Development and Validation of a Proximity Labeling Fusion Protein Construct to Identify the Protein-Protein Interactions of Transcription Factors.

Dynamic interactions between transcription factors govern changes in gene expression that mediate changes in cell state accompanying injury response and regeneration. Transcription factors frequently function as obligate dimers whose activity is often modulated by post-translational modifications. These critical and often transient interactions are not easily detected by traditional methods to investigate protein-protein interactions. This chapter discusses the design and validation of a fusion protein involving a transcription factor tethered to a proximity labeling ligase, APEX2. In this technique, proteins are biotinylated within a small radius of the transcription factor of interest, regardless of time of interaction. Here we discuss the validations required to ensure proper functioning of the transcription factor proximity labeling tool and the sample preparation of biotinylated proteins for mass spectrometry analysis of putative protein interactors.

Neuroinflammation inhibition and neuroprotective effects of purpurin, a potential anti-AD compound, screened via network proximity and gene enrichment analyses.

Alzheimer's disease (AD) is a complex neurodegenerative disease without any effective preventive or therapeutic drugs. Natural products with stable structures and pharmacological characteristics are valuable sources for the development of novel drugs for many complex diseases. This study aimed to discover potential natural compounds for the treatment of AD using new technologies and methods and explore the efficacy and mechanism of candidate compounds. AD-related large-scale genetic datasets were collated to construct disease-PPIs and natural products were collected from six databases to construct compound-protein interactions (CPIs). Potential relationships between natural compounds and AD were predicted via network proximity and gene enrichment analyses. Then, five AD-related cell models and d-galactose-induced aging rat model were established to evaluate the neuroprotective effects of candidate compounds in vitro and in vivo. We identified that 267 natural compounds were predicted to have close connections with AD and 19 compounds could exert protective effect in at least one cell model. Notably, purpurin exerted protective effect in three cell models and significantly improved the cognitive learning and memory functions, reduced the oxidative stress injuries and neuroinflammation, and enhanced the synaptic plasticity and neurotrophic effect in the brain of d-galactose-treated rats. In this study, AD-related natural compounds were identified via network proximity and gene enrichment analyses. In vivo and in vitro experiments revealed the therapeutic potential of purpurin for AD treatment, laying the foundation for further in-depth research and providing valuable information for the development of novel anti-AD drugs.

Probing hot spots of protein-protein interactions mediated by the safety-belt region of REV7.

REV7 is a HORMA (Hop1, Rev7, Mad2) family adaptor protein best known as an accessory subunit of the translesion synthesis (TLS) DNA polymerase ζ (Polζ). In this role, REV7 binds REV3, the catalytic subunit of Polζ, by locking REV7-binding motifs (RBMs) in REV3 underneath the REV7 safety-belt loop. The same mechanism is used by REV7 to interact with RBMs from other proteins in DNA damage response (DDR) and mitosis. Because of the importance of REV7 for TLS and other DDR pathways, targeting REV7:RBM protein-protein interactions (PPIs) with small molecules has emerged as a strategy to enhance cancer response to genotoxic chemotherapy. To identify druggable pockets at the REV7:RBM interface, we performed computational analyses of REV7 complexed with several RBM partners. The contributions of different interface regions to REV7:RBM stabilization were corroborated experimentally. These studies provide insights into key intermolecular interactions and establish targetable regions of REV7 for the design of REV7:RBM PPI inhibitors.

S-CDK-regulated bipartite interaction of Mcm10 with MCM is essential for DNA replication.

Mcm10 plays an essential role in the activation of replicative helicase CMG through the cell cycle-regulated interaction with the prototype MCM double hexamer in Saccharomyces cerevisiae. In this study, we reported that Mcm10 is phosphorylated by S-phase cyclin-dependent kinases (S-CDKs) at S66, which enhances Mcm10--MCM association during the S phase. S66A single mutation or even deletion of whole N-terminus (a.a. 1-128) only causes mild growth defects. Nevertheless, S66 becomes indispensable in the absence of the Mcm10 C-terminus ((a.a. 463-571), the major MCM-binding domain. Using a two-degron strategy to efficiently deplete Mcm10, we show that mcm10-S66AΔC has a severe defect in proceeding into the S phase. Notably, both lethality and S-phase deficiency can be rescued by artificially tethering mcm10-S66AΔC to MCM. These findings illustrate how the Mcm10-MCM association is regulated as a crucial event in DNA replication initiation.

