An Image Analysis System for Thin-Layer Chromatography Quantification and Its Validation

Purple coneflower [Echinacea purpurea (L.) Moench] is an increasingly popular crop because of its value in the U.S. botanical industry. At present, there is no rapid method of analyzing it for chicoric acid, the predominant phenolic acid associated with immunostimulation in humans. The objective of this study was to quantify chicoric acid in purple coneflower roots by near infrared (NIR) reflectance spectroscopy. One hundred sixty‐nine plants were harvested and their root tissues analyzed for chicoric acid by high performance liquid chromatography (HPLC). Root samples were scanned between 1100 and 2498 nm and reflectance data recorded. The HPLC data were regressed against infrared spectra to develop empirical prediction equations. The optimum prediction equation produced coefficients of determination for calibration and cross validation of 0.90 and 0.86, respectively. The mean chicoric acid concentration was 8.29 g kg DM−1, and the standard errors of calibration and cross validation were 0.89 and 1.06 g kg DM−1, respectively. We conclude that NIR reflectance spectroscopy can accurately quantitate chicoric acid in purple coneflower.

Purpose To devise a simple, fast, and low-cost method for glaucoma assessment using digital image analysis of the angle and optic nerve in human subjects. Methods Images from glaucoma and fundus assessment were used in this study, including color fundus photographs, standard optic nerve optical coherence tomography (OCT), and digital slit-lamp images of the angle/gonioscopy. Digital image conversion and analysis of the angle using ImageJ (NIH, USA) and adaptive histogram equalization contrast-limited AHE (CLAHE) to prevent noise amplification were implemented. Angle and optic nerve images were analyzed separately in the red, green, and blue (RGB) channels followed by 3D volumetric analysis of the degrees of angle depth and cup volume of the optic nerve. Horizontal tomogram reconstitution and nerve fiber detection methods were developed and compared to standard OCT images. Results Digital slit-lamp angle images showed similar accuracy as standard anterior OCT measurements. Comparative analysis of RGB channels produced volumetric cup and horizontal tomogram, which closely resembled the 3D OCT appearance and B-scan of the cup, respectively. RGB channel splitting and image subtraction produced a map closely resembling that of the retinal nerve fiber layer (RNFL) thickness map on OCT. Conclusions While OCT imaging is rapidly progressing in the area of optic disc and chamber angle assessment, rising healthcare costs and lack of availability of the technology open a demand for alternative and cost-minimizing forms of image analysis in glaucoma. Volumetric, geometric, and segmentational data obtained through digital image analysis correspond well to those obtained by OCT imaging.

In this paper, the current approaches and performance needs for whole slide image (WSI) analysis processing in breast cancer diagnostics are discussed. WSIs provide high resolution digital image data from the patient's diseased tissue. Digital whole slide images are typically very large and contain a high amount of information. Digitizing tissue specimen into the form of digital images allows the development and application of computational analysis algorithms. Biological tissues are complex with variance in tissue structures between healthy individuals as well as between patients with the same disease. Furthermore, the tissue preparation and digitization usually generates a lot of artifacts and more complexity, which causes classification challenges. This variance and also the large size of the images make creating an accurate and reliable automated breast cancer image analysis a challenge. In the ALMARVI project we aim at generating and implementing efficient histopathological image analysis algorithms in our breast cancer analysis scheme. This paper focuses on discussing relevant information concerning histopathological breast cancer diagnosis, and could also be considered as an introduction to the concept of WSI analysis to non-experts. Since the WSI sizes are very large (up to 40 GB with no compression) there are challenges on the computational analysis which requires computationally efficient tools and suitable approaches to relieve the problems caused by the large size of the images.

Digital imaging has experienced tremendous growth in recent decades, and digital camera images have been used in a growing number of applications. With such increasing popularity and the availability of low-cost image editing software, the integrity of digital image content can no longer be taken for granted. This paper introduces a new methodology for the forensic analysis of digital camera images. The proposed method is based on the observation that many processing operations, both inside and outside acquisition devices, leave distinct intrinsic traces on digital images, and these intrinsic fingerprints can be identified and employed to verify the integrity of digital data. The intrinsic fingerprints of the various in-camera processing operations can be estimated through a detailed imaging model and its component analysis. Further processing applied to the camera captured image is modelled as a manipulation filter, for which a blind deconvolution technique is applied to obtain a linear time-invariant approximation and to estimate the intrinsic fingerprints associated with these postcamera operations. The absence of camera-imposed fingerprints from a test image indicates that the test image is not a camera output and is possibly generated by other image production processes. Any change or inconsistencies among the estimated camera-imposed fingerprints, or the presence of new types of fingerprints suggest that the image has undergone some kind of processing after the initial capture, such as tampering or steganographic embedding. Through analysis and extensive experimental studies, this paper demonstrates the effectiveness of the proposed framework for nonintrusive digital image forensics.

