Biomarkers For Early Diagnosis Research Articles

Construction of a 3D Quantum Dot Nanoassembly with Two-Step FRET for One-Step Sensing of Human Telomerase RNA in Breast Cancer Cells and Tissues.

Telomerase is an important biomarker for early diagnosis of cancers, but current telomerase assays usually rely on measuring the extension products of telomerase substrates, which increases the assay complexity. More evidence indicates that human telomerase RNA (hTR), as a core component of telomerase, is positively correlated with the telomerase activity. Herein, we demonstrate the development of a duplex-specific nuclease (DSN)-propelled 3D quantum dot (QD) nanoassembly with two-step Föster resonance energy transfer (FRET) for the one-step sensing of hTR in breast cancer cells and tissues. This assay involves only one hairpin probe modified with a Cy5 at the sixth base from the 5'-biotin end and a BHQ2 at the 3'-terminus, which integrates three functions of target recognition, target recycling amplification, and signal readout. The anchoring of the hairpin probe on the 605QD surface results in the formation of a 3D 605QD-Cy5-probe-BHQ2 nanoassembly in which two-step FRET occurs among the 605QD, Cy5, and BHQ2 quencher. Notably, the formation of 605QD-Cy5-probe-BHQ2 nanoassembly facilitates the reduction of background signal and the increase of signal-to-background ratio due to its dense, highly oriented nucleic acid shell-induced steric hindrance effect. This assay can achieve one-step and rapid detection of hTR with a detection limit of 2.10 fM, which is the simplest and most rapid hTR assay reported so far. Moreover, this assay can efficiently distinguish single-base mismatched sequences, and it can discriminate the hTR level between breast cancer patients and healthy donors with a high accuracy of 100%, with great prospects for early diagnosis of cancers.

Potential Exosome Biomarkers for Parkinson's Disease Diagnosis: A Systematic Review and Meta-Analysis.

Parkinson's disease (PD) is the second most common neurodegenerative disease worldwide. Given its prevalence, reliable biomarkers for early diagnosis are required. Exosomal proteins within extracellular nanovesicles are promising candidates for diagnostic, screening, prognostic, and disease monitoring purposes in neurological diseases such as PD. This review aims to evaluate the potential of extracellular vesicle proteins or miRNAs as biomarkers for PD. A comprehensive literature search until January 2024 was conducted across multiple databases, including PubMed, EMBASE, Web of Science, and Cochrane Library, to identify relevant studies reporting exosome biomarkers in blood samples from PD patients. Out of 417 articles screened, 47 studies were selected for analysis. Among exosomal protein biomarkers, α-synuclein, tau, Amyloid β 1-42, and C-X-C motif chemokine ligand 12 (CXCL12) were identified as significant markers for PD. Concerning miRNA biomarkers, miRNA-24, miR-23b-3p, miR-195-3p, miR-29c, and mir-331-5p are promising across studies. α-synuclein exhibited increased levels in PD patients compared to control groups in twenty-one studies, while a decrease was observed in three studies. Our meta-analysis revealed a significant difference in total exosomal α-synuclein levels between PD patients and healthy controls (standardized mean difference [SMD] = 1.369, 95% confidence interval [CI] = 0.893 to 1.846, p < 0.001), although these results are limited by data availability. Furthermore, α-synuclein levels significantly differ between PD patients and healthy controls (SMD = 1.471, 95% CI = 0.941 to 2.002, p < 0.001). In conclusion, certain exosomal proteins and multiple miRNAs could serve as potential biomarkers for diagnosis, prognosis prediction, and assessment of disease progression in PD.

Small extracellular vesicles detection using dielectrophoresis-based microfluidic chip for diagnosis of breast cancer

Small extracellular vesicles (sEVs) reflect the genotype and phenotype of original cells and are biomarkers for early diagnosis and treatment monitoring of tumors. Yet, their small size and low density make them difficult to isolate and detect in body fluid samples. This study proposes a novel acDEP-Exo chip filled with transparent micro-beads, which formed a non-uniform electrical field, and finally achieved rapid, sensitive, and tunable sEVs capture and detection. The method requires only 20–50 μL of sample, achieved a limit of detection (LOD) of 161 particles/μL, and can detect biomarkers within 13 min. We applied the chip to analyze the two markers of sEV's EpCAM and MUC1 in clinical plasma samples from breast cancer (BC) patients and healthy volunteers and found that the combined evaluation of sEV's biomarkers has extremely high sensitivity, specificity and accuracy. The present study introduces an alternative approach to sEVs isolation and detection, has a great potential in real-time sEVs-based liquid biopsy.

