Natural killer (NK) cells discern the health of other cells by recognising the balance of activating and inhibitory ligands expressed by each target cell. However, how the integration of activating and inhibitory signals relates to formation of the NK cell immune synapse remains a central question in our understanding of NK cell recognition. Here we report that ligation of LFA-1 on NK cells induced asymmetrical cell spreading and migration. In contrast, ligation of the activating receptor NKG2D induced symmetrical spreading of ruffled lamellipodia encompassing a dynamic ring of f-actin, concurrent with polarization towards a target cell and a “stop” signal. Ligation of both LFA-1 and NKG2D together resulted in symmetrical spreading but co-ligation of inhibitory receptors reverted NK cells to an asymmetrical migratory configuration leading to inhibitory synapses being smaller and more rapidly disassembled. Using micropatterned activating and inhibitory ligands, signals were found to be continuously and locally integrated during spreading. Together, these data demonstrate that NK cells spread to form large, stable, symmetrical synapses if activating signals dominate, whereas asymmetrical migratory “kinapses” are favoured if inhibitory signals dominate. This clarifies how the integration of activating and inhibitory receptor signals is translated to an appropriate NK cell response.

The Analytical Data Store Tools market is experiencing robust growth, driven by the increasing need for real-time insights and advanced analytics across diverse industries. The market, estimated at $50 billion in 2025, is projected to maintain a healthy Compound Annual Growth Rate (CAGR) of 15% from 2025 to 2033, reaching approximately $150 billion by 2033. This expansion is fueled by several key factors: the proliferation of big data, the rising adoption of cloud-based solutions offering scalability and cost-effectiveness, and the growing demand for improved decision-making capabilities across organizations. Key trends include the increasing integration of AI and machine learning into analytical data store tools, the emergence of serverless architectures, and a focus on enhanced data security and governance. While the market faces challenges like data integration complexities and the need for skilled professionals, the overall outlook remains positive, driven by continued innovation and expanding enterprise adoption. The competitive landscape is highly dynamic, with major players like Google, Snowflake, Microsoft, Amazon, and Oracle leading the charge. These established players are constantly innovating and expanding their offerings to meet evolving customer needs, while smaller, specialized companies are emerging to cater to niche requirements. The market's segmentation reflects this diversity, with solutions catering to various data volumes, industry verticals, and deployment models (cloud, on-premise, hybrid). Geographical expansion, particularly in rapidly developing economies, presents a significant opportunity for growth. The historical period (2019-2024) likely saw a slower growth rate than the projected future growth, reflecting the time taken for market maturity and broader adoption of cloud technologies. The continued focus on data-driven decision-making across industries ensures the sustained growth trajectory of the Analytical Data Store Tools market.

The neural networks that regulate animal behaviors are encoded in terms of neuronal excitation and inhibition at the synapse. However, how the temporal activity of neural circuits is dynamically and precisely characterized by each signaling interaction via excitatory or inhibitory synapses, and how both synaptic patterns are organized to achieve fine regulation of circuit activities is unclear. Here, we show that in Caenorhabditis elegans, the excitatory/inhibitory switch from asymmetric sensory neurons (ASEL/R) following changes in NaCl concentration is required for a rapid and fine response in postsynaptic interneurons (AIBs). We found that glutamate released by the ASEL neuron inhibits AIBs via a glutamate-gated chloride channel localized at the distal region of AIB neurites. Conversely, glutamate released by the ASER neuron activates AIBs via an AMPA-type ionotropic receptor and a G-protein-coupled metabotropic glutamate receptor. Interestingly, these excitatory receptors are mainly distributed at the proximal regions of the neurite. Our results suggest that these convergent synaptic patterns can tune and regulate the proper behavioral response to environmental changes in NaCl.

