Multi-target Analysis Research Articles

Docking Score ML: Target-Specific Machine Learning Models Improving Docking-Based Virtual Screening in 155 Targets.

In drug discovery, molecular docking methods face challenges in accurately predicting energy. Scoring functions used in molecular docking often fail to simulate complex protein-ligand interactions fully and accurately leading to biases and inaccuracies in virtual screening and target predictions. We introduce the "Docking Score ML", developed from an analysis of over 200,000 docked complexes from 155 known targets for cancer treatments. The scoring functions used are founded on bioactivity data sourced from ChEMBL and have been fine-tuned using both supervised machine learning and deep learning techniques. We validated our approach extensively using multiple data sets such as validation of selectivity mechanism, the DUDE, DUD-AD, and LIT-PCBA data sets, and performed a multitarget analysis on drugs like sunitinib. To enhance prediction accuracy, feature fusion techniques were explored. By merging the capabilities of the Graph Convolutional Network (GCN) with multiple docking functions, our results indicated a clear superiority of our methodologies over conventional approaches. These advantages demonstrate that Docking Score ML is an efficient and accurate tool for virtual screening and reverse docking.

Development, Validation, and Implementation of an Augmented Multiwell, Multitarget Quantitative PCR for the Analysis of Human Papillomavirus Genotyping through Software Automation, Data Science, and Artificial Intelligence

The value of HPV testing for cervical cancer screening is well established, where its use as primary screening option or as reflex test after atypical cytology results has recently gained wide acceptance. The importance of full genotyping and viral load determination has been demonstrated to enhance the clinical understanding of the viral infection progression during follow-up or after treatment, thereby providing clinicians with supplementary tools for optimized patient management.In this study a new analysis method for the RIATOL quantitative PCR assay was developed, validated and implemented in the laboratory of clinical molecular pathology at A.M.L. (Sonic Healthcare, Belgium), under national accreditation and following the international ISO guidelines. It presents the successful validation of a high throughput, multi-target HPV analysis method, with enhanced accuracy on both qualitative and quantitative end-results. This is achieved by software standardization and automation of PCR curve analysis and interpretation, using data science and artificial intelligence (DS/AI). Moreover, the user-centric functionality of the platform was demonstrated to enhance both staff training and routine analysis workflows, thereby saving time and laboratory personnel resources.Overall, the integration of the FastFinder plugin semi-automatic analysis algorithm with the RIATOL qPCR assay proved to be a remarkable advancement in high throughput HPV quantification, with demonstrated capability to provide highly accurate clinical-grade results and to reduce manual variability and analysis time.

The Development of an Isotope Dilution Mass Spectrometry Method for Interleukin-6 Quantification.

Inflammatory responses and tumor developments are closely related, with interleukin-6 (IL-6) playing important roles in both processes. IL-6 has been extensively identified as a potential tumor biomarker. This study developed an isotope dilution mass spectrometry (IDMS) method for quantifying IL-6 based on signature peptides. These peptides were screened by excluding those with missed cleavage or post-translational modification. The method's accuracy was verified using amino acid-based IDMS, in which purified IL-6 protein samples were quantified after hydrolyzing them into amino acids, and no significant difference was observed (p-value < 0.05). The method demonstrated good linearity and sensitivity upon testing. The specificity and matrix effect of the method were verified, and a precision study showed that the coefficient of variation was less than 5% for both the intra-day and inter-day tests. Compared to immunoassays, this method offers distinct advantages, such as the facilitation of multi-target analysis. Furthermore, the peptides used in this study are much more convenient for storage and operation than the antibodies or purified proteins typically used in immunoassays.

Individual- vs. Multiple-Objective Strategies for Targeted Sentiment Analysis in Finances Using the Spanish MTSA 2023 Corpus

Multitarget sentiment analysis extracts the subjective polarity of text from multiple targets simultaneously in a given context. This approach is useful in finance, where opinions about different entities affect the target differently. Examples of possible targets are other companies and society. However, typical multitarget solutions are resource-intensive due to the need to deploy multiple classification models for each target. An alternative to this is the use of multiobjective training approaches, where a single model is capable of handling multiple targets. In this work, we propose the Spanish MTSACorpus 2023, a novel corpus for multitarget sentiment analysis in finance, and we evaluate its reliability with several large language models for multiobjective training. To this end, we compare three design approaches: (i) a Main Economic Target (MET) detection model based on token classification plus a multiclass classification model for sentiment analysis for each target; (ii) a MET detection model based on token classification but replacing the sentiment analysis models with a multilabel classification model; and (iii) using seq2seq-type models, such as mBART and mT5, to return a response sequence containing the MET and the sentiments of different targets. Based on the computational resources required and the performance obtained, we consider the fine-tuned mBART to be the best approach, with a mean F1 of 80.300%.

