Innovations in Biosensor Technologies for Healthcare Diagnostics and Therapeutic Drug Monitoring: Applications, Recent Progress, and Future Research Challenges.

This comprehensive review delves into the forefront of biosensor technologies and their critical roles in disease biomarker detection and therapeutic drug monitoring. It provides an in-depth analysis of various biosensor types and applications, including enzymatic sensors, immunosensors, and DNA sensors, elucidating their mechanisms and specific healthcare applications. The review highlights recent innovations such as integrating nanotechnology, developing wearable devices, and trends in miniaturisation, showcasing their transformative potential in healthcare. In addition, it addresses significant sensitivity, specificity, reproducibility, and data security challenges, proposing strategic solutions to overcome these obstacles. It is envisaged that it will inform strategic decision-making, drive technological innovation, and enhance global healthcare outcomes by synthesising multidisciplinary insights.

GP-Marker facilitates the analysis of intact glycopeptide quantitative data at different levels.

Protein glycosylation is a highly heterogeneous post-translational modification that has been demonstrated to exhibit significant variations in various diseases. Due to the differential patterns observed in disease and healthy populations, the glycosylated proteins hold promise as early indicators for multiple diseases. With the continuous development of liquid chromatography-mass spectrometry (LC-MS) technology and spectrum analysis software, the sensitivity for the decipher of the tandem mass spectra of the glycopeptides carrying intact glycans, i.e., intact glycopeptides, enzymatic hydrolyzed from glycoproteins has been significantly improved. From quantified intact glycopeptides, the difference of protein glycosylation at multiple levels, e.g., glycoprotein, glycan, glycosite, and site-specific glycans, could be obtained for different samples. However, the manual analysis of the intact glycopeptide quantitative data at multiple levels is tedious and time consuming. In this study, we have developed a software tool named "GP-Marker" to facilitate large-scale data mining of spectra dataset of intact N-glycopeptide at multiple levels. This software provides a user-friendly and interactive interface, offering operational tools for machine learning to researchers without programming backgrounds. It includes a range of visualization plots displaying differential glycosylation and provides the ability to extract multi-level data analysis from intact glycopeptide data quantified by Glyco-Decipher.

Nanopore-based detection of periodontitis biomarker miR31 in saliva samples.

MicroRNAs (miRNAs) play important roles in posttranscriptional gene regulation. Aberrations in the miRNA levels have been the cause behind various diseases, including periodontitis. Therefore, sensitive, specific, and accurate detection of disease-associated miRNAs is vital to early diagnosis and can facilitate inhibitor screening and drug design. In this study, we developed a label-free, real-time sensing method for the detection of miR31, which has been frequently linked to periodontitis, using an engineered protein nanopore and in the presence of a complementary ssDNA as a molecular probe. Our method is rapid and highly sensitive with nanomolar concentration of miR31 that could be determined in minutes. Furthermore, our sensor showed high selectivity toward the target miR31 sequence even in the presence of interfering nucleic acids. In addition, artificial saliva and human saliva samples were successfully analyzed. Our developed nanopore sensing platform could be used to detect other miRNAs and offers a potential application for the clinical diagnosis of disease biomarkers.

Low HDL-C/ApoA-I index is associated with cardiometabolic risk factors and coronary artery calcium: a sub-analysis of the genetics of atherosclerotic disease (GEA) study.

