Universal Biomarker Research Articles

Noninvasive in vivo photoacoustic detection of malaria with Cytophone in Cameroon

Current malaria diagnostics are invasive, lack sensitivity, and rapid tests are plagued by deletions in target antigens. Here we introduce the Cytophone, an innovative photoacoustic flow cytometer platform with high-pulse-rate lasers and a focused ultrasound transducer array to noninvasively detect and identify malaria-infected red blood cells (iRBCs) using specific wave shapes, widths, and time delays generated from the absorbance of laser energy by hemozoin, a universal biomarker of malaria infection. In a population of Cameroonian adults with uncomplicated malaria, we assess our device for safety in a cross-sectional cohort (n = 10) and conduct a performance assessment in a longitudinal cohort (n = 20) followed for 30 ± 7 days after clearance of parasitemia. Longitudinal cytophone measurements are compared to point-of-care and molecular assays (n = 94). Cytophone is safe with 90% sensitivity, 69% specificity, and a receiver-operator-curve-area-under-the-curve (ROC-AUC) of 0.84, as compared to microscopy. ROC-AUCs of Cytophone, microscopy, and RDT compared to quantitative PCR are not statistically different from one another. The ability to noninvasively detect iRBCs in the bloodstream is a major advancement which offers the potential to rapidly identify both the large asymptomatic reservoir of infection, as well as diagnose symptomatic cases without the need for a blood sample.

Liquid Biopsy in Pancreatic Ductal Adenocarcinoma: A Review of Methods and Applications

Pancreatic ductal adenocarcinoma (PDAC) remains a malignancy with one of the highest mortality rates. One limitation in the diagnosis and treatment of PDAC is the lack of an early and universal biomarker. Extensive research performed recently to develop new assays which could fit this role is available. In this review, we will discuss the current landscape of liquid biopsy in patients with PDAC. Specifically, we will review the various methods of liquid biopsy, focusing on circulating tumor DNA (ctDNA) and exosomes and future opportunities for improvement using artificial intelligence or machine learning to analyze results from a multi-omic approach. We will also consider applications which have been evaluated, including the utility of liquid biopsy for screening and staging patients at diagnosis as well as before and after surgery. We will also examine the potential for liquid biopsy to monitor patient treatment response in the setting of clinical trial development.

Role of oxidative stress in the occurrence of periodontitis in the background of metabolically associated diseases

Oxidative stress is an important component of slow pathological inflammation in metabolic diseases and chronic periodontitis. Periodontal diseases are interrelated with somatic pathology. This results in both local and systemic inflammatory reactions, which increases the risk of the onset and progression of somatic diseases. Psychological stress associated with oxidative stress with increased production of oxidants and oxidative damage is an important factor in the etiology of both periodontitis and metabolic disorders. Objective — to analyze the possible bond between chronic periodontitis, 8‑hydroxydeoxyguanosine (8‑OHdG), as a biomarker of oxidative stress, and cortisol in persons with metabolic‑associated diseases. Materials and methods. 68 people were surveyed, of which 47 had metabolically ‑associated diseases that were diagnosed according to domestic and international criteria. The control group consisted of systematically healthy people, representative by age and article that did not receive dental therapeutic and preventive measures for the last 6 months. The diagnosis of «chronic periodontitis» was carried out in accordance with existing recommendations provided at World Workshop on the Classification of Periodontal and Peri­Implant Diseases and Conditions (2017). The concentration of 8‑OHdG in plasma and the level of saliva cortisol were measured by the immunoenzyme method according to the manufacturer’s instructions. The arithmetic mean, standard error, and Student’s t‑test were calculated to compare the characteristics. Pearson’s correlation test was used to identify the relationship between the indicators. Results. Each of the groups had patients who had a healthy periodontium and those who had chronic periodontitis. The 8‑OHdG level in the main group was much higher (p<0.001) than in the control group, and the difference in the concentration of 8‑OHdG was also observed between those patients who had periodontal disease and those who had a healthy periodontium. The level of salivary cortisol in patients with chronic periodontitis was much higher compared to patients with clinically healthy periodontium (p=0.00). A correlation was found between cortisol levels and the presence of periodontal disease (r=0.619; p=0.00), between plasma 8OHdG levels and the epithelial attachment loss index (r=0.537; p=0.00), the hygiene index (r=0.599; p=0.00), and between 8OHdG levels and salivary cortisol concentrations (r=0.292; p=0.036). Conclusions. Oxidative stress plays an important role in delayed pathological inflammation in both metabolic diseases and chronic periodontitis. 8‑OHdG is a key and universal biomarker for the evaluation of DNA oxidative damage. There is a positive relationship between the oxidative marker, periodontitis and cortisol.

