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1161.
颜林林 (2022-05-31 07:28):
#paper doi:10.1038/s41586-021-03583-3 Nature 2021, Swarm Learning for decentralized and confidential clinical machine learning. 精准医学的发展得益于数据的快速积累,然而数据共享却始终是数据充分使用的重大障碍。本文提出一种群体学习方法,它结合了边缘计算、区块链等技术,使数据拥有者可以在不违反隐私法规的情况下,让数据可以在全球范围被集成使用,从而解决药物靶标发现、诊断标志物发现等精准医学研究目标所亟需的大规模数据整合需求。为验证该方法的可行性,本文选取了四种疾病,新冠、结核、白血病和肺病,包括血液转录组和胸部X光片数据,且这些数据存在普遍的异质性和对照分布不均匀等问题,对这些数据进行此群体学习的分析。通过将数据分散到不同网络节点,并让这些节点动态加入计算,最终实现对这些疾病的识别或亚型鉴定,并与传统机器学习方法结果进行对比。本文最近在Nature Reviews Immunology的一篇comment上被再次提及,并介绍了其白血病临床诊断已被欧盟成功标准化并随后商业化,进一步验证了该方法的实际价值。同时,由于它以“共享见解而非共享数据(sharing insights, not data)”的方式进行协作,对于当下诸如医学免疫学等复杂研究,也将起到更大作用。
IF:50.500Q1 Nature, 2021-06. DOI: 10.1038/s41586-021-03583-3 PMID: 34040261 PMCID:PMC8189907
Abstract:
Fast and reliable detection of patients with severe and heterogeneous illnesses is a major goal of precision medicine. Patients with leukaemia can be identified using machine learning on the basis … >>>
Fast and reliable detection of patients with severe and heterogeneous illnesses is a major goal of precision medicine. Patients with leukaemia can be identified using machine learning on the basis of their blood transcriptomes. However, there is an increasing divide between what is technically possible and what is allowed, because of privacy legislation. Here, to facilitate the integration of any medical data from any data owner worldwide without violating privacy laws, we introduce Swarm Learning-a decentralized machine-learning approach that unites edge computing, blockchain-based peer-to-peer networking and coordination while maintaining confidentiality without the need for a central coordinator, thereby going beyond federated learning. To illustrate the feasibility of using Swarm Learning to develop disease classifiers using distributed data, we chose four use cases of heterogeneous diseases (COVID-19, tuberculosis, leukaemia and lung pathologies). With more than 16,400 blood transcriptomes derived from 127 clinical studies with non-uniform distributions of cases and controls and substantial study biases, as well as more than 95,000 chest X-ray images, we show that Swarm Learning classifiers outperform those developed at individual sites. In addition, Swarm Learning completely fulfils local confidentiality regulations by design. We believe that this approach will notably accelerate the introduction of precision medicine. <<<
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1162.
Ricardo (2022-05-30 23:39):
#paper https://arxiv.org/abs/2102.04159v3 Deep Residual Learning in Spiking Neural Networks. 2021年发表于NIPS。基于人工神经网络的现代深度学习技术在各个领域上都取得了相当大的进展,但是由于其数学上的黑箱不可解释性、功耗高的问题,有一部分研究开始关注于基于生物脉冲神经元的脉冲神经网络上(SNN)。SNN有较高的生物解释性、事件驱动性和低功耗等特点,被视为人工神经网络的潜在竞争对手。但是SNN仍然面临许多理论和工程问题,在一些复杂任务上的表现仍然比ANN差。基于残差学习在ANN上取得的巨大成功,自然会去研究如何利用残差学习去训练SNN。之前的一些研究仿照ANN中标准的残差模块,简单地将relu激活函数替换成脉冲神经元,但是这样的网络伴随着深度的增加会出现退化问题,从而难以实现残差学习。在这篇论文里,作者证明了之前在SNN上的残差学习方法会导致梯度爆炸/消失问题,从而难以实现identity mapping。因此,他们提出了一个方法用来解决这么一个梯度爆炸/消失问题。实验结果也挺漂亮的,在多个数据集上都比之前的snn方法更好,当然不如ann的结果啦。并且能够通过加深网络深度提高snn的performance。而且,也首次实现了能够直接训练超过100层的snn。
Abstract:
Deep Spiking Neural Networks (SNNs) present optimization difficulties for gradient-based approaches due to discrete binary activation and complex spatial-temporal dynamics. Considering the huge success of ResNet in deep learning, it … >>>
Deep Spiking Neural Networks (SNNs) present optimization difficulties for gradient-based approaches due to discrete binary activation and complex spatial-temporal dynamics. Considering the huge success of ResNet in deep learning, it would be natural to train deep SNNs with residual learning. Previous Spiking ResNet mimics the standard residual block in ANNs and simply replaces ReLU activation layers with spiking neurons, which suffers the degradation problem and can hardly implement residual learning. In this paper, we propose the spike-element-wise (SEW) ResNet to realize residual learning in deep SNNs. We prove that the SEW ResNet can easily implement identity mapping and overcome the vanishing/exploding gradient problems of Spiking ResNet. We evaluate our SEW ResNet on ImageNet, DVS Gesture, and CIFAR10-DVS datasets, and show that SEW ResNet outperforms the state-of-the-art directly trained SNNs in both accuracy and time-steps. Moreover, SEW ResNet can achieve higher performance by simply adding more layers, providing a simple method to train deep SNNs. To our best knowledge, this is the first time that directly training deep SNNs with more than 100 layers becomes possible. <<<
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1163.
