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Background The AMPA-type ionotropic glutamate receptor mediates fast excitatory neurotransmission in the brain. A variety of auxiliary subunits regulate its gating properties, assembly, and trafficking, but it is unknown if the binding of these auxiliary subunits to the receptor core is dynamically regulated. Here we investigate the interplay of the two auxiliary subunits γ-2 and GSG1L when binding to the AMPA receptor composed of four GluA1 subunits. Methods We use a three-color single-molecule imaging approach in living cells, which allows the direct observation of the receptors and both auxiliary subunits. Colocalization of different colors can be interpreted as interaction of the respective receptor subunits. Results Depending on the relative expression levels of γ-2 and GSG1L, the occupancy of binding sites shifts from one auxiliary subunit to the other, supporting the idea that they compete for binding to the receptor. Based on a model where each of the four binding sites at the receptor core can be either occupied by γ-2 or GSG1L, our experiments yield apparent dissociation constants for γ-2 and GSG1L in the range of 2.0–2.5/µm 2 . Conclusions The result that both binding affinities are in the same range is a prerequisite for dynamic changes of receptor composition under native conditions.

Sequencing studies of diffuse large B cell lymphoma (DLBCL) have identified hundreds of recurrently altered genes. However, it remains largely unknown whether and how these mutations may contribute to lymphomagenesis, either individually or in combination. Existing strategies to address this problem predominantly utilize cell lines, which are limited by their initial characteristics and subsequent adaptions to prolonged in vitro culture. Here, we describe a co-culture system that enables the ex vivo expansion and viral transduction of primary human germinal center B cells. Incorporation of CRISPR/Cas9 technology enables high-throughput functional interrogation of genes recurrently mutated in DLBCL. Using a backbone of BCL2 with either BCL6 or MYC , we identify co-operating genetic alterations that promote growth or even full transformation into synthetically engineered DLBCL models. The resulting tumors can be expanded and sequentially transplanted in vivo, providing a scalable platform to test putative cancer genes and to create mutation-directed, bespoke lymphoma models. A dearth of adequate preclinical models to faithfully mimic diffuse large B-cell lymphoma has hampered the identification of driver genes. Here, the authors present a co-culture system that enables ex vivo expansion, viral transduction and transformation of primary human germinal center B cells.

Sensitive and multiplexed RNA analysis at the single-molecule level remains a key challenge in molecular diagnostics. Conventional fluorescence microarrays provide high throughput but lack molecular resolution, whereas single-molecule sensors such as nanopores offer exquisite precision but limited scalability. Here, we present a DNA carrier-based nanoarray that integrates programmable nucleic acid hybridization with solid-state nanopore readout for direct, multiplexed RNA detection. Each modular DNA carrier is pre-assembled with spatially defined probe sites that sequence-specifically capture RNA targets of varying lengths and conformations, in which poly(dT) sequences both structurally facilitate target binding and enhance signal strength without the need for fluorescent or protein labeling. Upon nanopore translocation, hybridized carrier-target complexes generate binary ionic current signatures, allowing single-molecule identification of target occupancy at each sensing site. Using a ternary coordinate encoding system, we constructed a nanoarray comprising 27 carriers with 81 addressable sensing sites, enabling simultaneous detection of multiple bacterial and viral RNA targets within a single assay directly from total RNA extracts without target-specific isolation, amplification, or enrichment. By combining the multiplexing capability of traditional microarrays with the single-molecule precision of nanopore sensing, this carrier-based nanoarray establishes a scalable, programmable, and universally adaptable framework for high-throughput molecular diagnostics in complex biological backgrounds.

Sequencing studies of Diffuse Large B Cell Lymphoma (DLBCL) have identified hundreds of recurrently altered genes. However, it remains largely unknown whether and how these mutations may contribute to lymphomagenesis, either individually or in combination. Existing strategies to address this problem predominantly utilize cell lines, which are limited by their initial characteristics and subsequent adaptions to prolonged in vitro culture. Here, vivo expansion and viral transduction of primary human germinal center B cells. The incorporation of CRISPR/Cas9 technology enables high-throughput functional interrogation of genes recurrently mutated in DLBCL. Using a backbone of BCL2 with either BCL6 or MYC we have identified cooperating oncogenes that promote growth and survival, or even full transformation into synthetically engineered models of DLBCL. The resulting tumors can be expanded and sequentially transplanted in vivo, providing a scalable platform to test putative cancer genes and for the creation of mutation-directed, bespoke lymphoma models.

