Pollen grains as a low-cost, green, alternative sorbent for hydrophilic solid-phase extraction.

Many natural products have demonstrated functionality as novel, green sorbents for organic compounds. However, only limited reports exist on the use of such green materials as solid-phase extraction (SPE) sorbents for select organic acids. In this study, we employed pollen grains as a hydrophilic sorbent and investigated the influence of various extraction parameters using a series of experimental designs. The chemical structure and surface properties of the prepared sorbent were investigated by Fourier-transform infrared spectroscopy and scanning electron microscopy. The Plackett-Burman design was used to experimentally screen for parameters that significantly influenced the extraction performance. Three selected parameters were then statistically optimized by applying a central composite design combined with a response surface methodology. Phenolic acid residues were determined and quantified using high performance liquid chromatography with ultraviolet detection; a mass spectrometric detector in the selected ion monitoring mode was also used for identification. As a practical example, phenolic acids in the soil were successfully separated by the developed pollen sorbent. These results therefore indicate that pollen grains can be considered as a sustainable, green, and safe alternative to bare silica for extraction and separation applications.

Isolation and Metabolic Assessment of Cancer Cell Mitochondria.

Mitochondrial metabolism plays an essential role in various biological processes of cancer cells. Herein, we established an experimental procedure for the metabolic assessment of mitochondria in cancer cells. We examined procedures for mitochondrial isolation coupled with various mitochondrial extraction buffers in three major cancer cell lines (PANC1, A549, and MDA-MB-231) and identified a potentially optimal and generalized approach. The purity of the mitochondrial fraction isolated by the selected protocol was verified using specific protein markers of cellular components, and the ultrastructure of the isolated mitochondria was also analyzed by transmission electron microscopy. The isolation procedure, involving a bead beater for cell lysis, a modified sucrose buffer, and differential centrifugation, appeared to be a suitable method for the extraction of mitochondria from cancer cells. Electron micrographs indicated an intact two-layer membrane and inner structures of mitochondria isolated by this procedure. Metabolomic and lipidomic analyses were conducted to examine the metabolic phenotypes of the mitochondria-enriched fractions and associated bulk cancer cells. A total of 44 metabolites, including malate and succinate, occurred at significantly higher levels in the mitochondrial fractions, whereas 51 metabolites, including citrate, oxaloacetate, and fumarate of the Krebs cycle and the oncometabolites glutamine and glutamate, were reduced in mitochondria compared to that in the corresponding bulk cells of PANC1. Similar patterns were observed in mitochondria and bulk cells of MDA-MB-231 and A549 cell lines. A clear difference between the lipid profiles of bulk PANC1, MDA-MB-231, and A549 and corresponding mitochondrial fractions of these cell lines was detected by principal component analysis. In conclusion, we developed an experimental procedure for a large-scale metabolic assessment for suborganelle metabolic profiling and multiple omics data integration in cancer cells with broad applications.

Comprehensive phenotyping and multi-omic profiling in the toxicity assessment of nanopolystyrene with different surface properties.

There is a growing concern regarding the toxic effects of terrestrial nanoplastic contaminants. However, an all-encompassing phenotyping- and omics-based strategy for the toxicity assessment of nanoplastics with different surface properties on soil living organisms remains to be established. Herein, we devised a comprehensive phenotyping and multi-omic profiling method to examine the molecular disturbance of nanopolystyrene (PS)-exposed Caenorhabditis elegans. The exposure time was 24 h with either 1 µg/mL or 10 µg/mL of PS. We found that PS considerably affected the reproduction and locomotion, as well as increased the oxidative stress of worms regardless of their surface properties. Nevertheless, each type of PS affected the metabolome and lipidome of the nematodes differently. Uncharged PS (PS-N) triggered significant metabolic disturbances, whereas the metabolic influences from PS-NH2 and PS-COOH were subtle. The dysregulated transcriptome profiles of PS-N were strongly associated with the metabolic pathways. Besides, the altered expression of several genes associated with autophagy and longevity was observed. Collectively, we demonstrated that comprehensive phenotyping and omics-based profiling establish a practical framework that allows us to gain deeper insights into the maladaptive consequences of PS in nematodes. It can be utilized for the evaluation of other environmental contaminants in the terrestrial ecosystem.

Steroidomics for the Prevention, Assessment, and Management of Cancers: A Systematic Review and Functional Analysis.

