Exploring Novel Fentanyl Analogues Using a Graph-Based Transformer Model.

The structures of fentanyl and its analogues are easy to be modified and few types have been included in database so far, which allow criminals to avoid the supervision of relevant departments. This paper introduces a molecular graph-based transformer model, which is combined with a data augmentation method based on substructure replacement to generate novel fentanyl analogues. 140,000 molecules were generated, and after a set of screening, 36,799 potential fentanyl analogues were finally obtained. We calculated the molecular properties of 36,799 potential fentanyl analogues. The results showed that the model could learn some properties of original fentanyl molecules. We compared the generated molecules from transformer model and data augmentation method based on substructure replacement with those generated by the other two molecular generation models based on deep learning, and found that the model in this paper can generate more novel potential fentanyl analogues. Finally, the findings of the paper indicate that transformer model based on molecular graph helps us explore the structure of potential fentanyl molecules as well as understand distribution of original molecules of fentanyl.

Dual-frequency resonant coil design for low-γ X-nuclear and proton magnetic resonance imaging at ultrahigh fields.

Low-γ X-nuclear MRS and imaging have played a key role in studying metabolism and physiopathology, especially at ultrahigh fields. We design and demonstrate a novel and simple dual-frequency RF resonant coil that can operate at both low-γ X-nuclear and proton frequencies. The dual-frequency resonant coil comprises an LC coil loop and a tuning-matching circuit bridged by two short wires of the desired length to generate two resonant modes: one for proton MRI and the other for low-γ X-nuclear MRS imaging with a large difference in their Larmor frequencies at ultrahigh fields. The coil parameters for the desired coil size and resonant frequencies can be determined via numerical simulations based on LC circuit theory. We designed, constructed, and evaluated several prototype surface coils and quadrature array coils for 1 H and 2 H or 17 O imaging, with small-sized (diameter ≤ 5 cm) coils evaluated using a 16.4 T animal scanner, and a large-sized (15 cm diameter) coil on a 7 T human scanner. All coils could be tuned/matched and driven in the single coil or array coil mode to the resonant frequencies of 1 H (698 and 298 MHz), 2 H (107 and 45.8 MHz), or 17 O (94.7 and 40.4 MHz) for imaging measurements and evaluation at 16.4 and 7 T, respectively. The dual-frequency resonant coil or array provides adequate detection sensitivity for 1 H MRI and excellent performance for low-γ X-nuclear MRS imaging applications, and excellent coil decoupling efficiency between the array coils at both resonant frequencies with an optimal geometric overlap. It provides a simple, cost-effective dual-frequency RF coil solution to perform low-γ X-nuclear MRS imaging for preclinical and human applications, especially at ultrahigh fields.

Elongase of very long chain fatty acids 6 (ELOVL6) promotes lipid synthesis in buffalo mammary epithelial cells.

Recent studies have shown elongase of very-long-chain fatty acids 6 (ELOVL6) is a vital protein for endogenous synthesis of saturated and monounsaturated long-chain fatty acids in some mammals. Nevertheless, its role in lipid synthesis in buffalo mammary gland is still unclear. In this work, the full-length coding sequence (CDS) of ELOVL6 was cloned and identified from buffalo mammary gland. As a result, the CDS of this gene is 795 bp, which encodes a polypeptide of 264 amino acid residues. The buffalo ELOVL6 contains an ELO domain which belongs to the ELO superfamily. Among the 10 tissues of buffalo in peak lactation detected by RT-qPCR, the expression level of ELOVL6 was the highest in the brain, followed by the spleen, and then decreased in the mammary gland, muscle, kidney, heart, liver, rumen, intestine and lung. However, only the expression in the brain and spleen was statistically different from that in other tissues (p < 0.05). Compared with that of the dry-off period, the mRNA abundance of ELOVL6 in the mammary gland was significantly increased in peak lactation. The experiments based on lentivirus transfection in buffalo mammary epithelial cells (BuMECs) displayed that the overexpression of ELOVL6 markedly promoted the expression of INSIG1, INSIG2, SREBP, PPARG, FASN, GPAM, DGAT2 and APGAT6 genes, and the knockdown of ELOVL6 significantly decreased the mRNA abundance of INSIG2, SREBP, FASN, SCD, GPAM, APGAT6 and TIP47 genes. In addition, the increase or decrease of ELOVL6 expression level also caused the corresponding change of total triglyceride content in the BuMECs. The results here suggest that the ELOVL6 can catalyse the synthesis of long-chain fatty acids in the BuMECs, and it can indirectly affect the expression of genes related to milk fat synthesis through its catalytic products to promote the lipid biosynthesis of BuMECs.