魏魏魏 (2022-05-30 23:07):
#paper doi:10.1016/j.paid.2015.01.017 Personality and Individual Differences, (2015), The impact of self-determined motivation on volunteer role identities: A cross-lagged panel study. 志愿者的工作在很多领域都被探讨,那么这种有计划且持久的亲社会行为的动机基础是什么?本研究探讨的就是这个问题,即志愿者是如何认同自己角色的。自我决定理论认为,动机的品质会极大影响人们在各种情况下的行为表现和幸福感等。当前研究采用了交叉滞后研究设计,探讨了自我决定及控制性动机与整体角色认同和组织特异性角色认同两种不同志愿者角色类型之间的交叉之后效应,这个交叉之后的时间间隔是16个月。最终的分析结果表明,自我决定的动机对两种不同志愿者角色类型都存在积极影响。只有组织特异性角色认同对随后的自我决定动机有积极影响。组织特异性角色认同对随后的控制性动机有积极的交叉之后效应。整体来讲,该研究支持了自我决定动机是志愿者角色认同的观点。
Abstract:
Volunteer role identity is regarded the direct and proximal cause of sustained volunteerism. Self-determination theory suggests that the quality of motivation greatly affects performance and well-being in various contexts. Therefore, … >>>
Volunteer role identity is regarded the direct and proximal cause of sustained volunteerism. Self-determination theory suggests that the quality of motivation greatly affects performance and well-being in various contexts. Therefore, this study investigated cross-lagged effects (over a time period of 16 months) between self-determined and controlled motivation, on the one hand, and two types of volunteer role identities, on the other hand: general role identity (GRI) and organization-specific role identity (OSRI). Analyses confirmed positive time-lagged effects of self-determined motivation on both GRI and OSRI. Time-lagged effects in opposite direction were significantly weaker; only OSRI showed a positive impact on subsequent self-determined motivation. OSRI (but not GRI) also had a positive lagged effect on controlled motivation. Overall, this study supported the idea that self-determined motivation represents a causal antecedent of volunteer role identities. <<<
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1164.
张浩彬 (2022-05-30 19:14):
#paper Wen, Ruofeng, et al. A Multi-Horizon Quantile Recurrent Forecaster. #paper Wen, Ruofeng, et al. A Multi-Horizon Quantile Recurrent Forecaster. DOI: 10.48550/arXiv.1711.11053 MQRNN,又是亚马逊的时序论文。之前看了DeepAR,可以对多个序列进行建模,并且也有很好的鲁棒性。但是相比之前的prophet和DeepAR,MQRNN走了另外一个路子,基于分位数的预测。这样的一个好处是,它认为我们不再去预测序列在t时刻的分布,而是预测t时刻的分位数,走了分位数回归的路子。另外,相比于DeepAR,MQRNN使用了水平多无预测,即不再采用迭代方式预测多步,而是一次性产生多步预测。按照论文的说法,这样的好处是提高了预测效率(毕竟可以并行),减少了累积误差(个人觉得这点,见仁见智,本质其实一样)
Abstract:
We propose a framework for general probabilistic multi-step time series regression. Specifically, we exploit the expressiveness and temporal nature of Sequence-to-Sequence Neural Networks (e.g. recurrent and convolutional structures), the nonparametric … >>>
We propose a framework for general probabilistic multi-step time series regression. Specifically, we exploit the expressiveness and temporal nature of Sequence-to-Sequence Neural Networks (e.g. recurrent and convolutional structures), the nonparametric nature of Quantile Regression and the efficiency of Direct Multi-Horizon Forecasting. A new training scheme, *forking-sequences*, is designed for sequential nets to boost stability and performance. We show that the approach accommodates both temporal and static covariates, learning across multiple related series, shifting seasonality, future planned event spikes and cold-starts in real life large-scale forecasting. The performance of the framework is demonstrated in an application to predict the future demand of items sold on this http URL, and in a public probabilistic forecasting competition to predict electricity price and load. <<<
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1165.
吴增丁 (2022-05-30 14:45):
#paper DOI: 10.1093/nar/gkaa379 分享这篇2020年发表在NAR上的文章:NetMHCpan-4.1 and NetMHCIIpan-4.0: improved predictions of MHC antigen presentation by concurrent motif deconvolution and integration of MS MHC eluted ligand data。该文章是丹麦科技大学对NetMHCpan系列预测系列软件的更新。人体免疫系统工作的一个很重要的工作原理是:细胞通过组织相容性复合体MHC将细胞内被蛋白酶降解的多肽呈递到细胞表面,从而被T细胞识别,进而激发免疫级联反应。按照呈递抗原表位的来源可将MHC分类为 呈递内源性多肽的MHCI 和呈递外源性多肽的MHCII。现在随着肿瘤免疫治疗的兴起,在治疗性疫苗设计中,关于抗原序列的设计是非常关键。然而设计的抗原是否真的有免疫反应?这个抗原呈递的预测就非常关键,这也是本文章要不断打磨提升抗原呈递算法的核心驱动力。 本文章的相对上一版本的提升之处有两点:1.改进了机器学习的framework,将之前的核心框架NNAlign提升为NNAlign_MA,即更加适应了质谱的训练数据;2.扩大了训练数据集,并且对数据进行了更新标签。做了这些更新后,在性能上相比上一版本及其他类似软件,都获得了更有的PPV.
