呫吨酮并吡啶衍生物XP-15联合紫杉醇对耐药肝癌细胞QGY-7701 的体外抑制作用

目的:探索呫吨酮并吡啶衍生物XP-15联合紫杉醇对人肝癌QGY-7701耐药细胞株的体外抗肿瘤作用。方法:运用CCK8法、Transwell实验和流式细胞仪检测凋亡技术观察细胞功能学变化，运用Western Blot蛋白免疫印迹技术探索其可能的作用机制。结果:XP-15可明显增强紫杉醇对耐药QGY-7701细胞的抑制作用，XP-15联合紫杉醇作用于耐药QGY-7701细胞24 h后，QGY-7701细胞活力明显减弱，且其侵袭迁移能力明显降低，同时流式细胞仪凋亡检测提示细胞凋亡百分比明显增加。Western Blot蛋白免疫印迹亦证实细胞抗凋亡蛋白bcl-2表达明显降低，肝癌增殖分化相关PI3K及AKT蛋白分子表达减少。结论:XP-15具有增敏紫杉醇诱导耐药QGY-7701细胞凋亡同时抑制其增殖活力的作用，其作用机制可能与下调PI3K-AKT通路活性，同时减少bcl-2抑制凋亡蛋白表达相关。     

The role of lncRNA MSC-AS1/miR-29b-3p axis-mediated CDK14 modulation in pancreatic cancer proliferation and Gemcitabine-induced apoptosis

Pancreatic ductal adenocarcinoma (PDAC) remains a leading cause of cancer-related death due to the failure of traditional therapies. In the present study, we attempted to construct a lncRNA-miRNA-mRNA network which may modulate PDAC cell proliferation and Gemcitabine-induced cell apoptosis starting from CDK14, a new member of the CDK family and an oncogene in many cancers. Based on TCGA data, a significant positive correlation was observed between lncRNA MSC-AS1 and CDK14. Moreover, MSC-AS1 expression was upregulated in PDAC tissues. Higher MSC-AS1 expression was correlated with poorer prognosis in patients with PDAC. MSC-AS1 knockdown in Panc-1 and BxPC-3 cells significantly inhibited the cell proliferation. Moreover, miR-29b-3p, which has been reported to act as a tumor suppressor, was predicted to bind to both MSC-AS1 and CDK14. Contrary to MSC-AS1, higher miR-29b-3p expression was correlated to better prognosis in patients with PDAC. In both PDAC cell lines, miR-29b-3p negatively regulated MSC-AS1 and CDK14. As confirmed using luciferase reporter gene and RIP assays, MSC-AS1 served as a ceRNA for miR-29b-3p to counteract miR-29b-mediated CDK14 repression. MSC-AS1 knockdown inhibited CDK14 protein levels and PDAC proliferation and enhanced gemcitabine-induced cell death and apoptosis while miR-29b-3p inhibition exerted an opposing effect; the effect of MSC-AS1 knockdown was partially attenuated by miR-29b-3p inhibition. Taken together, we demonstrated that MSC-AS1/miR-29b-3p axis modulates the cell proliferation and GEM-induced cell apoptosis in PDAC cell lines through CDK14. We provided a novel experimental basis for PDAC treatment from the perspective of lncRNA-miRNA-mRNA network.     

中药诱导胃癌细胞凋亡的研究进展

胃癌是世界上最常见的恶性肿瘤之一。随着科学技术的发展和人类对健康的需求,国内外对胃癌的研究越来越深入。目前,在胃癌综合治疗中,中医药所发挥的作用越来越大,可明显提高患者的生活质量,并延长生存期。中医药的抗癌机制研究日益受到重视,尤其是诱导癌细胞凋亡的相关作用机制。通过对单味中药及中药复方诱导胃癌细胞凋亡的总结,从而为中医药治疗胃癌的基础机制及临床应用提供指导,促进中医药在临床中治疗胃癌的发展。     

From the Cover: Communication consumes 35 times more energy than computation in the human cortex,but both costs are needed to predict synapse number