Identification, Molecular Characterization, and Tissue Expression Profiles of Three Smad Genes from Water Buffalo (Bubalus bubalis).

Smads are involved in a variety of biological activities by mediating bone morphogenetic protein (BMP) signals. The full-length coding sequences (CDSs) of buffalo Smads 1, 4, and 5 were isolated and identified through RT-PCR in this study. Their lengths are 1398 bp, 1662 bp, and 1398 bp, respectively. In silico analysis showed that their transcriptional region structures, as well as their amino acid sequences, physicochemical characteristics, motifs, conserved domains, and three-dimensional structures of their encoded proteins are highly consistent with their counterparts in the species of Bovidae. The three Smad proteins are all hydrophilic without the signal peptides and transmembrane regions. Each of them has an MH1 domain and an MH2 domain. A nuclear localization sequence was found in the MH1 domain of buffalo Smads 1 and 5. Prediction showed that the function of the three Smads is mainly protein binding, and they can interact with BMPs and their receptors. The three genes were expressed in all 10 buffalo tissues assayed, and their expression in the mammary gland, gonad, and spleen was relatively high. The results here indicate that the three buffalo Smads may be involved in the transcriptional regulation of genes in a variety of tissues.

QCL-Based Dual-Comb Spectrometer for Multi-Species Measurements at High Temperatures and High Pressures.

Rapid multi-species sensing is an overarching goal in time-resolved studies of chemical kinetics. Most current laser sources cannot achieve this goal due to their narrow spectral coverage and/or slow wavelength scanning. In this work, a novel mid-IR dual-comb spectrometer is utilized for chemical kinetic investigations. The spectrometer is based on two quantum cascade laser frequency combs and provides rapid (4 µs) measurements over a wide spectral range (~1175-1235 cm-1). Here, the spectrometer was applied to make time-resolved absorption measurements of methane, acetone, propene, and propyne at high temperatures (>1000 K) and high pressures (>5 bar) in a shock tube. Such a spectrometer will be of high value in chemical kinetic studies of future fuels.

SOMM4mC: a second-order Markov model for DNA N4-methylcytosine site prediction in six species.

MOTIVATION: DNA N4-methylcytosine (4mC) modification is an important epigenetic modification in prokaryotic DNA due to its role in regulating DNA replication and protecting the host DNA against degradation. An efficient algorithm to identify 4mC sites is needed for downstream analyses. RESULTS: In this study, we propose a new prediction method named SOMM4mC based on a second-order Markov model, which makes use of the transition probability between adjacent nucleotides to identify 4mC sites. The results show that the first-order and second-order Markov model are superior to the three existing algorithms in all six species (Caenorhabditis elegans, Drosophila melanogaster, Arabidopsis thaliana, Escherichia coli, Geoalkalibacter subterruneus and Geobacter pickeringii) where benchmark datasets are available. However, the classification performance of SOMM4mC is more outstanding than that of first-order Markov model. Especially, for E.coli and C.elegans, the overall accuracy of SOMM4mC are 91.8% and 87.6%, which are 8.5% and 6.1% higher than those of the latest method 4mcPred-SVM, respectively. This shows that more discriminant sequence information is captured by SOMM4mC through the dependency between adjacent nucleotides. AVAILABILITY AND IMPLEMENTATION: The web server of SOMM4mC is freely accessible at www.insect-genome.com/SOMM4mC. CONTACT: chenyuanyuan@njau.edu.cn or piancong@njau.edu.cn.

Discovering Cancer-Related miRNAs from miRNA-Target Interactions by Support Vector Machines.

MicroRNAs (miRNAs) have been shown to be closely related to cancer progression. Traditional methods for discovering cancer-related miRNAs mostly require significant marginal differential expression, but some cancer-related miRNAs may be non-differentially or only weakly differentially expressed. Such miRNAs are called dark matters miRNAs (DM-miRNAs) and are targeted through the Pearson correlation change on miRNA-target interactions (MTIs), but the efficiency of their method heavily relies on restrictive assumptions. In this paper, a novel method was developed to discover DM-miRNAs using support vector machine (SVM) based on not only the miRNA expression data but also the expression of its regulating target. The application of the new method in breast and kidney cancer datasets found, respectively, 9 and 24 potential DM-miRNAs that cannot be detected by previous methods. Eight and 15 of the newly discovered miRNAs have been found to be associated with breast and kidney cancers, respectively, in existing literature. These results indicate that our new method is more effective in discovering cancer-related miRNAs.

