Effect of menthol on human temperature sensitivity

Application of 1% methol, which, along with cold, activates specific thermosensitive ionic channels, changes the number of functioning cold receptors on the skin of the forearm similarly to the cold exposure test; however, it does not affect the number of heat receptors and does not significantly change the threshold of cold sensation. Group variants of responses to menthol that indicate individual differences in the sensitivity of skin receptors to the effects of methol and cold have been found. The results obtained give grounds to suggest that, from the variant of response to menthol (a decrease, increase, or absence of changes in the number of functioning cold receptors 5 min after menthol application), it is possible to predict specific features of response to cold.     

Multiomic Metabolic Enrichment Network Analysis Reveals Metabolite–Protein Physical Interaction Subnetworks Altered in Cancer

Metabolism is recognized as an important driver of cancer progression and other complex diseases, but global metabolite profiling remains a challenge. Protein expression profiling is often a poor proxy since existing pathway enrichment models provide an incomplete mapping between the proteome and metabolism. To overcome these gaps, we introduce multiomic metabolic enrichment network analysis (MOMENTA), an integrative multiomic data analysis framework for more accurately deducing metabolic pathway changes from proteomics data alone in a gene set analysis context by leveraging protein interaction networks to extend annotated metabolic models. We apply MOMENTA to proteomic data from diverse cancer cell lines and human tumors to demonstrate its utility at revealing variation in metabolic pathway activity across cancer types, which we verify using independent metabolomics measurements. The novel metabolic networks we uncover in breast cancer and other tumors are linked to clinical outcomes, underscoring the pathophysiological relevance of the findings.     

严重急性呼吸综合征冠状病毒2膜蛋白对宿主细胞pre-mRNA 3"UTR加工的影响

目的 研究严重急性呼吸综合征冠状病毒2（SARS-CoV-2）膜蛋白对宿主细胞mRNA前体（pre-mRNA）3"非翻译区（UTR）加工的影响。方法 本研究以人肺上皮细胞系A549为模型，利用瞬时转染在细胞内过表达SARS-CoV-2膜蛋白；利用RNA-Seq测序技术及生物信息学分析方法，系统性描绘宿主细胞选择性多聚腺苷酸化（alternative polyadenylation，APA）事件；Metascape数据库对发生显著APA变化的基因进行功能富集分析；RT-qPCR验证靶基因3"UTR长度变化；蛋白质免疫印迹（Western blot）检测目的蛋白表达水平。结果 SARS-CoV-2膜蛋白外源表达后宿主细胞内共813个基因发生显著APA变化。GO和KEGG分析显示，差异APA基因广泛参与有丝分裂细胞周期、调节细胞应激等生物过程，涉及病毒感染和蛋白质加工等。从中进一步筛选出AKT1基因，在IGV软件中显示3"UTR延长；RT-qPCR验证AKT1基因的3"UTR长度变化趋势；Western blot结果显示AKT1蛋白磷酸化水平增加。结论 SARS-CoV-2膜蛋白潜在影响宿主pre-mRNA的3"UTR加工，其中参与多种病毒性生物过程的AKT1基因 3"UTR延长，且其编码的蛋白质功能在细胞内被激活。     

Comparative analysis of respiratory activity in the wild type strain of <Emphasis Type="Italic">Neurospora crassa</Emphasis> and its photoreceptor complex mutants

Cell respiratory activity of protoplasts obtained from the wild type of Neurospora crassa and photoreceptor complex WCC—white collar 1 (wc-1) and white collar 2 (wc-2)—mutants of Neurospora crassa strains was investigated. Respiration inhibition by KCN in the presence of 25 mM succinate was similar in all strains and did not exceed 83–85% against control. The significant induction of KCN-resistant respiratory pathway occurred under 1% glucose oxidation in wc-1 and wc-2 mutants if compared with the wild type strains. The inhibitors of the main (cytochrome) pathway of electron transfer in mitochondria—1 mM KCN and antimycin A (4 μg/ml)—blocked the respiration rate of the protoplasts from N. crassa wild type by 75%, while the cell respiration of wc-1 and wc-2 strains was suppressed by approximately 50%. The specific inhibitor of alternative oxidase—10 mM salicylhydroxamic acid (SHAM)—in combination with the blockers of mitochondrial electron transfer chain caused the total suppression of respiratory activity of protoplasts in all studied strains. It is supposed that an increase of KCN-resistance in WCC mutants under glucose oxidation is connected with alternative oxidase activation as the result of failure in reception and signal transduction of active oxygen species.     

