A simple method to prepare anion exchange membrane by PVA/EVOH/MIDA for acid recovery by diffusion dialysis.

Given the substantial environmental pollution from industrial expansion, environmental protection has become particularly important. Nowadays, anion exchange membranes (AEMs) are widely used in wastewater treatment. With the use of polyvinyl alcohol (PVA), ethylene-vinyl alcohol (EVOH) copolymer, and methyl iminodiacetic acid (MIDA), a series of cross-linked AEMs were successfully prepared using the solvent casting technique, and the network structure was formed in the membranes due to the cross-linking reaction between PVA/EVOH and MIDA. Fourier transform infrared spectrometer, X-ray photoelectron spectroscopy, scanning electron microscopy, and transmission electron microscopy were used to analyze the prepared membranes. At the same time, its comprehensive properties which include water uptake, linear expansion rate, ion exchange capacity, thermal stability, chemical stability, and mechanical stability were thoroughly researched. In addition, diffusion dialysis performance in practical applications was also studied in detail. The acid dialysis coefficient (UH+) ranged from 10.2 to 35.6 × 10-3 m/h. Separation factor (S) value ranged from 25 to 38, which were all larger than that of the commercial membrane DF-120 (UH+: 8.5 × 10-3 m/h, S: 18.5). The prepared membranes had potential application value in acid recovery.

Anion Exchange Membrane Based on BPPO/PECH with Net Structure for Acid Recovery via Diffusion Dialysis.

In order to improve the performance of the anion exchange membrane (AEM) used in acid recovery from industrial wastewater, this study adopted a new strategy in which brominated poly (2,6-dimethyl-1,4-phenyleneoxide) (BPPO) and polyepichlorohydrin (PECH) were used as the polymer backbone of the prepared membrane. The new anion exchange membrane with a net structure was formed by quaternizing BPPO/PECH with N,N,N,N-tetramethyl-1,6-hexanediamine (TMHD). The application performance and physicochemical property of the membrane were adjusted by changing the content of PECH. The experimental study found that the prepared anion exchange membrane had good mechanical performance, thermostability, acid resistance and an appropriate water absorption and expansion ratio. The acid dialysis coefficient (UH+) of anion exchange membranes with different contents of PECH and BPPO was 0.0173-0.0262 m/h at 25 °C. The separation factors (S) of the anion exchange membranes were 24.6 to 27.0 at 25 °C. Compared with the commercial BPPO membrane (DF-120B), the prepared membrane had higher values of UH+ and S in this paper. In conclusion, this work indicated that the prepared BPPO/PECH anion exchange membrane had the potential for acid recovery using the DD method.

How do Chinese-English Bilinguals and Tibetan-Chinese-English Trilinguals Differ in Explicit and Implicit Aptitude?

This study seeks to empirically explore the relation between multilingual learning experiences and language aptitude. Through employing LLAMA aptitude test battery (Meara, 2005) and a probabilistic version of the serial reaction time (SRT) task (Kaufman et al., 2010), scores from 24 Chinese-English bilinguals and 24 Tibetan-Chinese-English trilinguals were analyzed with One-way Analyses of Variance (ANOVA). LLAMA-B, E, and F sub-tests measured explicit language aptitude, while LLAMA-D sub-test and SRT task measured implicit language aptitude, a cutting-edge that has gained sway in aptitude research. Qualitative and quantitative results showed that trilingual group performed better on the LLAMA-E sub-test than bilingual group, whereas bilingual group outperformed trilingual group on the SRT task. These findings suggested that trilinguals might possess higher explicit aptitude but lower implicit aptitude than bilinguals. Thus, prior language learning experiences might be positively (for explicit aptitude) or negatively (for implicit aptitude) correlated with language aptitude. Additionally, explicit aptitude and implicit aptitude might have a competitive relationship. Possible implications were discussed in this article.

E-cadherin on epithelial-mesenchymal transition in thyroid cancer.