miR+Pathway: the integration and visualization of miRNA and KEGG pathways.

miRNAs represent a type of noncoding small molecule RNA. Many studies have shown that miRNAs are widely involved in the regulation of various pathways. The key to fully understanding the regulatory function of miRNAs is the determination of the pathways in which the miRNAs participate. However, the major pathway databases such as KEGG only include information regarding protein-coding genes. Here, we redesigned a pathway database (called miR+Pathway) by integrating and visualizing the 8882 human experimentally validated miRNA-target interactions (MTIs) and 150 KEGG pathways. This database is freely accessible at http://www.insect-genome.com/miR-pathway. Researchers can intuitively determine the pathways and the genes in the pathways that are regulated by miRNAs as well as the miRNAs that target the pathways. To determine the pathways in which targets of a certain miRNA or multiple miRNAs are enriched, we performed a KEGG analysis miRNAs by using the hypergeometric test. In addition, miR+Pathway provides information regarding MTIs, PubMed IDs and the experimental verification method. Users can retrieve pathways regulated by an miRNA or a gene by inputting its names.

MM-6mAPred: identifying DNA N6-methyladenine sites based on Markov model.

MOTIVATION: Recent studies have shown that DNA N6-methyladenine (6mA) plays an important role in epigenetic modification of eukaryotic organisms. It has been found that 6mA is closely related to embryonic development, stress response and so on. Developing a new algorithm to quickly and accurately identify 6mA sites in genomes is important for explore their biological functions. RESULTS: In this paper, we proposed a new classification method called MM-6mAPred based on a Markov model which makes use of the transition probability between adjacent nucleotides to identify 6mA site. The sensitivity and specificity of our method are 89.32% and 90.11%, respectively. The overall accuracy of our method is 89.72%, which is 6.59% higher than that of the previous method i6mA-Pred. It indicated that, compared with the 41 nucleotide chemical properties used by i6mA-Pred, the transition probability between adjacent nucleotides can capture more discriminant sequence information. AVAILABILITY AND IMPLEMENTATION: The web server of MM-6mAPred is freely accessible at http://www.insect-genome.com/MM-6mAPred/. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Large-scale femtosecond holography for near simultaneous optogenetic neural modulation.

For better understanding of brain functions, optogenetic neural modulation has been widely employed in neural science research. For deep tissue in vivo applications, large-scale two-photon based near simultaneous 3D laser excitation is needed. Although 3D holographic laser excitation is nowadays common practice, the inherent short coherence length of the commonly used femtosecond pulses fundamentally restricts the achievable field-of-view. Here we report a technique for near simultaneous large-scale femtosecond holographic 3D excitation. Specifically, we achieved two-photon excitation over 1.3 mm field-of-view within 1.3 milliseconds, which is sufficiently fast even for spike timing recording. The method is scalable and compatible with the commonly used two-photon sources and imaging systems in neuroscience research.

Discovering the 'Dark matters' in expression data of miRNA based on the miRNA-mRNA and miRNA-lncRNA networks.

BACKGROUND: Since miRNAs can play important roles in different cancer types, how to discover cancer related miRNAs is an important issue. In general, the miRNAs with differential expression is the focus of attention. However, some important cancer related miRNAs are not excavated by differential expression analysis. We take this type of miRNAs as 'dark matters' (DM-miRNA). It is our great interests to develop an algorithm to discover DM-miRNAs. RESULTS: An effective method was developed to find DM-miRNAs. This method is mainly for mining potential DM-miRNAs by building basic miRNA-mRNA network (BMMN) and miRNA-lncRNA network (BMLN). The results indicate that miRNA-mRNA and miRNA-lncRNA interactions can be used as novel cancer biomarkers. CONCLUSIONS: The BMMN and BMLN can excavate the non-differentially expressed miRNAs which play an important role in the cancer. What's more, the edge biomarkers (miRNA-mRNA and miRNA-lncRNA interactions) contain more information than the node biomarkers. It will contribute to developing novel therapeutic candidates in cancers.

LncCeRBase: a database of experimentally validated human competing endogenous long non-coding RNAs.