Comparative analysis of gut microbiota in major depressive disorder and schizophrenia during hospitalisation - the case-control, post hoc study

The aim of this study was to investigate the relationship between gut microbiota and major depressive disorder (MDD) and schizophrenia (SCZ) by comparing 36 inpatients with these conditions to 29 healthy controls (HC) matched for age, sex, and body mass index (BMI). Individuals with SCZ exhibited greater microbiota richness compared to HC (FDR P(Q)=0.028). Taxonomically, while no significant differences were observed between the microbiota of MDD and SCZ patients in a head-to-head comparison, both patient groups differed significantly when compared to HC. Interestingly, besides common patterns (such as a higher abundance of Erysipelotrichaceae UCG-003 and Streptococcus, and a lower abundance of Lachnospiraceae ND3007 group), unique patterns were exhibited only in MDD (with a higher abundance of Anaerostipes, Q=0.004) or SCZ (with a higher abundance of Sutterella, Q=0.001, and a lower abundance of Clostridium sensu stricto 1, Q=0.002). The Random Forest algorithm identified Ruminococcus torques group, Lachnospiraceae UCG-001, and Erysipelotrichaceae UCG-003 as highly discriminative features for both SCZ and MDD, while Suturella and Holdemania were unique features for SZC, and Lachnospiraceae genus CAG-56 and Anaerostipes for MDD. Additionally, between 50 % and 60 % of the differentially abundant taxa were found among the top 10 influential features in the RF models. In conclusion, while no significant differences were found between the microbiota of MDD and SCZ patients, distinct microbial patterns were found in each group when compared to HC. The study did not confirm universal microbial biomarkers reported in other studies but showed that the observed differences concern the bacteria associated with inflammation, the production of short chain fatty acids (SCFA), and the synthesis of metabolites linked to mental health (lactic acid, gamma-aminobutyric acid - GABA). The application of machine learning holds promise for further understanding the complex relationship between microbiota and these psychiatric disorders. The observed results should be treated with caution due to the limitations of this study (mainly sample size), therefore further researches under standardized environmental conditions with consistent analytical and bioinformatics approaches are warranted.

An Update on Glutathione's Biosynthesis, Metabolism, Functions, and Medicinal Purposes.

Glutathione (GSH) has been the focus of increased scientific interest in the last decades. It plays a crucial role in all major physiological processes by supplying antioxidant defenses through participating in cellular redox reactions in the human body and other living organisms. GSH also participates in detoxifying xenobiotics, protecting protein thiols from crosslinking and oxidation, regulating the cell cycle, storing cysteine, etc. The significant role of GSH in the most important physiological processes has been highlighted, such as maintaining the redox balance and reducing oxidative stress due to its ability to inactivate the reactive oxygen, nitrogen, and sulfur species. It can also enhance metabolic detoxification and regulate the function of the immune system. All of these characteristics make it a universal biomarker since its proper balance is essential for improving health and treating some age-related disorders. This review presents a current concept of the synthesis and metabolism of GSH; its main functions in a living organism, and as a precursor and cofactor; data on the use of GSH for medicinal purposes in the prevention and treatment of some diseases, as well as a nutritional strategy to maintain a normal pool of GSH in the body. The data were gathered by searching relevant information in multiple databases, such as PubMed, Scopus, ScienceDirect, and Google Scholar.