CA regulates hepatic glucose homeostasisviathe AMPK pathway and improves hepatocyte injuryviaantioxidant responsein vitroandin vivo.

Cichorium intybus, commonly known as chicory, is a widespread plant, valued for its medicinal properties and use as a coffee substitute, chicoric acid being one of its key constituents. This study investigates the variation in chicoric acid content across different parts of the chicory plant-flowers, leaves, root and aerial parts. Three extraction methods, namely maceration in 70% ethanol, ultrasound-assisted extraction (UAE), and enzyme-assisted UAE were compared. A new optimized high-performance thin-layer chromatography (HPTLC) method was used to determine the chicoric acid quantities. The chicoric acid was separated on HPTLC silica gel F254 plates developed with a mixture of ethyl acetate‒formic acid‒acetic acid‒water (8:0.2:2:1.8, v/v) as the mobile phase. The detection was performed in UV light at 366 nm after derivatization with natural product (NP) and polyethylene glycol solution (PEG). The quantification was performed by image analysis (IA) using ImageJ software, with the green color channel offering the most sensitive detection (LOD = 2 ng/band and LOQ = 6 ng/band). The analysis revealed that leaves contained the highest concentration of chicoric acid, while roots exhibited the lowest. Enzyme-assisted UAE proved to be the most effective method. Antioxidant activity was tested using 1,1-diphenyl-2-picrylhydrazyl (DPPH) radical revealing that the chicoric acid possesses this activity. These findings highlight chicory leaves as a valuable source of chicoric acid and emphasize the importance of choosing effective extraction methods to maximize the yield of bioactive compounds.

Chicoric acid (CA), a polyphenolic acid obtained from chicory and purple coneflower (Echinacea purpurea), has been regarded as a nutraceutical to combat inflammation, viruses and obesity. Parkinson's disease (PD) is a common neurodegenerative disorder, and the microbiota-gut-brain axis might be the potential mechanism in the pathogenesis and development of PD. The results obtained in this study demonstrated that oral pretreatments of CA significantly prevented the 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP)-induced motor dysfunctions and death of nigrostriatal dopaminergic neurons along with the inhibition of glial hyperactivation and the increment in striatal neurotrophins. 16S rRNA sequence results showed that CA significantly reduced MPTP-induced microbial dysbiosis and partially restored the composition of the gut microbiota to normal, including decreased phylum Bacteroidetes and genera Parabacteroide, as well as increased phylum Firmicutes, genera Lactobacillus and Ruminiclostridium. Besides, CA promoted colonic epithelial integrity and restored normal SCFA production. We also observed that proinflammatory cytokines such as TNF-α and IL-1β in the serum, striatum and colon were reduced by CA, indicating that CA prevented neuroinflammation and gut inflammation, in which the suppression of the TLR4/MyD88/NF-κB signaling pathway might be the underlying molecular mechanism. These findings demonstrated that CA had neuroprotective effects on MPTP-induced PD mice possibly via modulating the gut microbiota and inhibiting inflammation throughout the brain-gut axis.

A reversed-phase high-performance liquid chromatography (HPLC) method has been developed to determine caffeic acid derivatives, for example, cichoric acid, and alkamides in plant parts and herbal products of Echinacea purpurea. The method consists of an extraction procedure whereby the hydrophilic phenolics as well as the lipophilic alkamides are released from the samples, followed by the analytical HPLC procedure for quantitative determination of these compounds. The method is the first one validated for the determination of these two groups of compounds in the same procedure. Naringenin has been used as an internal standard, as no other flavanones are present in the extract and it does not interfere with any of the compounds under investigation. Analysis of Danish-grown plant material shows that it is possible to raise plants of a very high chemical quality in Denmark. A selection of international herbal products available on the Danish market show surprisingly variable quality, not necessarily reflecting the product information given on the labels.

Transcriptomics and metabolomics analyses of the effects of plant age and organ on caffeic acid derivative accumulation in Echinacea purpurea.

Using phenotypic information extracted from digital images through automated computer vision analysis has become a promising avenue in ecological and evolutionary research. However, acquiring large quantities of high‐quality image data and processing them efficiently often remain a bottleneck. Here, we introduce the Wellcounter, an advanced platform designed for the automated high‐throughput phenotyping of aquatic microinvertebrates (100–2000 μm), utilizing common multiwell plates to facilitate large‐scale ecological experiments. The system automates image acquisition, processing and analysis, enabling the tracking of hundreds of populations with minimal daily manual effort. Key hardware components include a high‐resolution digital camera, a telecentric lens and a motorized XY linear guide system based on an open‐source design that moves to each individual well. A dark‐field illumination ring, which travels synchronously with the camera and lens, provides constant and standardized light conditions and enhances the visualization of microinvertebrates within each well, improving detection accuracy. Our prototype can handle 84 six‐well plates in two batches, ensuring efficient imaging and analysis of over 500 populations. The software, developed in Python, supports detailed population size measurements, growth rate analysis and swimming behaviour quantification. It includes modules for image acquisition control, image analysis and motion analysis, ensuring comprehensive data collection and interpretation. We also provide a module for generating ‘ground truth’ datasets, allowing to label the positions of all detectable specimens in an image, and an optimization module to fine‐tune imaging parameters for a new study organism. Validation of the Wellcounter was conducted using rotifers. The platform demonstrated high accuracy in detecting and counting individuals, as well as in measuring population growth rates and swimming behaviour. Image analysis parameters were optimized to minimize false negatives and false positives. We discuss adapting this protocol for different microorganisms and hardware configurations, as well as general caveats and current limitations of this phenotyping approach. For those interested in developing image analysis algorithms, we provide large annotated datasets, including high‐resolution movies and images with known quantities and positions of specimens. The approach and resources provided in this study aim to facilitate the adoption and further development of automated image analysis technologies in ecological research.