Identification and validation of hub differential genes in pulmonary sarcoidosis.

A total of 138 cDEGs were screened from mediastinal lymph nodes and peripheral whole blood. Among them, 6 hub cDEGs including CTSS, CYBB, FPR2, MNDA, TLR1 and TLR8 with elevated degree and betweenness levels were illustrated in protein-protein interaction network. In comparison to healthy controls, CTSS (1.61 vs. 1.05), CYBB (1.68 vs. 1.07), FPR2 (2.77 vs. 0.96), MNDA (2.14 vs. 1.23), TLR1 (1.56 vs. 1.09), and TLR8 (2.14 vs. 0.98) displayed notably elevated expression levels within pulmonary sarcoidosis PBMC samples (P < 0.0001 for FPR2 and P < 0.05 for others), echoing with prior mRNA microarray findings. The most significant functional pathways were immune response, inflammatory response, plasma membrane and extracellular exosome, with 6 hub cDEGs distributing along these pathways. CTSS, CYBB, FPR2, MNDA, TLR1, and TLR8 could be conducive to improving the diagnostic process and understanding the underlying mechanisms of pulmonary sarcoidosis.

In-silico analysis predicts disruption of normal angiogenesis as a causative factor in osteoporosis pathogenesis.

Angiogenesis-osteogenesis coupling is critical for proper functioning and maintaining the health of bones. Any disruption in this coupling, associated with aging and disease, might lead to loss of bone mass. Osteoporosis (OP) is a debilitating bone metabolic disorder that affects the microarchitecture of bones, gradually leading to fracture. Computational analysis revealed that normal angiogenesis is disrupted during the progression of OP, especially postmenopausal osteoporosis (PMOP). The genes associated with OP and PMOP were retrieved from the DisGeNET database. Hub gene analysis and molecular pathway enrichment were performed via the Cytoscape plugins STRING, MCODE, CytoHubba, ClueGO and the web-based tool Enrichr. Twenty-eight (28) hub genes were identified, eight of which were transcription factors (HIF1A, JUN, TP53, ESR1, MYC, PPARG, RUNX2 and SOX9). Analysis of SNPs associated with hub genes via the gnomAD, I-Mutant2.0, MUpro, ConSurf and COACH servers revealed the substitution F201L in IL6 as the most deleterious. The IL6 protein was modeled in the SWISS-MODEL server and the substitution was analyzed via the YASARA FoldX plugin. A positive ΔΔG (1.936) of the F201L mutant indicates that the mutated structure is less stable than the wild-type structure is. Thirteen hub genes, including IL6 and the enriched molecular pathways were found to be profoundly involved in angiogenesis/endothelial function and immune signaling. Mechanical loading of bones through weight-bearing exercises can activate osteoblasts via mechanotransduction leading to increased bone formation. The present study suggests proper mechanical loading of bone as a preventive strategy for PMOP, by which angiogenesis and the immune status of the bone can be maintained. This in silico analysis could be used to understand the molecular etiology of OP and to develop novel therapeutic approaches.

Temperature-jump microscopy and interaction of Hsp70 heat shock protein with a client protein in vivo.

Biomolecular processes such as protein-protein interactions can depend strongly on cell type and even vary within a single cell type. Here we develop a microscope with a Peltier-controlled temperature stage, a laser temperature jump to induce heat stress, and an autofocusing feature to mitigate temperature drift during experiments, to study a protein-protein interaction in a selected cell type within a live organism, the zebrafish larva. As an application of the instrument, we show that there is considerable cell-to-cell variation of the heat shock protein Hsp70 binding to one of its clients, phosphoglycerate kinase in vivo. We adapt a key feature from our previous folding study, rare transformation of cells within the larva, so that individual cells can be imaged and differentiated for cell-to-cell response. Our approach can be extended to other organisms and cell types than the ones demonstrated in this work.

