Nonthermal Plasma‐Induced Degradation of Morin and Enhancement of Biological Activities

In the present study, non‐thermal dielectric barrier discharge (DBD) plasma of induced structural changes of morin resulted in the isolation of one previously undescribed benzofuranone derivative, along with two known compounds. The chemical structures of these degradation products were elucidated by UV, NMR and FAB‐MS spectroscopic analyses. The isolated three compounds showed potent antioxidative activities in two different tests, with IC₅₀ values in the range of 12.9–41.8 μm in the 2,2′‐azino‐bis (3‐ethylbenzothiazoline‐6‐sulfonic acid) (ABTS⁺) radical scavenging activity, 19.0–71.9 μm for hydroxyl radical scavenging activity test. Furthermore, the new methoxylated benzofuranone exhibited enhancement of inhibitory effects against pancreatic lipase with an IC₅₀ value of 90.7±1.6 μm , when compared to the parent morin. These results suggested that the degradation products isolated from plasma exposed morin might be beneficial for prevention of obesity and related diseases.     

后疫情时代全球可持续发展目标加速行动的推动

“SDGs加速行动”是国际组织、政府部门、私营机构和其他利益攸关方为加快落实2030年可持续发展议程采取的全球行动。2019年联合国可持续发展目标峰会后，政府、国际组织、私营部门等提出了214项SDGs加速行动。2019年爆发的新型冠状病毒肺炎（Corona Virus Disease 2019，COVID-19）对实现可持续发展目标带来了系列影响，后疫情时代如何推动全球SDGs加速行动的实施成为重要的问题。对可持续发展评估报告（2019）和可持续发展目标加速行动等政策文件进行信息提取，建立加速行动匹配性指数模型和各国应对新冠疫情的恢复力指数模型，根据匹配性-恢复力分类体系将各国按照17项可持续发展目标分为9类，为推动后疫情时代全球可持续发展目标加速行动提供支撑。研究发现：（1）现有可持续发展目标加速行动的实施与区域需求不匹配，且这种不匹配的情况在COVID-19爆发前已经出现；（2）加速行动的实施受限于现有可持续发展水平和国家经济基础，区域关注的可持续发展目标与其自然地理位置和社会发展水平有着密切的关系，多边组织机构和其他利益攸关方需要在发展中国家大力推动可持续发展加速行动；（3）下一步实施加速行动需要加强国际间的合作，根据分类框架和可持续发展目标的关联关系，分重点推进加速行动的实施，完善可持续发展指标监测体系，分类设立后疫情时代不同时期的阶段目标，分阶段循序渐进，定期反馈追踪，以在2030年促进17项可持续目标的实现。     

Adipose-derived mesenchymal stem cells induced PAX8 promotes ovarian cancer cell growth by stabilizing TAZ protein

Our previous studies have shown that the Adipose-derived mesenchymal stem cells (ADSCs) can regulate metastasis and development of ovarian cancer. However, its specific mechanism has yet to be fully revealed. In this study, an RNA-seq approach was adopted to compare the differences in mRNA levels in ovarian cancer cells being given or not given ADSCs. The mRNA level of paired box 8 (PAX8) changed significantly and was confirmed as an important factor in tumour-inducing effect of ADSCs. In comparison with the ovarian cancer cells cultured in the common growth medium, those cultured in the medium supplemented with ADSCs showed a significant increase of the PAX8 level. Moreover, the cancer cell growth could be restricted, even in the ADSC-treated group (P < .05), by inhibiting PAX8. In addition, an overexpression of PAX8 could elevate the proliferation of ovarian cancer cells. Moreover, Co-IP assays in ovarian cancer cells revealed that an interaction existed between endogenous PAX8 and TAZ. And the PAX8 levels regulated the degradation of TAZ. The bioluminescence images captured in vivo manifested that the proliferation and the PAX8 expression level in ovarian cancers increased in the ADMSC-treated group, and the effect of ADSCs in promoting tumours was weakened through inhibiting PAX8. Our findings indicate that the PAX8 expression increment could contribute a role in promoting the ADSC-induced ovarian cancer cell proliferation through TAZ stability regulation.     

A Novel Strategy for Gene Selection of Microarray Data Based on Gene-to-Class Sensitivity Information

To obtain predictive genes with lower redundancy and better interpretability, a hybrid gene selection method encoding prior information is proposed in this paper. To begin with, the prior information referred to as gene-to-class sensitivity (GCS) of all genes from microarray data is exploited by a single hidden layered feedforward neural network (SLFN). Then, to select more representative and lower redundant genes, all genes are grouped into some clusters by K-means method, and some low sensitive genes are filtered out according to their GCS values. Finally, a modified binary particle swarm optimization (BPSO) encoding the GCS information is proposed to perform further gene selection from the remainder genes. For considering the GCS information, the proposed method selects those genes highly correlated to sample classes. Thus, the low redundant gene subsets obtained by the proposed method also contribute to improve classification accuracy on microarray data. The experiments results on some open microarray data verify the effectiveness and efficiency of the proposed approach.     

