3,4-Bis(4-meth­oxy­phen­yl)-2,5-dihydro-1H-pyrrole-2,5-dione

In the title compound, C18H15NO4, the benzene rings form quite different dihedral angles [16.07 (1) and 59.50 (1)°] with the central pyrrole ring, indicating a twisted mol­ecule. Conjugation is indicated between the five- and six-membered rings by the lengths of the C—C bonds which link them [1.462 (3) and 1.477 (3) Å]. The most prominent feature of the crystal packing is the formation of inversion dimers via eight-membered {⋯HNCO}2 synthons

NOTABLE: Transferable Backdoor Attacks Against Prompt-based NLP Models

Prompt-based learning is vulnerable to backdoor attacks. Existing backdoor attacks against prompt-based models consider injecting backdoors into the entire embedding layers or word embedding vectors. Such attacks can be easily affected by retraining on downstream tasks and with different prompting strategies, limiting the transferability of backdoor attacks. In this work, we propose transferable backdoor attacks against prompt-based models, called NOTABLE, which is independent of downstream tasks and prompting strategies. Specifically, NOTABLE injects backdoors into the encoders of PLMs by utilizing an adaptive verbalizer to bind triggers to specific words (i.e., anchors). It activates the backdoor by pasting input with triggers to reach adversary-desired anchors, achieving independence from downstream tasks and prompting strategies. We conduct experiments on six NLP tasks, three popular models, and three prompting strategies. Empirical results show that NOTABLE achieves superior attack performance (i.e., attack success rate over 90% on all the datasets), and outperforms two state-of-the-art baselines. Evaluations on three defenses show the robustness of NOTABLE. Our code can be found at https://github.com/RU-System-Software-and-Security/Notable

Bridging the gap: optimized fabrication of robust titania nanostructures on complex implant geometries towards clinical translation

Electrochemically anodized titanium surfaces with titania nanostructures (TNS; nanopores, nanotubes, etc.) have been widely applied as therapeutic bone/dental implant modifications. Despite the numerous advancements in the field of electrochemical anodization (EA), in terms of translation into the current implant market, research gaps in this domain include the lack of fabrication optimization, performed on a substrate of conventional implant surface/geometry, and inadequate mechanical stability. In the current study, we investigate the role of substrate pre-treatment on achieving desired nanotopographies for the purpose of reproducing optimized nanostructures on the complex geometry of commercial implant surfaces, as well as in-depth mechanical stability testing of these nano-engineered coatings. The results confirmed that: (a) substrate polishing/smoothening may be insignificant with respect to fabrication of well-ordered and high quality TNS on micro-rough implants with preserved underlying micro roughness; (b) optimized outcomes can be successfully translated onto complex geometries characteristic of the current implant market, including dental implant abutments and screws (also applicable to a wider implant market including orthopaedics); (c) mechanical stability testing revealed improved modulus and hardness values as compared to conventional nanotubes/pores. We believe that such optimization advances the existing knowledge of titanium anodization and anodized implants towards integration into the current implant market and successful clinical translation. (C) 2018 Elsevier Inc. All rights reserved

Understanding and augmenting the stability of therapeutic nanotubes on anodized titanium implants

Titanium is an ideal material choice for orthopaedic and dental implants, and hence a significant amount of research has been focused towards augmenting the therapeutic efficacy of titanium surfaces. More recently the focus has shifted to nano-engineered implants fabricated via anodization to generate self-ordered nanotubular structures composed of titania (TiO2). These structures (titania nanotubes/TNTs) enable local drug delivery and tailorable cellular modulation towards achieving desirable effects like enhanced osseointegration and antibacterial action. However, the mechanical stability of such modifications is often ignored and remains under explored, and any delamination or breakage in the TNTs modification can initiate toxicity and lead to severe immuno-inflammatory reactions. This review details and critically evaluates the progress made in relation to this aspect of TNT based implants, with a focus on understanding the interface between TNTs and the implant surface, treatments aimed at augmenting mechanical stability and strategies for advanced mechanical testing within the bone micro-environment ex vivo and in vivo. This review article extends the existing knowledge in this domain of TNTs implant technology and will enable improved understanding of the underlying parameters that contribute towards mechanically robust nano-engineered implants that can withstand the forces associated with implant surgical placement and the load bearing experienced at the bone/implant interface

