obese patients preoperatively (visit 1) followed by 41 patients 7 days post-LSG (visit 2) and 20 patients 1 month post-LSG (visit 3). Population pharmacokinetic analysis was performed using NONMEM to characterize the effect of LSG on omeprazole absorption and disposition. A one-compartment model with 12 transit absorption compartments and linear elimination successfully described the data. Compared with pre-surgery, the oral omeprazole time to maximum plasma concentration (Tmax) was reduced and maximum plasma concentration (Cmax) was higher, but the apparent clearance (CL/F) and area under the plasma concentration–time curve (AUC) were unchanged 7 days and 1 month after surgery. In addition, the CYP2C19 genotype and liver function exhibited a significant influence on omeprazole CL/F. LSG increased the rate of omeprazole absorption but did not affect omeprazole exposure. A dose of 20 mg omeprazole once daily may be adequate for relieving gastrointestinal tract discomfort at short-term follow-up post-LSG. [ABSTRACT FROM AUTHOR]

A high-efficiency regeneration and genetic transformation system is indispensable for generating desirable traits in important trees such as Eucalyptus. However, lower regeneration efficiency is common for most varieties because of the recalcitrance of this genus. Here, a stable and highly efficient in vitro organogenesis protocol and Agrobacterium-mediated genetic transformation system of Eucalyptus were developed, and transgenic plants were obtained. In this protocol, the preferred explants were the top and middle stem internodes from in vitro micro-shoots of the E. urophylla × E. tereticornis hybrid. Modified Woody Plant Medium (mWPM) containing 0.025 mg·L-1 thidiazuron (TDZ) and 0.10 mg·L-1 indole-3-butyric acid (IBA) was used to induce multiple adventitious buds that allowed 85.6% shoot formation. The binary vector pBI121 carrying the neomycin phosphotransferase II (nptII) and β-glucuronidase (uidA) genes was applied for transformation. The preferred internodes were precultured for 0 to 3 d and infected with A. tumefaciens strain GV3101 grown to a bacterial density of 0.5 (OD600). Then, they were transferred to a co-culture medium supplemented with 50 μM acetosyringone (AS) and co-cultured for 2 d in the dark. The transgenic adventitious buds formed in regeneration medium, which was replaced by the same medium with a 2-wk subculture interval through kanamycin selection. Using the aforementioned method, transgenic plantlets can be obtained within 3 mo with a transformation frequency of 3.8%, which was verified by polymerase chain reaction amplification (PCR) and histochemical analysis of GUS activity. The constructed genetic transformation system will lay a foundation for mining gene functions and further molecular breeding of Eucalyptus. [ABSTRACT FROM AUTHOR]

Patients with TP53 mutations represent a high-risk group, and detection for TP53 mutations in MPN patients should be considered [[2]]. Two out of 30 MPN patients carried double-positive mutation in TP53 mutations and MPL204F. Dear Editor: Myeloproliferative neoplasms (MPN) are classical BCR-ABL1-negative clonal haematopoietic disorders, which include polycythaemia vera (PV), essential thrombocythaemia (ET) and primary myelofibrosis (PMF).They are characterized by the presence of somatic driver mutations (JAK2 V617F or exon 12, CALR exon 9 and MPL exon10). However, a subset (10-15%) of MPN Ph- patients, the so-called triple-negative (TN), do not have driver mutations but may have other mutations that might be associated with myeloproliferative neoplasms [[2]]. [Extracted from the article]

Pulmonary hypertension (PH) is a life-threatening pathological state with elevated pulmonary arterial pressure, resulting in right ventricular failure and heart functional failure. Analyses of human samples and rodent models of pH support the infiltration of various immune cells, including neutrophils, mast cells, dendritic cells, B-cells, T-cells, and natural killer cells, to the lungs and pulmonary perivascular regions and their involvement in the PH development. There is evidence that macrophages are presented in the pulmonary lesions of pH patients as first-line myeloid leucocytes. Macrophage accumulation and presence, both M1 and M2 phenotypes, is a distinctive hallmark of pH which plays a pivotal role in pulmonary artery remodeling through various cellular and molecular interactions and mechanisms, including CCL2 and CX3CL1 chemokines, adventitial fibroblasts, glucocorticoid-regulated kinase 1 (SGK1), crosstalk with other immune cells, leukotriene B4 (LTB4), bone morphogenetic protein receptor 2 (BMPR2), macrophage migration inhibitory factor (MIF), and thrombospondin-1 (TSP-1). In this paper, we reviewed the molecular mechanisms and the role of immune cells and responses are involved in PH development. We also summarized the polarization of macrophages in response to different stimuli and their pathological role and their infiltration in the lung of pH patients and animal models. [ABSTRACT FROM AUTHOR]

Recently, interleukin‐38 (IL‐38) was identified as an important anti‐inflammatory and immunosuppressive factor, but its functional role in temporomandibular joint (TMJ) inflammation remains unknown. This study aimed to elucidate how IL‐38 affects chondrocytes and the underlying mechanism that contributes to anti‐inflammatory processes in the TMJ. Western blotting, quantitative real‐time PCR, enzyme‐linked immunosorbent assay, and immunofluorescence analysis were used to verify that IL‐38 has anti‐inflammatory effects on chondrocytes, and the related key pathways were analyzed by western blotting. SiRNA‐IL‐38, siRNA‐NLRP3, and MCC950 were used to investigate the mechanism underlying the anti‐inflammatory effects of IL‐38. Inflammation models were induced by injection of complete Freund's adjuvant in TMJ with mouse recombinant IL‐38 in in vivo studies. Histological and immunohistochemical analyses were used to investigate histological changes in the cartilage. The results showed that IL‐38 inhibited the expression of inflammatory cytokines and MMPs. IL‐38 limited inflammation by inhibiting the expression of MAPKs/NF‐κB and the NLRP3/caspase‐1 pathway. In vivo, IL‐38 reduced chondrocyte inflammation and limited cartilage degeneration. This study shows for the first time that IL‐38 plays a protective role in TMJ cartilage. IL‐38 exerts anti‐inflammatory effects through the NLRP3/caspase‐1 pathway and may be a promising agent for treating TMJ inflammation. [ABSTRACT FROM AUTHOR]