Selective Recruitment of Antibodies to Cancer Cells and Immune Cell-mediated Killing via In Situ Click Chemistry.

Many current cancer immunotherapies function by redirecting immune system components to recognize cancer biomarkers and initiate a cytotoxic attack. The lack of a universal tumor biomarker limits the therapeutic potential of these approaches. However, one feature characteristic of nearly all solid tumors is extracellular acidity. This inherent acidity provides the basis for targeted drug delivery via the pH-low insertion peptide (pHLIP), which selectively accumulates in tumors in vivo due to a pH-dependent membrane insertion propensity. Previously, we established that we could selectively decorate cancer cells with antigen-pHLIP conjugates to facilitate antibody recruitment and subsequent killing by engineered effector cells via antibody-depended cellular cytotoxicity (ADCC). Here, we present a novel strategy for opsonizing antibodies on target cell surfaces using click chemistry. We utilize pHLIP to facilitate selective tetrazine - trans-cyclooctene ligation of human IgGs to the cancer cell surface and induce ADCC. We demonstrate that our approach activates the primary ADCC signaling pathway via CD16a (FcγRIIIa) receptors on effector cells and induces the killing of cancer cell targets by engineered NK cells.

Salivary Proteins and Metabolites as Caries Biomarkers in Adolescents.

The identification of salivary molecules that can be associated to dental caries could provide insights about caries risk and offer valuable information to develop caries prediction models. However, the search for a universal caries biomarker has proven elusive due to the multifactorial nature of this oral disease. We have therefore performed a systematic effort to identify caries-associated metabolites and proteins in saliva samples from adolescents that had a caries experience and those that were caries-free. Quantification of approximately 100 molecules was performed by the use of a wide range of techniques, ranging from nuclear magnetic resonance metabolomics to ELISA, Luminex or colorimetric assays, as well as clinical features like plaque accumulation and gingival index. In addition, simplified dietary and oral hygiene habits questionnaires were also obtained. The caries-free group had significantly lower consumption of sweetened beverages and higher tooth brushing frequency. Surprisingly, very few compounds were found to individually provide discriminatory power between caries-experienced and caries-free individuals. The data analysis revealed several potential reasons that could underly this lack of association value with caries, including differences in metabolite concentrations throughout the day, a lack of correlation between metabolite concentrations in plaque and saliva, or sex-related differences, among others. However, when multiple compounds were combined by multivariate analysis and random forest modeling, a combination of 3-5 compounds were found to provide good prediction models for morning (with an AUC accuracy of 0.87) and especially afternoon samples (AUC = 0.93). While few salivary biomarkers could differentiate between caries-free and caries-experienced adolescents, a combination of markers proved effective, particularly in afternoon samples. To predict caries risk, these biomarkers should be validated in larger cohorts and longitudinal settings, considering factors such as gender differences, and variations in oral hygiene and diet.

PRC2-AgeIndex as a universal biomarker of aging and rejuvenation

DNA methylation (DNAm) is one of the most reliable biomarkers of aging across mammalian tissues. While the age-dependent global loss of DNAm has been well characterized, DNAm gain is less characterized. Studies have demonstrated that CpGs which gain methylation with age are enriched in Polycomb Repressive Complex 2 (PRC2) targets. However, whole-genome examination of all PRC2 targets as well as determination of the pan-tissue or tissue-specific nature of these associations is lacking. Here, we show that low-methylated regions (LMRs) which are highly bound by PRC2 in embryonic stem cells (PRC2 LMRs) gain methylation with age in all examined somatic mitotic cells. We estimated that this epigenetic change represents around 90% of the age-dependent DNAm gain genome-wide. Therefore, we propose the “PRC2-AgeIndex,” defined as the average DNAm in PRC2 LMRs, as a universal biomarker of cellular aging in somatic cells which can distinguish the effect of different anti-aging interventions.

Targeting SEZ6L2 in Colon Cancer: Efficacy of Bexarotene and Implications for Survival.

