SGTA Recognizes a Noncanonical Ubiquitin-like Domain in the Bag6-Ubl4A-Trc35 Complex to Promote Endoplasmic Reticulum-Associated Degradation

SummaryElimination of aberrantly folded polypeptides from the endoplasmic reticulum (ER) by the ER-associated degradation (ERAD) system promotes cell survival under stress conditions. This quality control mechanism requires movement of misfolded proteins across the ER membrane for targeting to the cytosolic proteasome, a process facilitated by a “holdase” complex, consisting of Bag6 and the cofactors Ubl4A and Trc35. This multiprotein complex also participates in several other protein quality control processes. Here, we report SGTA as a component of the Bag6 system, which cooperates with Bag6 to channel dislocated ERAD substrates that are prone to aggregation. Using nuclear magnetic resonance spectroscopy and biochemical assays, we demonstrate that SGTA contains a noncanonical ubiquitin-like-binding domain that interacts specifically with an unconventional ubiquitin-like protein/domain in Ubl4A at least in part via electrostatics. This interaction helps recruit SGTA to Bag6, enhances substrate loading to Bag6, and thus prevents the formation of nondegradable protein aggregates in ERAD

Accurate simulation of ice and snow runoff for the mountainous terrain of the Kunlun Mountains, China

While mountain runoff provides great potential for the development and life quality of downstream populations, it also frequently causes seasonal disasters. The accurate modeling of hydrological processes in mountainous areas, as well as the amount of meltwater from ice and snow, is of great significance for the local sustainable development, hydropower regulations, and disaster prevention. In this study, an improved model, the Soil Water Assessment Tool with added ice-melt module (SWATAI) was developed based on the Soil Water Assessment Tool (SWAT), a semi-distributed hydrological model, to simulate ice and snow runoff. A temperature condition used to determine precipitation types has been added in the SWATAI model, along with an elevation threshold and an accumulative daily temperature threshold for ice melt, making it more consistent with the runoff process of ice and snow. As a supplementary reference, the comparison between the normalized difference vegetation index (NDVI) and the quantity of meltwater were conducted to verify the simulation results and assess the impact of meltwater on the ecology. Through these modifications, the accuracy of the daily flow simulation results has been considerably improved, and the contribution rate of ice and snow melt to the river discharge calculated by the model increased by 18.73%. The simulation comparison of the flooding process revealed that the accuracy of the simulated peak flood value by the SWATAI was 77.65% higher than that of the SWAT, and the temporal accuracy was 82.93% higher. The correlation between the meltwater calculated by the SWATAI and the NDVI has also improved significantly. This improved model could simulate the flooding processes with high temporal resolution in alpine regions. The simulation results could provide technical support for economic benefits and reasonable reference for flood prevention

Linking Obesity with Colorectal Cancer: Epidemiology and Mechanistic Insights

The incidence of obesity and colorectal cancer (CRC) has risen rapidly in recent decades. More than 650 million obese and 2 billion overweight individuals are currently living in the world. CRC is the third most common cancer. Obesity is regarded as one of the key environmental risk factors for the pathogenesis of CRC. In the present review, we mainly focus on the epidemiology of obesity and CRC in the world, the United States, and China. We also summarize the molecular mechanisms linking obesity to CRC in different aspects, including nutriology, adipokines and hormones, inflammation, gut microbiota, and bile acids. The unmet medical needs for obesity-related CRC are still remarkable. Understanding the molecular basis of these associations will help develop novel therapeutic targets and approaches for the treatment of obesity-related CRC

A naphthalimide-based probe for phosgene sensing based on the phosgene-induced beckmann rearrangement

Abstract(#br)A new probe for selective and sensitive phosgene sensing in acetonitrile was developed. The sensing mechanism was based on the mechanism of the phosgene-induced Beckmann rearrangement of the naphthalimide fluorophore. An electron-withdrawing ketoxime, which was used as the phosgene receptor, was attached to the 4-position on the 1,8-naphthalimide chromophore to constituted a nonfluorescent probe. The reaction of phosgene with ketoxime induced a Beckmann rearrangement, which was followed by conversion of the nonfluorescent probe into the 4-acetamido-1,8- naphthalimide fluorophore, which emits bright blue fluorescence at 488 nm. The probe exhibited a detection limit of 6.3 nM for phosgene. In addition, the probe-loaded filter stripe for successful monitoring of gaseous phosgene was also demonstrated

On the Robustness of ChatGPT: An Adversarial and Out-of-distribution Perspective

ChatGPT is a recent chatbot service released by OpenAI and is receiving increasing attention over the past few months. While evaluations of various aspects of ChatGPT have been done, its robustness, i.e., the performance to unexpected inputs, is still unclear to the public. Robustness is of particular concern in responsible AI, especially for safety-critical applications. In this paper, we conduct a thorough evaluation of the robustness of ChatGPT from the adversarial and out-of-distribution (OOD) perspective. To do so, we employ the AdvGLUE and ANLI benchmarks to assess adversarial robustness and the Flipkart review and DDXPlus medical diagnosis datasets for OOD evaluation. We select several popular foundation models as baselines. Results show that ChatGPT shows consistent advantages on most adversarial and OOD classification and translation tasks. However, the absolute performance is far from perfection, which suggests that adversarial and OOD robustness remains a significant threat to foundation models. Moreover, ChatGPT shows astounding performance in understanding dialogue-related texts and we find that it tends to provide informal suggestions for medical tasks instead of definitive answers. Finally, we present in-depth discussions of possible research directions.Comment: Technical report; code is at: https://github.com/microsoft/robustlear

POST-IVUS: A perceptual organisation-aware selective transformer framework for intravascular ultrasound segmentation

Intravascular ultrasound (IVUS) is recommended in guiding coronary intervention. The segmentation of coronary lumen and external elastic membrane (EEM) borders in IVUS images is a key step, but the manual process is time-consuming and error-prone, and suffers from inter-observer variability. In this paper, we propose a novel perceptual organisation-aware selective transformer framework that can achieve accurate and robust segmentation of the vessel walls in IVUS images. In this framework, temporal context-based feature encoders extract efficient motion features of vessels. Then, a perceptual organisation-aware selective transformer module is proposed to extract accurate boundary information, supervised by a dedicated boundary loss. The obtained EEM and lumen segmentation results will be fused in a temporal constraining and fusion module, to determine the most likely correct boundaries with robustness to morphology. Our proposed methods are extensively evaluated in non-selected IVUS sequences, including normal, bifurcated, and calcified vessels with shadow artifacts. The results show that the proposed methods outperform the state-of-the-art, with a Jaccard measure of 0.92 for lumen and 0.94 for EEM on the IVUS 2011 open challenge dataset. This work has been integrated into a software QCU-CMS2 to automatically segment IVUS images in a user-friendly environment