Autonomous enzymatic synthesis of functional nucleic acids for sensitive measurement of long noncoding RNA in human lung tissues.

Aberrant long noncoding RNA (lncRNA) expression is linked to varied pathological processes and malignant tumors, and lncRNA can serve as potential disease biomarkers. Herein, we demonstrate the autonomous enzymatic synthesis of functional nucleic acids for sensitive measurement of lncRNA in human lung tissues on the basis of multiple primer generation-mediated rolling circle amplification (mPG-RCA). This assay involves two padlock probes that act as both a detection probe for recognizing target lncRNA and a domain for producing complementary DNAzyme. Two padlock probes can hybridize with target lncRNA at different sites, followed by ligation to form a circular template with the aid of RNA ligase. The circular template can initiate mPG-RCA to generate abundant Mg2+-dependent DNAzymes that can specifically cleave signal probes to induce the recovery of Cy3 fluorescence. The inherent characteristics of ligase-based ligation reaction and DNAzymes endow this assay with excellent specificity, and the introduction of multiple padlock probes endows this assay with high sensitivity. This strategy can rapidly and sensitively measure lncRNA with a wide linear range of 1 fM - 1 nM and a detection limit of 678 aM within 1.5 h, and it shows distinct advantages of simplicity and immobilization-free without the need of precise temperature control and tedious procedures of nanomaterial preparation. Moreover, it enables accurate measurement of lncRNA level in normal cells and malignant tumor cells as well as differentiation of lncRNA expressions in tissues of non-small cell lung cancer (NSCLC) patients and normal individuals, with promising applications in biomedical studies and disease diagnosis.

Next Generation Sequencing strategies in venous thromboembolism: in whom and for what purpose ?

This invited review follows the oral presentation "To Sequence or Not to Sequence, That Is Not the Question; But "When, Who, Which and What For?" Is " given during the State Of the Art session Translational Genomics in Thrombosis: From OMICs to Clinics" of the ISTH 2023 congress. Emphasizing the power of next-generation sequencing technologies and the diverse strategies associated with DNA variant analysis, this review highlights the unresolved questions and challenges in their implementation both for the clinical diagnosis of venous thromboembolism and in translational research.

Assessing the clinical diagnostic value of anti-Müllerian hormone in polycystic ovarian syndrome and its correlation with clinical and metabolism indicators.

BACKGROUND: This study investigated the association between Anti-Müllerian Hormone (AMH) and relevant metabolic parameters and assessed its predictive value in the clinical diagnosis of polycystic ovarian syndrome (PCOS). METHODS: A total of 421 women aged 20-37 years were allocated to the PCOS (n = 168) and control (n = 253) groups, and their metabolic and hormonal parameters were compared. Spearman correlation analysis was conducted to investigate associations, binary logistic regression was used to determine PCOS risk factors, and receiver operating characteristic (ROC) curves were generated to evaluate the predictive value of AMH in diagnosing PCOS. RESULTS: The PCOS group demonstrated significantly higher blood lipid, luteinizing hormone (LH), and AMH levels than the control group. Glucose and lipid metabolism and hormonal disorders in the PCOS group were more significant than in the control group among individuals with and without obesity. LH, TSTO, and AMH were identified as independent risk factors for PCOS. AMH along with LH, and antral follicle count demonstrated a high predictive value for diagnosing PCOS. CONCLUSION: AMH exhibited robust diagnostic use for identifying PCOS and could be considered a marker for screening PCOS to improve PCOS diagnostic accuracy. Attention should be paid to the effect of glucose and lipid metabolism on the hormonal and related parameters of PCOS populations.

Depressive symptomatology from a network perspective: Differences in the experience of symptoms involved in the self-recognition of depression and the diagnosis process by social position.

