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Neural circuits are characterized by genetically and functionally diverse cell types. A mechanistic understanding of circuit function is predicated on linking the genetic and physiological properties of individual neurons. However, it remains highly challenging to map the transcriptional properties to functionally heterogeneous neuronal subtypes in mammalian cortical circuits in vivo . Here, we introduce a high-throughput two-photon nuclear phototagging (2P-NucTag) approach optimized for on-demand and indelible labeling of single neurons via a photoactivatable red fluorescent protein following in vivo functional characterization in behaving mice. We demonstrate the utility of this function-forward pipeline by selectively labeling and transcriptionally profiling previously inaccessible 'place' and 'silent' cells in the mouse hippocampus. Our results reveal unexpected differences in gene expression between these hippocampal pyramidal neurons with distinct spatial coding properties. Thus, 2P-NucTag opens a new way to uncover the molecular principles that govern the functional organization of neural circuits.

Americans bear a high chronic stress burden, particularly during the COVID-19 pandemic. Although social media have many strengths to complement the weaknesses of conventional stress measures, including surveys, they have been rarely utilized to detect individuals self-reporting chronic stress. Thus, this study aimed to develop and evaluate an automatic system on Twitter to identify users who have self-reported chronic stress experiences. Using the Twitter public streaming application programming interface, we collected tweets containing certain stress-related keywords (eg, "chronic," "constant," "stress") and then filtered the data using pre-defined text patterns. We manually annotated tweets with (without) self-report of chronic stress as positive (negative). We trained multiple classifiers and tested them via accuracy and F1 score. We annotated 4195 tweets (1560 positives, 2635 negatives), achieving an inter-annotator agreement of 0.83 (Cohen's kappa). The classifier based on Bidirectional Encoder Representation from Transformers performed the best (accuracy of 83.6% [81.0-86.1]), outperforming the second best-performing classifier (support vector machines: 76.4% [73.5-79.3]). The past tweets from the authors of positive tweets contained useful information, including sources and health impacts of chronic stress. Our study demonstrates that users' self-reported chronic stress experiences can be automatically identified on Twitter, which has a high potential for surveillance and large-scale intervention., (Copyright © 2022 The Authors. Published by Wolters Kluwer Health, Inc.)

As a new family member of the emerging two-dimensional (2D) monoelemental materials (Xenes), germanene has shown promising advantages over the prototypical 2D Xenes, such as black phosphorus (BP) and graphene. However, efficient manufacture of novel germanene nanostructures is still a challenge. Herein, a simple top-down approach for the liquid-exfoliation of ultra-small germanene quantum dots (GeQDs) is presented. The prepared GeQDs possess an average lateral size of about 4.5 nm and thickness of about 2.2 nm. The functionalized GeQDs were demonstrated to be robust photothermal agents (PTAs) with outstanding photothermal conversion efficacy (higher than those of graphene and BPQDs), superior stability, and excellent biocompatibility. As a proof-of-principle, 2D GeQDs-based PTAs were used in fluorescence/photoacoustic/photothermal-imaging-guided hyperpyrexia ablation of tumors. This work could expand the application of 2D germanene to the field of photonic cancer nanomedicine., (© 2019 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.)