Potential Biomarkers For Early Diagnosis Research Articles

Plasma Proteomics Elucidated a Protein Signature in COVID-19 Patients with Comorbidities and Early-Diagnosis Biomarkers

Despite great scientific efforts, deep understanding of coronavirus-19 disease (COVID-19) immunopathology and clinical biomarkers remains a challenge. Pre-existing comorbidities increase the mortality rate and aggravate the exacerbated immune response against the severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) infection, which can result in more severe symptoms as well as long-COVID and post-COVID complications. In this study, we applied proteomics analysis of plasma samples from 28 patients with SARS-CoV-2, with and without pre-existing comorbidities, as well as their corresponding controls to determine the systemic protein changes caused by the SARS-CoV-2 infection. As a result, the protein signature shared amongst COVID-19 patients with comorbidities was revealed to be characterized by alterations in the coagulation and complement pathways, acute-phase response proteins, tissue damage and remodeling, as well as cholesterol metabolism. These altered proteins may play a relevant role in COVID-19 pathophysiology. Moreover, several novel potential biomarkers for early diagnosis of the SARS-CoV-2 infection were detected, such as increased levels of keratin K22E, extracellular matrix protein-1 (ECM1), and acute-phase response protein α-2-antiplasmin (A2AP). Importantly, elevated A2AP may contribute to persistent clotting complications associated with the long-COVID syndrome in patients with comorbidities. This study provides new insights into COVID-19 pathogenesis and proposes novel potential biomarkers for early diagnosis that could be facilitated for clinical application by further validation studies.

Discovery of the potential biomarkers for early diagnosis of endometrial cancer via integrating metabolomics and transcriptomics

Endometrial cancer (EC) is one of the most common malignant tumors in women, and the increasing incidence and mortality pose a serious threat to the public health. Early diagnosis of EC could prolong the survival period and optimize the survivorship, greatly alleviating patients’ suffering and social medical pressure. In this study, we collected urine and serum samples from the recruited patients, analyzed the samples using LC-MS approach, and identified the differential metabolites through metabolomic analysis. Then, the differentially expressed genes were identified through the systematic transcriptomic analysis of EC-related dataset from Gene Expression Omnibus (GEO), followed by network profiling of metabolic-reaction-enzyme-gene. In this experiment, a total of 83 differential metabolites and 19 hub genes were discovered, of which 10 different metabolites and 3 hub genes were further evaluated as more potential biomarkers based on network analysis. According to the KEGG enrichment analysis, the potential biomarkers and gene-encoded proteins were found to be involved in the arginine and proline metabolism, histidine metabolism, and pyrimidine metabolism, which was of significance for the early diagnosis of EC. In particular, the combination of metabolites (histamine, 1-methylhistamine, and methylimidazole acetaldehyde) as well as the combination of RRM2, TYMS and TK1 exerted more accurate discrimination abilities between EC and healthy groups, providing more criteria for the early diagnosis of EC.

Gene expression analysis in plasma of patients with Alzheimer's disease

Alzheimer's disease (AD), which is a neurodegenerative disease, cannot be noticed until severe symptoms are observed. This poses a global challenge as the average human lifespan increases, making it a concern for the entire world population. Early diagnosis can play a crucial role in slowing the progression of the disease, thereby enhancing the quality of life for both the patient and their relatives. AD has been linked to alterations in mRNA expressions. The objective of the presented study was to determine whether there were significant differences in gene expression in blood plasma between Alzheimer's patients and healthy controls. MAPT, APP, Tubb3, TrkB, and CDC42 genes were selected as target genes due to their potential associations with AD. To analyse mRNA expression levels in the control group and AD patients, the real-time PCR (qPCR) method was performed. The findings indicate that MAPT, APP, Tubb3, and CDC42 genes' expression levels were significantly downregulated by 1.09, 1.08, 1.09, and 1.14 times, respectively (p<0.05) in AD patients. Although the TrkB gene expression appeared to be downregulated by 1.03 times in the AD group, it is not statistically different. Given the molecular associations between the pathways of the target genes and AD, changes in the expression of these genes may contribute to the pathogenesis of AD. They may represent potential biomarkers for early diagnosis.

