Search

Abstract The Mg–9Gd–3Y–2Zn–0.5Zr alloy was studied for its long-term corrosion behavior in a simulated coastal storage environment. The results show that the Mg12 (Y, Gd) Zn phase in the Mg–9Gd–3Y–2Zn–0.5Zr alloy forms a galvanic couple with α-Mg, and the Mg12 (Y, Gd) Zn phase acts as a cathode to accelerate α-Mg during the corrosion initiation period. The corrosion of the anode is subsequently transformed into corrosive dissolution of the anode. With the dissolution of the Mg12 (Y, Gd) Zn phase, elements such as Gd and Y are gradually distributed into the entire corrosion product layer, improving the protective performance of the corrosion product layer by forming dense Gd2O3 and Y2O3.

Epigenetic pathways play a critical role in the initiation, progression, and metastasis of cancer. Over the past few decades, significant progress has been made in the development of targeted epigenetic modulators (e.g., inhibitors). However, epigenetic inhibitors have faced multiple challenges, including limited clinical efficacy, toxicities, lack of subtype selectivity, and drug resistance. As a result, the design of new epigenetic modulators (e.g., degraders) such as PROTACs, molecular glue, and hydrophobic tagging (HyT) degraders has garnered significant attention from both academia and pharmaceutical industry, and numerous epigenetic degraders have been discovered in the past decade. In this review, we aim to provide an in-depth illustration of new degrading strategies (2017–2023) targeting epigenetic proteins for cancer therapy, focusing on the rational design, pharmacodynamics, pharmacokinetics, clinical status, and crystal structure information of these degraders. Importantly, we also provide deep insights into the potential challenges and corresponding remedies of this approach to drug design and development. Overall, we hope this review will offer a better mechanistic understanding and serve as a useful guide for the development of emerging epigenetic-targeting degraders.

As people’s material quality of life continues to improve, water resources become subjected to varying degrees of contamination. As one of the most commonly utilised agents in water treatment, a flocculant exhibits a diverse range of forms and a vast scope of applications. However, the application of flocculants gives rise to a series of issues, including the use of large doses, the formation of sludge, the difficulty of recycling flocculants, and other concerns. The development of new flocculation technology has become a crucial step in enhancing the purification of wastewater and reducing environmental pollution. Magnetic flocculation can be classified into two main categories: magnetic seeds flocculation and magnetic flocculation. This paper presents an overview of the factors influencing magnetic flocculation, including the type of magnetic seeds, magnetic seeds particle size, and other pertinent considerations. Furthermore, the classification of magnetic flocculants in the process of magnetic flocculation is discussed. This includes the types of magnetic flocculant, namely, inorganic composite magnetic flocculants, organic composite magnetic flocculants, and biological composite magnetic flocculants. Inorganic composite magnetic flocculants are inexpensive and simple to produce; however, their dosage is considerable, and the resulting floc is not tightly formed, which impairs the efficacy of flocculation. The use of organic composite magnetic flocculants requires a smaller dosage and exhibits a strong flocculating ability; however, it may possess toxic properties and potentially cause harm to the water body. The biological composite magnetic flocculant exhibits high efficiency and no pollution, yet it is subject to stringent environmental conditions, displays poor stability, and is applicable to a relatively limited range of treatment scenarios. Furthermore, the integration of magnetic flocculation technology with other techniques is classified and summarised in diverse contexts, and the prospective research focus and direction of magnetic flocculants are proposed.

Abstract Revealing the electrocatalytic microstructure is the basis for finding more efficient and stable electrode materials for clean energy conversion devices. However, there is still a lack of direct understanding of the phase transition process of the sample during heating, which makes the synthesis conditions of the catalyst often rely on experienced guidance. Herein, ZIF‐8@α‐Co(OH)2 core‐shell structure and uniformly coated α‐Co(OH)2 nanosheets on the surface of ZIF‐8 are synthesized. The effect of temperature on microstructure evolution is studied by in situ heating technique with high‐resolution transmission electron microscopy. Based on understanding the relationship between temperature, microstructure, and OER properties, a simple annealing synthesis strategy is designed effectively. During the annealing process, ZnO@CoO heterogeneous structure is formed at 400 °C, and the material reached a stable hydroxyl oxide structure after electrochemical cycle voltammetry in an alkaline solution. The OER performance test shows that the commercial IrO2 catalyst has comparable catalytic performance.