The Data Warehousing market, valued at $31.15 billion in 2025, is projected to experience robust growth, driven by the increasing need for businesses to leverage data for informed decision-making. A Compound Annual Growth Rate (CAGR) of 13.64% from 2025 to 2033 indicates a significant expansion, fueled by several key factors. The rising adoption of cloud-based solutions offers scalability and cost-effectiveness, attracting businesses of all sizes. Furthermore, the growing volume and complexity of data necessitate efficient data warehousing solutions for better analysis and insights. Advancements in big data technologies and analytics further propel market growth, enabling businesses to derive valuable insights from previously untapped data sources. Competitive landscape analysis reveals a mix of established players like Microsoft, Oracle, and IBM, alongside emerging innovative companies focusing on cloud-native solutions and specialized analytics. The market segmentation, categorized by deployment (on-premise, hybrid, cloud-based), reflects the evolving preferences of businesses towards flexible and adaptable data warehousing solutions. Geographic expansion, particularly in rapidly developing economies of Asia-Pacific and parts of the Middle East and Africa, offers significant potential for future growth. However, challenges remain, including data security concerns, integration complexities, and the need for skilled professionals to manage and interpret data effectively. The forecast period (2025-2033) anticipates a substantial market expansion, with the cloud-based segment likely dominating due to its inherent scalability and cost advantages. North America is expected to maintain a substantial market share, driven by technological advancements and early adoption, but regions like Asia-Pacific and Europe are expected to witness faster growth due to increasing digital transformation initiatives and government investments in data infrastructure. The competitive landscape remains dynamic, with companies continually innovating and expanding their product offerings to meet evolving business needs and cater to specific industry verticals. Future growth hinges on addressing data security challenges, simplifying data integration processes, and fostering a skilled workforce capable of utilizing the full potential of data warehousing technologies.

The global Financial Data Warehouse (FDW) solution market is experiencing robust growth, driven by increasing regulatory compliance needs, the burgeoning adoption of advanced analytics, and the demand for improved decision-making capabilities within the financial services sector. The market, estimated at $15 billion in 2025, is projected to achieve a Compound Annual Growth Rate (CAGR) of 12% from 2025 to 2033, reaching approximately $40 billion by 2033. This expansion is fueled by several key factors, including the rising adoption of cloud-based solutions offering scalability and cost-effectiveness, the increasing integration of big data technologies to analyze complex financial datasets, and a growing need for real-time insights to support agile business strategies. Key players like Amazon Redshift, Snowflake, and Microsoft Azure Synapse are heavily invested in enhancing their FDW offerings, driving competition and innovation within the sector. The market is segmented by deployment (cloud, on-premises), solution type (data integration, data warehousing, data visualization), and end-user (banks, insurance companies, investment firms). The cloud segment is expected to dominate due to its inherent advantages in scalability, flexibility, and cost-efficiency. The competitive landscape is marked by a mix of established players and emerging technology providers. While established vendors like Oracle and IBM hold significant market share, cloud-based solutions are rapidly gaining traction, challenging traditional players. The geographic distribution of the market is diverse, with North America and Europe currently holding the largest market shares, but significant growth is anticipated in Asia-Pacific regions due to increasing digitalization and financial sector development. However, challenges such as data security concerns, integration complexities, and the high cost of implementation of advanced analytics remain potential restraints to market growth. Addressing these challenges through robust security measures, simplified integration processes, and flexible pricing models will be crucial for sustained market expansion.

The cloud data warehouse market is experiencing robust growth, driven by the increasing need for scalable, cost-effective, and readily accessible data analytics solutions. The market's expansion is fueled by several key factors, including the burgeoning adoption of cloud computing across various industries, the proliferation of big data, and the growing demand for real-time business intelligence. Organizations are migrating from on-premise data warehouses to cloud-based solutions to leverage enhanced scalability, reduced infrastructure costs, and improved agility. This shift is further accelerated by the availability of advanced analytics tools and services within the cloud ecosystem, enabling businesses to derive actionable insights from their data more efficiently. Competitive pressures and the need to gain a competitive edge are also significant drivers, pushing enterprises to adopt sophisticated data warehousing solutions capable of handling complex analytical workloads. The market is highly fragmented, with major players such as Amazon, Google, Microsoft, and others competing intensely through innovation, strategic partnerships, and aggressive pricing strategies. While the market shows significant promise, certain challenges persist. Data security and privacy concerns remain a major obstacle to wider adoption, particularly in regulated industries. Integration complexities with existing on-premise systems and the need for skilled professionals to manage and maintain cloud data warehouses also present hurdles. However, ongoing technological advancements in areas such as data encryption, access control, and automated data integration are mitigating these challenges. Furthermore, the emergence of new technologies, such as serverless architectures and AI-powered analytics, is continuously reshaping the market landscape, fostering innovation and expanding the market's potential. Over the forecast period (2025-2033), consistent growth is anticipated, fueled by ongoing digital transformation initiatives across various sectors. We estimate a conservative CAGR (considering industry averages for similar tech sectors) of 15% over this period, indicating substantial growth opportunities.