PDTD: a web-accessible protein database for drug target identification

<p>Abstract</p> <p>Background</p> <p>Target identification is important for modern drug discovery. With the advances in the development of molecular docking, potential binding proteins may be discovered by docking a small molecule to a repository of proteins with three-dimensional (3D) structures. To complete this task, a reverse docking program and a drug target database with 3D structures are necessary. To this end, we have developed a web server tool, TarFisDock (<it>Tar</it>get <it>Fis</it>hing <it>Dock</it>ing) <url>http://www.dddc.ac.cn/tarfisdock</url>, which has been used widely by others. Recently, we have constructed a protein target database, <it>P</it>otential <it>D</it>rug <it>T</it>arget <it>D</it>atabase (PDTD), and have integrated PDTD with TarFisDock. This combination aims to assist target identification and validation.</p> <p>Description</p> <p>PDTD is a web-accessible protein database for <it>in silico </it>target identification. It currently contains >1100 protein entries with 3D structures presented in the Protein Data Bank. The data are extracted from the literatures and several online databases such as TTD, DrugBank and Thomson Pharma. The database covers diverse information of >830 known or potential drug targets, including protein and active sites structures in both PDB and mol2 formats, related diseases, biological functions as well as associated regulating (signaling) pathways. Each target is categorized by both nosology and biochemical function. PDTD supports keyword search function, such as PDB ID, target name, and disease name. Data set generated by PDTD can be viewed with the plug-in of molecular visualization tools and also can be downloaded freely. Remarkably, PDTD is specially designed for target identification. In conjunction with TarFisDock, PDTD can be used to identify binding proteins for small molecules. The results can be downloaded in the form of mol2 file with the binding pose of the probe compound and a list of potential binding targets according to their ranking scores.</p> <p>Conclusion</p> <p>PDTD serves as a comprehensive and unique repository of drug targets. Integrated with TarFisDock, PDTD is a useful resource to identify binding proteins for active compounds or existing drugs. Its potential applications include <it>in silico </it>drug target identification, virtual screening, and the discovery of the secondary effects of an old drug (i.e. new pharmacological usage) or an existing target (i.e. new pharmacological or toxic relevance), thus it may be a valuable platform for the pharmaceutical researchers. PDTD is available online at <url>http://www.dddc.ac.cn/pdtd/</url>.</p

NH3 sensor based on 3D hierarchical flower-shaped n-ZnO/p-NiO heterostructures yields outstanding sensing capabilities at ppb level

Hierarchical three-dimensional (3D) flower-like n-ZnO/p-NiO heterostructures with various ZnxNiy molar ratios (Zn5Ni1, Zn2Ni1, Zn1Ni1, Zn1Ni2 and Zn1Ni5) were synthesized by a facile hydrothermal method. Their crystal phase, surface morphology, elemental composition and chemical state were comprehensively investigated by XRD, SEM, EDS, TEM and XPS techniques. Gas sensing measurements were conducted on all the as-developed ZnxNiy-based sensors toward ammonia (NH3) detection under various working temperatures from 160 to 340 °C. In particular, the as-prepared Zn1Ni2 sensor exhibited superior NH3 sensing performance under optimum working temperature (280 °C) including high response (25 toward 100 ppm), fast response/recovery time (16 s/7 s), low detection limit (50 ppb), good selectivity and long-term stability. The enhanced NH3 sensing capabilities of Zn1Ni2 sensor could be attributed to both the specific hierarchical structure which facilitates the adsorption of NH3 molecules and produces much more contact sites, and the improved gas response characteristics of p-n heterojunctions. The obtained results clear demonstrated that the optimum n-ZnO/p-NiO heterostructure is indeed very promising sensing material toward NH3 detection for different applications

