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Acute Intermittent Porphyria (AIP), an autosomal dominant hepatic disorder, results from hydroxymethylbilane synthase (HMBS) mutations that decrease the encoded enzymatic activity, thereby predisposing patients to life-threatening acute neurovisceral attacks. The ~1% penetrance of AIP suggests that other genetic factors modulate the onset and severity of the acute attacks. Here, we characterized the hepatic transcriptomic response to phenobarbital (PB) administration in AIP mice, which mimics the biochemical attacks of AIP. At baseline, the mRNA profiles of 14,138 hepatic genes prior to treatment were remarkably similar between AIP and the congenic wild-type (WT) mice. After PB treatment (~120 mg/kg x 3d), 1347 and 1120 genes in AIP mice and 422 and 404 genes in WT mice were uniquely up- and down-regulated, respectively, at a False Discovery Rate < 0.05. As expected, the ALAS1 expression increased 4.5-fold and 15.9-fold in the WT and AIP mice, respectively. ALA-dehydrogenase also was induced ~1.7-fold in PB-induced AIP mice, but was unchanged in PB-induced WT mice. There was no statistically significant difference in the overall expression of 155 hepatic cytochrome P450 enzymes, although Cyp2c40, Cyp2c68, Cyp2c69, Mgst3 were upregulated only in PB-induced AIP mice (>1.9-fold) and Cyp21a1 was upregulated only in PB-induced WT mice (>9-fold). Notably, the genes differentially expressed in induced AIP mice were enriched in circadian rhythm, mitochondria biogenesis and electron transport, suggesting these pathways were involved in AIP mice responding to PB treatment. These results advance our understanding of the hepatic metabolic changes in PB-induced AIP mice and have implications in the pathogenesis of AIP acute attacks. [ABSTRACT FROM AUTHOR]

[Display omitted] • A series of novel indole-2-carbonyl piperazine urea derivatives were discovered as FAAH inhibitors. • Active compound 4i showed potent FAAH activities (IC 50 = 0.12 μM) and high selectivity over CB receptors, CES2, ABHD6 and MAGL. • Compound 4i exhibited an adequate pharmacokinetics profile in rodents and superior metabolic stability in human liver microsome. • Compound 4i effectively ameliorated reserpine-induced depression-like behaviors and also exhibited remarkable analgesic activity in vivo test. Fatty acid amide hydrolase (FAAH), a serine hydrolase with significant role in the hydrolysis of endocannabinoids, is a promising therapeutic target for peripheral and central nervous system related disorders, including pain, neuroinflammation and depression. Employing a structure-based approach, a novel series of indole-2-carbonyl piperazine urea derivatives were designed and synthesized as FAAH inhibitors for the treatment of pain-depression comorbidity. Among them, compound 4i emerged as the most potent inhibitor (IC 50 = 0.12 μM) with fine selectivity versus CES2, ABHD6, MAGL and the cannabinoid receptor, which also displayed superior metabolic stability in human liver microsome and an adequate pharmacokinetic profile in rodents. Treatment of depressed rats with 4i demonstrated favorable antidepressant-like effects not only by increasing the level of BDNF in the hippocampus but also by restraining the apoptosis of hippocampal neurons. Also, 4i effectively suppressed the LPS-induced neuroinflammation in vitro. Moreover, 4i exhibited potent analgesic activity, which indicated its promising therapeutical application for pain and depression. These meaningful results shed light on FAAH inhibitors as promising pain-depression comorbidity therapeutics. [ABSTRACT FROM AUTHOR]

