A comprehensive review on knowledge graphs for complex diseases.

In recent years, knowledge graphs (KGs) have gained a great deal of popularity as a tool for storing relationships between entities and for performing higher level reasoning. KGs in biomedicine and clinical practice aim to provide an elegant solution for diagnosing and treating complex diseases more efficiently and flexibly. Here, we provide a systematic review to characterize the state-of-the-art of KGs in the area of complex disease research. We cover the following topics: (1) knowledge sources, (2) entity extraction methods, (3) relation extraction methods and (4) the application of KGs in complex diseases. As a result, we offer a complete picture of the domain. Finally, we discuss the challenges in the field by identifying gaps and opportunities for further research and propose potential research directions of KGs for complex disease diagnosis and treatment.

PON-Tm: A Sequence-Based Method for Prediction of Missense Mutation Effects on Protein Thermal Stability Changes.

Proteins, as crucial macromolecules performing diverse biological roles, are central to numerous biological processes. The ability to predict changes in protein thermal stability due to mutations is vital for both biomedical research and industrial applications. However, existing experimental methods are often costly and labor-intensive, while structure-based prediction methods demand significant computational resources. In this study, we introduce PON-Tm, a novel sequence-based method for predicting mutation-induced thermal stability variations in proteins. PON-Tm not only incorporates features predicted by a protein language model from protein sequences but also considers environmental factors such as pH and the thermostability of the wild-type protein. To evaluate the effectiveness of PON-Tm, we compared its performance to four well-established methods, and PON-Tm exhibited superior predictive capabilities. Furthermore, to facilitate easy access and utilization, we have developed a web server.

MiR-200/183 family-mediated module biomarker for gastric cancer progression: an AI-assisted bioinformatics method with experimental functional survey.

BACKGROUND: Gastric cancer (GC) is a major cancer burden throughout the world with a high mortality rate. The performance of current predictive and prognostic factors is still limited. Integrated analysis is required for accurate cancer progression predictive biomarker and prognostic biomarkers that help to guide therapy. METHODS: An AI-assisted bioinformatics method that combines transcriptomic data and microRNA regulations were used to identify a key miRNA-mediated network module in GC progression. To reveal the module's function, we performed the gene expression analysis in 20 clinical samples by qRT-PCR, prognosis analysis by multi-variable Cox regression model, progression prediction by support vector machine, and in vitro studies to elaborate the roles in GC cells migration and invasion. RESULTS: A robust microRNA regulated network module was identified to characterize GC progression, which consisted of seven miR-200/183 family members, five mRNAs and two long non-coding RNAs H19 and CLLU1. Their expression patterns and expression correlation patterns were consistent in public dataset and our cohort. Our findings suggest a two-fold biological potential of the module: GC patients with high-risk score exhibited a poor prognosis (p-value < 0.05) and the model achieved AUCs of 0.90 to predict GC progression in our cohort. In vitro cellular analyses shown that the module could influence the invasion and migration of GC cells. CONCLUSIONS: Our strategy which combines AI-assisted bioinformatics method with experimental and clinical validation suggested that the miR-200/183 family-mediated network module as a "pluripotent module", which could be potential marker for GC progression.

SLC6A14 facilitates epithelial cell ferroptosis via the C/EBPß-PAK6 axis in ulcerative colitis.

Emerging evidence suggests that ferroptosis is involved in the pathogenesis of ulcerative colitis (UC). However, the key regulator of this process remains uncertain. In this study, we aimed to explore the roles of solute carrier (SLC) family 6 member 14 (SLC6A14) in regulating ferroptosis in UC. The expression of SLC6A14 was significantly increased and positively associated with that of prostaglandin-endoperoxide synthase 2 (PTGS2) in tissue samples from patients with UC. Moreover, a series of in vitro and in vivo experiments showed that SLC6A14 knockdown markedly suppressed ferroptosis. RNA sequencing revealed that SLC6A14 inhibited the expression of P21 (RAC1)-activated kinase 6 (PAK6) and that PAK6 knockdown abolished the effects of SLC6A14 on RAS-selective lethal 3 (RSL3)-induced ferroptosis in Caco-2 cells. Furthermore, chromatin immunoprecipitation (ChIP) and Western blot analysis demonstrated that SLC6A14 negatively regulated PAK6 expression in a CCAAT enhancer binding protein beta (C/EBPß)-dependent manner. Collectively, these findings indicate that SLC6A14 facilitates ferroptosis in UC by promoting C/EBPß expression and binding activity to inhibit PAK6 expression, suggesting that targeting SLC6A14-C/EBPß-PAK6 axis-mediated ferroptosis may be a promising therapeutic alternative for UC.