Potential clinical applications of extracellular vesicles in pancreatic cancer: exploring untapped opportunities from biomarkers to novel therapeutic approaches

Pancreatic cancer is a highly lethal and metastatic malignancy, mainly because it often remains undetected until advanced stages due to the limitations of current diagnostic methods, rendering currently available therapies ineffective. Therefore, it is imperative to identify useful biomarkers for early diagnosis and new therapeutic targets for pancreatic cancer. Recently, extracellular vesicles have emerged as promising biomarkers for the diagnosis and prognosis of pancreatic cancer. Given their presence in various bodily fluids, extracellular vesicles offer a non-invasive approach through liquid biopsy to detect and monitor cancer progression. In this review, we comprehensively examine the multifaceted roles of extracellular vesicles in the progression of cancer, while also exploring their potential as diagnostic, prognostic, and therapeutic biomarkers in the context of pancreatic cancer.

Greatly isolated heterogeneous circulating tumor cells using hybrid engineered cell membrane-camouflaged magnetic nanoparticles

BackgroundCirculating tumor cells (CTCs) are considered as a useful biomarker for early cancer diagnosis, which play a crucial role in metastatic process. Unfortunately, the tumor heterogeneity and extremely rare occurrence rate of CTCs among billions of interfering leukocytes seriously hamper the sensitivity and purity of CTCs isolation.MethodsTo address these, we firstly used microfluidic chips to detect the broad-spectrum of triple target combination biomarkers in CTCs of 10 types of cancer patients, including EpCAM, EGFR and Her2. Then, we constructed hybrid engineered cell membrane-camouflaged magnetic nanoparticles (HE-CM-MNs) for efficient capture of heterogeneous CTCs with high-purity, which was enabled by inheriting the recognition ability of HE-CM for various CTCs and reducing homologous cell interaction with leukocytes. Compared with single E-CM-MNs, HE-CM-MNs showed a significant improvement in the capture efficiency for a cell mixture, with an efficiency of 90%. And the capture efficiency of HE-CM-MNs toward 12 subpopulations of tumor cells was ranged from 70 to 85%. Furthermore, by using HE-CM-MNs, we successfully isolated heterogeneous CTCs with high purity from clinical blood samples. Finally, the captured CTCs by HE-CM-MNs could be used for gene mutation analysis.ConclusionsThis study demonstrated the promising potential of HE-CM-MNs for heterogeneous CTCs detection and downstream analysis.Graphical abstract

Seminal plasma S100A8/A9 as a potential biomarker of genital tract inflammation

Abstract Infections and inflammatory reactions in the male genital tract are the leading causes of male infertility with a prevalence of 6%–10%, primarily affecting testicular and epididymal function and ultimately compromising sperm quality. However, most infertile patients with genital infection/inflammation are asymptomatic and easily overlooked. Traditional indicators, including white blood cells, elastase, and other components in semen, can reflect inflammation of the genital tract, but there is still a lack of a uniform standard method of detection. Therefore, it is necessary to explore reliable markers in semen that reflect the inflammatory status of the genital tract. Using the experimental autoimmune orchitis (EAO) model to simulate noninfectious chronic orchitis, we successfully collected ejaculated seminal fluid from EAO rats using optimized electrical stimulation devices. Proteomic analysis was performed using isobaric tags for relative and absolute quantification (iTRAQ). Compared to the control group, 55 upregulated and 105 downregulated proteins were identified in seminal plasma samples from the EAO group. In a preliminary screening, the inflammation-related protein S100A8/A9 was upregulated. We further verified that S100A8/A9 was increased in seminal plasma and highly expressed in testicular macrophages of the EAO model. In patients with oligoasthenospermia and genital tract infections, we also found that S100A8/A9 levels were remarkably increased in seminal plasma and testicular macrophages. S100A8/A9 in semen may be a potential biomarker for chronic genital inflammation. Our study provides a new potential biomarker for early diagnosis and further understanding of male infertility caused by genital inflammation.

