Dual-Region Computed Tomography Radiomics-Based Machine Learning Predicts Subcarinal Lymph Node Metastasis in Patients with Non-small Cell Lung Cancer.

BACKGROUND: Noninvasively and accurately predicting subcarinal lymph node metastasis (SLNM) for patients with non-small cell lung cancer (NSCLC) remains challenging. This study was designed to develop and validate a tumor and subcarinal lymph nodes (tumor-SLNs) dual-region computed tomography (CT) radiomics model for predicting SLNM in NSCLC. METHODS: This retrospective study included NSCLC patients who underwent lung resection and SLNs dissection between January 2017 and December 2020. The radiomic features of the tumor and SLNs were extracted from preoperative CT, respectively. Ninety machine learning (ML) models were developed based on tumor region, SLNs region, and tumor-SLNs dual-region. The model performance was assessed by the area under the curve (AUC) and validated internally by fivefold cross-validation. RESULTS: In total, 202 patients were included in this study. ML models based on dual-region radiomics showed good performance for SLNM prediction, with a median AUC of 0.794 (range, 0.686-0.880), which was superior to those of models based on tumor region (median AUC, 0.746; range, 0.630-0.811) and SLNs region (median AUC, 0.700; range, 0.610-0.842). The ML model, which is developed by using the naive Bayes algorithm and dual-region features, had the highest AUC of 0.880 (range of cross-validation, 0.825-0.937) among all ML models. The optimal logistic regression model was inferior to the optimal ML model for predicting SLNM, with an AUC of 0.727. CONCLUSIONS: The CT radiomics showed the potential for accurately predicting SLNM in NSCLC patients. The ML model with dual-region radiomic features has better performance than the logistic regression or single-region models.

Automated recognition and analysis of body bending behavior in C. elegans.

BACKGROUND: Locomotion behaviors of Caenorhabditis elegans play an important role in drug activity screening, anti-aging research, and toxicological assessment. Previous studies have provided important insights into drug activity screening, anti-aging, and toxicological research by manually counting the number of body bends. However, manual counting is often low-throughput and takes a lot of time and manpower. And it is easy to cause artificial bias and error in counting results. RESULTS: In this paper, an algorithm is proposed for automatic counting and analysis of the body bending behavior of nematodes. First of all, the numerical coordinate regression method with convolutional neural network is used to obtain the head and tail coordinates. Next, curvature-based feature point extraction algorithm is used to calculate the feature points of the nematode centerline. Then the maximum distance between the peak point and the straight line between the pharynx and the tail is calculated. The number of body bends is counted according to the change in the maximum distance per frame. CONCLUSION: Experiments are performed to prove the effectiveness of the proposed algorithm. The accuracy of head coordinate prediction is 0.993, and the accuracy of tail coordinate prediction is 0.990. The Pearson correlation coefficient between the results of the automatic count and manual count of the number of body bends is 0.998 and the mean absolute error is 1.931. Different strains of nematodes are selected to analyze differences in body bending behavior, demonstrating a relationship between nematode vitality and lifespan. The code is freely available at https://github.com/hthana/Body-Bend-Count .

Application of Feature Definition and Quantification in Biological Sequence Analysis.

Biological sequence analysis is the most fundamental work in bioinformatics. Many research methods have been developed in the development of biological sequence analysis. These methods include sequence alignment-based methods and alignment-free methods. In addition, there are also some sequence analysis methods based on the feature definition and quantification of the sequence itself. This editorial introduces the methods of biological sequence analysis and explores the significance of defining features and quantitative research of biological sequences.

A Systematic Survey of the Light/Dark-dependent Protein Degradation Events in a Model Cyanobacterium.