DeepTP: A Deep Learning Model for Thermophilic Protein Prediction.

Thermophilic proteins have important value in the fields of biopharmaceuticals and enzyme engineering. Most existing thermophilic protein prediction models are based on traditional machine learning algorithms and do not fully utilize protein sequence information. To solve this problem, a deep learning model based on self-attention and multiple-channel feature fusion was proposed to predict thermophilic proteins, called DeepTP. First, a large new dataset consisting of 20,842 proteins was constructed. Second, a convolutional neural network and bidirectional long short-term memory network were used to extract the hidden features in protein sequences. Different weights were then assigned to features through self-attention, and finally, biological features were integrated to build a prediction model. In a performance comparison with existing methods, DeepTP had better performance and scalability in an independent balanced test set and validation set, with AUC values of 0.944 and 0.801, respectively. In the unbalanced test set, DeepTP had an average precision (AP) of 0.536. The tool is freely available.

A Protein Co-Conservation Network Model Characterizes Mutation Effects on SARS-CoV-2 Spike Protein.

The emergence of numerous variants of SARS-CoV-2 has presented challenges to the global efforts to control the COVID-19 pandemic. The major mutation is in the SARS-CoV-2 viral envelope spike protein that is responsible for virus attachment to the host, and is the main target for host antibodies. It is critically important to study the biological effects of the mutations to understand the mechanisms of how mutations alter viral functions. Here, we propose a protein co-conservation weighted network (PCCN) model only based on the protein sequence to characterize the mutation sites by topological features and to investigate the mutation effects on the spike protein from a network view. Frist, we found that the mutation sites on the spike protein had significantly larger centrality than the non-mutation sites. Second, the stability changes and binding free energy changes in the mutation sites were positively significantly correlated with their neighbors' degree and the shortest path length separately. The results indicate that our PCCN model provides new insights into mutations on spike proteins and reflects the mutation effects on protein function alternations.

H19 promotes aerobic glycolysis, proliferation, and immune escape of gastric cancer cells through the microRNA-519d-3p/lactate dehydrogenase A axis.

Long noncoding RNAs (lncRNAs) have been investigated in multiple human cancers including gastric cancer (GC). Our research aims to explore the role of H19 in aerobic glycolysis, proliferation, and immune escape of GC cells. The expression of H19 in GC samples was analyzed using Gene Expression Profiling Interactive Analysis, Gene Expression Omnibus data, and real-time quantitative PCR analysis. Relative quantification of glucose consumption and lactate production from cell supernatant were applied to assess the aerobic glycolysis of GC cells. Subcellular fractionation, luciferase reporter, and western blot assays certified the binding between genes. Cell Counting Kit-8 and colony formation assays were used to determine GC cell proliferation. Flow cytometry, ELISA, and real-time quantitative PCR assays were applied to analyze the immunosuppressive effect of H19. H19 was highly expressed in samples of patients with GC, and associated with tumor growth in vivo. H19 knockdown suppressed glucose consumption, lactate production, and proliferation of GC cells by regulating the microRNA (miR)-519d-3p/lactate dehydrogenase A (LDHA) axis. Both miR-519d-3p depletion and LDHA overexpression could reverse the H19 knockdown-induced decrease in aerobic glycolysis and proliferation. Moreover, conditioned medium from stable knockdown H19 GC cells modulated the activity of immune cells including γδT cells, Jurkat cells, and tumor-associated macrophages in a miR-519d-3p/LDHA/lactate axis-dependent manner. The H19/miR-519d-3p/LDHA axis mainly contributed to aerobic glycolysis, proliferation, and immune escape of GC cells.

Simultaneous detection of four flavonoids and two alkaloids in rat plasma by LC-MS/MS and its application to a comparative study of the pharmacokinetics between Abri Herba and Abri mollis Herba extract after oral administration.

