Pt@WS2 -an Extrinsic 2D Dilute Ferromagnetic Semiconductor Beyond Room Temperature.

Extrinsic dilute magnetic semiconductors achieve magnetic functionality through tailored interaction between a semiconducting matrix and a non-magnetic dopant. The absence of intrinsic magnetic impurities makes this approach promising to investigate the newly emerging field of 2D dilute magnetic semiconductors. Here the first realization of an extrinsic 2D DMS in Pt-doped WS2 is demonstrated. A bottom-up synthesis approach yields a uniform and highly crystalline monolayer where platinum selectively occupies the tungsten sub-lattice. The orbital overlap between W 4d and Pt 5d results in spin-selective hybrid states that produce a strong valley-Zeeman splitting. Combined experimental and theoretical results show that this interaction yields a sizable ferromagnetic response with a Curie temperature ≈375 K. These results open up a new route toward 2D magnetic properties through tailoring of atomic interactions for future applications in spintronics and magnetic nanoactuation.

Deciphering the roles of bacterial and fungal communities in the formation and quality of agarwood.

Aquilaria sinensis is a significant resin-producing plant worldwide that is crucial for agarwood production. Agarwood has different qualities depending on the method with which it is formed, and the microbial community structures that are present during these methods are also diverse. Furthermore, the microbial communities of plants play crucial roles in determining their health and productivity. While previous studies have investigated the impact of microorganisms on agarwood formation, they lack comprehensiveness, particularly regarding the properties of the microbial community throughout the entire process from seedling to adult to incense formation. We collected roots, stems, leaves, flowers, fruits and other tissues from seedlings, healthy plants and agarwood-producing plants to address this gap and assess the dominant bacterial species in the microbial community structures of A. sinensis at different growth stages and their impacts on growth and agarwood formation. The bacteria and fungi in these tissues were classified and counted from different perspectives. The samples were sequenced using the Illumina sequencing platform, and sequence analyses and species annotations were performed using a range of bioinformatics tools to assess the plant community compositions. An additional comparison of the samples was conducted using diversity analyses to assess their differences. This research revealed that Listeria, Kurtzmanomyces, Ascotaiwania, Acinetobacter, Sphingobium, Fonsecaea, Acrocalymma, Allorhizobium, Bacillus, Pseudomonas, Peethambara, and Debaryomyces are potentially associated with the formation of agarwood. Overall, the data provided in this article help us understand the important roles played by bacteria and fungi in the growth and agarwood formation process of A. sinensis, will support the theoretical basis for the large-scale cultivation of A. sinensis, and provide a basis for further research on microbial community applications in agarwood production and beyond.

Effect of moxibustion on ATP-sensitive potassium channel (KATP) of bladder in detrusor overactivity rats. / 隔姜隔盐灸"神阙"å¯¹é€¼å°¿è‚Œè¿‡åº¦æ´»åŠ¨å¤§é¼ è†€èƒ±ATP敏感性钾离子通道的影响.

OBJECTIVES: To observe the effect of ginger-salt-partitioned moxibustion on ATP-sensitive potassium (KATP) channel of bladder in detrusor overactivity (DO) rats. METHODS: Female SD rats were randomly divided into sham operation, model, moxibustion and antagonist groups (n=9 in each group). Thorax (T) 10 spinal cord transection was performed by surgery. Ginger-salt partitioned moxibustion was applied to "Shenque" (CV8) for 3 cones, once daily for 14 consecutive days. Rats of the antagonist group were intraperitoneally injected with KATP channel specific antagonist glibenclamide (10 µg·kg-1·d-1) once daily for 14 consecutive days. Urodynamic tests were performed after treatment. The distribution and expression of KATP channel tetrameric subunit (SUR2B) in the bladder of rats was observed by immunofluorescence. The protein and mRNA expression levels of SUR2B in bladder tissue were detected by Western blot and qPCR respectively. RESULTS: Compared with the sham operation group, rats of the model group showed intensive and large phasic contractions of the detrusor during bladder filling, the frequency and amplitude of phasic contractions of the detrusor 5 min before leakage were significantly increased (P<0.001)；the voiding threshold pressure was significantly decreased (P<0.001)；the bladder perfusion volume was increased (P<0.001)；the SUR2B protein and mRNA expression in bladder tissue were significantly reduced (P<0.001). Compared with the model group and the antagonist group, the above-mentioned indicators in the moxibustion group were all reversed (P<0.01, P<0.001, P<0.05). CONCLUSIONS: Ginger-salt partitioned moxibustion can reduce the frequency and amplitude of detrusor phase contraction during bladder filling and prolong the time of first phase contraction in DO rats, which may be associated with up-regulating the expression level of KATP channel protein and mRNA, promoting the outflow of potassium ions, and inhibiting the inflow of calcium ions, thus improve the stability of detrusor during storage.