Homocystein, Vitamin B12 and Folic Acid as Screening Biomarkers in Early Diagnosis and Gastric Cancer Monitoring.

Gastric cancer has been demonstrating a reduction in the number of cases over the past decades, largely attributed to advancements in public health practices and increased accessibility to educational initiatives for the general population. Nevertheless, it persists as the third leading cause of mortality globally among both men and women. These fatalities are typically associated with delayed disease detection. The current study assessed the levels of homocysteine, vitamin B12, and folic acid as a means of establishing a screening biomarker profile that could be integrated into routine testing protocols to facilitate swift diagnosis of the illness. A total of 207 control subjects and 207 individuals with gastric cancer were scrutinized, with biochemical measurements conducted using chemiluminescence for homocysteine, folic acid, and vitamin B12. The two groups were matched based on age, tumor location, subtype, tumor classification, presence of Epstein-Barr Virus infection (EBV), and Helicobacter pylori (H. pylori). Significant statistical variances were identified in the mean levels of the triad of substances among cancer patients when compared to the control group for all corresponding variables. In conclusion, our study indicated that analyzing the triad of homocysteine, vitamin B12, and folic acid holds diagnostic value for gastric cancer and could potentially serve as an effective screening marker for this type of cancer in the future.

Targeted metabolomics combined with machine learning to identify and validate new biomarkers for early SLE diagnosis and disease activity

BackgroundThe early diagnosis of systemic lupus erythematosus (SLE) and the assessment of disease activity progression remain a great challenge. Targeted metabolomics has great potential to identify new biomarkers of SLE. MethodsSerum from 44 healthy participants and 89 SLE patients were analyzed using HM400 high-throughput targeted metabolomics. Machine learning (ML) with seven learning models and trained the model several times iteratively selected the two best prediction model in a competitive way, which were independent validated by enzyme-linked immunosorbent (ELISA) with 90 SLE patients. ResultsIn this study, 146 differential metabolites, most of them organic acids, amino acids, and bile acids, were detected between patients with initial SLE and healthy participants, and 8 potential biomarkers were found by intersection of ML and statistics (area under the curve [AUC] > 0.95) showing a significant positive correlation with clinical indicators. In addition, we identified and validated 2 potential biomarkers for SLE classification (P < 0.05, AUC > 0.775; N-Methyl-L-glutamic acid, L-2-aminobutyric acid) showing a significant correlation with the SLE Disease Activity Index. These differential metabolites were mainly involved in metabolic pathways, amino acid biosynthesis, 2-oxocarboxylic acid metabolism and other pathways. ConclusionThis study indicated that the tricarboxylic acid cycle might be associated with SLE drug therapy. We identified 8 diagnostic models biomarkers and 2 biomarkers that could be used to identify initial SLE and distinguish different activity degree, which will promote the development of new tools for the diagnosis and evaluation of SLE.

Cutaneous biomarkers of therapeutic efficacy in early treatment of hereditary ATTR amyloid polyneuropathy with tafamidis.