BACKGROUND: The high-density lipoprotein cholesterol to apolipoprotein A-I index (HDL-C/ApoA-I) may be practical and useful in clinical practice as a marker of atherosclerosis. This study aimed to investigate the association between the HDL-C/ApoA-I index with cardiometabolic risk factors and subclinical atherosclerosis. METHODS: In this cross-sectional sub-analysis of the GEA study, 1,363 individuals, women (51.3%) and men (48.7%) between 20 and 75 years old, without coronary heart disease or diabetes mellitus were included. We defined an adverse cardiometabolic profile as excess adipose tissue metrics, non-alcoholic liver fat measured by non-contrasted tomography, metabolic syndrome, dyslipidemias, and insulin resistance. The population was stratified by quartiles of the HDL-C/Apo-AI index, and its dose-relationship associations were analysed using Tobit regression, binomial, and multinomial logistic regression analysis. RESULTS: Body mass index, visceral and pericardial fat, metabolic syndrome, fatty liver, high blood pressure, and CAC were inversely associated with the HDL-C/ApoA-I index. The CAC > 0 prevalence was higher in quartile 1 (29.2%) than in the last quartile (22%) of HDL-C/ApoA-I index (p = 0.035). The probability of having CAC > 0 was higher when the HDL-C/ApoA-I index was less than 0.28 (p < 0.001). This association was independent of classical coronary risk factors, visceral and pericardial fat measurements. CONCLUSION: The HDL-C/ApoA-I index is inversely associated with an adverse cardiometabolic profile and CAC score, making it a potentially useful and practical biomarker of coronary atherosclerosis. Overall, these findings suggest that the HDL-C/ApoA-I index could be useful for evaluating the probability of having higher cardiometabolic risk factors and subclinical atherosclerosis in adults without CAD.

Deciphering the molecular nexus between Omicron infection and acute kidney injury: a bioinformatics approach.

Background: The ongoing global health crisis of COVID-19, and particularly the challenges posed by recurrent infections of the Omicron variant, have significantly strained healthcare systems worldwide. There is a growing body of evidence indicating an increased susceptibility to Omicron infection in patients suffering from Acute Kidney Injury (AKI). However, the intricate molecular interplay between AKI and Omicron variant of COVID-19 remains largely enigmatic. Methods: This study employed a comprehensive analysis of human RNA sequencing (RNA-seq) and microarray datasets to identify differentially expressed genes (DEGs) associated with Omicron infection in the context of AKI. We engaged in functional enrichment assessments, an examination of Protein-Protein Interaction (PPI) networks, and advanced network analysis to elucidate the cellular signaling pathways involved, identify critical hub genes, and determine the relevant controlling transcription factors and microRNAs. Additionally, we explored protein-drug interactions to highlight potential pharmacological interventions. Results: Our investigation revealed significant DEGs and cellular signaling pathways implicated in both Omicron infection and AKI. We identified pivotal hub genes, including EIF2AK2, PLSCR1, GBP1, TNFSF10, C1QB, and BST2, and their associated regulatory transcription factors and microRNAs. Notably, in the murine AKI model, there was a marked reduction in EIF2AK2 expression, in contrast to significant elevations in PLSCR1, C1QB, and BST2. EIF2AK2 exhibited an inverse relationship with the primary AKI mediator, Kim-1, whereas PLSCR1 and C1QB demonstrated strong positive correlations with it. Moreover, we identified potential therapeutic agents such as Suloctidil, Apocarotenal, 3'-Azido-3'-deoxythymidine, among others. Our findings also highlighted a correlation between the identified hub genes and diseases like myocardial ischemia, schizophrenia, and liver cirrhosis. To further validate the credibility of our data, we employed an independent validation dataset to verify the hub genes. Notably, the expression patterns of PLSCR1, GBP1, BST2, and C1QB were consistent with our research findings, reaffirming the reliability of our results. Conclusion: Our bioinformatics analysis has provided initial insights into the shared genetic landscape between Omicron COVID-19 infections and AKI, identifying potential therapeutic targets and drugs. This preliminary investigation lays the foundation for further research, with the hope of contributing to the development of innovative treatment strategies for these complex medical conditions.

Extracellular vesicles: Function, resilience, biomarker, bioengineering, and clinical implications.