Identification of function modules in the co-expression protein-protein interaction network of Bombyx mori in response to Beauveria bassiana infection.

Beauveria bassiana (B. bassiana) is a common fungal disease in sericulture. Previous research has primarily focused on investigating genes involved in innate immunity. However, the response of Bombyx mori (B. mori) to B. bassiana requires the coordination of other biological processes in addition to the immune system. We measured protein expression profile of B. mori after inoculating B. bassiana using iTRAQ technology in previous. Here we constructed a co-expression protein-protein interaction network of B. mori in response to B. bassiana infection. Subnetworks and modules were analyzed, and the functions of these modules were annotated. The results revealed the identification of numerous proteins associated with cellular immunity, including those involved in phagosomes, lysosomes, mTOR signaling, sugar metabolism, and the ubiquitin-proteasome pathway. Meanwhile, we observed that the pathways involved in protein synthesis were activated, including pyruvate and purine metabolism, RNA transport, ribosome, protein processing in endoplasmic reticulum, and protein export pathways, during B. bassiana infection. Based on this analysis, we selected six candidate genes (shock protein, ribosome, translocon, actin muscle-type A2, peptidoglycan recognition protein, and collagenase) that were found to be related to the response to B. bassiana. Further verification experiments demonstrated significant changes in their expression levels after inoculation with B. bassiana. These research findings provide new insights into the molecular mechanism of insect immune response to fungal infection.

The Effect of Vitamin D Deficiency on Immune-Related Hub Genes: A Network Analysis Associated With Type 1 Diabetes.

Background Type 1 diabetes (T1D) is an autoimmune disorder that results in the destruction of pancreatic beta cells, causing a shortage of insulin secretion. The development of T1D is influenced by both genetic predisposition and environmental factors, such as vitamin D. This vitamin is known for its ability to regulate the immune system and has been associated with a decreased risk of T1D. However, the specific ways in which vitamin D affects immune regulation and the preservation of beta cells in T1D are not yet fully understood. Gaining a better understanding of these interactions is essential for identifying potential targets for preventing and treating T1D. Methods The analysis focused on two Gene Expression Omnibus (GEO) datasets, namely, GSE55098 and GSE50012, to detect differentially expressed genes (DEGs). Enrichr (Ma'ayan Laboratory, New York, NY) was used to perform enrichment analysis for the Gene Ontology (GO) biological process and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways. The Search Tool for the Retrieval of Interacting Genes 12.0 (STRING) database was used to generate a protein-protein interaction (PPI) network. The Cytoscape 3.10.1 (Cytoscape Team, San Diego, CA) was used to analyze the PPI network and discover the hub genes. Results The DEGs in both datasets were identified using the GEO2R tool, with a particular focus on genes exhibiting contrasting regulations. Enrichment analysis unveiled the participation of these oppositely regulated DEGs in processes relevant to the immune system. Cytoscape analysis of the PPI network revealed five hub genes, MNDA, LILRB2, FPR2, HCK, and FCGR2A, suggesting their potential role in the pathogenesis of T1D and the response to vitamin D. Conclusion The study elucidates the complex interaction between vitamin D metabolism and immune regulation in T1D. The identified hub genes provide important knowledge on the molecular pathways that underlie T1D and have the potential to be targeted for therapeutic intervention. This research underscores the importance of vitamin D in the immune system's modulation and its impact on T1D development.

Plasma proteomics for risk prediction of Alzheimer's disease in the general population.