Abiotic stress is the main factor that severely limits crop growth and yield. NAC (NAM , ATAF1/2 and CUC2) transcription factors play an important role in dealing with various abiotic stresses. Here, we discovered the ZmSNAC13 gene in drought-tolerant maize lines by RNA-seq analysis and verified its function in Arabidopsis thaliana. First, its gene structure showed that ZmSNAC1 3 had a typical NAC domain and a highly variable C-terminal. There were multiple cis-acting elements related to stress in its promoter region. Overexpression of ZmSNAC13 resulted in enhanced tolerances to drought and salt stresses in Arabidopsis , characterized by a reduction in the water loss rate, a sustained effective photosynthesis rate, and increased cell membrane stability in leaves under drought conditions. Transcriptome analysis showed that a large number of differentially expressed genes regulated by overexpression of ZmSNAC13 were identified, and the main drought tolerance regulatory pathways involved were the ABA pathway and MAPK cascade signaling pathway. Overexpression of ZmSNAC13 promoted the expression of genes, such as PYL9 and DREB3 , thereby enhancing tolerance to adverse environments. Adaptability, while restraining genes expression such as WRKY53 and MPK3 , facilitates regulation of senescence in Arabidopsis and improves plant responses to adversity. Therefore, ZmSNAC13 is promising gene of interest for use in transgenic breeding to improve abiotic stress tolerance in crops. [ABSTRACT FROM AUTHOR]

The traditional photoacoustic cavity has the advantages of simple structure, low cost, and easy integration with optical cavity technology, so it has significant advantages in the measurement of the optical characteristics of respirable dust. In order to meet the demand of high-precision respirable dust measurements in practical applications, it is necessary to improve the measurement accuracy of respirable dust by traditional photoacoustic spectroscopy technology. Therefore, the structure size of the photoacoustic cavity was determined by theoretical and simulation analysis. A system for measuring respirable dust by photoacoustic spectroscopy was designed, which was applied to the atmospheric respirable dust detection simultaneously with the cavity ring-down spectroscopy system. The results showed that the correlation between the two systems was poor. Therefore, the three-layer back propagation neural network algorithm was used to correct the photoacoustic response values, and the measured value of the cavity ring-down spectroscopy system was used as the reference truth value. The calibration results showed that the output value of the neural network model was in good agreement with the reference true value: the slope was above 0.96. The results showed that the neural network algorithm could effectively improve the measurement accuracy of the photoacoustic spectroscopy system to respirable dust, improve the linearity, and reduce the detection error. [ABSTRACT FROM AUTHOR]

With the increased production, usage, and disposal of engineered nanoparticles (ENPs), there is growing concern over the fate of ENPs in the environment, their potential bioavailability and ecotoxicity. It is assumed that bioavailability and uptake into organisms depend on the environmental conditions as well as the physicochemical properties of ENPs, such as particle size or surface coating. A major sink for nanoparticles is expected to be sediments due to sorption and agglomeration processes. Accordingly, this study, investigated how different sizes (5 and 30 nm) and surface coatings of three different AuENPs based on citrate (AuCIT), mercaptoundecanoic acid (AuMUDA), and bovine serum albumin (AuBSA) affected the retention of ENPs in a sediment-water system and subsequent uptake into sediment-dwelling organism Lumbriculus variegatus (L. variegatus). Surface charge was found to be one of the factors affecting retention of the AuENPs in the sediment-water system. More negatively charged AuENPs had a higher mass fraction in the supernatant after 24 h exposure. Furthermore, the stability of AuENPs in the supernatant depended more on their zeta potential than particle size (5 nm vs. 30 nm). The surface coating was found to play an important role in the uptake (after depuration) of Au in L. variegatus, that is, AuBSA > AuCIT > AuMUDA. [ABSTRACT FROM AUTHOR]

Background: High-risk human papillomavirus (HR-HPV) infection is an important factor for the development of cervical cancer. HPV18 is the second most common HR-HPV after HPV16. Methods: In this study, MEGA11 software was used to analyze the variation and phylogenetic tree of HPV18 E6-E7 and L1 genes. The selective pressure to E6, E7 and L1 genes was estimated using pamlX. In addition, the B cell epitopes of L1 amino acid sequences and T cell epitopes of E6-E7 amino acid sequences in HPV18 were predicted by ABCpred server and IEDB website, respectively. Results: A total of 9 single nucleotide variants were found in E6-E7 sequences, of which 2 were nonsynonymous variants and 7 were synonymous variants. Twenty single nucleotide variants were identified in L1 sequence, including 11 nonsynonymous variants and 9 synonymous variants. Phylogenetic analysis showed that E6-E7 and L1 sequences were all distributed in A lineage. In HPV18 E6, E7 and L1 sequences, no positively selected site was found. The nonconservative substitution R545C in L1 affected hypothetical B cell epitope. Two nonconservative substitutions, S82A in E6, and R53Q in E7, impacted multiple hypothetical T cell epitopes. Conclusion: The sequence variation data of HPV18 may lay a foundation for the virus diagnosis, further study of cervical cancer and vaccine design in central China. [ABSTRACT FROM AUTHOR]