The spatial organization of synaptic inputs on the dendritic tree of cortical neurons is considered to play an important role in the dendritic integration of synaptic activity. Active electrical properties of dendrites and mechanisms of dendritic integration have been studied for a long time. New technological developments are now enabling the characterization of the spatial organization of synaptic inputs on dendrites. However, quantitative methods for the analysis of such data are lacking. In order to place cluster parameters into the framework of dendritic integration and synaptic summation, these parameters need to be assessed rigorously in a quantitative manner. Here I present an approach for the analysis of synaptic input clusters on the dendritic tree that is based on combinatorial analysis of the likelihoods to observe specific input arrangements. This approach is superior to the commonly applied analysis of nearest neighbor distances between synaptic inputs comparing their distribution to simulations with random reshuffling or bootstrapping. First, the new approach yields exact likelihood values rather than approximate numbers obtained from simulations. Second and more importantly, the new approach identifies individual clusters and thereby allows to quantify and characterize individual cluster properties.

A central process in immunity is the activation of T cells through interaction of T cell receptors (TCRs) with agonistic peptide-major histocompatibility complexes (pMHC) on the surface of antigen presenting cells (APCs). TCR-pMHC binding triggers the formation of an extensive contact between the two cells termed the immunological synapse, which acts as a platform for integration of multiple signals determining cellular outcomes, including those from multiple co-stimulatory/inhibitory receptors. Contributors to this include a number of chemokine receptors, notably CXC-chemokine receptor 4 (CXCR4), and other members of the G protein-coupled receptor (GPCR) family. Although best characterized as mediators of ligand-dependent chemotaxis, some chemokine receptors are also recruited to the synapse and contribute to signaling in the absence of ligation. How these and other GPCRs integrate within the dynamic structure of the synapse is unknown, as is how their normally migratory Gαi-coupled signaling is terminated upon recruitment. Here, we report the spatiotemporal organization of several GPCRs, focusing on CXCR4, and the G protein Gαi2 within the synapse of primary human CD4+ T cells on supported lipid bilayers, using standard- and super-resolution fluorescence microscopy. We find that CXCR4 undergoes orchestrated phases of reorganization, culminating in recruitment to the TCR-enriched center. This appears to be dependent on CXCR4 ubiquitination, and does not involve stable interactions with TCR microclusters, as viewed at the nanoscale. Disruption of this process by mutation impairs CXCR4 contributions to cellular activation. Gαi2 undergoes active exclusion from the synapse, partitioning from centrally-accumulated CXCR4. Using a CRISPR-Cas9 knockout screen, we identify several diverse GPCRs with contributions to T cell activation, most significantly the sphingosine-1-phosphate receptor S1PR1, and the oxysterol receptor GPR183. These, and other GPCRs, undergo organization similar to CXCR4; including initial exclusion, centripetal transport, and lack of receptor-TCR interactions. These constitute the first observations of GPCR dynamics within the synapse, and give insights into how these receptors may contribute to T cell activation. The observation of broad GPCR contributions to T cell activation also opens the possibility that modulating GPCR expression in response to cell status or environment may directly regulate responsiveness to pMHC.