Light is essential for photosynthetic organisms and is involved in the regulation of protein synthesis and degradation. The significance of light-regulated protein degradation is exemplified by the well-established light-induced degradation and repair of the photosystem II reaction center D1 protein in higher plants and cyanobacteria. However, systematic studies of light-regulated protein degradation events in photosynthetic organisms are lacking. Thus, we conducted a large-scale survey of protein degradation under light or dark conditions in the model cyanobacterium Synechocystis sp. PCC 6803 (hereafter referred to as Synechocystis) using the isobaric labeling-based quantitative proteomics technique. The results revealed that 79 proteins showed light-regulated degradation, including proteins involved in photosystem II structure or function, quinone binding, and NADH dehydrogenase. Among these, 25 proteins were strongly dependent on light for degradation. Moreover, the light-dependent degradation of several proteins was sensitive to photosynthetic electron transport inhibitors (DCMU and DBMIB), suggesting that they are influenced by the redox state of the plastoquinone (PQ) pool. Together, our study comprehensively cataloged light-regulated protein degradation events, and the results serve as an important resource for future studies aimed at understanding light-regulated processes and protein quality control mechanisms in cyanobacteria.

Automated recognition and analysis of head thrashes behavior in C. elegans.

BACKGROUND: Locomotive behaviors are a rapid evaluation indicator reflecting whether the nervous system of worms is damaged, and has been proved to be sensitive to chemical toxicity. In many toxicological studies, C. elegans head thrashes is a key indicator of locomotive behaviors to measure the vitality of worms. In previous studies, the number of head thrashes was manually counted, which is time-consuming and labor-intensive. RESULTS: This paper presents an automatic recognition and counting method for head thrashes behavior of worms from experimental videos. First, the image processing algorithm is designed for worm morphology features calculation, mean gray values of head and tail are used to locate the head of worm accurately. Next, the worm skeleton is extracted and divided into equal parts. The angle formulas are used to calculate the bending angle of the head of worm. Finally, the number of head thrashes is counted according to the bending angle of the head in each frame. The robustness of the proposed algorithm is evaluated by comparing the counting results of the manual counting. It is proved that the proposed algorithm can recognize the occurrence of head thrashes of C. elegans of different strains. In addition, the difference of the head thrashes behavior of different worm strains is analyzed, it is proved that the relationship between worm head thrashes behavior and lifespan. CONCLUSIONS: A new method is proposed to automatically count the number of head thrashes of worms. This algorithm makes it possible to count the number of head thrashes from the worm videos collected by the automatic tracking system. The proposed algorithm will play an important role in toxicological research and worm vitality research. The code is freely available at https://github.com/hthana/HTC .

Bioautography-guided HPTLC-MS as a rapid hyphenated technique for the identification of antimicrobial compounds from selected South African Combretaceae species.

INTRODUCTION: Many species within Combretaceae are traditionally used for the treatment of bacterial infections. The similarity in chemistry and antimicrobial activities within the family pose a challenge in selecting suitable species for herbal drug development. OBJECTIVE: This study aimed at rapidly identifying antimicrobial compounds using bioautography-guided high-performance thin-layer chromatography coupled with mass spectrometry (HPTLC-MS). METHODS: Hierarchical cluster analysis of ultra-performance liquid chromatography-mass spectrometry data from the methanol extracts of 77 samples, representing four genera within Combretaceae, was carried out. Based on groupings on the dendrogram, 15 samples were selected for bioautography analysis against four pathogens (Staphylococcus aureus, Bacillus cereus, Escherichia coli and Salmonella typhimurium). Active compounds were identified using HPTLC-MS analysis of bands corresponding to the inhibition zones. RESULTS: Bioautography revealed 15 inhibition zones against the four pathogens, with the most prominent present for Combretum imberbe. Analysis of the active bands, using HPTLC-MS indicated that flavonoids, triterpenoids and combretastatin B5 contributed to the antibacterial activity. The compounds corresponding to molecular ions m/z 471 (Combretum imberbe) and 499 (Combretum elaeagnoides) inhibited all four pathogens, and were identified as imberbic acid and jessic acid, respectively. Chemotaxonomic analysis indicated that arjunic acid, ursolic acid and an unidentified triterpenoid (m/z 471) were ubiquitous in the Combretaceae species and could be responsible for their antibacterial activities. CONCLUSION: Application of HPTLC-MS enabled the rapid screening of extracts to identify active compounds within taxonomically related species. This approach allows for greater efficiency in the natural product research workflow to identify bioactive compounds in crude extracts.

Releasing Addiction Memories Trapped in Perineuronal Nets.