Preoperative systemic and local inflammation are independent risk factors for difficult laparoscopic cholecystectomy after percutaneous transhepatic gallbladder drainage.

Background: Laparoscopic cholecystectomy (LC) is required for acute cholecystitis patient with percutaneous transhepatic gallbladder drainage (PTGBD). However, it's unknown how to distinguishing the surgical difficulty for these patients. Methods: Data of patients who underwent LC after PTGBD between 2016 and 2022 were collected. Patients were categorized into difficult and non-difficult operations based on operative time, blood loss, and surgical conversion. Performance of prediction model was evaluated by ROC, calibration, and decision curves. Results: A total of 127 patients were analyzed, including 91 in non-difficult operation group and 36 in difficult operation group. Elevated CRP (P = 0.011), pericholecystic effusion (P < 0.001), and contact with stomach or duodenal (P = 0.015) were independent risk factors for difficult LC after PTGBD. A nomogram was developed according to these risk factors, and was well-calibrated and good at distinguishing difficult LC after PTGBD. Conclusion: Preoperative elevated systemic and local inflammation indictors are predictors for difficult LC after PTGBD.

Molecular phylogeny and taxonomy of Phlomoides (Lamiaceae subfamily Lamioideae) in China: Insights from molecular and morphological data.

Phlomoides, with 150-170 species, is the second largest and perhaps most taxonomically challenging genus within the subfamily Lamioideae (Lamiaceae). With about 60 species, China is one of three major biodiversity centers of Phlomoides. Although some Phlomoides species from China have been included in previous molecular phylogenetic studies, a robust and broad phylogeny of this lineage has yet to be completed. Moreover, given the myriad new additions to the genus, the existing infrageneric classification needs to be evaluated and revised. Here, we combine molecular and morphological data to investigate relationships within Phlomoides, with a focus on Chinese species. We observed that plastid DNA sequences can resolve relationships within Phlomoides better than nuclear ribosomal internal and external transcribed spacer regions (nrITS and nrETS). Molecular phylogenetic analyses confirm the monophyly of Phlomoides, but most previously defined infrageneric groups are not monophyletic. In addition, morphological analysis demonstrates the significant taxonomic value of eight characters to the genus. Based on our molecular phylogenetic analyses and morphological data, we establish a novel section Notochaete within Phlomoides, and propose three new combinations as well as three new synonyms. This study presents the first molecular phylogenetic analyses of Phlomoides in which taxa representative of the entire genus are included, and highlights the phylogenetic and taxonomic value of several morphological characters from species of Phlomoides from China. Our study suggests that a taxonomic revision and reclassification for the entire genus is necessary in the future.

Preparation and characterization of hierarchically porous hybrid gels for efficient dye adsorption.