Steroidomics, an analytical technique for steroid biomarker mining, has received much attention in recent years. This systematic review and functional analysis, following the PRISMA statement, aims to provide a comprehensive review and an appraisal of the developments and fundamental issues in steroid high-throughput analysis, with a focus on cancer research. We also discuss potential pitfalls and proposed recommendations for steroidomics-based clinical research. Forty-five studies met our inclusion criteria, with a focus on 12 types of cancer. Most studies focused on cancer risk prediction, followed by diagnosis, prognosis, and therapy monitoring. Prostate cancer was the most frequently studied cancer. Estradiol, dehydroepiandrosterone, and cortisol were mostly reported and altered in at least four types of cancer. Estrogen and estrogen metabolites were highly reported to associate with women-related cancers. Pathway enrichment analysis revealed that steroidogenesis; androgen and estrogen metabolism; and androstenedione metabolism were significantly altered in cancers. Our findings indicated that estradiol, dehydroepiandrosterone, cortisol, and estrogen metabolites, among others, could be considered oncosteroids. Despite noble achievements, significant shortcomings among the investigated studies were small sample sizes, cross-sectional designs, potential confounding factors, and problematic statistical approaches. More efforts are required to establish standardized procedures regarding study design, analytical procedures, and statistical inference.

Metabolomics and phenotype assessment reveal cellular toxicity of triclosan in Caenorhabditis elegans.

Triclosan (TCS) is an antibiotic that is added to household and personal care products. Recently, it has become more popular, turning into one of the major contaminants of the environment. This raises a dawning awareness regarding health and environmental issues. In this study, the toxicity of TCS to Caenorhabditis elegans was evaluated using a metabolomics approach. Additionally, the lifespan, locomotion, and reproduction of C. elegans were monitored for a better interpretation of toxic effects. In C. elegans exposed to TCS at the concentration of 1 mg/L, the average lifespan decreased in approximately 3 days. Reproduction and locomotion were also decreased with TCS exposure. The number of progenies, head thrashes, and body bends decreased to 45.15 ±â€¯11.63, 39.60 ±â€¯5.90, and 9.20 ±â€¯1.56 with the exposure to TCS, respectively. Oxidative stress was induced by TCS exposure, which was confirmed by using DAF-16:GFP strain and H2DCF-DA-based ROS assay. Metabolomics analysis revealed that carbohydrates and amino acids related to energy production were considerably affected by TCS exposure. Additionally, levels of tyrosine, serine, and polyamines, responsible for neurotransmitter and stress response, were significantly altered. Collectively, our findings suggest that TCS induces toxic effects by various mechanisms and exerts a strong influence in various phenotypes of the tested model.

Assessment of chemical equivalence in herbal materials using chromatographic fingerprints by combination of three similarity indices and three-dimensional kernel density estimation.

An intuitive and practical way to control chemical equivalence of secondary metabolites in herbal materials based on chromatographic fingerprints deserves a thorough discussion, yet it is relatively unexplored. For the first time, we propose a mixture of three similarity indices, the congruence coefficient, the average of the peak area ratios, and the larger value between the maximum peak area ratio and the reciprocal of the minimum peak area ratio, to make up for the weak points of some widely used similarity indices and to evaluate the chemical equivalence of two fingerprints from various perspectives. The three similarity values are fed into a three-dimensional kernel density estimation to determine the quality of herbal materials. This estimation enables precise detection of anomalies in the absence of prior quality determination experience. Forty Atractylodes samples similar in appearance and indiscriminately used for medical purposes were used to demonstrate the effectiveness of the developed approach. After a reference sample was postulated, a quality assessment of the 40 samples was performed using the three similarity values and the estimated kernel density. The samples that were judged by the developed approach to be of good quality were compared with those chosen by the most popular approach using decision criterion of a single similarity index. The benefits of the proposed approach were evident in that the qualified samples had the composition ratio and individual concentrations of multi-components closer to those of the reference in general, and their inter-sample deviation was significantly smaller.

Association between the symptoms of benign prostatic hyperplasia and social disparities: Does social capital promote prostate health?

This cross-sectional study investigated the relationships between socioeconomic factors and social capital and benign prostatic hyperplasia symptoms. The participants were 100,000 adult men who participated in the Korea Community Health Survey. The surveyors used the International Prostate Symptom Score. As regards occupation, the prevalence of benign prostatic hyperplasia was higher in men with blue-collar occupations or those who were unemployed than in those with white-collar jobs. In terms of marital status, the prevalence of benign prostatic hyperplasia was 1.319 times higher among divorced men than married men. As regards social capital, the prevalence of benign prostatic hyperplasia in men with positive attitudes towards one's community scores that reflected good, poor and very poor community scores was 1.228, 1.246 and 1.447 times higher than that of men who had very good scores respectively. The groups with good, poor, and very poor community participation scores had 1.115, 1.202 and 1.364 times higher prevalence of benign prostatic hyperplasia than the group with very good scores. Social disparities and social capital of a community were associated with the prevalence of benign prostatic hyperplasia. Thus, the use of social capital in the community setting will be effective in the management of the condition.

Development and assessment of a lysophospholipid-based deep learning model to discriminate geographical origins of white rice.