Bexarotene, also recognized as Targretin, is categorized as a retinoid, a type of cancer drug. Nevertheless, the precise mechanisms of bexarotene in relation to colon cancer remain unclear. In colon cancer, SEZ6L2 was suggested as one of the biomarkers and targets. This study presents a comprehensive exploration of the role of SEZ6L2 in colon cancer. We utilized both TCGA data and a cohort of Chinese patients. In a meticulous analysis of 478 colon cancer cases, SEZ6L2 expression levels were examined in relation to clinical characteristics, staging parameters, and treatment outcomes. Additionally, we investigated the pharmacological impact of bexarotene on SEZ6L2, demonstrating a significant downregulation of SEZ6L2 at both mRNA and protein levels in colon cancer patients following bexarotene treatment. SEZ6L2 consistently overexpresses in colon cancer, serving as a potential universal biomarker with prognostic significance, validated in a diverse Chinese cohort. In vitro, SEZ6L2 promotes cell viability without affecting migration. Bexarotene treatment inhibits SEZ6L2 expression, correlating with reduced viability both in vitro and in vivo. SEZ6L2 overexpression accelerates declining survival rates in an in vivo context. Bexarotene's efficacy is context-dependent, effective in parental cells but not with SEZ6L2 overexpression. Computational predictions suggest a direct SEZ6L2-bexarotene interaction, warranting further experimental exploration. The study provides valuable insights into SEZ6L2 as a prognostic biomarker in colon cancer, revealing its intricate relationship with clinical parameters, treatment outcomes, and bexarotene effects. Context-dependent therapeutic responses emphasize the nuanced understanding required for SEZ6L2's role in colon cancer, paving the way for targeted therapeutic strategies.

Biomarkers of Cellular Senescence and Aging: Current State-of-the-Art, Challenges and Future Perspectives.

Population aging has increased the global prevalence of aging-related diseases, including cancer, sarcopenia, neurological disease, arthritis, and heart disease. Understanding aging, a fundamental biological process, has led to breakthroughs in several fields. Cellular senescence, evinced by flattened cell bodies, vacuole formation, and cytoplasmic granules, ubiquitously plays crucial roles in tissue remodeling, embryogenesis, and wound repair as well as in cancer therapy and aging. The lack of universal biomarkers for detecting and quantifying senescent cells, in vitro and in vivo, constitutes a major limitation. The applications and limitations of major senescence biomarkers, including senescence-associated β-galactosidase staining, telomere shortening, cell-cycle arrest, DNA methylation, and senescence-associated secreted phenotypes are discussed. Furthermore, explore senotherapeutic approaches for aging-associated diseases and cancer. In addition to the conventional biomarkers, this review highlighted the in vitro, in vivo, and disease models used for aging studies. Further, technologies from the current decade including multi-omics and computational methods used in the fields of senescence and aging are also discussed in this review. Understanding aging-associated biological processes by using cellular senescence biomarkers can enable therapeutic innovation and interventions to improve the quality of life of older adults.

Presepsin as a biomarker of bacterial translocation and an indicator for the prescription of probiotics in cirrhosis.