Water treatment faces significant challenges due to the increasing complexity of pollutants and the need for more efficient, sustainable treatment methods. However, current adsorbent materials often struggle with issues such as low adsorption capacity, slow kinetics, and poor reusability, limiting their practical application. In this study, we developed a novel hierarchical porous hybrid gel (HPHG) for water treatment to address the limitations of conventional adsorbents. The HPHG features a multi-level porous structure (from 48 ± 28 nm to 4385 ± 823 nm) that significantly enhances its porosity and specific surface area. We systematically investigated the relationship between the material's structure and its adsorption performance. Kinetic studies revealed a tendency towards a pseudo-second-order adsorption model, attributed to the material's unique structural features that facilitate rapid mass exchange channels inside HPHG and provide abundant active sites for pollutant adsorption. Reusability tests demonstrated that the material retained 85.4% of its initial adsorption capacity after five adsorption-desorption cycles, highlighting its potential for practical applications. This study provides valuable insights into structure-performance relationships in advanced water treatment materials, offering a promising approach for designing next-generation adsorbents with superior efficiency and sustainability.

HI-6-Loaded Vehicle of Liposomes Mediated by an Amphiphilic Pillar[5]arene against Paraoxon Poisoning.

Organophosphate (OP) intoxication has become a severe common health matter all over the world. For the treatment of acute OP poisoning, the effective intracerebral delivery of acetylcholinesterase reactivators is crucial. Here, an amphiphilic hydrazide-pillar[5]arene (HP5A-6C), which could be readily integrated into liposomal bilayers' zwitterionic disaturated phosphatidylcholine (DSPC), was synthesized. A T7 peptide-containing guest (G) was attached on the surface via a noncovalent interaction to make mixed liposomes a particularly appealing candidate for brain-targeting delivery. Such coassembly could remain stable at room temperature for up to 6 weeks, and safety evaluations initially verified its fine biological compatibility. The hydrophilic interiors of T7/HP5A-6C@DSPC could further load HI-6 with 89.70% encapsulation efficiency. Support for brain-targeting potency came from imaging results. Notably, intravenous injection of HI-6-loaded vesicles exhibited a remarkable therapeutic effect on paraoxon (POX)-poisoned mice, effectively alleviating seizures and brain damage and significantly increasing the improving survival rate to 60% over the course of 7 days.

FGTN: Fragment-based graph transformer network for predicting reproductive toxicity.

Reproductive toxicity is one of the important issues in chemical safety. Traditional laboratory testing methods are costly and time-consuming with raised ethical issues. Only a few in silico models have been reported to predict human reproductive toxicity, but none of them make full use of the topological information of compounds. In addition, most existing atom-based graph neural network methods focus on attributing model predictions to individual nodes or edges rather than chemically meaningful fragments or substructures. In current studies, we develop a novel fragment-based graph transformer network (FGTN) approach to generate the QSAR model of human reproductive toxicity by considering internal topological structure information of compounds. In the FGTN model, the compound is represented by a graph architecture using fragments to be nodes and bonds linking two fragments to be edges. A super molecule-level node is further proposed to connect all fragment nodes by undirected edges, obtaining global molecular features from fragment embeddings. The FGTN model achieved an accuracy (ACC) of 0.861 and an area under the receiver operating characteristic curve (AUC) value of 0.914 on nonredundant blind tests, outperforming traditional fingerprint-based machine learning models and atom-based GCN model. The FGTN model can attribute toxic predictions to fragments, generating specific structural alerts for the positive compound. Moreover, FGTN may also have the capability to distinguish various chemical isomers. We believe that FGTN can be used as a reliable and effective tool for human reproductive toxicity prediction in contribution to the advancement of chemical safety assessment.

Stereoselective toxicity: Investigating the adverse effects of benzovindiflupyr on Xenopus laevis tadpoles.

The novel chiral fungicide benzovindiflupyr exerts adverse effects on aquatic organisms; however, its toxic mechanism and stereoselectivity remain largely unknown. The current study aimed to investigate the enantioselective ecotoxicity mechanism of benzovindiflupyr in Xenopus laevis tadpoles using a 28-day exposure experiment. Results of the acute toxicity assessment indicated that (1S,4R)- and (1R,4S)-benzovindiflupyr exhibited high toxicity, with (1S,4R)- demonstrating approximately 75 times greater toxicity than (1R,4S)-. Compared to the latter, (1S,4R)-benzovindiflupyr significantly affected the growth, movement behavior, and oxidative stress of X. laevis tadpoles. The integration of metabolomics and transcriptomics data revealed that (1S,4R)-benzovindiflupyr disrupted the glycine, serine, and threonine metabolic pathways by modulating the activities of key enzymes. This dysregulation resulted in aberrant carbohydrate utilization, antioxidant pathways, and structural protein synthesis and degradation. Molecular docking confirmed that (1S,4R)-benzovindiflupyr exhibited superior docking activity with key enzymes, potentially contributing to its stereoselective toxicity. This study offers novel molecular perspectives on the enantioselective ecotoxicity mechanism of benzovindiflupyr toward aquatic organisms and highlights potential target proteins implicated in metabolic disorders.

