A supramolecular photosensitizer based on triphenylamine and pyrazine with aggregation-induced emission properties for high-efficiency photooxidation reactions.

Recently, there has been a great interest in the study of photocatalysts (PCs) and photosensitizers (PSs) in the field of organic photocatalysis. In the present study, a pure organic thermally activated delayed fluorescence (TADF) molecule 4,4'-(12-(pyridin-4-yl)dibenzo[f,h]pyrido[2,3-b]quinoxaline-3,6-diyl)bis(N,N-diphenylaniline) (DPQ-TPA) was designed and synthesized, which not only have excellent TADF property and small energy splitting (ΔEST), but also can self-assembly in water to form cross-linked nanoparticles with exceptional aggregation-induced emission (AIE) characteristics. DPQ-TPA exhibits excellent remarkable selectivity and notably enhances the production capacity of reactive oxygen species (ROS), particularly 1O2, which was employed as a highly effective photocatalyst in the photooxidation reaction of phosphine and hydroazobenzenes under blue light irradiation with high yields up to 94% and 91%, respectively. This work expands the potential application of (donor-acceptor) D-A type AIE-TADF molecules in photocatalytic organic transformations through supramolecular self-assembly.

Single-Mg-Atom Catalyst with a Dual Active Center as an Emerging Promising Sensing Platform.

Bisphenol compounds [bisphenol A (BPA), etc.] are one class of the most important and widespread pollutants in food and environment, which pose severe endocrine disrupting effect, reproductive toxicity, immunotoxicity, and metabolic toxicity on humans and animals. Simultaneous rapid determination of BPA and its analogues (bisphenol S, bisphenol AF, etc.) with extraordinary potential resolution and sensitivity is of great significance but still extremely challenging. Herein, a series of single-atom catalysts (SACs) were synthesized by anchoring different metal atoms (Mg, Co, Ni, and Cu) on N-doped carbon materials and used as sensing materials for simultaneous detection of bisphenols with similar chemical structures. The Mg-based SAC enables the potential discrimination and simultaneous rapid detection of multiple bisphenols, showing outstanding analytical performances, outperforming all other SACs and traditional electrode materials. Our experiments and density functional theory calculations show that pyrrolic N serves as the adsorption site for the adsorption of bisphenols and the Mg atom serves as the active site for the electrocatalytic oxidation of bisphenols, which play a synergistic role as dual active centers in improving the sensing performance. The results of this work may pave the way for the rational design of SACs as advanced sensing and catalytic materials.

Photocatalytic selective oxidation of toluene under encapsulated air conditions.

Benzaldehydes are indispensable building blocks in chemistry. However, the selective oxidation of toluene to benzaldehyde remains an ongoing challenge due to the low oxidation potential of benzaldehyde compared to toluene. We report herein a mild protocol that combines hydrogen atom transfer (HAT) with encapsulated air conditions and suitable catalyst loading for selective oxidation of toluene with high selectivity as well as good functional-group tolerance and a broad substrate scope for the synthesis of various high-value aromatic aldehydes. Moreover, the compatibility of this reaction with toluene derivatives of bioactive molecules further demonstrated the practicality of this approach. Mechanism studies have demonstrated that the collaboration between the oxygen quantity and the HAT catalytic system has a major impact on the high selectivity of the reaction. This study not only showcases the effectiveness of HAT strategies toward selective oxidation of toluene to benzaldehyde, but also provides an approach to controlling the selectivity of HAT reactions.

Comprehensive Attribute Prediction Learning for Person Search by Language.

Person search by language refers to searching for the interested pedestrian images given natural language sentences, which requires capturing fine-grained differences to accurately distinguish different pedestrians, while still far from being well addressed by most of the current solutions. In this paper, we propose the Comprehensive Attribute Prediction Learning (CAPL) method, which explicitly carries out attribute prediction learning, for improving the modeling capabilities of fine-grained semantic attributes and obtaining more discriminative visual and textual representations. First, we construct the semantic ATTribute Vocabulary (ATT-Vocab) based on sentence analysis. Second, the complementary context-wise and attribute-wise attribute predictions are simultaneously conducted to better model the high-frequency in-vocab attributes in our In-vocab Attribute Prediction (IAP) module. Third, to additionally consider the out-of-vocab semantics, we present the Attribute Completeness Learning (ACL) module for better capturing the low-frequency attributes outside the ATT-Vocab, obtaining more comprehensive representations. Combining the IAP and ACL modules together, our CAPL method has obtained the currently state-of-the-art retrieval performance on two widely-used benchmarks, i.e., CUHK-PEDES and ICFG-PEDES datasets. Extensive experiments and analyses have been carried out to validate the effectiveness and generalization capacities of our CAPL method.