The regional distribution of neurofibrillary tangles of hyperphosphorylated tau aggregates is associated with the progression of Alzheimer’s disease (AD). Misfolded proteopathic tau recruits naïve tau and templates its misfolding and aggregation in a prion-like fashion, which is believed to be the molecular basis of propagation of tau pathology. A practical way to assess tau seeding activity is to measure its ability to recruit/bind other tau molecules and to induce tau aggregation. Based on the properties of proteopathic tau, here we report the development of two simple assays to assess tau seeding activity ----- capture assay in vitro and seeded-tau aggregation assay in cultured cells. In the capture assay, proteopathic tau was applied onto a nitrocellulose membrane and the membrane was incubated with cell lysate containing HA-tagged tau151-391 (HA-tau151-391). The captured tau on the membrane was determined by immuno-blots developed with anti-HA. For the seeded-tau aggregation assay, HEK-293FT cells transiently expressing HA-tau151-391 were treated with proteopathic tau in the presence of Lipofectamine 2000 and then lysed with RIPA buffer. RIPA-insoluble fraction containing aggregated tau was obtained by ultracentrifugation and analyzed by immuno-blot developed with anti-HA. To validate these two assays, we assessed the seeding activity of tau in the middle frontal gyrus, middle temporal gyrus and basal forebrain of AD and control brains and found that AD, but not control, brain extracts effectively captured and seeded tau151-391 aggregation. Basal forebrain contained less phospho-tau and tau seeding activity. The levels of captured tau or seeded-tau aggregates were positively correlated to the levels of phospho-tau, Braak stages and tangle sores. These two assays are specific and sensitive and can be carried out in a regular biomedical laboratory setting by using routine biochemical techniques.

Abstract Freezing fraction and collision coefficient are the key parameters in the ice accretion model, which should be calculated to predict the icing trend for transmission lines. Here a mathematical relation between freezing fraction and collision coefficient was derived using the simplified head balance model of transmission lines icing. Combined with the empirical formula of the liquid water content in air, a calculation method of the freezing fraction and collision coefficient was proposed using the ice surface temperature of transmission lines and the icing mass growth rate. The method to measure the icing mass growth rate based on online monitoring data and icing experiments was proposed. The icing experiments were carried out in the low‐temperature ice chamber with the same parameters as the online monitoring environmental parameters. The values of the freezing fraction and collision coefficient were calculated by using the online monitoring data and icing experiments data respectively, the calculation results were compared. The maximum relative differences between the calculation results from the online monitoring data and the icing experiments data do not exceed 18%, which proves the validity of the calculation method of the freezing fraction and collision coefficient in ice accretion model of transmission lines.

An approach to optimize the sensitivity and the limit of detection of on-chip refractive index sensor is proposed and demonstrated based on sub-wavelength grating racetrack microring resonator and Vernier effect. The sub-wavelength grating waveguide can reduce the structure limitation of the light field, which is beneficial to enhancing the interaction between the photon and analyte. By optimizing the parameters of the sub-wavelength grating racetrack microring resonator, the sensitivity of the sensor could be significantly improved to 664 nm/RIU. Subsequently, capitalizing the Vernier effect, a two cascaded microring-based refractive index sensor is designed. Owing to the Vernier effect, the wavelength spacings among the overlapped peaks could be effectively amplified more than ten times, leading to a high performance. The results demonstrate that an ultra-high sensitivity of 7061 nm/RIU and a low limit of detection of 1.74 × 10−5 RIU. With the advantages of ultra-high sensitivity and low limit of detection, the integrated device has important value in the fields of environmental monitoring and biosensors.

The impact of Pulsed Electric Field (PEF) processing pre-treatment on the texture and kinetics of in vitro starch digestibility of French fries made from two potato cultivars (Solanum tuberosum L.) containing dry matter content ranging from 19 to 22% was investigated. Whole and steam-peeled potato tubers were treated with a pilot scale PEF unit (electric field strength of 1.1 and 1.9 kV/cm with energy input 21%) tubers pretreated with PEF at electric field strength of 1.9 kV/cm. The findings generated in this study demonstrate PEF pretreatment may influence the texture of French fries and the extent of starch digestion that occurs.

To date, the underlying mechanisms involved intervertebral disc degeneration (IDD) remain unclear, which has hindered the development of molecular biological therapy for IDD. Autophagy is vital for intracellular quality control and metabolic balance in intervertebral disc cells. Hence, autophagy homeostasis is important. Emerging evidence has implicated vitamin D (VD) and the vitamin D receptor (VDR) in IDD progression because of their effects on different autophagy steps. However, the results of clinical trials in which VD supplementation was assessed as a treatment for IDD are controversial. Furthermore, experimental studies on the interplay between VD/VDR and autophagy are still in their infancy. In view of the significance of the crosstalk between VD/VDR and autophagy components, this review focuses on the latest research on VD/VDR modulation in autophagy and investigates the possible regulatory mechanisms. This article will deepen our understanding of the relationship between VD/VDR and autophagy and suggests novel strategies for IDD prevention and treatment.