Abri Herba and Abri mollis Herba both were important members of the Leguminosae family in southwestern China. Abri mollis Herba was often used as Abri Herba due to their proximity, but there are few studies on pharmacokinetics to compare their main identical active compositions. A sensitive and selective high-performance liquid chromatography with tandem mass spectrometry method in the positive/negative electrospray ionization switching mode was developed and validated for the simultaneous analysis of four flavonoids and two alkaloids in rat plasma. The chromatographic separation was carried out on a C18 column with a gradient mobile phase consisting of methanol and 0.5% acetic acid. The detection of the target compounds was conducted in multiple-reaction monitoring mode with a hybrid triple quadrupole linear ion trap mass spectrometer equipped with positive/negative ion-switching electrospray ion source. The differences in pharmacokinetics were discovered, which indicated that the substitution between them is some degree of irrationality. The validated method was successfully applied to pharmacokinetic study of the six components in male rat plasma after oral administration of Abri Herba and Abri mollis Herba extract and the results in the study would provide a useful guide for the clinical application of Abri Herba with those in Abri mollis Herba.

Differential Expression of MiR-106b-5p and MiR-200c-3p in Newly Diagnosed Versus Chronic Primary Immune Thrombocytopenia Patients Based on Systematic Analysis.

BACKGROUND/AIMS: MicroRNAs (miRNAs) have been described to have important roles in primary immune thrombocytopenia (ITP). To gain additional understanding, we have now further evaluated the involvement of miRNAs in ITP. METHODS: Microarray experiments were performed to examine the expression profiles of miRNAs and mRNAs in samples from subjects with newly diagnosed ITP (G1), chronic ITP (G2), and normal controls. The systematic Pipeline of Outlier MicroRNA Analysis framework was applied to identify key miRNAs expressed in the G1 and G2 samples. Quantitative PCR and receiver operator characteristic curves were used to confirm the performance of key miRNAs. RESULTS: Compared with normal controls, 14 miRNAs (12 over-expressed and 2 under-expressed) and 7 over-expressed miRNAs were identified as key in G1 and G2 samples, respectively. miR-106b-5p, miR-200c-3p, and miR-92a-3p exhibited significantly different expression profiles among the groups. In particular, miR-106b-5p and miR-200c-3p were expressed at higher levels in patients with ITP compared to the normal controls. Furthermore, these two miRNAs expressions were even higher in patients with chronic ITP. CONCLUSION: MiR-106b-5p and miR-200c-3p may represent valuable biomarkers of ITP, although further studies are needed to confirm and assess the value of these potential biomarkers at various stages of ITP.

Deciphering the role of dimer interface in intrinsic dynamics and allosteric pathways underlying the functional transformation of DNMT3A.

BACKGROUND: DNMT3A, as de novo DNA methyltransferase, is essential for regulating gene expression through cellular development and differentiation. The functions of DNMT3A rely on its oligomeric states and allosteric regulations between its catalytic domain and binding partners. Despite recent resolution of autoinhibitory and active DNMT3A/3L crystal structures, the mechanism of their functional motions and interdomain allostery in regulating the activity remains to be established. METHODS: The hybrid approach, comprising Elastic Network Models coupled with information theory, Protein Structure Network, and sequence evolution analysis was employed to investigate intrinsic dynamics and allosteric properties of DNMT3A resolved in autoinhibitory and active states. RESULTS: The conformational transition between two states is characterized by global motions, and the homo-dimer displays the similar dynamic properties as tetramer, acting as the basic functional unit. The hinge residues with restricted fluctuations are clustered at the dimer interface, which are predicted to enjoy remarkably efficient signal transduction properties. The allosteric pathways through the dimer interface are achieved by a cascade of interactions predominantly involving conserved and co-evolved residues. CONCLUSIONS: Our results suggest that structural topology coupled with global motions indicates the structural origin of the functional transformation of DNMT3A. The comprehensive analysis further highlights the pivotal role of the dimer interface of DNMT3A both in defining the quaternary structure dynamics and establishing interdomain communications. GENERAL SIGNIFICANCE: Understanding the global motions of DNMT3As not only provides mechanical insights into the functions of such molecular machines, but also reveals the mediators that determine their allosteric regulations.