Photoacoustic spectroscopy technology is an important method to detect the concentration of trace gases, so it is of great significance to improve the detection accuracy of the photoacoustic spectroscopy system (PAS). In this paper, a multiple linear regression algorithm was proposed to correct the accuracy of the PAS based on the high-precision cavity ring-down spectroscopy measurement system. The results showed that the correlation coefficient R2 between the corrected values of the multiple linear regression model and the reference true values was 0.903. It can be seen that the algorithm can effectively improve the detection accuracy of the PAS. A comparative experiment was carried out with the long optical path differential absorption spectroscopy system (LP-DOAS) for measuring the NO2 concentration in an ambient atmosphere. The experimental results showed that the corrected PAS and the LP-DOAS had a good correlation in measuring the NO2 concentration, the slope of linear fitting was 1.012 ± 0.040, and the correlation coefficient was 0.948. [ABSTRACT FROM AUTHOR]

A seamless mode-switch control scheme for primary side regulation flyback with capacitorless self-adaptive startup is presented in this article to increase the system stability for full-load range and reduce the area cost. Instead of traditional soft-startup, a peak current of primary side (PCPS) control scheme without off-chip capacitor is adapted during the startup process and a homologous startup modeling is built. Including the traditional pulsewidth modulation (PWM), the pulse frequency modulation (PFM), and deep pulsewidth modulation (DPWM) are adapted to reduce the standby power at utralight load. Meanwhile, a seamless control scheme is proposed to assure the continuity among the PCPS, PWM, PFM, and DPWM mode switch. The controller chip is fabricated in 0.18 μm BCD process. The experiment results show that the startup time and overshoot voltage are, respectively, 35 ms and 4 V at 0.8 A load current, 48 ms, and 0.2 V at 0.008 A load current. The accuracy of output voltage is within ±0.98% under different input voltages and loads while the peak power efficiency of 88.52% is achieved. [ABSTRACT FROM AUTHOR]

Background: With the development of the technology of single-cell sequence, revealing homogeneity and heterogeneity between cells has become a new area of computational systems biology research. However, the clustering of cell types becomes more complex with the mutual penetration between different types of cells and the instability of gene expression. One way of overcoming this problem is to group similar, related single cells together by the means of various clustering analysis methods. Although some methods such as spectral clustering can do well in the identification of cell types, they only consider the similarities between cells and ignore the influence of dissimilarities on clustering results. This methodology may limit the performance of most of the conventional clustering algorithms for the identification of clusters, it needs to develop special methods for high-dimensional sparse categorical data. Results: Inspired by the phenomenon that same type cells have similar gene expression patterns, but different types of cells evoke dissimilar gene expression patterns, we improve the existing spectral clustering method for clustering single-cell data that is based on both similarities and dissimilarities between cells. The method first measures the similarity/dissimilarity among cells, then constructs the incidence matrix by fusing similarity matrix with dissimilarity matrix, and, finally, uses the eigenvalues of the incidence matrix to perform dimensionality reduction and employs the K-means algorithm in the low dimensional space to achieve clustering. The proposed improved spectral clustering method is compared with the conventional spectral clustering method in recognizing cell types on several real single-cell RNA-seq datasets. Conclusions: In summary, we show that adding intercellular dissimilarity can effectively improve accuracy and achieve robustness and that improved spectral clustering method outperforms the traditional spectral clustering method in grouping cells. [ABSTRACT FROM AUTHOR]

• The V–O layer spacing expanded from 4.35 to 13.58 Å. • PANI inserted as extra active sites can participate energy storage. • PANI inserted shields the charge of the V–O layer, improving kinetics. • The PANI@V 2 O 5 cathode for CIBs exhibits a high capacity up to 205 mAh·g−1. Calcium-ion batteries (CIBs) have attracted growing interest owing to abundant Ca resources and its high gravimetric capacity. However, potent electrostatic interactions between Ca2+ ions and host material, can lead to slow diffusion kinetics and crystal structure destabilization. A pre-intercalation strategy involving polyaniline (PANI) was employed in this study to enhance the cathode material performance of PANI@V 2 O 5 (PVO) for CIBs. PANI pre-intercalation improved both the diffusion kinetics and capacity by increasing the distance between the V-O layers (13.8 Å) and significantly enhancing the material conductivity. Meanwhile, the intercalation of PANI as extra active sites also can participate in the redox reaction, providing additional capacity. Moreover, density functional theory calculations demonstrated that the PANI intercalation improved the conductivity and relieved the electrostatic repulsion between Ca2+ ions and the V–O layer. Benefiting from a large layer spacing and dual active sites, PVO achieved a high specific capacity of 205 mAh g−1 at 100 mA g−1. This work provides insight into the mechanism of PANI intercalation to improve electrochemical performance, which sheds light on the rational design of organic–inorganic cathode materials for calcium ion batteries. [ABSTRACT FROM AUTHOR]

Complex diseases are associated with a set of genes (called disease genes), the identification of which can help scientists uncover the mechanisms of diseases and develop new drugs and treatment strategies. Due to the huge cost and time of experimental identification techniques, many computational algorithms have been proposed to predict disease genes. Although several review publications in recent years have discussed many computational methods, some of them focus on cancer driver genes while others focus on biomolecular networks, which only cover a specific aspect of existing methods. In this review, we summarize existing methods and classify them into three categories based on their rationales. Then, the algorithms, biological data, and evaluation methods used in the computational prediction are discussed. Finally, we highlight the limitations of existing methods and point out some future directions for improving these algorithms. This review could help investigators understand the principles of existing methods, and thus develop new methods to advance the computational prediction of disease genes. This article is categorized under:Technologies > Machine LearningTechnologies > PredictionAlgorithmic Development > Biological Data Mining [ABSTRACT FROM AUTHOR]