IF:16.600Q1 Nucleic acids research, 2020-07-02. DOI: 10.1093/nar/gkaa379 PMID: 32406916 PMCID:PMC7319546
Abstract:
Major histocompatibility complex (MHC) molecules are expressed on the cell surface, where they present peptides to T cells, which gives them a key role in the development of T-cell immune … >>>
Major histocompatibility complex (MHC) molecules are expressed on the cell surface, where they present peptides to T cells, which gives them a key role in the development of T-cell immune responses. MHC molecules come in two main variants: MHC Class I (MHC-I) and MHC Class II (MHC-II). MHC-I predominantly present peptides derived from intracellular proteins, whereas MHC-II predominantly presents peptides from extracellular proteins. In both cases, the binding between MHC and antigenic peptides is the most selective step in the antigen presentation pathway. Therefore, the prediction of peptide binding to MHC is a powerful utility to predict the possible specificity of a T-cell immune response. Commonly MHC binding prediction tools are trained on binding affinity or mass spectrometry-eluted ligands. Recent studies have however demonstrated how the integration of both data types can boost predictive performances. Inspired by this, we here present NetMHCpan-4.1 and NetMHCIIpan-4.0, two web servers created to predict binding between peptides and MHC-I and MHC-II, respectively. Both methods exploit tailored machine learning strategies to integrate different training data types, resulting in state-of-the-art performance and outperforming their competitors. The servers are available at http://www.cbs.dtu.dk/services/NetMHCpan-4.1/ and http://www.cbs.dtu.dk/services/NetMHCIIpan-4.0/. <<<
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1166.
尹志 (2022-05-30 13:31):
#paper https://doi.org/10.48550/arXiv.1907.05600 Generative Modeling by Estimating Gradients of the Data Distribution NeurIPS 2019 (Oral) (2019). 继续生成模型啊,这篇文章作者提出了一种基于评分的生成模型。我们知道现在主流的生成模型基本可以分为likelihood-based和类似GAN那样通过对抗而不计算具体的概率密度函数的隐式模型。前者的代表如VAE、normalizing flow等。而本文的模型也属于这个范畴。在这类模型中,由于需要对条件概率进行积分,归一化常数Z的计算非常困难,因此派生出各类解决方法。本文其核心思想是通过对概率密度的梯度进行建模估计(准确来说是对log概率密度函数)。这里的log概率密度函数的梯度被定义为score function,而作者也是通过评分匹配(score matching)进行估计的。在生成模型建立之后,进而通过Langevin动力学进行采样,即生成样本。部分细节还在推,代码也在复现中,感觉是一类比较有效的生成模型,生成图片的质量较高,改进版本已经可以和GAN的生成质量一较高下。但目前最大的问题是废卡,非常废卡,希望后面自己可以在如何提高其训练效率及抽样效率上做一些工作。
Abstract:
We introduce a new generative model where samples are produced via Langevin dynamics using gradients of the data distribution estimated with score matching. Because gradients can be ill-defined and hard … >>>
We introduce a new generative model where samples are produced via Langevin dynamics using gradients of the data distribution estimated with score matching. Because gradients can be ill-defined and hard to estimate when the data resides on low-dimensional manifolds, we perturb the data with different levels of Gaussian noise, and jointly estimate the corresponding scores, i.e., the vector fields of gradients of the perturbed data distribution for all noise levels. For sampling, we propose an annealed Langevin dynamics where we use gradients corresponding to gradually decreasing noise levels as the sampling process gets closer to the data manifold. Our framework allows flexible model architectures, requires no sampling during training or the use of adversarial methods, and provides a learning objective that can be used for principled model comparisons. Our models produce samples comparable to GANs on MNIST, CelebA and CIFAR-10 datasets, achieving a new state-of-the-art inception score of 8.87 on CIFAR-10. Additionally, we demonstrate that our models learn effective representations via image inpainting experiments. <<<
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1167.
白义民 (2022-05-30 08:56):
#paper 《坛经和明代大藏经》,主要考据了坛经入藏时间很晚,史上最早是洪武南藏,这和朱元璋从乞丐和尚到皇帝的经历密不可分,于是朱元璋授意和自己差不多背景的慧能的坛经入佛学大藏经,并把目不识丁不读经瞎臆想的民间哲学家慧能推崇到祖师禅鼻祖的地位,以此为荣,来说明乞丐皇帝的法统正当性。却不料对祖师教的堕落产生了长期的推波助澜的文化恶劣影响。
1168.
颜林林 (2022-05-29 23:45):
#paper doi:10.1016/j.ccell.2022.05.005 Cancer Cell, 2022, Redefining breast cancer subtypes to guide treatment prioritization and maximize response: Predictive biomarkers across 10 cancer therapies. 这篇论文是关于一项正在进行的、开放标签、适应性、随机II期、多中心的临床试验(NCT01042379)I-SPY2。该临床试验入组高危II期和III期乳腺癌患者,并用70基因MammaPrint测试来排除其中无法从化疗获益的患者,将她们随机分配到10个不同用药组,并在手术前的新辅助治疗期间的不同时间点,进行MRI检查、穿刺取样和/或外周血采集,新辅助治疗前的穿刺样本,同时开展了基因表达芯片、蛋白磷酸化和免疫组化/原位杂交的检测。通过这些检测数据和患者用药响应结果,本研究对入组的987例患者做了重新分类,定义出五种亚型:HER2-/Immune-/DRD-、HER2-/Immune+、HER2-/Immune-/DRD+、HER2+/BP-HER2_or_Basal及HER2+/BP-Luminal。这个重定义过程,除了纳入传统定义所采用的HR/HER2状态外,也包含了诸如增值、DRD、免疫等其他表型特征,在确保分型区分选取最佳治疗方案,即获得最高的pCR(病理完全缓解)的概率,同时也兼顾检测平台稳健性和临床实施简单。虽然目前每个单臂上的病例数还并不算特别多,但相信随着该临床试验的持续开展和更多病例数据的积累,这项研究将优化出相比当前指南建议更好的治疗决策路径。而相应的研究方法和数据分析套路,也预期可以套用到其他癌种上,并在各类高通量多组学检测方法快速发展的今天,持续产出更多精准医疗实践应用。
IF:48.800Q1 Cancer cell, 2022-06-13. DOI: 10.1016/j.ccell.2022.05.005 PMID: 35623341 PMCID:PMC9426306
Abstract:
Using pre-treatment gene expression, protein/phosphoprotein, and clinical data from the I-SPY2 neoadjuvant platform trial (NCT01042379), we create alternative breast cancer subtypes incorporating tumor biology beyond clinical hormone receptor (HR) and … >>>
Using pre-treatment gene expression, protein/phosphoprotein, and clinical data from the I-SPY2 neoadjuvant platform trial (NCT01042379), we create alternative breast cancer subtypes incorporating tumor biology beyond clinical hormone receptor (HR) and human epidermal growth factor receptor-2 (HER2) status to better predict drug responses. We assess the predictive performance of mechanism-of-action biomarkers from ∼990 patients treated with 10 regimens targeting diverse biology. We explore >11 subtyping schemas and identify treatment-subtype pairs maximizing the pathologic complete response (pCR) rate over the population. The best performing schemas incorporate Immune, DNA repair, and HER2/Luminal phenotypes. Subsequent treatment allocation increases the overall pCR rate to 63% from 51% using HR/HER2-based treatment selection. pCR gains from reclassification and improved patient selection are highest in HR subsets (>15%). As new treatments are introduced, the subtyping schema determines the minimum response needed to show efficacy. This data platform provides an unprecedented resource and supports the usage of response-based subtypes to guide future treatment prioritization. <<<
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1169.