Thyroid carcinoma is a common malignant tumor of endocrine system and head and neck. Recurrence, metastasis and high malignant expression after routine treatment are serious clinical problems, so it is of great significance to explore its mechanism and find action targets. Epithelial-mesenchymal transition (EMT) is associated with tumor malignancy and invasion. One key change in tumour EMT is low expression of E-cadherin. Therefore, this article reviews the expression of E-cadherin in thyroid cancers (TC), discuss the potential mechanisms involved, and outline opportunities to exploit E-cadherin on regulating the occurrence of EMT as a critical factor in cancer therapeutics.

A survey of core replacements in indole-based HIV-1 attachment inhibitors.

Indole- and azaindole-based glyoxylyl amide derivatives have been described as HIV-1 attachment inhibitors (AIs) that act by blocking the interaction between the viral gp120 coat protein and the human host cell CD4 receptor. As part of an effort to more deeply understand the role of the indole/azaindole heterocycle in the expression of antiviral activity, a survey of potential replacements was conducted using parallel synthesis methodology. The design and optimization was guided by a simple 2-dimensional overlay based on an overall planar topography between the indole/azaindole and C-7 substituents that had been deduced from structure-activity studies leading to the discovery of temsavir (3). 2-Substituted naphthalene- and quinoline-derived chemotypes emerged as the most interesting prototypes, with C-5 and C-6 substituents enhancing antiviral potency. Despite the fact that neither of these chemotypes incorporated a H-bond donor that has been shown to engage the side chain carboxylate of Asp113 in gp120, the antiviral potency of several analogues met or exceeded that of 3, demonstrating that engaging Asp113 is not a prerequisite for potent antiviral activity.

Effectiveness of Mindfulness-Based Cognitive Therapy on Depressive Symptoms, Brain Potential, and Neuroimmunoinflammatory Factors in Depressed Patients.

OBJECTIVE: This study was aimed to investigate the effectiveness of mindfulness-based cognitive therapy (MBCT) on depressive symptoms, brain potential, and neuroimmunoinflammatory factors in patients with depression. METHODS: Sixty-four eligible patients according to the inclusion criteria were randomly divided into the control group and the observation group, with 32 patients in each group. The control group received conventional therapy, while the observation group received MBCT on top of conventional therapy. The depressive symptoms, brain potential, and neuroimmunoinflammatory factors were measured in the two groups. RESULTS: After treatment, the Hamilton Depression Rating Scale score, tumor necrosis factor α, and interleukin-6 levels were decreased, while the World Health Organization Quality of Life Scale score, total number of response execution score, and 5-hydroxy tryptamine level were increased in both groups. Moreover, the Hamilton Depression Rating Scale score, tumor necrosis factor α, and interleukin-6 levels were decreased more significantly, while the World Health Organization Quality of Life Scale score, total number of response execution score, and 5-hydroxy tryptamine level were increased more significantly in the observation group compare to the control group ( P < 0.01). In addition, the latency in the observation group was shorter and the amplitude was longer than those in the control group ( P < 0.01). CONCLUSIONS: Compared with conventional therapy, the use of MBCT combined with conventional therapy can effectively reduce depressive symptoms, suppresses inflammatory responses, and optimize attention and response to target stimulation and is worthy of wide clinical implementation.

Rare taxa mediate microbial carbon and nutrient limitation in the rhizosphere and bulk soil under sugarcane-peanut intercropping systems.