We address a learning-to-normalize problem by proposing Switchable Normalization (SN), which learns to select different normalizers for different normalization layers of a deep neural network. SN employs three distinct scopes to compute statistics (means and variances) including a channel, a layer, and a minibatch. SN switches between them by learning their importance weights in an end-to-end manner. It has several good properties. First, it adapts to various network architectures and tasks (see). Second, it is robust to a wide range of batch sizes, maintaining high performance even when small minibatch is presented (e.g., 2 images/GPU). Third, SN does not have sensitive hyper-parameter, unlike group normalization that searches the number of groups as a hyper-parameter. Without bells and whistles, SN outperforms its counterparts on various challenging benchmarks, such as ImageNet, COCO, CityScapes, ADE20K, MegaFace and Kinetics. Analyses of SN are also presented to answer the following three questions: (a) Is it useful to allow each normalization layer to select its own normalizer? (b) What impacts the choices of normalizers? (c) Do different tasks and datasets prefer different normalizers? We hope SN will help ease the usage and understand the normalization techniques in deep learning. The code of SN has been released at https://github.com/switchablenorms. [ABSTRACT FROM AUTHOR]

Pleural effusion is a common respiratory disease worldwide; however, rapid and accurate diagnoses of tuberculosis pleural effusion (TPE) and malignancy pleural effusion (MPE) remain challenging. Although extracellular vesicles (EVs) have been confirmed as promising sources of disease biomarkers, little is known about the metabolite compositions of its subpopulations and their roles in the diagnosis of pleural effusion. Here, we performed metabolomics and lipidomics analysis to investigate the metabolite characteristics of two EV subpopulations derived from pleural effusion by differential ultracentrifugation, namely large EVs (lEVs, pelleted at 20,000 × g) and small EVs (sEVs, pelleted at 110,000 × g), and assessed their metabolite differences between tuberculosis and malignancy. A total of 579 metabolites, including amino acids, acylcarnitines, organic acids, steroids, amides and various lipid species, were detected. The results showed that the metabolic profiles of lEVs and sEVs overlapped with and difference from each other but significantly differed from those of pleural effusion. Additionally, different type of vesicles and pleural effusion showed unique metabolic enrichments. Furthermore, lEVs displayed more significant and larger metabolic alterations between the tuberculosis and malignancy groups, and their differential metabolites were more closely related to clinical parameters than those of sEV. Finally, a panel of four biomarker candidates, including phenylalanine, leucine, phosphatidylcholine 35:0, and sphingomyelin 44:3, in pleural lEVs was defined based on the comprehensive discovery and validation workflow. This panel showed high performance for distinguishing TPE and MPE, particularly in patients with delayed or missed diagnosis, such as the area under the receiver-operating characteristic curve (AUC) >0.95 in both sets. We conducted comprehensive metabolic profiling analysis of EVs, and further explored the metabolic reprogramming of tuberculosis and malignancy at the level of metabolites in lEVs and sEVs, providing insight into the mechanism of pleural effusion, and identifying novel biomarkers for diagnosing TPE and MPE. [ABSTRACT FROM AUTHOR]

Purpose: Cisplatin resistance is still a serious problem in the clinic. However, the underlying mechanism remains unknown. In our study, we investigated cisplatin resistance by using the cisplatin-resistant cell line HCT116R. Methods: The HCT116 cell line, a colon cancer cell line, was purchased. Cell viability was determined using CCK-8 Assay Kit. The gene expression levels of MIR4435-2HG, Nrf2, and HO-1, and caspase activity were determined using qRT-PCR and Caspase 3 Assay Kit, respectively. Results: In this study, we found that the levels of the lncRNA MIR4435-2HG were dramatically increased in the cisplatin-resistant cell line HCT116R. Knockdown of MIR4435-2HG in HCT116R cells significantly restored the sensitivity to cisplatin, inhibited cell proliferation and promoted cell apoptosis. Furthermore, Nrf2 and HO-1 mRNA levels, as critical molecules in the oxidative stress pathway, were inhibited by siRNAs targeting MIR4435-2HG, suggesting that MIR4435-2HG-mediated cisplatin resistance occurs through the Nrf2/HO-1 pathway. Conclusion: Our findings demonstrate that the lncRNA MIR4435-2HG is a main factor driving the cisplatin resistance of HCT116 cells. [ABSTRACT FROM AUTHOR]

The toxic effects of various substances on Daphnia magna (D. magna) observed through traditional waterborne uptake may involve alterations to the nutritional quality of the contaminated algae and culture media. It is essential to find an alternative delivery method that will not affect the nutritional quality of D. magna's diet in order to elucidate the mechanisms of dietary metal toxicity. Therefore, this study examined the application of liposome encapsulation on the dietary toxicity of D. magna. Ag+-laden liposomes were prepared and the Ag encapsulation efficiency and inhibition effect on algae growth were examined. Then, acute and 14-day subchronic studies were performed to examine the effect of Ag+-laden liposomes on D. magna. The EC50 for the 24 h immobilization test was 10.59 µg/L for Ag+-laden liposomes and 3.07 µg/L for Ag+. In terms of subchronic effects, the estimated ECx values under the Ag+-laden liposome condition were always higher than the direct exposure condition. Furthermore, the bioaccumulation of Ag+-laden liposomes was about 1.68 times lower than direct exposure. Generally, Ag+-laden liposomes produced less efficient toxicity than direct exposure, e.g., lower D. magna mortality, production of more neonates, higher intrinsic rate of natural increase (rm), earlier time to first brood, and higher enzyme activities. [ABSTRACT FROM AUTHOR]