Switchover from singlet oxygen to superoxide radical through a photoinduced two-step sequential energy transfer process.

The competitive nature of type II photosensitizers in the transfer of excitation energy for the generation of singlet oxygen (1O2) presents significant challenges in the design of type I photosensitizers to produce the superoxide anion radical (O2˙-). In this study, we present an efficient method for the direct transformation of type II photosensitizers into type I photosensitizers through the implementation of an artificial light-harvesting system (ALHSs) involving a two-step sequential energy transfer process. The designed supramolecular complex (DNPY-SBE-ß-CD) not only has the ability to generate 1O2 as type II photosensitizers, but also demonstrates remarkable fluorescence properties in aqueous solution, which renders it an efficient energy donor for the development of type I photosensitizers ALHSs, thereby enabling the efficient generation of O2˙-. Meanwhile, to ascertain the capability and practicality of this method, two organic reactions were conducted, namely the photooxidation reaction of thioanisole and oxidative hydroxylation of arylboronic acids, both of which display a high level of efficiency and exhibit significant catalytic performance. This work provides an efficient method for turning type II photosensitizers into type I photosensitizers by a two-step sequential energy transfer procedure.

Ion Migration in Lead-Halide Perovskites: Cation Matters.

Metal halide perovskites exhibit remarkable properties for optoelectronic applications, yet their susceptibility to ion migration poses challenges for device stability. Previous research has predominantly focused on the migration of the halide ions. However, the migration of cations, which also has a significant influence on the device performance, is largely overlooked. In this Perspective, we review the migration of cations and their impacts on perovskite materials and devices. Special attention shall be devoted to recent insights into the migration of L-site organic cations in 2D/3D perovskites. We outline inspirations and directions for further research into the cation migration of perovskites, highlighting new possibilities in advancing perovskite optoelectronics.

Multifunctional cardiac microphysiological system based on transparent ITO electrodes for simultaneous optical measurement and electrical signal monitoring.

Drug-induced cardiotoxicity is a significant contributor to drug recalls, primarily attributed to limitations in existing drug screening platforms. Traditional heart-on-a-chip platforms often employ metallic electrodes to record cardiomyocyte electrical signals. However, this approach hinders direct cardiomyocyte morphology observation and typically yields limited functionality. Consequently, this limitation may lead to an incomplete understanding of cardiomyocyte characteristics. To address these challenges, we introduce a multifunctional cardiac microphysiological system featuring transparent indium tin oxide electrodes. This innovative design aims to overcome the limitations of conventional heart-on-a-chip systems where metal electrodes interfere with the observation of cells and increase the difficulty of subsequent image processing of cell images. In addition to facilitating optical measurement combined with image processing capabilities, this system integrates a range of electrodes with diverse functionalities. These electrodes can realize cellular electrical stimulation, field potential monitoring, and impedance change tracking, enabling a comprehensive investigation of various cardiomyocyte traits. To demonstrate its versatility, we investigate the effects of four cardiac drugs with distinct pharmacological profiles on cardiomyocytes using this system. This platform provides a means for quantitatively and predictively assessing cardiac toxicity, which could be applied to conduct a comprehensive evaluation during the drug discovery process.

Visible-light-mediated direct C3 alkylation of quinoxalin-2(1H)-ones using alkanes.

Due to the high C-H bond dissociation energy of alkanes, the utilization of alkanes as alkyl radical precursors for C-H functionalization of heteroarenes is synthetically captivating but practically challenging, especially under metal- and photocatalyst-free conditions. We report herein a mild and practical visible-light-mediated method for C-H alkylation of quinoxalin-2(1H)-ones using trifluoroacetic acid as a hydrogen atom transfer reagent and air as an oxidant. This mild protocol was performed under metal- and photocatalyst-free circumstances and presented good functional-group tolerance as well as a broad substrate scope.