Darwinian evolution tends to produce energy-efficient outcomes. On the other hand, energy limits computation, be it neural and probabilistic or digital and logical. Taking a particular energy-efficient viewpoint, we define neural computation and make use of an energy-constrained computational function. This function can be optimized over a variable that is proportional to the number of synapses per neuron. This function also implies a specific distinction between adenosine triphosphate (ATP)-consuming processes, especially computation per se vs. the communication processes of action potentials and transmitter release. Thus, to apply this mathematical function requires an energy audit with a particular partitioning of energy consumption that differs from earlier work. The audit points out that, rather than the oft-quoted 20 W of glucose available to the human brain, the fraction partitioned to cortical computation is only 0.1 W of ATP [L. Sokoloff, Handb. Physiol. Sect. I Neurophysiol. 3, 1843–1864 (1960)] and [J. Sawada, D. S. Modha, “Synapse: Scalable energy-efficient neurosynaptic computing” in Application of Concurrency to System Design (ACSD) (2013), pp. 14–15]. On the other hand, long-distance communication costs are 35-fold greater, 3.5 W. Other findings include 1) a 108-fold discrepancy between biological and lowest possible values of a neuron’s computational efficiency and 2) two predictions of N, the number of synaptic transmissions needed to fire a neuron (2,500 vs. 2,000).

The purpose of the brain is to process information, but that leaves us with the problem of finding appropriate definitions of information processing. We assume that given enough time and given a sufficiently stable environment (e.g., the common internals of the mammalian brain), then Nature’s constructions approach an optimum. The problem is to find which function or combined set of functions is optimal when incorporating empirical values into these function(s). The initial example in neuroscience is ref. 1, which shows that information capacity is far from optimized, especially in comparison to the optimal information per joule which is in much closer agreement with empirical values. Whenever we find such an agreement between theory and experiment, we conclude that this optimization, or near optimization, is Nature’s perspective. Using this strategy, we and others seek quantified relationships with particular forms of information processing and require that these relationships are approximately optimal (1–7). At the level of a single neuron, a recent theoretical development identifies a potentially optimal computation (8). To apply this conjecture requires understanding certain neuronal energy expenditures. Here the focus is on the energy budget of the human cerebral cortex and its primary neurons. The energy audit here differs from the premier earlier work (9) in two ways: The brain considered here is human not rodent, and the audit here uses a partitioning motivated by the information-efficiency calculations rather than the classical partitions of cell biology and neuroscience (9). Importantly, our audit reveals greater energy use by communication than by computation. This observation in turn generates additional insights into the optimal synapse number. Specifically, the bits per joule optimized computation must provide sufficient bits per second to the axon and presynaptic mechanism to justify the great expense of timely communication. Simply put from the optimization perspective, we assume evolution would not build a costly communication system and then not supply it with appropriate bits per second to justify its costs. The bits per joule are optimized with respect to N, the number of synaptic activations per interpulse interval (IPI) for one neuron, where N happens to equal the number of synapses per neuron times the success rate of synaptic transmission (below).To measure computation, and to partition out its cost, requires a suitable definition at the single-neuron level. Rather than the generic definition “any signal transformation” (3) or the neural-like “converting a multivariate signal to a scalar signal,” we conjecture a more detailed definition (8). To move toward this definition, note two important brain functions: estimating what is present in the sensed world and predicting what will be present, including what will occur as the brain commands manipulations. Then, assume that such macroscopic inferences arise by combining single-neuron inferences. That is, conjecture a neuron performing microscopic estimation or prediction. Instead of sensing the world, a neuron’s sensing is merely its capacitive charging due to recently active synapses. Using this sampling of total accumulated charge over a particular elapsed time, a neuron implicitly estimates the value of its local latent variable, a variable defined by evolution and developmental construction (8). Applying an optimization perspective, which includes implicit Bayesian inference, a sufficient statistic, and maximum-likelihood unbiasedness, as well as energy costs (8), produces a quantified theory of single-neuron computation. This theory implies the optimal IPI probability distribution. Motivating IPI coding is this fact: The use of constant amplitude signaling, e.g., action potentials, implies that all information can only be in IPIs. Therefore, no code can outperform an IPI code, and it can equal an IPI code in bit rate only if it is one to one with an IPI code. In neuroscience, an equivalent to IPI codes is the instantaneous rate code where each message is IPI−1. In communication theory, a discrete form of IPI coding is called differential pulse position modulation (10); ref. 11 explicitly introduced a continuous form of this coding as a neuron communication hypothesis, and it receives further development in ref. 12.Results recall and further develop earlier work concerning a certain optimization that defines IPI probabilities (8). An energy audit is required to use these developments. Combining the theory with the audit leads to two outcomes: 1) The optimizing N serves as a consistency check on the audit and 2) future energy audits for individual cell types will predict N for that cell type, a test of the theory. Specialized approximations here that are not present in earlier work (9) include the assumptions that 1) all neurons of cortex are pyramidal neurons, 2) pyramidal neurons are the inputs to pyramidal neurons, 3) a neuron is under constant synaptic bombardment, and 4) a neuron’s capacitance must be charged 16 mV from reset potential to threshold to fire.Following the audit, the reader is given a perspective that may be obvious to some, but it is rarely discussed and seemingly contradicts the engineering literature (but see ref. 6). In particular, a neuron is an incredibly inefficient computational device in comparison to an idealized physical analog. It is not just a few bits per joule away from optimal predicted by the Landauer limit, but off by a huge amount, a factor of 108. The theory here resolves the efficiency issue using a modified optimization perspective. Activity-dependent communication and synaptic modification costs force upward optimal computational costs. In turn, the bit value of the computational energy expenditure is constrained to a central limit like the result: Every doubling of N can produce no more than 0.5 bits. In addition to 1) explaining the 108 excessive energy use, other results here include 2) identifying the largest “noise” source limiting computation, which is the signal itself, and 3) partitioning the relevant costs, which may help engineers redirect focus toward computation and communication costs rather than the 20-W total brain consumption as their design goal.     