Objectives IL-37 has been identified as an important anti-inflammatory and immunosuppressive factor. This study was undertaken to explore how IL-37 affects M1/M2-like macrophage polarization and thus contributes to anti-inflammatory processes in the temporomandibular joint. Methods Western blotting, quantitative real-time PCR (qRT-PCR) and immunofluorescence were used to verify the IL-37-induced polarization shift from the M1 phenotype to the M2 phenotype, and the related key pathways were analysed by western blotting. Human chondrocytes were stimulated with M1-conditioned medium (CM) or IL-37-pretreated M1-CM, and inflammatory cytokines were detected. siRNA-IL-1R8 and MCC-950 were used to investigate the mechanism underlying the anti-inflammatory effects of IL-37. Complete Freund's adjuvant-induced and disc perforation-induced inflammation models were used for in vivo studies. Haematoxylin and eosin, immunohistochemical and safranin-O staining protocols were used to analyse histological changes in the synovium and condyle. Results Western blotting, qRT-PCR and immunofluorescence showed that IL-37 inhibited M1 marker expression and upregulated M2 marker expression. Western blotting and qRT-PCR showed that pretreatment with IL-37 suppressed inflammatory cytokine expression in chondrocytes. IL-37 inhibited the expression of NLRP3 and upregulated the expression of IL-1R8. Si-IL-1R8 and MCC-950 further confirmed that the anti-inflammatory properties of IL-37 were dependent on the presence of IL-1R8 and NLRP3. In vivo , IL-37 reduced synovial M1 marker expression and cartilage degeneration and increased M2 marker expression. Conclusion IL-37 shifting of the polarization of macrophages from the pro-inflammatory M1 phenotype to the beneficial anti-inflammatory M2 phenotype seems to be a promising therapeutic strategy for treating temporomandibular joint inflammation. [ABSTRACT FROM AUTHOR]

Numerous studies have solved the problem of monitoring statistical processes with complete samples. However, censored or incomplete samples are commonly encountered due to constraints such as time and cost. Adaptive progressive Type II hybrid censoring is a novel method with the advantages of saving time and improving efficiency. On the basis of this scheme, the problem of monitoring a downward shift in the quantiles of the inverted exponentiated half logistic distribution is considered. The conventional Shewhart control chart is insensitive to detect quantile shifts from faulty data processes that exhibit deviations from normality or symmetry. To overcome this limitation, Bootstrap control charts combining with the exponentially weighted moving average method based on the Bayesian estimation and maximum likelihood estimation are proposed, respectively. They are compared with the conventional Shewhart control chart via average run length through Monte-Carlo simulations. Finally, a real dataset related to the tensile strength of carbon fibers is employed to demonstrate the ascendancy of the Bootstrap control charts. [ABSTRACT FROM AUTHOR]

The highly conserved actin depolymerizing factor (ADF) plays an important role in plant growth, development and responses to biotic and abiotic stresses. A total of 72 ADF genes in Arabidopsis, wheat, rice and sorghum can be divided into four groups. The multicollinearity analysis revealed that the maize ADF gene family exhibited more collinearity events with closely related gramineous plants. Fifteen ADF genes in maize were screened from the latest database, and bioinformatics analysis showed that these ADF genes were distributed across seven chromosomes in maize. The gene structure of the ADF gene family in maize exhibits significant conservation and cluster consistency. The promoter region contains rich regulatory elements that are involved in various regulations related to growth, development and adverse stresses. The drought-tolerant ZmADF5 gene in maize was further studied, and it was found that the allelic variations in ZmADF5 were mainly concentrated in its promoter region. A superior haplotype, with drought tolerance, was identified by candidate-gene association analysis of 115 inbred lines. By comparing the phenotypes of anthesis silking interval, grain yield and ear height, it was found that Hap2 performed better than Hap1 under drought stress. This study provides a theoretical reference for understanding the function of the ADF gene family and proposes further investigation into the role of ZmADF5 in abiotic-stress tolerance. [ABSTRACT FROM AUTHOR]

The Wilms' tumor 1 (WT1) gene is an important regulatory molecule that plays a vital role in cell growth and development. Initially, knowledge of WT1 was mostly limited to Wilms' tumor. Over the past years, numerous studies have shown that WT1 is aberrant expressed or mutated in hematopoietic malignancies, including acute leukemia (AL), myelodysplastic syndrome (MDS) and chronic myelogenous leukemia (CML). Currently, many studies focus on exploring the role of WT1 in hematopoietic malignancies. Such studies improve the understanding of hematopoietic malignancies, and the collection of data about WT1 expression or mutation in hematopoietic malignancies over the past years can facilitate the risk stratification of hematopoietic malignancies. In this review, we highlight the important role of WT1 in hematopoietic malignancies, discuss its potential clinical applications as a minimal residual disease (MRD) and prognostic biomarker, and evaluate the possible therapy target of WT1 in hematopoietic malignancies. [ABSTRACT FROM AUTHOR]

Pleural effusion is a common respiratory disease worldwide; however, rapid and accurate diagnoses of tuberculosis pleural effusion (TPE) and malignancy pleural effusion (MPE) remain challenging. Although extracellular vesicles (EVs) have been confirmed as promising sources of disease biomarkers, little is known about the metabolite compositions of its subpopulations and their roles in the diagnosis of pleural effusion. Here, we performed metabolomics and lipidomics analysis to investigate the metabolite characteristics of two EV subpopulations derived from pleural effusion by differential ultracentrifugation, namely large EVs (lEVs, pelleted at 20,000 × g) and small EVs (sEVs, pelleted at 110,000 × g), and assessed their metabolite differences between tuberculosis and malignancy. A total of 579 metabolites, including amino acids, acylcarnitines, organic acids, steroids, amides and various lipid species, were detected. The results showed that the metabolic profiles of lEVs and sEVs overlapped with and difference from each other but significantly differed from those of pleural effusion. Additionally, different type of vesicles and pleural effusion showed unique metabolic enrichments. Furthermore, lEVs displayed more significant and larger metabolic alterations between the tuberculosis and malignancy groups, and their differential metabolites were more closely related to clinical parameters than those of sEV. Finally, a panel of four biomarker candidates, including phenylalanine, leucine, phosphatidylcholine 35:0, and sphingomyelin 44:3, in pleural lEVs was defined based on the comprehensive discovery and validation workflow. This panel showed high performance for distinguishing TPE and MPE, particularly in patients with delayed or missed diagnosis, such as the area under the receiver‐operating characteristic curve (AUC) >0.95 in both sets. We conducted comprehensive metabolic profiling analysis of EVs, and further explored the metabolic reprogramming of tuberculosis and malignancy at the level of metabolites in lEVs and sEVs, providing insight into the mechanism of pleural effusion, and identifying novel biomarkers for diagnosing TPE and MPE. [ABSTRACT FROM AUTHOR]