Paeoniflorin improves ulcerative colitis via regulation of PI3K­AKT based on network pharmacology analysis.

Paeoniflorin (PF) is the primary component derived from Paeonia lactiflora and white peony root and has been used widely for the treatment of ulcerative colitis (UC) in China. UC primarily manifests as a chronic inflammatory response in the intestine. In the present study, a network pharmacology approach was used to explore the specific effects and underlying mechanisms of action of PF in the treatment of UC. A research strategy based on network pharmacology, combining target prediction, network construction, Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis, and molecular docking simulation was used to predict the targets of PF. A total of 288 potential targets of PF and 599 UC-related targets were identified. A total of 60 therapeutic targets of PF against UC were identified. Of these, 20 core targets were obtained by protein-protein interaction network construction. GO and KEGG pathway analyses showed that PF alleviated UC through EGFR tyrosine kinase inhibitor resistance, the IL-17 signaling pathway, and the PI3K/AKT signaling pathway. Molecular docking simulation showed that AKT1 and EGFR had good binding energy with PF. Animal-based experiments revealed that the administration of PF ameliorated the colonic pathological damage in a dextran sulfate sodium-induced mouse model, resulting in lower levels of proinflammatory cytokines including IL-1ß, IL-6, and TNF-α, and higher levels of IL-10 and TGF-ß. PF decreased the mRNA and protein expression levels of AKT1, EGFR, mTOR, and PI3K. These findings suggested that PF plays a therapeutic protective role in the treatment of UC by regulating the PI3K/AKT signaling pathway.

Deep Learning Based Prediction of Myopia Control Effect in Children Treated With Overnight Orthokeratology.

OBJECTIVES: To develop and validate a deep learning-based model for predicting 12-month axial length (AL) elongation using baseline factors and early corneal topographic changes in children treated with orthokeratology (Ortho-K) and to investigate the association between these factors and myopia control impact. METHODS: A total of 115 patients with Ortho-K were enrolled. Influential baseline factors that have a statistically significant correlation with 12-month AL from medical records were selected using Pearson correlation coefficients. Simultaneously, the height, area, and volume of the defocus region were directly calculated from the corneal topography. Then, the prediction model was developed by combining multiple linear regression and deep neural network and evaluated in an independent group (83 patients for developing the algorithm and 32 patients for evaluation). RESULTS: Age ( r= -0.30, P <0.001), spherical equivalent refractive (SE; r =0.20, P =0.032), and sex ( r =0.19, P =0.032) were significantly correlated with the AL elongation while pupil diameter, flat k, steep k, horizontal corneal diameter (white to white), anterior chamber depth, and cell density were not ( P >0.1). The prediction model was developed using age, SE, and corneal topographic variation, and the validation of the model demonstrated its effectiveness in predicting AL elongation. CONCLUSIONS: The AL elongation was accurately predicted by the deep learning model, which effectively incorporated both baseline factors and corneal topographic variation.

Attention-Based Deep Learning Model for Prediction of Major Adverse Cardiovascular Events in Peritoneal Dialysis Patients.

Major adverse cardiovascular events (MACE) encompass pivotal cardiovascular outcomes such as myocardial infarction, unstable angina, and cardiovascular-related mortality. Patients undergoing peritoneal dialysis (PD) exhibit specific cardiovascular risk factors during the treatment, which can escalate the likelihood of cardiovascular events. Hence, the prediction and key factor analysis of MACE have assumed paramount significance for peritoneal dialysis patients. Current pathological methodologies for prognosis prediction are not only costly but also cumbersome in effectively processing electronic health records (EHRs) data with high dimensionality, heterogeneity, and time series. Therefore in this study, we propose the CVEformer, an attention-based neural network designed to predict MACE and analyze risk factors. CVEformer leverages the self-attention mechanism to capture temporal correlations among time series variables, allowing for weighted integration of variables and estimation of the probability of MACE. CVEformer first captures the correlations among heterogeneous variables through attention scores. Then, it analyzes the correlations within the time series data to identify key risk variables and predict the probability of MACE. When trained and evaluated on data from a large cohort of peritoneal dialysis patients across multiple centers, CVEformer outperforms existing models in terms of predictive performance.

