Autoimmunity is defined as the inability to regulate immunological activities in the body, especially in response to external triggers, leading to the attack of the tissues and organs of the host. Outcomes include the onset of autoimmune diseases whose effects are primarily due to dysregulated immune responses. In past years, there have been cases that show an increased susceptibility to other autoimmune disorders in patients who are already experiencing the same type of disease. Research in this field has started analyzing the potential molecular and cellular causes of this interconnectedness, bearing in mind the possibility of advancing drugs and therapies for the treatment of autoimmunity. With that, this study aimed to determine the correlation of four autoimmune diseases, which are type 1 diabetes (T1D), psoriasis (PSR), systemic sclerosis (SSc), and systemic lupus erythematosus (SLE), by identifying highly preserved co-expressed genes among datasets using WGCNA. Functional annotation was then employed to characterize these sets of genes based on their systemic relationship as a whole to elucidate the biological processes, cellular components, and molecular functions of the pathways they are involved in. Lastly, drug repurposing analysis was performed to screen candidate drugs for repositioning that could regulate the abnormal expression of genes among the diseases. A total of thirteen modules were obtained from the analysis, the majority of which were associated with transcriptional, post-transcriptional, and post-translational modification processes. Also, the evaluation based on KEGG suggested the possible role of T_H17 differentiation in the simultaneous onset of the four diseases. Furthermore, clomiphene was the top drug candidate for regulating overexpressed hub genes; meanwhile, prilocaine was the top drug for regulating under-expressed hub genes. This study was geared towards utilizing transcriptomics approaches for the assessment of microarray data, which is different from the use of traditional genomic analyses. Such a research design for investigating correlations among autoimmune diseases may be the first of its kind.

Bipolar disorder (BPD) is a serious psychiatric condition that is characterized by the frequent shifting of mood patterns, ranging from manic to depressive episodes. Although there are already treatment strategies that aim at regulating the manifestations of this disorder, its etiology remains unclear and continues to be a question of interest within the scientific community. The development of RNA sequencing techniques has provided newer and better approaches to studying disorders at the transcriptomic level. Hence, using RNA-seq data, we employed intramodular connectivity analysis and network pharmacology assessment of disease-associated variants to elucidate the biological pathways underlying the complex nature of BPD. This study was intended to characterize the expression profiles obtained from three regions in the brain, which are the nucleus accumbens (nAcc), the anterior cingulate cortex (AnCg), and the dorsolateral prefrontal cortex (DLPFC), provide insights into the specific roles of these regions in the onset of the disorder, and present potential targets for drug design and development. The nAcc was found to be highly associated with genes responsible for the deregulated transcription of neurotransmitters, while the DLPFC was greatly correlated with genes involved in the impairment of components crucial in neurotransmission. The AnCg did show association with some of the expressions, but the relationship was not as strong as the other two regions. Furthermore, disease-associated variants or single nucleotide polymorphisms (SNPs) were identified among the significant genes in BPD, which suggests the genetic interrelatedness of such a disorder and other mental illnesses. DRD2, GFRA2, and DCBLD1 were the genes with disease-associated variants expressed in the nAcc; ST8SIA2 and ADAMTS16 were the genes with disease-associated variants expressed in the AnCg; and FOXO3, ITGA9, CUBN, PLCB4, and RORB were the genes with disease-associated variants expressed in the DLPFC. Aside from unraveling the molecular and cellular mechanisms behind the expression of BPD, this investigation was envisioned to propose a new research pipeline in studying the transcriptome of psychiatric disorders to support and improve existing studies.

OT has gained attention for its high polyphenol content and therapeutic potential. To elucidate this further, this study investigated the electron-shuttling bioactive compounds of OT and evaluated their effect on dysregulated breast cancer (BC) genes. OT extracts were obtained via solvent extraction (SE) and supercritical fluid extraction (SFE), followed by in vitro assays. Phytochemical analysis revealed that ethanol-extracted OT (OTL-E) had the highest polyphenol, flavonoid, and tannin contents, correlating with strong antioxidant activity, while water-extracted OT (OTL-W) exhibited greater bioelectricity-stimulating properties in microbial fuel cells (MFC), confirmed by cyclic voltammetry (CV). Based on phytochemical analyses, SE displayed a better extraction technique for isolating OT bioactive compounds compared to SFE. In silico approaches through network pharmacology, molecular docking and dynamics simulations revealed that polyphenols with ortho- or para-dihydroxyl groups targeted dysregulated BC proteins involved in kinase signaling, apoptosis, and hormone receptor pathways. Luteolin exhibited the highest binding affinities to MAPK1 and PIK3CA with free energy (ΔG) of −9.1 and −8.4 kcal/mol, respectively. Trajectory-based analyses confirmed enthalpy-favored ligand-induced conformational changes to these oncoproteins, altering their function in BC development. These findings suggest the potential of OT as a bioelectricity-stimulating and chemopreventive agent, warranting further in vitro and in vivo validation.