To further investigate fresh‐keeping effect of fucoidan from Laminaria japonica (FL) on postharvest strawberry, this study assessed the degradation kinetics of antioxidant capacity and antioxidants in cold‐stored strawberry coated with FL by layer‐by‐layer method. Fruit coated with FL were subjected to determine antioxidant capacity and endogenous antioxidants contents during the scheduled cold‐storage period. Results showed that FL obviously suppressed degradation rates of both antioxidant capacity and contents of phenolic compounds and ascorbic acid, which were demonstrated by reduced rate constant and increased half‐time periods of antioxidant activity and antioxidants in FL‐coated strawberry during cold storage. High Pearson correlation coefficients and significant differences among antioxidant‐associated indicators indicated that there was a close relationship between antioxidant activity degradation and antioxidants degradation in strawberry fruit during cold‐storage period. FL treatment inhibited degradation of total polyphenol and ascorbic acid which ultimately controlled degradation of antioxidant capacity in cold‐storage strawberry. Practical applications: Laminaria japonica rich in brown seaweed may be developed to be a natural and nontoxic preservative for postharvest strawberry or other fruit and vegetables. [ABSTRACT FROM AUTHOR]

Background: Disease gene prediction is a critical and challenging task. Many computational methods have been developed to predict disease genes, which can reduce the money and time used in the experimental validation. Since proteins (products of genes) usually work together to achieve a specific function, biomolecular networks, such as the protein-protein interaction (PPI) network and gene co-expression networks, are widely used to predict disease genes by analyzing the relationships between known disease genes and other genes in the networks. However, existing methods commonly use a universal static PPI network, which ignore the fact that PPIs are dynamic, and PPIs in various patients should also be different. Results: To address these issues, we develop an ensemble algorithm to predict disease genes from clinical sample-based networks (EdgCSN). The algorithm first constructs single sample-based networks for each case sample of the disease under study. Then, these single sample-based networks are merged to several fused networks based on the clustering results of the samples. After that, logistic models are trained with centrality features extracted from the fused networks, and an ensemble strategy is used to predict the finial probability of each gene being disease-associated. EdgCSN is evaluated on breast cancer (BC), thyroid cancer (TC) and Alzheimer's disease (AD) and obtains AUC values of 0.970, 0.971 and 0.966, respectively, which are much better than the competing algorithms. Subsequent de novo validations also demonstrate the ability of EdgCSN in predicting new disease genes. Conclusions: In this study, we propose EdgCSN, which is an ensemble learning algorithm for predicting disease genes with models trained by centrality features extracted from clinical sample-based networks. Results of the leave-one-out cross validation show that our EdgCSN performs much better than the competing algorithms in predicting BC-associated, TC-associated and AD-associated genes. de novo validations also show that EdgCSN is valuable for identifying new disease genes. [ABSTRACT FROM AUTHOR]

The dense NaZr 2 (PO 4) 3 (NZP) ceramics were successfully prepared by a microwave sintering process with x wt.% ZnO as a sintering aid (where x = 0, 0.5, 1.0, 2.0 and 3.0). The effects of ZnO additive on the crystal structure, microstructure and sintering behavior of as-prepared NZP ceramics were systematically investigated. The single NZP phase can be achieved in the wide temperature range of 900–1200 °C holding for 2 h by microwave-sintering technology. The addition of ZnO sintering aid would not noticeably change the crystal structure of NZP. Importantly, ZnO additive significantly promoted the densification and 1.0 wt% ZnO-added sample possessed the maximum relative density of 96.5% after sintering at 1100 °C, considerably higher than that of pure NZP sample. Besides, the Vickers hardness of the above sample could attain near 800 MPa, which is about four times as hard as the pure NZP ceramics without ZnO additive. It was suggested that the combination of microwave sintering with appropriate addition of ZnO sintering aid would provide a convenient and efficient method for rapid fabrication of dense NZP ceramics. [ABSTRACT FROM AUTHOR]

Background Prescribing opioids for chronic noncancer pain (CNCP) has been strictly regulated in Taiwan. This study was undertaken to survey pain and non-pain related physicians' knowledge, attitudes, and practices regarding prescribing opioids for CNCP. Methods A questionnaire survey was conducted in this comparison study. All 66 physicians who were treating officially registered CNCP outpatients were visited and completed anonymous questionnaires. The other physicians (anesthesiologists, oncologists, and non-pain physicians) were surveyed by a mailed questionnaire. Results A total of 266 (75%) questionnaires were received from 355 board-certified physicians. More CNCP physicians (81.8%) and anesthesiologists (69.7%) had received prior CNCP-related training courses than had oncologists (21.2%) and non-pain physicians (10.3%). Varied proportions of physicians by type were unfamiliar with the Taiwan opioid regulations (16.7–86.8%) and would accordingly skip or reduce dosage of opioid prescriptions (27.3–73.5%). In addition, non-pain physicians had a significantly lower knowledge level, more negative attitudes, and greater hesitation about prescribing opioids compared to the pain-related physicians (P  < 0.001). CNCP physicians who had received CNCP-related training courses had a higher knowledge score than did those not receiving training (P  = 0.002). Overall, the leading barriers for prescribing opioids were inadequate knowledge of pain management (76%), physician reluctance (73%), and family reluctance (78%). Conclusion There are substantial knowledge gaps, negative attitudes, and hesitation toward prescribing long-term opioids for CNCP patients by physicians in Taiwan, suggesting that efforts are needed to improve postgraduate education regarding adequate opioid management for CNCP. [ABSTRACT FROM AUTHOR]