Nitrogen-doped Carbon Dots as Efficient Photocatalysts for High Selectivity of Dehalogenative Oxyalkylation of Styrene.

Carbon dots (CDs) are a type of carbon-based luminescent material with a zero-dimensional structure and a size of less than 10 nm, which are composed of sp2/sp3 hybrid carbon nuclei and surface functional groups. Because CDs has strong photoluminescence and good light absorption in the ultraviolet and near visible regions, it is an excellent candidate for photocatalytic applications. However, the use of nonmetallic doped CDs as photosensitizers for direct photocatalytic organic reactions has been limited to several scattered reports. Herein, we present nitrogen-doped carbon dots (N-CDs) that has a capability for not only produce reactive oxygen species (ROS), including superoxide anion radical (O2⋅-) and singlet oxygen (1O2), but also provide an unprecedented high activity of dehalogenative oxyalkylation of styrene with a yield of 93 %. This work develops a novel opportunity to utilize cost-effective and easily accessible CDs for the advancement of photocatalysis.

In vitro antibacterial effects of Broussonetia papyrifera leaf extract and its anti-colitis in DSS-treated mice.

Recently, the hybrid Broussonetia papyrifera (BP) has been extensively cultivated and predominantly utilized in ruminants because of its high protein and bioactive compound content. In the present study, the effects of an ethanolic extract of BP leaves (BPE, 200 mg/kg) on mitigating 2% dextran sodium sulfate (DSS)-induced intestinal inflammation in mice were evaluated. BPE is rich in flavonoids, polyphenols, and polysaccharides, and displays potent antioxidant and antibacterial activities against pathogenic strains such as Clostridium perfringens, Salmonella Typhimurium, and Salmonella enterica subsp. enterica in vitro. In a mouse study, oral administration of DSS resulted in weight loss, incidence of diarrhea, enlargement of the liver and spleen, impaired colonic morphology, downregulation of both gene and protein expression related to intestinal antioxidant (Nrf2) and barrier function (ZO-1), decreased diversity of colonic microbiota, and 218 differentially altered colonic metabolites; however, co-treatment with BPE did not restore these modified aspects except for the liver index and colonic bacterial diversity. The singular treatment with BPE did not manifest evident side effects in normal mice but induced a mild occurrence of diarrhea and a notable alteration in the colonic metabolite profile. Moreover, a single BPE administration augmented the abundance of the commensal beneficial bacteria Faecalibaculum and Akkermansia genera. Overall, the extract of BP leaves did not demonstrate the anticipated effectiveness in alleviating DSS-induced intestinal inflammation.

Host-Guest Photosensitizer of a Cationic BODIPY Derivative and Cucurbit[7]uril for High-Efficiency Visible Light-Induced Photooxidation Reactions.

In recent years, there has been a notable surge of interest in the fields of organic and pharmaceutical research about photocatalysts (PCs) and photosensitizers (PSs). In this study, a 4,4-difluoro-4-bora-3a,4a-diaza-s-indacene (BODIPY) molecule adorned with quaternary ammonium (TMB) functionality was meticulously designed and synthesized. This compound has remarkable characteristics such as exceptional water solubility, great optical qualities, and commendable photostability. It can form a 1:1 complex (TMB-CB[7]) with cucurbit[7]uril (CB[7]) through host-guest interactions in the aqueous solution and shows obvious fluorescence enhancement. The reactive oxygen species (ROS) including superoxide anion radical (O2·-) and singlet oxygen (1O2) generation ability of TMB-CB[7] were promoted compared with that of TMB in the aqueous solution. More interestingly, the ROS generated from TMB-CB[7] can be used as PCs for aerobic cross dehydrogenation coupling reactions and photooxidation reactions in water with high yields of 89 and 95%, respectively. Therefore, the utilization of a host-guest PS presents a novel and environmentally friendly approach for conducting photocatalyzed organic processes under ambient conditions using visible light.

Construction of an efficient artificial light-harvesting system based on hyperbranched polyethyleneimine and improvement of photocatalytic performance.