Fluorescent Selectivity-Enhanced FRET Based on 3D Photonic Crystals for Multianalyte Sensing.

Fluorescence resonance energy transfer (FRET) finds widespread utility in biochemical sensing, single-molecule experiments, cell physiology, and various other domains due to its inherent simplicity and high sensitivity. Nevertheless, the efficiency of energy transfer between the FRET donor and acceptor is significantly contingent on the local photonic environment, a factor that limits its application in complex systems or multianalyte detections. Here, a fluorescent selectivity-enhanced acridine orange (AO)-aflatoxins (AFs) FRET system based on a range of 3D topological photonic crystals (PCs) was developed with the aim of enhancing the selectivity and discrimination capabilities of FRET. By exploring the angle-dependent characteristics of the photonic stopband, the stopband distribution across different 3D topological PCs pixels was investigated. This approach led to selective fluorescence enhancement in PCs that matched the stopbands, enabling the successful discrimination of six distinct aflatoxins and facilitating complex multianalysis of moldy food samples. In particular, the stopband, which was strategically positioned within the blue-purple structural color range, exhibited a strong alignment with the fluorescence peaks of both the FRET donor and acceptor. This alignment allowed the 3D three-pointed star PCs to be effectively employed for the identification of mixed samples containing six distinct aflatoxins as well as the detection of real aflatoxin samples present in moldy potatoes, bread, oats, and peanuts. Impressively, this approach achieved a remarkable accuracy rate of 100%. This innovative strategy not only presents a novel avenue for developing a multitarget discrimination analysis system but also offers a convenient pretreatment method for the quantitative detection of various aflatoxins.

Recent advances in nonenzymatic electrochemical biosensors for sports biomarkers: focusing on antibodies, aptamers and molecularly imprinted polymers.

Nonenzymatic electrochemical biosensors, renowned for their high sensitivity, multi-target analysis capabilities, and miniaturized integration, align well with the requirements of non-invasive, multi-index integrated, continuous monitoring, and user-friendly wearable biosensors in sports science. In the past three years, novel strategies targeting specific responses to sports biomarkers have opened new avenues for applications in sports science. However, these advancements also pose challenges in achieving adequate sensitivity and specificity for online analysis of complex sweat bio-samples. Our article focuses on three key nonenzymatic electrochemical biosensing strategies: antigen-antibody reactions, nucleic acid aptamer recognition, and molecular imprinting capture. We delve into strategies to enhance specificity and sensitivity in the application of biosensors in sports science, including shortening signal transduction paths through built-in signal probes, increasing reaction sites through increased surface area and the introduction of nanostructures, multi-target analyses, and microfluidic techniques.

The molecular mechanism of "Dahuang-Shengjiang-Banxia decoction" in the treatment of diabetic kidney disease was verified based on network pharmacology and molecular docking

BackgroundExplore the molecular mechanism of Dahuang-Shengjiang-Banxia Decoction (DSBD) in the treatment of diabetic kidney disease (DKD), using network pharmacology and molecular docking technology. MethodThe effective ingredients and targets of the DSBD were taken from the TCMSP database, while the disease targets were obtained via GeneCards, OMIM, DrugBank, TTD, and DisGeNET. Cytoscape 3.9.1 was used to create a drug-ingredient-target network diagram. STRING databases are also used to analyze the Protein-Protein Interaction (PPI) network of intersecting targets. The core targets was obtained by the intersection of the differential genes screened from the intersection target and GEO, and the core targets was enriched by Gene ontology (GO), Kyoto gene and genome (KEGG), and Gene Set Enrichment Analysis (GSEA). CIBERSORTx was used for immunoinfiltration analysis, and then the core targets was analyzed by Nephroseq V5 and KIT for clinical correlation analysis and single-cell sequencing. Lastly, AutoDock Vina was used for molecular docking of both the core targets and the top active elements. ResultsA total of 177 DSBD and 2906 DKD targets were screened. Six core targets were identified by screening, which were IL1B, MMP9, EGF, VEGFA, HIF1A, and PTGS2. The top 6 active ingredients are 6-gingerol, baicalin, oleic acid, β-sitosterol, linolenic acid, and aloe emodin. The core targets has good docking activity with the active ingredient. ConclusionDSBD may exert its therapeutic effect on DKD through multicomponent, multipath, and multi-target analyses. It is possible that VEGFA is a key target in therapy, and that the VEGF/PI3K/AKT signaling pathway plays a key role in therapy.