An efficient 3D bifunctional nanofiber electrocatalyst with synergistic multiple active sites for high-performance aqueous/solid ZABs was developed by electrospinning and MOF/COF in-situ growth strategy. [Display omitted] Covalent organic frameworks (COFs) and metal–organic frameworks (MOFs) have attracted growing attention in electrochemical energy storage and conversion systems (e.g., Zn-air batteries, ZABs) owing to their structural tunability, ordered porosity and high specific surface area. In this work, for the first time, the three-dimensional (3D) highly open catalyst (CNFs/CoZn-MOF@COF) possessing hierarchical porous structure and high-density active sites of uniform cobalt (Co) nanoparticles and metal-N x (M-N x , M = Co and Zn) is demonstrated, which is fabricated using electrospinning technique in combination with MOF/COF hybridization strategy and direct pyrolysis. Benefiting from the well-designed branch-leaf nanostructures, plentiful and uniform active sites on the MOF/COF-derived carbon frameworks, as well as the synergistic effect of multiple active sites, CNFs/CoZn-MOF@COF catalyst achieves superior electrocatalytic activity and stability towards both oxygen reduction reaction (ORR) and oxygen evolution reaction (OER) with a small potential gap (ΔE = 0.75 V). In situ Raman spectroscopy and X-ray photoelectron spectroscopy results indicate that the CoOOH intermediates are the main active species during OER/ORR. Significantly, both aqueous and all-solid-state rechargeable ZABs assembled with CNFs/CoZn-MOF@COF as the air cathode show high open-circuit potential, outstanding peak power density, large capacity and long cycle life. More impressively, the obtained all-solid-state ZAB also displays superb mechanical flexibility and device stability under different, showcasing great application deformations potential in portable and wearable electronics. This work provides a new insight into the design and exploitation of bifunctional catalysts from MOF/COF hybrid materials for energy storage and conversion devices. [ABSTRACT FROM AUTHOR]

[Display omitted] Lignin upgrading to various functional products is promising to realize high-value utilization of low-cost and renewable biomass waste, but is still in its infancy. Herein, using industry waste lignosulfonate as the biomass-based carbon source and urea as the dopant, we constructed a heteroatom-doped porous carbon nanosheet structure by a simple NaCl template-assisted pyrolytic strategy. Through the synergistic effect of the NaCl template and urea, the optimized lignin-derived porous carbon catalyst with high content of active nitrogen species and large specific surface area can be obtained. As a result, the fabricated catalysts exhibited excellent electrocatalytic oxygen reduction activity, as well as good methanol tolerance and stability, comparable to that of commercial Pt/C. Moreover, rechargeable Zn-air batteries assembled with this electrocatalyst have a peak power density of up to 150 mW cm-2 and prominent long-term cycling stability. This study offers an inexpensive and efficient way for the massive production of highly active metal-free catalysts from the plentiful, inexpensive and environmentally friendly lignin, offering a good direction for biomass waste recycling and utilization. [ABSTRACT FROM AUTHOR]

Lung squamous cell carcinoma (SCC) is a fatal disease in both male and female, for which current treatments are inadequate. Surgical resection is regarded as the cornerstone of treatment for patients with lung SCC, but even for the same stage patients, the wide spectrum of disease-free survival (DFS) times exits. Therefore, how to improve the DFS prediction performance of lung SCC becomes one major research area. In this study, we proposed a novel method called LSCDFS-MKL, which was on the basis of multiple kernel learning to predict DFS of lung SCC. In LSCDFS-MKL, we first efficiently integrated pathological images and genomic data (copy number aberration, gene expression, protein expression) from lung SCC. The results of LSCDFS-MKL between different types of data show that the features extracted from pathological images play an important role in DFS prediction of lung SCC. Then we compared our method LSCDFS-MKL with other existing methods and performance analysis indicates that LSCDFS-MKL has a significantly better performance than other prediction methods. After that, we applied the proposed method on different stage stratums and the performance demonstrates that LSCDFS-MKL remains efficient in DFS prediction of lung SCC patients. Finally, we performed LSCDFS-MKL on an independent validation dataset and the accuracy of DFS prediction achieves 100%, which is promising. [ABSTRACT FROM AUTHOR]

Open-hollow microcapsule with oxygen vacancies and Ni/NiO hybrids is used as host materials of anchoring sulfur. Chemisorption, physical confinement and catalyst effect accelerate kinetics and improve the electrochemical performance of Li-S battery synergistically. [Display omitted] The fast development of lithium-sulfur (Li-S) batteries is catching more attention to improve cycling stability and kinetics. Herein, a hierarchical porous Ni/NiO/C microsphere (NIONC) with openings assembled by ultrathin nanosheets is introduced to solve the poor conductivity, shuttle effect, and slow electrochemical kinetics of Li-S batteries. The structure of NIONC open-hollow microcapsules combines several advantageous properties for the improvement of electrochemical performances. Primarily, a well-developed hollow structure and openings can perform as containers and doors for sulfur immobilization. Therefore, the confinement effect to sulfur species is obtained by this hollow sphere. Secondly, the nanosheets with oxygen vacancies and Ni active sites provide abundant active sites for the chemical absorption of polysulfides. Based on the open structure and oxygen vacancies of Ni/NiO, both the physical absorption and chemical immobilization of sulfur are realized, with high stability and fast kinetics. The S-injected NIONC (NIONC/S) cathode exhibits outstanding rate performance at 5 A g-1 with a high capability of 794 mAh g-1 and excellent long-cycle performance of 653 mAh g-1 after 300 cycles at 1 A g-1. We proposed a simple and controllable route to fabricate sulfur hosts by structure and composition adjustment, which will inspire the commercial application of Li-S batteries. [ABSTRACT FROM AUTHOR]