Transcriptome profiling and analysis of patients with esophageal squamous cell carcinoma from Kazakhstan.

Esophageal squamous cell carcinoma (ESCC) is the predominant subtype of esophageal cancer in Central Asia, often diagnosed at advanced stages. Understanding population-specific patterns of ESCC is crucial for tailored treatments. This study aimed to unravel ESCC's genetic basis in Kazakhstani patients and identify potential biomarkers for early diagnosis and targeted therapies. ESCC patients from Kazakhstan were studied. We analyzed histological subtypes and conducted in-depth transcriptome sequencing. Differential gene expression analysis was performed, and significantly dysregulated pathways were identified using KEGG pathway analysis (p-value < 0.05). Protein-protein interaction networks were constructed to elucidate key modules and their functions. Among Kazakhstani patients, ESCC with moderate dysplasia was the most prevalent subtype. We identified 42 significantly upregulated and two significantly downregulated KEGG pathways, highlighting molecular mechanisms driving ESCC pathogenesis. Immune-related pathways, such as viral protein interaction with cytokines, rheumatoid arthritis, and oxidative phosphorylation, were elevated, suggesting immune system involvement. Conversely, downregulated pathways were associated with extracellular matrix degradation, crucial in cancer invasion and metastasis. Protein-protein interaction network analysis revealed four distinct modules with specific functions, implicating pathways in esophageal cancer development. High-throughput transcriptome sequencing elucidated critical molecular pathways underlying esophageal carcinogenesis in Kazakhstani patients. Insights into dysregulated pathways offer potential for early diagnosis and precision treatment strategies for ESCC. Understanding population-specific patterns is essential for personalized approaches to ESCC management.

Novel plasma microRNA expression features in diagnostic use for Epstein-Barr virus-associated febrile diseases

BackgroundEpstein-Barr virus (EBV) is widely infected in humans and causes various diseases. Among them, microRNAs of EBV play a key role in the progression of EBV-associated febrile diseases. There're few specific indicators for rapid differential diagnosis of various febrile diseases associated with EBV, and the lack of more reliable screening methods with high diagnostic utility has led to spaces for improvement in the accurate diagnosis and efficient treatment of relevant patients, making EBV infection a complicated clinical problem. With recent advances in plasma microRNA testing, the apparent presence of EBV microRNAs in plasma can help screen for EBV infection. The gene networks targeted by these microRNAs can also indicate potential biomarkers of EBV-associated febrile diseases. This study aimed to identify some novel miRNAs as potential biomarkers for early diagnosis of respectively EBV-associated febrile diseases. Materials and methodsA total of 110 participants were recruited for this task. First, we performed high-throughput sequencing and preliminary PCR validation of differentially expressed miRNAs in 15 participants with EBV-associated fever (divided into 5 groups, common EBV carriers, infectious mononucleosis (IM) and chronic active EBV infection (CAEBV), EBV-associated Hemophagocytic Lymphohistiocytosis (EBV-HLH), and 3 healthy individuals). After a comprehensive analysis, 10 miRNAs with abnormal expression were screened, and then qRT-PCR was performed in the rest of 95 participants to detect the validation of miRNAs expression in plasma samples. Thereafter, we further investigated their potential for clinical application in EBV-related febrile diseases by using a combination of Gene Ontology analysis, Kyoto Encyclopedia of Genes and Genomes pathway analysis, and Protein-protein interaction network analysis. ResultsThrough identification and detailed analysis of the obtained data, we found significant differences in the expression of Hsa-miR-320d, EBV-miR-BART22, and EBV-miR-BART2-3p in blood samples from patients with different EBV-related febrile diseases. We found that the expression levels of Hsa-miR-320d, EBV-miR-BART22, and EBV-miR-BART2-3p in plasma are indicative of determining different disease types of EBV-related febrile diseases, while EBV-miR-BART22 and EBV-miR-BART2-3p may be potential therapeutic targets. ConclusionThe expression levels of Hsa-miR-320d, EBV-miR-BART22, and EBV-miR-BART2-3p suggest that they may be used as transcriptional features for early differential diagnosis of EBV-related febrile diseases, and EBV-miR-BART22 and EBV-miR-BART2-3p may be potential therapeutic targets.

