Enhanced drug delivery can improve the therapeutic efficacy of drugs and help overcome side effects. However, many reported drug‐delivery systems are too complex and irreproducible for practical use. ...In this work, the design of a hypoxia‐responsive molecular container based on calixarene, called CAC4A, which presents a significant advance in practical, hypoxia‐targeted drug‐delivery, is reported. CAC4A enables a wide variety of clinical drugs to be quantitatively loaded to improve their solubility and stability, as well as enable the administration of reduced doses. Furthermore, as a result of its azo functional groups, which are sensitive to reduction within a hypoxic environment, it is possible to achieve tumor‐targeted drug‐release with reduced side effects. CAC4A fulfils all essential requirements for a drug‐delivery system in addition to multiple advantages, including facile preparation, well‐defined molecular weight, and structure, and universal applicability. Such features collectively enable supramolecular prodrugs to be formulated simply and reproducibly, with potential for bench‐to‐bedside translation. Moreover, CAC4A is amenable to other therapy modalities and can be facilely decorated with functional groups and hybridized with nanomaterials, providing ample possibilities for its role in future drug‐delivery systems.
Carboxylated azocalix4arene is designed as a hypoxia‐responsive molecular container, which affords strong binding toward a series of chemotherapeutic drugs, and improves the drugs’ solubility and stability, demonstrating its universality as a supramolecular drug carrier. Taking one supramolecular prodrug as an example, the efficacy of this hypoxia‐targeted therapy is validated in vitro and in vivo.
Psycholinguistics has provided numerous theories that explain how a person acquires a language, produces and perceives both spoken and written language, including theories of proceduralization. ...Learners of English as a foreign language (hereafter referred to as EFL learners) often find it difficult to achieve oral fluency, a key construct closely related to the mental state or even mental health of learners. According to previous research, this problem could be addressed by the mastery of formulaic sequences, since the employment of formulaic sequences could often promote oral fluency in the long run, reflected in the positive relationship between formulaic sequence use and oral fluency. However, there are also findings contradicting the abovementioned ones, without adequate explanations. This study aims to explore the roles of formulaic sequences in oral fluency, taking into account the relationship between formulaic sequence use and oral fluency. This study investigated 120 pieces of spoken narratives by Chinese EFL learners, using both quantitative and qualitative methods, combined with artificial intelligence techniques. Results of canonical correlation analysis showed that the frequency of formulaic sequences was significantly related to speed fluency (
r
= 0.563,
p
= 0.000) and breakdown fluency (
r
= 0.360,
p
= 0.001), while the variety of formulaic sequences was significantly related to repair fluency (
r
= 0.292,
p
= 0.035). Case studies further demonstrated that formulaic sequences could contribute to oral fluency development by promoting speed and reducing pausing when retrieved holistically, but they sometimes lost processing advantages when retrieved and processed in a word-by-word manner. The inappropriate use of formulaic sequences also neutralized the facilitative effects of formulaic sequences on repair fluency and could mirror speakers’ occasional tendency to sacrifice repair fluency for the improvement of speed and breakdown fluency when using formulaic sequences. Pedagogical implications were provided accordingly to promote sustainable oral fluency development through the use of formulaic sequences.
Sampling complex free-energy surfaces is one of the main challenges of modern atomistic simulation methods. The presence of kinetic bottlenecks in such surfaces often renders a direct approach ...useless. A popular strategy is to identify a small number of key collective variables and to introduce a bias potential that is able to favor their fluctuations in order to accelerate sampling. Here, we propose to use machine-learning techniques in conjunction with the recent variationally enhanced sampling method O. Valsson, M. Parrinello, Phys. Rev. Lett. 113, 090601 (2014) in order to determine such potential. This is achieved by expressing the bias as a neural network. The parameters are determined in a variational learning scheme aimed at minimizing an appropriate functional. This required the development of a more efficient minimization technique. The expressivity of neural networks allows representing rapidly varying free-energy surfaces, removes boundary effects artifacts, and allows several collective variables to be handled.
Display omitted
•The impact spatial agglomeration economy on regional pollution control is studied.•There is a significant positive correlation of the pollution control among regions.•The spatial ...agglomeration of patent has a negative impact on pollution control.•The spatial agglomeration of employee has a positive impact on pollution control.•Some suggestions are put forward to improve the performance of pollution control.
With the increasing prominence of China’s energy security and environmental pollution issues, improving environmental control performance is significant for China to achieve a sustainable economy and environment. In this study, the impact of the spatial agglomeration of the new energy industry on the regional pollution control performance was considered in a spatial econometric model. From the two perspectives of technology patents and employees, the impact of the spatial agglomeration of the new energy industry was explored using the spatial panel data model. The research results show the existence of spatial correlation of the pollution control performance among regions. Moreover, the spatial agglomeration of relevant technology patents can have a negative effect and the spatial agglomeration of employees a positive effect on the improvement in regional pollution control performance. Then, policy recommendations to improve the regional pollution control performance are proposed based on the research results: establishing a regional environmental joint governance system, improving the diffusion mode of new energy technology patents, and quickly constructing a new energy industrial park.