The gut-liver axis and bacterial translocation are important in cirrhosis, but there is no available universal biomarker of cellular bacterial translocation, for which presepsin may be a candidate. To evaluate the relationship of the blood presepsin levels with the state of the gut microbiota in cirrhosis in the absence of obvious infection. This study included 48 patients with Child-Pugh cirrhosis classes B and C and 15 healthy controls. The fecal microbiome was assessed using 16S rRNA gene sequencing. Plasma levels of presepsin were measured. A total of 22 patients received a probiotic (Saccharomyces boulardii) for 3 months. Presepsin levels were higher in patients with cirrhosis than in healthy individuals [342 (91-2875) vs 120 (102-141) pg/mL; P = 0.048]. Patients with elevated presepsin levels accounted for 56.3% of all included patients. They had lower levels of serum albumin and higher levels of serum total bilirubin and overall severity of cirrhosis as assessed using the Child-Pugh scale. Patients with elevated presepsin levels had an increased abundance of the main taxa responsible for bacterial translocation, namely Bacilli and Proteobacteria (including the main class Gammaproteobacteria and the minor taxa Xanthobacteraceae and Stenotrophomonas), and a low abundance of bacteria from the family Lachnospiraceae (including the minor genus Fusicatenibacter), which produce short-chain fatty acids that have a positive effect on intestinal barrier function. The presepsin level directly correlated with the relative abundance of Bacilli, Proteobacteria, and inversely correlated with the abundance of Lachnospiraceae and Propionibacteriaceae. After 3 months of taking the probiotic, the severity of cirrhosis on the Child-Pugh scale decreased significantly only in the group with elevated presepsin levels [from 9 (8-11) to 7 (6-9); P = 0.004], while there were no significant changes in the group with normal presepsin levels [from 8 (7-8) to 7 (6-8); P = 0.123]. A high level of presepsin before the prescription of the probiotic was an independent predictor of a greater decrease in Child-Pugh scores (P = 0.046), as well as a higher level of the Child-Pugh scale (P = 0.042), but not the C-reactive protein level (P = 0.679) according to multivariate linear regression analysis. The level of presepsin directly correlates with the abundance in the gut microbiota of the main taxa that are substrates of bacterial translocation in cirrhosis. This biomarker, in the absence of obvious infection, seems important for assessing the state of the gut-liver axis in cirrhosis and deciding on therapy targeted at the gut microbiota in this disease.

Meta-analysis identifying gut microbial biomarkers of Qinghai-Tibet Plateau populations and the functionality of microbiota-derived butyrate in high-altitude adaptation

ABSTRACT The extreme environmental conditions of a plateau seriously threaten human health. The relationship between gut microbiota and human health at high altitudes has been extensively investigated. However, no universal gut microbiota biomarkers have been identified in the plateau population, limiting research into gut microbiota and high-altitude adaptation. 668 16s rRNA samples were analyzed using meta-analysis to reduce batch effects and uncover microbiota biomarkers in the plateau population. Furthermore, the robustness of these biomarkers was validated. Mendelian randomization (MR) results indicated that Tibetan gut microbiota may mediate a reduced erythropoietic response. Functional analysis and qPCR revealed that butyrate may be a functional metabolite in high-altitude adaptation. A high-altitude rat model showed that butyrate reduced intestinal damage caused by high altitudes. According to cell experiments, butyrate may downregulate hypoxia-inducible factor-1α (HIF-1α) expression and blunt cellular responses to hypoxic stress. Our research found universally applicable biomarkers and investigated their potential roles in promoting human health at high altitudes.

Immunoinformatics-Based Designing of Novel and Potent Multi-Epitope PSA D15 and Cag11 Immunogens for Helicobacter pylori Immunodiagnostic Assay Development.

Helicobacter pylori (H. pylori) strain is the most genetically diverse pathogenic bacterium and now alarming serious human health concern ranging from chronic gastritis to gastric cancer and human death all over the world. Currently, the majority of commercially available diagnostic assays for H. pylori is a challenging task due to the heterogeneity of virulence factors in various geographical regions. In this concern, designing of universal multi-epitope immunogenic biomarker targeted for all H. pylori strains would be crucial to successfully immunodiagnosis assay and vaccine development for H. pylori infection. Hence, the present study aimed to explore the potential immunogenic epitopes of PSA D15 and Cag11 proteins of H. pylori, using immunoinformatics web tools in order to design novel immune-reactive multi-epitope antigens for enhanced immunodiagnosis in humans. Through an in silico immunoinformatics approach, high-ranked B-cell, MHC-I, and MHC-II epitopes of PSA D15 and Cag11 proteins were predicted, screened, and selected. Subsequently, a novel multi-epitope PSA D15 and Cag11 antigens were designed by fused the high-ranked B-cell, MHC-I, and MHC-II epitopes and 50S ribosomal protein L7/L12 adjuvant using linkers. The antigenicity, solubility, physicochemical properties, secondary and tertiary structures, 3D model refinement, and validations were carried. Furthermore, the designed multi-epitope antigens were subjected to codon adaptation and in silico cloning, immune response simulation, and molecular docking with receptor molecules. A novel, stable multi-epitope PSA D15 and Cag11 H. pylori antigens were developed and immune simulation of the designed antigens showed desirable levels of immunological response. Molecular docking of designed antigens with immune receptors (B-cell, MHC-I, MHC-II, and TLR-2/4) revealed robust interactions and stable binding affinity to the receptors. The codon optimized and in silico cloned showed that the designed antigens were successfully expressed (CAI value of 0.95 for PSA D15 and 1.0 for Cag11) after inserted into pET-32ba (+) plasmid of the E. coli K12 strain. In conclusion, this study revealed that the designed multi-epitope antigens have a huge immunological potential candidate biomarker and useful in developing immunodiagnostic assays and vaccines for H. pylori infection.