Motivation Computationally predicting disease genes helps scientists optimize the in-depth experimental validation and accelerates the identification of real disease-associated genes. Modern high-throughput technologies have generated a vast amount of omics data, and integrating them is expected to improve the accuracy of computational prediction. As an integrative model, multimodal deep belief net (DBN) can capture cross-modality features from heterogeneous datasets to model a complex system. Studies have shown its power in image classification and tumor subtype prediction. However, multimodal DBN has not been used in predicting disease–gene associations. Results In this study, we propose a method to predict disease–gene associations by multimodal DBN (dgMDL). Specifically, latent representations of protein-protein interaction networks and gene ontology terms are first learned by two DBNs independently. Then, a joint DBN is used to learn cross-modality representations from the two sub-models by taking the concatenation of their obtained latent representations as the multimodal input. Finally, disease–gene associations are predicted with the learned cross-modality representations. The proposed method is compared with two state-of-the-art algorithms in terms of 5-fold cross-validation on a set of curated disease–gene associations. dgMDL achieves an AUC of 0.969 which is superior to the competing algorithms. Further analysis of the top-10 unknown disease–gene pairs also demonstrates the ability of dgMDL in predicting new disease–gene associations. Availability and implementation Prediction results and a reference implementation of dgMDL in Python is available on https://github.com/luoping1004/dgMDL. Supplementary information Supplementary data are available at Bioinformatics online. [ABSTRACT FROM AUTHOR]

This paper presents a high-efficiency boost converter with a wide input range and a start-up strategy of sharing main power NMOS which can start-up at an input voltage of 700 mV. A burst mode with boundary conduction mode (BMBCM) control is utilized in the proposed boost converter to achieve high efficiency across the wide input power range. A method is also suggested to determine the optimal peak inductor current for a given input range. Compared to other start-up strategies, the proposed start-up circuit reduces chip area by sharing the main power NMOS with the normal operation mode, eliminating the need for an additional start-up power transistor. A new ultra-low-power voltage detection circuit is used to control the start-up process. The proposed boost converter is designed and fabricated in a 180 nm BCD process with an active chip area of only 0.33 mm2. The circuit achieves a peak efficiency of 94.8% at an input voltage of 3 V and an output voltage of 3.6 V, while maintaining an efficiency of at least 65.9% across the input power range of 7 μW to 300 mW. [ABSTRACT FROM AUTHOR]

The apparent viscosity, rheology, resistance and residual resistance coefficients, microstructure and hydrodynamic radius of polymer solution after shearing by well transition zone shear simulation experiment device were investigated with hydrophobic polymer AP-P4 under different water absorption strength conditions. The results showed that the polymer AP-P4 solution lost up to 61.4% of viscosity and reduced more than 40.0% of its ability to build up the drag and residual drag coefficients with the increase of water absorption strength after shearing by the well ground transition zone, but the reduction of its ability to build up the residual drag coefficient was smaller than the reduction of its ability to build up the drag coefficient. The lower the energy storage modulus and loss modulus of the polymer solution, the more severely the microstructure is disrupted, and the smaller the hydrodynamic radius. [ABSTRACT FROM AUTHOR]

Omics techniques develop quickly and have made a great contribution to disease study. Omics data are usually complex. How to analyze the data and mine important information has been a key part in omics research. To study the nature of disease mechanisms systematically, we propose a new data analysis method to define the network biomarkers based on horizontal comparison (DNB-HC). DNB-HC performs molecule horizontal relationships to characterize the physiological status and differential network analysis to screen the biomarkers. We applied DNB-HC to analyze a large-scale metabolomics data, which contained 550 samples from a nested case-control hepatocellular carcinoma (HCC) study. A network biomarker was defined, and its areas under curves (AUC) in the receiver-operating characteristic (ROC) analysis for HCC discrimination were larger than those defined by six efficient feature selection methods in most cases. The effectiveness was further corroborated by another nested HCC dataset. Besides, the performance of the defined biomarkers was better than that of α-fetoprotein (AFP), a commonly used clinical biomarker for distinguishing HCC from high-risk population of liver cirrhosis in other two independent metabolomics validation sets. All and 90.3% of the AFP false-negative patients with HCC were correctly diagnosed in these two sets, respectively. The experimental results illustrate that DNB-HC can mine more important information reflecting the nature of the research problems by studying the feature horizontal relationship systematically and identifying effective disease biomarkers in clinical practice. [ABSTRACT FROM AUTHOR]

Sodium zirconium phosphate (NZP) was synthesized by microwave-assisted solid-state reaction method with addition of x wt.% excess Na2CO3 powders (where x = 0, 2.5, 5, 7.5, and 10). The effects of the synthesis temperature and the excess sodium content on the phase compositions of the resultant samples were systematically investigated. XRD and Raman results showed that pure NZP phase could be synthesized successfully at 1100 °C for 2 h when 5 wt.% of excess sodium was introduced. Comparing with the traditional solid-state reaction method, the microwave-assisted solid-state method with the addition of appropriate excess sodium was beneficial to the synthesis of pure NZP phase, which would provide a new idea of achieving the low-temperature rapid synthesis of compounds of NZP family. [ABSTRACT FROM AUTHOR]