Proteomic analyses of urinary exosomes identify novel potential biomarkers for early diagnosis of sickle cell nephropathy, a sex-based study.

Sickle cell nephropathy (SCN) is a leading cause of morbidity and mortality in sickle cell disease (SCD). Early intervention is crucial for mitigating its effects. However, current diagnostic methods rely on generic tests and may not detect SCN until irreversible renal damage occurs. Therefore, specific biomarkers for early diagnosis of SCN are needed. Urinary exosomes, membrane-bound vesicles secreted by renal podocytes and epithelial cells, contain both common and cell type-specific membrane and cytosolic proteins, reflecting the physiologic and pathophysiologic states of the kidney. Using proteomics, we analyzed the proteomes of urinary exosomes from humanized SCD mice at 2months (without albuminuria) and 4months (with albuminuria) of age. Excretion of 164 proteins were significantly increased and 176 proteins was significantly decreased in the exosomes when mice developed albuminuria. Based on the relevance to SCD, chronic kidney disease and Western blot confirmation in mice, we analyzed protein abundance of heparanase, cathepsin C, α2-macroglobulin and sarcoplasmic endoplasmic Ca2+ ATPase-3 (SERCA3) in the urinary exosomes and urine of 18 SCD subjects without albuminuria and 12 subjects with albuminuria using Western blot analyses. Both male and female subjects increased or tended to increase the excretion of these proteins in their urinary exosomes upon developing albuminuria, but female subjects demonstrated stronger correlations between the excretion of these proteins and urine albumin creatinine ratio (UACR) compared to male subjects. In contrast, exosomal excretion of Tamm-Horsfall protein, β-actin and SHP-1 was independent of albuminuria. These findings provide a foundation for a time-course study to determine whether increases in the levels of these proteins precede the onset of albuminuria in patients, which will help determine the potential of these proteins as biomarkers for early detection of SCN.

Understanding the Potential of mRNA as Biomarker to Revolutionize Diagnosis of Colorectal Cancer.

MicroRNA as potential biomarker for early diagnosis, differentiating various stages, interpreting the success of postoperative curative surgery and predicting early relapse of Colorectal cancer.In the realm of medical research, the quest to find effective biomarkers for various diseases has always been a top priority. Colorectal cancer (CRC), one of the leading causes of cancer-related deaths worldwide, is no exception. The emergence of microRNA (mRNA) as a potential biomarker for CRC has sparked immense interest among scientists and clinicians alike. mRNA, a molecule responsible for translating genetic information into functional proteins, presents a promising avenue for early detection and personalized treatment of this deadly disease. By analyzing the specific patterns and levels of mRNA expression in CRC cells, researchers have the ability to identify signatures that can aid in accurate diagnosis, predict patient prognosis, and even guide targeted therapies. This breakthrough in molecular biology not only enhances our understanding of CRC but also holds the potential to revolutionize the field of cancer diagnostics and treatment. In this article, we will delve deeper into the potential of mRNA as a biomarker for CRC, exploring its benefits and challenges in the field of cancer research.

