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As the best adapted high altitude population, Tibetans feature a relatively high offspring survival rate. Genome-wide studies have identified hundreds of candidate SNPs related to high altitude adaptation of Tibetans, although most of them have unknown functional relevance. To explore the mechanisms behind successful reproduction at high altitudes, we compared the placental transcriptomes of Tibetans, sea level Hans (SLHan), and Han immigrants (ImHan). Among the three populations, placentas from ImHan showed a hyperactive gene expression pattern. Their increased activation demonstrates a hypoxic stress response similar to sea level individuals experiencing hypoxic conditions. Unlike ImHan, Tibetan placentas were characterized by the significant up-regulation of placenta-specific genes, and the activation of autophagy and the tricarboxylic acid (TCA) cycle. Certain conserved hypoxia response functions, including the antioxidant system and angiogenesis, were activated in both ImHan and Tibetans, but mediated by different genes. The coherence of specific transcriptome features linked to possible genetic contribution was observed in Tibetans. Furthermore, we identified a novel Tibetan-specific EPAS1 isoform with a partial deletion at exon six, which may be involved in the adaption to hypoxia through the EPAS1-centred gene network in the placenta. Overall, our results show that the placenta grants successful pregnancies in Tibetans by strengthening the natural functions of the placenta itself. On the other hand, the placenta of ImHan was in an inhabiting time-dependent acclimatization process representing a common hypoxic stress response pattern.

BackgroundMyopia is the leading cause of refractive errors. As its pathogenesis is poorly understood, we determined if the retinal VIP-VIPR2 signalling pathway axis has a role in controlling signalling output that affects myopia development in mice.MethodsAssociation analysis meta-study, single-cell transcriptome, bulk RNA sequencing, pharmacological manipulation and VIPR2 gene knockout studies were used to clarify if changes in the VIP-VIPR2 signalling pathway affect refractive development in mice.ResultsThe SNP rs6979985 of the VIPR2 gene was associated with high myopia in a Chinese Han cohort (randomceffect model: p=0.013). After either 1 or 2 days’ form deprivation (FD) retinal VIP mRNA expression was downregulated. Retinal single-cell transcriptome sequencing showed that VIPR2 was expressed mainly by bipolar cells. Furthermore, the cAMP signalling pathway axis was inhibited in some VIPR2+ clusters after 2 days of FD. The selective VIPR2 antagonist PG99-465 induced relative myopia, whereas the selective VIPR2 agonist Ro25-1553 inhibited this response. In Vipr2 knockout (Vipr2-KO) mice, refraction was significantly shifted towards myopia (pVipr2-KO mice were significantly larger than those in their WT littermates (pConclusionsLoss of VIPR2 function likely compromises bipolar cell function based on presumed changes in signal transduction due to altered signature electrical wave activity output in these mice. As these effects correspond with increases in form deprivation myopia (FDM), the VIP-VIPR2 signalling pathway axis is a viable novel target to control the development of this condition.

Background and objective Liver disease is a multifactorial complex disease with high global prevalence and poor long-term clinical efficacy and liver disease patients with different comorbidities often incorporate multiple phenotypes in the clinic. Thus, there is a pressing need to improve understanding of the complexity of clinical liver population to help gain more accurate disease subtypes for personalized treatment. Methods Individualized treatment of the traditional Chinese medicine (TCM) provides a theoretical basis to the study of personalized classification of complex diseases. Utilizing the TCM clinical electronic medical records (EMRs) of 6475 liver inpatient cases, we built a liver disease comorbidity network (LDCN) to show the complicated associations between liver diseases and their comorbidities, and then constructed a patient similarity network with shared symptoms (PSN). Finally, we identified liver patient subgroups using community detection methods and performed enrichment analyses to find both distinct clinical and molecular characteristics (with the phenotype-genotype associations and interactome networks) of these patient subgroups. Results From the comorbidity network, we found that clinical liver patients have a wide range of disease comorbidities, in which the basic liver diseases (e.g. hepatitis b, decompensated liver cirrhosis), and the common chronic diseases (e.g. hypertension, type 2 diabetes), have high degree of disease comorbidities. In addition, we identified 303 patient modules (representing the liver patient subgroups) from the PSN, in which the top 6 modules with large number of cases include 51.68% of the whole cases and 251 modules contain only 10 or fewer cases, which indicates the manifestation diversity of liver diseases. Finally, we found that the patient subgroups actually have distinct symptom phenotypes, disease comorbidity characteristics and their underlying molecular pathways, which could be used for understanding the novel disease subtypes of liver conditions. For example, three patient subgroups, namely Module 6 (M6, n = 638), M2 (n = 623) and M1 (n = 488) were associated to common chronic liver disease conditions (hepatitis, cirrhosis, hepatocellular carcinoma). Meanwhile, patient subgroups of M30 (n = 36) and M36 (n = 37) were mostly related to acute gastroenteritis and upper respiratory infection, respectively, which reflected the individual comorbidity characteristics of liver subgroups. Furthermore, we identified the distinct genes and pathways of patient subgroups and the basic liver diseases (hepatitis b and cirrhosis), respectively. The high degree of overlapping pathways between them (e.g. M36 with 93.33% shared enriched pathways) indicates the underlying molecular network mechanisms of each patient subgroup. Conclusions Our results demonstrate the utility and comprehensiveness of disease classification study based on community detection of patient network using shared TCM symptom phenotypes and it can be used to other more complex diseases.