张德祥 (2022-05-26 21:26):
#paper https://doi.org/10.1017/S0140525X19002000 大脑的贝叶斯预测理论需要哪些具体的技术理论支撑,这篇论文认为需要抽象的表示,这篇论文对抽象表示进行了分析,从业界缺乏的抽象定义开始,持续进行了深入的分析 详细参考:https://mp.weixin.qq.com/s/bOVnaFqjvmAXXEDTq36yWQ
Abstract:
In recent years, scientists have increasingly taken to investigate the predictive nature of cognition. We argue that prediction relies on abstraction, and thus theories of predictive cognition need an explicit … >>>
In recent years, scientists have increasingly taken to investigate the predictive nature of cognition. We argue that prediction relies on abstraction, and thus theories of predictive cognition need an explicit theory of abstract representation. We propose such a theory of the abstract representational capacities that allow humans to transcend the "here-and-now." Consistent with the predictive cognition literature, we suggest that the representational substrates of the mind are built as a hierarchy, ranging from the concrete to the abstract; however, we argue that there are qualitative differences between elements along this hierarchy, generating meaningful, often unacknowledged, diversity. Echoing views from philosophy, we suggest that the representational hierarchy can be parsed into: modality-specific representations, instantiated on perceptual similarity; multimodal representations, instantiated primarily on the discovery of spatiotemporal contiguity; and categorical representations, instantiated primarily on social interaction. These elements serve as the building blocks of complex structures discussed in cognitive psychology (e.g., episodes, scripts) and are the inputs for mental representations that behave like functions, typically discussed in linguistics (i.e., predicators). We support our argument for representational diversity by explaining how the elements in our ontology are all required to account for humans' predictive cognition (e.g., in subserving logic-based prediction; in optimizing the trade-off between accurate and detailed predictions) and by examining how the neuroscientific evidence coheres with our account. In doing so, we provide a testable model of the neural bases of conceptual cognition and highlight several important implications to research on self-projection, reinforcement learning, and predictive-processing models of psychopathology. <<<
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1170.
masion (2022-05-26 10:30):
#paper doi: 10.3389/fmicb.2020.574771 Front. Microbiol.,  11:574771.Production of Neoagaro-Oligosaccharides With Various Degrees of Polymerization by Using a Truncated Marine Agarase. 推荐理由:来源于海洋红藻的琼胶大分子多糖,可以被降解为小分子的寡糖,后者具有抗癌、抗炎、美白、益生元等重要的生物活性。化学降解过程中会产生大量含酸废水,相较而言,生物酶解法更加高效、稳定且环境友好。因此,生物酶解法在新琼寡糖制备产业有着重要的应用价值。但是,生物酶解法只能获得1-3种聚合度的新琼寡糖,且聚合度较低(<6),限制了生物法的应用。 该研究利用基因截短方法,删除了野生型琼胶酶AgaM1碳端的60个氨基酸,通过大肠杆菌异源表达该截短的琼胶酶基因,可以一次性同时产生聚合度在4-12的新琼寡糖,大大提高了酶解法产物的聚合度与多样性,且可以把酶产量提高了842倍,进一步降低了多种聚合度新琼寡糖的生产成本。
Abstract:
Bioactivities, such as freshness maintenance, whitening, and prebiotics, of marine neoagaro-oligosaccharides (NAOS) with 4-12 degrees of polymerization (DPs) have been proven. However, NAOS produced by most marine β-agarases always possess … >>>
Bioactivities, such as freshness maintenance, whitening, and prebiotics, of marine neoagaro-oligosaccharides (NAOS) with 4-12 degrees of polymerization (DPs) have been proven. However, NAOS produced by most marine β-agarases always possess low DPs (≤6) and limited categories; thus, a strategy that can efficiently produce NAOS especially with various DPs ≥8 must be developed. In this study, 60 amino acid residues with no functional annotation result were removed from the C-terminal of agarase AgaM1, and truncated recombinant AgaM1 (trAgaM1) was found to have the ability to produce NAOS with various DPs (4-12) under certain conditions. The catalytic efficiency and stability of trAgaM1 were obviously lower than the wild type (rAgaM1), which probably endowed trAgaM1 with the ability to produce NAOS with various DPs. The optimum conditions for various NAOS production included mixing 1% agarose (w/v) with 10.26 U/ml trAgaM1 and incubating the mixture at 50°C in deionized water for 100 min. This strategy produced neoagarotetraose (NA4), neoagarohexaose (NA6), neoagarooctaose (NA8), neoagarodecaose (NA10), and neoagarododecaose (NA12) at final concentrations of 0.15, 1.53, 1.53, 3.02, and 3.02 g/L, respectively. The NAOS served as end-products of the reaction. The conditions for trAgaM1 expression in a shake flask and 5 L fermentation tank were optimized, and the yields of trAgaM1 increased by 56- and 842-fold compared with those before optimization, respectively. This study provides numerous substrate sources for production and activity tests of NAOS with high DPs and offers a foundation for large-scale production of NAOS with various DPs at a low cost. <<<
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1171.