Extracellular vesicles (EVs) have emerged as key players in intercellular communication, disease pathology, and therapeutic innovation. Initially overlooked as cellular debris, EVs are now recognized as vital mediators of cell-to-cell communication, ferrying a cargo of proteins, nucleic acids, and lipids, providing cellular resilience in response to stresses. This review provides a comprehensive overview of EVs, focusing on their role as biomarkers in disease diagnosis, their functional significance in physiological and pathological processes, and the potential of bioengineering for therapeutic applications. EVs offer a promising avenue for noninvasive disease diagnosis and monitoring, reflecting the physiological state of originating cells. Their diagnostic potential spans a spectrum of diseases, including cancer, cardiovascular disorders, neurodegenerative diseases, and infectious diseases. Moreover, their presence in bodily fluids such as blood, urine, and cerebrospinal fluid enhances their diagnostic utility, presenting advantages over traditional methods. Beyond diagnostics, EVs mediate crucial roles in intercellular communication, facilitating the transfer of bioactive molecules between cells. This communication modulates various physiological processes such as tissue regeneration, immune modulation, and neuronal communication. Dysregulation of EV-mediated communication is implicated in diseases such as cancer, immune disorders, and neurodegenerative diseases, highlighting their therapeutic potential. Bioengineering techniques offer avenues for manipulating EVs for therapeutic applications, from isolation and purification to engineering cargo and targeted delivery systems. These approaches hold promise for developing novel therapeutics tailored to specific diseases, revolutionizing personalized medicine. However, challenges such as standardization, scalability, and regulatory approval need addressing for successful clinical translation. Overall, EVs represent a dynamic frontier in biomedical research with vast potential for diagnostics, therapeutics, and personalized medicine.

APOE ε4 is associated with decreased synaptic density in cognitively impaired participants.

INTRODUCTION: We aimed to investigate the effect of apolipoprotein E4 (APOE) ε4 on synaptic density in cognitively impaired (CI) participants. METHODS: One hundred ten CI participants underwent amyloid positron emission tomography (PET) with 18F-florbetapir and synaptic density PET with 18F-SynVesT-1. We evaluated the influence of APOE ε4 allele on synaptic density and investigated the effects of ε4 genotype on the associations of synaptic density with Alzheimer's disease (AD) biomarkers. The mediation effects of AD biomarkers on ε4-associated synaptic density loss were analyzed. RESULTS: Compared with non-carriers, APOE ε4 allele carriers exhibited significant synaptic loss in the medial temporal lobe. Amyloid beta (Aß) and tau pathology mediated the effects of APOE ε4 on synaptic density to different extents. The associations between synaptic density and tau pathology were regulated by the APOE ε4 genotype. DISCUSSION: The APOE ε4 allele was associated with decreased synaptic density in CI individuals and may be driven by AD biomarkers.

Computational modelling and optimization studies of electropentamer for molecular imprinting of DJ-1.

Parkinson's disease (PD) is the most prevalent type of incurable movement disorder. Recent research findings propose that the familial PD-associated molecule DJ-1 exists in cerebrospinal fluid (CSF) and that its levels may be altered as Parkinson's disease advances. By using a molecularly imprinted polymer (MIP) as an artificial receptor, it becomes possible to create a functional MIP with predetermined selectivity for various templates, particularly for the DJ-1 biomarker associated with Parkinson's disease. It mostly depends on molecular recognition via interactions between functional monomers and template molecules. So, the computational methods for the appropriate choice of functional monomers for creating molecular imprinting electropolymers (MIEPs) with particular recognition for the detection of DJ-1, a pivotal biomarker involved in PD, are undertaken in this study. Here, molecular docking, molecular dynamics simulations (MD), molecular mechanics Poisson-Boltzmann surface area (MM-PBSA) methods, and quantum mechanical calculation have been applied to investigate the intermolecular interaction between DJ-1 and several functional electropentamers, viz., polypyrrole (PPy), poly(3,4-ethylenedioxythiophene) (PEDOT), poly(o-aminophenol) (POAP), and polythiophene (PTS). In this context, the electropentamers were selected to mimic the imprinted electropolymer system. We analyzed the most stable configurations of the formed complexes involving DJ-1 and electropentamers as a model system for MIEPs. Among these, PEDOT exhibited a more uniform arrangement around DJ-1, engaging in numerous van der Waals, H-bond, electrostatic, and hydrophobic interactions. Hence, it can be regarded as a preferable choice for synthesizing a MIP for DJ-1 recognition. Thus, it will aid in selecting a suitable functional monomer, which is of greater significance in the design and development of selective DJ-1/MIP sensors.

Impact of aging on copper isotopic composition in the murine brain.