Comprehensive hepatotoxicity prediction: ensemble model integrating machine learning and deep learning.

Background: Chemicals may lead to acute liver injuries, posing a serious threat to human health. Achieving the precise safety profile of a compound is challenging due to the complex and expensive testing procedures. In silico approaches will aid in identifying the potential risk of drug candidates in the initial stage of drug development and thus mitigating the developmental cost. Methods: In current studies, QSAR models were developed for hepatotoxicity predictions using the ensemble strategy to integrate machine learning (ML) and deep learning (DL) algorithms using various molecular features. A large dataset of 2588 chemicals and drugs was randomly divided into training (80%) and test (20%) sets, followed by the training of individual base models using diverse machine learning or deep learning based on three different kinds of descriptors and fingerprints. Feature selection approaches were employed to proceed with model optimizations based on the model performance. Hybrid ensemble approaches were further utilized to determine the method with the best performance. Results: The voting ensemble classifier emerged as the optimal model, achieving an excellent prediction accuracy of 80.26%, AUC of 82.84%, and recall of over 93% followed by bagging and stacking ensemble classifiers method. The model was further verified by an external test set, internal 10-fold cross-validation, and rigorous benchmark training, exhibiting much better reliability than the published models. Conclusion: The proposed ensemble model offers a dependable assessment with a good performance for the prediction regarding the risk of chemicals and drugs to induce liver damage.

Removal of Moxifloxacin from Aqueous Solutions Using GO/Cr-MOFs.

The composite material, consisting of graphene oxide (GO) and chromium metal-organic frameworks (Cr-MOFs), was successfully synthesized by using a solvothermal method. The organic ligand employed was 2,5-dihydroxyterephthalic acid, while chromium acetate served as the source of the metal. The resulting material underwent characterization through Fourier transform infrared, scanning electron microscopy, and X-ray diffraction techniques. Subsequently, the adsorption capacity of the composite material toward moxifloxacin was evaluated. The results indicated a gradual increase in the moxifloxacin removal rate from GO/Cr-MOFs over time until reaching an equilibrium with a maximum removal rate of 90.4%. Additionally, it was observed that higher temperatures led to a decrease in the adsorption capacity. By incorporating 30 mg of GO/Cr-MOFs into a solution containing 40 ppm of moxifloxacin, the adsorption capacity could be maximized at 222.25 mg/g. Experimental data on MOF adsorption of moxifloxacin were analyzed using pseudo-first-order kinetics (PFO), pseudo-second-order kinetics (PSO), and Langmuir, Freundlich, and Temkin isotherm models for theoretical research purposes. Results showed that the PSO model exhibited a better correlation than the PFO model did. Furthermore, experimental data demonstrated good agreement with the Freundlich isothermal model, suggesting its effectiveness in accurately describing the adsorption process. Henceforth, it can be concluded that chemisorption plays a significant role in removing moxifloxacin by GO/Cr-MOFs. The van't Hoff equation analysis revealed an exothermic and spontaneous nature of moxifloxacin adsorption onto GO/Cr-MOFs. Compared to other materials, the GO/Cr-MOF composite exhibited high potential for applications such as drug removal or related fields.

Cascade internal electric field dominated carbon nitride decorated with gold nanoparticles as SERS substrate for thiram assay.