Comprehensive bioinformatics analysis of NOX4 as a biomarker for pan-cancer prognosis and immune infiltration.

NADPH oxidase 4 (NOX4) has been proven to be associated with the prognosis of tumors in multiple cancers and can serve as a potential immunotherapy target to provide new treatment options for various tumors. In this study, our aim is to conduct an in-depth investigation of NOX4 across a range of cancer types to determine the relationship between NOX4 and tumors. Utilizing large-scale transcriptomic and clinical data from public databases, a systematic examination of NOX4 expression patterns was performed in pan-cancer cohorts. Survival analysis, methylation analysis, and correlation studies were employed to assess the diagnostic and prognostic significance of NOX4 in diverse cancer types. Additionally, an exploration of the relationship between NOX4 expression and immune infiltration across various tumors was conducted. The analyses unveiled a consistent upregulation of NOX4 expression in multiple cancer types relative to normal tissues, indicating its potential as a universal cancer biomarker. Elevated NOX4 expression significantly correlated with poor overall survival in several cancers. Furthermore, the study demonstrated a robust correlation between NOX4 expression and immune cell infiltration, signifying its involvement in the modulation of the tumor microenvironment. This study imparts valuable insights into the potential applications of NOX4 in cancer research, highlighting its significance as a multifaceted biomarker with diagnostic, prognostic, and immunomodulatory implications across diverse malignancies.

Near-Infrared Light-Powered and DNA Nanocage-Confined Catalytic Hairpin Assembly Nanobiosensor with a Nucleic Acid Restriction Behavior and Reinforced Enzymatic Resistance for Robust Imaging Assay in Live Biosystems.

While DNA amplifier-built nanobiosensors featuring a DNA polymerase-free catalytic hairpin assembly (CHA) reaction have shown promise in fluorescence imaging assays within live biosystems, challenges persist due to unsatisfactory precision stemming from premature activation, insufficient sensitivity arising from low reaction kinetics, and poor biostability caused by endonuclease degradation. In this research, we aim to tackle these issues. One aspect involves inserting an analyte-binding unit with a photoinduced cleavage bond to enable a light-powered notion. By utilizing 808 nm near-infrared (NIR) light-excited upconversion luminescence as the ultraviolet source, we achieve entirely a controllable sensing event during the biodelivery phase. Another aspect refers to confining the CHA reaction within the finite space of a DNA self-assembled nanocage. Besides the accelerated kinetics (up to 10-fold enhancement) resulting from the nucleic acid restriction behavior, the DNA nanocage further provides a 3D rigid skeleton to reinforce enzymatic resistance. After selecting a short noncoding microRNA (miRNA-21) as the modeled low-abundance sensing analyte, we have verified that the innovative NIR light-powered and DNA nanocage-confined CHA nanobiosensor possesses remarkably high sensitivity and specificity. More importantly, our sensing system demonstrates a robust imaging capability for this cancer-related universal biomarker in live cells and tumor-bearing mouse bodies, showcasing its potential applications in disease analysis.

Prediction and prevention of preterm birth: Quality assessment and systematic review of clinical practice guidelines using the AGREE II framework.

