Flows: Building Blocks of Reasoning and Collaborating AI

Recent advances in artificial intelligence (AI) have produced highly capable and controllable systems. This creates unprecedented opportunities for structured reasoning as well as collaboration among multiple AI systems and humans. To fully realize this potential, it is essential to develop a principled way of designing and studying such structured interactions. For this purpose, we introduce the conceptual framework of Flows: a systematic approach to modeling complex interactions. Flows are self-contained building blocks of computation, with an isolated state, communicating through a standardized message-based interface. This modular design allows Flows to be recursively composed into arbitrarily nested interactions, with a substantial reduction of complexity. Crucially, any interaction can be implemented using this framework, including prior work on AI--AI and human--AI interactions, prompt engineering schemes, and tool augmentation. We demonstrate the potential of Flows on the task of competitive coding, a challenging task on which even GPT-4 struggles. Our results suggest that structured reasoning and collaboration substantially improve generalization, with AI-only Flows adding +$21$ and human--AI Flows adding +$54$ absolute points in terms of solve rate. To support rapid and rigorous research, we introduce the aiFlows library. The library comes with a repository of Flows that can be easily used, extended, and composed into novel, more complex Flows. The aiFlows library is available at https://github.com/epfl-dlab/aiflows. Data and Flows for reproducing our experiments are available at https://github.com/epfl-dlab/cc_flows

Tumorigenesis of basal muscle invasive bladder cancer was mediated by PTEN protein degradation resulting from SNHG1 upregulation

Abstract Background Phosphatase and tensin homolog deleted on chromosome ten (PTEN) serves as a powerful tumor suppressor, and has been found to be downregulated in human bladder cancer (BC) tissues. Despite this observation, the mechanisms contributing to PTEN’s downregulation have remained elusive. Methods We established targeted genes’ knockdown or overexpressed cell lines to explore the mechanism how it drove the malignant transformation of urothelial cells or promoted anchorageindependent growth of human basal muscle invasive BC (BMIBC) cells. The mice model was used to validate the conclusion in vivo. The important findings were also extended to human studies. Results In this study, we discovered that mice exposed to N-butyl-N-(4-hydroxybu-tyl)nitrosamine (BBN), a specific bladder chemical carcinogen, exhibited primary BMIBC accompanied by a pronounced reduction in PTEN protein expression in vivo. Utilizing a lncRNA deep sequencing high-throughput platform, along with gain- and loss-of-function analyses, we identified small nucleolar RNA host gene 1 (SNHG1) as a critical lncRNA that might drive the formation of primary BMIBCs in BBN-treated mice. Cell culture results further demonstrated that BBN exposure significantly induced SNHG1 in normal human bladder urothelial cell UROtsa. Notably, the ectopic expression of SNHG1 alone was sufficient to induce malignant transformation in human urothelial cells, while SNHG1 knockdown effectively inhibited anchorage-independent growth of human BMIBCs. Our detailed investigation revealed that SNHG1 overexpression led to PTEN protein degradation through its direct interaction with HUR. This interaction reduced HUR binding to ubiquitin-specific peptidase 8 (USP8) mRNA, causing degradation of USP8 mRNA and a subsequent decrease in USP8 protein expression. The downregulation of USP8, in turn, increased PTEN polyubiquitination and degradation, culminating in cell malignant transformation and BMIBC anchorageindependent growth. In vivo studies confirmed the downregulation of PTEN and USP8, as well as their positive correlations in both BBN-treated mouse bladder urothelium and tumor tissues of bladder cancer in nude mice. Conclusions Our findings, for the first time, demonstrate that overexpressed SNHG1 competes with USP8 for binding to HUR. This competition attenuates USP8 mRNA stability and protein expression, leading to PTEN protein degradation, consequently, this process drives urothelial cell malignant transformation and fosters BMIBC growth and primary BMIBC formation

Towards a Dynamic Clamp for Neurochemical Modalities

The classic dynamic clamp technique uses a real-time electrical interface between living cells and neural simulations in order to investigate hypotheses about neural function and structure. One of the acknowledged drawbacks of that technique is the limited control of the cells’ chemical microenvironment. In this manuscript, we use a novel combination of nanosensor and microfluidic technology and microfluidic and neural simulations to add sensing and control of chemical concentrations to the dynamic clamp technique. Specifically, we use a microfluidic lab-on-a-chip to generate distinct chemical concentration gradients (ions or neuromodulators), to register the concentrations with embedded nanosensors and use the processed signals as an input to simulations of a neural cell. The ultimate goal of this project is to close the loop and provide sensor signals to the microfluidic lab-on-a-chip to mimic the interaction of the simulated cell with other cells in its chemical environment