Introduction: LncRNA (Long non-coding RNA) ZFAS1 (zinc finger antisense 1) functions as the oncogene in multiple cancers, including gastric cancer. However, its function and underlying mechanism in the GCA (gastric cardia adenocarcinoma), the most aggressive type of gastric cancer, remain unknown. Objective: In the current study, the expression level of LncRNA ZFAS1 was quantified in 762 GCA tissues and the paired adjacent non-tumor tissues. The expression level of LncRNA ZFAS1 was quantified in 762 GCA tissues and the paired adjacent non-tumor tissues, and further confirmed using in vitro cell and animal model based assays. Conclusion: We demonstrated here that the LncRNA ZFAS1 was up-regulated in GCA tissues. Furthermore, the elevated level of ZFAS1 was significantly associated with the GCA metastasis and cancer recurrence. It was also demonstrated to be an independent prognostic indicator of disease-free survival and overall survival for GCA patients. RNA sequencing showed that the up-regulated ZFAS1 was tightly associated with the down-regulated hypoxia inducible factor 1 (HIF1) and up-regulated EPAS1 (Endothelial PAS domain protein 1, also known as HIF2). In vitro studies showed that the ZFAS1 could bind to EPAS1, enhance its abilities to epigenetically silence the HIF1, and promote its own expression in GCA cell lines. In the animal model, codelivering the EPAS1 and the ZFAS1 antisense oligos could significantly boost up their therapeutic effects on tumor growth. Thus, targeting ZFAS1 and EPAS1 might be an alternative therapeutic option in GCA.

Stateful network protocol fuzzing is one of the essential means for ensuring network communication security. However, the existing methods have problems, including frequent auxiliary message interaction, no in-depth state-space exploration, and high shares of invalid interaction time. To this end, we propose SATFuzz, a stateful network protocol fuzzing framework. SATFuzz first prioritizes the states identified by the status codes in response messages, then randomly selects a state to test among the high-priority states, and determines its corresponding optimal test sequence, which is composed of the minimum pre-lead sequence, the test case, and the fittest post-end sequence. Finally, SATFuzz uses a quasi-recurrent neural network (QRNN) to filter the test cases before performing interaction, and only the optimal test sequence, including the valid test case, can be fed to the protocol entity. To verify the proposed framework, we conduct extensive experiments with the state-of-the-art fuzzer on two popular protocols. The results show that the vulnerability discovery efficiency of the proposed approach increases by at least 1.48 times (at most by 3.06 times), making it superior to the rival methods. This not only confirms the effectiveness of SATFuzz in terms of improving the vulnerability discovery efficiency but also shows that SATFuzz has significant advantages.

There is large interest in networked social science experiments for understanding human behavior at-scale. Significant effort is required to perform data analytics on experimental outputs and for computational modeling of custom experiments. Moreover, experiments and modeling are often performed in a cycle, enabling iterative experimental refinement and data modeling to uncover interesting insights and to generate/refute hypotheses about social behaviors. The current practice for social analysts is to develop tailor-made computer programs and analytical scripts for experiments and modeling. This often leads to inefficiencies and duplication of effort. In this work, we propose a pipeline framework to take a significant step towards overcoming these challenges. Our contribution is to describe the design and implementation of a software system to automate many of the steps involved in analyzing social science experimental data, building models to capture the behavior of human subjects, and providing data to test hypotheses. The proposed pipeline framework consists of formal models, formal algorithms, and theoretical models as the basis for the design and implementation. We propose a formal data model, such that if an experiment can be described in terms of this model, then our pipeline software can be used to analyze data efficiently. The merits of the proposed pipeline framework is elaborated by several case studies of networked social science experiments.

Based on various carbon nano materials, the ternary composite functionalized carbon nanotubes (FMWCNTs) @ carbon quantum dots (CQDs) @ polyaniline (PANI) was prepared by in-situ polymerization and hydrothermal method. The carbon-based material was made into an electrode sheet. The morphology and microscopic nanostructures were characterized by FTIR, field emission scanning electron microscopy and field emission transmission electron microscopy. Cyclic voltammetry and the galvanostatic charge discharge method was adapted to study the electrochemical properties of these active materials. Our results showed that the specific capacitance of FMWCNTs @ CQDs @ PANI was as high as 534 F/g, while it was 362 F/g, 319 F/g and 279 F/g for PANI @ FMWCNTs, PANI @ CQDs and polyaniline. This means that the specific capacitance of FMWCNTs @ CQDs @ PANI is increased by 47.5%, 67.4% and 91.4% comparing with the capacitance of PANI @ FMWCNTs, PANI @ CQDs and polyaniline, respectively. Moreover, the specific capacitance retention rate of the ternary active electrode after 1000 times of constant current charge and discharge cycle reached 86%, while it was 60% for PANI @ FMWCNTs, 72% for PANI @ CQDs and 65% for polyaniline.

This paper studies the influence of salience on nominal and real yield curves by introducing the salience effect in the Piazzesi and Schneider model (hereafter PS). We construct the salience values based on the expected consumption growth using U.S. data. We find that salience values are negatively correlated with the expected consumption growth rates. Based on U.S. data from 1960q1 to 2020q4, we find that the salience model can generate upward nominal and real yield curves within reasonable risk aversion coefficients (less than 10), as well as well-fitted average yields with actual data. The salience model compensates for the PS or recursive preference model’s inability to generate an upward nominal or real yield curve within reasonable risk aversion. Furthermore, we provide empirical support for model implications. [ABSTRACT FROM AUTHOR]