Prediction of pregnancies at risk of preterm birth (PTB) may allow targeted prevention strategies. To assess quality of clinical practice guidelines (CPGs) and identify areas of agreement and contention in prediction and prevention of spontaneous PTB. We searched for CPGs regarding PTB prediction and prevention in asymptomatic singleton pregnancies without language restriction in January 2024. CPGs included were published between July 2017 and December 2023 and contained statements intended to direct clinical practice. CPG quality was assessed using the AGREE-II tool. Recommendations were extracted and grouped under domains of prediction and prevention, in general populations and high-risk groups. We included 37 CPGs from 20 organizations; all were of moderate or high quality overall. There was consensus in prediction of PTB by identification of risk factors and cervical length screening in high-risk pregnancies and prevention of PTB by universal screening and treatment for asymptomatic bacteriuria, screening and treatment for BV in high-risk pregnancies, and use of preventative progesterone and cerclage. Areas of contention or limited consensus were the role of PTB clinics, universal cervical length measurement, biomarkers and cervical pessaries. This review identified strengths and limitations of current PTB CPGs, and areas for future research.

Unraveling the enigma: housekeeping gene Ugt1a7c as a universal biomarker for microglia.

Microglia, brain resident macrophages, play multiple roles in maintaining homeostasis, including immunity, surveillance, and protecting the central nervous system through their distinct activation processes. Identifying all types of microglia-driven populations is crucial due to the presence of various phenotypes that differ based on developmental stages or activation states. During embryonic development, the E8.5 yolk sac contains erythromyeloid progenitors that go through different growth phases, eventually resulting in the formation of microglia. In addition, microglia are present in neurological diseases as a diverse population. So far, no individual biomarker for microglia has been discovered that can accurately identify and monitor their development and attributes. Here, we highlight the newly defined biomarker of mouse microglia, UGT1A7C, which exhibits superior stability in expression during microglia development and activation compared to other known microglia biomarkers. The UGT1A7C sensing chemical probe labels all microglia in the 3xTG AD mouse model. The expression of Ugt1a7c is stable during development, with only a 4-fold variation, while other microglia biomarkers, such as Csf1r and Cx3cr1, exhibit at least a 10-fold difference. The UGT1A7C expression remains constant throughout its lifespan. In addition, the expression and activity of UGT1A7C are the same in response to different types of inflammatory activators' treatment in vitro. We propose employing UGT1A7C as the representative biomarker for microglia, irrespective of their developmental state, age, or activation status. Using UGT1A7C can reduce the requirement for using multiple biomarkers, enhance the precision of microglia analysis, and even be utilized as a standard for gene/protein expression.

G-Protein Signaling Modulator 2 as a Potential Biomarker in Colorectal Cancer: Integrative Analysis Using Genetic Profiling and Pan-Cancer Studies.

Colorectal cancer (CRC) imposes a significant healthcare burden globally, prompting the quest for innovative biomarkers to enhance diagnostic and therapeutic strategies. This study investigates the G-protein signaling modulator (GPSM) family across several cancers and presents a comprehensive pan-cancer analysis of the GPSM2 gene across several gastrointestinal (GI) cancers. Leveraging bioinformatics methodologies, we investigated GPSM2 expression patterns, protein interactions, functional enrichments, prognostic implications, genetic alterations, and immune infiltration associations. Furthermore, the expression of the GPSM2 gene was analyzed using real-time analysis. Our findings reveal a consistent upregulation of GPSM2 expression in all GI cancer datasets analyzed, suggesting its potential as a universal biomarker in GI cancers. Functional enrichment analysis underscores the involvement of GPSM2 in vital pathways, indicating its role in tumor progression. The prognostic assessment indicates that elevated GPSM2 expression correlates with adverse overall and disease-free survival outcomes across multiple GI cancer types. Genetic alteration analysis highlights the prevalence of mutations, particularly missense mutations, in GPSM2. Furthermore, significant correlations between GPSM2 expression and immune cell infiltration are observed, suggesting its involvement in tumor immune evasion mechanisms. Collectively, our study underscores the multifaceted role of GPSM2 in GI cancers, particularly in CRC, emphasizing its potential as a promising biomarker for prognosis and therapeutic targeting. Further functional investigations are warranted to elucidate its clinical utility and therapeutic implications in CRC management.