An artificial light-harvesting system (ALHS) was developed in aqueous solution by employing the electrostatic co-assembly of a tetraphenylethylene derivative modified with two sulfonate groups (TPE-BSBO) and hyperbranched polyethyleneimine (PEI) as the energy donors, and 4,7-bis(2-thienyl)-2,1,3-benzothiadiazole (DBT) as the energy acceptors. The ALHS exhibits not only high efficiency in energy transfer and conversion but also a significant enhancement in the generation of reactive oxygen species (ROS), especially superoxide anion radicals (O2˙-), facilitating its utilization in photocatalytic oxidation reactions.

Pre-Configured Error Pattern Ordered Statistics Decoding for CRC-Polar Codes.

In this paper, we propose a pre-configured error pattern ordered statistics decoding (PEPOSD) algorithm and discuss its application to short cyclic redundancy check (CRC)-polar codes. Unlike the traditional OSD that changes the most reliable independent symbols, we regard the decoding process as testing the error patterns, like guessing random additive noise decoding (GRAND). Also, the pre-configurator referred from ordered reliability bits (ORB) GRAND can better control the range and testing order of EPs. An offline-online structure can accelerate the decoding process. Additionally, we also introduce two orders to optimize the search order for testing EPs. Compared with CRC-aided OSD and list decoding, PEPOSD can achieve a better trade-off between accuracy and complexity.

Metagenomic characterization of the cecal microbiota community and functions in finishing pigs fed fermented Boehmeria nivea.

Ramie (Boehmeria nivea, BN) is used as livestock forage through suitable silage fermentation owing to its nutritional value. To date, relatively few studies have investigated the effects of dietary fermented BN (FBN) on gut health in finishing pigs. The aim of the present study was to investigate the effects of dietary supplementation with 20% FBN on intestinal morphology, gene expression, and the functional response of the gut microbiota in finishing pigs. We found that FBN did not significantly affect serum antioxidant enzyme activities, ileal morphology, or the expression of genes encoding antioxidant enzymes, inflammatory cytokines, or tight junction proteins in the liver of the pigs. However, the gene expression levels of aryl hydrocarbon receptor (AHR) and interleukin 6 (IL6) were significantly downregulated in the ileum. A metagenomic analysis demonstrated that, compared with that seen in the control group, the cecal microbiota of pigs in the FBN treatment group was more closely clustered and contained a greater number of unique microbes. Bacteria were the predominant kingdom in the cecal microbiota, while Firmicutes, Bacteroidetes, and Proteobacteria were the dominant phyla, and Streptococcus, Lactobacillus, and Prevotella were the dominant genera. Dietary FBN significantly increased the abundance of the probiotic bacterium Roseburia inulinivorans (p < 0.05). Functional analysis of the cecal microbiota showed that ABC transporter levels and glycolysis/gluconeogenesis-associated functions were diminished in FBN-fed pigs. Meanwhile, CAZyme analysis revealed that dietary FBN significantly downregulated the contents of carbohydrate-active enzymes, such as GT2, GH1, GH25, and GH13_31. In addition, cytochrome P450 analysis revealed that the abundance of CYP51 and CYP512 decreased with FBN treatment. An assessment of antibiotic resistance based on the Comprehensive Antibiotic Resistance Database (CARD) annotation indicated that the cecal microbes from pigs in the FBN treatment group had increased resistance to lincosamide, streptogramin, and chloramphenicol and reduced resistance to amikacin, isepamicin, neomycin, lividomycin, gentamicin, paromomycin, ribostamycin, and butirosin. Finally, virulence factor-related analysis showed that putative hemolysin-associated functions were decreased, whereas fibronectin-binding protein, flagella, and alginate-associated functions were increased. Taken together, our data showed that FBN supplementation exerted only minor effects on intestinal morphology and microbial community composition, suggesting that it is potentially safe for use as a supplement in the diets of finishing pigs. However, more studies are needed to validate its functionality.

Ultrasensitive rapid detection of antibiotic resistance genes by electrochemical ratiometric genosensor based on 2D monolayer Ti3C2@AuNPs.