Long non-coding RNAs (lncRNAs) are endogenous molecules longer than 200 nucleotides, and lack coding potential. LncRNAs that interact with microRNAs (miRNAs) are known as a competing endogenous RNAs (ceRNAs) and have the ability to regulate the expression of target genes. The ceRNAs play an important role in the initiation and progression of various cancers. However, until now, there is no a database including a collection of experimentally verified, human ceRNAs. We developed the LncCeRBase database, which encompasses 432 lncRNA-miRNA-mRNA interactions, including 130 lncRNAs, 214 miRNAs and 245 genes from 300 publications. In addition, we compiled the signaling pathways associated with the included lncRNA-miRNA-mRNA interactions as a tool to explore their functions. LncCeRBase is useful for understanding the regulatory mechanisms of lncRNA.Database URL: http://lnccerbase.it1004.com.

Identification of cancer-related miRNA-lncRNA biomarkers using a basic miRNA-lncRNA network.

LncRNAs are regulatory noncoding RNAs that play crucial roles in many biological processes. The dysregulation of lncRNA is thought to be involved in many complex diseases; lncRNAs are often the targets of miRNAs in the indirect regulation of gene expression. Numerous studies have indicated that miRNA-lncRNA interactions are closely related to the occurrence and development of cancers. Thus, it is important to develop an effective method for the identification of cancer-related miRNA-lncRNA interactions. In this study, we compiled 155653 experimentally validated and predicted miRNA-lncRNA associations, which we defined as basic interactions. We next constructed an individual-specific miRNA-lncRNA network (ISMLN) for each cancer sample and a basic miRNA-lncRNA network (BMLN) for each type of cancer by examining the expression profiles of miRNAs and lncRNAs in the TCGA (The Cancer Genome Atlas) database. We then selected potential miRNA-lncRNA biomarkers based on the BLMN. Using this method, we identified cancer-related miRNA-lncRNA biomarkers and modules specific to a certain cancer. This method of profiling will contribute to the diagnosis and treatment of cancers at the level of gene regulatory networks.

Knockdown of XBP1 by RNAi in Mouse Granulosa Cells Promotes Apoptosis, Inhibits Cell Cycle, and Decreases Estradiol Synthesis.

Granulosa cells are crucial for follicular growth, development, and follicular atresia. X-box binding protein 1 (XBP1), a basic region-leucine zipper protein, is widely involved in cell differentiation, proliferation, apoptosis, cellular stress response, and other signaling pathways. In this study, RNA interference, flow cytometry, western blot, real-time PCR, Cell Counting Kit (CCK8), and ELISA were used to investigate the effect of XBP1 on steroidogenesis, apoptosis, cell cycle, and proliferation of mouse granulosa cells. ELISA analysis showed that XBP1 depletion significantly decreased the concentrations of estradiol (E2). Additionally, the expression of estrogen synthesis enzyme Cyp19a1 was sharply downregulated. Moreover, flow cytometry showed that knockdown of XBP1 increased the apoptosis rate and arrests the cell cycle in S-phase in granulosa cells (GCs). Further study confirmed these results. The expression of CCAAT-enhancer-binding protein homologous protein (CHOP), cysteinyl aspartate specific proteases-3 (caspase-3), cleaved caspase-3, and Cyclin E was upregulated, while that of Bcl-2, Cyclin A1, and Cyclin B1 was downregulated. Simultaneously, CCK8 analysis indicated that XBP1 disruption inhibited cell proliferation. In addition, XBP1 knockdown also alters the expression of Has2 and Ptgs2, two essential genes for folliculogenesis. Collectively, these data reveal a novel critical role of XBP1 in folliculogenesis by regulating the cell cycle, apoptosis, and steroid synthesis of mouse granulosa cells.

V-ELMpiRNAPred: Identification of human piRNAs by the voting-based extreme learning machine (V-ELM) with a new hybrid feature.

Piwi-interacting RNAs (piRNAs) were recently discovered as endogenous small noncoding RNAs. Some recent research suggests that piRNAs may play an important role in cancer. So the precise identification of human piRNAs is a significant work. In this paper, we introduce a series of new features with 80 dimension called short sequence motifs (SSM). A hybrid feature vector with 1444 dimension can be formed by combining 1364 features of [Formula: see text]-mer strings and 80 features of SSM features. We optimize the 1444 dimension features using the feature score criterion (FSC) and list them in descending order according to the scores. The first 462 are selected as the input feature vector in the classifier. Moreover, eight of 80 SSM features appear in the top 20. This indicates that these eight SSM features play an important part in the identification of piRNAs. Since five of the above eight SSM features are associated with nucleotide A and G ('A*G', 'A**G', 'A***G', 'A****G', 'A*****G'). So, we guess there may exist some biological significance. We also use a neural network algorithm called voting-based extreme learning machine (V-ELM) to identify real piRNAs. The Specificity (Sp) and Sensitivity (Sn) of our method are 95.48% and 94.61%, respectively in human species. This result shows that our method is more effective compared with those of the piRPred, piRNApredictor, Asym-Pibomd, Piano and McRUMs. The web service of V-ELMpiRNAPred is available for free at http://mm20132014.wicp.net:38601/velmprepiRNA/Main.jsp .

