Search

Summary: Gelatine is obtained from the hydrolysis of collagen in bones, skin, fins, fish scales and insect bodies of cattle, pigs, camels, poultry, fish and insects. Consequently, the diversity and availability of gelatine sources, along with gelatine authentication, are concerns for those consuming gelatine products from religious, health and economic perspectives. Therefore, rapid and reliable protein‐ or DNA‐based detection methods have been developed for gelatine authentication. This review discusses and evaluates biosensor methods, comparing them with various analytical methods in terms of their popularity and precision. Additionally, the development of biosensor methods has been explored to identify a reference for a rapid, accurate, portable and simple method for gelatine detection with a low detection limit and high specificity. [ABSTRACT FROM AUTHOR]

Despite recent therapeutic advancements, outcomes for advanced hepatocellular carcinoma (HCC) remain unsatisfactory, highlighting the need for novel treatments. The CRISPR (Clustered Regularly Interspaced Short Palindromic Repeats) gene-editing technology offers innovative treatment approaches, involving genetic manipulation of either cancer cells or adoptive T cells to combat HCC. This review comprehensively assesses the applications of CRISPR systems in HCC treatment, focusing on in vivo targeting of cancer cells and the development of chimeric antigen receptor (CAR) T cells and T cell receptor (TCR)-engineered T cells. We explore potential synergies between CRISPR-based cancer therapeutics and existing treatment options, discussing ongoing clinical trials and the role of CRISPR technology in improving HCC treatment outcomes with advanced safety measures. In summary, this review provides insights into the promising prospects and current challenges of using CRISPR technology in HCC treatment, with the ultimate goal of improving patient outcomes and revolutionizing the landscape of HCC therapeutics. [ABSTRACT FROM AUTHOR]

Coronaviridae family consists of many virulent viruses with zoonotic properties that can be transmitted from animals to humans. Different strains of these viruses have caused pandemic in the past such as Severe Respiratory Syndrome Coronavirus (SARS-CoV) in 2002, Middle East respiratory syndrome coronavirus (MERS-CoV) in 2012 and recently Severe Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) also known as COVID-19 in December 2019. Scientists utilised different approaches for the detection and characterisation of CoVs using samples such as serum, throat swabs, nose swabs, nasopharyngeal aspirates and bronchoalveolar lavages. The two common approaches include antigen-based approach and molecular diagnostic approach, which are hindered by limitations such as low sensitivity and requirement for high level of biosafety during isolation of the virus from cell culture. Thus, there is a need for developing a more rapid, sensitive, simple and cheap diagnostic kit for diagnosis of different strains of coronavirus. In this article, we overview 2019 novel coronavirus, pandemic, prior epidemics, diagnosis, treatments, identification of drugs detection based on classification and prediction using artificial intelligence-driven tools. We also overview in-lab molecular testing and on-site testing using CRISPR-based biosensing tools. We also outline limitations of laboratory techniques and open-research issues in the current state of CRISPR-based biosensing applications and artificial intelligence for treatment of Coronaviruses. [ABSTRACT FROM AUTHOR]

Reverse‐Transcription Polymerase Chain Reaction (RT‐PCR) method is currently the gold standard method for detection of viral strains in human samples, but this technique is very expensive, take time and often leads to misdiagnosis. The recent outbreak of COVID‐19 has led scientists to explore other options such as the use of artificial intelligence driven tools as an alternative or a confirmatory approach for detection of viral pneumonia. In this paper, we utilized a Convolutional Neural Network (CNN) approach to detect viral pneumonia in x‐ray images using a pretrained AlexNet model thereby adopting a transfer learning approach. The dataset used for the study was obtained in the form of optical Coherence Tomography and chest X‐ray images made available by Kermany et al. (2018, https://doi.org/10.17632/rscbjbr9sj.3) with a total number of 5853 pneumonia (positive) and normal (negative) images. To evaluate the average efficiency of the model, the dataset was split into on 50:50, 60:40, 70:30, 80:20 and 90:10 for training and testing respectively. To evaluate the performance of the model, 10 K Cross‐validation was carried out. The performance of the model using overall dataset was compared with the means of cross‐validation and the currents state of arts. The classification model has shown high performance in terms of accuracy, sensitivity and specificity. 70:30 split performed better compare to other splits with accuracy of 98.73%, sensitivity of 98.59% and specificity of 99.84%. [ABSTRACT FROM AUTHOR]