BACKGROUND: While social disparities in depression are well-documented, the symptom experience across social positions remains less studied. AIMS: This study examines the connections between depressive symptoms and self-recognizing a depressive episode, on the one hand, and clinical diagnosis, on the other hand, by three social position indicators. METHODS: We analyzed baseline data from a population-based cohort of adults living in France, grouping participants by three indicators: education, financial difficulties, and occupation, and stratifying by sex. Utilizing a psychometric network approach, we estimated 24 networks. Nodes corresponded to the 20 CES-D items and 1 external variable, either 'Limitations due to depression' or 'Clinical depression'. Comparisons between socially disadvantaged and advantaged groups across the three social indicators were made in terms of network structures, global strength, and edge weights involving symptoms and both external nodes. RESULTS: The study included data from 201,952 participants. Individuals in lower social positions exhibited higher rates of depressive-related variables. Four depressive symptoms emerged as crucial, being linked both to 'Clinical depression' and 'Limitations' across all social positions. Socially disadvantaged groups had denser networks. Some of the tests comparing network structures according to social position were significant, suggesting differences in the symptom activation chains. Connections between each external node and 'Felt depressed' and 'Could not get going' were non-invariant in educational and financial-based networks. CONCLUSIONS: Findings highlight four depressive symptoms, likely to play a key role in the experience of depression across all social positions. Other insights from specific symptoms could be used for improving depression care among disadvantaged populations.

A novel homozygous variant in SLC25A46 gene associated with pontocerebellar hypoplasia type 1E: a case report.

Neonatal encephalopathy (NE) is a complex clinical condition with diverse etiologies. Hypoxic-ischemic encephalopathy (HIE) is a major contributor to NE cases. However, distinguishing NE subtypes, such as pontocerebellar hypoplasia type 1E (PCH1E), from HIE can be challenging due to overlapping clinical features. Here, we present a case of PCH1E in a neonate with a homozygous mutation c.72delT p. (Phe24LeufsTer20) in the SLC25A46 gene. The severity of PCH1E associated NE highlighted the significance of early recognition to guide appropriate clinical management.

Impact of muscle biopsy on the clinical decision-making process in patients with suspected idiopathic inflammatory myopathy.

BACKGROUND: The significance of muscle biopsy as a diagnostic tool in idiopathic inflammatory myopathies (IIM) remains elusive. We aimed to determine the diagnostic weight that has been given to muscle biopsy in patients with suspected IIM, particularly in terms of clinical diagnosis and therapeutic decisions. MATERIAL AND METHODS: In this retrospective multicentric study, we analyzed muscle biopsy results of adult patients with suspected IIM referred to a tertiary center between January 1, 2007, and October 31, 2021. Information regarding referral department, suspected diagnosis, biopsy site, demographic, clinical, laboratory data, and imaging results were extracted. Statistical analyses included the level of agreement between suspected and histological diagnosis and calculation of diagnostic performance (positive and negative predictive values, positive and negative likelihood ratios, sensitivity, and specificity of muscle biopsy in relation to clinical diagnosis and/or treatment initiation). Performance was tested in different strata based on clinical pre-test probability. RESULTS: Among 758 muscle biopsies, IIM was histologically compatible in 357/758 (47.1%) cases. Proportion of IIM was higher if there was a solid clinical pre-test probability (64.3% vs. 42.4% vs. 48% for high, medium and low pre-test probability). Sensitivity and specificity of muscle biopsy were highest (82%) when the diagnosis by the clinician was used as outcome scenario. Negative predictive value was only moderate (between 63% and 80%) and lowest if autoantibodies were positive (35%). CONCLUSION: In patients with clinically suspected IIM, approximately 50% of biopsies revealed features indicative of IIM. Diagnostic performance of muscle biopsy was moderate to high depending on clinical pre-test probability.

The Diagnostic Accuracy of Procalcitonin, Soluble Urokinase-Type Plasminogen Activator Receptors, and C-Reactive Protein in Diagnosing Urinary Tract Infections in the Emergency Department-A Diagnostic Accuracy Study.