The development of valid chemical enhancement strategy with charge transfer (CT) for semiconductors has great scientific significance in surface-enhanced Raman scattering (SERS) technology. Herein, a phosphorus doped crystalline/amorphous polymeric carbon nitride (PCPCN) is fabricated by a facile molten salt method, and is employed as a SERS substrate for the first time. Upon the synergies of phosphatization and molten salt etching, PCPCN owns a cascaded internal electric field (IEF) due to the formation of p-n homojunction (interface-IEF) and crystalline/amorphous homojunction (bulk-IEF). The interface-IEF and bulk-IEF could effectively suppress the recombination of charge carriers and promote electron transfer between PCPCN and target methylene blue (MB), respectively. The strong CT interaction endows PCPCN substrate with superior SERS activity with an enhancement factor (EF) of 5.53 × 105. Au nanoparticles (Au NPs) are subsequently decorated on PCPCN to introduce electromagnetic enhancement for a better SERS response. The Au/PCPCN substrate allows to reliably detect trace crystal violet, as well as the thiram residue on cherry tomato. This work offers an integrated solution to enhance CT efficiency based on collaborative homojunction and internal electric field, and may inspire the design of novel semiconductor-based SERS substrates.

Dynamic changes in volatile profiles and bacterial communities during natural fermentation of Mei yu, traditional Chinese fermented fish pieces.

Microbial metabolism is important for the unique flavor formation of Mei yu, a kind of traditional Chinese fermented fish pieces. However, the interactive relationship between microorganisms and flavor components during fermentation is still unclear. In this study, electronic nose and headspace-solid-phase microextraction-gas chromatography-mass spectrometry analysis were performed to identify flavor components in Mei yu during the fermentation, and the absolute microbial quantification was conducted to identify the diversity and succession of microbial communities. During fermentation, there was an increase in the types of volatile compounds. Alcohols, aldehydes, aromatics and esters were the main flavor compounds and significantly increased in Mei yu, while hydrocarbon and aldehydes significantly decreased. The absolute abundances of Lactobacillus, Lactococcus and Weissella increased significantly after 3 days' fermentation, which were closely associated with the productions of 1-nonanol, 2-methoxy-4-vinylphenol, guaiacol, ethyl palmitate and ethyl caprylate that might though pathways related to fatty acid biosynthesis and amino acid metabolism. However, these genera were negatively correlated with the production of indole. Additionally, the total volatile basic nitrogen (TVB-N) levels of Mei yu fermented during 3 days were within the limits of 25 mg TVB-N/100 g fish, with the contents of free amino acids and lipoxygenase activities were significant lower than that of 4 days' fermentation. In view of food safety and flavor, it suggested that the natural fermented Mei yu at room temperature should be controlled within 3 days. This study highlights the application of absolute quantification to microbiome analysis in traditional fermented Mei yu and provides new insights into the roles of microorganisms in flavor formation during fermentation.

A dual analysis of bougie and stylet development trend and impact of Chinese regulations on medical devices innovation.

Medical device research and development are characterized by high costs, extended timelines, inherent risks, and the necessity for interdisciplinary knowledge and skills. It is significantly influenced by policies, making the understanding of medical device innovation both important and challenging. This paper takes a dual approach to analyze medical device innovation. We reviewed representative clinical product of bougie and stylet and summarized the common characteristics and trend of these product. Innovations in these products often involve adding depth markings, replacing material and design structure, enhancing visualization, deciding between reusable or disposable designs, and integrating multi-functional features. This underscores the delicate balance between technological advancements and medical costs for widespread clinical applicability. We explored the guiding role of policy in medical device innovation, emphasizing its impact through an analysis of medical device regulations and policies in China. By offering insights from the perspectives of medical device companies and regulators, this paper aims to elucidate the critical aspects of medical device innovation, assisting researchers in mitigating risks during product development.

PNBACE: an ensemble algorithm to predict the effects of mutations on protein-nucleic acid binding affinity.