• Species-specific ubiquitination site prediction method superior to general method. • Studies species-specific ubiquitination site prediction by using transfer learning technique. • The proposed DeepTL-Ubi method is very excellent in species-specific ubiquitination site prediction work. Ubiquitination is one of the most important post-translational modifications which involves in many biological processes. Because mass spectrometry-based ubiquitination site identification methods are costly and time consuming, computational approaches provide alternative ways to the determination of ubiquitination sites. Although machine learning based methods can effectively predict ubiquitination sites, most of them rely on feature engineering, which may lead to bias or incomplete feature. Recently, deep learning has achieved great success in prediction of post-translational modification sites. However, deep learning method has not been explored in the prediction of species-specific ubiquitination sites. In this paper, we propose a novel transfer deep learning method, named DeepTL-Ubi, for predicting ubiquitination sites of multiple species. DeepTL-Ubi enhances the performance of species-specific ubiquitination site prediction by transferring common knowledge from the large amount of human data to other species, which effectively solves the problem of insufficient training data for other species. Besides, we train and test our model by collecting ubiquitination sites for multiple species from several sources. Experiment results show that our transfer learning technique can effectively improve the predictive performance of species with small sample size, and DeepTL-Ubi is superior to existing tools in many species. The source code and training data of DeepTL-Ubi are publicly deposited at https://github.com/USTC-HIlab/DeepTL-Ubi. [ABSTRACT FROM AUTHOR]

Episodic memory of scatter-hoarding animals involves encoding and storage of memories of cached food items, in conjunction with subsequent retrieval or recovery. Although the reward values mediate the interaction of item memory and source memory, whether nonhuman animals divide their spatial memory resources between cached items of different values has never been tested. Here, we used a unique scatter-hoarder/seed system to test our 'cache value hypothesis', which proposes that scatter-hoarding animals will preferentially allocate spatial memory resources towards higher-valued caches. By making Edwards's long-tailed rats, Leopoldamys edwardsi , anosmic, using Triton X-100, we showed that L. edwardsi recovered more caches containing large nuts than those containing small ones, although the two kinds of nuts were equivalently cached. Our results therefore support the hypothesis that scatter-hoarding animals allocate more spatial memory resources to caches containing high-valued items. This is one of the few studies to investigate how item memory regulates source memory (order information) in the context of food storing and recovery by animals, especially by scatter-hoarding rodents. That high-valued items were remembered better than low-valued ones in our study suggests that item memory appears to be contextually associated with order information of items in animal memory processes, which is not in agreement with a previous suggestion that order information is independent of content or item information. • We used a scatter-hoarding rodent to test episodic memory. • Edward's long-tailed rats allocated more memory on high-valued caches. • High-valued items were remembered better than low-valued ones. • The rats know 'what food' was cached 'where' or 'when'. [ABSTRACT FROM AUTHOR]

• Desfluoroquinolone-based hybrids with involvement of C-7 aminopyrimidine functional group was designed and synthesized. • The most active B14 exhibited activities at submicromolar concentration against a panel of MRSA strains. • B14 also displayed highly selective toxicity toward bacterial cells and low hERG inhibition. • Further resistance development study indicated MRSA is unlikely to acquire resistance against B14. Despite the fact that the introduction of a fluorine atom at the C-6 position has resulted in the evolution of fluoroquinolones, fluoroquinolone-induced cardiac toxicity has drawn considerable attention. In this context, desfluoroquinolone-based hybrids with involvement of C-7 aminopyrimidine functional group were designed and synthesized. The biological results showed majority of these hybrids still demonstrated potent anti-MRSA activity with MIC values between 0.38 and 1.5 μg/mL, despite the lack of the typical C-6 fluorine atom. Particularly, the most active B14 exhibited activities at submicromolar concentrations against a panel of MRSA strains including vancomycin-intermediate strains, levofloxacin-resistant isolates, and linezolid-resistant isolates, etc. As expected, it also displayed highly selective toxicity toward bacterial cells and low hERG inhibition. Further resistance development study indicated MRSA is unlikely to acquire resistance against B14. The docking study revealed that two hydrogen bonds were formed between the C-7 substituent and the surrounding DNA bases, which might contribute to overcome resistance by reducing the dependence on the magnesium-water bridge interactions with topoisomerase IV. These results indicate a promising strategy for developing new antibiotic quinolones to combat multidrug resistance and cardiotoxicity. [ABSTRACT FROM AUTHOR]

