Mechanisms through which tissues are formed and maintained remain unknown but are fundamental aspects in biology. Tissue‐specific gene expression is a valuable tool to study such mechanisms. But in ...many biomedical studies, cell lines, rather than human body tissues, are used to investigate biological mechanisms Whether or not cell lines maintain their tissue‐specific characteristics after they are isolated and cultured outside the human body remains to be explored. In this study, we applied a novel computational method to identify core genes that contribute to the differentiation of cell lines from various tissues. Several advanced computational techniques, such as Monte Carlo feature selection method, incremental feature selection method, and support vector machine (SVM) algorithm, were incorporated in the proposed method, which extensively analyzed the gene expression profiles of cell lines from different tissues. As a result, we extracted a group of functional genes that can indicate the differences of cell lines in different tissues and built an optimal SVM classifier for identifying cell lines in different tissues. In addition, a set of rules for classifying cell lines were also reported, which can give a clearer picture of cell lines in different issues although its performance was not better than the optimal SVM classifier. Finally, we compared such genes with the tissue‐specific genes identified by the Genotype‐tissue Expression project. Results showed that most expression patterns between tissues remained in the derived cell lines despite some uniqueness that some genes show tissue specificity.
We used several advanced computational methods to analyze the gene expression profiles of cell lines from different tissues. Several biomarker genes and interpretable classification rules were identified and an optimal classifier was constructed.
A facile modulation strategy was adopted to fabricate hierarchically porous HP-UOH- X (HP, UOH and X represented the hierarchical pores, UiO-66-(OH) 2 and the dosage of benzoic acid, respectively) ...via introducing benzoic acid with different dosages into the precursor solution of UiO-66-(OH) 2 . The formation of hierarchical pores boosted the exposure of –OH groups and the Cr( vi ) mass transfer in HP-UOH- X , which vastly enhanced its sorption capacities and sorption rates. The optimal adsorbent (HP-UOH-80) displayed better sorption capacity (266.74 mg g −1 ) toward Cr( vi ) ( T = 308 K, pH = 2.0) and faster diffusion rate ( k 1 = 14.21 mg g −1 min 0.5 , k 2 = 6.25 mg g −1 min 0.5 ) than those of the pristine UiO-66-(OH) 2 and other HP-UOH- X adsorbents. Interestingly, HP-UOH-80 exhibited good selective uptake ability toward Cr( vi ) in different simulated water samples containing various competing anions. The corresponding mechanism was proposed that the –OH groups and the defect sites played the dominant contribution to Cr( vi ) adsorption, which could be affirmed by Fourier-transform infrared (FTIR) spectroscopy and X-ray photoelectron spectroscopy (XPS). In addition, the strategy of photocatalytic Cr( vi ) reduction for desorption was introduced to replace traditional chemical desorption. In all, this work presented an effective adsorbent and a sustainable approach for Cr( vi ) elimination, which can regenerate the adsorbent via a photocatalytic process rather than chemical washing.
Methylation is one of the most common and considerable modifications in biological systems mediated by multiple enzymes. Recent studies have shown that methylation has been widely identified in ...different RNA molecules. RNA methylation modifications have various kinds, such as 5-methylcytosine (m5C). However, for individual methylation sites, their functions still remain to be elucidated. Testing of all methylation sites relies heavily on high-throughput sequencing technology, which is expensive and labor consuming. Thus, computational prediction approaches could serve as a substitute. In this study, multiple machine learning models were used to predict possible RNA m5C sites on the basis of mRNA sequences in human and mouse. Each site was represented by several features derived from k-mers of an RNA subsequence containing such site as center. The powerful max-relevance and min-redundancy (mRMR) feature selection method was employed to analyse these features. The outcome feature list was fed into incremental feature selection method, incorporating four classification algorithms, to build efficient models. Furthermore, the sites related to features used in the models were also investigated.
Hydroxyl modified UiO-66 ((OH)2-UiO-66-X%, X represents the mass content ratio of introduced 2,5-dihydroxyterephthalic acid) was prepared via a solvothermal reaction between zirconium tetrachloride, ...benzene-1,4-dicarboxylic acid (H2BDC), as well as 2,5-dihydroxyterephthalic acid (H2BDC-(OH)2). It was found that hydroxyl groups can act as the intramolecular hole scavenger to boost the photo-induced charge carrier separation to enhance Cr(VI) reduction. The photocatalytic Cr(VI) reduction activities of (OH)2-UiO-66-X% were investigated upon the irradiation of low-power ultraviolet LED light. The findings demonstrated that (OH)2-UiO-66-20% with good cyclicity and stability exhibited superior photocatalytic performances to both UiO-66 and (OH)2-UiO-66. The introduction of hydroxyl groups can also extend the light absorption region to longer wavelength in visible range, which provides possibility for displaying photocatalytic activities under sunlight. The effect of small molecule organic acid (SOAs), pH value, and co-existing inorganic ions on photocatalytic performances of (OH)2-UiO-66-20% were investigated. Tartaric acid (TA) as typical SOAs was introduced to the reaction system to further boost the photocatalytic Cr(VI) reduction via acting as hole scavenger, constructing charge-transfer-complex for quick electron transportation, and producing COO·- radicals. This work opened a new opportunity for modified MOFs for boosted elimination activities for environmental pollutants.
