【标题速读】【Nmeth】【2022年】【7-12月】
声明：本专栏主要对生命科学领域的一些期刊文章标题进行翻译，所有内容均由本人手工整理翻译。由于本人专业为生物分析相关，其他领域如果出现翻译错误请谅解。
JeWell microchips facilitate compartmentalized organoid culture and allow single-objective light sheet imaging of up to 96 organoids in 3D and in three colors in one hour.
JeWell微芯片促进了类器官的区域化培养，并允许在一小时内对多达96个类器官进行3D和三种颜色的单目标光片成像。
1.Direct identification of A-to-I editing sites with nanopore native RNA sequencing.
用纳米孔原生RNA测序直接识别A-I编辑位点。
2.Emu: species-level microbial community profiling of full-length 16S rRNA Oxford Nanopore sequencing data.
Emu：全长16S rRNA牛津纳米孔测序数据的物种级微生物群落分析。
3.Cyclic immonium ion of lactyllysine reveals widespread lactylation in the human proteome.
乳酸菌素的环状铵离子揭示了人类蛋白质组中广泛的乳酸化。
4.MSNovelist: de novo structure generation from mass spectra.
MSNovelist：从质谱中生成新的结构。
5.A general approach for engineering RTKs optically controlled with far-red light.
用远红光进行光学控制的RTKs工程的一般方法。
6.Automated high-speed 3D imaging of organoid cultures with multi-scale phenotypic quantification.
具有多尺度表型定量的类器官培养物的自动高速三维成像。
7.Multiplexed bioluminescence microscopy via phasor analysis.
通过相位分析的多重生物发光显微镜。
以高时空分辨率监测大脑中的血流
Functional ultrasound localization microscopy reveals whole-brain vascular changes during neuronal activation at high resolution, providing quantitative information on changes in flow, speed and vessel diameter in multiple vascular compartments over a wide field of view.
功能性超声定位显微镜以高分辨率揭示神经元激活过程中的全脑血管变化，提供关于宽视野内多个血管隔室中流量、速度和血管直径变化的定量信息。
1.Integrative genome modeling platform reveals essentiality of rare contact events in 3D genome organizations.
综合基因组建模平台揭示了三维基因组组织中罕见接触事件的本质。
2.Sprod for de-noising spatially resolved transcriptomics data based on position and image information.
Sprod用于基于位置和图像信息的空间分辨率转录组学数据的去噪。
3.PROBER identifies proteins associated with programmable sequence-specific DNA in living cells.
PROBER确定了与活细胞中可编程序列特异性DNA相关的蛋白质。
4.Real age prediction from the transcriptome with RAPToR.
用RAPToR从转录组中预测真实年龄。
5.Directed evolution of adeno-associated virus for efficient gene delivery to microglia.
用于向小胶质细胞有效传递基因的腺相关病毒的定向进化。
6.Photoswitching fingerprint analysis bypasses the 10-nm resolution barrier.
光开关指纹分析绕过了10纳米的分辨率障碍。
7.Self-supervised deep learning encodes high-resolution features of protein subcellular localization.
自我监督的深度学习编码了蛋白质亚细胞定位的高分辨率特征。
8.Functional ultrasound localization microscopy reveals brain-wide neurovascular activity on a microscopic scale.
功能性超声定位显微镜显示了微观尺度上的全脑神经血管活动。
用于快速深层组织免疫标记的热稳定抗体
Heat-stabilized antibodies (SPEARS) enable thermally facilitated 3D immunolabeling (THiCK staining) of parvalbumin-expressing cells in a mouse cerebellar hemisphere.
热稳定抗体（SPEARS）可对小鼠小脑半球中表达小白蛋白的细胞进行热促进3D免疫标记（THiCK染色）。
1.Cell type-specific inference of differential expression in spatial transcriptomics.
在空间转录组学中推断特定细胞类型的差异性表达。
2.scBasset: sequence-based modeling of single-cell ATAC-seq using convolutional neural networks.
scBasset：使用卷积神经网络对单细胞ATAC-seq进行基于序列的建模。
3.MIRA: joint regulatory modeling of multimodal expression and chromatin accessibility in single cells.
MIRA：单细胞中多模式表达和染色质可及性的联合调节模型。
4.US-align: universal structure alignments of proteins, nucleic acids, and macromolecular complexes.
US-align：蛋白质、核酸和大分子复合物的通用结构比对。
5.Residue-wise local quality estimation for protein models from cryo-EM maps.
从低温电镜图中获得的蛋白质模型的残基局部质量估计。
6.Single-particle cryo-EM structures from iDPC–STEM at near-atomic resolution.
来自iDPC-STEM的单颗粒低温冷冻电镜结构，分辨率接近原子级。
7.Antibody stabilization for thermally accelerated deep immunostaining.
用于热加速深度免疫染色的抗体稳定化。
专注于研究非编码RNA的方法
This month we present a Focus on methods for studying noncoding RNA and future directions for deciphering the regulatory roles of noncoding RNA. The confetti conceptually illustrates the broad diversity of noncoding RNA and the complexity of their biological implications.
本月，我们将重点介绍研究非编码RNA的方法以及破译非编码RNA调控作用的未来方向。五彩纸屑从概念上说明了非编码RNA的广泛多样性及其生物学意义的复杂性。
1.RNA secondary structure packages evaluated and improved by high-throughput experiments.