Panax ginseng and Panax quinquefolium are two valuable Chinese herbal medicines that should not be mixed because they differ in drug properties and efficacy. The traditional identification method is easily affected by subjective factors and cannot effectively distinguish between ginseng products. This study aimed to develop a new chemical analysis method to visually identify P. ginseng and P. quinquefolium. In this method, a large number of sequences containing G-quadruplex were generated by loop-mediated isothermal amplification, and the combination of G-quadruplex and hemin was used to form deoxyribozyme, which catalyzed the color change of H 2 O 2. Artificial simulation of adulteration experiments revealed that this method could detect more than 20% adulterated P. quinquefolium. Compared with the traditional identification methods, this technology was simpler and more efficient, providing a reference for developing rapid visual identification methods and reagents for P. ginseng and P. quinquefolium. [Display omitted] • Find the difference region between Panax ginseng and Panax quinquefolium and establish LAMP reaction. • To facilitate the observation of LAMP reaction results, G-4 complementary sequence was introduced into BIP sequence. • The visual detection method based on LAMP and DNAzyme can be used to identify the components of ginseng products. [ABSTRACT FROM AUTHOR]

Mitochondrion is important organelle of most eukaryotes and play an important role in participating in various life activities of cells. However, some functions of mitochondria can only be achieved in specific submitochondrial location, the study of submitochondrial locations will help to further understand the biological function of protein, which is a hotspot in proteomics research. In this paper, we propose a new method for protein submitochondrial locations prediction. Firstly, the features of protein sequence are extracted by combining Chou's pseudo-amino acid composition (PseAAC) and pseudo-position specific scoring matrix (PsePSSM). Then the extracted feature information is denoised by two-dimensional (2-D) wavelet denoising. Finally, the optimal feature vectors are input to the SVM classifier to predict the protein submitochondrial locations. We obtained the ideal prediction results by jackknife test and compared with other prediction methods. The results indicate that the proposed method is significantly better than the existing research results, which can provide a new method to predict protein locations in other organelles. The source code and all datasets are available at https://github.com/QUST-BSBRC/PseAAC-PsePSSM-WD/ for academic use. [ABSTRACT FROM AUTHOR]

It has been widely reported that the general population was at an increased risk of allergy diseases, which probably be related with household allergens exposure. However, the difference of local and systemic allergic reactions exposure to allergens has not been reported in the general population previously. The data of 1094 U.S. adults from the National Health and Nutrition Examination Survey (NHANES) 2005–2006 data bank were analyzed. Dust, allergens (Bia g 1, Bia g 2, Can f 1, Feld 1, Derp 1, Mus m 1, Rat n 1, Alternaria alternate , and Aspergillus fumigatus), and endotoxin, were measured to estimate sensitizing source exposure. And allergy-related outcomes indicators including hay fever, sneezing, allergic rhinitis (AR), immunoglobulin E (IgE), and allergic sensitization, were evaluzted to estimate local and systemic allergic reactions. Multiple linear regression and logistic regression models were used to examine the associations of sensitizer and allergy-related outcomes. The mean or median concentration of dust and endotoxin were 0.66 g and 12.98 EU/mg dust. The Derp 1, Mus m 1, Rat n 1, Alternaria alternate , and Aspergillus fumigatus were the main allergens in the dust, with the concentrations of 30.66 ng/g dust, 30.73 ng/g dust, 5.94 ng/g dust, 5.20 ng/g dust, and 207.68 μg/g dust, respectively. The prevalence of AR was 34.2% among the general population. After controlling for sociodemographic factors, we found that the allergens, such as Can f 1 and Feld 1, were positively associated with AR. The prevalence of allergic sensitization was about 20%. Dust and endotoxin were found positively associated with allergic sensitization, while Bia g 2, Rat n 1, Alternaria alternate , and Aspergillus fumigatus were inversely associated with that. Dust and endotoxin probably be associated with higher risk of local allergic reactions, while some allergens, such as Bia g 2, Rat n 1, Alternaria alternate , and Aspergillus fumigatus probably be associated with lower risk of systemic allergic reactions. [Display omitted] • Household low concentration of dust, allergens, and endotoxin exposure probably be related with allergy-related outcomes. • Dust and endotoxin probably be associated with higher risk of local allergic reactions. • Some allergens probably be associated with lower risk of systemic allergic reactions. [ABSTRACT FROM AUTHOR]