Drug addiction can be conceptualized at a basic level as maladaptive learning and memory. Addictive substances elicit changes in brain circuitry involved in reward, cognition, and emotional state, leading to the formation and persistence of strong drug-associated memories that lead to craving and relapse. Recently, perineuronal nets (PNNs), extracellular matrix (ECM) structures surrounding neurons, have emerged as regulators of learning, memory, and addiction behaviors. PNNs do not merely provide structural support to neurons but are dynamically remodeled in an experience-dependent manner by metalloproteinases. They function in various brain regions through constituent proteins such as brevican that are implicated in neural plasticity. Understanding the function of PNN components in memory processes may lead to new therapeutic approaches to treating addiction.

Elevated Fructose and Uric Acid Through Aldose Reductase Contribute to Experimental and Human Alcoholic Liver Disease.

BACKGROUND AND AIMS: Alcohol-associated liver disease (ALD) is a common chronic liver disease worldwide with high morbidity and mortality, and no Food and Drug Administration-approved therapies. Fructose (dietary or endogenous), its metabolite uric acid, and aldose reductase (AR, the only endogenous enzyme that produces fructose) are strongly associated with the development of nonalcoholic fatty liver disease. However, the role of AR or its metabolites in ALD remains understudied and was examined using human specimens, cultured cells, and mouse model systems. APPROACH AND RESULTS: We demonstrated in liver specimens from patients with alcoholic hepatitis, the AR up-regulation and elevated AR metabolites (sorbitol, fructose, and uric acid), which correlated significantly with (1) increased lipid peroxidation byproducts and endoplasmic reticulum (ER) stress, (2) decreased protective ER chaperones, and (3) greater cell death and liver injury. Furthermore, we established a causal role for AR in ALD by showing that the genetic deficiency of AR (knockout mice) prevented alcohol-induced increase in harmful AR metabolites, toxic aldehydes, steatosis, ER stress, apoptosis, and liver injury. Finally, we demonstrated the therapeutic potential of pharmacological AR inhibition against alcohol-induced hepatic injury in experimental ALD. CONCLUSIONS: Our data demonstrate that hepatic AR up-regulation, and consequent elevation in fructose, sorbitol and/or uric acid, are important factors contributing to alcohol-induced steatosis, ER stress, apoptosis, and liver injury in both experimental and human ALD. Our study provides a strong rationale to evaluate AR as a potential therapeutic target and to test AR inhibitors to ameliorate alcohol-induced liver injury.

Automatic Detection of Scattered Garbage Regions Using Small Unmanned Aerial Vehicle Low-Altitude Remote Sensing Images for High-Altitude Natural Reserve Environmental Protection.

Recently, some famous high-altitude nature reserves have been shut down due to tourist garbage pollution. In order to clean up such garbage more conveniently and quickly, a novel detection framework is proposed to automatically detect scattered garbage regions using low-altitude remote sensing of small unmanned aerial vehicles (SUAVs), and it contains the following steps. First, high-resolution, low-altitude, multitemporal remote sensing images containing scattered garbage regions are collected by SUAVs, and two data augmentation methods are proposed to expand the training samples. Second, low-altitude remote sensing image registration and target-level image change detection are used to extract the candidate regions of garbage. Finally, a deep learning detection network is adopted to classify the scattered garbage regions. Experimental results show that the proposed detection framework achieves a mean accuracy of 96.94% and provides better performances on the real dataset compared with state-of-the-art methods.

Phytochemical Profiling and Quality Control of Terminalia sericea Burch. ex DC. Using HPTLC Metabolomics.