Determination of biomarker candidates for the placenta accreta spectrum by plasma proteomic analysis

Placenta accreta spectrum (PAS) presents a significant obstetric challenge, associated with considerable maternal and fetal-neonatal morbidity and mortality. Nevertheless, it is imperative to acknowledge that a noteworthy subset of PAS cases remains undetected until the time of delivery, thereby contributing to an augmented incidence of morbidity among the affected individuals. The delayed identification of PAS not only hinders timely intervention but also exacerbates the associated health risks for both the maternal and fetal outcomes. This underscores the urgency to innovate strategies for early PAS diagnosis. In this study, we aimed to explore plasma proteins as potential diagnostic biomarkers for PAS. Integrated transcriptome and proteomic analyses were conducted to establish a novel diagnostic approach. A cohort of 15 pregnant women diagnosed with PAS and delivering at Inonu University Faculty of Medicine between 01/04/2021 and 01/01/2023, along with a matched control group of 15 pregnant women without PAS complications, were enrolled. Plasma protein identification utilized enzymatic digestion and liquid chromatography-tandem mass spectrometry techniques. Proteomic analysis identified 228 plasma proteins, of which 85 showed significant differences (P < 0.001) between PAS and control cases. We refined this to a set of 20 proteins for model construction, resulting in a highly accurate classification model (96.9% accuracy). Notable associations were observed for proteins encoded by P01859 (Immunoglobulin heavy constant gamma 2), P02538 (Keratin type II cytoskeletal 6A), P29622 [Kallistatin (also known as Serpin A4)], P17900 (Ganglioside GM2 activator Calmodulin-like protein 5), and P01619 (Immunoglobulin kappa variable 3–20), with fold changes indicating their relevance in distinguishing PAS from control groups. In conclusion, our study has identified novel plasma proteins that could serve as potential biomarkers for early diagnosis of PAS in pregnant women. Further research and validation in larger PAS cohorts are necessary to determine the clinical utility and reliability of these proteomic biomarkers for diagnosing PAS.

Plasma metabolomics for diagnostic biomarkers on ectopic pregnancy

Metabolomics is a relatively novel omics tool to provide potential biomarkers for early diagnosis of the diseases and to insight the pathophysiology not having discussed ever before. In the present study, an ultra-performance liquid chromatography-quadrupole time-of-flight mass spectrometry (UPLC-Q-TOF-MS) was employed to the plasma samples of Group T1: Patients with ectopic pregnancy diagnosed using ultrasound, and followed-up with beta-hCG level (n = 40), Group T2: Patients with ectopic pregnancy diagnosed using ultrasound, underwent surgical treatment and confirmed using histopathology (n = 40), Group P: Healthy pregnant women (n = 40) in the first prenatal visit of pregnancy, Group C: Healthy volunteers (n = 40) scheduling a routine gynecological examination. Metabolite extraction was performed using 3 kDa pores - Amicon® Ultra 0.5 mL Centrifugal Filters. A gradient elution program (mobile phase composition was water and acetonitrile consisting of 0.1% formic acid) was applied using a C18 column (Agilent Zorbax 1.8 μM, 100 x 2.1 mm). Total analysis time was 25 min when the flow rate was 0.2 mL/min. The raw data was processed through XCMS – R program language edition where the optimum parameters detected using Isotopologue Parameter Optimization (IPO). The potential metabolites were identified using MetaboAnalyst 5.0 and finally 27 metabolites were evaluated to be proposed as potential biomarkers to be used for the diagnosis of ectopic pregnancy.

MicroRNA biomarkers in leprosy: insights from the Northern Brazilian Amazon population and their implications in disease immune-physiopathology.