Background: Urinary tract infections (UTIs) are a leading bacterial infection in the emergency department (ED). Diagnosing UTIs in the ED can be challenging due to the heterogeneous presentation; therefore, fast and precise tests are needed. We aimed to evaluate the diagnostic precision of procalcitonin (PCT), soluble urokinase plasminogen activator receptors (suPARs), and C-reactive protein (CRP) in diagnosing UTIs, grading the severity of UTIs, and ruling out bacteremia. Methods: We recruited adults admitted to three Danish EDs with suspected UTIs. PCT, suPAR, and CRP were used in index tests, while blood cultures, expert panel diagnosis, and severity grading were used in the reference tests. Logistic regression and area under the receiver operator characteristic curves (AUROCs) were utilized to evaluate the models and determine the optimal cut-offs. Results: We enrolled 229 patients. PCT diagnosed UTI with an AUROC of 0.612, detected severe disease with an AUROC of 0.712, and ruled out bacteremia with an AUROC of 0.777. SuPAR had AUROCs of 0.480, 0.638, and 0.605, while CRP had AUROCs of 0.599, 0.778, and 0.646. Conclusions: The diagnostic performance of PCT, suPAR, or CRP for UTIs or to rule out severe disease was poor. However, PCT can safely rule out bacteremia in clinically relevant numbers in ED patients suspected of UTI.

Clinical relevance and advances in detection of translational biomarker cardiac troponin.

Cardiovascular diseases (CVD) are a range of diseases, pointing the functional hindrances in the heart and blood vessels of the human system that contributes to 48.6 % of the world's adult death rate. The diagnosis of CVD relies upon the Electro Cardio Gram (ECG) and detection of muscle markers such as troponins. Among the cardiac trio, Cardiac Troponin I (cTnI) weighing 23 KiloDalton (kDa) is a sorted biomarker for CVD. cTnI remains high in the blood after 1-2 weeks of myocardial damage. Testing of cTnI in CVD patients aids in diagnosis and risk stratification of the disease. Different determination systems including optical, electrochemical, and acoustic have been put forward for monitoring the cTnI which are Point of Care (POC) that promotes simple and sensitive detection of cTnI. The modern era has paved way to high-sensitivity Troponin I (hscTnI) devices that can detect up to 0.01 ng/ml in human blood/plasma/serum. Yet, the practice of hscTnI is impracticable due to cost inefficiency. Development of new hscTnI devices with minimal investment and maximal detection range will meet the global requirement. This review gives an over view on different detection systems of cardiac troponin I which stands as a translational detection molecule for CVDs.

Design and application of a novel "turn-on" fluorescent probe for imaging sulfite in living cells and inflammation models.

Sulfite is one of the main existing forms of sulfur dioxide (SO2) in living system, which has been recognized as an endogenous mediator in inflammation. Evidence has accumulated to show that abnormal level of sulfite is associated with many inflammatory diseases, including neurological diseases and cancers. Herein, a novel fluorescent probe named QX-OA was designed and synthesized to detect sulfite. QX-OA was constructed by choosing quinolinium-xanthene as the fluorophore and levulinate as the specific and relatively steady recognition reaction. The probe showed remarkable green turn-on signal at 550 nm, together with high sensitivity (90-fold) and excellent selectivity to sulfite over other possible interfering species. In the meantime, QX-OA was successfully applied to visualize endogenous and exogenous sulfite in Hela cells. In the LPS-induced inflammation model, QX-OA could visualize the dose-dependent increase of sulfite level (0-2 mg/mL). Consequently, QX-OA was determined to be a potential method for detecting sulfite in pre-clinical diagnosis.

Diagnosis and treatment of Paget's disease of bone: position paper from the Italian Society of Osteoporosis, Mineral Metabolism and Skeletal Diseases (SIOMMMS).