As an important emerging pollutant, antibiotic resistance genes (ARGs) monitoring is crucial to protect the ecological environment and public health, but its rapid and accurate detection is still a major challenge. In this study, a new single-labeled dual-signal output ratiometric electrochemical genosensor (E-DNA) was developed for the rapid and highly sensitive detection of ARGs using a synergistic signal amplification strategy of T3C2@Au nanoparticles (T3C2@AuNPs) and isothermal strand displacement polymerase reaction (ISDPR). Specially, two-dimensional monolayer T3C2 nanosheets loaded with uniformly gold nanoparticles were prepared and used as the sensing platform of the E-DNA sensor. Benefiting from excellent conductivity and large specific surface area of Ti3C2@AuNPs, the probe immobilization capacity of the E-DNA sensor is doubled, and electrochemical response signals of the E-DNA sensor were significantly improved. The proposed single-labeled dual-signal output ratiometric sensing strategy exhibits three to six times higher sensitivity for the sul2 gene than the single-signal sensing strategy, which significantly reduces cost meanwhile retaining the advantages of high sensitivity and reliability offered by conventional dual-labeled ratiometric sensors. Coupled with ISDPR amplification technology, the E-DNA sensor has a wider linear range from 10 fM to 10 nM and a limit of detection as low as 2.04 fM (S/N=3). More importantly, the E-DNA sensor demonstrates excellent specificity, good stability and reproducibility for target ARGs detection in real water samples. The proposed new sensing strategy provides a highly sensitive and versatile tool for the rapid and accurate quantitative analysis of various ARGs in environmental water samples.

Improving Inconspicuous Attributes Modeling for Person Search by Language.

Person search by language aims to retrieve the interested pedestrian images based on natural language sentences. Although great efforts have been made to address the cross-modal heterogeneity, most of the current solutions suffer from only capturing salient attributes while ignoring inconspicuous ones, being weak in distinguishing very similar pedestrians. In this work, we propose the Adaptive Salient Attribute Mask Network (ASAMN) to adaptively mask the salient attributes for cross-modal alignments, and therefore induce the model to simultaneously focus on inconspicuous attributes. Specifically, we consider the uni-modal and cross-modal relations for masking salient attributes in the Uni-modal Salient Attribute Mask (USAM) and Cross-modal Salient Attribute Mask (CSAM) modules, respectively. Then the Attribute Modeling Balance (AMB) module is presented to randomly select a proportion of masked features for cross-modal alignments, ensuring the balance of modeling capacity of both salient attributes and inconspicuous ones. Extensive experiments and analyses have been carried out to validate the effectiveness and generalization capacity of our proposed ASAMN method, and we have obtained the state-of-the-art retrieval performance on the widely-used CUHK-PEDES and ICFG-PEDES benchmarks.

Impact of interictal epileptiform discharges on brain network in self-limited epilepsy with centrotemporal spikes: A magnetoencephalography study.

OBJECTIVE: This study aimed to investigate the differences on resting-state brain networks between the interictal epileptiform discharge (IED) group with self-limited epilepsy with centrotemporal spikes (SeLECTS), the non-IED group with SeLECTS, and the healthy control (HC) group. METHODS: Patients were divided into the IED and non-IED group according to the presence or absence of IED during magnetoencephalography (MEG). We used Wechsler Intelligence Scale for Children, fourth edition (WISC-IV) to assess cognition in 30 children with SeLECTS and 15 HCs. Functional networks were constructed at the whole-brain level and graph theory (GT) analysis was used to quantify the topology of the brain network. RESULTS: The IED group had the lowest cognitive function scores, followed by the non-IED group and then HCs. Our MEG results showed that the IED group had more dispersed functional connectivity (FC) in the 4-8 Hz frequency band, and more brain regions were involved compared to the other two groups. Furthermore, the IED group had fewer FC between the anterior and posterior brain regions in the 12-30 Hz frequency band. Both the IED group and the non-IED group had fewer FC between the anterior and posterior brain regions in the 80-250 Hz frequency band compared to the HC group. GT analysis showed that the IED group had a higher clustering coefficient compared to the HC group and a higher degree compared to the non-IED group in the 80-250 Hz frequency band. The non-IED group had a lower path length in the 30-80 Hz frequency band compared to the HC group. CONCLUSIONS: The study data obtained in this study suggested that intrinsic neural activity was frequency-dependent and that FC networks of the IED group and the non-IED group underwent changes in different frequency bands. These network-related changes may contribute to cognitive dysfunction in children with SeLECTS.