Rapid and Accurate Detection of Marssonina coronariae in Apple Trees using Loop-Mediated Isothermal Amplification (LAMP).

Marssonina blotch of apple is a well-known plant disease caused by Marssonina coronariae, which can cause severe economic consequences. Due to the importance of early diagnosis for effective plant disease management, we aimed to develop a loop-mediated isothermal amplification (LAMP) assay that could rapidly detect M. coronariae in apple plants. The ribosomal DNA internal transcribed spacer (rDNA-ITS) sequence of M. coronariae was selected as the target for primer design. Our results showed optimal conditions for the LAMP reaction at 62℃ for 50 min, as indicated by color change and gel electrophoresis. The LAMP assay demonstrated specific discriminatory capability in differentiating M. coronariae from other pathogenic fungi in apple plants. In addition, the sensitivity tests revealed a detection limit of 100 fg µL-1 genomic DNA and 100 spores of M. coronariae for the LAMP assay. Finally, we successfully applied the LAMP assay to detect M. coronariae in apple leaf samples from the field. In general, our study provided a straightforward and efficient method for rapid diagnosis of apple blotch caused by M. coronariae, which could be applied in field condition and early occurrence of disease caused by M. coronariae could be detected.

Automatic multi-class intertrochanteric femur fracture detection from CT images based on AO/OTA classification using faster R-CNN-BO method.

Intertrochanteric (IT) femur fractures are the most common fractures in elderly people, and they lead to significant morbidity, mortality, and reduced quality of life. The different types of fractures require a careful definition to ensure accurate surgical planning and reduce the operation time, healing time, and number of surgical failures. In this study, a deep learning-based automatic multi-class IT fracture detection model was developed using computed tomography (CT) images and based on the AO/OTA classification method. The original CT image was resized and rearranged according to the fracture location and an unsharp masking filter was applied. A multi-class classification of nine different types of IT fractures and no fracture was performed using the faster regional-convolutional neural network (R-CNN). Bayesian optimization was also implemented to determine the optimal hyperparameter values for the faster R-CNN algorithm. In our proposed model, IT fractures classified into two classes showed an average accuracy of 0.97 ± 0.02, which was 0.90 ± 0.02 when classified into ten classes. Additionally, the detected region of interest from our proposed model showed minimum root mean square error and intersection over union values of 16.34 ± 47.01 pixels and 0.87 ± 0.12, respectively. In the future, our proposed automatic multi-class IT femur fracture detection model could allow clinicians to identify the fracture region and diagnose different types of femur fractures faster and more accurately. This will increase the probability of correct surgical treatment and minimize postoperative complications.

Selection of aptamers against pathogenic bacteria and their diagnostics application.

Aptamers are short nucleotide sequences which can specifically bind to a variety of targets with high affinity. They are identified and selected via systematic evolution of ligands by exponential enrichment (SELEX). Compared to antibodies, aptamers offer several advantages including easy labeling, high stability and lower cost. Those advantages make it possible to be a potential for use as a recognition probe to replace antibody in the diagnostic field. This article is intended to provide a comprehensive review, which is focused on systemizing recent advancements concerning SELEX procedures, with special emphasis on the key steps in SELEX procedures. The principles of various aptamer-based detections of pathogenic bacteria and their application are discussed in detail, including colorimetric detection, fluorescence detection, electrochemical detection, lateral flow strip test, mass sensitive detection and PCR-based aptasensor. By discussing recent research and future trends based on many excellent publications and reviews, we attempt to give the readers a comprehensive view in the field of aptamer selection against pathogenic bacteria and their diagnostics application. Authors hope that this review will promote lively and valuable discussions in order to generate new ideas and approaches towards the development of aptamer-based methods for application in pathogenic bacteria diagnosis.

Toward Pre-Diagnostic Detection of Dementia in Primary Care.