TarFisDock: a web server for identifying drug targets with docking approach

TarFisDock is a web-based tool for automating the procedure of searching for small molecule–protein interactions over a large repertoire of protein structures. It offers PDTD (potential drug target database), a target database containing 698 protein structures covering 15 therapeutic areas and a reverse ligand–protein docking program. In contrast to conventional ligand–protein docking, reverse ligand–protein docking aims to seek potential protein targets by screening an appropriate protein database. The input file of this web server is the small molecule to be tested, in standard mol2 format; TarFisDock then searches for possible binding proteins for the given small molecule by use of a docking approach. The ligand–protein interaction energy terms of the program DOCK are adopted for ranking the proteins. To test the reliability of the TarFisDock server, we searched the PDTD for putative binding proteins for vitamin E and 4H-tamoxifen. The top 2 and 10% candidates of vitamin E binding proteins identified by TarFisDock respectively cover 30 and 50% of reported targets verified or implicated by experiments; and 30 and 50% of experimentally confirmed targets for 4H-tamoxifen appear amongst the top 2 and 5% of the TarFisDock predicted candidates, respectively. Therefore, TarFisDock may be a useful tool for target identification, mechanism study of old drugs and probes discovered from natural products. TarFisDock and PDTD are available at

Therapy by physician–pharmacist combination and economic returns for cancer pain management in China: a cost-effectiveness analysis

Objective: To examine whether joint management of cancer pain by physicians and pharmacists in clinics provides economic advantages from the perspective of the Chinese healthcare system.Methods: From February 2018 to March 2020, 100 patients who visited the joint cancer pain clinic at the Xiangya Hospital of Central South University were included. These patients were randomly assigned to either the control or intervention groups. The control group received regular outpatient services from a physician, while the intervention group received regular outpatient services from a physician and medication education provided by a pharmacist. The study considered various direct costs, including drug expenses, physician-pharmacist outpatient services, adverse event management, consultations, examinations, and readmissions. The outcome indicators considered were the cancer pain control rate and the reduction in pain scores. Decision tree modeling, single-factor sensitivity analysis, and probabilistic sensitivity analysis were performed to evaluate the cost-effectiveness of joint physician-pharmacist outpatient services compared to physician-alone outpatient services.Results: The intervention group showed a significantly higher cancer pain control rate than the control group (0.69 vs. 0.39, p = 0.03). In the decision tree model, the intervention group had a significantly lower pain score than the control group (0.23 vs. 0.14). The cost per person in the intervention group was $165.39, while it was$191.1 per person in the control group. The univariate sensitivity analysis showed that the cost of self-management for patients in the control group was identified as the primary sensitivity factor. Probabilistic sensitivity analysis indicated that the joint clinic group had a favorable incremental cost-effectiveness compared to the physician clinic group. In addition, the probabilistic sensitivity analysis demonstrated an absolute advantage in the incremental cost-effectiveness of the joint clinic group over the outpatient physician group.Conclusion: The participation of pharmacists in joint cancer pain clinic services led to improved pain management for patients, demonstrating a clear advantage in terms of cost-effectiveness

Phototunable biomemory based on light-mediated charge trap

Phototunable biomaterial‐based resistive memory devices and understanding of their underlying switching mechanisms may pave a way toward new paradigm of smart and green electronics. Here, resistive switching behavior of photonic biomemory based on a novel structure of metal anode/carbon dots (CDs)‐silk protein/indium tin oxide is systematically investigated, with Al, Au, and Ag anodes as case studies. The charge trapping/detrapping and metal filaments formation/rupture are observed by in situ Kelvin probe force microscopy investigations and scanning electron microscopy and energy‐dispersive spectroscopy microanalysis, which demonstrates that the resistive switching behavior of Al, Au anode‐based device are related to the space‐charge‐limited‐conduction, while electrochemical metallization is the main mechanism for resistive transitions of Ag anode‐based devices. Incorporation of CDs with light‐adjustable charge trapping capacity is found to be responsible for phototunable resistive switching properties of CDs‐based resistive random access memory by performing the ultraviolet light illumination studies on as‐fabricated devices. The synergistic effect of photovoltaics and photogating can effectively enhance the internal electrical field to reduce the switching voltage. This demonstration provides a practical route for next‐generation biocompatible electronics