Promising applications of cold plasma for microbial safety,chemical decontamination and quality enhancement in fruits

Consumers’ demand is increasing for safe foods without impairing the phytochemical and sensory quality. In turn, it has increased research interest in the exploration of innovative food processing technologies. Cold plasma technology is getting popularity now days owing to its high efficacy in decontamination of microbes in fruit and fruit-based products. As a on-thermal approach, plasma processing maintains the quality of fruits and minimizes the thermal effects on nutritional properties. Cold plasma is also exploited for inactivating enzymes and degrading pesticides as both are directly related with quality loss and presently are most important concerns in fresh produce industry. The present review covers the influence of cold plasma technology on reducing microbial risks and enhancing the quality attributes in fruits.     

The C‐degron pathway eliminates mislocalized proteins and products of deubiquitinating enzymes

Protein termini are determinants of protein stability. Proteins bearing degradation signals, or degrons, at their amino‐ or carboxyl‐termini are eliminated by the N‐ or C‐degron pathways, respectively. We aimed to elucidate the function of C‐degron pathways and to unveil how normal proteomes are exempt from C‐degron pathway‐mediated destruction. Our data reveal that C‐degron pathways remove mislocalized cellular proteins and cleavage products of deubiquitinating enzymes. Furthermore, the C‐degron and N‐degron pathways cooperate in protein removal. Proteome analysis revealed a shortfall in normal proteins targeted by C‐degron pathways, but not of defective proteins, suggesting proteolysis‐based immunity as a constraint for protein evolution/selection. Our work highlights the importance of protein termini for protein quality surveillance, and the relationship between the functional proteome and protein degradation pathways.     

Involvement of Putrescine,Nitric Oxide,and Hydrogen Peroxide in Methyl Jasmonate-Induced Ginsenoside Synthesis in Adventitious Root Cultures of Panax ginseng C.A. Meyer

Journal of Plant Growth Regulation - The adventitious root (AR) culture of Panax ginseng C.A. Meyer is an alternative route for mass production of ginsenosides. During the AR culture of P. ginseng,...     

Genomic regions associated with microdeletion/microduplication syndromes exhibit extreme diversity of structural variation

Segmental duplications (SDs) are a class of long, repetitive DNA elements whose paralogs share a high level of sequence similarity with each other. SDs mediate chromosomal rearrangements that lead to structural variation in the general population as well as genomic disorders associated with multiple congenital anomalies, including the 7q11.23 (Williams–Beuren Syndrome, WBS), 15q13.3, and 16p12.2 microdeletion syndromes. Population-level characterization of SDs has generally been lacking because most techniques used for analyzing these complex regions are both labor and cost intensive. In this study, we have used a high-throughput technique to genotype complex structural variation with a single molecule, long-range optical mapping approach. We characterized SDs and identified novel structural variants (SVs) at 7q11.23, 15q13.3, and 16p12.2 using optical mapping data from 154 phenotypically normal individuals from 26 populations comprising five super-populations. We detected several novel SVs for each locus, some of which had significantly different prevalence between populations. Additionally, we localized the microdeletion breakpoints to specific paralogous duplicons located within complex SDs in two patients with WBS, one patient with 15q13.3, and one patient with 16p12.2 microdeletion syndromes. The population-level data presented here highlights the extreme diversity of large and complex SVs within SD-containing regions. The approach we outline will greatly facilitate the investigation of the role of inter-SD structural variation as a driver of chromosomal rearrangements and genomic disorders.     

Childhood rare diseases and the UN convention on the rights of the child

Purpose

The aim of this case control study was to evaluate the prognostic value of automatically quantified retinal vessel tortuosity from fundus images and vessel density from OCT-A in Fabry disease and to evaluate the correlation of these with systemic disease parameters.

Methods

Automatically quantified perimacular retinal vessel tortuosity (MONA REVA software), acquired by fundus imaging, and perifoveal retinal vessel density, acquired by optic coherence tomography angiography (OCT-A) were compared between 26 FD patients and 26 controls. Gender and FD phenotype were analyzed to the obtained retinovascular data and correlated to the Mainz severity score index (MSSI) and plasma lyso-Gb3.

Results

Automatically quantified retinal vessel tortuosity indices of FD patients were significantly lower, reflecting an increased vessel tortuosity, compared to controls (p = 0.008). Males with a classical phenotype showed significantly lower retinal vessel tortuosity indices compared to males with an oligosymptomatic phenotype and females with a classical or oligosymptomatic phenotype (p < 0.001). The retinal vessel tortuosity index correlated significantly with systemic disease severity parameters [global MSSI (r = − 0.5; p < 0.01), cardiovascular MSSI (r = − 0.5; p < 0.01), lyso-Gb3 (r = − 0.6; p < 0.01)].

Conclusion

We advocate fundus imaging based automatically quantified retinal vessel tortuosity index over OCT-A imaging as it is a quick, non-invasive, easily assessable, objective and reproducible marker.

     

Proteomics advances for precision therapy in ovarian cancer

ABSTRACT

Introduction: Due to the relatively low mutation rate and high frequency of copy number variation, finding actionable genetic drivers of high-grade serous carcinoma (HGSC) is a challenging task. Furthermore, emerging studies show that genetic alterations are frequently poorly represented at the protein level adding a layer of complexity. With improvements in large-scale proteomic technologies, proteomics studies have the potential to provide robust analysis of the pathways driving high HGSC behavior.