Terminalia sericea is used throughout Africa for the treatment of a variety of conditions and has been identified as a potential commercial plant. The study was aimed at establishing a high-performance thin layer chromatography (HPTLC) chemical fingerprint for T. sericea root bark as a reference for quality control and exploring chemical variation within the species using HPTLC metabo3lomics. Forty-two root bark samples were collected from ten populations in South Africa and extracted with dichloromethane: methanol (1:1). An HPTLC method was optimized to resolve the major compounds from other sample components. Dichloromethane: ethyl acetate: methanol: formic acid (90:10:30:1) was used as the developing solvent and the plates were visualized using 10% sulfuric acid in methanol as derivatizing agent. The concentrations of three major bioactive compounds, sericic acid, sericoside and resveratrol-3-O-ß-rutinoside, in the extracts were determined using a validated ultra-performance liquid chromatography-photodiode array (UPLC-PDA) detection method. The rTLC software (written in the R-programming language) was used to select the most informative retardation factor (Rf) ranges from the images of the analysed sample extracts. Further chemometric models, including principal component analysis (PCA) and hierarchical cluster analysis (HCA), were constructed using the web-based high throughput metabolomic software. The rTLC chemometric models were compared with the models previously obtained from ultra-performance liquid chromatography coupled with mass spectrometry (UPLC-MS). A characteristic fingerprint containing clear bands for the three bioactive compounds was established. All three bioactive compounds were present in all the samples, although their corresponding band intensities varied. The intensities correlated with the UPLC-PDA results, in that samples containing a high concentration of a particular compound, displayed a more intense band. Chemometric analysis using HCA revealed two chemotypes, and the subsequent construction of a loadings plot indicated that sericic acid and sericoside were responsible for the chemotypic variation; with sericoside concentrated in Chemotype 1, while sericic acid was more abundant in Chemotype 2. A characteristic chemical fingerprint with clearly distinguishable features was established for T. sericea root bark that can be used for species authentication, and to select samples with high concentrations of a particular marker compound(s). Different chemotypes, potentially differing in their therapeutic potency towards a particular target, could be distinguished. The models revealed the three analytes as biomarkers, corresponding to results reported for UPLC-MS profiling and thereby indicating that HPTLC is a suitable technique for the quality control of T. sericea root bark.

Urinary acrolein metabolite levels in severe acute alcoholic hepatitis patients.

Alcohol-associated liver disease (ALD) remains a major health concern worldwide. Alcohol consumption gives rise to reactive/toxic acrolein, a pathogenic mediator of liver injury in experimental ALD. Elevated acrolein adducts and metabolites are detectable in blood and urine. This study evaluates the major urinary acrolein metabolite, 3-hydroxypropylmercapturic acid (HPMA), in patients with acute alcoholic hepatitis (AAH) and examines its association with disease severity and markers of hepatic inflammation and injury. Urine HPMA was significantly higher in patients with severe [model for end-stage liver disease (MELD) ≥ 20] AAH compared with nonsevere AAH (MELD ≤ 19) or non-alcohol-consuming controls, suggesting that urine HPMA is a novel noninvasive biomarker in severe AAH. The association between HPMA and MELD in patients with AAH was nonlinear. In patients with nonsevere AAH, there was a positive trend, although not significant, whereas in severe AAH the association was negative, indicative of extensive injury and glutathione depletion. Consistent with the multifactorial etiology of ALD, our data identified strong combined effects of HPMA and proinflammatory cytokines on hepatocyte cell death, thereby supporting the pathogenic role of acrolein in liver injury. HPMA, together with IL-1ß, showed robust associations with cytokeratin 18 caspase-cleaved fragment (CK18-M30; adjusted R2 = 0.812, P = 0.016) and cytokeratin 18 full-length protein (CK18-M65; adjusted R2 = 0.670, P = 0.048); similarly, HPMA, with IL-8, correlated with CK18-M30 (adjusted R2 = 0.875, P = 0.007) and CK18-M65 (adjusted R2 = 0.831, P = 0.013). The apoptosis index (CK18-M30:CK18-M65 ratio) strongly correlated with HPMA, together with IL-1ß (adjusted R2 = 0.777, P = 0.022) or tumor necrosis factor-α (TNFα; adjusted R2 = 0.677, P = 0.046). In patients with severe AAH, IL-1ß, IL-8, and TNFα are the predominant proinflammatory cytokines that interact with HPMA and play important mediating roles in influencing the extent/pattern of liver cell death. NEW & NOTEWORTHY This is the first study to examine the urinary acrolein metabolite 3-hydroxypropylmercapturic acid (HPMA) in alcoholic liver disease. HPMA was higher in patients with severe acute alcoholic hepatitis (AAH) compared with controls or nonsevere AAH and may be a novel selective, noninvasive biomarker for severe AAH. Consistent with the multifactorial etiology of alcohol-associated liver disease, we identified strong combined effects of HPMA and proinflammatory cytokines (IL-1ß, IL-8, and TNFα) on the extent/pattern of liver cell death, thereby supporting the pathogenic role of acrolein.