Integrative multi-target analysis of Urtica dioica for gout arthritis treatment: a network pharmacology and clustering approach.

The online version contains supplementary material available at 10.1007/s40203-024-00254-9.

A metal-phenolic coordination framework nanozyme exhibits dual enzyme mimicking activity and its application is effective for colorimetric detection of biomolecules.

Biomolecules play vital roles in many biological processes and diseases, making their identification crucial. Herein, we present a colorimetric sensing method for detecting biomolecules like cysteine (Cys), homocysteine (Hcy), and glutathione (GSH). This approach is based on a reaction system whereby colorless 3,3',5,5'-tetramethylbenzidine (TMB) undergoes catalytic oxidation to form blue-colored oxidized TMB (ox-TMB) in the presence of hydrogen peroxide (H2O2), utilizing the peroxidase and catalase-mimicking activities of metal-phenolic coordination frameworks (MPNs) of Cu-TA, Co-TA, and Fe-TA nanospheres. The Fe-TA nanospheres demonstrated superior activity, more active sites and enhanced electron transport. Under optimal conditions, the Fe-TA nanospheres were used for the detection of biomolecules. When present, biomolecules inhibit the reaction between TMB and H2O2, causing various colorimetric responses at low detection limits of 0.382, 0.776 and 0.750 μM for Cys, Hcy and GSH. Furthermore, it was successfully applied to real water samples with good recovery results. The developed sensor not only offers a rapid, portable, and user-friendly technique for multi-target analysis of biomolecules at low concentrations but also expands the potential uses of MPNs for other targets in the environmental field.

Programmable Gravity Self-Driven Microfluidic Chip for Point-of-Care Multiplied Immunoassays.

Point-of-care testing (POCT) is experiencing a groundbreaking transformation with microfluidic chips, which offer precise fluid control and manipulation at the microscale. Nevertheless, chip design or operation for existing platforms is rather cumbersome, with some even heavily depending on external drivers or devices, impeding their broader utilization. This study develops a unique programmable gravity self-driven microfluidic chip (PGSMC) capable of simultaneous multi-reagent sequential release, multi-target analysis, and multi-chip operation. All necessary reagents are introduced in a single step, and the process is initiated simply by flipping the PGSMC vertically, eliminating the need for additional steps or devices. Additionally, it demonstrates successful immunoassays in less than 60 min for antinuclear antibodies testing, compared to more than 120 min by traditional methods. Assessment using 25 clinically diagnosed cases showcases remarkable sensitivity (96%), specificity (100%), and accuracy (99%). These outcomes underscored its potential as a promising platform for POCT with high accuracy, speed, and reliability, highlighting its capability for automated fluid control.

Dual-color MoS2@QD nanosheets mediated dual-mode lateral flow immunoassay for flexible and ultrasensitive detection of multiple drug residues

The sensitive on-site monitoring of multiple agricultural drugs in complex real media is critical to human health but remains a challenge. In this paper, we reported the design of film-like dual-mode nanolabel (MTQD), using molybdenum disulfide (MoS2) nanosheet-loaded numerous quantum dots (QDs) to generated co-enhanced colorimetric-fluorescence signals, and demonstrated its powerful capabilities in competitive lateral flow immunoassay (LFA) for flexible, ultrasensitive, and multiplex detection of four kinds of common agricultural drugs. Three layers of red and green QDs were continuously coated onto the surface of MoS2 to suppress the inner filter effect of two-dimensional nanomaterials effectively and greatly improve the specificity of the LFA system for multitarget analysis. The dual-mode LFA combined with a low-cost dual-fluorescence reading instrument can flexibly and simultaneously monitor two pesticides (clothianidin, carbendazim) and two veterinary drugs (kanamycin, chloramphenicol) in complex food and experimental samples with low detection limits of 0.1 ng/mL level in the observation of colorimetric signals and showed at least a 46-fold improvement in sensitivity in the sensing of fluorescence signals. This colorimetric dual-fluorescence platform greatly broadens the application range of existing LFA techniques without increasing testing time, thus showing great application prospects for the point-of-care testing of small-molecule pollutants in different situations.