Although hepatitis C virus (HCV) prevails in patients receiving methadone maintenance treatment (MMT), most do not receive anti-HCV therapy. This single-center observational study aimed to achieve HCV micro-elimination at an MMT center during the COVID-19 pandemic using a collaborative referral model, which comprised a referral-for-diagnosis stage (January 2020 to August 2020) and an on-site-diagnosis stage (September 2020 to January 2021). A multidisciplinary team was established and all MMT center patients were enrolled. HCV micro-elimination was defined as >90% of HCV-infected patients diagnosed and >80% of HCV-viremic patients treated. A total of 305 MMT patients, including 275 (90.2%) anti-HCV seropositive patients, were enrolled. Among 189 HCV-infected patients needing referral, the accumulative percentage receiving HCV RNA testing increased from 93 (49.2%) at referral-for-diagnosis stage to 168 (88.9%) at on-site-diagnosis stage. Among 138 HCV-viremic patients, the accumulative percentage receiving direct-acting antiviral (DAA) therapy increased from 77 (55.8%) at referral-for-diagnosis stage to 129 (93.5%) at on-site-diagnosis stage. We achieved an HCV RNA testing rate of 92.4% (254/275), an HCV treatment rate of 95.8% (203/212) and a sustained virological response rate of 94.1% (191/203). The collaborative referral model is highly effective in HCV RNA testing and HCV treatment uptake among MMT patients, achieving HCV micro-elimination.

In this paper, based on the improved convolutional neural network, in-depth analysis of the CT image of the new coronary pneumonia, using the U-Net series of deep neural networks to semantically segment the CT image of the new coronary pneumonia, to obtain the new coronary pneumonia area as the foreground and the remaining areas as the background of the binary image, provides a basis for subsequent image diagnosis. Secondly, the target-detection framework Faster RCNN extracts features from the CT image of the new coronary pneumonia tumor, obtains a higher-level abstract representation of the data, determines the lesion location of the new coronary pneumonia tumor, and gives its bounding box in the image. By generating an adversarial network to diagnose the lesion area of the CT image of the new coronary pneumonia tumor, obtaining a complete image of the new coronary pneumonia, achieving the effect of the CT image diagnosis of the new coronary pneumonia tumor, and three-dimensionally reconstructing the complete new coronary pneumonia model, filling the current the gap in this aspect, provide a basis to produce new coronary pneumonia prosthesis and improve the accuracy of diagnosis.

Chaperonin-containing tailless complex polypeptide 1 subunit 6A (CCT6A) plays roles in cancer progression, but its clinical implication in hepatocellular carcinoma (HCC) management needs further exploration. This study aimed to explore the correlation of CCT6A with clinical characteristics, liver function indexes, tumor markers and prognosis in HCC patients.240 HCC patients were retrospectively enrolled. 240 pairs of cancer and adjacent specimens were used to evaluate CCT6A protein expression by immunohistochemistry assay; among which 184 pairs were used to assess CCT6A mRNA expression by reverse transcription-quantitative polymerase chain reaction.Both CCT6A protein expression and CCT6A mRNA expression were higher in HCC tumor tissue than in adjacent tissue (P0.001). The receiver operating characteristic (ROC) curve showed that CCT6A had certain potential in discriminating tumor tissues from adjacent tissues. In addition, CCT6A protein expression was positively correlated with multifocal tumor nodule (P = 0.001), ≥ 5.0 cm tumor size (P = 0.028), BCLC stage (P = 0.002) and abnormal AFP (P = 0.021). Besides, CCT6A mRNA expression was associated with multifocal tumor nodule (P = 0.025), ≥ 5.0 cm tumor size (P = 0.018), higher BCLC stage (P = 0.036), abnormal CA199 (P = 0.027) and abnormal AFP (P = 0.008). However, no correlation was found in CCT6A with liver function indexes (all P ≥ 0.05). Moreover, CCT6A protein and mRNA high expressions were both correlated with poor accumulating overall survival (OS) (P = 0.004, P = 0.002, respectively). Furthermore, CCT6A protein high expression (vs. low) independently predicted shorter OS (P = 0.027).CCT6A serves as a possible biomarker reflecting tumor features and prognostication in HCC patients.