Polymerase chain reaction (PCR) technique is one of the molecular methods in amplifying DNA for the detection of malaria. However, the collection and transportation of samples and the processing and dissemination of results via conventional PCR, especially when used for routine clinical practice, can hamper the technique’s sensitivity and specificity. The rampancy of such disease in the Philippines is aggravated by the limited supply of medical machinery and the poor economic state of the country; thus, the need to innovate a device for the early detection of malaria is necessary. With that, this study focuses on designing a microfluidic device that will mimic the function of a conventional genus-specific PCR based on the 18S rRNA gene to detect malaria parasites (Plasmodium falciparum) at low-grade parasitemia. The design was intended to be portable, accessible, and economical, which none from past literature has dealt with specifically for malaria detection. This in silico design is a first in the country specially crafted for such reasons. The proposed device was developed and simulated using ANSYS software for Computational Fluid Dynamics (CFD) analyses. The simulation shows that adding loops to the design increases its relative deviation but minimally compared to having only a straight path design. This indicates that looping is acceptable in designing a microfluidic device to minimize chip length. It was also found that increasing the cross-sectional area of the fluid path decreases the efficiency of the design. Lastly, among the three materials utilized, the chip made of polypropylene is the most efficient, with a relative deviation of 0.94 compared to polycarbonate and polydimethylsiloxane, which have relative deviations of 2.78 and 1.92, respectively. Future researchers may mesh the 44-cycle microfluidic chip due to the limitations of the software used in this study, and other materials, such as biocomposites, may be assessed to broaden the application of the design.

Epstein-Barr virus (EBV), or the human herpesvirus four is one of the most common human viruses affecting approximately 90% of the global population with infectious mononucleosis. Currently, there are no specific treatments or commercially available vaccines to protect against EBV. This study aims to develop an mRNA-based vaccine from the GP350 and BDLF3 envelope glycoproteins found within EBV via immunoinformatics. The researchers were able to identify 29 CTL, 4 HTL, and 1 B-cell epitopes using the process of reverse vaccinology. A multiple-epitope peptide vaccine construct was then designed using these predicted epitopes and was evaluated using different online bioinformatic platforms, as indicated in the methodology. Results indicate the potential of the vaccine construct to induce a human immune response. The peptide vaccine construct was evaluated for its primary sequence, secondary and tertiary structures, structural flexibility, residual frustrations, and subsequent docking with TLR2-TLR1 heterodimeric receptors. The designed vaccine construct had possessed desirable characteristics such alpha-helices, beta-sheets, partial structural flexibility, and minimal residual frustrations. Additionally, the predicted model had been able to bind the TLR2-TLR1 heterodimeric receptors with a stable binding energy. The peptide the vaccine construct was then optimized for in silico cloning and expression to E. coli strain K12, and the adapted codon sequence was then transcribed into an mRNA sequence serving as the final mRNA-based vaccine against EBV: ‘EBV-mRNAV’. The proposed vaccine construct was evaluated using the RNAfold web server, with results denoting that the adapted codon sequence was stable. The vaccine construct was then inserted into a plasmid vector for cloning, and the predicted secondary structures of the mRNA vaccine construct were shown to also be thermodynamically stable, in terms of its free energy. 'EBV-mRNAV' is a potential model that may be used for further studies, in order to contribute toward the development of an actual EBV mRNA-based vaccine. It is recommended that future studies elucidate an alternative tertiary model and cloning vector for the proposed vaccine construct.

Polymerase chain reaction (PCR) technique is one of the molecular methods in amplifying DNA for the detection of malaria. However, the limitations of PCR especially when used for routine clinical practice can hamper its sensitivity and specificity. With that, this study focuses on designing a microfluidic device that will mimic the function of a conventional genus-specific PCR based on 18S rRNA gene to detect malaria parasites (Plasmodium falciparum) at low grade parasitemia. The design was drawn and simulated using ANSYS 14.5 Computational Fluid Dynamics (CFD). The simulation shows that adding loops to the design increases its relative deviation but to a minimal extent as compared to having only a straight path design, which indicates that looping is acceptable in designing a microfluidic device to minimize chip length. Also, increasing the cross-sectional area of the fluid path decreases the efficiency of the design, thus, the design with a relatively smaller cross-sectional area is favored. And lastly, among the three materials utilized, the chip made of polypropylene is the most efficient with a relative deviation of 0.94 as compared to polycarbonate and polydimethylsiloxane which have relative deviations of 2.78 and 1.92, respectively.