INTRODUCTION: Paget's disease of bone is a focal skeletal disorder causing bone deformities and impairing bone quality. Despite the prevalence of asymptomatic cases is increasing, the progression of the disease can lead to invalidating complications that compromise the quality of life. Doubts on clinical and therapeutic management aspects exist, although beneficial effects of antiresorptive drugs, particularly bisphosphonates are known. However, limited information is available from randomized controlled trials on the prevention of disease complications so that somewhat contrasting positions about treatment indications between expert panels from the main scientific societies of metabolic bone diseases exist. This task force, composed by expert representatives appointed by the Italian Society of Osteoporosis, Mineral Metabolism and Skeletal Diseases and members of the Italian Association of Paget's disease of bone, felt the necessity for more specific and up to date indications for an early diagnosis and clinical management. METHODS: Through selected key questions, we propose evidence-based recommendations for the diagnosis and treatment of the disease. In the lack of good evidence to support clear recommendations, available information from the literature together with expert opinion of the panel was used to provide suggestions for the clinical practice. RESULTS AND CONCLUSION: Description of the evidence quality and support of the strength of the statements was provided on each of the selected key questions. The diagnosis of PDB should be mainly based on symptoms and the typical biochemical and radiological features. While treatment is mandatory to all the symptomatic cases at diagnosis, less evidence is available on treatment indications in asymptomatic as well as in previously treated patients in the presence of biochemical recurrence. However, given the safety and long-term efficacy of potent intravenous bisphosphonates such as zoledronate, a suggestion to treat most if not all cases at the time of diagnosis was released.

Construction of a glycosylation-mediated fluorescent biosensor for label-free measurement of site-specific 5-hydroxymethylcytosine in cancer cells with zero background signal.

BACKGROUND: 5-hydroxymethylcytosine (5hmC) as an epigenetic modification can regulate gene expression, and its abnormal level is related with various tumor invasiveness and poor prognosis. Nevertheless, the current methods for 5hmC assay usually involve expensive instruments/antibodies, radioactive risk, high background, laborious bisulfite treatment procedures, and non-specific/long amplification time. RESULTS: We develop a glycosylation-mediated fluorescent biosensor based on helicase-dependent amplification (HDA) for label-free detection of site-specific 5hmC in cancer cells with zero background signal. The glycosylated 5hmC-DNA (5ghmC) catalyzed by ß-glucosyltransferase (ß-GT) can be cleaved by AbaSI restriction endonuclease to generate two dsDNA fragments with sticky ends. The resultant dsDNA fragments are complementary to the biotinylated probes and ligated by DNA ligases, followed by being captured by magnetic beads. After magnetic separation, the eluted ligation products act as the templates to initiate HDA reaction, generating abundant double-stranded DNA (dsDNA) products within 20 min. The dsDNA products are measured in a label-free manner with SYBR Green I as an indicator. This biosensor can measure 5hmC with a detection limit of 2.75 fM and a wide linear range from 1 × 10-14 to 1 × 10-8 M, and it can discriminate as low as 0.001% 5hmC level in complex mixture. Moreover, this biosensor can measure site-specific 5hmC in cancer cells, and distinguish tumor cells from normal cells. SIGNIFICANCE: This biosensor can achieve a zero-background signal without the need of either 5hmC specific antibody or bisulfite treatment, and it holds potential applications in biological research and disease diagnosis.

Lumbar disc herniation: Epidemiology, clinical and radiologic diagnosis WFNS spine committee recommendations.

Objective: To formulate the most current, evidence-based recommendations regarding the epidemiology, clinical diagnosis, and radiographic diagnosis of lumbar herniated disk (LDH). Methods: A systematic literature search in PubMed, MEDLINE, and CENTRAL was performed from 2012 to 2022 using the search terms "herniated lumbar disc", "epidemiology", "prevention" "clinical diagnosis", and "radiological diagnosis". Screening criteria resulted in 17, 16, and 90 studies respectively that were analyzed regarding epidemiology, clinical diagnosis, and radiographic diagnosis of LDH. Using the Delphi method and two rounds of voting at two separate international meetings, ten members of the WFNS (World Federation of Neurosurgical Societies) Spine Committee generated eleven final consensus statements. Results: The lifetime risk for symptomatic LDH is 1-3%; of these, 60-90% resolve spontaneously. Risk factors for LDH include genetic and environmental factors, strenuous activity, and smoking. LDH is more common in males and in 30-50 year olds. A set of clinical tests, including manual muscle testing, sensory testing, Lasegue sign, and crossed Lasegue sign are recommended to diagnose LDH. Magnetic resonance imaging (MRI) is the gold standard for confirming suspected LDH. Conclusions: These eleven final consensus statements provide current, evidence-based guidelines on the epidemiology, clinical diagnosis, and radiographic diagnosis of LDH for practicing spine surgeons worldwide.