Quantitative Automated Segmentation of Lipiodol Deposits on Cone-Beam CT Imaging Acquired during Transarterial Chemoembolization for Liver Tumors: A Deep Learning Approach

PurposeTo show that a deep learning (DL)–based, automated model for Lipiodol (Guerbet Pharmaceuticals, Paris, France) segmentation on cone-beam computed tomography (CT) after conventional transarterial chemoembolization performs closer to the “ground truth segmentation” than a conventional thresholding-based model.Materials and MethodsThis post hoc analysis included 36 patients with a diagnosis of hepatocellular carcinoma or other solid liver tumors who underwent conventional transarterial chemoembolization with an intraprocedural cone-beam CT. Semiautomatic segmentation of Lipiodol was obtained. Subsequently, a convolutional U-net model was used to output a binary mask that predicted Lipiodol deposition. A threshold value of signal intensity on cone-beam CT was used to obtain a Lipiodol mask for comparison. The dice similarity coefficient (DSC), mean squared error (MSE), center of mass (CM), and fractional volume ratios for both masks were obtained by comparing them to the ground truth (radiologist-segmented Lipiodol deposits) to obtain accuracy metrics for the 2 masks. These results were used to compare the model versus the threshold technique.ResultsFor all metrics, the U-net outperformed the threshold technique: DSC (0.65 ± 0.17 vs 0.45 ± 0.22, P < .001) and MSE (125.53 ± 107.36 vs 185.98 ± 93.82, P = .005). The difference between the CM predicted and the actual CM was 15.31 mm ± 14.63 versus 31.34 mm ± 30.24 (P < .001), with lesser distance indicating higher accuracy. The fraction of volume present ([predicted Lipiodol volume]/[ground truth Lipiodol volume]) was 1.22 ± 0.84 versus 2.58 ± 3.52 (P = .048) for the current model’s prediction and threshold technique, respectively.ConclusionsThis study showed that a DL framework could detect Lipiodol in cone-beam CT imaging and was capable of outperforming the conventionally used thresholding technique over several metrics. Further optimization will allow for more accurate, quantitative predictions of Lipiodol depositions intraprocedurally.     

糖尿病视网膜病变中视网膜内皮细胞功能障碍的研究进展北大核心

视网膜内皮细胞(REC)是参与糖尿病视网膜病变和许多眼部疾病的主要细胞类型之一。视网膜微血管系统有助于血-视网膜屏障的维持,这对正常的视功能至关重要。REC的改变在视网膜疾病的发生发展中起着关键作用。高血糖是糖尿病微血管损伤的重要原因,通过不同的机制导致REC功能障碍,包括向衰老表型改变、迁移和增殖能力增强、炎性凋亡等,最终导致无细胞毛细血管及病理性新生血管形成。本文对糖尿病视网膜病变中REC的功能障碍作一综述。     

LncRNA XIST acts as a MicroRNA-520 sponge to regulate the Cisplatin resistance in NSCLC cells by mediating BAX through CeRNA network