Introduction: Microbial carbon (C) and nutrient limitation exert key influences on soil organic carbon (SOC) and nutrient cycling through enzyme production for C and nutrient acquisition. However, the intercropping effects on microbial C and nutrient limitation and its driving factors between rhizosphere and bulk soil are unclear. Methods: Therefore, we conducted a field experiment that covered sugarcane-peanut intercropping with sole sugarcane and peanut as controls and to explore microbial C and nutrient limitation based on the vector analysis of enzyme stoichiometry; in addition, microbial diversity was investigated in the rhizosphere and bulk soil. High throughput sequencing was used to analyze soil bacterial and fungal diversity through the 16S rRNA gene and internal transcribed spacer (ITS) gene at a phylum level. Results: Our results showed that sugarcane-peanut intercropping alleviated microbial C limitation in all soils, whereas enhanced microbial phosphorus (P) limitation solely in bulk soil. Microbial P limitation was also stronger in the rhizosphere than in bulk soil. These results revealed that sugarcane-peanut intercropping and rhizosphere promoted soil P decomposition and facilitated soil nutrient cycles. The Pearson correlation results showed that microbial C limitation was primarily correlated with fungal diversity and fungal rare taxa (Rozellomycota, Chyltridiomycota, and Calcarisporiellomycota) in rhizosphere soil and was correlated with bacterial diversity and most rare taxa in bulk soil. Microbial P limitation was solely related to rare taxa (Patescibacteria and Glomeromycota) in rhizosphere soil and related to microbial diversity and most rare taxa in bulk soil. The variation partitioning analysis further indicated that microbial C and P limitation was explained by rare taxa (7%-35%) and the interactions of rare and abundant taxa (65%-93%). Conclusion: This study indicated the different intercropping effects on microbial C and nutrient limitation in the rhizosphere and bulk soil and emphasized the importance of microbial diversity, particularly rare taxa.

RAD18 O-GlcNAcylation promotes translesion DNA synthesis and homologous recombination repair.

RAD18, an important ubiquitin E3 ligase, plays a dual role in translesion DNA synthesis (TLS) and homologous recombination (HR) repair. However, whether and how the regulatory mechanism of O-linked N-acetylglucosamine (O-GlcNAc) modification governing RAD18 and its function during these processes remains unknown. Here, we report that human RAD18, can undergo O-GlcNAcylation at Ser130/Ser164/Thr468, which is important for optimal RAD18 accumulation at DNA damage sites. Mechanistically, abrogation of RAD18 O-GlcNAcylation limits CDC7-dependent RAD18 Ser434 phosphorylation, which in turn significantly reduces damage-induced PCNA monoubiquitination, impairs Polη focus formation and enhances UV sensitivity. Moreover, the ubiquitin and RAD51C binding ability of RAD18 at DNA double-strand breaks (DSBs) is O-GlcNAcylation-dependent. O-GlcNAcylated RAD18 promotes the binding of RAD51 to damaged DNA during HR and decreases CPT hypersensitivity. Our findings demonstrate a novel role of RAD18 O-GlcNAcylation in TLS and HR regulation, establishing a new rationale to improve chemotherapeutic treatment.

VGLL3 modulates chemosensitivity through promoting DNA double-strand break repair.

Transcription cofactor vestigial-like 3 (VGLL3), as a master regulator of female-biased autoimmunity, also functions in tumor development, while the underlying mechanisms remain largely elusive. Here, we report that VGLL3 plays an important role in DNA damage response (DDR). VGLL3 can be recruited to damage sites in a PARylation-dependent manner. VGLL3 depletion impairs the accumulation of RNF8 and RAD51 at sites of DNA damage, leading to reduced homologous recombination efficiency and increased cellular sensitivity to chemotherapeutic drugs. Mechanistically, VGLL3 can prevent CtIP from KLHL15-mediated ubiquitination and degradation through competitive binding with KLHL15 and, meanwhile, stabilize MDC1 by limiting TRIP12-MDC1 but promoting USP7-MDC1 associations for optimal RNF8 signaling initiation. Consistently, VGLL3 depletion delays tumor development and sensitizes the xenografts to etoposide treatment. Overall, our results reveal an unexpected role of VGLL3 in DDR, which is distinct from its transcriptional cofactor function and not conserved among VGLL family members.

Inhibitors of HIV-1 attachment. Part 10. The discovery and structure-activity relationships of 4-azaindole cores.