Curcumin improves memory deficits by inhibiting HMGB1-RAGE/TLR4-NF-κB signalling pathway in APPswe/PS1dE9 transgenic mice hippocampus

Amyloid-β (Aβ) deposition in the brain has been implicated in the development of Alzheimer's disease (AD), and neuroinflammation generates AD progression. Therapeutic effects of anti-inflammatory approaches in AD are still under investigation. Curcumin, a potent anti-inflammatory and antioxidant, has demonstrated therapeutic potential in AD models. However, curcumin's anti-inflammatory molecular mechanisms and its associated cognitive impairment mechanisms in AD remain unclear. The high-mobility group box-1 protein (HMGB1) participates in the regulation of neuroinflammation. Herein, we attempted to evaluate the anti-inflammatory effects of chronic oral administration of curcumin and HMGB1 expression in APP/PS1 transgenic mice AD model. We found that transgenic mice treated with a curcumin diet had shorter escape latencies and showed a significant increase in percent alternation, when compared with transgenic mice, in the Morris water maze and Y-maze tests. Additionally, curcumin treatment could effectively decrease HMGB1 protein expression, advanced glycosylation end product-specific receptor (RAGE), Toll-like receptors-4 (TLR4) and nuclear factor kappa B (NF-κB) in transgenic mice hippocampus. However, amyloid plaques detected with thioflavin-S staining in transgenic mice hippocampus were not affected by curcumin treatment. In contrast, curcumin significantly decreased GFAP-positive cells, as assessed by immunofluorescence staining. Taken together, these data indicate that oral administration of curcumin may be a promising agent to attenuate memory deterioration in AD mice, probably inhibiting the HMGB1-RAGE/TLR4-NF-κB inflammatory signalling pathway.     

Stimulus-Specific Adaptation at the Synapse Level In Vitro

Stimulus-specific adaptation (SSA) is observed in many brain regions in humans and animals. SSA of cortical neurons has been proposed to accumulate through relays in ascending pathways. Here, we examined SSA at the synapse level using whole-cell patch-clamp recordings of primary cultured cortical neurons of the rat. First, we found that cultured neurons had high firing capability with 100-Hz current injection. However, neuron firing started to adapt to repeated electrically activated synaptic inputs at 10 Hz. Next, to activate different dendritic inputs, electrical stimulations were spatially separated. Cultured neurons showed similar SSA properties in the oddball stimulation paradigm compared to those reported in vivo. Single neurons responded preferentially to a deviant stimulus over repeated, standard stimuli considering both synapse-driven spikes and excitatory postsynaptic currents (EPSCs). Compared with two closely placed stimulating electrodes that activated highly overlapping dendritic fields, two separately placed electrodes that activated less overlapping dendritic fields elicited greater SSA. Finally, we used glutamate puffing to directly activate postsynaptic glutamate receptors. Neurons showed SSA to two separately placed puffs repeated at 10 Hz. Compared with EPSCs, GABAa receptor-mediated inhibitory postsynaptic currents showed weaker SSA. Heterogeneity of the synaptic inputs was critical for producing SSA, with glutamate receptor desensitization participating in the process. Our findings suggest that postsynaptic fatigue contributes largely to SSA at low frequencies.     

Modeling drug response using network-based personalized treatment prediction (NetPTP) with applications to inflammatory bowel disease

For many prevalent complex diseases, treatment regimens are frequently ineffective. For example, despite multiple available immunomodulators and immunosuppressants, inflammatory bowel disease (IBD) remains difficult to treat. Heterogeneity in the disease across patients makes it challenging to select the optimal treatment regimens, and some patients do not respond to any of the existing treatment choices. Drug repurposing strategies for IBD have had limited clinical success and have not typically offered individualized patient-level treatment recommendations. In this work, we present NetPTP, a Network-based Personalized Treatment Prediction framework which models measured drug effects from gene expression data and applies them to patient samples to generate personalized ranked treatment lists. To accomplish this, we combine publicly available network, drug target, and drug effect data to generate treatment rankings using patient data. These ranked lists can then be used to prioritize existing treatments and discover new therapies for individual patients. We demonstrate how NetPTP captures and models drug effects, and we apply our framework to individual IBD samples to provide novel insights into IBD treatment.