Background: In recent years, LncRNA acts as a member of competing endogenous RNA (ceRNA), playing an important role in drug resistance of lung cancer. The aim of this study was to identify potential biomarkers about cisplatin resistant lung cancer cells using a comprehensive ceRNA network.Methods: {"type":"entrez-geo","attrs":{"text":"GSE6410","term_id":"6410"}}GSE6410 (GPL-201) analyzed gene expression changes about cisplatin resistance in A549 NSCLC cells. {"type":"entrez-geo","attrs":{"text":"GSE43249","term_id":"43249"}}GSE43249 (GPL-14613) included noncoding RNA expression profiling derived from the cisplatin resistant A549 lung cells. GEO2R, an online analysis tool, analyzed the differentially expressed mRNAs and miRNAs (DEmRNAs and DEmiRNAs). To explore the functional enrichment implication of differentially expressed mRNAs, we used the GO (Gene ontology) and KEGG (Kyoto Encyclopedia of Genes and Genomes) pathway analysis. Through miRDB, Targetscan, Starbase and miRWalk, we found targeted miRNAs. The Kaplan-Meier curve method was used to show clinical survival analysis of targeted RNAs (P<0.05). The Starbase database predicted potential lncRNAs mediated targeted miRNAs. Eventually, the novel ceRNA network of lncRNAs, miRNAs, mRNA was constructed by cytoscape3.7.2.Results: 118 differentially expressed mRNAs were the basis of the mediated ceRNA network. DAVID and Kaplan-Meier picked out BAX, an apoptosis regulator. Venn diagram demonstrated 8 miRNAs commonly regulating BAX. Starbase predicted lncRNA XIST mediated miRNAs. Finally, lncRNA XIST may be a useful biomarker regulating cisplatin resistance in lung cancer cells and further, we explored the BAX may effect tumor-infiltrating immune cells.Conclusions: LncRNA XIST competitively bound to miRNA 520 in the regulation of cisplatin resistance by BAX, participating apoptosis in the p53 signaling pathway.     

白藜芦醇联合顺铂对神经胶质瘤细胞的作用*

目的： 探讨白藜芦醇联合顺铂对神经胶质瘤细胞C6 的作用。方法：不同浓度的白藜芦醇与顺铂单独联合 作用于神经胶质瘤细胞C6，24、48 h 和72 h 后，CCK8法检测增殖，并选出合适浓度进行后续试验；不同浓度的 药物作用于细胞24 h 后，吖啶橙法观察细胞形态变化、流式细胞仪检测细胞凋亡、细胞周期和免疫印迹检测蛋白 Bax、Bcl-2 和p-Erk1/2 变化。结果：白藜芦醇与顺铂能协同抑制神经胶质瘤细胞C6 的增殖。联合用药后细胞周 期抑制在S 期。免疫印迹结果显示凋亡蛋白Bax 的表达量增加，而凋亡抑制蛋白Bcl-2 的表达量减少，细胞外调 节蛋白激酶p-Erk1/2 的表达量减少。结论：白藜芦醇与顺铂联合对神经胶质瘤细胞具有相互增敏作用，能够协同 抑制细胞增殖，并通过Ras-Raf-MEK-Erk 信号通路促进其凋亡。     

妊娠期糖尿病中胎盘外泌体对滋养细胞增殖、细胞周期及凋亡的影响*

目的：探讨妊娠期糖尿病（GDM）中胎盘外泌体对滋养细胞增殖、细胞周期及细胞凋亡的影响。方法： 选取2018 年3 月至2019 年4 月间重庆市第七人民医院50 例诊断为GDM患者（GDM组），另选取50 例正常孕产 妇作为对照组。分离纯化GDM组和对照组孕产妇外周血血浆中的胎盘外泌体，通过透射电镜观察外泌体的形 态，纳米粒径分析检测外泌体的直径，免疫印迹检测外泌体标志性蛋白CD63、TSG101 及胎盘标志性分子胎盘 碱性磷酸酶（PLAP）的表达。PKH67染色后荧光共聚焦显微镜观察体外培养滋养细胞系对外泌体的摄取情况； 应用MTT实验检测外泌体对滋养细胞增殖能力的影响，流式细胞术检测外泌体对滋养细胞周期的影响，Annexin V-FITC/PI 双染色结合流式细胞术检测外泌体对滋养细胞凋亡的影响。结果：成功从外周血中分离获得了胎盘外 泌体，形态呈典型的杯状或双凹状，直径为40 ～ 120 nm，CD63、TSG101、PLAP 表达呈阳性；与对照组相比， GDM组胎盘外泌体以浓度依赖性促进滋养细胞的增殖、细胞周期进展，并抑制滋养细胞的凋亡。结论：GDM中 胎盘外泌体可能通过促进滋养细胞的增殖、细胞周期进展，抑制滋养细胞凋亡等参与GDM的发生和发展。