A series of 4-azaindole oxoacetic acid piperazine benzamides was synthesized and evaluated in an effort to identify an oral HIV-1 attachment inhibitor with the potential to improve upon the pre-clinical profile of BMS-378806 (7), an initial clinical compound. Modifications at the 7-position of the 4-azaindole core modulated potency significantly and SAR showed that certain compounds with a 5-membered ring heteroaryl group at that position were the most potent. Four of the compounds with the best profiles were evaluated in a rat pharmacokinetic model and all had superior oral bioavailability and lower clearance when compared with 7.

Inhibitors of HIV-1 attachment. Part 11: the discovery and structure-activity relationships associated with 4,6-diazaindole cores.

A series of HIV-1 attachment inhibitors containing a 4,6-diazaindole core were examined in an effort to identify a compound which improved upon the potency and oral exposure of BMS-488043 (2). BMS-488043 (2) is a 6-azaindole-based HIV-1 attachment inhibitor which established proof-of-concept for this mechanism in human clinical studies but required high doses and concomitant administration of a high fat meal to achieve efficacious exposures. Based on previous studies in indole and azaindole scaffolds, SAR investigation was concentrated around the key 7-position in the 4,6-diazaindole series and led to the discovery of molecules with 5- to 20-fold increases in potency and three- to seven-fold increases in exposure over 2 in a rat PK studies.

Inhibitors of HIV-1 attachment. Part 7: indole-7-carboxamides as potent and orally bioavailable antiviral agents.

A series of substituted carboxamides at the indole C7 position of the previously described 4-fluoro-substituted indole HIV-1 attachment inhibitor 1 was synthesized and the SAR delineated. Heteroaryl carboxamide inhibitors that exhibited pM potency in the primary cell-based assay against a pseudotype virus expressing a JRFL envelope were identified. The simple methyl amide analog 4 displayed a promising in vitro profile, with its favorable HLM stability and membrane permeability translating into favorable pharmacokinetic properties in preclinical species.

Inhibitors of HIV-1 attachment. Part 8: the effect of C7-heteroaryl substitution on the potency, and in vitro and in vivo profiles of indole-based inhibitors.

As part of the SAR profiling of the indole-oxoacetic piperazinyl benzamide class of HIV-1 attachment inhibitors, substitution at the C7 position of the lead 4-fluoroindole 2 with various 5- and 6-membered heteroaryl moieties was explored. Highly potent (picomolar) inhibitors of pseudotyped HIV-1 in a primary, cell-based assay were identified and select examples were shown to possess nanomolar inhibitory activity against M- and T-tropic viruses in cell culture. These C7-heteroaryl-indole analogs maintained the ligand efficiency (LE) of 2 and were also lipophilic efficient as measured by LLE and LELP. Pharmacokinetic studies of this class of inhibitor in rats showed that several possessed substantially improved IV clearance and half-lives compared to 2. Oral exposure in the rat correlated with membrane permeability as measured in a Caco-2 assay where the highly permeable 1,2,4-oxadiazole analog 13 exhibited the highest exposure.

The (dis)engagement of different components of inhibitory control in trilingual language control.

Despite the worldwide prevalence of multilingualism, the knowledge of the relationship between domain-general cognitive control and multilingual language control remains scant. Here we provide new insights into this issue by examining systematically how different components of inhibitory control (i.e., response inhibition and interference suppression) contribute to language control in multilingual populations with high L2 proficiency. To this end, 65 Tibetan-Chinese-English trilinguals highly proficient in L2 were recruited to complete three tasks: a picture-naming task measuring the performance of online trilingual speech production, and two nonlinguistic tasks, a go/no-go task and a Simon task, as proxies for measuring response inhibition and interference suppression abilities, respectively. Using mixed-effects modeling, we analyzed both the trilingual language switching/nonswitching performances and their correlations with these two components of inhibitory control. Our data revealed unexpected patterns of reversed language dominance effect and (a)symmetries in switch costs. Notably, interaction analysis revealed that while response inhibition was robustly engaged in trilingual language control, interference suppression did not appear to play a role. Taken together, our study suggests that, for trilingual speakers highly proficient in L2, the recruitment of different subprocesses of inhibitory control in lexical access was selective and was constrained to reactive and local-level language control. We conclude by discussing theoretical implications. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

Food volume estimation by multi-layer superpixel.