Node-Weighted Amino Acid Network Strategy for Characterization and Identification of Protein Functional Residues.

The study of functional residues (FRs) is essential for understanding protein functions and biological processes. The amino acid network (AAN) has become an emerging paradigm for studying FRs during the past decade. Current AAN models ignore the heterogeneity of nodes and treat amino acids in the AAN as the same. However, the properties of each amino acid node are of fundamental importance. We here proposed a node-weighted AAN strategy termed the node-weighted amino acid contact energy network (NACEN) to characterize and predict three types of FRs, namely, hot spots, catalytic residues, and allosteric residues. We first constructed NACENs with their nodes weighted based on structural, sequence, physicochemical, and dynamical properties of the amino acids and then characterized the FRs with the NACEN parameters. We finally built machine learning predictors to identify each type of FR. The results revealed that residues characterized with NACEN parameters are more distinguishable between FRs and non-FRs than those with unweighted network ones. With few features for classification, NACEN yields comparable performance for FR identification and provides residue level prediction for allosteric regulation. The proposed strategy can be easily implemented to other functional residue identification. An R package is also provided for NACEN construction and analysis at http://sysbio.suda.edu.cn/NACEN/index.html .

CT pulmonary angiogram for assessing the treatment outcome of acute pulmonary embolism.

OBJECTIVE: To discuss the value of CT pulmonary angiogram (CTPA) for assessing the treatment outcome of acute pulmonary embolism (APE). MATERIALS AND METHODS: CT pulmonary angiogram data and other clinical data were collected for 28 cases diagnosed as APE and analyzed retrospectively. The number and positions of emboli in the pulmonary artery, pulmonary artery obstruction index, right ventricular/left ventricular diameter ratio, main pulmonary artery/ascending aorta diameter ratio and blood oxygen saturation, and pulmonary arterial pressure were compared before and after treatment. RESULTS: Of 28 cases, emboli in the pulmonary artery completely or partially disappeared in 16 and 12 cases, respectively. CPTA indicated that the pulmonary arterial pressure decreased dramatically and the blood oxygen saturation increased after treatment in 26 cases. There were significant differences in the number and positions of pulmonary emboli and in pulmonary artery obstruction index before and after treatment in 28 cases (P < .05). However, no significant differences were found in the right ventricular/left ventricular diameter ratio or main pulmonary artery/ascending aorta diameter ratio (P > .05). CONCLUSION: CT pulmonary angiogram proved reliable for assessing the treatment efficacy of APE, providing more clinical information on the patients' status.

Identification of the genes regulated by Wnt-4, a critical signal for commitment of the ovary.

The indifferent mammalian embryonic gonad generates an ovary or testis, but the factors involved are still poorly known. The Wnt-4 signal represents one critical female determinant, since its absence leads to partial female-to-male sex reversal in mouse, but its signalling is as well implicated in the testis development. We used the Wnt-4 deficient mouse as a model to identify candidate gonadogenesis genes, and found that the Notum, Phlda2, Runx-1 and Msx1 genes are typical of the wild-type ovary and the Osr2, Dach2, Pitx2 and Tacr3 genes of the testis. Strikingly, the expression of these latter genes becomes reversed in the Wnt-4 knock-out ovary, suggesting a role in ovarian development. We identified the transcription factor Runx-1 as a Wnt-4 signalling target gene, since it is expressed in the ovary and is reduced upon Wnt-4 knock-out. Consistent with this, introduction of the Wnt-4 signal into early ovary cells ex vivo induces Runx-1 expression, while conversely Wnt-4 expression is down-regulated in the absence of Runx-1. We conclude that the Runx-1 gene can be a Wnt-4 signalling target, and that Runx-1 and Wnt-4 are mutually interdependent in their expression. The changes in gene expression due to the absence of Wnt-4 in gonads reflect the sexually dimorphic role of this signal and its complex gene network in mammalian gonad development.

Simultaneous Detection of Flavonoids, Phenolic Acids and Alkaloids in Abri Herba and Abri Mollis Herba using Liquid Chromatography Tandem Mass Spectrometry.