Improving synthesis and binding affinities of nucleic acid aptamers and their therapeutics and diagnostic applications.

Nucleic acid aptamers have captivated the attention of analytical and medicinal scientists globally due to their several advantages as recognition molecules over conventional antibodies because of their small size, simple and inexpensive synthesis, broad target range, and high stability in varied environmental conditions. These recognition molecules can be chemically modified to make them resistant to nuclease action in blood serum, reduce rapid renel clearance, improve the target affinity and selectivity, and make them amenable to chemically conjugate with a support system that facilitates their selective applications. This review focuses on the development of efficient aptamer candidates and their application in clinical diagnosis and therapeutic applications. Significant advances have been made in aptamer-based diagnosis of infectious and non-infectious diseases. Collaterally, the progress made in therapeutic applications of aptamers is encouraging, as evident from their use in diagnosing cancer, neurodegenerative diseases, microbial infection, and in imaging. This review also updates the progress on clinical trials of many aptamer-based products of commercial interests. The key development and critical issues on the subject have been summarized in the concluding remarks.

Machine Learning Techniques for Canine Myxomatous Mitral Valve Disease Classification: Integrating Anamnesis, Quality of Life Survey, and Physical Examination.

Myxomatous mitral valve disease (MMVD) is a prevalent canine cardiac disease typically diagnosed and classified using echocardiography. However, accessibility to this technique can be limited in first-opinion clinics. This study aimed to determine if machine learning techniques can classify MMVD according to the ACVIM classification (B1, B2, C, and D) through a structured anamnesis, quality of life survey, and physical examination. This report encompassed 23 veterinary hospitals and assessed 1011 dogs for MMVD using the FETCH-Q quality of life survey, clinical history, physical examination, and basic echocardiography. Employing a classification tree and a random forest analysis, the complex model accurately identified 96.9% of control group dogs, 49.8% of B1, 62.2% of B2, 77.2% of C, and 7.7% of D cases. To enhance clinical utility, a simplified model grouping B1 and B2 and C and D into categories B and CD improved accuracy rates to 90.8% for stage B, 73.4% for stages CD, and 93.8% for the control group. In conclusion, the current machine-learning technique was able to stage healthy dogs and dogs with MMVD classified into stages B and CD in the majority of dogs using quality of life surveys, medical history, and physical examinations. However, the technique faces difficulties differentiating between stages B1 and B2 and determining between advanced stages of the disease.

Nucleic Acid and Nanomaterial Synergistic Amplification Enables Dual Targets of Ultrasensitive Fluorescence Quantification to Improve the Efficacy of Clinical Tuberculosis Diagnosis.

Interferon-γ (IFN-γ) release assays (IGRAs) are constrained by the limited diagnostic performance of a single indicator and the excessive Mycobacterium tuberculosis (Mtb) antigen stimulation time. This study presents a simultaneous, homogeneous, rapid, and ultrasensitive fluorescence quantification strategy for IFN-γ and IFN-γ-induced protein 10 (IP-10). This method relies on the high-affinity binding of aptamers to IFN-γ and IP-10, the enzyme-free catalytic hairpin assembly reaction, and the heightened sensitivity of CdTe quantum dots to Ag+ and hairpin structure C-Ag+-C and carbon dots to Hg2+ and hairpin structure T-Hg2+-T. Under optimized conditions, the selectivity of IFN-γ and IP-10 was excellent, with a linear range spanning from 1 to 100 ag/mL and low limits of detection of 0.3 and 0.5 ag/mL, respectively. Clinical practicality was confirmed through testing of 57 clinical samples. The dual-indicator combination detection showed 92.8% specificity and 93.1% sensitivity, with an area under the curve of 0.899, representing an improvement over the single-indicator approach. The Mtb antigen stimulation time was reduced to 8 h for 6/7 clinical samples. These findings underscore the potential of our approach to enhance the efficiency and performance of a tuberculosis (TB) clinical diagnosis.