洪媛媛 (2022-05-25 18:31):
#paper doi: 10.1093/nar/gkx345 Nucleic Acids Research, 2017, Vol. 45, No. 13 7655–7665. APOBEC3A efficiently deaminates methylated, but not TET-oxidized, cytosine bases in DNA.推荐理由:这篇文章主要研究了AID/APOBEC家族的human APOBEC3A (A3A)脱氨酶,对不同氧化程度的胞嘧啶核苷酸,包括C, 5mC, 5hmC, 5fC, and 5caC的脱氨能力,还细致研究了DNA底物的序列特征对酶活的影响。研究发现APOBEC3A对C的脱氨能力最强,其次是5mC,对5hmC和5fc的脱氨能力只有C的~5600分之一和~3700分之一,对5caC几乎不起作用。当APOBEC3A酶过量时,所有的C和5mC都能够被脱氨,无论其前后是何种碱基;当酶量不足时,C和5mC -1位的碱基种类对脱氨效果影响最大,其次是C和5mC -2位的碱基种类。
IF:16.600Q1 Nucleic acids research, 2017-Jul-27. DOI: 10.1093/nar/gkx345 PMID: 28472485 PMCID:PMC5570014
Abstract:
AID/APOBEC family enzymes are best known for deaminating cytosine bases to uracil in single-stranded DNA, with characteristic sequence preferences that can produce mutational signatures in targets such as retroviral and … >>>
AID/APOBEC family enzymes are best known for deaminating cytosine bases to uracil in single-stranded DNA, with characteristic sequence preferences that can produce mutational signatures in targets such as retroviral and cancer cell genomes. These deaminases have also been proposed to function in DNA demethylation via deamination of either 5-methylcytosine (mC) or TET-oxidized mC bases (ox-mCs), which include 5-hydroxymethylcytosine, 5-formylcytosine and 5-carboxylcytosine. One specific family member, APOBEC3A (A3A), has been shown to readily deaminate mC, raising the prospect of broader activity on ox-mCs. To investigate this claim, we developed a novel assay that allows for parallel profiling of activity on all modified cytosines. Our steady-state kinetic analysis reveals that A3A discriminates against all ox-mCs by >3700-fold, arguing that ox-mC deamination does not contribute substantially to demethylation. A3A is, by contrast, highly proficient at C/mC deamination. Under conditions of excess enzyme, C/mC bases can be deaminated to completion in long DNA segments, regardless of sequence context. Interestingly, under limiting A3A, the sequence preferences observed with targeting unmodified cytosine are further exaggerated when deaminating mC. Our study informs how methylation, oxidation, and deamination can interplay in the genome and suggests A3A's potential utility as a biotechnological tool to discriminate between cytosine modification states. <<<
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1172.
孤舟蓑笠翁 (2022-05-23 19:00):
#paper 10.1080/01621459.2020.1721245。Journal of the American Statistical Association。2020。The Book of Why: The New Science of Cause and Effect。 这是对Judea Pearl的《the book of why》的书评。从这个书评来看,Judea Pearl的《the book of why》有较大的局限。比如,Judea Pearl在《the book of why》只处理了因果分析,而忽略了因果结构的确定。但有时往往连因果结构也是不清楚或者不确定的。基于我的阅读理解,这个书评还指出,Judea Pearl认为随机实验不重要,只要看起来没有受到干扰就可以了。但书评作者认为,随机实验的作用在于能让研究者对实验设计和过程做检查。另外,实验允许我们不知道因果结构。然后,书评作者认为Judea Pearl的因果分析模型的表达能力不够强;还说Judea Pearl虽然回顾了因果研究的历史,但他的回顾是不完整的,忽略了其它因果研究方向;说Judea Pearl认为不接受他的理论的研究者是“文化抵触”,但其实是因为他的理论用处不大;说Judea Pearl的理论和之前Robin的因果理论关系密切,仅仅是多了一些独立性假设,但Robin没提这些假设不是因为他提不出来,而是因为认为太牵强,而且也无法得到实验验证。看了这个书评后我估计不会优先看The Book of Why了。
1173.
张德祥 (2022-05-22 05:39):
#paper book ISBN: 978-3-319-42337-1 https://doi.org/10.1007/978-3-319-42337-1 这本书介绍了主观逻辑推理及相关很多内容,扩展了概率推理,包括演绎推理,因果溯源推理,多来源信息证据的融合算法,贝叶斯主观网络等内容。很新的前沿内容。16年出版;全书ppt等等参考:https://mp.weixin.qq.com/s/wLRHPnJaUWM1cVgBfqmWgA
Abstract: No abstract available.
1174.