A general purpose enzyme-based amperometric electrochemical genosensor assay was developed wherein polymerase chain reaction (PCR) amplicons labeled with both biotin and fluorescein were detected with peroxidase-conjugated antifluorescein antibody on a screen-printed carbon electrode (SPCE). As a proof of principle, the response selectivity of the genosensor was evaluated using PCR amplicons derived from lolB gene of Vibrio cholerae. Factors affecting immobilization, hybridization, and nonspecific binding were optimized to maximize sensitivity and reduce assay time. On the basis of the background amperometry signals obtained from nonspecific organisms and positive signals obtained from known V. cholerae, a threshold point of 4.20 [micro]A signal was determined as positive. Under the optimum conditions, the limit of detection (LOD) of the assay was 10 CFU/mL of V. cholerae. The overall precision of this assay was good, with the coefficient of variation (CV) being 3.7% using SPCE and intermittent pulse amperometry (IPA) as an electrochemical technique. The assay is sensitive, safe, and cost-effective when compared to conventional agarose gel electrophoresis, real-time PCR, and other enzyme-linked assays for the detection of PCR amplicons. Furthermore, the use of a hand-held portable reader makes it suitable for use in the field.

Psychiatric disorders are common and complex diseases that show polygenic and multifactorial heredity. A single nucleotide polymorphism (Val108/158Met) in the catechol-O-methyl transferase (COMT) gene is related to many psychiatric disorders such as schizophrenia, alcoholism, bipolar disorder, and obsessive-compulsive disorder. Schizophrenia is a complex disorder and a single nucleotide polymorphism (Val108/158Met) at the COMT gene is related to schizophrenia susceptibility. A novel hybridization-based disposable electrochemical DNA biosensor for the detection of a common functional polymorphism in the COMT gene from polymerase chain reaction (PCR) amplicons has been described without using an external label. This developed technology combined with a disposable carbon graphite electrode and differential pulse voltammetry was performed by using short synthetic oligonucleotides and PCR amplicons in length 203 bp to measure the change of guanine oxidation signal obtained at ~+1.0 V after DNA hybridization between probe and target (synthetic target or denatured PCR samples). COMT-specific oligonucleotides were immobilized onto the carbon surface with a simple adsorption method in two different modes: (a) Guanine-containing targets were attached or (b) inosine-substituted probes were attached onto an electrode. By controlling the surface coverage of the target DNA, the hybridization event between the probes and their synthetic targets or specific PCR products was optimized. The wild-type or polymorphic allele-specific probes/targets were also interacted with an equal amount of noncomplementary and one-base mismatch-containing DNAs in order to measure the sensor selectivity. The decrease or appearance in the intrinsic guanine signal simplified the detection procedure and shortened the assay time because protocol eliminates the label-binding step. The nonspecific binding effects were minimized by using sodium dodecyl sulfate with different washing methods. The Va1108/158Met COMT genotype detection were performed with real samples containing wild-type (healthy controls), polymorphic (mutant type), and heterozygous PCR products. The detection limit (S/N = 3) of the biosensor was 2.44 pmol of target sequence in the 30-[micro]L samples. Analytical performance of the sensor is described, along with future prospects.

Telomerase is an important biomarker for cancer cells and its activation in 85% of all cancer types confers a clinical diagnostic value. A label-free electrochemical assay based on guanine oxidation signal to measure telomerase activity is described. This developed technology combined with a disposable sensor, carbon graphite electrode (CGE), and differential pulse voltammetry (DPV) was performed by using PCR amplicons with/without telomeric repeats as the guanine oxidation signal observed at + 1.0 V measured after the immobilization of PCR products. Guanine oxidation signal was chosen as a measure of telomerase activity because a substantial increase in the number of guanines was introduced by the action of telomerase which adds hexameric repeats [(TTAGGG).sub.n] that contain 50% guanine. The developed assay was shown to specifically measure telomerase activity from cell extracts, and elongation rates increased linearly in a concentration dependent manner. Telomerase activity could be detected in cell extracts containing as low as 100 ng/[micro]L of protein. All of the electrochemical measurements were also confirmed with the conventional TRAP-silver staining assay. Rapidity, simplicity, and the label-free nature of the developed assay make it suitable for practical use in quantitative determination of telomerase activity from clinical samples for diagnosis of cancer.