Improving preliminary clinical diagnosis accuracy through knowledge filtering techniques in consultation dialogues.

BACKGROUND AND OBJECTIVE: Symptom descriptions by ordinary people are often inaccurate or vague when seeking medical advice, which often leads to inaccurate preliminary clinical diagnoses. To address this issue, we propose a deep learning model named the knowledgeable diagnostic transformer (KDT) for the natural language processing (NLP)-based preliminary clinical diagnoses. METHODS: The KDT extracts symptom-disease relation triples (h,r,t) from patient symptom descriptions by using a proposed bipartite medical knowledge graph (bMKG). To avoid too many relation triples causing the knowledge noise issue, we propose a knowledge inclusion-exclusion approach (KIA) to eliminate undesirable triples (a knowledge filtering layer). Next, we combine token embedding techniques with the transformer model to predict the diseases that patients may encounter. RESULTS: To train the KDT, a medical diagnosis question-answering dataset (named MDQA dataset) containing large-scale, high-quality questions (patient syndrome description) and answering (diagnosis) corpora with 2.6M entries (1.07GB in size) in Mandarin was built. We also train the KDT with the National Institutes of Health (NIH) English dataset (MedQuAD). The KDT marks a transformative approach by achieving a remarkable accuracy of 99% for different evaluation metrics when compared with the baseline transformers used for the NLP-based preliminary clinical diagnoses approaches. CONCLUSIONS: In essence, our study not only demonstrates the effectiveness of the KDT in enhancing diagnostic precision but also underscores its potential to revolutionize the field of preliminary clinical diagnoses. By harnessing the power of knowledge-based approaches and advanced NLP techniques, we have paved the way for more accurate and reliable diagnoses, ultimately benefiting both healthcare providers and patients. The KDT has the potential to significantly reduce misdiagnoses and improve patient outcomes, marking a pivotal advancement in the realm of medical diagnostics.

Construction of a label-free fluorescent biosensor for homogeneous detection of m6A eraser FTO in breast cancer tissues.

Fat mass and obesity-associated protein (FTO) is a crucial eraser of RNA N6- methyladenosine (m6A) modification, and abnormal FTO expression level is implicated in pathogenesis of numerous cancers. Herein, we demonstrate the construction of a label-free fluorescent biosensor for homogeneous detection of m6A eraser FTO in breast cancer tissues. When FTO is present, it specifically erases the methyl group in m6A, inducing the cleavage of demethylated DNA by endonuclease DpnII and the generation of a single-stranded DNA (ssDNA) with a 3'-hydroxyl group. Subsequently, terminal deoxynucleotidyl transferase (TdT) promotes the incorporation of dTTPs into the ssDNA to obtain a long polythymidine (T) DNA sequence. The resultant long poly (T) DNA sequence can act as a template to trigger hyperbranched strand displacement amplification (HSDA), yielding numerous DNA fragments that may be stained by SYBR Gold to produce an enhanced fluorescence signal. This biosensor processes ultrahigh sensitivity with a detection limit of 1.65 × 10-10 mg/mL (2.6 fM), and it can detect the FTO activity in a single MCF-7 cell. Moreover, this biosensor can screen the FTO inhibitors, evaluate enzyme kinetic parameters, and discriminate the FTO expression levels in the tissues of breast cancer patients and healthy persons.

Clinical Diagnosis and Laboratory Testing of Abnormal Appearing Toenails: A Retrospective Assessment of Confirmatory Testing for Onychomycosis in the United States, 2022-2023.