Areas covered: This review summarizes recent large-scale proteomics findings across adequately sized ovarian cancer sample sets. Key words combined with ‘ovarian cancer’ including ‘proteomics’, ‘proteogenomic’, ‘reverse-phase protein array’, ‘mass spectrometry’, and ‘adaptive response’, were used to search PubMed.

Expert opinion: Proteomics analysis of HGSC as well as their adaptive responses to therapy can uncover new therapeutic liabilities, which can reduce the emergence of drug resistance and potentially improve patient outcomes. There is a pressing need to better understand how the genomic and epigenomic heterogeneity intrinsic to ovarian cancer is reflected at the protein level and how this information could be used to improve patient outcomes.     

Determine the quality of human embryonic stem colonies with laser light scattering patterns

Background

With the prompt developments of regenerative medicine, the potential clinical applications of human embryonic stem cells have attracted intense attention. However, the labor-intensive and complex manual cell selection processes required during embryonic stem cell culturing have seriously limited large-scale production and broad applications. Thus, availability of a label-free, non-invasive platform to replace the current cumbersome manual selection has become a critical need.

Results

A non-invasive, label-free, and time-efficient optical platform for determining the quality of human embryonic stem cell colonies was developed by analyzing the scattering signals from those stem cell colonies. Additionally, confocal microscopy revealed that the cell colony morphology and surface structures were correlated with the resulting characteristic light scattering patterns. Standard immunostaining assay (Oct-4) was also utilized to validate the quality-determination from this light scattering protocol. The platform developed here can therefore provide identification accuracy of up to 87% for colony determination.

Conclusions

Our study here demonstrated that light scattering patterns can serve as a feasible alternative approach to replace conventional manual selection for human embryonic stem cell cultures.     

The impacts of climate change and human activities on biogeochemical cycles on the Qinghai‐Tibetan Plateau

With a pace of about twice the observed rate of global warming, the temperature on the Qinghai‐Tibetan Plateau (Earth's ‘third pole’) has increased by 0.2 °C per decade over the past 50 years, which results in significant permafrost thawing and glacier retreat. Our review suggested that warming enhanced net primary production and soil respiration, decreased methane (CH₄) emissions from wetlands and increased CH₄ consumption of meadows, but might increase CH₄ emissions from lakes. Warming‐induced permafrost thawing and glaciers melting would also result in substantial emission of old carbon dioxide (CO₂) and CH₄. Nitrous oxide (N₂O) emission was not stimulated by warming itself, but might be slightly enhanced by wetting. However, there are many uncertainties in such biogeochemical cycles under climate change. Human activities (e.g. grazing, land cover changes) further modified the biogeochemical cycles and amplified such uncertainties on the plateau. If the projected warming and wetting continues, the future biogeochemical cycles will be more complicated. So facing research in this field is an ongoing challenge of integrating field observations with process‐based ecosystem models to predict the impacts of future climate change and human activities at various temporal and spatial scales. To reduce the uncertainties and to improve the precision of the predictions of the impacts of climate change and human activities on biogeochemical cycles, efforts should focus on conducting more field observation studies, integrating data within improved models, and developing new knowledge about coupling among carbon, nitrogen, and phosphorus biogeochemical cycles as well as about the role of microbes in these cycles.     

The Use of Molecular Analyses in Voided Urine for the Assessment of Patients with Hematuria

Introduction

Patients presenting with painless hematuria form a large part of the urological patient population. In many cases, especially in younger patients, the cause of hematuria is harmless. Nonetheless, hematuria could be a symptom of malignant disease and hence most patients will be subject to cystoscopy. In this study, we aimed to develop a prediction model based on methylation markers in combination with clinical variables, in order to stratify patients with high risk for bladder cancer.

Material and Methods

Patients (n=169) presenting with painless hematuria were included. 54 patients were diagnosed with bladder cancer. In the remaining 115 patients, the cause of hematuria was non-malignant. Urine samples were collected prior to cystoscopy. Urine DNA was analyzed for methylation of OSR1, SIM2, OTX1, MEIS1 and ONECUT2. Methylation percentages were calculated and were combined with clinical variables into a logistic regression model.

Results

Logistic regression analysis based on the five methylation markers, age, gender and type of hematuria resulted in an area under the curve (AUC) of 0.88 and an optimism corrected AUC of 0.84 after internal validation by bootstrapping. Using a cut-off value of 0.307 allowed stratification of patients in a low-risk and high-risk group, resulting in a sensitivity of 82% (44/54) and a specificity of 82% (94/115). Most aggressive tumors were found in patients in the high-risk group. The addition of cytology to the prediction model, improved the AUC from 0.88 to 0.89, with a sensitivity and specificity of 85% (39/46) and 87% (80/92), retrospectively.

Conclusions

This newly developed prediction model could be a helpful tool in risk stratification of patients presenting with painless hematuria. Accurate risk prediction might result in less extensive examination of low risk patients and thereby, reducing patient burden and costs. Further validation in a large prospective patient cohort is necessary to prove the true clinical value of this model.