Aging is the main risk factor for Alzheimer's disease (AD). AD is linked to alterations in metal homeostasis and changes in stable metal isotopic composition can occur, possibly allowing the latter to serve as relevant biomarkers for potential AD diagnosis. Copper stable isotopes are used to investigate changes in Cu homeostasis associated with various diseases. Prior work has shown that in AD mouse models, the accumulation of 63Cu in the brain is associated with the disease's progression. However, our understanding of how the normal aging process influences the brain's isotopic composition of copper remains limited. In order to determine the utility and predictive power of Cu isotopes in AD diagnostics, we aim-in this study-to develop a baseline trajectory of Cu isotopic composition in the normally aging mouse brain. We determined the copper concentration and isotopic composition in brains of 30 healthy mice (WT) ranging in age from 6 to 12 mo, and further incorporate prior data obtained for 3-mo-old healthy mice; this range approximately equates to 20-50 yr in human equivalency. A significant 65Cu enrichment has been observed in the 12-mo-old mice compared to the youngest group, concomitant with an increase in Cu concentration with age. Meanwhile, literature data for brains of AD mice display an enrichment in 63Cu isotope compared to WT. It is acutely important that this baseline enrichment in 65Cu is fully constrained and normalized against if any coherent diagnostic observations regarding 63Cu enrichment as a biomarker for AD are to be developed.

SRY-box transcription factor 21 antisense divergent transcript 1: Regulatory roles and clinical significance in neoplastic conditions and Alzheimer's Disease.

SRY-box transcription factor 21 antisense divergent transcript 1 (SOX21-AS1) is a multifaceted long non-coding RNA (lncRNA) that plays diverse roles in both neoplastic conditions and Alzheimer's disease. Its aberrant expression intricately regulates a wide spectrum of cellular processes, spanning from epithelial-mesenchymal transition (EMT), apoptosis, migration, metastasis, and stemness to drug resistance. SOX21-AS1 achieves these effects through its involvement in the competitive endogenous RNA (ceRNA) network, modulation of downstream genes, and regulation of critical pathways, including PI3K/AKT, Hippo, Wnt/ß-catenin, and ERK signaling. Of significant clinical relevance, SOX21-AS1 expression has shown robust correlations with various clinical-pathological features. Moreover, it has demonstrated promising prognostic and diagnostic potential across a spectrum of tumors, as evidenced by existing literature and TCGA pan-cancer analyses. In Alzheimer's disease, SOX21-AS1 assumes a distinctive role. It influences neuronal viability, apoptosis, and oxidative stress by interacting with miR-107 and miR-132, and affecting the PI3K/AKT and Wnt signaling pathways. This comprehensive review sheds light on the functions of SOX21-AS1 and the regulated mechanisms underpinning its impact on neoplastic conditions and Alzheimer's disease. It underscores the clinical significance of SOX21-AS1 and positions it as a promising therapeutic target in both the oncological and neurodegenerative domains.

In Vitro microRNA Expression Profile Alterations under CDK4/6 Therapy in Breast Cancer.

BACKGROUND: Breast cancer is the most common type of cancer worldwide. Cyclin-dependent kinase inhibition is one of the backbones of metastatic breast cancer therapy. However, there are a significant number of therapy failures. This study evaluates the biomarker potential of microRNAs for the prediction of a therapy response under cyclin-dependent kinase inhibition. METHODS: This study comprises the analysis of intracellular and extracellular microRNA-expression-level alterations of 56 microRNAs under palbociclib mono as well as combination therapy with letrozole. Breast cancer cell lines BT-474, MCF-7 and HS-578T were analyzed using qPCR. RESULTS: A palbociclib-induced microRNA signature could be detected intracellularly as well as extracellularly. Intracellular miR-10a, miR-15b, miR-21, miR-23a and miR-23c were constantly regulated in all three cell lines, whereas let-7b, let-7d, miR-15a, miR-17, miR-18a, miR-20a, miR-191 and miR301a_3p were regulated only in hormone-receptor-positive cells. Extracellular miR-100, miR-10b and miR-182 were constantly regulated across all cell lines, whereas miR-17 was regulated only in hormone-receptor-positive cells. CONCLUSIONS: Because they are secreted and significantly upregulated in the microenvironment of tumor cells, miRs-100, -10b and -182 are promising circulating biomarkers that can be used to predict or detect therapy responses under CDK inhibition. MiR-10a, miR-15b, miR-21, miR-23a and miR-23c are potential tissue-based biomarkers.