Leprosy, or Hansen's Disease, is a chronic infectious disease caused by Mycobacterium leprae that affects millions of people worldwide. Despite persistent efforts to combat it leprosy remains a significant public health concern particularly in developing countries. The underlying pathophysiology of the disease is not yet fully understood hindering the development of effective treatment strategies. However, recent studies have shed light on the potential role of microRNAs (miRNAs), small non-coding RNA molecules that can regulate gene expression, as promising biomarkers in various disease, including leprosy. This study aimed to validate a set of nine circulating miRNAs to propose new biomarkers for early diagnosis of the disease. Hsa-miR-16-5p, hsa-miR-106b-5p, hsa-miR-1291, hsa-miR-144-5p, and hsa-miR-20a-5p showed significant differential expression between non-leprosy group (non-LP) and leprosy group (LP), accurately discriminating between them (AUC > 0.75). In addition, our study revealed gender-based differences in miRNA expression in LP. Notably, hsa-miR-1291 showed higher expression in male LP, suggesting its potential as a male-specific biomarker. Similarly, hsa-miR-16-5p and hsa-miR-20a-5p displayed elevated expression in female LP, indicating their potential as female-specific biomarkers. Additionally, several studied miRNAs are involved in the dysregulation of apoptosis, autophagy, mitophagy, cell cycle, and immune system in leprosy. In conclusion, the validation of miRNA expression highlights several miRNAs as potential biomarkers for early diagnosis and provides new insights into the pathogenesis of the disease.

PGK1 is a potential biomarker for early diagnosis and prognosis of hepatocellular carcinoma.

Hepatocellular carcinoma (HCC), a common type of liver cancer, is increasing in incidence worldwide. An early diagnosis of hepatocellular carcinoma (HCC) is still challenging: Currently, few biomarkers are available to diagnose the early stage of HCC, therefore, additional prognostic biomarkers are required to identify potential risk factors. The present study analyzed gene expression levels of HCC tissue samples and the protein expression levels obtained from the GSE46408 HCC dataset using Gene Ontology and Kyoto Encyclopedia of Genes and Genomes enrichment analyses. The metabolically associated differentially expressed genes (DEGs), including DEGs involved in the glucose metabolism pathway, were selected for further analysis. Phosphoglycerate kinase 1 (PGK1), a glycolytic enzyme, was determined as a potential prognostic biomarker through Kaplan-Meier curve and clinical association variable analyses. This was also verified based on the expression levels of PGK1 in tumor tissue and protein expression levels in several liver cancer cell lines. PGK1 mRNA demonstrated a high level of expression in HCC tissue and was significantly associated with a poor prognosis, showing a negative association with survival time. In addition, as an independent risk factor, PGK1 may potentially be a valuable prognostic biomarker for patients with HCC. Furthermore, expression of PGK1 was associated with the early stages (stage I and T1) of HCC. Moreover, PGK1 mRNA expression levels demonstrated a positive association with progression of liver cancer. The results suggested that PGK1 mRNA may be involved in the degree of HCC malignancy and may be a future potential prognostic biomarker for HCC progression.

Identification of taxonomic changes in the fecal bacteriome associated with colorectal polyps and cancer: potential biomarkers for early diagnosis.

Colorectal cancer (CRC) commonly arises in individuals with premalignant colon lesions known as polyps, with both conditions being influenced by gut microbiota. Host-related factors and inherent characteristics of polyps and tumors may contribute to microbiome variability, potentially acting as confounding factors in the discovery of taxonomic biomarkers for both conditions. In this study we employed shotgun metagenomics to analyze the taxonomic diversity of bacteria present in fecal samples of 90 clinical subjects (comprising 30 CRC patients, 30 with polyps and 30 controls). Our findings revealed a decrease in taxonomic richness among individuals with polyps and CRC, with significant dissimilarities observed among the study groups. We identified significant alterations in the abundance of specific taxa associated with polyps (Streptococcaceae, Lachnoclostridium, and Ralstonia) and CRC (Lactobacillales, Clostridiaceae, Desulfovibrio, SFB, Ruminococcus, and Faecalibacterium). Clostridiaceae exhibited significantly lower abundance in the early stages of CRC. Additionally, our study revealed a positive co-occurrence among underrepresented genera in CRC, while demonstrating a negative co-occurrence between Faecalibacterium and Desulfovibrio, suggesting potential antagonistic relationships. Moreover, we observed variations in taxonomic richness and/or abundance within the polyp and CRC bacteriome linked to polyp size, tumor stage, dyslipidemia, diabetes with metformin use, sex, age, and family history of CRC. These findings provide potential new biomarkers to enhance early CRC diagnosis while also demonstrating how intrinsic host factors contribute to establishing a heterogeneous microbiome in patients with CRC and polyps.