BACKGROUND Transglutaminase 3 (TGM3) regulates multiple oncogene pathways (GSK-3β/β-catenin pathway, Akt/ERK pathway, etc.) to promote hepatocellular carcinoma (HCC) cell proliferation, migration and invasion, however, its clinical value for HCC management is still limited. Therefore, we conducted this study to compare the TGM3 expression between tumor tissue and paired adjacent noncancerous tissue, aiming to explore the clinical application of TGM3 in HCC patients. METHODS Totally, 208 HCC patients were enrolled and their clinicopathological features were collected. Then, 208 pairs of HCC specimens and adjacent noncancerous specimens were used to detect TGM3 protein expression by IHC assay and assessed by a semi-quantitative scoring method. Besides, 157 pairs were proposed to detect TGM3 mRNA expression by RT-qPCR. RESULTS Both TGM3 protein (P

Background Myopia is a good model for understanding the interaction between genetics and environmental stimuli. Here we dissect the biological processes affecting myopia progression. Methods Human Genetic Analyses: (1) gene set analysis (GSA) of new genome wide association study (GWAS) data for 593 individuals with high myopia (refraction ≤ -6 diopters [D]); (2) over-representation analysis (ORA) of 196 genes with de novo mutations, identified by whole genome sequencing of 45 high-myopia trio families, and (3) ORA of 284 previously reported myopia risk genes. Contributions of the enriched signaling pathways in mediating the genetic and environmental interactions during myopia development were investigated in vivo and in vitro. Results All three genetic analyses showed significant enrichment of four KEGG signaling pathways, including amphetamine addiction, extracellular matrix (ECM) receptor interaction, neuroactive ligand-receptor interaction, and regulation of actin cytoskeleton pathways. In individuals with extremely high myopia (refraction ≤ -10 D), the GSA of GWAS data revealed significant enrichment of the HIF-1α signaling pathway. Using human scleral fibroblasts, silencing the key nodal genes within protein-protein interaction networks for the enriched pathways antagonized the hypoxia-induced increase in myofibroblast transdifferentiation. In mice, scleral HIF-1α downregulation led to hyperopia, whereas upregulation resulted in myopia. In human subjects, near work, a risk factor for myopia, significantly decreased choroidal blood perfusion, which might cause scleral hypoxia. Interpretation Our study implicated the HIF-1α signaling pathway in promoting human myopia through mediating interactions between genetic and environmental factors. Funding National Natural Science Foundation of China grants; Natural Science Foundation of Zhejiang Province.

Worldwide, myopia is the leading cause of visual impairment. It results from inappropriate extension of the ocular axis and concomitant declines in scleral strength and thickness caused by extracellular matrix (ECM) remodeling. However, the identities of the initiators and signaling pathways that induce scleral ECM remodeling in myopia are unknown. Here, we used single-cell RNA-sequencing to identify pathways activated in the sclera during myopia development. We found that the hypoxia-signaling, the eIF2-signaling, and mTOR-signaling pathways were activated in murine myopic sclera. Consistent with the role of hypoxic pathways in mouse model of myopia, nearly one third of human myopia risk genes from the genome-wide association study and linkage analyses interact with genes in the hypoxia-inducible factor-1α (HIF-1α)–signaling pathway. Furthermore, experimental myopia selectively induced HIF-1α up-regulation in the myopic sclera of both mice and guinea pigs. Additionally, hypoxia exposure (5% O2) promoted myofibroblast transdifferentiation with down-regulation of type I collagen in human scleral fibroblasts. Importantly, the antihypoxia drugs salidroside and formononetin down-regulated HIF-1α expression as well as the phosphorylation levels of eIF2α and mTOR, slowing experimental myopia progression without affecting normal ocular growth in guinea pigs. Furthermore, eIF2α phosphorylation inhibition suppressed experimental myopia, whereas mTOR phosphorylation induced myopia in normal mice. Collectively, these findings defined an essential role of hypoxia in scleral ECM remodeling and myopia development, suggesting a therapeutic approach to control myopia by ameliorating hypoxia.