Estimating the volume of food plays an important role in diet monitoring. However, it is difficult to perform this estimation automatically and accurately. A new method based on the multi-layer superpixel technique is proposed in this paper to avoid tedious human-computer interaction and improve estimation accuracy. Our method includes the following steps: 1) obtain a pair of food images along with the depth information using a stereo camera; 2) reconstruct the plate plane from the disparity map; 3) warp the input image and the disparity map to form a new direction of view parallel to the plate plane; 4) cut the warped image into a series of slices according to the depth information and estimate the occluded part of the food; and 5) rescale superpixels for each slice and estimate the food volume by accumulating all available slices in the segmented food region. Through a combination of image data and disparity map, the influences of noise and visual error in existing interactive food volume estimation methods are reduced, and the estimation accuracy is improved. Our experiments show that our method is effective, accurate and convenient, providing a new tool for promoting a balanced diet and maintaining health.

Recent Progress on Natural Clay Minerals for Lithium-Sulfur Batteries.

Li-S batteries with high energy density have the potential to become a viable alternative to Li-ion batteries. However, Li-S batteries still face several challenges, including the shuttle effect, low conversion kinetics, and Li dendrite growth. Natural clay minerals with porous structures, abundant Lewis-acid sites, high mechanical modulus, and versatile structural regulation show great potential for improving the performance of Li-S batteries. However, so far, relevant reviews focusing on the applications of natural clay minerals in Li-S batteries are still missing. To fill the gap, this review first presents an overview of the crystal structures of several natural clay minerals, including 1D (halloysites, attapulgites, and sepiolite), 2D (montmorillonite and vermiculite), and 3D (diatomite) structures, providing a theoretical basis for the application of natural clay minerals in Li-S batteries. Subsequently, research advancements in the natural clay-based energy materials in Li-S batteries have been comprehensively reviewed. Finally, the perspectives concerning the development of natural clay minerals and their applications in Li-S batteries are provided. We hope this review can provide timely and comprehensive information on the correlation between the structure and function of natural clay minerals in Li-S batteries and offer guidance for material selection and structure optimization of natural clay-based energy materials.

Drug-target affinity prediction method based on multi-scale information interaction and graph optimization.

Drug-target affinity (DTA) prediction as an emerging and effective method is widely applied to explore the strength of drug-target interactions in drug development research. By predicting these interactions, researchers can assess the potential efficacy and safety of candidate drugs at an early stage, narrowing down the search space for therapeutic targets and accelerating the discovery and development of new drugs. However, existing DTA prediction models mainly use graphical representations of drug molecules, which lack information on interactions between individual substructures, thus affecting prediction accuracy and model interpretability. Therefore, transformer and diffusion on drug graphs in DTA prediction (TDGraphDTA) are introduced to predict drug-target interactions using multi-scale information interaction and graph optimization. An interactive module is integrated into feature extraction of drug and target features at different granularity levels. A diffusion model-based graph optimization module is proposed to improve the representation of molecular graph structures and enhance the interpretability of graph representations while obtaining optimal feature representations. In addition, TDGraphDTA improves the accuracy and reliability of predictions by capturing relationships and contextual information between molecular substructures. The performance of the proposed TDGraphDTA in DTA prediction was verified on three publicly available benchmark datasets (Davis, Metz, and KIBA). Compared with state-of-the-art baseline models, it achieved better results in terms of consistency index, R-squared, etc. Furthermore, compared with some existing methods, the proposed TDGraphDTA is demonstrated to have better structure capturing capabilities by visualizing the feature capturing capabilities of the model using Grad-AAM toxicity labels in the ToxCast dataset. The corresponding source codes are available at https://github.com/Lamouryz/TDGraph.