龙海晨 (2022-05-12 11:23):
#paper Artesunate exhibits synergistic anti-cancer effects with cisplatin on lung cancer A549 cells by inhibiting MAPK pathway PMID: 32898605 GENE杂志Gene 2021 Jan 15;766:145134. doi: 10.1016/j.gene.2020.145134. Epub 2020 Sep 6. DOI: 10.1016/j.gene.2020.145134 文章研究了青蒿琥酯(Artesunate,ART)与顺铂(cisplatin,CIS)联合发挥抗肺癌作用。使用A549肺癌细胞系进行研究。发现ART加大剂量获延长使用时间均能抑制细胞增殖。且ART与CIS联合使用,抑癌效果要显著强于单独用ART获单独用CIS,使用裸鼠进行动物实验也得到了同样结果。并证明,联合效果是通过P38/JNK/ERK MAPK信号通路发挥作用。
IF:2.600Q2 Gene, 2021-1. DOI: 10.1016/j.gene.2020.145134 PMID: 32898605
Abstract:
BACKGROUND: Artesunate (ART) has been used extensively as anti-malarial drugs worldwide. Besides, it has also been reported to have anti-cancer activities. This study was aimed to explore the anti-cancer activity … >>>
BACKGROUND: Artesunate (ART) has been used extensively as anti-malarial drugs worldwide. Besides, it has also been reported to have anti-cancer activities. This study was aimed to explore the anti-cancer activity of ART in combination with cisplatin (CIS) on A549 cells.METHODS: Cells were cultured with different concentrations of ART and/or CIS for 24, 48, or 72 h to test the anti-proliferative effects by CCK-8 assay. Colony formation assay and EdU staining were also performed. TUNEL staining was used to illustrate the morphologic changes. Cell cycle and apoptosis were determined by flow cytometry assay, and Western blot analysis was conducted to detect the expression of apoptosis- and proliferation-related proteins. Caspase activities were determined by colorimetric assay kit. Moreover, the synergistic effect of ART with CIS in A549 cell xenograft model was also determined.RESULTS: ART significantly inhibited cell proliferation in dose- and time-dependent manners. Collectively, the combination treatment remarkably decreased colony formation rates and increased the rates of TUNEL-positive cells compared with mono-treatment. Mechanistically, the combination treatment influenced the expression of Bcl-2, Bax, p-P53, Caspase-3/7, Caspase-9, CyclinB1, P34, P21, and synergistically regulated the activity of P38/JNK/ERK1/2 MAPK pathway. In mice A549 xenograft tumors, the combination strategy significantly increased the anti-cancer efficacy of ART and CIS alone, consistent with the in vitro observations.CONCLUSIONS: ART exhibited significant anti-tumor effect on A549 cells and this efficiency could be enhanced by combination with CIS. <<<
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1175.
张德祥 (2022-05-07 11:31):
#paper doi:10.11896/jsjkx.210500158 基于物理信息的神经网络: 最新进展与展望 神经网络的强大高效已经被人们认识,缺点也逐渐暴露,物理模型有严格的推导,对物理世界有很好的先验,结合起来效率提升,这篇中文文章调研了这个领域的最新进展,表一对理论和应用总结的不错,论文对NS方程也有大量的调研,值得参考。
Abstract:
基于物理信息的神经网络(Physics-informed Neural Networks,PINN),是一类用于解决有监督学习任务的神经网络,它不仅尽力遵循训练数据样本的分布规律,而且遵守由偏微分方程描述的物理定律。与纯数据驱动的神经网络学习相比,PINN在训练过程中施加了物理信息约束,因此能用更少的数据样本学习得到更具泛化能力的模型。近年来,PINN已逐渐成为机器学习和计算数学交叉学科的研究热点,并在理论和应用方面都获得了相对深入的研究,取得了可观的进展。但PINN独特的网络结构在实际应用中也存在训练缓慢甚至不收敛、精度低等问题。文中在总结当前PINN研究的基础上,对其网络/体系设计及其在流体力学等多个领域中的应用进行了探究,并展望了进一步的研究方向。 >>>
基于物理信息的神经网络(Physics-informed Neural Networks,PINN),是一类用于解决有监督学习任务的神经网络,它不仅尽力遵循训练数据样本的分布规律,而且遵守由偏微分方程描述的物理定律。与纯数据驱动的神经网络学习相比,PINN在训练过程中施加了物理信息约束,因此能用更少的数据样本学习得到更具泛化能力的模型。近年来,PINN已逐渐成为机器学习和计算数学交叉学科的研究热点,并在理论和应用方面都获得了相对深入的研究,取得了可观的进展。但PINN独特的网络结构在实际应用中也存在训练缓慢甚至不收敛、精度低等问题。文中在总结当前PINN研究的基础上,对其网络/体系设计及其在流体力学等多个领域中的应用进行了探究,并展望了进一步的研究方向。 <<<
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1176.
张德祥 (2022-05-02 09:28):
#paper https://doi.org/10.48550/arXiv.2001.04385 Universal Differential Equations for Scientific Machine Learnin 我们提供一流的工具来求解微分方程 我们提供用于推导和拟合科学模型的工具 我们提供高级域特定建模工具,使科学建模更易于访问 我们提供科学机器学习中最新算法的高级实现 我们为所有常见科学编程语言的用户提供使用我们工具的能力 我们提供用于研究科学机器学习方法的工具 我们的目标是什么 我们构建的一切都与自动微分兼容 性能被视为优先事项,性能问题被视为错误 我们的软件包使用科学模拟和机器学习工具进行了常规和稳健的测试 我们紧跟计算硬件的进步,以确保与最新的高性能计算工具兼容。 https://mp.weixin.qq.com/s/jR_2A1IqqZ1J8idmXb9Tpg
Abstract:
In the context of science, the well-known adage "a picture is worth a thousand words" might well be "a model is worth a thousand datasets." In this manuscript we introduce … >>>
In the context of science, the well-known adage "a picture is worth a thousand words" might well be "a model is worth a thousand datasets." In this manuscript we introduce the SciML software ecosystem as a tool for mixing the information of physical laws and scientific models with data-driven machine learning approaches. We describe a mathematical object, which we denote universal differential equations (UDEs), as the unifying framework connecting the ecosystem. We show how a wide variety of applications, from automatically discovering biological mechanisms to solving high-dimensional Hamilton-Jacobi-Bellman equations, can be phrased and efficiently handled through the UDE formalism and its tooling. We demonstrate the generality of the software tooling to handle stochasticity, delays, and implicit constraints. This funnels the wide variety of SciML applications into a core set of training mechanisms which are highly optimized, stabilized for stiff equations, and compatible with distributed parallelism and GPU accelerators. <<<
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1177.