A toolbox for genetic manipulation in intestinal Clostridium symbiosum

Gut microbes are closely related with human health, but remain much to learn. Clostridium symbiosum is a conditionally pathogenic human gut bacterium and regarded as a potential biomarker for early diagnosis of intestinal tumors. However, the absence of an efficient toolbox that allows diverse genetic manipulations of this bacterium limits its in-depth studies. Here, we obtained the complete genome sequence of C. symbiosum ATCC 14940, a representative strain of C. symbiosum. On this basis, we further developed a series of genetic manipulation methods for this bacterium. Firstly, following the identification of a functional replicon pBP1 in C. symbiosum ATCC 14940, a highly efficient conjugative DNA transfer method was established, enabling the rapid introduction of exogenous plasmids into cells. Next, we constructed a dual-plasmid CRISPR/Cas12a system for genome editing in this bacterium, reaching over 60 % repression for most of the chosen genes as well as efficient deletion (>90 %) of three target genes. Finally, this toolbox was used for the identification of crucial functional genes, involving growth, synthesis of important metabolites, and virulence of C. symbiosum ATCC 14940. Our work has effectively established and optimized genome editing methods in intestinal C. symbiosum, thereby providing strong support for further basic and application research in this bacterium.

Survivin as a potential biomarker for early diagnosis of the progression of precancerous lesions to gastric cancer.

Gastric cancer is a common cancer developed in a carcinogenesis process from precancerous lesions including chronic gastritis, intestinal metaplasia, and dysplasia. Survivin, an inhibitor-of-apoptosis protein, is associated with the initiation and progression of gastric cancer. The present study aimed to evaluate the immunohistochemical expression patterns of survivin and its relationship with early diagnosis of gastric cancer in Iranian patients. In this retrospective case-control study, immunoexpression of survivin was investigated on sections obtained from formalin-fixed paraffin-embedded tissue blocks of 38 chronic gastritis, 32 intestinal metaplasia, 20 dysplasia, 28 gastric adenocarcinoma, and 22 controls. Survivin immunoexpression in chronic gastritis was higher than controls, but this difference was not statistically significant (P > 0.05). However, survivin immunoexpression had a steady significant increase from control and chronic gastritis to intestinal metaplasia to dysplasia to gastric adenocarcinoma (P < 0.05). Sensitivity, specificity, and area under the curve of survivin immunohistochemical test for the diagnosis of gastric cancer were 87.5%, 74.4%, and 0.85, respectively. Males had a significantly higher survivin expression than females (P < 0.001). Also, survivin expression was significantly higher in older patients than in younger ones (P < 0.001). It seems that the steady increase in survivin expression from different precancerous lesions to gastric adenocarcinoma suggests that survivin can be used as a potential biomarker for the prevention and early diagnosis of gastric cancer.

Dysregulation of miRNA expression in patients with chronic myelogenous leukemia at diagnosis: a systematic review.

Aim: The present systematic review aimed to explore miRNAs as a potential biomarker for early diagnosis of chronic myeloid leukemia (CML). Materials & methods: A systematic search was conducted in three electronic databases, including Web of Science, Scopus and PubMed, to obtain relevant articles investigating the alteration of miRNA expression in patients with CML. Results: The authors found miRNAs whose expression changes are effective in the induction of CML disease. Among them, miR-21 and miR-155 were identified as the most common miRNAs with increased expression and miR-150 and miR-146 as the most common miRNAs with decreased expression. Conclusion: miRNAs can be used as an indicator for the early detection and treatment of CML phase.