ATTR (ATTRv) amyloidosis neuropathy is characterized by progressive sensorimotor and autonomic nerve degeneration secondary to amyloid deposition caused by a misfolded transthyretin protein (TTR). Small nerve fiber neuropathy is an early clinical manifestation of this disease resulting from the dysfunction of the Aδ and C small nerve fibers. Tafamidis, a selective TTR stabilizer, has proven its efficacy in the earlier stages of hATTR. To evaluate the clinical course and utility of cutaneous pathological biomarkers in patients with ATTR amyloidosis treated with tafamidis compared to control patients. Forty patients diagnosed with early stages of ATTRv amyloidosis (polyneuropathy disability [PND] scores 0-II) underwent small and large nerve fiber neurological evaluations, and annual skin biopsies for intraepidermal nerve fiber density (IENFD) and amyloid deposition index (ADI) estimation. Thirty patients were allocated to receive tafamidis, and 10 patients served as controls. Tafamidis pharmacokinetics analysis was performed in patients who received the treatment. At baseline, 12% of patients in stage PND 0 and 28% in PND I displayed small nerve fiber denervation in the distal thigh, whereas 23% and 38%, respectively, in the distal leg. Similarly, 72% and 84% had amyloid deposition in the distal thigh and 56% and 69% in the distal leg. Following 1 year of treatment, the tafamidis group showed significant clinical improvement compared to the control group, revealed by the following mean differences (1) -9.3 versus -4 points (p = <.00) in the patient's neuropathy total symptom score 6 (NTSS-6) questionnaire, (2) -2.5 versus +2.8 points (p = <.00) in the Utah Early Neuropathy Score (UENS), and (3) +1.2°C versus -0.6 (p = .01) in cold detection thresholds. Among the patients who received tafamidis, 65% had stable or increased IENFD in their distal thigh and 27% in the distal leg. In contrast, all patients in the control group underwent denervation. The ADI either decreased or remained constant in 31% of the biopsies in the distal thigh and in 24% of the biopsies in the distal leg of the tafamidis-treated patients, whereas it rose across all the biopsies in the control group. At the 4-year follow-up, the tafamidis group continued to display less denervation in the distal thigh (mean difference [MD] of -3.0 vs. -9.3 fibers/mm) and the distal leg (mean difference [MD] -4.9 vs. -8.6 fibers/mm). ADI in tafamidis-treated patients was also lower in the distal thigh (10 vs. 30 amyloid/mm2) and the distal leg (23 vs. 40 amyloid/mm2) compared to control patients. Plasma tafamidis concentrations were higher in patients with IENFD improvement and in patients with reduced amyloid deposition. Patients without amyloid deposition in the distal leg at baseline displayed delayed disease progression at 4 years. Cutaneous IENFD and amyloid deposition assessments in the skin of the distal thigh and distal leg are valuable biomarkers for early diagnosis of ATTR amyloidosis and for measuring the progression of small nerve fiber neuropathy. Early treatment with tafamidis slows the clinical progression of the disease, skin denervation, and amyloid deposition in the skin. Higher plasma concentrations of tafamidis are associated with better disease outcomes, suggesting that increasing the drug dose could achieve better plasma concentrations and response rates. This study describes the longest small nerve fiber neuropathy therapeutic trial with tafamidis and is the first to report small fiber symptoms, function, and structural assessments as outcomes.

MiR-3653-3p Expression in PBMCs: Unveiling the Diagnostic Potential for Ovarian Cancer.

Ovarian cancer is typically diagnosed at an advanced stage, recurs early and often, and currently lacks effective treatment. Therefore, overall survival and progression-free survival are relatively short for this disease. Sensitive and specific biomarkers for early diagnosis and follow-up for effective treatment of the disease are currently lacking. MicroRNA (miRNA/miR) expression studies are widely used in cancer research. Disruption or malfunction of miRNAs, a class of noncoding small RNAs, has been implicated in cancer progression in several publications. Of note, the expression of a series of miRNAs is known to differ in ovarian cancer. In cancer research, it is crucial to analyze expression patterns in both cancer patients and healthy individuals to identify cancer-specific biological markers and to understand their role in cancer. In the present study, the expression levels of miR-3653-3p in the peripheral blood mononuclear cells (PBMCs) of 150 patients with high-risk ovarian cancer were determined, including those with a family history of cancer or an early-age diagnosis of ovarian cancer, as well as 100 healthy individuals. The results were then compared between the two groups. The expression level of miR-3653-3p in the PBMCs of patients with ovarian cancer was determined to be 9.49-fold higher than that in the healthy control group, and this result was statistically significant (P < 0.001). In addition, receiver-operating characteristic curve analysis of PBMC showed statistical significance of miR-3653-3p in discriminating ovarian cancer patients from healthy subjects (P < 0.001). These results suggest that miR-3653-3p detected in peripheral blood may be used as a non-invasive biomarker for ovarian cancer.

New Paradigms in the Clinical Management of Li-Fraumeni Syndrome.

Approximately 8.5%-16.2% of childhood cancers are associated with a pathogenic/likely pathogenic germline variant-a prevalence that is likely to rise with improvements in phenotype recognition, sequencing, and variant validation. One highly informative, classical hereditary cancer predisposition syndrome is Li-Fraumeni syndrome (LFS), associated with germline variants in the TP53 tumor suppressor gene, and a >90% cumulative lifetime cancer risk. In seeking to improve outcomes for young LFS patients, we must improve the specificity and sensitivity of existing cancer surveillance programs and explore how to complement early detection strategies with pharmacology-based risk-reduction interventions. Here, we describe novel precision screening technologies and clinical strategies for cancer risk reduction. In particular, we summarize the biomarkers for early diagnosis and risk stratification of LFS patients from birth, noninvasive and machine learning-based cancer screening, and drugs that have shown the potential to be repurposed for cancer prevention.