MicroRNAs (miRNAs) play important roles in the pathogenesis of many types of cancers by negatively regulating gene expression at posttranscriptional level. Here, we identified that miR-599 is up-regulated in non-small cell lung cancer (NSCLC) patients. It promoted NSCLC cell proliferation by negatively regulating SATB2. In NSCLC cell lines, CCK-8 proliferation assay indicated that the cell proliferation is promoted by miR-599 mimics. Transwell assay showed that miR-599 mimics promoted the invasion and migration of NSCLC cells. Luciferase assays confirmed that miR-599 directly binds to the 3'untranslated region of SATB2, and western blotting showed that miR-599 suppresses the expression of SATB2 at the protein level. This study indicates that miR-599 promotes proliferation and invasion of NSCLC cell lines via SATB2. The miR-599 may represent a potential therapeutic target for NSCLC treatment. [ABSTRACT FROM AUTHOR]

The signal transducer and activator of transcription 3 (STAT3) signaling pathway was involved in regulation of endothelial cell survival/apoptosis and was regarded as a target for prevention of atherosclerosis or other cardiovascular diseases. Factors, regulating STAT3 expression and activity, have aroused a wide range of interest, such as miRNAs or transcription factors. The aim of this study is to explore the role of miR-351, a miRNA found not long before, in the regulation of STAT3 expression and endothelial cell survival in the model mice with atherosclerosis (AS). Expression of miR-351 in the serum and cardiac arterial endothelial cells of the WT mice and AS mice was detected. Real-time qPCR analysis showed that miR-351 was upregulated in the serum and endothelial cells of the AS mice, displaying an opposite expression pattern with STAT3. To explore the role and mechanism of miR-351 in the endothelial cell survival, the miR-351 mimic was transfected in to the endothelial cells. MTT and Trypan Blue assays showed miR-351 attenuated the survival of endothelial cells. Our results of the TargetScan output and the 3′UTR luciferase reporter assay indicated that STAT3 was target of miR-351. Additionally, miR-351 resisted the elevation of STAT3 protein level and promotion of endothelial cell survival caused by SD19. Finally, our in vitro angiogenesis assay revealed that miR-351 suppressed angiogenesis and resisted the promotion of angiogenesis caused by SD19. In conclusion, miR-351 was upregulated in the atherosclerotic mice. MiR-351 can attenuate the survival of endothelial cells and suppress angiogenesis through targeting STAT3 in vitro. [ABSTRACT FROM AUTHOR]

l A novel method (SGL-SVM) for tumor classification on two-class and multi-class tumor datasets. l Gene primary selection reduces the computational complexity of the selection largely. l Sparse group Lasso considers the group effect variables and select more effective feature genes. l We investigate different feature gene selection methods and classifiers on the results. l The proposed method has better performance than other methods. At present, with the in-depth study of gene expression data, the significant role of tumor classification in clinical medicine has become more apparent. In particular, the sparse characteristics of gene expression data within and between groups. Therefore, this paper focuses on the study of tumor classification based on the sparsity characteristics of genes. On this basis, we propose a new method of tumor classification—Sparse Group Lasso (least absolute shrinkage and selection operator) and Support Vector Machine (SGL-SVM). Firstly, the primary selection of feature genes is performed on the normalized tumor datasets using the Kruskal–Wallis rank sum test. Secondly, using a sparse group Lasso for further selection, and finally, the support vector machine serves as a classifier for classification. We validate proposed method on microarray and NGS datasets respectively. Formerly, on three two-class and five multi-class microarray datasets it is tested by 10-fold cross-validation and compared with other three classifiers. SGL-SVM is then applied on BRCA and GBM datasets and tested by 5-fold cross-validation. Satisfactory accuracy is obtained by above experiments and compared with other proposed methods. The experimental results show that the proposed method achieves a higher classification accuracy and selects fewer feature genes, which can be widely applied in classification for high-dimensional and small-sample tumor datasets. The source code and all datasets are available at https://github.com/QUST-AIBBDRC/SGL-SVM/. [ABSTRACT FROM AUTHOR]