Cortical surface functional magnetic resonance imaging (cs-fMRI) has recently grown in popularity versus traditional volumetric fMRI. In addition to offering better whole-brain visualization, ...dimension reduction, removal of extraneous tissue types, and improved alignment of cortical areas across subjects, it is also more compatible with common assumptions of Bayesian spatial models. However, as no spatial Bayesian model has been proposed for cs-fMRI data, most analyses continue to employ the classical general linear model (GLM), a "massive univariate" approach. Here, we propose a spatial Bayesian GLM for cs-fMRI, which employs a class of sophisticated spatial processes to model latent activation fields. We make several advances compared with existing spatial Bayesian models for volumetric fMRI. First, we use integrated nested Laplacian approximations, a highly accurate and efficient Bayesian computation technique, rather than variational Bayes. To identify regions of activation, we utilize an excursions set method based on the joint posterior distribution of the latent fields, rather than the marginal distribution at each location. Finally, we propose the first multi-subject spatial Bayesian modeling approach, which addresses a major gap in the existing literature. The methods are very computationally advantageous and are validated through simulation studies and two task fMRI studies from the Human Connectome Project.
Supplementary materials
for this article, including a standardized description of the materials available for reproducing the work, are available as an online supplement.
Polydimethylsiloxanes (PDMS) foam as one of next‐generation polymer foam materials shows poor surface adhesion and limited functionality, which greatly restricts its potential applications. ...Fabrication of advanced PDMS foam materials with multiple functionalities remains a critical challenge. In this study, unprecedented self‐adhesive PDMS foam materials are reported with worm‐like rough structure and reactive groups for fabricating multifunctional PDMS foam nanocomposites decorated with MXene/cellulose nanofiber (MXene/CNF) interconnected network by a facile silicone foaming and dip‐coating strategy followed by silane surface modification. Interestingly, such self‐adhesive PDMS foam produces strong interfacial adhesion with the hybrid MXene/CNF nano‐coatings. Consequently, the optimized PDMS foam nanocomposites have excellent surface super‐hydrophobicity (water contact angle of ≈159o), tunable electrical conductivity (from 10−8 to 10 S m−1), stable compressive cyclic reliability in both wide‐temperature range (from −20 to 200 oC) and complex environments (acid, sodium, and alkali conditions), outstanding flame resistance (LOI value of >27% and low smoke production rate), good thermal insulating performance and reliable strain sensing in various stress modes and complex environmental conditions. It provides a new route for the rational design and development of advanced PDMS foam nanocomposites with versatile multifunctionalities for various promising applications such as intelligent healthcare monitoring and fire‐safe thermal insulation.
Polydimethylsiloxanes (PDMS) foam usually exhibits poor surface adhesion and limited functionality, restricting the potential applications. Here, self‐adhesive PDMS foams with worm‐like rough structure and reactive groups are fabricated by a facile silicone foaming approach. Decorating with MXene/cellulose nanofiber interconnected network and using silane modification, exceptional multifunctionalities PDMS nanocomposites are prepared, showing versatile applications in thermal insulating and smart sensing fields.
Poisoning is a leading cause of admission to medical emergency departments and intensive care units. Supramolecular detoxification, which involves injecting supramolecular receptors that bind with ...toxins to suppress their biological activity, is an emerging strategy for poisoning treatment; it has few requirements and a broad application scope. However, it is still a formidable challenge to design supramolecular therapeutic materials as an antidote to macromolecular toxins, because the large size, flexible conformation, and presence of multiple and diverse binding sites of biomacromolecules hinder their recognition. Herein, a supramolecular antidote to macromolecular toxins is developed through the coassembly of macrocyclic amphiphiles, relying on heteromultivalent recognition between the coassembled components and toxic macromolecules. The coassembly of amphiphilic cyclodextrin and calixarene strongly and selectively captures melittin, a toxin studied herein; this imparts various therapeutic effects such as inhibiting the interactions of melittin with cell membranes, alleviating melittin cytotoxicity and hemolytic toxicity, reducing the mortality rate of melittin‐poisoned mice, and mitigating damage to major organs. The use of the proposed antidote overcomes the limitation of supramolecular detoxification applicability to only small‐molecular toxins. The antidote can also detoxify other macromolecular toxins as long as selective and strong binding is achieved because of the coassembling tunability.
Supramolecular detoxification is an emerging strategy for treating poisoning; however, developing supramolecular therapeutic materials as an antidote to macromolecular toxins is challenging. To overcome this challenge, a heteromultivalent coassembling material (CCA‐CD) comprising macrocyclic amphiphiles is developed. The CCA‐CD binds with melittin strongly and selectively, and significantly alleviates its toxicity, serving as a novel supramolecular antidote used for melittin poisoning treatment.