BACKGROUND: Mutations occurring in nucleic acids or proteins may affect the binding affinities of protein-nucleic acid interactions. Although many efforts have been devoted to the impact of protein mutations, few computational studies have addressed the effect of nucleic acid mutations and explored whether the identical methodology could be applied to the prediction of binding affinity changes caused by these two mutation types. RESULTS: Here, we developed a generalized algorithm named PNBACE for both DNA and protein mutations. We first demonstrated that DNA mutations could induce varying degrees of changes in binding affinity from multiple perspectives. We then designed a group of energy-based topological features based on different energy networks, which were combined with our previous partition-based energy features to construct individual prediction models through feature selections. Furthermore, we created an ensemble model by integrating the outputs of individual models using a differential evolution algorithm. In addition to predicting the impact of single-point mutations, PNBACE could predict the influence of multiple-point mutations and identify mutations significantly reducing binding affinities. Extensive comparisons indicated that PNBACE largely performed better than existing methods on both regression and classification tasks. CONCLUSIONS: PNBACE is an effective method for estimating the binding affinity changes of protein-nucleic acid complexes induced by DNA or protein mutations, therefore improving our understanding of the interactions between proteins and DNA/RNA.

FGF20 modulates gut microbiota to mitigate dextran sodium sulfate-induced ulcerative colitis in mouse models.

Ulcerative colitis (UC), a prevalent form of inflammatory bowel disease (IBD), presents a significant clinical challenge due to the lack of optimal therapeutic strategies. Emerging evidence suggests that fibroblast growth factor 20 (FGF20) may play a crucial role in mitigating UC symptoms, though the mechanistic underpinnings remain elusive. In this study, a mouse model of UC was established using dextran sodium sulfate (DSS) to investigate the potential role of FGF20. Our findings revealed a marked reduction in FGF20 expression in the serum and colonic tissues of DSS-treated mice. Furthermore, FGF20 knockout did not exacerbate colonic damage in these mice. Conversely, overexpression of FGF20 via adeno-associated virus (AAV) significantly alleviated UC-associated symptoms. This alleviation was evidenced by attenuated intestinal shortening, mitigated weight loss, increased colonic goblet cell density and crypt formation, reduced inflammation severity and inflammatory cell infiltration, and enhanced expression of tight junction and mucin proteins. Moreover, FGF20 significantly ameliorated the dysbiosis of gut microbiota in DSS-treated mice by increasing the abundance of beneficial bacteria and decreasing the abundance of harmful bacteria. The beneficial effects of FGF20 were notably attenuated following gut microbiota depletion with an antibiotic regimen. Fecal microbiota transplantation experiments further supported the critical role of gut microbiota in mediating the effects of FGF20 on DSS-treated mice. In conclusion, these findings highlight the potential involvement of gut microbiota in the therapeutic effects of FGF20 in UC.

Biomimetic Colored Coating toward Robust Display under Hostile Conditions.

Structural colors particularly of the angle-independent category stemming from wavelength-dependent light scattering have aroused increasing interest due to their considerable applications spanning displays and sensors to detection. Nevertheless, these colors would be heavily altered and even disappear during practical applications, which is related with the variation of refractive index mismatch by liquid wetting/infiltrating. Inspired by bird feathers, we propose a simple deposition toward the coating with angle-independent structural color and superamphiphobicity. The coating is composed of ∼200 nm-sized channel-type structures between hollow silica and air nanostructures, exhibiting a robust sapphire blue color independent of intense liquid intrusion, which duplicates the characteristics of the back feather of Eastern Bluebird. A high color saturation and superamphiphobicity of the biomimetic coating are optimized by manipulating the coating parameters or adding black substances. Excellent durability under harsh conditions endows the coating with long-term service life in various extreme environments.

Cadmium causes cerebral mitochondrial dysfunction through regulating mitochondrial HSF1.