Characterization of antigen presentation capability for neoantigen-based products using targeted LC-MS/MS method

The generation of an immune response in neoantigen-based products relies on antigen presentation, which is closely analyzed by bioassays for T-cell functions such as tetramer or cytokine release. Mass spectrometry (MS) has the potential to directly assess the antigen-presenting capability of antigen-presenting cells (APCs), offering advantages such as speed, multi-target analysis, robustness, and ease of transferability. However, it has not been used for quality control of these products due to challenges in sensitivity, including the number of cells and peptide diversity. In this study, we describe the development and validation of an improved targeted LC-MS/MS method with high sensitivity for characterizing antigen presentation, which could be applied in the quality control of neoantigen-based products. The parameters for the extraction were carefully optimized by different short peptides. Highly sensitive targeted triple quadrupole mass spectrometry combined with ultra-high performance liquid chromatography (UHPLC) was employed using a selective ion monitoring mode (Multiple Reaction Monitoring, MRM). Besides, we successfully implemented robust quality control peptides to ensure the reliability and consistency of this method, which proved invaluable for different APCs. With reference to the guidelines from ICH Q2 (R2), M10, as well as considering the specific attributes of the product itself, we validated the method for selectivity, specificity, sensitivity, limit of detection (LOD), recovery rate, matrix effect, repeatability, and application in dendritic cells (DCs) associated with neoantigen-based products. The validation process yields satisfactory results. Combining this approach with T cell assays will comprehensively assess cell product quality attributes from physicochemical and biological perspectives.

Evaluating membrane bioreactor treatment for the elimination of emerging contaminants using different analytical methods

Since wastewater treatment plants (WWTPs) were not originally designed to eliminate contaminants of emerging concern (CECs), alternative strategies like membrane bioreactor (MBR) technology are gaining importance in achieving effective CEC removal and minimising their environmental impact. In this study, composite wastewater samples were collected from the biggest WWTP in the Basque Country (Galindo, Biscay) and the performance of two secondary treatments (i.e. conventional activated sludge treatment, CAS, and MBR) was assessed. The combination of a suspect screening approach using liquid chromatography tandem high-resolution mass spectrometry (LC-HRMS) and multitarget analysis by gas chromatography-mass spectrometry (GC-MS) allowed the detection of approximately 200 compounds in the WWTP effluents. The estimated removal efficiencies (REs) revealed that only 16 micropollutants exhibited enhanced removal by MBR treatment (RE > 70% or 40 – 60%). The environmental risk posed by the non-eliminated compounds after both treatments remained similar, being anthracene, clarithromycin, bis(2-ethylhexyl) phthalate (DEHP) and dilantin the most concerning pollutants (RQ > 1). The Microtox® bioassay confirmed the MBR’s efficiency in removing baseline toxicity, while suggesting a similar performance of CAS treatment. These minimal differences between treatments call into question the worthiness of MBR treatment and emphasise the need to seek more efficient alternative treatment methods.

Multi-target photothermal immunochromatography for simultaneous detection of three mycotoxins in foods