Transcriptomic analyses have revealed an unexpected complexity in the eukaryote transcriptome, which includes not only protein-coding transcripts but also an expanding catalog of noncoding RNAs (ncRNAs). Diverse coding and noncoding RNAs (ncRNAs) perform functions through interaction with each other in various cellular processes. In this project, we have developed RAID (http://www.rna-society.org/raid), an RNA-associated (RNA–RNA/RNA–protein) interaction database. RAID intends to provide the scientific community with all-in-one resources for efficient browsing and extraction of the RNA-associated interactions in human. This version of RAID contains more than 6100 RNA-associated interactions obtained by manually reviewing more than 2100 published papers, including 4493 RNA–RNA interactions and 1619 RNA–protein interactions. Each entry contains detailed information on an RNA-associated interaction, including RAID ID, RNA/protein symbol, RNA/protein categories, validated method, expressing tissue, literature references (Pubmed IDs), and detailed functional description. Users can query, browse, analyze, and manipulate RNA-associated (RNA–RNA/RNA–protein) interaction. RAID provides a comprehensive resource of human RNA-associated (RNA–RNA/RNA–protein) interaction network. Furthermore, this resource will help in uncovering the generic organizing principles of cellular function network.

For gene expression in non-cancerous complex diseases, we systemically evaluated the sensitivities of biological discoveries to violation of the common normalization assumption. Our results indicated that gene expression may be widely up-regulated in digestive system and musculoskeletal diseases. However, global signal intensities showed little difference in other four disease types.

Cell death is a critical biological process, serving many important functions within multicellular organisms. Aberrations in cell death can contribute to the pathology of human diseases. Significant progress made in the research area enormously speeds up our understanding of the biochemical and molecular mechanisms of cell death. According to the distinct morphological and biochemical characteristics, cell death can be triggered by extrinsic or intrinsic apoptosis, regulated necrosis, autophagic cell death, and mitotic catastrophe. Nevertheless, the realization that all of these efforts seek to pursue an effective treatment and cure for the disease has spurred a significant interest in the development of promising biomarkers of cell death to early diagnose disease and accurately predict disease progression and outcome. In this review, we summarize recent knowledge about cell death, survey current and emerging biomarkers of cell death, and discuss the relationship with human diseases.

An increasing number of experiments have been designed to detect intracellular and intercellular molecular interactions. Based on these molecular interactions (especially protein interactions), molecular networks have been built for using in several typical applications, such as the discovery of new disease genes and the identification of drug targets and molecular complexes. Because the data are incomplete and a considerable number of false-positive interactions exist, protein interactions from different sources are commonly integrated in network analyses to build a stable molecular network. Although various types of integration strategies are being applied in current studies, the topological properties of the networks from these different integration strategies, especially typical applications based on these network integration strategies, have not been rigorously evaluated. In this paper, systematic analyses were performed to evaluate 11 frequently used methods using two types of integration strategies: empirical and machine learning methods. The topological properties of the networks of these different integration strategies were found to significantly differ. Moreover, these networks were found to dramatically affect the outcomes of typical applications, such as disease gene predictions, drug target detections, and molecular complex identifications. The analysis presented in this paper could provide an important basis for future network-based biological researches.

Programmed cell death (PCD) is a critical biological process involved in many important processes, and defects in PCD have been linked with numerous human diseases. In recent years, the protein architecture in different PCD subroutines has been explored, but our understanding of the global network organization of the noncoding RNA (ncRNA)-mediated cell death system is limited and ambiguous. Hence, we developed the comprehensive bioinformatics resource (ncRDeathDB, www.rna-society.org/ncrdeathdb ) to archive ncRNA-associated cell death interactions. The current version of ncRDeathDB documents a total of more than 4600 ncRNA-mediated PCD entries in 12 species. ncRDeathDB provides a user-friendly interface to query, browse and manipulate these ncRNA-associated cell death interactions. Furthermore, this resource will help to visualize and navigate current knowledge of the noncoding RNA component of cell death and autophagy, to uncover the generic organizing principles of ncRNA-associated cell death systems, and to generate valuable biological hypotheses.