Association Between ACE2 and Lung Diseases.

Angiotensin-converting enzyme 2 (ACE2) is an important regulator of the Renin-Angiotensin System (RAS). Additionally, it has been identified as a functional receptor for the Coronavirus. Research indicates that ACE2 plays a role in the regulation of cardiovascular systems by modulating blood pressure and electrolyte balance. Its role in pulmonary diseases has also garnered significant attention due to the widespread prevalence of Coronavirus. There is solid evidence linking ACE2 to other pulmonary diseases, including chronic obstructive pulmonary disease, acute respiratory distress syndrome, allergic asthma, among others. However, the exact pathological and physiological mechanisms of ACE2 in these diseases remain elusive. Our research aims to review and explore the latest advancements in ACE2-related studies in pulmonary diseases. These findings have the potential to open new avenues for utilizing ACE2 as a potential biomarker for early diagnosis and monitoring of pulmonary diseases.

Combined Biomarkers for Early Diagnosis of Hepatocellular Carcinoma

Combined Biomarkers for Early Diagnosis of Hepatocellular Carcinoma

DHEA-S, Androstenedione, 17-β-estradiol signature as novel biomarkers for early prediction of risk of malignant pleural mesothelioma linked to asbestos-exposure: A preliminary investigation

17-β-estradiol, involved in mesothelioma pathogenesis, and its precursors were explored as potential biomarkers for the early diagnosis of mesothelioma. Using enzyme-linked immunosorbent assay(ELISA) for 17-β-estradiol and ultra-high performance liquid chromatography/tandem mass spectrometry(UHPLC-MS/MS) for 19 17-β-estradiol precursors, a comprehensive analysis of 20steroid hormones was conducted in the serum of mesothelioma patients(n=67), asbestos-exposed healthy subjects(n=39), and non-asbestos-exposed healthy subjects(n=35). Bioinformatics analysis explored three potential serum biomarkers: 17-β-estradiol, DHEA-S, and androstenedione. The results revealed significant differences in 17-β-estradiol levels between mesothelioma patients and both non-asbestos-exposed and asbestos-exposed healthy subjects. No significant variations in serum 17-β-estradiol levels were observed among mesothelioma patients at different stages, suggesting its potential as an early diagnostic marker. 17-β-estradiol levels were similar in mesothelioma patients with environmental and occupational asbestos exposure, while males with occupational asbestos exposure exhibited significantly higher levels of 17-β-estradiol compared to females. Significant reduction in androstenedione and an increase in DHEA-S were observed in asbestos-exposed individuals compared to non-asbestos-exposed individuals. The analysis of DHEA-S-androstenedione-17-β-estradiol signature score showed an increase in asbestos-exposed individuals and mesothelioma patients compared to non-asbestos-exposed individuals, and this score effectively distinguished between the groups. The Cancer Genome Atlas data was utilized to analyze the expression of 5-α-reductase1 and hydroxysteroid-17β-dehydrogenase2 genes. The findings indicated that mesothelioma patients with elevated gene values for 5-α-reductase1 and hydroxysteroid-17β-dehydrogenase2 have a worse or better prognosis on overall survival, respectively. In conclusion, this study suggests 17-β-estradiol, DHEA-S, and androstenedione as biomarkers for mesothelioma risk and early diagnosis of mesothelioma in asbestos-exposed individuals, aiding timely intervention and improved care.

Diagnostic Potential Role of CXCL3 and Leptin Levels in Breast Cancer

The risk of breast cancer development is believed to be attributed to the alterations of a number of key biological components. Within this context, elevated levels of some chemokines that act as growth factors and can promote cancer development. The current study was designed to evaluate CXCL3 (a chemokine C-X-C Motif Ligand 3) and leptin (a peptide hormone synthesized by adipose tissue with cytokine activity) serum of Iraqi breast cancer patients in comparison to healthy controls. A total of 90 participants consisted of 60 patients diagnosed with breast cancer and 30 healthy women as control group were enrolled into this case-control study. Venous blood samples were collected from all participants to evaluate CXCL3 and leptin serum levels using ELISA. The results demonstrated significantly (P≤0.001) higher mean levels of CXCL3 and leptin in breast cancer patients (1.19±0.10 ng/mL and 130.44± 3.72pg/mL) compared to those of their healthy counterparts (0.430± 0.02\ng/mL and 57.1± 3.2pg/mL respectively). Interestingly, vast majority of the assessed breast cancer cases (up to 95-98%) showed to have elevated serum levels of both of the assessed potential biomarkers (CXCL3 and leptin). The present study results suggest an association of both CXCL3 and leptin in breast cancer pathogenicity. This supports the possibility of utilizing these potential biomarkers for breast cancer early detection and diagnosis.

