Direct grafting of tetraaniline via perfluorophenylazide photochemistry to create antifouling, low bio-adhesion surfaces.

Conjugated polyaniline has shown anticorrosive, hydrophilic, antibacterial, pH-responsive, and pseudocapacitive properties making it of interest in many fields. However, in situ grafting of polyaniline without harsh chemical treatments is challenging. In this study, we report a simple, fast, and non-destructive surface modification method for grafting tetraaniline (TANI), the smallest conjugated repeat unit of polyaniline, onto several materials via perfluorophenylazide photochemistry. The new materials are characterized by nuclear magnetic resonance (NMR) and electrospray ionization (ESI) mass spectroscopy. TANI is shown to be covalently bonded to important carbon materials including graphite, carbon nanotubes (CNTs), and reduced graphene oxide (rGO), as confirmed by transmission electron microscopy (TEM). Furthermore, large area modifications on polyethylene terephthalate (PET) films through dip-coating or spray-coating demonstrate the potential applicability in biomedical applications where high transparency, patternability, and low bio-adhesion are needed. Another important application is preventing biofouling in membranes for water purification. Here we report the first oligoaniline grafted water filtration membranes by modifying commercially available polyethersulfone (PES) ultrafiltration (UF) membranes. The modified membranes are hydrophilic as demonstrated by captive bubble experiments and exhibit extraordinarily low bovine serum albumin (BSA) and Escherichia coli adhesions. Superior membrane performance in terms of flux, BSA rejection and flux recovery after biofouling are demonstrated using a cross-flow system and dead-end cells, showing excellent fouling resistance produced by the in situ modification

Pharmacologically blocking p53-dependent apoptosis protects intestinal stem cells and mice from radiation.

Exposure to high levels of ionizing radiation (IR) leads to debilitating and dose-limiting gastrointestinal (GI) toxicity. Using three-dimensional mouse crypt culture, we demonstrated that p53 target PUMA mediates radiation-induced apoptosis via a cell-intrinsic mechanism, and identified the GSK-3 inhibitor CHIR99021 as a potent radioprotector. CHIR99021 treatment improved Lgr5+ cell survival and crypt regeneration after radiation in culture and mice. CHIR99021 treatment specifically blocked apoptosis and PUMA induction and K120 acetylation of p53 mediated by acetyl-transferase Tip60, while it had no effect on p53 stabilization, phosphorylation or p21 induction. CHIR99021 also protected human intestinal cultures from radiation by PUMA but not p21 suppression. These results demonstrate that p53 posttranslational modifications play a key role in the pathological and apoptotic response of the intestinal stem cells to radiation and can be targeted pharmacologically

Unlock the Power: Competitive Distillation for Multi-Modal Large Language Models

Recently, multi-modal content generation has attracted lots of attention from researchers by investigating the utilization of visual instruction tuning based on large language models (LLMs). To enhance the performance and generalization ability of such LLMs, the practice of distilling knowledge from pretrained multi-modal models (a.k.a. teachers) to more compact multi-modal LLMs (students) has gained considerable interest. However, the prevailing paradigm of instructiontuning in multi-modal LLMs knowledge distillation is resource-intensive and unidirectional, neglecting the potential for mutual feedback between the student and teacher models. Thus, we propose an innovative Competitive Multi-modal Distillation framework (CoMD), which captures bidirectional feedback between teacher and student models and continually updates the multi-modal capabilities that the student model has learned. It comprises two stages: multi-modal pre-training and multi-modal competitive distillation. The first stage pre-trains the student model on a large number of filtered multi-modal datasets. The second stage facilitates a bidirectional knowledge transfer between the student and teacher models. Our experimental analysis of diverse datasets shows that our knowledge transfer method consistently improves the capabilities of the student model. Finally, the 7B-sized student model after four distillations surpassed the current state-of-the-art model LLaVA-13B on the ScienceQA and LLaVA Test dataset, also outperforms other strong baselines in the zero-shot setting

Heteroepitaxy of La2O3La_2O_3 and La2−xYxO3La_{2-x}Y_xO_3 on GaAs (111)A by Atomic Layer Deposition: Achieving Low Interface Trap Density

GaAs metal–oxide–semiconductor devices historically suffer from Fermi-level pinning, which is mainly due to the high trap density of states at the oxide/GaAs interface. In this work, we present a new way of passivating the interface trap states by growing an epitaxial layer of high-k dielectric oxide, $La_{2–x}Y_xO_3$, on GaAs(111)A. High-quality epitaxial $La_{2–x}Y_xO_3$ thin films are achieved by an ex situ atomic layer deposition (ALD) process, and GaAs MOS capacitors made from this epitaxial structure show very good interface quality with small frequency dispersion and low interface trap densities $(D_{it})$. In particular, the $La_2O_3$/GaAs interface, which has a lattice mismatch of only 0.04%, shows very low $D_{it}$ in the GaAs bandgap, below $3 × 10^{11} cm^{–2} eV^{–1}$ near the conduction band edge. The $La_2O_3$/GaAs capacitors also show the lowest frequency dispersion of any dielectric on GaAs. This is the first achievement of such low trap densities for oxides on GaAs.Chemistry and Chemical Biolog