BACKGROUND: Preventing dementia warrants the pragmatic engagement of primary care. OBJECTIVE: This study predicted conversion to dementia 12 months before diagnosis with indicators that primary care can utilize within the practical constraints of routine practice. METHODS: The study analyzed data from the Alzheimer's Disease Neuroimaging Initiative (Total sample = 645, converting participants = 54). It predicted the conversion from biological (plasma neurofilament light chain), cognitive (Trails Making Test- B), and functional (Functional Activities Questionnaire) measures, in addition to demographic variables (age and education). RESULTS: A Gradient Booster Trees classifier effectively predicted the conversion, based on a Synthetic Minority Oversampling Technique (n = 1,290, F1 Score = 92, AUC = 94, Recall = 87, Precision = 97, Accuracy = 92). Subsequent analysis indicated that the MCI False Positive group (i.e., non-converting participants with cognitive impairment flagged by the model for prospective conversion) scored significantly lower on multiple cognitive tests (Montreal Cognitive Assessment, p < 0.002; ADAS-13, p < 0.0004; Rey Auditory Verbal Learning Test, p < 0.002/0.003) than the MCI True Negative group (i.e., correctly classified non-converting participants with cognitive impairment). These groups also differed in CSF tau levels (p < 0.04), while consistent effect size differences emerged in the all-pairwise comparisons of hippocampal volume and CSF Aß1 - 42. CONCLUSION: The model effectively predicted 12-month conversion to dementia and further identified non-converting participants with MCI, in the False Positive group, at relatively higher neurocognitive risk. Future studies may seek to extend these results to earlier prodromal phases. Detection of dementia before diagnosis may be feasible and practical in primary care settings, pending replication of these findings in diverse clinical samples.

One test for all: whole exome sequencing significantly improves the diagnostic yield in growth retarded patients referred for molecular testing for Silver-Russell syndrome.

BACKGROUND: Silver-Russell syndrome (SRS) is an imprinting disorder which is characterised by severe primordial growth retardation, relative macrocephaly and a typical facial gestalt. The clinical heterogeneity of SRS is reflected by a broad spectrum of molecular changes with hypomethylation in 11p15 and maternal uniparental disomy of chromosome 7 (upd(7)mat) as the most frequent findings. Monogenetic causes are rare, but a clinical overlap with numerous other disorders has been reported. However, a comprehensive overview on the contribution of mutations in differential diagnostic genes to phenotypes reminiscent to SRS is missing due to the lack of appropriate tests. With the implementation of next generation sequencing (NGS) tools this limitation can now be circumvented. MAIN BODY: We analysed 75 patients referred for molecular testing for SRS by a NGS-based multigene panel, whole exome sequencing (WES), and trio-based WES. In 21/75 patients a disease-causing variant could be identified among them variants in known SRS genes (IGF2, PLAG1, HMGA2). Several patients carried variants in genes which have not yet been considered as differential diagnoses of SRS. CONCLUSIONS: WES approaches significantly increase the diagnostic yield in patients referred for SRS testing. Several of the identified monogenetic disorders have a major impact on clinical management and genetic counseling.

Specific and Quantitative Detection of Albumin in Biological Fluids by Tetrazolate-Functionalized Water-Soluble AIEgens.

The analysis of albumin has clinical significance in diagnostic tests and obvious value to research studies on the albumin-mediated drug delivery and therapeutics. The present immunoassay, instrumental techniques, and colorimetric methods for albumin detection are either expensive, troublesome, or insensitive. Herein, a class of water-soluble tetrazolate-functionalized derivatives with aggregation-induced emission (AIE) characteristics is introduced as novel fluorescent probes for albumin detection. They can be selectively lighted up by site-specific binding with albumin. The resulting albumin fluorescent assay exhibits a low detection limit (0.21 nM), high robustness in aqueous buffer (pH = 6-9), and a broad tunable linear dynamic range (0.02-3000 mg/L) for quantification. The tetrazolate functionality endows the probes with a superior water solubility (>0.01 M) and a high binding affinity to albumin (KD = 0.25 µM). To explore the detection mechanism, three unique polar binding sites on albumin are computationally identified, where the multivalent tetrazolate-lysine interactions contribute to the tight binding and restriction of the molecular motion of the AIE probes. The key role of lysine residues is verified by the detection of poly-l-lysine. Moreover, we applied the fluorogenic method to quantify urinary albumin in clinical samples and found it a feasible and practical strategy for albumin analysis in complex biological fluids.