张德祥 (2022-05-01 09:56):
#paper https://doi.org/10.48550/arXiv.2204.07953 Learning with Signatures mnist等识别100% ,这个结果一下子炸了锅了,reddit质疑诋毁一片, https://github.com/decurtoydiaz/learning_with_signatures/issues 的讨论也很激动,但是作者开放了代码,回应了质疑,https://www.kaggle.com/code/mlsnatcher/replicate-results-signature-model/notebook也有可以直接运行的代码,在issue5讨论中作者也承认了有一个不足,除了不认可,是否可以深入了解一下这个技术具体使用的方法?论文不用深度学习,使用了:The signature was first defined for smooth paths by Chen in the 60s (Chen, 1957; 1958; 1977) and was rediscovered in the 90s in the context of rough path theory;这个数学很难,想真正搞懂这个论文的底细很难,挑战很大,搞懂了也是本事,如果技术真的ok,那也是领先一步。
Abstract:
In this work we investigate the use of the Signature Transform in the context of Learning. Under this assumption, we advance a supervised framework that potentially provides state-of-the-art classification accuracy … >>>
In this work we investigate the use of the Signature Transform in the context of Learning. Under this assumption, we advance a supervised framework that potentially provides state-of-the-art classification accuracy with the use of few labels without the need of credit assignment and with minimal or no overfitting. We leverage tools from harmonic analysis by the use of the signature and log-signature, and use as a score function RMSE and MAE Signature and log-signature. We develop a closed-form equation to compute probably good optimal scale factors, as well as the formulation to obtain them by optimization. Techniques of Signal Processing are addressed to further characterize the problem. Classification is performed at the CPU level orders of magnitude faster than other methods. We report results on AFHQ, MNIST and CIFAR10, achieving 100% accuracy on all tasks assuming we can determine at test time which probably good optimal scale factor to use for each category. <<<
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1178.
笑对人生 (2022-05-01 00:03):
#paper Transfer learning between preclinical models and human tumors identifies a conserved NK cell activation signature in anti-CTLA-4 responsive tumors, Genome Med. 2021 Aug 11;13(1):129. doi: 10.1186/s13073-021-00944-5. 目前,单细胞转录组测序在临床前动物实验研究应用较为普遍,然而,如何将这些新的发现迁移到人类的肿瘤单细胞转录组研究中,仍然是一大挑战。该研究利用机器学习中迁移学习方法,识别出在Anti-CTLA-4响应小鼠和人类肿瘤中共有的NK细胞状态特征,并发现该特征与患者更长的总生存期相关,能用于预测ICBs治疗疗效。最近,NK细胞的研究在CNS频繁“出镜”,可能NK细胞的过继细胞疗法在临床上取得较大进展有关,这也提示我们,相比于T细胞,NK细胞尚未有很大的研究空白,借助目前单细胞转录组测序技术,可能会找到一些有趣的新发现。
IF:10.400Q1 Genome medicine, 2021-08-11. DOI: 10.1186/s13073-021-00944-5 PMID: 34376232 PMCID:PMC8356429
Abstract:
BACKGROUND: Tumor response to therapy is affected by both the cell types and the cell states present in the tumor microenvironment. This is true for many cancer treatments, including immune … >>>
BACKGROUND: Tumor response to therapy is affected by both the cell types and the cell states present in the tumor microenvironment. This is true for many cancer treatments, including immune checkpoint inhibitors (ICIs). While it is well-established that ICIs promote T cell activation, their broader impact on other intratumoral immune cells is unclear; this information is needed to identify new mechanisms of action and improve ICI efficacy. Many preclinical studies have begun using single-cell analysis to delineate therapeutic responses in individual immune cell types within tumors. One major limitation to this approach is that therapeutic mechanisms identified in preclinical models have failed to fully translate to human disease, restraining efforts to improve ICI efficacy in translational research.METHOD: We previously developed a computational transfer learning approach called projectR to identify shared biology between independent high-throughput single-cell RNA-sequencing (scRNA-seq) datasets. In the present study, we test this algorithm's ability to identify conserved and clinically relevant transcriptional changes in complex tumor scRNA-seq data and expand its application to the comparison of scRNA-seq datasets with additional data types such as bulk RNA-seq and mass cytometry.RESULTS: We found a conserved signature of NK cell activation in anti-CTLA-4 responsive mouse and human tumors. In human metastatic melanoma, we found that the NK cell activation signature associates with longer overall survival and is predictive of anti-CTLA-4 (ipilimumab) response. Additional molecular approaches to confirm the computational findings demonstrated that human NK cells express CTLA-4 and bind anti-CTLA-4 antibodies independent of the antibody binding receptor (FcR) and that similar to T cells, CTLA-4 expression by NK cells is modified by cytokine-mediated and target cell-mediated NK cell activation.CONCLUSIONS: These data demonstrate a novel application of our transfer learning approach, which was able to identify cell state transitions conserved in preclinical models and human tumors. This approach can be adapted to explore many questions in cancer therapeutics, enhance translational research, and enable better understanding and treatment of disease. <<<
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1179.
旺旺小小酥 (2022-05-01 00:02):
#paper 预期寿命、人力资本与提前退休行为[J].经济研究,2021,56(09):90-106. 作者根据计划生育政策、预期寿命延长、人力资本投资和内生退休决策构建OLG模型。本人从自己打工人的视角看这篇文章,作者深入讨论,寿命延长,咱们打工人能否提前退休根据个人成长性、家庭环境、工资增长程度等等因素综合下来:①年轻的时候一定要多存钱,多读书,特别是人力资本投入影响特别重要。 ②作者还谈到了生育政策的外生影响,主要就是家庭子女增加导致的养育成本上升,也会使得人在老的时候会不想动弹只想躺平
经济研究, 2021.