BackgroundMycotoxin contaminated food poses a threat to human health. On-site detection of mycotoxin contamination is of significance to reduce the agricultural and food industries loss. Lateral flow immunochromatography (LFIC) as on-site detection method for mycotoxins has the advantages of low cost, easy to operate and short time-consuming. Of the various types of LFIC, photothermal LFIC possesses better sensitivity and stronger quantitative capability, but is unable to conduct synchronous multi-target analysis because that the laser can only activate one test area at a time. It was clear that a synchronous multi-target photothermal LFIC method was needed. ResultsIn this study, a photothermal LFIC method for the simultaneous detection of three mycotoxins, deoxynivalenol (DON), aflatoxin B1 (AFB1) and zearalenone (ZEN), was developed. We broadened the laser source with a beam expander and realized the irradiation and activation of three test zones simultaneously. In addition, the competitive photothermal LFIC was constructed by using Cu2-xSe-Au nanocomposites with excellent photothermal properties (η = 87.47%) as photothermal signal probes and thermal imager as photothermal signal collector. Under optimized experimental conditions, the limits of detection (LOD) were 73 ng L−1, 45 ng L−1 and 43 ng L−1 for DON, AFB1 and ZEN, respectively. The method had good linearity in three orders of magnitude and good specificity. The recoveries of the three mycotoxins in oat, cornmeal and millet samples ranged from 78.6% to 112.4%. SignificanceCompared with previous studies, this method improved the sensitivity, broadened the linear range of detection without large equipment and realized synchronous multi-target analysis for DON, AFB1 and ZEN. We addressed a key limitation of photothermal LFIC by a simple way, facilitating the application of this technique in multi-target on-site detection in wider fields.

Multitarget and suspect screening of antimicrobials in soil and manure by means of QuEChERS — liquid chromatography tandem mass spectrometry

The present work aimed to develop an accurate analytical method for the simultaneous analysis of twenty-four antimicrobials in soil:compost and animal manure samples by means of ultra-high performance liquid chromatography coupled to a triple-quadrupole mass spectrometer (UHPLC-QqQ). For this purpose, the effectiveness of two extraction techniques (i.e. focused ultrasound solid–liquid extraction (FUSLE) and QuEChERS (quick, easy, cheap, effective, rugged and safe)) was evaluated, and the clean-up step using solid-phase extraction (SPE) was also thoroughly studied. The method was successfully validated at 10 μg·kg−1, 25 μg·kg−1, and 50 μg·kg−1 showing adequate trueness (70–130%) and repeatability (RSD < 30%), with few exceptions. Procedural limits of quantification (LOQPRO) were determined for soil:compost (0.45 to 7.50 μg·kg−1) and manure (0.31 to 5.53 μg·kg−1) samples. Pefloxacin could not be validated at the lowest level since LOQPRO ≥ 10 μg·kg−1. Sulfamethazine (7.9 ± 0.8 µg·kg−1), danofloxacin (27.1 ± 1.4 µg·kg−1) and trimethoprim (4.9 ± 0.5 µg·kg−1) were detected in soil samples; and tetracycline (56.8 ± 2.8 µg·kg−1), among other antimicrobials, in the plants grown on the surface of the studied soil samples. Similarly, sulfonamides (SAs), tetracyclines (TCs) and fluoroquinolones (FQs) were detected in sheep manure in a range of 1.7 ± 0.3 to 93.3 ± 6.8 µg·kg−1. Soil and manure samples were also analysed through UHPLC coupled to a high-resolution mass-spectrometer (UHPLC-qOrbitrap) in order to extend the multitarget method to suspect screening of more than 22,281 suspects. A specific transformation product (TP) of sulfamethazine (formyl-sulfamethazine) was annotated at 2a level in manure samples, among others. This work contributes to the efforts that have been made in the last decade to develop analytical methods that allow multitarget analysis of a wide variety of antimicrobials, including TPs, which is a complex task due to the diverse physicochemical properties of the antimicrobials.

Optimization and validation of an extraction method for the analysis of multi-class emerging contaminants in soil and sediment

Analytical methods for the determination of multi-class emerging contaminants are limited for soil and sediment while they are essential to provide a more complete picture of their distribution in the environment and to understand their fate in different environmental compartments. In this paper, we present the development and optimization of an analytical strategy that combines reliable extraction, purification and the analysis using ultra-pressure liquid chromatography triple quadrupole mass spectrometry (UPLC-MS/MS) of 90 emerging organic contaminants including pesticides, pharmaceuticals and personal care products, flame retardants, per- and polyfluoroalkyl substances (PFASs) and plasticizers in soil and sediment. To extract a wide range of chemicals, the extraction strategy is based on the QuEChERS (Quick, Easy, Cheap, Effective, Rugged and Safe) approach. A number of different options were investigated (buffer, acidification, addition of EDTA, different types and combinations of dispersive SPE etc.) and the effectiveness of the chemical extraction procedure and the clean-up was assessed for two matrices: soil (organic matter content of 9%) and sediment (organic matter content of 1.9%). The method was fully validated for both matrices, in terms of accuracy, linearity, repeatability (intra-day), reproducibility (inter-day), method limits of detection and quantification (LODs and MLOQs, respectively). The final performance showed good accuracy and precision (mean recoveries were between 70 and 120% with relative standard deviations (RSD) less than 20% in most cases), low matrix effects, good linearity for the matrix-matched calibration curve (R2≥0.991) and MLOQs ranged from 0.25 and 10 µg/kg. To demonstrate the applicability and suitability of the validated method, soil and sediment samples from Vietnam, France, Sweden and Mexico were analyzed. The results showed that of the 90 target compounds, a total of 33 were quantified in the sediment and soil samples analyzed. In addition to multi-target analysis, this strategy could be suitable for non-target screening, to provide a more comprehensive view of the contaminants present in the samples.

