BaCKgRoUND aND aIMS: Hepatocellular carcinoma (HCC) is associated with high malignancy rates. Recently, a known deacetylase silent information regulator 1 (SIRT1) was discovered in HCC, and its presence is positively correlated with malignancy and metastasis. N 6-methyladenosine (m 6 A) is the most prominent modification, but the exact mechanisms on how SIRT1 regulates m 6 A modification to induce hepatocarcinogenesis remain unclear. appRoaCH aND ReSUltS: Here we demonstrate that SIRT1 exerts an oncogenic role by down-regulating fat mass and obesity-associated protein (FTO), which is an m 6 A demethylase. A crucial component of small ubiquitin-related modifiers (SUMOs) E3 ligase, RANBP2, is activated by SIRT1, and it is indispensable for FTO SUMOylation at Lysine (K)-216 site that promotes FTO degradation. Moreover, Guanine nucleotide-binding protein G (o) subunit alpha (GNAO1) is identified as m 6 A downstream targets of FTO and tumor suppressor in HCC, and depletion of FTO by SIRT1 improves m 6 A + GNAO1 and down-regulates its mRNA expression. CoNClUSIoNS: We demonstrate an important mechanism whereby SIRT1 destabilizes FTO, steering the m 6 A + of downstream molecules and subsequent mRNA expression in HCC tumorigenesis. Our findings uncover a target of SIRT1 for therapeutic agents to treat HCC.

Identification of protein–protein interactions (PPIs) is a difficult and important problem in biology. Since experimental methods for predicting PPIs are both expensive and time-consuming, many computational methods have been developed to predict PPIs and interaction networks, which can be used to complement experimental approaches. However, these methods have limitations to overcome. They need a large number of homology proteins or literature to be applied in their method. In this paper, we propose a novel matrix-based protein sequence representation approach to predict PPIs, using an ensemble learning method for classification. We construct the matrix of Amino Acid Contact (AAC), based on the statistical analysis of residue-pairing frequencies in a database of 6323 protein–protein complexes. We first represent the protein sequence as a Substitution Matrix Representation (SMR) matrix. Then, the feature vector is extracted by applying algorithms of Histogram of Oriented Gradient (HOG) and Singular Value Decomposition (SVD) on the SMR matrix. Finally, we feed the feature vector into a Random Forest (RF) for judging interaction pairs and non-interaction pairs. Our method is applied to several PPI datasets to evaluate its performance. On the S.cerevisiae dataset, our method achieves 94.83% accuracy and 92.40% sensitivity. Compared with existing methods, and the accuracy of our method is increased by 0.11 percentage points. On the H.pylori dataset, our method achieves 89.06% accuracy and 88.15% sensitivity, the accuracy of our method is increased by 0.76%. On the Human PPI dataset, our method achieves 97.60% accuracy and 96.37% sensitivity, and the accuracy of our method is increased by 1.30%. In addition, we test our method on a very important PPI network, and it achieves 92.71% accuracy. In the Wnt-related network, the accuracy of our method is increased by 16.67%. The source code and all datasets are available at .

Context Previous studies suggest that maternal thyroid function affects fetal growth, but the association between combined thyroid hormones from early to late pregnancy and newborn birth weight remains unknown. Objective To explore the association of maternal thyroid function during early and late pregnancy with birth weight. Design A large prospective cohort study of a Chinese population. Setting This study recruited pregnant women who underwent first-trimester prenatal screenings at the International Peace Maternity and Child Health Hospital between January 2013 and December 2016. Participants This study enrolled 46,186 mothers in whom TSH, free thyroxine (FT4), T3, and thyroid peroxidase antibody concentrations were measured in the first and third trimesters and in whom data on birth weight were available. Main Outcome Measures Birth weight, small for gestational age, large for gestational age (LGA). Results A higher TSH or FT4 concentration, or a lower T3 concentration, during the first or third trimester was associated with a lower birth weight. The lowest percentiles of maternal FT4 (FT4 < 2.5th percentile) in both trimesters were associated with a 0.34-SD higher birth weight. The effect estimates were greater in those in the first trimester (0.23 SD) or in the third trimester (0.17 SD). The association of maternal TSH and FT4 with birth weight differed according to fetal sex. Conclusions Persistently low FT4 concentrations throughout pregnancy were associated with higher birth weight and an increased risk of LGA. Based on these findings, we recommend monitoring mildly altered concentrations of thyroid hormone throughout pregnancy.