Novel Variants Linked to the Prodromal Stage of Parkinson's Disease (PD) Patients.

The symptoms of most neurodegenerative diseases, including Parkinson's disease (PD), usually do not occur until substantial neuronal loss occurs. This makes the process of early diagnosis very challenging. Hence, this research used variant call format (VCF) analysis to detect variants and novel genes that could be used as prognostic indicators in the early diagnosis of prodromal PD. Data were obtained from the Parkinson's Progression Markers Initiative (PPMI), and we analyzed prodromal patients with gVCF data collected in the 2021 cohort. A total of 304 participants were included, including 100 healthy controls, 146 prodromal genetic individuals, 21 prodromal hyposmia individuals, and 37 prodromal individuals with RBD. A pipeline was developed to process the samples from gVCF to reach variant annotation and pathway and disease association analysis. Novel variant percentages were detected in the analyzed prodromal subgroups. The prodromal subgroup analysis revealed novel variations of 1.0%, 1.2%, 0.6%, 0.3%, 0.5%, and 0.4% for the genetic male, genetic female, hyposmia male, hyposmia female, RBD male, and RBD female groups, respectively. Interestingly, 12 potentially novel loci (MTF2, PIK3CA, ADD1, SYBU, IRS2, USP8, PIGL, FASN, MYLK2, USP25, EP300, and PPP6R2) that were recently detected in PD patients were detected in the prodromal stage of PD. Genetic biomarkers are crucial for the early detection of Parkinson's disease and its prodromal stage. The novel PD genes detected in prodromal patients could aid in the use of gene biomarkers for early diagnosis of the prodromal stage without relying only on phenotypic traits.

Metabolomics Analysis Identifies Differential Metabolites as Biomarkers for Acute Myocardial Infarction.

Myocardial infarction (MI), including ST-segment elevation MI (STEMI) and non-ST-segment elevation MI (NSTEMI), is still a leading cause of death worldwide. Metabolomics technology was used to explore differential metabolites (DMs) as potential biomarkers for early diagnosis of STEMI and NSTEMI. In the study, 2531 metabolites, including 1925 DMs, were discovered. In the selected 27 DMs, 14 were successfully verified in a new cohort, and the AUC values were all above 0.8. There were 10 in STEMI group, namely L-aspartic acid, L-acetylcarnitine, acetylglycine, decanoylcarnitine, hydroxyphenyllactic acid, ferulic acid, itaconic acid, lauroylcarnitine, myristoylcarnitine, and cis-4-hydroxy-D-proline, and 5 in NSTEMI group, namely L-aspartic acid, arachidonic acid, palmitoleic acid, D-aspartic acid, and palmitelaidic acid. These 14 DMs may be developed as biomarkers for the early diagnosis of MI with high sensitivity and specificity. These findings have particularly important clinical significance for NSTEMI patients because these patients have no typical ECG changes.

Exonuclease-iii -propelled DNAzyme cascade for sensitive and reliable cervical cancer related miRNA analysis

MicroRNAs (miRNAs) can serve as biomarkers for early-diagnosis, therapy, and postoperative care of cervical cancer. Sensitive and reliable quantification of miRNA remains a huge challenge due to its low expressing levels and background interference. Herein, we propose a novel exonuclease-III (Exo–III)–propelled DNAzyme cascade for sensitive and high-efficient miRNA analysis. This method involves the engineering of compact DNAzyme hairpin probes, including the H1 probe and H2 probe. The H1 probe is designed with exposed analyte recognition subunits that can specifically recognize target miRNA. This recognition triggers two processes: Exo-iii-assisted target regeneration and successive substrate cleavage catalyzed by DNAzyme. The unique character of Exo-III that catalyzes removal of mononucleotides from the blunt or recessed 3′-OH termini of dsDNA confers the approach with a minimal background signal. The multiple signal cycles provided an abundant signal amplification and consequently, the method exhibited a low limit of detection of 3.12 fM, and a better specificity over several homologous miRNAs. In summary, this powerful Exo-III driven DNAzyme cascaded system offers broader and more adaptable methods for comprehending the activities of miRNA in various biological occurrences.