A hub gene signature as a therapeutic target and biomarker for sepsis and geriatric sepsis-induced ARDS concomitant with COVID-19 infection.

Background: COVID-19 and sepsis represent formidable public health challenges, characterized by incompletely elucidated molecular mechanisms. Elucidating the interplay between COVID-19 and sepsis, particularly in geriatric patients suffering from sepsis-induced acute respiratory distress syndrome (ARDS), is of paramount importance for identifying potential therapeutic interventions to mitigate hospitalization and mortality risks. Methods: We employed bioinformatics and systems biology approaches to identify hub genes, shared pathways, molecular biomarkers, and candidate therapeutics for managing sepsis and sepsis-induced ARDS in the context of COVID-19 infection, as well as co-existing or sequentially occurring infections. We corroborated these hub genes utilizing murine sepsis-ARDS models and blood samples derived from geriatric patients afflicted by sepsis-induced ARDS. Results: Our investigation revealed 189 differentially expressed genes (DEGs) shared among COVID-19 and sepsis datasets. We constructed a protein-protein interaction network, unearthing pivotal hub genes and modules. Notably, nine hub genes displayed significant alterations and correlations with critical inflammatory mediators of pulmonary injury in murine septic lungs. Simultaneously, 12 displayed significant changes and correlations with a neutrophil-recruiting chemokine in geriatric patients with sepsis-induced ARDS. Of these, six hub genes (CD247, CD2, CD40LG, KLRB1, LCN2, RETN) showed significant alterations across COVID-19, sepsis, and geriatric sepsis-induced ARDS. Our single-cell RNA sequencing analysis of hub genes across diverse immune cell types furnished insights into disease pathogenesis. Functional analysis underscored the interconnection between sepsis/sepsis-ARDS and COVID-19, enabling us to pinpoint potential therapeutic targets, transcription factor-gene interactions, DEG-microRNA co-regulatory networks, and prospective drug and chemical compound interactions involving hub genes. Conclusion: Our investigation offers potential therapeutic targets/biomarkers, sheds light on the immune response in geriatric patients with sepsis-induced ARDS, emphasizes the association between sepsis/sepsis-ARDS and COVID-19, and proposes prospective alternative pathways for targeted therapeutic interventions.

Molecularly Imprinted Polymer-Based Electrochemical Sensors for the Diagnosis of Infectious Diseases.

The appearance of biological molecules, so-called biomarkers in body fluids at abnormal concentrations, is considered a good tool for detecting disease. Biomarkers are usually looked for in the most common body fluids, such as blood, nasopharyngeal fluids, urine, tears, sweat, etc. Even with significant advances in diagnostic technology, many patients with suspected infections receive empiric antimicrobial therapy rather than appropriate treatment, which is driven by rapid identification of the infectious agent, leading to increased antimicrobial resistance. To positively impact healthcare, new tests are needed that are pathogen-specific, easy to use, and produce results quickly. Molecularly imprinted polymer (MIP)-based biosensors can achieve these general goals and have enormous potential for disease detection. This article aimed to overview recent articles dedicated to electrochemical sensors modified with MIP to detect protein-based biomarkers of certain infectious diseases in human beings, particularly the biomarkers of infectious diseases, such as HIV-1, COVID-19, Dengue virus, and others. Some biomarkers, such as C-reactive protein (CRP) found in blood tests, are not specific for a particular disease but are used to identify any inflammation process in the body and are also under consideration in this review. Other biomarkers are specific to a particular disease, e.g., SARS-CoV-2-S spike glycoprotein. This article analyzes the development of electrochemical sensors using molecular imprinting technology and the used materials' influence. The research methods, the application of different electrodes, the influence of the polymers, and the established detection limits are reviewed and compared.

Integrative bioinformatics and validation studies reveal KDM6B and its associated molecules as crucial modulators in Idiopathic Pulmonary Fibrosis.