Class 2 CRISPR/Cas: an expanding biotechnology toolbox for and beyond genome editing.

Artificial nuclease-dependent DNA cleavage systems (zinc-finger nuclease, ZFN; transcription activator like effectors, TALENs) and exogenous nucleic acid defense systems (CRISPR/Cas) have been used in the new era for genome modification. The most widely used toolbox for genome editing, modulation and detection contains Types II, V and VI of CRISPR/Cas Class 2 systems, categorized and characterized by Cas9, Cas12a and Cas13 respectively. In this review, we (1) elaborate on the definition, classification, structures of CRISPR/Cas Class 2 systems; (2) advance our understanding of new molecular mechanisms and recent progress in their applications, especially beyond genome-editing applications; (3) provide the insights on the specificity, efficiency and versatility of each tool; (4) elaborate the enhancement on specificity and efficiency of the CRISPR/Cas toolbox. The expanding and concerted usage of the CRISPR/Cas tools is making them more powerful in genome editing and other biotechnology applications.

A new sensitive automated assay for procalcitonin detection: LIAISON® BRAHMS PCT® II GEN.

OBJECTIVES: To assess the performance of LIAISON® BRAHMS PCT® II GEN (DiaSorin, Saluggia, Italy) in procalcitonin (PCT) determination by comparing it to the assay reference method B·R·A·H·M·S PCT KRYPTOR (Thermo Fisher Scientific Clinical Diagnostics, Hennigsdorf, Germany) and assessing its ability to discriminate between healthy subjects and patients with suspected infection. METHODS: Diagnostic performance was evaluated on: a) 193 selected samples covering the assay range, whose procalcitonin levels were already evaluated with the B·R·A·H·M·S PCT® KRYPTOR; b) prospective samples: 150 apparently healthy specimens obtained from a blood bank, 161 hospitalized patients (not with specific pathologies), 243 apparently healthy children. RESULTS: The comparison of LIAISON® BRAHMS PCT® II GEN to the reference method B·R·A·H·M·S PCT KRYPTOR yielded high correlation coefficients: slope of Deming fit equal to 1.04 (95% CI: 0.99-1.09) with an intercept equal to 0.05 (95% CI: -0.09 to 0.19) and a high concordance (98.4% (95% CI: 95.5-99.7%)) at the 0.5 ng/mL cut-off. Moreover, the results obtained using prospective samples showed: (i) no samples with PCT concentration >0.5 ng/mL (cut-off) for the apparently healthy adults (highest value=0.033 ng/mL, 95th percentile and 97.5th percentile <0.02 ng/mL); (ii) 2 samples >0.5 ng/mL for hospitalized patients (highest value=0.715 ng/mL, 95th percentile: 0.054 ng/mL; 97.5th percentile: 0.088 ng/mL); (iii) 3 samples >0.5 ng/mL for the healthy children population (highest value=0.713 ng/mL, 95th percentile: 0.155 ng/mL; 97.5th percentile: 0.275 ng/mL). CONCLUSION: The fully automated LIAISON® BRAHMS PCT® II GEN agrees well with the reference method and is suitable for early diagnosis of sepsis, severe bacterial infection and guiding antibiotic therapy.

Particles and microfluidics merged: perspectives of highly sensitive diagnostic detection.

There is a growing need for diagnostic technologies that provide laboratories with solutions that improve quality, enhance laboratory system productivity, and provide accurate detection of a broad range of infectious diseases and cancers. Recent advances in micro- and nanoscience and engineering, in particular in the areas of particles and microfluidic technologies, have advanced the "lab-on-a-chip" concept towards the development of a new generation of point-of-care diagnostic devices that could significantly enhance test sensitivity and speed. In this review, we will discuss many of the recent advances in microfluidics and particle technologies with an eye towards merging these two technologies for application in medical diagnostics. Although the potential diagnostic applications are virtually unlimited, the most important applications are foreseen in the areas of biomarker research, cancer diagnosis, and detection of infectious microorganisms.