Study on the Method of Voigt Profiles Two Wings Fitting Non-Uniform Flow Field Absorbance.

In the field of the absorption spectrum, especially for direct tunable diode laser absorption spectroscopy (dTDLAS) technology, the integrated area of the absorption spectrum is needed to be measured accurately for calculating the temperature and the component concentration of the flow field. Doing single optical path absorption spectroscopic measurement in the non-uniform flow field, spectral lineshape broadening is varied with the flow changes, in previous research reports, researchers mainly use single Voigt or Lorentz profile to fit absorbance curve or use directly integral to obtain the integrated area of the absorption spectrum. There are some shortcomings in these methods, resulting in certain error between the fitting result and the actual area, which is not conducive to the accurate measurement of flow field parameters. Firstly, the error is analyzed theoretically, and then, we adopt the simulation method to obtain the error size of the method. Finally, we proposed the Voigt wings fitting absorbance method to reduce the fitting error. The operation of Voigt wings fitting method is to Select the wings of the spectral line, and then use Voigt profile fitting, The difference between the two wings was used the numerical integral method to calculate area, the integrated area is sum of Voigt profile fitting area and numerical integral area. We have used water vapor as the target gas, with eight absorption lines which have different low-level states energy from HITRAN 2012 database being selected-, building two kinds of non-uniform flow field model base on the flat flame furnace, and through the method of segmentation to equivalent processing the no uniformity of flow field. Using Voigt profile fitting method, numerical integral method and Voigt profile wings fitting method to obtain the integral area of models, the error size is obtained by comparing with the theoretical value. As the result of contrast, the fitting error of Voigt profile fitting method is large and related to the different absorption line, the error of numerical integral method is biggest but it is nothing to do with absorption line, the fitting error of Voigt profile wings fitting method is least and stable. By force of contrast, we determined the appropriate method to obtain integral area in the different non-uniform flow field, which is beneficial to obtain accurate integrated area and flow field parameters.

LncRNApred: Classification of Long Non-Coding RNAs and Protein-Coding Transcripts by the Ensemble Algorithm with a New Hybrid Feature.

As a novel class of noncoding RNAs, long noncoding RNAs (lncRNAs) have been verified to be associated with various diseases. As large scale transcripts are generated every year, it is significant to accurately and quickly identify lncRNAs from thousands of assembled transcripts. To accurately discover new lncRNAs, we develop a classification tool of random forest (RF) named LncRNApred based on a new hybrid feature. This hybrid feature set includes three new proposed features, which are MaxORF, RMaxORF and SNR. LncRNApred is effective for classifying lncRNAs and protein coding transcripts accurately and quickly. Moreover,our RF model only requests the training using data on human coding and non-coding transcripts. Other species can also be predicted by using LncRNApred. The result shows that our method is more effective compared with the Coding Potential Calculate (CPC). The web server of LncRNApred is available for free at http://mm20132014.wicp.net:57203/LncRNApred/home.jsp.

[Reconstruction Research for Gas Concentration and Temperature of Flame Based on Algebraic Reconstruction Technique].

We specify water vapor among combustion products as the target gas based on tunable diode absorption spectroscopy in this paper. The direct absorption signals of water vapor after being processed can be used to calculate the gas concentration distributions and temperature distributions of the combustion region of methane and air flat flame furnace via algebraic reconstruction technique (ART). In the numerical simulation, reconstruction region is a grid of five by five, we assume a temperature and water vapor concentration distribution of 25 grid, then simulate different direction laser rays which cross the combustion region, generating projection of each ray, by ART reconstruction algorithm, it turns out that the temperature and water vapor distribution reconstruction error is less than 1%. In the experiment, we chose a distributed-feedback laser to scan the target gas H2O7 153.722, 7 153.748 and 7 154.354 cm(-1) as absorbtion line pair to measure temperature of the flame, we consider the former two line as one absorbtion line. By Stages multi-directional scanning, the authors abtain 16 different regions distributin of temperature and gas concentration of furnace when we collecte 30 different angle data by spectral data processing, reconstruction algorithm, two absorbtion line ratio method for temperature sensing, finding the temperature and water concentration are higher in the center than in the edge, it turns out that the reconstruction algorithm is good enough to achieve the distributions of gas concentration and temperature of the combustion region.