INTRODUCTION: Abri Herba has remarkable properties, such as cleanup heat detoxification, dampness and activating blood circulation to dissipate blood stasis; as a result, it has been applied to treat acute or chronic hepatitis and mastitis. Abri mollis Herba is often used as Abri Herba. Hierarchical cluster analysis (HCA) was applied to compare the similarities and differences of the chemical compositions in the two types of medicinal materials. OBJECTIVE: To establish a high-performance liquid chromatography and tandem mass spectrometry (HPLC-MS/MS) method for the simultaneous analysis of 15 flavonoids, two phenolic acids and three alkaloids in Abri Herba and Abri mollis Herba. METHODOLOGY: The chromatographic separation was performed on a C18 column with a mobile phase of methanol (A), acetonitrile (B) and 0.5‰ acetic acid in water (C) using gradient elution. The detection of the target compounds was performed in multiple-reaction monitoring (MRM) mode using a hybrid quadrupole linear ion trap mass spectrometer equipped with positive/negative ion-switching electrospray ionisation (ESI) source. RESULTS: The developed method is reliable, sensitive and specific. In addition, the method has been successfully applied to differentiate 15 batches of Abri Herba and 27 batches of Abri mollis Herba stems. Furthermore, a comparison of the contents among stems, roots and leaves from the same strain in seven batches of Abri mollis Herba and four batches of Abri Herba has also been performed. CONCLUSION: HPLC-MS/MS method is sensitive and selective and can be suitable for the reliable quality control of Abri mollis Herba and Abri Herba.

Wnt4, a pleiotropic signal for controlling cell polarity, basement membrane integrity, and antimüllerian hormone expression during oocyte maturation in the female follicle.

Wnt4 is a key signal that channels the developmental fate of the indifferent mammalian gonad toward the ovary, but whether Wnt4 has later roles during ovary development remains unknown. To investigate this, we inactivated the Wnt4 gene by crossing Amhr2Cre and doxycycline-inducible Rosa(rtTA)-knock-in Cre mice with mice carrying a floxed Wnt4 allele and used a novel Wnt4(mCherry)-knock-in mouse. In these models, ovarian folliculogenesis was compromised, and female fertility was severely reduced, and Wnt4 deficiency eventually led to premature ovarian failure. These anomalies were associated with cell polarity defects in the follicle. Within the follicle, laminin and type IV collagen assembled ectopic basement membrane-like structures, the cell adherens junction components N-cadherin and ß-catenin lost their polarized expression pattern, and expression of the gap junction protein connexin 43 was reduced by ~30% when compared with that of the controls. Besides these changes, expression of antimüllerian hormone (Amh) was inhibited in the absence of Wnt4 signaling in vivo. Consistent with this, Wnt4 signaling up-regulated Amh gene expression in KK1 cells in vitro. Thus, Wnt4 signaling is necessary during maturation of the ovarian follicles, where it coordinates expression of Amh, cell survival, and polarized organization of the follicular cells.

Simultaneous quantification of 25 active constituents in the total flavonoids extract from Herba Desmodii Styracifolii by high-performance liquid chromatography with electrospray ionization tandem mass spectrometry.

A sensitive and selective high-performance liquid chromatography coupled with electrospray ionization tandem mass spectrometry method has been developed and validated for the simultaneous determination of 25 active constituents, including 21 flavonoids and four phenolic acids in the total flavonoids extract from Herba Desmodii Styracifolii for the first time. Among the 25 compounds, seven compounds including caffeic acid, acacetin, genistein, genistin, diosmetin, diosmin and hesperidin were identified and quantified for the first time in Herba Desmodii Styracifolii. Chromatographic separation was accomplished on a ZORBAX SB-C18 (250 mm×4.6 mm, 5.0 µm) column using gradient elution of methanol and 0.1‰ acetic acid v/v at a flow rate of 1.0 mL/min. The identification and quantification of the analytes were achieved using negative electrospray ionization mass spectrometry in multiple-reaction monitoring mode. The method was fully validated in terms of limits of detection and quantification, linearity, precision and accuracy. The results indicated that the developed method is simple, rapid, specific and reliable. Furthermore, the developed method was successfully applied to quantify the 25 active components in six batches of total flavonoids extract from Herba Desmodii Styracifolii.

Simultaneous determination of linarin, naringenin and formononetin in rat plasma by LC-MS/MS and its application to a pharmacokinetic study after oral administration of Bushen Guchi Pill.