Abstract:
随着人均预期寿命的延长和受教育年限的提高,包括中国在内的世界各国劳动者的实际退休年龄却普遍低于法定退休年龄,呈现提前退休趋势。本文试图在生育受到约束的制度环境下对上述反常现象进行理论解释,通过构建一个动态一般均衡世代交叠(OLG)模型,考察预期寿命延长对劳动者的人力资本投资、退休年龄选择的影响机制,并结合中国的现实经济进行数值模拟。研究表明:当预期寿命提高时,人力资本投资能够在生命周期中获得更高的工资率回报,劳动者在少年期倾向于进行更多的人力资本投资,提高受教育年限;人力资本积累、有效工资率上升和利率下降引起的收入效应超过了替代效应,使得劳动者在老年期增加对闲暇的需求,有能力和意愿提早退休,减少终生劳动供给时间;进一步地,本文发现放松生育控制政策也会使劳动者享受更多闲暇时间的意愿增强,选择提前退休。本文还考察了个体退休行为的异质性,发现随着预期寿命的延长,相对穷人而言,富人的退休年龄和终生劳动供给更低。本文的结论有益于厘清劳动者在老年期的退休决策机理,为如何推进退休制度改革提供理论依据。 >>>
随着人均预期寿命的延长和受教育年限的提高,包括中国在内的世界各国劳动者的实际退休年龄却普遍低于法定退休年龄,呈现提前退休趋势。本文试图在生育受到约束的制度环境下对上述反常现象进行理论解释,通过构建一个动态一般均衡世代交叠(OLG)模型,考察预期寿命延长对劳动者的人力资本投资、退休年龄选择的影响机制,并结合中国的现实经济进行数值模拟。研究表明:当预期寿命提高时,人力资本投资能够在生命周期中获得更高的工资率回报,劳动者在少年期倾向于进行更多的人力资本投资,提高受教育年限;人力资本积累、有效工资率上升和利率下降引起的收入效应超过了替代效应,使得劳动者在老年期增加对闲暇的需求,有能力和意愿提早退休,减少终生劳动供给时间;进一步地,本文发现放松生育控制政策也会使劳动者享受更多闲暇时间的意愿增强,选择提前退休。本文还考察了个体退休行为的异质性,发现随着预期寿命的延长,相对穷人而言,富人的退休年龄和终生劳动供给更低。本文的结论有益于厘清劳动者在老年期的退休决策机理,为如何推进退休制度改革提供理论依据。 <<<
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1180.
masion (2022-04-30 23:26):
#paper https://doi.org/10.1016/j.envint.2021.106438, Environment International 151 (2021) 。本文在全球范围内调查了38个涵盖来自淡水、海水和土壤不同栖息地生态系统中的3178个样本细菌和原生生物序列数据对,绘制了地球跨生态系统的微生物群落分布图。结果表明,原生生物和细菌的群落特征在栖息地之间和栖息地内具有强烈的相关性,而营养微生物群落结构在栖息地之间存在根本性差异。土壤中的微生物群最为异质和多样。原生生物群落主要由土壤中的捕食者和水生环境中的光养生物组成。这导致原生生物总数与细菌丰富度之比的变化,在海洋中最高,而捕食性原生生物与细菌之比在土壤中最高。海洋生境中捕食性原生生物的分类单元丰富度和相对丰富度与细菌丰富度呈正相关。这些联系在土壤中有所不同,在森林和草原土壤中,捕食性原生生物的丰富度和相对丰富度与细菌丰富度呈正相关,而在农业土壤中则没有。我们的结果表明,人为压力对较高营养水平的影响大于对较低营养水平的影响,从而导致微生物群中的营养结构解耦。这些结果表明,人为因素可能会对微生物群落的营养结构产生负面影响,特别是对高营养水平的影响,因此,人工生态系统中生态系统功能降低可能部分归因于营养复杂性的降低。
Abstract:
The colossal project of mapping the microbiome on Earth is rapidly advancing, with a focus on individual microbial groups. However, a global assessment of the associations between predatory protists and … >>>
The colossal project of mapping the microbiome on Earth is rapidly advancing, with a focus on individual microbial groups. However, a global assessment of the associations between predatory protists and their bacterial prey is still missing at a cross-ecosystem level. This knowledge is critical to better understand the importance of top-down links in structuring microbiomes. Here, we examined 38 sequence-based datasets of paired bacterial and protistan taxa, covering 3,178 samples from diverse habitats including freshwater, marine and soils. We show that community profiles of protists and bacteria strongly correlated across and within habitats, with trophic microbiome structures fundamentally differing across habitats. Soils hosted the most heterogenous and diverse microbiomes. Protist communities were dominated by predators in soils and phototrophs in aquatic environments. This led to changes in the ratio of total protists to bacteria richness, which was highest in marine, while that of predatory protists to bacteria was highest in soils. Taxon richness and relative abundance of predatory protists positively correlated with bacterial richness in marine habitats. These links differed between soils, predatory protist richness and the relative abundance of predatory protists positively correlated with bacterial richness in forest and grassland soils, but not in agricultural soils. Our results suggested that anthropogenic pressure affects higher trophic levels more than lower ones leading to a decoupled trophic structure in microbiomes. Together, our cumulative overview of microbiome patterns of bacteria and protists at the global scale revealed major patterns and differences of the trophic structure of microbiomes across Earth's habitats, and show that anthropogenic factors might have negative effects on the trophic structure within microbiomes. Furthermore, the increased impact of anthropogenic factors on especially higher trophic levels suggests that often-observed reduced ecosystem functions in anthropogenic systems might be partly attributed to a reduction of trophic complexity. <<<
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