Large-scale galactic shocks, predicted by density wave theory, trigger star formation (SF-arms) downstream from the potential of the oldest stars (P-arms), resulting in a color jump from red to blue ...across spiral arms in the direction of rotation, while aging of these newly formed young stars induces the opposite but coexisting classic age gradient further downstream from the SF-arms. As the techniques for measuring pitch angle are intensity-weighted, they trace both the SF-arms and P-arms and are not sensitive to the classic age gradient. Consequently, the measured pitch angle of spiral arms should be systematically smaller in bluer bandpasses compared to redder bandpasses. We test these predictions using a comprehensive sample of high-quality optical (BVRI) images of bright, nearby spiral galaxies acquired as part of the Carnegie-Irvine Galaxy Survey, supplemented by Spitzer 3.6 m data to probe evolved stars and Galaxy Evolution Explorer ultraviolet images to trace recent star formation. We apply one-dimensional and two-dimensional techniques to measure the pitch angle of spiral arms, paying close attention to adopt consistent procedures across the different bandpasses to minimize error and systematic bias. We find that the pitch angle of spiral arms decreases mildly but statistically significantly from the reddest to the bluest bandpass, demonstrating conclusively that young stars trace tighter spiral arms than old stars. Furthermore, the correlation between the pitch angle of blue and red bandpasses is nonlinear, such that the absolute value of pitch angle offset increases with increasing pitch angle. Both effects can be naturally explained in the context of the density wave theory for spiral structure.
Lead zirconate titanate (PZT)‐based piezoelectric ceramics are important functional materials for various electromechanical applications, including sensors, actuators, and transducers. High ...piezoelectric coefficient and mechanical quality factor are essential for the resonant piezoelectric application. However, since these properties are often inversely proportional, simultaneously high performances are hard to achieve, consequently, a wide range of applications are strongly restricted. In the present study, exceptionally well‐balanced performances are achieved in PZT‐based ceramics via innovative defect engineering, which involves multi‐scale coordination among defect dipole, domain‐wall density, and grain boundary. These materials are superior to many state‐of‐the‐art commercial counterparts, which can potentially satisfy high‐end requirements for advanced electromechanical applications, such as energy harvesting, structural health monitoring, robotic sensors, and actuator.
Exceptionally well‐balanced piezoelectric performances are achieved in (Pb0.92Sr0.08)(Zr0.533Ti0.443Nb0.024)O3‐xwt%Mn (abbreviated as PSZTN‐Mn) ferroelectric ceramics (d33 = 510–460 pC N−1, Qm = 614–750), which is superior to many state‐of‐the‐art commercial piezoelectric ceramics. The high performance is proposed to originate from multi‐sale coordination among defect dipoles, domain wall, and grain boundary.
Emerging evidence indicates that inflammasome-induced inflammation plays a crucial role in the pathogenesis of Parkinson's disease (PD). Several proteins including α-synuclein trigger the activation ...of NLRP3 inflammasome. However, few studies examined whether inflammasomes are activated in the periphery of PD patients and their possible value in the diagnosis or tracking of the progress of PD. The aim of this study was to determine the association between inflammasome-induced inflammation and clinical features in PD.
There were a total of 67 participants, including 43 patients with PD and 24 controls, in the study. Participants received a complete evaluation of motor and non-motor symptoms, including Hoehn and Yahr (H-Y) staging scale. Blood samples were collected from all participants. The protein and mRNA expression levels of inflammasomes subtypes and components in peripheral blood mononuclear cells (PBMCs) were determined using western blotting and RT-qPCR. We applied Meso Scale Discovery (MSD) immunoassay to measure the plasma levels of IL-1β and α-synuclein.
We observed increased gene expression of NLRP3, ASC, and caspase-1 in PBMCs, and increased protein levels of NLRP3, caspase-1, and IL-1β in PD patients. Plasma levels of IL-1β were significantly higher in patients with PD compared with controls and have a positive correlation with H-Y stage and UPDRS part III scores. Furthermore, plasma α-synuclein levels were also increased in PD patients and have a positive correlation with both UPDRS part III scores and plasma IL-1β levels.
Our data demonstrated that the NLRP3 inflammasome is activated in the PBMCs from PD patients. The related inflammatory cytokine IL-1β and total α-synuclein in plasma were increased in PD patients than controls, and both of them presented a positive correlation with motor severity in patients with PD. Furthermore, plasma α-synuclein levels have a positive correlation with IL-1β levels in PD patients. All these findings suggested that the NLRP3 inflammasome activation-related cytokine IL-1β and α-synuclein could serve as non-invasive biomarkers to monitor the severity and progression of PD in regard to motor function.
PDF
