Self-assembly of protein superstructures by physical interactions under cytoplasm-like conditions

The structure-driven assembly of multimeric protein complexes and the formation of intracellular phase-like protein condensates have been the subject of intense research. However, the assembly of larger superstructures comprising cellular components, such as protein nanoparticles driven by general physical rather than specific biochemical interactions, remains relatively uncharacterized. Here, we use gas vesicles (GVs)—genetically encoded protein nanoparticles that form ordered intracellular clusters—as a model system to study the forces driving multiparticle assembly under cytoplasm-like conditions. Our calculations and experimental results show that the ordered assembly of GVs can be achieved by screening their mutual electrostatic repulsion with electrolytes and creating a crowding force with dissolved macromolecules. The precise balance of these forces results in different packing configurations. Biomacromolecules such as polylysine and DNA are capable of driving GV clustering. These results provide basic insights into how physically driven interactions affect the formation of protein superstructures, offer guidance for manipulating nanoparticle assembly in cellular environments through synthetic biology methods, and inform research on the biotechnology applications of GVs

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

The role of circadian clock in astrocytes: From cellular functions to ischemic stroke therapeutic targets

Accumulating evidence suggests that astrocytes, the abundant cell type in the central nervous system (CNS), play a critical role in maintaining the immune response after cerebral infarction, regulating the blood-brain barrier (BBB), providing nutrients to the neurons, and reuptake of glutamate. The circadian clock is an endogenous timing system that controls and optimizes biological processes. The central circadian clock and the peripheral clock are consistent, controlled by various circadian components, and participate in the pathophysiological process of astrocytes. Existing evidence shows that circadian rhythm controls the regulation of inflammatory responses by astrocytes in ischemic stroke (IS), regulates the repair of the BBB, and plays an essential role in a series of pathological processes such as neurotoxicity and neuroprotection. In this review, we highlight the importance of astrocytes in IS and discuss the potential role of the circadian clock in influencing astrocyte pathophysiology. A comprehensive understanding of the ability of the circadian clock to regulate astrocytes after stroke will improve our ability to predict the targets and biological functions of the circadian clock and gain insight into the basis of its intervention mechanism

Investigation of hydrate slurry flow behaviors in deep-sea pipes with different inclination angles

The marine area is the main direction of the development of oil and gas resources in the world. The pipeline transportation technology of natural gas hydrate slurry plays an important role in the exploitation of marine oil and gas and the exploitation of marine gas hydrate resources. In order to study the influence of pipe inclination on pipeline transportation, population balance model based on hydrate particle aggregation dynamics was coupled with the Eulerian–Eulerian two-fluid multiphase flow model to simulate the flow behaviors of hydrate slurry flow in pipes with different inclination angles. In the study, three variables of inclination, flow rate and initial particle size were considered. The results show that tilted pipes are beneficial to hydrate slurry transport rather than harmful. Meanwhile, higher flow rates and lower initial particle sizes are beneficial for promoting the flow safety of hydrate slurry transport. However, the flow pressure drop of the hydrate slurry increases with the increase of the flow rate and the decrease of the initial particle size, which is not conducive to the economics of mining. The research results in this paper can provide reference for the research of hydrate slurry flow safety and parameter guidance for hydrate solid fluidized mining

Improved Prognostic Prediction of Pancreatic Cancer Using Multi-Phase CT by Integrating Neural Distance and Texture-Aware Transformer

Pancreatic ductal adenocarcinoma (PDAC) is a highly lethal cancer in which the tumor-vascular involvement greatly affects the resectability and, thus, overall survival of patients. However, current prognostic prediction methods fail to explicitly and accurately investigate relationships between the tumor and nearby important vessels. This paper proposes a novel learnable neural distance that describes the precise relationship between the tumor and vessels in CT images of different patients, adopting it as a major feature for prognosis prediction. Besides, different from existing models that used CNNs or LSTMs to exploit tumor enhancement patterns on dynamic contrast-enhanced CT imaging, we improved the extraction of dynamic tumor-related texture features in multi-phase contrast-enhanced CT by fusing local and global features using CNN and transformer modules, further enhancing the features extracted across multi-phase CT images. We extensively evaluated and compared the proposed method with existing methods in the multi-center (n=4) dataset with 1,070 patients with PDAC, and statistical analysis confirmed its clinical effectiveness in the external test set consisting of three centers. The developed risk marker was the strongest predictor of overall survival among preoperative factors and it has the potential to be combined with established clinical factors to select patients at higher risk who might benefit from neoadjuvant therapy.Comment: MICCAI 202

Impaired reverse cholesterol transport and hepatic steatosis contribute to pathogenesis of high fat dietinduced hyperlipidemia in murine models

Purpose: To investigate the pathogenesis of high fat diet (HFD)-induced hyperlipidemia (HLP) in mice, rats and hamsters and to comparatively evaluate their sensitivity to HFD.Methods: Mice, rats and hamsters were fed with high-fat diet formulation (HFD, n = 8) or a control diet (control, n = 8) for 4 weeks. Changes in body weight, relative liver weight, serum lipid profile, expressions of hepatic marker gene of lipid metabolism and liver morphology were observed in three hyperlipidemic models.Results: Elevated total cholesterol (TC), triglyceride, low density lipoprotein-cholesterol (LDL-C) and high density lipoprotein-cholesterol (HDL-C) levels and body weight were observed in all hyperlipidemic animals (p < 0.05), while hepatic steatosis was manifested in rat and hamster HLP models, and increased hepatic TC level was only seen (p < 0.05) in hamster HLP model. Suppression of HMG-CoA reductase and up-regulation of lipoproteinlipase were observed in all HFD groups. Hepatic gene expression of LDLR, CYP7A1, LCAT, SR-B1, and ApoA I, which are a response to reverse cholesterol transport (RCT), were inhibited by HFD in the three models. Among these models, simultaneous suppression of HMG-CR, LCAT, LDLR and SR-BI and elevated LPL were features of the hamster model.Conclusion: As the results show, impaired RCT and excessive fat accumulation are major contributors to pathogenesis of HFD-induced murine HLP. Thus, the hamster model is more appropriate for hyperlipidemia research.Keywords: Hyperlipidemic model, Murine, Hamster, mRNA, Reverse cholesterol transport, High-fat diet, Pathogenesi

Dynamic air/liquid pockets for guiding microscale flow

Microscale flows of fluids are mainly guided either by solid matrices or by liquid–liquid interfaces. However, the solid matrices are plagued with persistent fouling problems, while liquid–liquid interfaces are limited to low-pressure applications. Here we report a dynamic liquid/solid/gas material containing both air and liquid pockets, which are formed by partially infiltrating a porous matrix with a functional liquid. Using detailed theoretical and experimental data, we show that the distribution of the air- and liquid-filled pores is responsive to pressure and enables the formation and instantaneous recovery of stable liquid–liquid interfaces that sustain a wide range of pressures and prevent channel contamination. This adaptive design is demonstrated for polymeric materials and extended to metal-based systems that can achieve unmatched mechanical and thermal stability. Our platform with its unique adaptive pressure and antifouling capabilities may offer potential solutions to flow control in microfluidics, medical devices, microscale synthesis, and biological assays