We aimed to develop and validate a protein risk score for predicting Alzheimer's disease (AD) and compare its performance with a validated clinical risk model (Cognitive Health and Dementia Risk Index for AD [CogDrisk-AD]) and apolipoprotein E (APOE) genotypes. The development cohort, consisting of 35,547 participants from England in the UK Biobank, was randomly divided into a 7:3 training-testing ratio. The validation cohort included 4667 participants from Scotland and Wales in the UK Biobank. In the training set, an AD protein risk score was constructed using 31 proteins out of 2911 proteins. In the testing set, the AD protein risk score had a C-index of 0.867 (95% CI, 0.828, 0.906) for AD prediction, followed by CogDrisk-AD risk factors (C-index, 0.856; 95% CI, 0.823, 0.889), and APOE genotypes (C-index, 0.705; 95% CI, 0.660, 0.750). Adding the AD protein risk score to CogDrisk-AD risk factors (C-index increase, 0.050; 95% CI, 0.008, 0.093) significantly improved the predictive performance for AD. However, adding CogDrisk-AD risk factors (C-index increase, 0.040; 95% CI, -0.007, 0.086) or APOE genotypes (C-index increase, 0.000; 95% CI, -0.054, 0.055) to the AD protein risk score did not significantly improve the predictive performance for AD. The top 10 proteins with the highest coefficients in the AD protein risk score contributed most of the predictive power for AD risk. These results were verified in the external validation cohort. EGFR, GFAP, and CHGA were identified as key proteins within the protein network. Our result suggests that the AD protein risk score demonstrated a good predictive performance for AD risk.

Plant Phytochrome Interactions Decode Light and Temperature Signals.

Plant phytochromes perceive red and far-red light to elicit adaptations to the changing environment. Downstream physiological responses revolve around red-light-induced interactions with phytochrome-interacting factors (PIF). Phytochromes double as thermoreceptors, owing to the pronounced temperature dependence of thermal reversion from the light-adapted Pfr to the dark-adapted Pr state. Here, we assess whether thermoreception may extend to the phytochrome:PIF interactions. While the association between Arabidopsis (Arabidopsis thaliana) PHYTOCHROME B (PhyB) and several PHYTOCHROME-INTERACTING FACTOR (PIF) variants moderately accelerates with temperature, the dissociation does more so, thus causing net destabilization of the phytochrome:PIF complex. Markedly different temperature profiles of PIF3 and PIF6 might underlie stratified temperature responses in plants. Accidentally, we identify a photoreception mechanism under strong continuous light, where the extent of phytochrome:PIF complexation decreases with red-light intensity rather than increases. Mathematical modeling rationalizes this attenuation mechanism and ties it to rapid red-light-driven Pr⇄Pfr interconversion and complex dissociation out of Pr. Varying phytochrome abundance, e.g., during diurnal and developmental cycles, and interaction dynamics, e.g., across different PIFs, modify the nature and extent of attenuation, thus permitting light-response profiles more malleable than possible for the phytochrome Pr⇄Pfr interconversion alone. Our data and analyses reveal a photoreception mechanism with implications for plant physiology, optogenetics, and biotechnological applications.

ATP synthase subunit ATP5B interacts with TGEV Nsp2 and acts as a negative regulator of TGEV replication.

Coronavirus nonstructural protein 2 (Nsp2) is regarded as a virulence determinant and plays a critical role in virus replication, and innate immunity. Screening and identifying host cell proteins that interact with viral proteins is an effective way to reveal the functions of viral proteins. In this study, the host proteins that interacted with transmissible gastroenteritis virus (TGEV) Nsp2 were identified using immunoprecipitation combined with LC-MS/MS. 77 host cell proteins were identified as putative Nsp2 interaction host cell proteins and a protein-protein interaction (PPI) was constructed. The identified proteins were found to be associated with various subcellular locations and functional categories through Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis. It is hypothesized that the host cell proteins interacting with TGEV Nsp2 are mainly involved in the formation of the cytoplasmic translation initiation complex, mRNA binding, ribosomes, and proteasomes. Among these, the ATP5B, a core subunit of the mitochondrial ATP synthase was further studied. The Coimmunoprecipitation (Co-IP) and indirect immunofluorescence (IFA) results confirmed that TGEV Nsp2 interacted with ATP5B. Furthermore, the downregulation of ATP5B expression was found to promote TGEV replication, suggesting that ATP5B might function as a negative regulator of TGEV replication. Collectively, our results offer additional insights into the functions of Nsp2 and provide a novel antiviral target against TGEV.