Geographical origin determination of white rice has become the major issue of food industry. However, there is still lack of a high-throughput method for rapidly and reproducibly differentiating the geographical origins of commercial white rice. In this study, we developed a method that employed lipidomics and deep learning to discriminate white rice from Korea to China. A total of 126 white rice of 30 cultivars from different regions were utilized for the method development and validation. By using direct infusion-mass spectrometry-based targeted lipidomics, 17 lysoglycerophospholipids were simultaneously characterized within minutes per sample. Unsupervised data exploration showed a noticeable overlap of white rice between two countries. In addition, lysophosphatidylcholines (lysoPCs) were prominent in white rice from Korea while lysophosphatidylethanolamines (lysoPEs) were enriched in white rice from China. A deep learning prediction model was built using 2014 white rice and validated using two different batches of 2015 white rice. The model accurately discriminated white rice from two countries. Among 10 selected predictors, lysoPC(18:2), lysoPC(14:0), and lysoPE(16:0) were the three most important features. Random forest and gradient boosting machine models also worked well in this circumstance. In conclusion, this study provides an architecture for high-throughput classification of white rice from different geographical origins.

Systematic assessment of cervical cancer initiation and progression uncovers genetic panels for deep learning-based early diagnosis and proposes novel diagnostic and prognostic biomarkers.

Although many outstanding achievements in the management of cervical cancer (CxCa) have obtained, it still imposes a major burden which has prompted scientists to discover and validate new CxCa biomarkers to improve the diagnostic and prognostic assessment of CxCa. In this study, eight different gene expression data sets containing 202 cancer, 115 cervical intraepithelial neoplasia (CIN), and 105 normal samples were utilized for an integrative systems biology assessment in a multi-stage carcinogenesis manner. Deep learning-based diagnostic models were established based on the genetic panels of intrinsic genes of cervical carcinogenesis as well as on the unbiased variable selection approach. Survival analysis was also conducted to explore the potential biomarker candidates for prognostic assessment. Our results showed that cell cycle, RNA transport, mRNA surveillance, and one carbon pool by folate were the key regulatory mechanisms involved in the initiation, progression, and metastasis of CxCa. Various genetic panels combined with machine learning algorithms successfully differentiated CxCa from CIN and normalcy in cross-study normalized data sets. In particular, the 168-gene deep learning model for the differentiation of cancer from normalcy achieved an externally validated accuracy of 97.96% (99.01% sensitivity and 95.65% specificity). Survival analysis revealed that ZNF281 and EPHB6 were the two most promising prognostic genetic markers for CxCa among others. Our findings open new opportunities to enhance current understanding of the characteristics of CxCa pathobiology. In addition, the combination of transcriptomics-based signatures and deep learning classification may become an important approach to improve CxCa diagnosis and management in clinical practice.

Determination of PDE-5 inhibitors and appetite suppressants in adulterated dietary supplements using LC/PDA and LC/MS.

There have been a number of reports of dietary supplements contaminated with illegal adulterants that threaten consumers' health because of their adverse pharmacological effects. In the present study, a convenient and economic method was developed to detect illegal pharmaceutics, such as PDE-5 inhibitor and appetite suppressants, using liquid chromatography (LC)/photodiode array (PDA) for screening and LC/mass spectrometry (MS) for successive confirmation. Target peaks were identified by comparison of their chromatographic retention times and PDA spectra with those of synthetic standards and finally confirmed by LC/MS. As a result, tadalafil, a PDE-5 inhibitor, and N-desmethylsibutramine, a derivative of sibutramine, were detected in various dietary supplements at concentrations of 13.5-21.9 mg and 3.0 mg per single dose, respectively. The present study will contribute to the development of an analytical method enabling rapid screening of a variety of health foods, and the result suggests that consumers should be aware of serious health risks related to these illegal compounds.

Determination of volatile biomarkers for apoptosis and necrosis by solid-phase microextraction-gas chromatography/mass spectrometry: a pharmacometabolomic approach to cisplatin's cytotoxicity to human lung cancer cell lines.

In order to find potential new biomarkers of cisplatin-induced apoptosis and necrosis, volatile organic compounds (VOCs) from cisplatin-treated human lung cancer cell lines were investigated. The biological system employed was human non-small cell lung carcinoma A549 cell lines. The cell lines were treated with two different concentrations of cisplatin, 100 microM and 400 microM, and apoptosis and necrosis were determined by flow cytometric analysis. For each drug concentration, the VOCs from the treated cell lines were extracted by solid-phase microextraction (SPME), and subsequently analyzed by gas chromatography/mass spectrometry (GC/MS). The compounds that change during cisplatin-induced apoptosis and necrosis of lung cancer cell lines can serve as new biomarkers. The pharmacometabolomic approach presented in this study, significantly, implicates a non-destructive, sample-thrifty and time-saving tool for finding new biomarkers for the assessment of drug-induced cell death pathways.