Chicoric acid has been widely used in food, medicine, animal husbandry, and other commercial products because of its significant pharmacological activities. However, the shortage of chicoric acid limits its further development and utilization. Currently, Echinacea purpurea (L.) Moench serves as the primary natural resource of chicoric acid, while other sources of it are poorly known. Extracting chicoric acid from plants is the most common approach. Meanwhile, chicoric acid levels vary in different plants as well as in the same plant from different areas and different medicinal parts, and different extraction methods. We comprehensively reviewed the information regarding the sources of chicoric acid from plant extracts, its chemical synthesis, biosynthesis, and bioactive effects.

Automated invasive ductal carcinoma detection based using deep transfer learning with whole-slide images

Sand response depends on particle morphology (size and shape). In geotechnical research and practice, size is typically assessed by sieve analysis and particle shapes are qualitatively described. Technological developments mean that digital images of sand particles can easily be obtained, enabling shape to be quantified. The complexity associated with many digital image analysis algorithms seems to have restricted their use to fundamental research studies. This study introduces a pragmatic approach for quantitative shape analysis that has the potential to be broadly adopted in geotechnical engineering research and practice. The approach generates three shape measures (convexity, sphericity, and aspect ratio) that can easily be calculated from digital images. Following an analysis of these shape measures and the imaging method used here, a database of 36 sands, including many of the sands commonly used in geotechnical research, is presented. The subjective nature of qualitative description is clear from the discrepancies that were found in published shape assessments of these sands. Convexity, sphericity, and aspect ratio data for each of the 36 sands are presented. The relevance of these parameters to geotechnical engineering is established by comparing them with widely used qualitative descriptions.

Selected chemotherapeutic agents used for the treatment of cancer are known to cause skin toxicities. One group of agents, epidermal growth factor receptor (EGFR) inhibitors, characteristically precipitates an acneform rash. Currently, no standard of care exists for the management of the rash resulting from EGFR inhibitors. In order to objectively evaluate any management strategy, a method to quantify the rash is required. The purpose of this paper is to describe a method to quantify the erythema of a facial rash through the use of digital photography and image analysis. A Canfield OMNIA System using a Canon PowerShot Pro1 camera was used to obtain high-resolution digital images of facial rashes. Digital images were recorded in Joint Photographic Experts Group format, corrected for brightness and white balance and color. A method was developed to analyze digital images of erythema independent of the range of skin pigmentation. Two examples are given to illustrate the method developed and its utility. An inexpensive and portable method is described for objectively monitoring the development of facial erythema in subjects of the full range of skin pigmentation. This method can be used clinically to examine the development and resolution of facial rash erythema in response to treatment.

To determine, with novel software, the feasibility of measuring the tortuosity and width of retinal veins and arteries from digital retinal images of infants at risk of retinopathy of prematurity (ROP). The Computer-Aided Image Analysis of the Retina (CAIAR) program was developed to enable semiautomatic detection of retinal vasculature and measurement of vessel tortuosity and width from digital images. CAIAR was tested for accuracy and reproducibility of tortuosity and width measurements by using computer-generated vessel-like lines of known frequency, amplitude, and width. CAIAR was then tested by using clinical digital retinal images for correlation of vessel tortuosity and width readings compared with expert ophthalmologist grading. When applied to 16 computer-generated sinusoidal vessels, the tortuosity measured by CAIAR correlated very well with the known values. Width measures also increased as expected. When the CAIAR readings were compared with five expert ophthalmologists' grading of 75 vessels on 10 retinal images, moderate correlation was found in 10 of the 14 tortuosity output calculations (Spearman rho = 0.618-0.673). Width was less well correlated (rho = 0.415). The measures of tortuosity and width in CAIAR were validated using sequential model vessel analysis. On comparison of CAIAR output with assessments made by expert ophthalmologists, CAIAR correlates moderately with tortuosity grades, but less well with width grades. CAIAR offers the opportunity to develop an automated image analysis system for detecting the vascular changes at the posterior pole, which are becoming increasingly important in diagnosing treatable ROP.