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The imaging of sentinel lymph nodes (SLNs), the first defense against primary tumor metastasis, has been considered as an important strategy for noninvasive tracking tumor metastasis in clinics. In this study, we developed an imaging contrast system based on fluorescent dye-loaded mesoporous silica nanoparticles (MSNPs) that integrate near-infrared (NIR) fluorescent and photoacoustic (PA) imaging modalities for efficient SLN mapping. By balancing the ratio of dye and nanoparticles for simultaneous optimization of dual-modality imaging (NIR and PA), the dye encapsulated MSNP platform was set up to generate both a moderate NIR emission and PA signals simultaneously. Moreover, the underlying mechanisms of the relevance between optical and PA properties were discovered. Subsequently, dual-modality imaging was achieved to visualize tumor draining SLNs up to 2 weeks in a 4T1 tumor metastatic model. Obvious differences in uptake rate and contrast between metastatic and normal SLNs were observed both in vivo and ex vivo. Based on all these imaging data, it was demonstrated that the dye-loaded MSNPs allow detection of regional lymph nodes in vivo with time-domain NIR fluorescent and PA imaging methods efficiently.

Background/Aims: The placenta has been suggested to play a crucial role in the pathology of gestational diabetes mellitus (GDM). Placenta-specific microRNAs (miRNAs) and the corresponding targeting genes involved in the pathology of GDM still remain to be elucidated. We aimed to identify the dysregulated miRNAs and the corresponding mRNA targets through an integrated miRNA and mRNA transcriptomic profiles analysis and investigate the role of differentially expressed miR-138-5p/TBL1X in GDM. Methods: RNA sequencing (RNA-seq) was performed in 16 placentas from GDM and control group. Differentially expressed mRNAs and miRNAs in GDM were validated by quantitative PCR (qPCR). The wound healing assay and transwell migration assay were used to analyze cell migration ability. The cell proliferation was determined by CCK8 assay. Luciferase assay was used to confirm the direct binding of the targeted TBL1X with miR-138-5p. Results: Totally, 281 mRNAs and 32 miRNAs were found to be differentially expressed in the GDM placentas. The biological relationships of the miRNA/mRNA pairs were related to cellular development and function and organ morphology. Among the aberrantly expressed molecules, we selected miR-138-5p from the bioinformatics analysis and found that miR-138-5p significantly inhibited the migration and proliferation of trophoblasts (HTR-8/SVneo) by targeting the 3’-UTR of TBL1X. Furthermore, the aberrant expression of miR-138-5p and TBL1X was significantly correlated with the weight of the placenta. Conclusion: We present the first integrative analysis of miRNA and mRNA expression profiles in GDM placenta and uncover a more detailed role for miR-138-5p, as well as its target TBL1X in the pathology of GDM.

Diabetes is a highly prevalent metabolic disease that has emerged as a global challenge due to its increasing prevalence and lack of sustainable treatment. Diabetic kidney disease (DKD), which is one of the most frequent and severe microvascular complications of diabetes, is difficult to treat with contemporary glucose-lowering medications. The gut microbiota plays an important role in human health and disease, and its metabolites have both beneficial and harmful effects on vital physiological processes. In this review, we summarize the current findings regarding the role of gut microbial metabolites in the development and progression of DKD, which will help us better understand the possible mechanisms of DKD and explore potential therapeutic approaches for DKD.

The viral G-protein coupled receptor (vGPCR) specified by human herpesvirus 8 (HHV-8) open reading frame 74 (ORF74) is a ligand-independent chemokine receptor that has structural and functional homologues among other characterized gammaherpesviruses and related receptors in the betaherpesviruses. Sequence comparisons of the gammaherpesvirus vGPCRs revealed a highly conserved region in the C tail, just distal to the seventh transmembrane domain. Mutagenesis of the corresponding codons of HHV-8 ORF74 was carried out to provide C-tail-altered proteins for functional analyses. By measuring receptor-activated vascular endothelial growth factor promoter induction and NF-B, mitogen-activated protein kinase, and Ca 2؉ signaling, we found that while some altered receptors showed general signaling deficiencies, others had distinguishable activation profiles, suggestive of selective G␣ protein coupling. This was supported by the finding that vGPCR and representative functionally altered variants, vGPCR.8 (R322W) and vGPCR.15 (M325S), were affected differently by inhibitors of G␣ i (pertussis toxin), protein kinase C (GF109203X), and phosphatidylinositol 3-kinase (wortmannin). Consistent with the signaling data, [35 S]GTP␥S incorporation assays revealed preferential coupling of vGPCR.15 to G␣ q and an inability of vGPCR.8 to couple functionally to G␣ q . However, both variants, wild-type vGPCR, and a C-tail deletion version of the receptor were equally able to associate physically with G␣ q . Combined, our data demonstrate that HHV-8 vGPCR contains discrete sites of G␣ interaction and that receptor residues in the proximal region of the cytoplasmic tail are determinants of G␣ protein coupling specificity.