通过高通量实验对RNA二级结构包进行评估和改进。
2.ISSAAC-seq enables sensitive and flexible multimodal profiling of chromatin accessibility and gene expression in single cells.
ISSAAC-seq能够对单细胞中的染色质可及性和基因表达进行敏感和灵活的多模态分析。
3.BIONIC: biological network integration using convolutions.
BIONIC：使用卷积的生物网络整合。
4.Event-driven acquisition for content-enriched microscopy.
事件驱动的采集，用于内容丰富的显微镜。
5.Event-triggered STED imaging.
事件触发的STED成像。
6.Cell region fingerprints enable highly precise single-cell tracking and lineage reconstruction.
细胞区域指纹实现了高度精确的单细胞追踪和血统重建。
7.A fluorescent sensor for real-time measurement of extracellular oxytocin dynamics in the brain.
用于实时测量大脑中细胞外催产素动态的荧光传感器。
8.A bead-based method for high-throughput mapping of the sequence- and force-dependence of T cell activation.
一种基于珠子的方法，用于高通量绘制T细胞激活的序列和力依赖性。
9.De novo construction of T cell compartment in humanized mice engrafted with iPSC-derived thymus organoids.
用iPSC衍生的胸腺器官移植的人源化小鼠中T细胞区的重新构建。
影像之美
The winning image of the Nikon Small World 2022 Photomicrography Competition, an embryonic foot of a Madagascar giant day gecko (Phelsuma grandis). The image was captured using whole-mount fluorescence staining, tissue clearing, high-resolution confocal microscopy and image stitching.
尼康小世界2022年显微摄影比赛的获奖图片，一只马达加斯加巨日壁虎（Phelsuma grandis）的胚胎脚。 该图像是使用整体荧光染色、组织透明化、高分辨率共聚焦显微镜和图像拼接捕获的。
1.Improved AlphaFold modeling with implicit experimental information.
用隐含的实验信息改进AlphaFold建模。
2.Profiling RNA at chromatin targets in situ by antibody-targeted tagmentation.
通过抗体靶向标记在原位对染色质目标的RNA进行分析。
3.Light-Seq: light-directed in situ barcoding of biomolecules in fixed cells and tissues for spatially indexed sequencing.
Light-Seq：对固定细胞和组织中的生物大分子进行光定向原位条码化，用于空间索引测序。
4.ClampFISH 2.0 enables rapid, scalable amplified RNA detection in situ.
ClampFISH 2.0实现了快速、可扩展的原位扩增RNA检测。
5.Annotation of spatially resolved single-cell data with STELLAR.
用STELLAR对空间分辨率的单细胞数据进行注释。
6.Resolution doubling in light-sheet microscopy via oblique plane structured illumination.
通过斜面结构照明实现光片显微镜的分辨率翻倍。
7.Incorporating the image formation process into deep learning improves network performance.
将图像形成过程纳入深度学习，提高了网络性能。
8.Omnipose: a high-precision morphology-independent solution for bacterial cell segmentation.
Omnipose：一种用于细菌细胞分割的高精度形态无关的解决方案。
9.Geometric engineering of organoid culture for enhanced organogenesis in a dish.
培养类器官的几何工程，以增强皿中的器官生成。
10.Sensitive genetically encoded sensors for population and subcellular imaging of cAMP in vivo.
敏感的基因编码传感器用于体内cAMP的群体和亚细胞成像。
11.neuromaps: structural and functional interpretation of brain maps.
neuromaps：脑图的结构和功能解释。
12.Netie: inferring the evolution of neoantigen–T cell interactions in tumors.
Netie：推断肿瘤中新抗原-T细胞相互作用的演变。
13.CODA: quantitative 3D reconstruction of large tissues at cellular resolution.
CODA：以细胞分辨率对大型组织进行定量三维重建。
14.Estimation of skeletal kinematics in freely moving rodents.
自由运动的啮齿动物的骨骼运动学的估计。
通过测序共同分析细胞外蛋白复合物和 mRNA
Proximity-sequencing (Prox-seq) uses DNA-barcoded antibody probes to detect proteins and their pairwise complexes on the surface of single cells.
邻近测序（Prox-seq）使用DNA条形码抗体探针检测单细胞表面的蛋白质及其成对复合物。
1.Quantification of extracellular proteins, protein complexes and mRNAs in single cells by proximity sequencing.
通过近距离测序对单细胞中的细胞外蛋白、蛋白复合物和mRNA进行量化。
2.Detection of m6A from direct RNA sequencing using a multiple instance learning framework.
使用多实例学习框架从直接RNA测序中检测m6A.
3.A framework for detecting noncoding rare-variant associations of large-scale whole-genome sequencing studies.
检测大规模全基因组测序研究的非编码罕见变异关联的框架。
4.Chemically stable fluorescent proteins for advanced microscopy.
用于高级显微镜的化学稳定荧光蛋白.
5.Image-seq: spatially resolved single-cell sequencing guided by in situ and in vivo imaging.
Image-seq：由原位和体内成像指导的空间分辨率单细胞测序。
6.Cellpose 2.0: how to train your own model.
Cellpose 2.0：如何训练自己的模型。
7.Capturing the start point of the virus–cell interaction with high-speed 3D single-virus tracking.
用高速三维单病毒追踪捕捉病毒-细胞相互作用的起始点。
8.Unsupervised discovery of tissue architecture in multiplexed imaging.
多重成像中组织结构的无监督发现。