Identification and analysis correlation between hub genes and immune cell infiltration related to LPS-induced cognitive impairment.

Background: The occurrence of immunity and inflammation outside the central nervous system frequently results in acute cognitive impairment among elderly patients. However, there is currently a lack of standardized methods for diagnosing acute cognitive impairment. The objective of our study was to identify potential mRNA biomarkers and investigate the pathogenesis of acute cognitive impairment in mice brains. Methods: To analyze changes in hub genes associated with acute cognitive impairment, bioinformatics analysis was performed on the mouse brain injury data of sterile saline control group and lipopolysaccharide (LPS) induced experimental group in Gene Expression Omnibus (GEO). Functional analysis was conducted using Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), which facilitated to identify some potential mRNA biomarkers for hub gene expression in mice brains. Additionally, the "CIBERSORT X″ R kit was employed to examine immune cell infiltrations of mice brains in LPS group and saline group. Results: In the LPS and saline group, 102 significantly upregulated differentially expressed genes (DEGs) and 32 downregulated DEGs were identified. The pathway enrichment analysis using GO and KEGG revealed that these DEGs were mainly related to the regulation of cytokine, cytokine-cytokine receptor interaction, as well as protein interaction with cytokine and cytokine receptor. Immune cell infiltration analysis indicated potential involvement of M1 macrophages, NK cells resting, T cells CD4 memory, and T cells CD8 naive in the process of cognitive impairment. By constructing a protein-protein interaction (PPI) network, five hub genes (Cxcl10, Cxcl12, Cxcr3, Gbp2, and Ifih1) showed significant associations with immune cell types by using a threshold Spearman's rank correlation coefficient of R > 0.50 and p < 0.05. Conclusion: The mRNA expression profile of the mice brain tissues in the LPS group differed from that in the normal saline group. These significantly expressed mRNAs may act an importance in the pathogenesis of acute cognitive impairment through mechanisms involving immunity and neuroinflammation.

Sex-dependent differences in the ability of nicotine to modulate discrimination learning and cognitive flexibility in mice.

Nicotine, an addictive compound found in tobacco, functions as an agonist of nicotinic acetylcholine receptors (nAChRs) in the brain. Interestingly, nicotine has been reported to act as a cognitive enhancer in both human subjects and experimental animals. However, its effects in animal studies have not always been consistent, and sex differences have been identified in the effects of nicotine on several behaviors. Specifically, the role that sex plays in modulating the effects of nicotine on discrimination learning and cognitive flexibility in rodents is still unclear. Here, we evaluated sex-dependent differences in the effect of daily nicotine intraperitoneal (i.p.) administration at various doses (0.125, 0.25, and 0.5 mg/kg) on visual discrimination (VD) learning and reversal (VDR) learning in mice. In male mice, 0.5 mg/kg nicotine significantly improved performance in the VDR, but not the VD, task, while 0.5 mg/kg nicotine significantly worsened performance in the VD, but not VDR task in female mice. Furthermore, 0.25 mg/kg nicotine significantly worsened performance in the VD and VDR task only in female mice. Next, to investigate the cellular mechanisms that underlie the sex difference in the effects of nicotine on cognition, transcriptomic analyses were performed focusing on the medial prefrontal cortex tissue samples from male and female mice that had received continuous administration of nicotine for 3 or 18 days. As a result of pathway enrichment analysis and protein-protein interaction analysis using gene sets of differentially expressed genes, decreased expression of postsynaptic-related genes in males and increased expression of innate immunity-related genes in females were identified as possible molecular mechanisms related to sex differences in the effects of nicotine on cognition in discrimination learning and cognitive flexibility. Our result suggests that nicotine modulates cognitive function in a sex-dependent manner by alternating the expression of specific gene sets in the medial prefrontal cortex.

ITIH4 in Rheumatoid Arthritis Pathogenesis: Network Pharmacology and Molecular Docking Analysis Identify CXCR4 as a Potential Receptor.