Background: Idiopathic Pulmonary Fibrosis (IPF) can be described as a debilitating lung disease that is characterized by the complex interactions between various immune cell types and signaling pathways. Chromatin-modifying enzymes are significantly involved in regulating gene expression during immune cell development, yet their role in IPF is not well understood. Methods: In this study, differential gene expression analysis and chromatin-modifying enzyme-related gene data were conducted to identify hub genes, common pathways, immune cell infiltration, and potential drug targets for IPF. Additionally, a murine model was employed for investigating the expression levels of candidate hub genes and determining the infiltration of different immune cells in IPF. Results: We identified 33 differentially expressed genes associated with chromatin-modifying enzymes. Enrichment analyses of these genes demonstrated a strong association with histone lysine demethylation, Sin3-type complexes, and protein demethylase activity. Protein-protein interaction network analysis further highlighted six hub genes, specifically KDM6B, KDM5A, SETD7, SUZ12, HDAC2, and CHD4. Notably, KDM6B expression was significantly increased in the lungs of bleomycin-induced pulmonary fibrosis mice, showing a positive correlation with fibronectin and α-SMA, two essential indicators of pulmonary fibrosis. Moreover, we established a diagnostic model for IPF focusing on KDM6B and we also identified 10 potential therapeutic drugs targeting KDM6B for IPF treatment. Conclusion: Our findings suggest that molecules related to chromatin-modifying enzymes, primarily KDM6B, play a critical role in the pathogenesis and progression of IPF.

Self-Therapeutic Nanomaterials: Applications in Biology and Medicine.

Over past decades, nanotechnology has contributed to the biomedical field in areas including detection, diagnosis, and drug delivery via opto-electronic properties or enhancement of biological effects. Though generally considered inert delivery vehicles, a plethora of past and present evidence demonstrates that nanomaterials also exude unique intrinsic biological activity based on composition, shape, and surface functionalization. These intrinsic biological activities, termed self-therapeutic properties, take several forms, including mediation of cell-cell interactions, modulation of interactions between biomolecules, catalytic amplification of biochemical reactions, and alteration of biological signal transduction events. Moreover, study of biomolecule-nanomaterial interactions offers a promising avenue for uncovering the molecular mechanisms of biology and the evolution of disease. In this review, we observe the historical development, synthesis, and characterization of self-therapeutic nanomaterials. Next, we discuss nanomaterial interactions with biological systems, starting with administration and concluding with elimination. Finally, we apply this materials perspective to advances in intrinsic nanotherapies across the biomedical field, from cancer therapy to treatment of microbial infections and tissue regeneration. We conclude with a description of self-therapeutic nanomaterials in clinical trials and share our perspective on the direction of the field in upcoming years.

Proteomic Approaches and Potential Applications in Autosomal Dominant Polycystic Kidney Disease and Fabry Disease.

Although rare, hereditary diseases, such as autosomal dominant polycystic kidney disease (ADPKD) and Fabry disease (FD) may significantly progress towards severe nephropathy. It is crucial to characterize it accurately, predict the course of the illness and estimate treatment effectiveness. A huge effort has been undertaken to find reliable biomarkers that might be useful for an early prevention of the disease progression and/or any invasive diagnostic procedures. The study of proteomics, or the small peptide composition of a sample, is a field of study under continuous development. Over the past years, several strategies have been created to study and define the proteome of samples from widely varying origins. However, urinary proteomics has become essential for discovering novel biomarkers in kidney disease. Here, the extracellular vesicles in human urine that contain cell-specific marker proteins from every segment of the nephron, offer a source of potentially valuable urinary biomarkers, and may play an essential role in kidney development and kidney disease. This review summarizes the relevant literature investigating the proteomic approaches and potential applications in the regular studies of ADPKD and FD.

Molecularly imprinted polymers for the recognition of biomarkers of certain neurodegenerative diseases.

The appearance of the biomarkers in body fluids like blood, urine, saliva, tears, etc. can be used for the identification of many diseases. This article aimed to summarize the studies about electrochemical biosensors with molecularly imprinted polymers as sensitive and selective layers on the electrode to detect protein-based biomarkers of such neurodegenerative diseases as Alzheimer's disease, Parkinson's disease, and stress. The main attention in this article is focused on the detection methods of amyloid-ß oligomers and p-Tau which are representative biomarkers for Alzheimer's disease, α-synuclein as the biomarker of Parkinson's disease, and α-amylase and lysozyme as the biomarkers of stress using molecular imprinting technology. The research methods, the application of different electrodes, the influence of the polymers, and the established detection limits are reviewed and compared.