Active stiffening of F-actin network dominated by structural transition of actin filaments into bundles

Molecular motor regulated active contractile force is key for cells sensing and responding to their mechanical environment, which leads to characteristic structures and functions of cells. The F-actin network demonstrates a two-order of magnitude increase in its modulus due to contractility; however, the mechanism for this active stiffening remains unclear. Two widely acknowledged hypotheses are that active stiffening of F-actin network is caused by (1) the nonlinear force-extension behavior of cross-linkers, and (2) the loading mode being switched from bending to stretching dominated regime. Direct evidence supporting either theory is lacking. Here we examined these hypotheses and showed that a reorganization of F-actin network from cross-linked filament state to bundled stress fiber state plays a key role on active stiffening of actin network. We demonstrated through computational models that the stretching of cross-linkers and molecular motors has less impact on the active stiffening, while it is more sensitive to cytoskeleton reorganization during the elasticity sensing. The proposed new mechanism involving the cytoskeletal remodeling was able to integrate discrete experimental observations and has the potential to advance our understanding of active sensing and responding of cells

Multimodal Table Understanding

Although great progress has been made by previous table understanding methods including recent approaches based on large language models (LLMs), they rely heavily on the premise that given tables must be converted into a certain text sequence (such as Markdown or HTML) to serve as model input. However, it is difficult to access such high-quality textual table representations in some real-world scenarios, and table images are much more accessible. Therefore, how to directly understand tables using intuitive visual information is a crucial and urgent challenge for developing more practical applications. In this paper, we propose a new problem, multimodal table understanding, where the model needs to generate correct responses to various table-related requests based on the given table image. To facilitate both the model training and evaluation, we construct a large-scale dataset named MMTab, which covers a wide spectrum of table images, instructions and tasks. On this basis, we develop Table-LLaVA, a generalist tabular multimodal large language model (MLLM), which significantly outperforms recent open-source MLLM baselines on 23 benchmarks under held-in and held-out settings. The code and data is available at this https://github.com/SpursGoZmy/Table-LLaVAComment: 23 pages, 16 figures, ACL 2024 main conference, camera-ready versio

The Predictive Value of Coronary Microvascular Dysfunction For Left Ventricular Reverse Remodelling in Dilated Cardiomyopathy

AIMS: to evaluate the degree of coronary microvascular dysfunction (CMD) in dilated cardiomyopathy (DCM) patients by cardiac magnetic resonance (CMR) first-pass perfusion parameters and to examine the correlation between myocardial perfusion and left ventricle reverse remodelling (LVRR). METHODS: In this study, 94 DCM patients and 35 healthy controls matched for age and sex were included. Myocardial perfusion parameters, including upslope, time to maximum signal intensity (Time RESULTS: With a median follow-up period of 12 months [interquartile range (IQR), 8-13], 41 DCM patients (44%) achieved LVRR. Compared with healthy controls, DCM patients presented CMD with reduced upslope, SI CONCLUSIONS: CMD could be found in DCM patients and was more impaired in patients with non-LVRR than LVRR patients. Tim

Post-Quantum Secure Remote Password Protocol from RLWE Problem

Secure Remote Password (SRP) protocol is an augmented Password-based Authenticated Key Exchange (PAKE) protocol based on discrete logarithm problem (DLP) with various attractive security features. Compared with basic PAKE protocols, SRP does not require server to store user\u27s password and user does not send password to server to authenticate. These features are desirable for secure client-server applications. SRP has gained extensive real-world deployment, including Apple iCloud, 1Password etc. However, with the advent of quantum computer and Shor\u27s algorithm, classic DLP-based public key cryptography algorithms are no longer secure, including SRP. Motivated by importance of SRP and threat from quantum attacks, we propose a RLWE-based SRP protocol (RLWE-SRP) which inherit advantages from SRP and elegant design from RLWE key exchange. We also present parameter choice and efficient portable C++ implementation of RLWE-SRP. Implementation of our 209-bit secure RLWE-SRP is more than 3x faster than 112-bit secure original SRP protocol, 5.5x faster than 80-bit secure J-PAKE and 14x faster than two 184-bit secure RLWE-based PAKE protocols with more desired properties