Exploring the Neurogenetic Landscape of Autism Spectrum Disorder: The Role of Brain-Derived Neurotrophic Factor (BDNF) Gene in the Complex Web of Neurodevelopment

Autism Spectrum Disorder (ASD) is a complex neurodevelopmental disorder with varied manifestations including altered metabolic profiles. Recent research highlights the potential role of Brain-Derived Neurotrophic Factor (BDNF), a hormone derived from adipose tissue, in the pathology of ASD. BDNF levels are reportedly correlated with the severity of autism symptoms, suggesting a link between metabolic dysfunction and the disorder. Objective: This study aims to deepen the understanding of BDNF levels in individuals with ASD and to explore the implications for diagnosis, treatment, and management of the disorder. It seeks to elucidate the relationship between low BDNF levels and increased autism severity, and to identify potential therapeutic interventions targeting BDNF dysregulation. Methods: EDTA blood samples (5ml each) from 140 participants (108 with ASD and 32 healthy controls) were collected across various hospitals in Karachi. Plasma serum levels of BDNF were analyzed following a six-month follow-up. A comprehensive statistical analysis was performed, focusing on the relationship between BDNF levels and autism severity, and evaluating diagnostic and therapeutic implications of BDNF dysregulation. Results: Analysis revealed that lower BDNF serum levels were consistently associated with higher autism severity. Specifically, 60-70% of participants with ASD scored below 8 on the Mini-Mental State Examination (MMSE), indicating significant cognitive impairment. The statistical significance of these findings was confirmed with p-values &lt;0.05. Conclusion: The study confirms that low BDNF levels are significantly associated with greater severity of autism symptoms, underscoring the importance of metabolic factors in the pathogenesis of ASD. BDNF stands out as a potential biomarker for early ASD diagnosis and personalized treatment strategies. Future Prospects: Future research should aim to delineate the mechanistic relationship between BDNF dysregulation and ASD pathology. Longitudinal studies are needed to assess the long-term effects of BDNF modulation on ASD outcomes and to validate its effectiveness as both a diagnostic and prognostic marker.

Diagnostic and prognostic value of plasma miR-106a-5p levels in patients with acute heart failure

BackgroundIt is essential to find reliable biomarkers for early diagnosis and prognosis of acute heart failure (AHF) for its mitigation. Currently, increasing attention is paid to the role of microRNAs (miRNAs/miRs) as diagnostic or prognostic markers for cardiovascular diseases. Since plasma miR-106a-5p has been observed to be downregulated in AHF, its value in the diagnosis and prognostic assessment of AHF deserves further exploration. Accordingly, this study analyzed the diagnostic and prognostic value of plasma miR-106a-5p in AHF patients.MethodsProspectively, this study included 127 AHF patients who met the 2021 European Society of Cardiology Guidelines and 127 control individuals. Plasma miR-106a-5p levels were determined with RT-qPCR. Spearman correlation analysis was performed to evaluate the correlation of plasma miR-106a-5p levels with NT-proBNP and hs-CRP levels in AHF patients. All AHF patients were followed up for 1 year and allocated into poor and good prognosis groups, and plasma miR-106a-5p levels were compared. The diagnostic and prognostic value of plasma miR-106a-5p for AHF was assessed with a receiver-operating characteristic curve.ResultsPlasma miR-106a-5p was lowly expressed in AHF patients versus controls (0.53 ± 0.26 vs. 1.09 ± 0.46) and showed significant negative correlations with NT-proBNP and hs-CRP levels. Plasma miR-106a-5p level < 0.655 could assist in AHF diagnosis. Plasma miR-106a-5p levels were markedly lower in poor-prognosis AHF patients than in good-prognosis patients. Plasma miR-106a-5p level < 0.544 could assist in predicting poor prognosis in AHF patients.ConclusionPlasma miR-106a-5p is downregulated in AHF patients and could assist in diagnosis and poor prognosis prediction of AHF.