Abstract In this paper, we study the problem of discovering and learning sensational episodes of news events. A sensational episode of news events is in the form of lhs → rhs , where lhs is an antecedent event, rhs is a consequent event, and rhs often happens shortly after lhs. Such pairs of co-occurring news events within short period, while not necessarily bearing causal relationship between each other, are possible essential to media since they deliberately seek and broadcast examples of uncommon events to fascinate crowd attentions. First, to find all frequent episodes, we propose an efficient algorithm, MEELO, which significantly outperforms conventional algorithms. There can be a large number of frequent episodes. We rank them by their sensational effect from the perspectives of news audience, through learning from manually labeled examples. Instead of limiting ourselves to any individual subjective measure of sensational effect, we utilize a learning-to-rank approach that exploits multiple features to capture the sensational effect of a news episode from various aspects. NLP tools combined with knowledge bases are used in extracting and aggregating news events from news text. Experiments on real data verify our approach’s efficiency and effectiveness. [ABSTRACT FROM AUTHOR]

This Letter presents a high‐performance self‐biased and all‐in‐one voltage and current reference without BJT and V–I converter exploiting the zero‐temperature‐coefficient point of the N‐type MOSFET. With the help of the low‐temperature‐coefficient resistors and the self‐biased two‐stage OTA structure, the all‐in‐one reference can achieve the average temperature coefficients of 6.6 and 34 ppm/°C of voltage and current reference from −40 to 125 °C, respectively. Meanwhile, the line sensitivities are 0.08%/V and 0.23%/V of voltage and current reference. And the power supply rejection ratio of the voltage reference is −93 dB@100 Hz with the power consumption of 12.6 μW@tt corner and VDD = 2.5 V. The reference circuit is realized in a standard 180 nm CMOS process with the area of 0.0621 mm × mm. [ABSTRACT FROM AUTHOR]

[Display omitted] • IL-38 inhibits macrophage M1 polarization by suppressing GLUT-1 expression. • IL-38 has a protective effect on chondrocytes by suppressing macrophage M1 polarization. • IL-38 improves CFA-induced mouse TMJ inflammation by inhibiting synovial macrophage M1 polarization through GLUT-1 inhibition in vivo. Interleukin (IL)-38 was discovered as an anti-inflammatory factor. However, IL-38′s role in M1 macrophage polarization in the temporomandibular joint (TMJ) and the related mechanism are still unclear. We aimed to explore the effect and the mechanism of IL-38 on synovial inflammation in the TMJ in this study. The expression of IL-38 in the TMJ synovium and macrophages was determined using immunohistochemistry (IHC) and Western blotting (WB). M1 macrophage polarization was induced by LPS, the macrophages were pre-treated with IL-38, and the levels of inflammatory markers associated with M1 macrophages were measured. To assess the mechanism of IL-38, small-interfering RNA (siRNA)‐GLUT-1 and STF31 were administered to macrophages, and the affected pathways were identified by WB. The effect of macrophage-conditioned medium (CM) on chondrocyte function was also determined. Finally, a mouse model of CFA‐induced TMJ inflammation was established. Histological staining and IHC were used to determine the effect of IL-38. IL-38 was detected at high levels in macrophages after lipopolysaccharide (LPS) challenge, and IL-38 downregulated M1 macrophage-related proinflammatory markers (iNOS, IL-6, TNF-α, and COX-2) in vitro. IL-38 suppressed M1 polarization by inhibiting GLUT-1 expression, NF-κB signaling, and MAPK signaling. Intriguingly, CM from macrophages that were pretreated with IL-38 and STF31 decreased inflammatory protein expression in chondrocytes. In addition, intra-articular injection of recombinant IL-38 ameliorated synovial inflammation in the TMJ by inhibiting M1 macrophage polarization and suppressing cartilage inflammation in vivo. IL-38 is a novel anti-inflammatory factor that contributes to alleviating TMJ inflammation by inhibiting macrophage M1 polarization, thereby ameliorating chondrocyte inflammation and restoring TMJ homeostasis. [ABSTRACT FROM AUTHOR]

High tolerance to inhibitors is crucial for microorganisms and difficult to achieve by manipulating single genes because strain tolerance involves multiple genes and several complicated regulation mechanisms. The present study demonstrated that irrE gene from Deinococcus radiodurans R1 promoted the furfural resistance of Saccharomyces cerevisiae through directed evolution. Compared to the wild-type strain, the FR mutant not only showed improved tolerance to single- or multi- inhibitors (furfural, 5-hydroxymethylfurfural, formic and acetic acid), but also obtained better ability of eliminating reactive oxygen species. Consequently, batch fermentation of the FR mutant in synthetic medium (200 g/L glucose and 2.0 g/L furfural) resulted in an 37% increase in ethanol productivity, although ethanol titer (∼88 g/L) was comparable to that of the control. This study provides the first evidence that an exogenous global regulator can improve the stress tolerance of yeast, which is significant for production of industrial products from lignocellulose by S. cerevisiae . [ABSTRACT FROM AUTHOR]

We propose a deep convolutional neural network (CNN) for face detection leveraging on facial attributes based supervision. We observe a phenomenon that part detectors emerge within CNN trained to classify attributes from uncropped face images, without any explicit part supervision. The observation motivates a new method for finding faces through scoring facial parts responses by their spatial structure and arrangement. The scoring mechanism is data-driven, and carefully formulated considering challenging cases where faces are only partially visible. This consideration allows our network to detect faces under severe occlusion and unconstrained pose variations. Our method achieves promising performance on popular benchmarks including FDDB, PASCAL Faces, AFW, and WIDER FACE. [ABSTRACT FROM AUTHOR]