Ovarian cancer remains a dismal disease with diagnosing in the late, metastatic stages, therefore, there is a growing realization of the critical need to develop effective biomarkers for understanding underlying mechanisms. Although existing evidences demonstrate the important role of the single genetic abnormality in pathogenesis, the perturbations of interactors in the complex network are often ignored. Moreover, ovarian cancer diagnosis and treatment still exist a large gap that need to be bridged. In this work, we adopted a network-based survival-associated approach to capture a 12-gene network module based on differential co-expression PPI network in the advanced-stage, high-grade ovarian serous cystadenocarcinoma. Then, regulatory genes (protein-coding genes and non-coding genes) direct interacting with the module were found to be significantly overlapped with cell death genes. More importantly, these overlapping genes tightly clustered together pointing to the module, deciphering the crosstalk between network-based survival-associated module and cell death in ovarian cancer.

Synthetic biologists have developed DNA/molecular modules that perform genetic logic operations in living cells to track key moments in a cell's life or change the fate of a cell. Increasing evidence has also revealed that diverse genetic logic gates capable of generating a Boolean function play critically important roles in synthetic biology. Basic genetic logic gates have been designed to combine biological science with digital logic. SynBioLGDB (http://bioinformatics.ac.cn/synbiolgdb/) aims to provide the synthetic biology community with a useful resource for efficient browsing and visualization of genetic logic gates. The current version of SynBioLGDB documents more than 189 genetic logic gates with experimental evidence involving 80 AND gates and 16 NOR gates, etc. in three species (Human, Escherichia coli and Bacillus clausii). SynBioLGDB provides a user-friendly interface through which conveniently to query and browse detailed information about these genetic logic gates. SynBioLGDB will enable more comprehensive understanding of the connection of genetic logic gates to execute complex cellular functions in living cells.

Background Late-life depression is common among elderly patients. Ignorance of the health problem, either because of under-diagnosis or under-treatment, causes additional medical cost and comorbidity. For a better health and quality of life (QoL), evaluation, prevention and treatment of late-life depression in elderly patients is essential. Methods This study examined (1) the differences of clinical characteristics, degree of improvement on QoL and functionality on discharge between non-depressed and depressed elderly inpatients and (2) factors associated with QoL on discharge. Four hundred and seventy-one elderly inpatients admitted to a geriatric evaluation and management unit (GEMU) from 2009 to 2010 were enrolled in this study. Comprehensive geriatric assessment including the activities of daily living (ADL), geriatric depression scale, and mini-mental state examination were conducted. QoL was assessed using the European Quality of Life-5 Dimensions and the European Quality of Life-5 Dimensions Visual Analog Scale on discharge. Information on hospital stay and Charlson comorbidity index were obtained by chart review. Chi-square tests, independent t-tests, Mann–Whitney U tests and multiple linear regressions were used in statistical analysis. Results Worse QoL and ADL on discharge were found among the depressed. Depressive symptoms, female gender, duration of hospital stay, and rehabilitation were significant factors affecting QoL on discharge in linear regression models. Conclusions The importance of the diagnosis and treatment of depression among elderly inpatients should not be overlooked during hospital stay and after discharge. Greater efforts should be made to improve intervention with depressed elderly inpatients.

Normalization of array data relies on the assumption that most genes are not altered, which means that the signals for different samples should be scaled to have similar median or average values. However, accumulating evidence suggests that gene expression could be widely up-regulated in cancers. Our previous results and subsequent findings have shown that violation of the assumption led to erroneous interpretation of microarray data. To decipher the global signal features of microarray data from cancer samples, we empirically evaluated a large collection of gene and miRNA expression profiles and copy-number variation arrays. Our results showed that, at the transcriptomic level, genes and miRNAs are widely over-expressed in a large proportion of cancers. In contrast, at the genomic level, global raw signal intensities for methylation and copy number variation show negligible differences between cancer and normal samples. These results force us to re-evaluate the proper use of normalization procedures under different experimental conditions and for different array platforms.

MicroRNAs (miRNAs) are a class of small noncoding RNAs that can regulate gene expression by binding to target mRNAs and induce translation repression or RNA degradation. There have been many studies indicating that both miRNAs and mRNAs display aberrant expression in breast cancer. Previously, most researches into the molecular mechanism of breast cancer examined miRNA expression patterns and mRNA expression patterns separately. In this study, we systematically analysed miRNA-mRNA paired variations (MMPVs), which are miRNA-mRNA pairs whose pattern of regulation can vary in association with biopathological features, such as the oestrogen receptor (ER), TP53 and human epidermal growth factor receptor 2 (HER2) genes, survival time, and breast cancer subtypes. We demonstrated that the existence of MMPVs is general and widespread but that there is a general unbalance in the distribution of MMPVs among the different biopathological features. Furthermore, based on studying MMPVs that are related to multiple biopathological features, we propose a potential crosstalk mechanism between ER and HER2.