Schedules of survival, growth and reproduction are key life‐history traits. Data on how these traits vary among species and populations are fundamental to our understanding of the ecological conditions that have shaped plant evolution. Because these demographic schedules determine population growth or decline, such data help us understand how different biomes shape plant ecology, how plant populations and communities respond to global change and how to develop successful management tools for endangered or invasive species. Matrix population models summarize the life cycle components of survival, growth and reproduction, while explicitly acknowledging heterogeneity among classes of individuals in the population. Matrix models have comparable structures, and their emergent measures of population dynamics, such as population growth rate or mean life expectancy, have direct biological interpretations, facilitating comparisons among populations and species. Thousands of plant matrix population models have been parameterized from empirical data, but they are largely dispersed through peer‐reviewed and grey literature, and thus remain inaccessible for synthetic analysis. Here, we introduce the compadre Plant Matrix Database version 3.0, an open‐source online repository containing 468 studies from 598 species world‐wide (672 species hits, when accounting for species studied in more than one source), with a total of 5621 matrices. compadre also contains relevant ancillary information (e.g. ecoregion, growth form, taxonomy, phylogeny) that facilitates interpretation of the numerous demographic metrics that can be derived from the matrices. Synthesis. Large collections of data allow broad questions to be addressed at the global scale, for example, in genetics (genbank), functional plant ecology (try, bien, d3) and grassland community ecology (nutnet). Here, we present compadre, a similarly data‐rich and ecologically relevant resource for plant demography. Open access to this information, its frequent updates and its integration with other online resources will allow researchers to address timely and important ecological and evolutionary questions.

Externally modulated DFB lasers (EML) and vertically illuminated photodetectors are presented. Because of their excellent high-speed behavior and operation wavelength of 1310 nm, the devices are of interest for intra-data center communication. Since the EML and the photodetector chips are compatible with current systems, these devices are candidates for upgrading existing transceivers to higher baud rates. Therefore, a proof of concept for 100 GBaud data transmission with the presented components is demonstrated. Even without predistortion, the experiments show clearly open eye diagrams.

1. Schedules of survival, growth and reproduction are key life-history traits. Data on how these traits vary among species and populations are fundamental to our understanding of the ecological conditions that have shaped plant evolution. Because these demographic schedules determine population growth or decline, such data help us understand how different biomes shape plant ecology, how plant populations and communities respond to global change and how to develop successful management tools for endangered or invasive species. 2. Matrix population models summarize the life cycle components of survival, growth and reproduction, while explicitly acknowledging heterogeneity among classes of individuals in the population. Matrix models have comparable structures, and their emergent measures of population dynamics, such as population growth rate or mean life expectancy, have direct biological interpretations, facilitating comparisons among populations and species. 3. Thousands of plant matrix population models have been parameterized from empirical data, but they are largely dispersed through peer-reviewed and grey literature, and thus remain inaccessible for synthetic analysis. Here, we introduce the COMPADRE Plant Matrix Database version 3.0, an open-source online repository containing 468 studies from 598 species world-wide (672 species hits, when accounting for species studied in more than one source), with a total of 5621 matrices. COMPADRE also contains relevant ancillary information (e.g. ecoregion, growth form, taxonomy, phylogeny) that facilitates interpretation of the numerous demographic metrics that can be derived from the matrices. 4. Synthesis. Large collections of data allow broad questions to be addressed at the global scale, for example, in genetics (GENBANK), functional plant ecology (TRY, BIEN, D3) and grassland community ecology (NUTNET). Here, we present COMPADRE, a similarly data-rich and ecologically relevant resource for plant demography. Open access to this information, its frequent updates and its integration with other online resources will allow researchers to address timely and important ecological and evolutionary questions.

Schedules of survival, growth and reproduction are key life‐history traits. Data on how these traits vary among species and populations are fundamental to our understanding of the ecological conditions that have shaped plant evolution. Because these demographic schedules determine population growth or decline, such data help us understand how different biomes shape plant ecology, how plant populations and communities respond to global change and how to develop successful management tools for endangered or invasive species. Matrix population models summarize the life cycle components of survival, growth and reproduction, while explicitly acknowledging heterogeneity among classes of individuals in the population. Matrix models have comparable structures, and their emergent measures of population dynamics, such as population growth rate or mean life expectancy, have direct biological interpretations, facilitating comparisons among populations and species. Thousands of plant matrix population models have been parameterized from empirical data, but they are largely dispersed through peer‐reviewed and grey literature, and thus remain inaccessible for synthetic analysis. Here, we introduce the compadre Plant M atrix D atabase version 3.0, an open‐source online repository containing 468 studies from 598 species world‐wide (672 species hits, when accounting for species studied in more than one source), with a total of 5621 matrices. compadre also contains relevant ancillary information (e.g. ecoregion, growth form, taxonomy, phylogeny) that facilitates interpretation of the numerous demographic metrics that can be derived from the matrices. Synthesis . Large collections of data allow broad questions to be addressed at the global scale, for example, in genetics ( genbank ), functional plant ecology ( try, bien, d3 ) and grassland community ecology ( nutnet ). Here, we present compadre , a similarly data‐rich and ecologically relevant resource for plant demography. Open access to this information, its frequent updates and its integration with other online resources will allow researchers to address timely and important ecological and evolutionary questions.