Elevated levels of Inter-alpha-trypsin-inhibitor heavy chain 4 (ITIH4) have grabbed attention in rheumatoid arthritis (RA) pathogenesis, though its precise mechanisms remain unexplored. To elucidate these mechanisms, a comprehensive strategy employing network pharmacology and molecular docking was utilized. RA targets were sourced from the DisGeNET Database while interacting targets of ITIH4 were retrieved from the STRING and Literature databases. Venny 2.1 was used to identify overlapping genes, followed by Gene ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) through Cytoscape 3.10.2 software, and molecular docking was performed in the ClusPro server. The study identified 18 interacting proteins of ITIH4 associated with RA, demonstrating their major involvement in the chemokine signaling pathway by enrichment analysis. Molecular docking of ITIH4 with the 18 proteins revealed that C-X-C chemokine-receptor type 4 (CXCR4), a major protein associated with chemokine signaling, has the highest binding affinity with ITIH4 with energy -1705.7 kcal/mol forming 3 Hydrogen bonds in the active site pocket of ITIH4 with His441, Arg288, Asp443 amino acids. The effect of ITIH4 on CXCR4 was analyzed via knockdown studies in rheumatoid arthritis fibroblast-like synoviocytes (RA-FLS), demonstrating the significant downregulation of CXCR4 protein expression validated by Western blot in RA-FLS. In conclusion, it was speculated that CXCR4 might serve as a potential receptor for ITIH4 to activate the chemokine signaling, exacerbating RA pathogenesis.

Proteomic analysis of cerebrospinal fluid of amyotrophic lateral sclerosis patients in the presence of autologous bone marrow derived mesenchymal stem cells.

BACKGROUND: Amyotrophic lateral sclerosis (ALS) is a fatal and rapidly progressive motoneuron degenerative disorder. There are still no drugs capable of slowing disease evolution or improving life quality of ALS patients. Thus, autologous stem cell therapy has emerged as an alternative treatment regime to be investigated in clinical ALS. METHOD: Using Proteomics and Protein-Protein Interaction Network analyses combined with bioinformatics, the possible cellular mechanisms and molecular targets related to mesenchymal stem cells (MSCs, 1 × 106 cells/kg, intrathecally in the lumbar region of the spine) were investigated in cerebrospinal fluid (CSF) of ALS patients who received intrathecal infusions of autologous bone marrow-derived MSCs thirty days after cell therapy. Data are available via ProteomeXchange with identifier PXD053129. RESULTS: Proteomics revealed 220 deregulated proteins in CSF of ALS subjects treated with MSCs compared to CSF collected from the same patients prior to MSCs infusion. Bioinformatics enriched analyses highlighted events of Extracellular matrix and Cell adhesion molecules as well as related key targets APOA1, APOE, APP, C4A, C5, FGA, FGB, FGG and PLG in the CSF of cell treated ALS subjects. CONCLUSIONS: Extracellular matrix and cell adhesion molecules as well as their related highlighted components have emerged as key targets of autologous MSCs in CSF of ALS patients. TRIAL REGISTRATION: Clinicaltrial.gov identifier NCT0291768. Registered 28 September 2016.

In vitro ADME, mouse pharmacokinetics of LD14b, and bioanalysis of a novel aß 17ß-HSD10 modulator for the treatment of Alzheimer's disease.

LD14b is an amyloid-ß (Aß) 17ß-hydroxysteroid dehydrogenase type 10 (Aß-17ß-HSD10) protein-protein interaction modulator that shows promising in vitro and ex vivo activity to rescue Aß-induced mitochondrial dysfunction, Aß-induced toxicity, and Aß-mediated inhibition of estradiol synthesis.The current study investigated in vitro human S9 fractions metabolic stability, apparent permeability, human and mouse plasma protein binding, in vivo pharmacokinetics, and tissue distribution in Balb/cJ mice. A fast (8-min), sensitive, reliable, and reproducible LC-MS/MS method was developed and validated over the dynamic range of 1-1000 ng/mL for the quantification of LD14b in different biological matrices (plasma, liver, kidney, brain, lungs, heart).LD14b was metabolically stable in human liver S9 fractions with 70% remaining after 90 minutes of incubation, showed intermediate apparent permeability of 3.55 × 10-06 cm/s and 6.16 × 10-06 cm/s for apical-to-basolateral (A-to-B) and basolateral-to-apical (B-to-A), respectively across the Caco-2 monolayer, and was medium/highly bound to human plasma proteins (84.1%), mouse plasma proteins (85.7%), and mouse brain homogenate (95.4%).LD14b showed an in vivo predicted % absorption of 52% in Balb/cJ mice and was well-distributed to the peripheral tissues (liver, kidney, lungs, and heart) including the brain.