•Hydroxyl modified UiO-66 was successfully constructed with mixed ligands.•The introduced hydroxyl promoted the separation of the photo-induced charge carriers.•The tartaric acid boosted the Cr(VI) reduction resulted from the formed COO·-.•The possible mechanisms of Cr(VI) reduction in different systems were proposed.
The CRISPR/Cas9 system is a creative and innovative gene editing biotechnology tool in genetic engineering. Although several achievements have been attained using the CRISPR/Cas9 system, it is still ...a challenge to avoid off-target effects and improve the editing efficacy. Previous efforts on evaluating the efficacy and designing the guide RNA mainly focused on DNA properties. However, some DNA features have not been characterized but can be reflected by protein properties, such as the disorder features and the sequence conservation. In this paper, we provided a computational framework to identify important features related to the efficacy of CRISPR/Cas9 focusing on the properties of the proteins encoded by the target DNA fragments. The feature selection method, maximal-relevance-minimal-redundancy, was adopted to analyze these features. And incremental feature selection together with support vector machine, were employed to extract optimal features, on which an optimal classifier can be constructed. As a result, 152 important features were extracted, with which an optimal classifier based on support vector machine was built. This classifier obtained the highest MCC value of 0.355. Finally, a series of detailed biological analyses were performed on the optimal features. From the results, we found that some key factors may differentially affect the binding activity of sgRNAs to their targets. Among them, the disorder status of the target protein sequences was found to be a major factor that is related to the efficacy of sgRNAs, suggesting the DNA features associated with the protein disorder status could also affect the CRISPR/Cas9 efficacy.
We demonstrate a narrow-linewidth, high side-mode suppression ratio (SMSR) semiconductor laser based on the external optical feedback injection locking technology of a femtosecond-apodized ...(Fs-apodized) fiber Bragg grating (FBG). A single frequency output is achieved by coupling and integrating a wide-gain quantum dot (QD) gain chip with a Fs-apodized FBG in a 1-μm band. We propose this low-cost and high-integration scheme for the preparation of a series of single-frequency seed sources in this wavelength range by characterizing the performance of 1030 nm and 1080 nm lasers. The lasers have a maximum SMSR of 66.3 dB and maximum output power of 134.6 mW. Additionally, the lasers have minimum Lorentzian linewidths that are measured to be 260.5 kHz; however, a minimum integral linewidth less than 180.4 kHz is observed by testing and analyzing the power spectra of the frequency noise values of the lasers.
Breast cancer is a common and threatening malignant disease with multiple biological and clinical subtypes. It can be categorized into subtypes of luminal A, luminal B, Her2 positive, and basal-like. ...Copy number variants (CNVs) have been reported to be a potential and even better biomarker for cancer diagnosis than mRNA biomarkers, because it is considerably more stable and robust than gene expression. Thus, it is meaningful to detect CNVs of different cancers. To identify the CNV biomarker for breast cancer subtypes, we integrated the CNV data of more than 2000 samples from two large breast cancer databases, METABRIC and The Cancer Genome Atlas (TCGA). A Monte Carlo feature selection-based and incremental feature selection-based computational method was proposed and tested to identify the distinctive core CNVs in different breast cancer subtypes. We identified the CNV genes that may contribute to breast cancer tumorigenesis as well as built a set of quantitative distinctive rules for recognition of the breast cancer subtypes. The tenfold cross-validation Matthew’s correlation coefficient (MCC) on METABRIC training set and the independent test on TCGA dataset were 0.515 and 0.492, respectively. The CNVs of
PGAP3, GRB7, MIR4728, PNMT, STARD3, TCAP
and
ERBB2
were important for the accurate diagnosis of breast cancer subtypes. The findings reported in this study may further uncover the difference between different breast cancer subtypes and improve the diagnosis accuracy.
Dysregulated rRNA synthesis by RNA polymerase I (Pol I) is associated with uncontrolled cell proliferation. Here, we report a box H/ACA small nucleolar RNA (snoRNA)-ended long noncoding RNA (lncRNA) ...that enhances pre-rRNA transcription (SLERT). SLERT requires box H/ACA snoRNAs at both ends for its biogenesis and translocation to the nucleolus. Deletion of SLERT impairs pre-rRNA transcription and rRNA production, leading to decreased tumorigenesis. Mechanistically, SLERT interacts with DEAD-box RNA helicase DDX21 via a 143-nt non-snoRNA sequence. Super-resolution images reveal that DDX21 forms ring-shaped structures surrounding multiple Pol I complexes and suppresses pre-rRNA transcription. Binding by SLERT allosterically alters individual DDX21 molecules, loosens the DDX21 ring, and evicts DDX21 suppression on Pol I transcription. Together, our results reveal an important control of ribosome biogenesis by SLERT lncRNA and its regulatory role in DDX21 ring-shaped arrangements acting on Pol I complexes.
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•SLERT is a box H/ACA snoRNA-ended lncRNA that enhances pre-rRNA transcription•DDX21 forms ring-shaped structures surrounding Pol I and inhibits Pol I transcription•SLERT binds to DDX21 and modulates DDX21 rings to evict their suppression on Pol I•SLERT-DDX21 interactions regulate differential expression of rDNAs
A long non-coding RNA promotes pre-ribosomal RNA transcription by loosening the ring-shaped structure surrounding multiple RNA Pol I complexes formed by RNA helicase DDX21.