A novel strategy for key gene identification in hypertrophic cardiomyopathy based on cuproptosis and multiple WGCNA analyses

Abstract Background Hypertrophic cardiomyopathy (HCM) is a potentially fatal disease, and early diagnosis is crucial for effective treatment. Microarray analysis and the discovery of cuproptosis, a new form of cell death, offer new possibilities for identifying potential biomarkers for early diagnosis. Purpose This study aimed to identify cuproptosis-related genes associated with HCM and potential biomarkers for early diagnosis using machine learning. Methods Expression data of cuproptosis-related genes were extracted from the GSE36961 dataset, and differential expression analysis was conducted. Immune infiltration analyses were also performed. Samples were categorized into two clusters, and cluster weighted gene coexpression network analysis (WGCNA) was performed based on HCM and cluster clinical data. The results were combined to develop the best machine learning model, which was verified through calibration and external validation (GSE1145 and GSE32453). Results Cuproptosis-related genes (NLRP3, ATP7B, ATP7A, SLC31A1, LIAS, LIPT1, DLD, DLAT, PDHB, and DBT) were differentially expressed between HCM and control samples. Five key genes (TSPAN12, ANP32C, C4ORF18, COL21A1, and HMGB2) were identified, which showed great efficiency in the diagnosis of HCM in external validation, with an AUC of 0.948. These genes may play critical roles in megakaryocyte differentiation, RAGE receptor binding, and protein digestion and absorption. Conclusions Cuproptosis-related genes may play significant roles in HCM, and TSPAN12, ANP32C, C4ORF18, COL21A1, and HMGB2 may be potential biomarkers for the early diagnosis of HCM. This study provides new insights for further research on HCM diagnosis and treatment.Flow chart of research designEvaluation and verification results

Functional connectivity alterations in the frontoparietal network and sensorimotor network are associated with behavioral heterogeneity in blepharospasm.

Primary blepharospasm (BSP) is a clinically heterogeneous disease that manifests not only as spasmodic closure of the eyelids but also sometimes with apraxia of eyelid opening (AEO). This cross-sectional study aimed to investigate differences in the neural mechanisms of isolated BSP and BSP-associated AEO subtypes, which may reveal the pathophysiology underlying different phenotypes. A total of 29 patients manifested as isolated BSP, 17 patients manifested as BSP associated with AEO, and 28 healthy controls underwent resting-state functional near-infrared spectroscopy (fNIRS). We assessed functional connectivity (FC) between regions of interest (ROIs) in the fronto-parietal control network (PFCN) and sensorimotor network (SMN). We also examined the relationship between altered FC and behavioral data. In the FPCN, ROI- analyses showed decreased FC between the left premotor cortex and supramarginal gyrus in the BSP with AEO group compared to the isolated BSP group. In the SMN, both subgroups showed hypoconnectivity of the left premotor cortex with the right primary motor cortex, primary sensory cortex, and somatosensory association cortex. This hypoconnectivity was positively correlated with the total number of botulinum toxin A treatments, which suggests that long-term botulinum toxin A treatment may modulate motor sequence planning and coordination. These findings showed different connectivity alterations in neural networks associated with motor and cognitive control among different behavioral phenotypes of BSP. The identification of specific alterations in various networks that correspond to clinical heterogeneity may inform the identification of potential biomarkers for early diagnosis and personalized neuromodulation targets for treating different BSP subphenotypes.

Identification of biomarkers of acne based on transcriptome analysis and combined with network pharmacology to explore the therapeutic mechanism of Jinhuang ointment.