Onychomycosis is an under-recognized healthcare burden. Despite the risk of misdiagnosis, confirmatory laboratory testing is under-utilized. Histopathologic examination with polymerase chain reaction (PCR) is currently the most effective diagnostic method; it offers direct detection and identification of a fungal invasion. In this retrospective cohort study, we assessed confirmatory testing results, with matching clinical diagnoses, in 96,293 nail specimens submitted during a 9-month period from 2022 to 2023. Toenail specimens were examined using fungal culture, histopathology and/or PCR. Clinical diagnoses were identified using the International Classification of Diseases 10th Revision codes. For clinically diagnosed onychomycosis patients, the overall positivity rate was 59.4%; a similar positivity rate (59.5%) was found in patients with clinically diagnosed non-fungal nail dystrophy. Performing a histopathologic examination with PCR was more likely to provide pathogen identification results than using fungal culture. Male patients had a higher rate of onychomycosis overall; however, female patients had more non-dermatophyte mold onychomycosis caused by Aspergillus. Clinically diagnosed onychomycosis patients with a co-diagnosis of tinea pedis were more likely to test positive for onychomycosis by PCR (odds ratio [OR]: 4.2; 95% confidence interval [CI]: 2.7-6.4), histopathology (OR: 2.5; 95% CI: 2.0-3.1) and fungal culture (OR: 3.2; 95% CI: 1.5-6.6). Our results support the use of confirmatory laboratory testing when there is a clinical diagnosis of onychomycosis.

Smartphone-Based Free-to-Total Prostate Specific Antigen Ratio Detection System Using a Colorimetric Reaction Integrated with Proximity-Induced Bio-Barcode and CRISPR/Cas12a Assay.

The free-to-total prostate-specific antigen (f/t-PSA) ratio is of great significance in the accurate diagnosis of prostate cancer. Herein, a smartphone-based detection system is reported using a colorimetric reaction integrated with proximity-induced bio-barcode and the clustered regularly interspaced short palindromic repeats (CRISPR)/Cas12a assay for f/t-PSA ratio detection. DNA/antibody recognition probes are designed to bind f-PSA or t-PSA and induce the release of the DNA bio-barcode. The CRISPR/Cas12a system is activated by the DNA bio-barcode to release Ag+ from the C-Ag+-C structure of the hairpin DNA. The released Ag+ is used to affect the tetramethylbenzidine (TMB)-H2O2-based colorimetric reaction catalyzed by Pt nanoparticles (NPs), as the peroxidase-like activity of the Pt NPs can be efficiently inhibited by Ag+. A smartphone with a self-developed app is used as an image reader and analyzer to analyze the colorimetric reaction and provide the results. A limit of detection of 0.06 and 0.04 ng mL-1 is achieved for t-PSA and f-PSA, respectively. The smartphone-based method showed a linear response between 0.1 and 100 ng mL-1 of t-PSA or f-PSA. In tests with clinical samples, the smartphone-based method successfully diagnosed prostate cancer patients from benign prostatic hyperplasia patients and healthy cases with high sensitivity and specificity.

Electrochemical peptide-based biosensor for the detection of the inflammatory disease biomarker, interleukin-1beta.

This paper reports the development of a highly sensitive and selective electrochemical peptide-based biosensor for the detection of the inflammatory disease biomarker, interleukin-1beta (IL-1ß). To this end, flower-like Au-Ag@MoS2-rGO nanocomposites were used as the signal amplification platform to achieve a label-free biosensor with a high sensitivity and selectivity. First, a high-affinity peptide for IL-1ß was identified through biopanning with M13 random peptide libraries, and was newly designed by incorporating cysteine at the C-terminus. An IL-1ß specific binding peptide was used as the bio-receptor, and the interaction between the IL-1ß binding peptide and IL-1ß was confirmed via enzyme-linked immunosorbent assay and various physicochemical and electrochemical analyses. Under optimal conditions, the biosensor achieved an ultrasensitive and specific IL-1ß detection in a wide linear concentration range of 0-250 ng/mL with a picomolar-level detection limit (∼2.4 pM), low binding constant (∼0.62 pM), and a low coefficient of variation (<1.65 %). The biosensor was successfully utilized for IL-1ß determination in the serum of Crohn's disease patients with a good correlation coefficient. In addition, the detection performance was comparable to that of commercially available IL-1ß ELISA kit. This indicates that the electrochemical peptide-based biosensor may offer a potentially valuable platform for the clinical diagnosis of various inflammatory disease biomarkers.