In vitro antiviral characteristics of HIV-1 attachment inhibitor BMS-626529, the active component of the prodrug BMS-663068.

BMS-663068 is the phosphonooxymethyl prodrug of BMS-626529, a novel small-molecule attachment inhibitor that targets HIV-1 gp120 and prevents its binding to CD4(+) T cells. The activity of BMS-626529 is virus dependent, due to heterogeneity within gp120. In order to better understand the anti-HIV-1 spectrum of BMS-626529 against HIV-1, in vitro activities against a wide variety of laboratory strains and clinical isolates were determined. BMS-626529 had half-maximal effective concentration (EC(50)) values of <10 nM against the vast majority of viral isolates; however, susceptibility varied by >6 log(10), with half-maximal effective concentration values in the low pM range against the most susceptible viruses. The in vitro antiviral activity of BMS-626529 was generally not associated with either tropism or subtype, with few exceptions. Measurement of the binding affinity of BMS-626529 for purified gp120 suggests that a contributory factor to its inhibitory potency may be a relatively long dissociative half-life. Finally, in two-drug combination studies, BMS-626529 demonstrated additive or synergistic interactions with antiretroviral drugs of different mechanistic classes. These results suggest that BMS-626529 should be active against the majority of HIV-1 viruses and support the continued clinical development of the compound.

Conditional Feature Embedding by Visual Clue Correspondence Graph for Person Re-Identification.

Although Person Re-Identification has made impressive progress, difficult cases like occlusion, change of view-point, and similar clothing still bring great challenges. In order to tackle these challenges, extracting discriminative feature representation is crucial. Most of the existing methods focus on extracting ReID features from individual images separately. However, when matching two images, we propose that the ReID features of a query image should be dynamically adjusted based on the contextual information from the gallery image it matches. We call this type of ReID features conditional feature embedding. In this paper, we propose a novel ReID framework that extracts conditional feature embedding based on the aligned visual clues between image pairs, called Clue Alignment based Conditional Embedding (CACE-Net). CACE-Net applies an attention module to build a detailed correspondence graph between crucial visual clues in image pairs and uses discrepancy-based GCN to embed the obtained complex correspondence information into the conditional features. The experiments show that CACE-Net achieves state-of-the-art performance on three public datasets.

Conditional Feature Learning Based Transformer for Text-Based Person Search.

Text-based person search aims at retrieving the target person in an image gallery using a descriptive sentence of that person. The core of this task is to calculate a similarity score between the pedestrian image and description, which requires inferring the complex latent correspondence between image sub-regions and textual phrases at different scales. Transformer is an intuitive way to model the complex alignment by its self-attention mechanism. Most previous Transformer-based methods simply concatenate image region features and text features as input and learn a cross-modal representation in a brute force manner. Such weakly supervised learning approaches fail to explicitly build alignment between image region features and text features, causing an inferior feature distribution. In this paper, we present CFLT, Conditional Feature Learning based Transformer. It maps the sub-regions and phrases into a unified latent space and explicitly aligns them by constructing conditional embeddings where the feature of data from one modality is dynamically adjusted based on the data from the other modality. The output of our CFLT is a set of similarity scores for each sub-region or phrase rather than a cross-modal representation. Furthermore, we propose a simple and effective multi-modal re-ranking method named Re-ranking scheme by Visual Conditional Feature (RVCF). Benefit from the visual conditional feature and better feature distribution in our CFLT, the proposed RVCF achieves significant performance improvement. Experimental results show that our CFLT outperforms the state-of-the-art methods by 7.03% in terms of top-1 accuracy and 5.01% in terms of top-5 accuracy on the text-based person search dataset.