Unravelling the role of NDUFAF4 in Colon Cancer: Insights from multi-omics analysis.

Colon cancer is a significant public health issue, and a deeper understanding of the molecular fundamentals [16] ehind is required to improve sensitivity and curability. This research explored the gene NDUFAF4 as a target of concern due to its link to a mitochondrial function and protein "Relatively of liver tumorigenesis", which remains unclear is attributable to its inclusion into the complex I (CI) pathway. The gene ontology analysis, in turn, showed that NDUFAF4 is a key player in several critical biological phases linked to mitochondrial function and energy metabolism. Furthermore, survival analysis displayed that there was a strong correlation between NDUFAF4 expression and the patients' longevity suggesting that this factor may be important in colon cancer prognosis as well. The TCGA data proved that NDUFAF4 is elevated in colon cancer making the results of the analysis reported credible. All of the above justified the understanding of the role and importance of NDUFAF4 in treating each colon cancer patient as a molecular target. The findings help in understanding the colon cancer pathogenesis and suggest ways for developing more efficient diagnosis and treatment of the disease. SIGNIFICANCE: This research explored the gene NDUFAF4 as a target of concern due to its link to a mitochondrial function and protein "Relatively of liver tumorigenesis", which remains unclear is attributable to its inclusion into the complex I (CI) pathway. Using a comprehensive approach to Gene Ontology analysis, Protein-Protein Interaction network modelling, survival analysis, KEGG pathway analysis, and validation using TCGA data, we identified the activities of NDUFAF4 in colon cancer. The Gene Ontology analysis, in turn, showed that NDUFAF4 is a key player in several critical biological phases linked to mitochondrial function and energy metabolism. The construction of the PPI network illustrates the interactors of NDUFAF4, the functional association protein within the cellular regulatory networks. In addition, survival analysis indicated that there was a considerable relationship between the expression of NDUFAF4 and patient survival, indicating its potential role as a prognostic factor in colon cancer. KEGG pathway analysis suggested that NDUFAF4 plays a role in thermogenesis and mitochondrial biogenesis, biological processes that should be targeted due to their implication in cellular metabolism and cancer onset. The use of TCGA information confirmed the upregulation of NDUFAF4 in colon cancer, thus making the findings of the analysis reported dependable. Overall, our study provided necessary information on the role and significance of NDUFAF4, a potential molecular target in colon cancer cases. These present findings enhance our knowledge of the pathogenesis of colon cancer and open new opportunities for designing novel diagnostic and therapeutic approaches to improve patient outcomes.

Identification of molecular subtypes of dementia by using blood-proteins interaction-aware graph propagational network.

Plasma protein biomarkers have been considered promising tools for diagnosing dementia subtypes due to their low variability, cost-effectiveness, and minimal invasiveness in diagnostic procedures. Machine learning (ML) methods have been applied to enhance accuracy of the biomarker discovery. However, previous ML-based studies often overlook interactions between proteins, which are crucial in complex disorders like dementia. While protein-protein interactions (PPIs) have been used in network models, these models often fail to fully capture the diverse properties of PPIs due to their local awareness. This drawback increases the chance of neglecting critical components and magnifying the impact of noisy interactions. In this study, we propose a novel graph-based ML model for dementia subtype diagnosis, the graph propagational network (GPN). By propagating the independent effect of plasma proteins on PPI network, the GPN extracts the globally interactive effects between proteins. Experimental results showed that the interactive effect between proteins yielded to further clarify the differences between dementia subtype groups and contributed to the performance improvement where the GPN outperformed existing methods by 10.4% on average.