Drug repurposing: databases and pipelines.

The concept of drug repurposing is focused on the repositioning of drug molecules that have already undergone safety trials. There are different strategies for drug repurposing. Network-based strategy focuses on the evaluation of drug combinations in a molecular environment with multi-target hits and analysis of drug interactions. Implementation of any in silico strategy requires several databases and pipelines for executing the process of shortlisting appropriate drugs.

Multicompartmental Hydrogel Microspheres as a Tool for Multicomponent Analysis.

Developing advanced tools for multicomponent analysis is an open challenge in engineering and life science. Herein, multicompartmental hydrogel microspheres with multi-material compatibility and structural scalability are developed as a tool for multicomponent analysis at a single-particle level. Microfluidic technology endows particles with adjustable sizes and super-segmented layouts that can be used to load various analyte probes. In order to perform multicomponent analysis, these microspheres are structurally divided into identifier regions for indicating reading direction and analyte regions for detecting target molecules. The multiplex detection ability of these particles is demonstrated in microRNA bioassays with high specificity and sensitivity. The multi-target analysis is performed on a single-particle level, and the bioassay is free of conventional labeling interference. We expect these particles to reach their potential in clinical diagnostics.

Network pharmacology and multitarget analysis of Nigella sativa in the management of diabetes and obesity: a computational study

Obesity and diabetes are commonly associated with one another and represent a significant global health issue, with a recent surge in disease incidence. Nigella sativa, also known as black cumin, is believed to possess several health benefits, including anti-diabetic, anticancer, antioxidant, antimicrobial, and anti-obesity properties. In this study, we aimed to identify the active compounds derived from N. sativa, which can potentially inhibit key protein targets and signaling pathways associated with diabesity treatment. We employed an exhaustive in silico search, which led to the identification of 22 potential compounds. Out of these, only five hits were found to be non-toxic, including Arabic and ascorbic acids, dihydrocodeine, catechin, and kaempferol. Our analysis revealed that these hits were associated with genes such as AKT1, IL6, SRC, and EGFR. Finally, we conducted molecular docking and molecular dynamics simulations, which identified kaempferol as the best binder for AKT1 in comparison to the reference molecule. Overall, our in silico integrated pipeline provides a useful approach to identify non-toxic phytocompounds as promising drug candidates to treat diabetes and obesity. Communicated by Ramaswamy H. Sarma

Combining multisite functionalized magnetic nanomaterials with interference-free SERS nanotags for multi-target sepsis biomarker detection

Surface-enhanced Raman scattering (SERS) is an ultra-sensitive vibration spectroscopy technology, with the advantages of multi-index and non-destructive quantitative detection, has attracted much attention in the joint detection of biomarkers. A novel SERS biosensor with multisite capture and interference-free quantification was designed for the joint detection of the sepsis biomarker interleukin-6 (IL-6) and procalcitonin (PCT). This biosensor had two interference-free core-shell SERS probes with highly efficient electromagnetic enhancement and a multisite functionalized magnetic nanomaterial with high adsorption capacity. They formed sandwich structure with the targets through boronic affinity and immunoreaction, and the multi-target quantitative analysis of biomarkers in serum was performed using a portable Raman spectrometer in the Raman-silent region. The SERS biosensor was exhibited highly sensitive with detection limits of 0.584 and 2.99 pg/mL for IL-6 and PCT, respectively. In addition, it exhibited excellent selectivity and specificity even with the interference of other proteins. As this SERS method showed excellent performance in the detection of sepsis, it has great potential for multi-index detection in clinical diagnosis of major diseases.