The incidence of acne is on the rise due to unhealthy diet and living habits. Jinhuang ointment (JHO) is a classic prescription composed of 10 kinds of commonly used Chinese herbal medicine, which has been widely used in clinical prevention and treatment of skin inflammatory diseases since ancient times. However, the pharmacological mechanism and target of JHO are not clear. The acne microarray dataset was downloaded from gene expression omnibus database to identify differentially expressed genes (DEG). Immune infiltration was analyzed by CiberSort algorithm. HUB gene was identified by protein-protein interaction network. The gene expression omnibus dataset validates the biomarkers of acne with high diagnostic value. The potential active components and targets of JHO were obtained through Traditional Chinese Medicine Systems Pharmacology database, and the therapeutic targets were obtained by crossing with disease targets. R-packet is used for enrichment analysis. Molecular docking using Auto Dock Tools. A total of 202 DEGs were identified from 12 skin samples in the GSE6475. Immune infiltration analysis showed that there were a large number of macrophages and mast cells in acne skin. Gene set enrichment analysis analysis showed that DEGS was mainly involved in bacterial reaction, inflammatory reaction and so on. Six central genes and gene cluster modules were identified by Cytoscape software. A total of 185 JHO active components and 220 targets were obtained, of which 10 targets were potential targets for JHO in the treatment of acne. Kyoto encyclopedia of genes and genomes enrichment analysis showed that JHO treatment of acne was mainly related to Toll-like receptors, IL-17 and other signal pathways. The results of molecular docking showed that 5 active compounds in JHO had strong binding activity to the core protein receptor. IL-1 β, CXCL8, toll-like receptor 2, CXCL2, LCN2, and secretory phosphoprotein 1 may be potential biomarkers for early diagnosis of acne. JHO active components may regulate skin cell metabolism and inflammatory response and improve cellular immune microenvironment by acting on core targets (CXCL8, ESR1, IL-1 β, MMP1, MMP3, secretory phosphoprotein 1), thus achieving the purpose of treating acne. This is the result of the joint action of multiple targets and multiple pathways. It provides an idea for the development of a new combination of drugs for the treatment of acne.

Lactate plasma level as a potential biomarker in early diagnosis of ectopic pregnancy: A case-control survey.

A novel metabolomics survey proposed lactic acid as a diagnostic biomarker to detect ectopic pregnancy (EP). Here we investigate the plasma level of lactate for early diagnosis of EP as a potential biomarker. In a case-control study, the reproductive aged women with definite tubal EP (6-10 weeks' gestation), referred to our department during 2021-2022, considered as case group, and women with normal singleton pregnancy in the same gestational age as control group. After informed concept, demographic data (maternal and gestational age and parity) recorded and 5 mL venous blood samples were taken to detect the lactate plasma level. The data analyzed using SPSS software ver22. Finally, 95 participations (50 in case and 45 in control group) enrolled. The clinical results showed that the most of case group were aged more than 35 years old with had higher parity and body mass index, but, no statistically significant difference showed up. On the other hand, although the lactate level was slightly higher in women with EP, but, the plasma lactate level did not statistically differ between the two study groups. Also, the logistic regression showed no relationship between the demographic variables and the lactate plasma level. It seems that the plasma level of lactate cannot be a diagnostic biomarker for EP.

Metabolic biomarkers for Alzheimer's disease: A mini review

Alzheimer's disease (AD) is the most common neurodegenerative disorder and a leading cause of dementia worldwide, which characterized by progressive cognitive decline, memory impairment, and changes in behavior and personality. The prevalence of AD is expected to rise significantly in the coming decades due to the aging population, making it a major public health concern. Mounting evidence suggests that metabolic dysregulation plays a critical role in the pathogenesis of AD. In this mini review, we provide an overview of the current understanding of the interplay between metabolism and AD. Specifically, we explore the dysregulation of glucose metabolism, lipid metabolism, amino acid metabolism, and nitrogen oxide synthesis pathways in AD. These metabolic alterations have been identified as potential biomarkers for early diagnosis and prognosis of AD. Additionally, we discuss the current status of research in this field, including the advancements in metabolomics and imaging techniques that have allowed for the identification and validation of metabolic biomarkers.