Translating Divergent Environmental Stresses into a Common Proteome Response through Hik33 in a Model Cyanobacterium.

The histidine kinase Hik33 plays important roles in mediating cyanobacterial response to divergent types of abiotic stresses including cold, salt, high light (HL), and osmotic stresses. However, how these functions are regulated by Hik33 remains to be addressed. Using a hik33-deficient strain (Δhik33) of Synechocystis sp. PCC 6803 (Synechocystis) and quantitative proteomics, we found that Hik33 depletion induces differential protein expression highly similar to that induced by divergent types of stresses. This typically includes downregulation of proteins in photosynthesis and carbon assimilation that are necessary for cell propagation, and upregulation of heat shock proteins, chaperons, and proteases that are important for cell survival. This observation indicates that depletion of Hik33 alone mimics divergent types of abiotic stresses, and that Hik33 could be important for preventing abnormal stress response in the normal condition. Moreover, we found the majority of proteins of plasmid origin were significantly upregulated in Δhik33, though their biological significance remains to be addressed. Together, the systematically characterized Hik33-regulated cyanobacterial proteome, which is largely involved in stress responses, builds the molecular basis for Hik33 as a general regulator of stress responses.

Translating Divergent Environmental Stresses into a Common Proteome Response through the Histidine Kinase 33 (Hik33) in a Model Cyanobacterium.

The histidine kinase Hik33 plays important roles in mediating cyanobacterial response to divergent types of abiotic stresses including cold, salt, high light (HL), and osmotic stresses. However, how these functions are regulated by Hik33 remains to be addressed. Using a hik33-deficient strain (Δhik33) of Synechocystis sp. PCC 6803 (Synechocystis) and quantitative proteomics, we found that Hik33 depletion induces differential protein expression highly like that induced by divergent types of stresses. This typically includes downregulation of proteins in photosynthesis and carbon assimilation that are necessary for cell propagation, and upregulation of heat shock proteins, chaperons, and proteases that are important for cell survival. This observation indicates that depletion of Hik33 alone mimics divergent types of abiotic stresses, and that Hik33 could be important for preventing abnormal stress response in the normal condition. Moreover, we found most proteins of plasmid origin were significantly upregulated in Δhik33, though their biological significance remains to be addressed. Together, the systematically characterized Hik33-regulated cyanobacterial proteome, which is largely involved in stress responses, builds the molecular basis for Hik33 as a general regulator of stress responses.

Activation of the Oxidative Pentose Phosphate Pathway is Critical for Photomixotrophic Growth of a hik33-Deletion Mutant of Synechocystis sp. PCC 6803.

The histidine kinase Hik33 plays a central role in acclimation to changing environments in cyanobacteria. Deletion of hik33 induces a strong stress-like response in Synechocystis sp. PCC 6803 (Synechocystis) as represented by repressed photoautotrophic growth and photosynthesis, and differential expression of stress-responsive proteins. In contrast, the photomixotrophic growth of the hik33-deletion mutant (Δhik33) with glucose as the exogenous carbon source is only marginally repressed. To investigate how glucose rescues the growth of Δhik33, the proteomes of the photomixotrophically growing wild-type (WT) and the mutant strains of Synechocystis are quantitatively analyzed. It is found that glucose induces upregulation of the oxidative pentose phosphate (OPP) pathway. Depletion of glucose-6-phosphate dehydrogenase (G6PDH), which catalyzes the first and the rate-limiting step of the OPP pathway, significantly inhibits the photomixotrophic growth of Δhik33 but not of the WT. The result suggests that the OPP pathway, which is usually nonfunctional in the photomixotrophically growing WT, plays a major role in the photomixotrophic growth of Δhik33.

Acrolein Disrupts Tight Junction Proteins and Causes Endoplasmic Reticulum Stress-Mediated Epithelial Cell Death Leading to Intestinal Barrier Dysfunction and Permeability.