A sensitive and reproducible liquid chromatography tandem mass spectrometry (LC-MS/MS) method was developed and validated for the simultaneous determination of linarin, naringenin and formononetin in rat plasma after addition of sulfamethoxazole as the internal standard (IS). Separation was carried out on a Diamonsil C18 column (150 × 4.6 mm, 5 µm) with liner gradient elution using methanol (A) and 0.5‰ formic acid aqueous solution (B). Detection was performed on a triple-quadrupole linear ion trap mass spectrometer with the negative ion electrospray ionization in multiple-reaction monitoring (MRM) mode. The MRM transitions were m/z 591.2 → 283.2, 271.0 → 150.9, 266.9 → 252.0 and 252.0 → 155.9 for linarin, naringenin, formononetin and IS, respectively. All analytes showed good linearity within the concentration range (r > 0.9973). The lower limits of quantitation of linarin, naringenin and formononetin were 0.64, 1.07 and 1.04 ng/mL, respectively. Intra-day and inter-day precisions of the investigated components exhibited an RSD within 9.96%, and the accuracy (relative error) ranged from -11.25 to 9.38% at all quality control levels. The developed method was successfully applied to a pharmacokinetic study of linarin, naringenin and formononetin in rats after oral administration of Bushen Guchi Pill.

SVR_CAF: an integrated score function for detecting native protein structures among decoys.

An accurate score function for detecting the most native-like models among a huge number of decoy sets is essential to the protein structure prediction. In this work, we developed a novel integrated score function (SVR_CAF) to discriminate native structures from decoys, as well as to rank near-native structures and select best decoys when native structures are absent. SVR_CAF is a machine learning score, which incorporates the contact energy based score (CE_score), amino acid network based score (AAN_score), and the fast Fourier transform based score (FFT_score). The score function was evaluated with four decoy sets for its discriminative ability and it shows higher overall performance than the state-of-the-art score functions.

Identification of candidate miRNA biomarkers from miRNA regulatory network with application to prostate cancer.

BACKGROUND: MicroRNAs (miRNAs) are a class of non-coding regulatory RNAs approximately 22 nucleotides in length that play a role in a wide range of biological processes. Abnormal miRNA function has been implicated in various human cancers including prostate cancer (PCa). Altered miRNA expression may serve as a biomarker for cancer diagnosis and treatment. However, limited data are available on the role of cancer-specific miRNAs. Integrative computational bioinformatics approaches are effective for the detection of potential outlier miRNAs in cancer. METHODS: The human miRNA-mRNA target network was reconstructed by integrating multiple miRNA-mRNA interaction datasets. Paired miRNA and mRNA expression profiling data in PCa versus benign prostate tissue samples were used as another source of information. These datasets were analyzed with an integrated bioinformatics framework to identify potential PCa miRNA signatures. In vitro q-PCR experiments and further systematic analysis were used to validate these prediction results. RESULTS: Using this bioinformatics framework, we identified 39 miRNAs as potential PCa miRNA signatures. Among these miRNAs, 20 had previously been identified as PCa aberrant miRNAs by low-throughput methods, and 16 were shown to be deregulated in other cancers. In vitro q-PCR experiments verified the accuracy of these predictions. miR-648 was identified as a novel candidate PCa miRNA biomarker. Further functional and pathway enrichment analysis confirmed the association of the identified miRNAs with PCa progression. CONCLUSIONS: Our analysis revealed the scale-free features of the human miRNA-mRNA interaction network and showed the distinctive topological features of existing cancer miRNA biomarkers from previously published studies. A novel cancer miRNA biomarker prediction framework was designed based on these observations and applied to prostate cancer study. This method could be applied for miRNA biomarker prediction in other cancers.

The construction of an amino acid network for understanding protein structure and function.

Amino acid networks (AANs) are undirected networks consisting of amino acid residues and their interactions in three-dimensional protein structures. The analysis of AANs provides novel insight into protein science, and several common amino acid network properties have revealed diverse classes of proteins. In this review, we first summarize methods for the construction and characterization of AANs. We then compare software tools for the construction and analysis of AANs. Finally, we review the application of AANs for understanding protein structure and function, including the identification of functional residues, the prediction of protein folding, analyzing protein stability and protein-protein interactions, and for understanding communication within and between proteins.