Mitochondria, as the powerhouse of the cell, play a vital role in maintaining cellular energy homeostasis and are known to be a primary target of cadmium (Cd) toxicity. The improper targeting of proteins to mitochondria can compromise the normal functions of the mitochondria. However, the precise mechanism by which protein localization contributes to the development of mitochondrial dysfunction induced by Cd is still not fully understood. For this research, Hy-Line white variety chicks (1-day-old) were used and equally distributed into 4 groups: the Control group (fed with a basic diet), the Cd35 group (basic diet with 35 mg/kg CdCl2), the Cd70 group (basic diet with 70 mg/kg CdCl2) and the Cd140 group (basic diet with 140 mg/kg CdCl2), respectively for 90 days. It was found that Cd caused the accumulation of heat shock factor 1 (HSF1) in the mitochondria, and the overexpression of HSF1 in the mitochondria led to mitochondrial dysfunction and neuronal damage. This process is due to the mitochondrial HSF1 (mtHSF1), causing mitochondrial fission through the upregulation of dynamin-related protein 1 (Drp1) content, while inhibiting oligomer formation of single-stranded DNA-binding protein 1 (SSBP1), resulting in the mitochondrial DNA (mtDNA) deletion. The findings unveil an unforeseen role of HSF1 in triggering mitochondrial dysfunction.

Supramolecular assemblies with aggregation-induced emission for in situ active imaging-guided photodynamic therapy of cancer cells.

Photodynamic therapy (PDT) has attracted widespread attention as a novel non-invasive anticancer approach. However, the diminished photosensitivity and limited oxygen exposure caused by the aggregation of traditional photosensitizers greatly impair its overall therapeutic efficacy. Herein, a series of water-soluble aggregation-induced emission luminogens (AIEgens) with triphenylamine as skeleton were synthesized and exhibited bright Near-infrared (NIR) emission and strong reactive oxygen species (ROS) generation. Through host-guest complexation between the multicharged triphenylamine units on AIEgens and cucurbit[10]uril (CB[10]) host molecule, supramolecular nanoassemblies were constructed and exhibited negligible phototoxicity to normal cells due to their limited oxygen contact. In contrast, the efficient release of AIEgens from nanoassemblies through competitive binding of overexpressed peptides in cancer cells with CB[10], enabled the full exploitation of the photosensitivity of AIEgens to produce highly efficient ROS, achieving selective ablation of cancer cells. Moreover, due to the restriction of intramolecular motion (RIM) upon anchored on organelle membranes through electrostatic interactions, the cationic AIEgens with weak fluorescence in physiological environment exhibited intense fluorescence emission, thus realizing imaging-guided PDT. This work may open up an avenue for the development of simple and feasible smart responsive nanomaterials for cancer treatment using supramolecular host-guest complexation strategy.

MOSDNET: A multi-omics classification framework using simplified multi-view deep discriminant representation learning and dynamic edge GCN with multi-task learning.

The integration of multi-omics data offers a robust approach to understanding the complexity of diseases by combining information from various biological levels, such as genomics, transcriptomics, proteomics, and metabolomics. This integrated approach is essential for a comprehensive understanding of disease mechanisms and for developing more effective diagnostic and therapeutic strategies. Nevertheless, most current methodologies fail to effectively extract both shared and specific representations from omics data. This study introduces MOSDNET, a multi-omics classification framework that effectively extracts shared and specific representations. This framework leverages Simplified Multi-view Deep Discriminant Representation Learning (S-MDDR) and Dynamic Edge GCN (DEGCN) to enhance the accuracy and efficiency of disease classification. Initially, MOSDNET utilizes S-MDDR to establish similarity and orthogonal constraints for extracting these representations, which are then concatenated to integrate the multi-omics data. Subsequently, MOSDNET constructs a comprehensive view of the sample data by employing patient similarity networks. By incorporating similarity networks into DEGCN, MOSDNET learns intricate network structures and node representations, which enables superior classification outcomes. MOSDNET is trained through a multitask learning approach, effectively leveraging the complementary knowledge from both the data integration and classification components. After conducting extensive comparative experiments, we have conclusively demonstrated that MOSDNET outperforms leading state-of-the-art multi-omics classification models in terms of classification accuracy. Simultaneously, we employ MOSDNET to identify pivotal biomarkers within the multi-omics data, providing insights into disease etiology and progression.