Increasing evidence suggests that environmental and dietary factors can affect intestinal epithelial integrity leading to gut permeability and bacterial translocation. Intestinal barrier dysfunction is a pathogenic process associated with many chronic disorders. Acrolein is an environmental and dietary pollutant and a lipid-derived endogenous metabolite. The impact of acrolein on the intestine has not been investigated before and is evaluated in this study, both in vitro and in vivo. Our data demonstrate that oral acrolein exposure in mice caused damage to the intestinal epithelial barrier, resulting in increased permeability and subsequently translocation of bacterial endotoxin-lipopolysaccharide into the blood. Similar results were seen in vitro using established Caco-2 cell monolayers wherein acrolein decreased barrier function and increased permeability. Acrolein also caused the down-regulation and/or redistribution of three representative tight junction proteins (ie, zonula occludens-1, Occludin, Claudin-1) that critically regulate epithelial paracellular permeability. In addition, acrolein induced endoplasmic reticulum stress-mediated death of epithelial cells, which is an important mechanism contributing to intestinal barrier damage/dysfunction, and gut permeability. Overall, we demonstrate that exposure to acrolein affects the intestinal epithelium by decrease/redistribution of tight junction proteins and endoplasmic reticulum stress-mediated epithelial cell death, thereby resulting in loss of barrier integrity and function. Our findings highlight the adverse consequences of environmental and dietary pollutants on intestinal barrier integrity/function with relevance to gut permeability and the development of disease.

Use of image texture analysis to find DNA sequence similarities.

Sequence similarity analysis is a basic method in computational biological studies. Determining the similarity of biological sequences is a vital step in much research, such as exploring the evolutionary relationship among species, gene function analysis, protein structure prediction, and sequence retrieving. This paper introduces a method that uses the theory of the gray-level co-occurrence matrix, which is important in image texture analysis, to define and calculate the features of a DNA sequence. The proposed method can make a quantitative analysis and compute the defined texture features of a DNA sequence. Using these quantified sequence features, a similarity distance matrix can be computed and phylogenetic relationships also can be inferred. From the quantified features, we found that the DNA sequence of humans has the highest entropy and lowest energy. From human to chimpanzee, orangutan, gorilla, and other species, the entropy decreases and energy increases. The advantage of the proposed method is that it can compute multiple features inherent in each sequence. Furthermore, the defined features can be the key values or tags for each sequence for sequence retrieval and similarity analysis.

Hyperspectral Imaging and Support Vector Machine: A Powerful Combination to Differentiate Black Cohosh (Actaea racemosa) from Other Cohosh Species.

Actaea racemosa (black cohosh) has a history of traditional use in the treatment of general gynecological problems. However, the plant is known to be vulnerable to adulteration with other cohosh species. This study evaluated the use of shortwave infrared hyperspectral imaging (SWIR-HSI) in tandem with chemometric data analysis as a fast alternative method for the discrimination of four cohosh species (Actaea racemosa, Actaea podocarpa, Actaea pachypoda, Actaea cimicifuga) and 36 commercial products labelled as black cohosh. The raw material and commercial products were analyzed using SWIR-HSI and ultra-high-performance liquid chromatography coupled to mass spectrometry (UHPLC-MS) followed by chemometric modeling. From SWIR-HSI data (920 - 2514 nm), the range containing the discriminating information of the four species was identified as 1204 - 1480 nm using Matlab software. After reduction of the data set range, partial least squares discriminant analysis (PLS-DA) and support vector machine discriminant analysis (SVM-DA) models with coefficients of determination (R2 ) of ≥ 0.8 were created. The novel SVM-DA model showed better predictions and was used to predict the commercial product content. Seven out of 36 commercial products were recognized by the SVM-DA model as being true black cohosh while 29 products indicated adulteration. Analysis of the UHPLC-MS data demonstrated that six commercial products could be authentic black cohosh. This was confirmed using the fragmentation patterns of three black cohosh markers (cimiracemoside C; 12-ß,21-dihydroxycimigenol-3-O-L-arabinoside; and 24-O-acetylhydroshengmanol-3-O-ß-D-xylopyranoside). SWIR-HSI in conjunction with chemometric tools (SVM-DA) could identify 80% adulteration of commercial products labelled as black cohosh.