Navigating Uncertain Waters: First-Trimester Screening's Role in Identifying Neonatal Complications.

Background: Contemporary diagnostic methods aimed at assessing neonatal outcomes predominantly rely on the medical history of pregnant women. Ideally, universal biomarkers indicating an increased risk of delivering infants in poor clinical condition, with a heightened likelihood of requiring hospitalization in a Neonatal Intensive Care Unit (NICU), would be beneficial for appropriately stratifying pregnant women into a high-risk category. Our study evaluated whether biochemical and ultrasonographical markers universally used in first-trimester screenings for non-heritable chromosomal aberrations could serve this purpose. Methods: This study encompassed 1164 patients who underwent first-trimester screening, including patient history, ultrasound examinations, and biochemical tests for pregnancy-associated plasma protein-A (PAPP-A) and the free beta-HCG subunit (fbHCG), from January 2019 to December 2021. The research concentrated on the correlation between these prenatal test results and neonatal outcomes, particularly Apgar scores, umbilical blood pH levels, and the necessity for NICU admission. Results: In our cohort, neonates scoring lower than 8 on the Apgar scale at birth exhibited lower concentrations of PAPP-A in the first trimester, both in raw and normalized values (PAPP-A MoM 0.93 vs. 1.027, p = 0.032). We also observed a higher pulsatility index in the venous duct in the first trimester in full-term neonates born with <8 points on the Apgar scale. Additionally, newborns born with an umbilical blood pH < 7.2 had lower normalized first-trimester PAPP-A concentrations (0.69 vs. 1.01 MoM, p = 0.04). We also noted that neonates requiring NICU hospitalization post-delivery had lower first-trimester bHCG concentrations (0.93 MoM vs. 1.11 MoM, p = 0.03). However, none of the correlations in our study translated into a robust prognostic ability for predicting dichotomous outcomes. All areas under the curve achieved a value < 0.7. Conclusions: Low concentrations of PAPP-A and free bHCG subunit in the first trimester may be associated with poorer clinical and biochemical conditions in neonates post-delivery. However, the relationship is weak and has limited predictive capability. Further research evaluating these relationships is necessary for the appropriate stratification of pregnant women into high-risk categories for neonatological complications.

A novel machine learning algorithm selects proteome signature to specifically identify cancer exosomes

Non-invasive early cancer diagnosis remains challenging due to the low sensitivity and specificity of current diagnostic approaches. Exosomes are membrane-bound nanovesicles secreted by all cells that contain DNA, RNA, and proteins that are representative of the parent cells. This property, along with the abundance of exosomes in biological fluids makes them compelling candidates as biomarkers. However, a rapid and flexible exosome-based diagnostic method to distinguish human cancers across cancer types in diverse biological fluids is yet to be defined. Here, we describe a novel machine learning-based computational method to distinguish cancers using a panel of proteins associated with exosomes. Employing datasets of exosome proteins from human cell lines, tissue, plasma, serum, and urine samples from a variety of cancers, we identify Clathrin Heavy Chain (CLTC), Ezrin, (EZR), Talin-1 (TLN1), Adenylyl cyclase-associated protein 1 (CAP1), and Moesin (MSN) as highly abundant universal biomarkers for exosomes and define three panels of pan-cancer exosome proteins that distinguish cancer exosomes from other exosomes and aid in classifying cancer subtypes employing random forest models. All the models using proteins from plasma, serum, or urine-derived exosomes yield AUROC scores higher than 0.91 and demonstrate superior performance compared to Support Vector Machine, K Nearest Neighbor Classifier and Gaussian Naive Bayes. This study provides a reliable protein biomarker signature associated with cancer exosomes with scalable machine learning capability for a sensitive and specific non-invasive method of cancer diagnosis.