The Big Data Services market, valued at $32.51 billion in 2025, is experiencing robust growth, projected to expand at a Compound Annual Growth Rate (CAGR) of 27.81% from 2025 to 2033. This explosive growth is fueled by several key drivers. The increasing volume and variety of data generated across industries necessitate sophisticated solutions for storage, processing, and analysis. The rise of cloud computing provides scalable and cost-effective infrastructure for Big Data initiatives, further accelerating market expansion. Furthermore, the growing adoption of advanced analytics techniques, such as machine learning and artificial intelligence, is driving demand for Big Data services to extract valuable insights from complex datasets. This allows businesses to make more informed decisions, optimize operations, and gain a competitive edge. While data security and privacy concerns represent a potential restraint, the market's overall trajectory remains strongly positive. The market is segmented by service type (consulting, implementation, integration, managed services), deployment model (cloud, on-premise), organization size (small, medium, large), and industry vertical (BFSI, healthcare, retail, manufacturing). Key players like IBM, Microsoft, Oracle, and Amazon Web Services are fiercely competitive, investing heavily in research and development to maintain market leadership. The forecast period (2025-2033) anticipates continued high growth, driven by increasing digital transformation across sectors. Businesses are leveraging Big Data to personalize customer experiences, improve operational efficiency, and develop new revenue streams. The expansion into emerging economies will also contribute significantly to market expansion, as these regions adopt Big Data technologies at a rapid pace. However, the successful implementation of Big Data initiatives relies on skilled professionals. Addressing the talent gap through robust training and development programs will be crucial for sustaining this rapid growth. Competitive pricing strategies and the emergence of innovative service offerings will shape the competitive landscape. The market’s long-term outlook remains exceptionally strong, driven by technological advancements and the ever-increasing reliance on data-driven decision-making. Recent developments include: May 2023 : Microsoft has introduced Microsft fabric an softend-to-end, Unified Analytics Platform, which enables organisations to integrate all data and analytical tools they need, Where By making it possible for data and business professionals to unlock their potential, as well as lay the foundation for an era of Artificial Intelligence, fabric creates a single unified product that brings together technologies like Azure Data Factory, Azure Synapse Analytics, and Power BI., November 2022: Amazon Web Services, Inc. (AWS) released five new features in its database and analytics portfolios. These updates enable users to manage and analyze data at a petabyte scale more efficiently and quickly, simplifying the process for customers to operate the high-performance database and analytics workloads at scale., October 2022: Oracle introduced the Oracle Network Analytics Suite, which includes a new cloud-native portfolio of analytics tools. This suite enables operators to make more automated and informed decisions regarding the performance and stability of their entire 5G network core by combining network function data with machine learning and artificial intelligence.. Key drivers for this market are: Increasing Cloud Adoption And Rise In The Data Volume Generated, Increasing Demand For Improving Organization's Internal Efficiency; Growing Adoption of Private Cloud. Potential restraints include: Increasing Cloud Adoption And Rise In The Data Volume Generated, Increasing Demand For Improving Organization's Internal Efficiency; Growing Adoption of Private Cloud. Notable trends are: Growing Adoption of Private Cloud is Driving the Market.

This file contains the source data for all figures from "Structured Dendritic Inhibition Supports Branch-selective Integration in CA1 Pyramidal Cells" by Bloss et al (2016). Each tab relates to a figure (Figures 1-5 and Figures S1-S5). Where applicable, the group mean, SD, and N have been provided.

The superior colliculus (SC), a conserved midbrain node with extensive long-range connectivity throughout the brain, is a key structure for innate behaviors. Descending cortical pathways are increasingly recognized as central control points for SC-mediated behaviors, but how cortico-collicular pathways coordinate SC activity at the cellular level is poorly understood. Moreover, despite the known role of the SC as a multisensory integrator, the involvement of the SC in the somatosensory system is largely unexplored in comparison to its involvement in the visual and auditory systems. Here, we mapped the connectivity of the whisker-sensitive region of the SC in mice with trans-synaptic and intersectional tracing tools and in vivo electrophysiology. The results reveal a novel trans-collicular connectivity motif in which neurons in motor- and somatosensory cortices impinge onto the brainstem-SC-brainstem sensory-motor arc and onto SC-midbrain output pathways via only one synapse in the SC. Intersectional approaches and optogenetically assisted connectivity quantifications in vivo reveal convergence of motor and somatosensory cortical input on individual SC neurons, providing a new framework for sensory-motor integration in the SC. More than a third of the cortical recipient neurons in the whisker SC are GABAergic neurons, which include a hitherto unknown population of GABAergic projection neurons targeting thalamic nuclei and the zona incerta. These results pinpoint a whisker region in the SC of mice as a node for the integration of somatosensory and motor cortical signals via parallel excitatory and inhibitory trans-collicular pathways, which link cortical and subcortical whisker circuits for somato-motor integration.