Potential Herb-Drug Pharmacokinetic Interactions between African Wild Olive Leaf Extract and Selected Antihypertensive Drugs.

The African wild olive (Olea europaea subsp. africana) is traditionally used as a hypotensive agent. Herb-drug interactions may result from the concurrent use of herbal medicines and conventional prescription drugs. This aspect was investigated by determining the effect of the extract on the in vitro intestinal epithelial permeation of selected hypotensive drugs using the Caco-2 cell culture model. The phytochemical profiles of leaf extracts of African wild olive from different localities in South Africa were compared, since efficacy is determined by the chemical composition. Extracts were analysed using ultra-performance liquid chromatography. The oleuropein concentration varied considerably from below the detection limit (4.94 µg/mL) to 59.4 mg/g dry weight. Chemometric models constructed from the aligned chromatographic data indicated only quantitative differences between the profiles. The leaf extract was found to increase the permeability of propranolol in the absorptive direction (Papp = 8.93 × 10-6 cm/s) across Caco-2 cell monolayers, but considerably decreased transport in the secretory direction (Papp = 3.68 × 10-6 cm/s). The permeation of diltiazem was enhanced by the extract in both the absorptive (Papp = 7.33 × 10-6 cm/s) as well as in the secretory direction (Papp = 7.16 × 10-6 cm/s), but a decrease in the efflux ratio was observed. The extract therefore caused a net increase in the transport of both drugs in the absorptive direction due to an inhibition effect on their efflux. This suggests a potential increase in the blood levels of these drugs when taken simultaneously with African wild olive leaf extract, indicating potential adverse effects that must be verified in vivo.

Identification, Isolation and Determination of Biomarkers for Quality Control of Bush Tea (Athrixia phyllicoides).

Athrixia phylicoides, known as "bush tea", grows abundantly in South Africa. An infusion of the leaves is used as a beverage and to treat a multitude of health conditions. The aim of this study was to investigate the chemical variation within A. phylicoides and to identify characteristic compounds for quality control. Samples from 12 locations in South Africa were analysed using ultra-performance liquid chromatography. Hierarchical cluster analysis of the aligned ultra-performance liquid chromatography-time-of-flight mass spectrometry data indicated two groups on the resulting dendrogram, representing 48 samples. Five marker compounds, identified through visual inspection and the construction of a discriminant analysis model, were evident on the ultra-performance liquid chromatography-MS profiles. Four of these compounds were isolated and identified, three as hydroxy methoxyflavones and the fourth as a coumarate, using nuclear magnetic resonance spectroscopy. An ultra-performance liquid chromatography-photodiode array method was developed and validated for the determination of the marker compounds using the isolates as standards. The limits of detection for the four compounds ranged from 0.92 - 2.50 µg/mL. Their recoveries at three concentration levels (1.00, 10.0, and 100 µg/mL) were between 97.0 and 101%, while acceptable intra- and inter-day precision was obtained as reflected by percentage relative standard deviation values below 2.24%. The concentrations of all the marker compounds were found to be higher in samples corresponding to Group 1 of the dendrogram than in those from Group 2. This may be attributable to differences in altitude, climate, and some edaphic factors. Identification of these marker compounds will make a valuable contribution towards the quality control and sustainable commercialisation of bush tea.

Bioimaging for quantitative phenotype analysis.

With the development of bio-imaging techniques, an increasing number of studies apply these techniques to generate a myriad of image data. Its applications range from quantification of cellular, tissue, organismal and behavioral phenotypes of model organisms, to human facial phenotypes. The bio-imaging approaches to automatically detect, quantify, and profile phenotypic changes related to specific biological questions open new doors to studying phenotype-genotype associations and to precisely evaluating molecular changes associated with quantitative phenotypes. Here, we review major applications of bioimage-based quantitative phenotype analysis. Specifically, we describe the biological questions and experimental needs addressable by these analyses, computational techniques and tools that are available in these contexts, and the new perspectives on phenotype-genotype association uncovered by such analyses.