A study on giant panda recognition based on images of a large proportion of captive pandas

1. As a highly endangered species, the giant panda (panda) has attracted significant attention in the past decades. Considerable efforts have been put on panda conservation and reproduction, offering the promising outcome of maintaining the population size of pandas. To evaluate the effectiveness of conservation and management strategies, recognizing individual pandas is critical. However, it remains a challenging task because the existing methods, such as traditional tracking method, discrimination method based on footprint identification, and molecular biology method, are invasive, inaccurate, expensive, or challenging to perform. The advances of imaging technologies have led to the wide applications of digital images and videos in panda conservation and management, which makes it possible for individual panda recognition in a noninvasive manner by using image‐based panda face recognition method.
2. In recent years, deep learning has achieved great success in the field of computer vision and pattern recognition. For panda face recognition, a fully automatic deep learning algorithm which consists of a sequence of deep neural networks (DNNs) used for panda face detection, segmentation, alignment, and identity prediction is developed in this study. To develop and evaluate the algorithm, the largest panda image dataset containing 6,441 images from 218 different pandas, which is 39.78% of captive pandas in the world, is established.
3. The algorithm achieved 96.27% accuracy in panda recognition and 100% accuracy in detection.
4. This study shows that panda faces can be used for panda recognition. It enables the use of the cameras installed in their habitat for monitoring their population and behavior. This noninvasive approach is much more cost‐effective than the approaches used in the previous panda surveys.

     

20-hydroxyecdysone accumulation and regulation in Ajuga lobata D. Don suspension culture

Suspension culture of Ajuga lobata D. Don cells provides a method of synthesis of the phytoecdysteroid 20-hydroxyecdysone (20E) which can regulate the molting process of larvae. We characterized the culture conditions to optimize 20E production. Growth of A. lobata D. Don cells fits the logistic equation curve with a growth cycle of 19 days. Medium conductivity was negatively correlated with dry cell weight and 20E accumulation, thus could be used to determine the optimal time for cell harvest. Continuous subculture reduced 20E synthesis, but supplementing medium with 20E precursors mevalonic (MVA), α-Pinene, and nitric oxide (NO) can significantly promote cell growth and influence 20E accumulation. Combination of α-Pinene, MVA, and SNP significantly elevated 20E accumulation, thus may synergistically enhance 20E synthesis in A. lobata D. Don. The optimal concentrations of α-Pinene, MVA, and NO donor SNP in suspension culture were 50 μL L^?1, 10 mg L^?1, and 80 μmol L^?1.     

Mass Collaboration in Earthquake Risk Management

The mechanism of mass collaboration in risk management was studied during the Sichuan earthquake under a Web-based “PeopleFinder” project, where information is contributed and shared among mass contributors. The case study is provided by a great earthquake that happened in Wenchuan County, Sichuan Province, of southwestern China at 2:28 p.m. on May 12, 2008. We witnessed and experienced the rescue and relief efforts for the great earthquake. In this article, two fundamental frameworks are developed to study the mechanism of mass collaboration. Mass collaboration is proven to be effective in a big public crisis such as the Sichuan earthquake.     

Biopolymer of alginate nature with a predominance of L-guluronic acid

Highly viscous polysaccharide (250–350 kDa) of an alginate nature with a predominance of α-L-guluronic acid (M/G = 0.22) was obtained from Azotobacter vinelandi. The yield of polysaccharide was 20.5 ± 0.5 g/l when cultured in a medium containing molasses at a viscosity of the cultural liquid of over 30000 cSt. The biopolymer is stable at pH 4.0–9.0 in a wide temperature range and well soluble in highly mineralized water; it retains a high viscosity level and can be used in the petroleum industry for enhanced oil recovery.