Single Atom Ag Bonding Between PF3T Nanocluster and TiO2 Leads the Ultra-Stable Visible-Light-Driven Photocatalytic H2 Production.

Atomic Ag cluster bonding is employed to reinforce the interface between PF3T nano-cluster and TiO2 nanoparticle. With an optimized Ag loading (Ag/TiO2 = 0.5 wt%), the Ag atoms will uniformly disperse on TiO2 thus generating a high density of intermediate states in the band gap to form the electron channel between the terthiophene group of PF3T and the TiO2 in the hybrid composite (denoted as T@Ag05-P). The former expands the photon absorption band width and the latter facilitates the core-hole splitting by injecting the photon excited electron (from the excitons in PF3T) into the conduction band (CB) of TiO2. These characteristics enable the high efficiency of H2 production to 16 580 µmol h-1 g-1 and photocatalysis stability without degradation under visible light exposure for 96 h. Compared to that of hybrid material without Ag bonding (TiO2@PF3T), the H2 production yield and stability are improved by 4.1 and 18.2-fold which shows the best performance among existing materials in similar component combination and interfacial reinforcement. The unique bonding method offers a new prospect to accelerate the development of photocatalytic hydrogen production technologies.

Recent research progress on tumour-specific responsive hydrogels.

Most existing hydrogels, even recently developed injectable hydrogels that undergo a reversible sol-gel phase transition in response to external stimuli, are designed to gel immediately before or after implantation/injection to prevent the free diffusion of materials and drugs; however, the property of immediate gelation leads to a very weak tumour-targeting ability, limiting their application in anticancer therapy. Therefore, the development of tumour-specific responsive hydrogels for anticancer therapy is imperative because tumour-specific responses improve their tumour-targeting efficacy, increase therapeutic effects, and decrease toxicity and side effects. In this review, we introduce the following three types of tumour-responsive hydrogels: (1) hydrogels that gel specifically at the tumour site; (2) hydrogels that decompose specifically at the tumour site; and (3) hydrogels that react specifically with tumours. For each type, their compositions, the mechanisms of tumour-specific responsiveness and their applications in anticancer treatment are comprehensively discussed.

Genetically Engineered Membrane-Coated Nanoparticles for Enhanced Prostate-Specific Membrane Antigen Targeting and Ferroptosis Treatment of Castration-Resistant Prostate Cancer.

Conventional androgen deprivation therapy (ADT) targets the androgen receptor (AR) inhibiting prostate cancer (PCa) progression; however, it can eventually lead to recurrence as castration-resistant PCa (CRPC), which has high mortality rates and lacks effective treatment modalities. The study confirms the presence of high glutathione peroxidase 4 (GPX4) expression, a key regulator of ferroptosis (i.e., iron-dependent program cell death) in CRPC cells. Therefore, inducing ferroptosis in CRPC cells might be an effective therapeutic modality for CRPC. However, nonspecific uptake of ferroptosis inducers can result in undesirable cytotoxicity in major organs. Thus, to precisely induce ferroptosis in CRPC cells, a genetic engineering strategy is proposed to embed a prostate-specific membrane antigen (PSMA)-targeting antibody fragment (gy1) in the macrophage membrane, which is then coated onto mesoporous polydopamine (MPDA) nanoparticles to produce a biomimetic nanoplatform. The results indicate that the membrane-coated nanoparticles (MNPs) exhibit high specificity and affinity toward CRPC cells. On further encapsulation with the ferroptosis inducers RSL3 and iron ions, MPDA/Fe/RSL3@M-gy1 demonstrates superior synergistic effects in highly targeted ferroptosis therapy eliciting significant therapeutic efficacy against CRPC tumor growth and bone metastasis without increased cytotoxicity. In conclusion, a new therapeutic strategy is reported for the PSMA-specific, CRPC-targeting platform for ferroptosis induction with increased efficacy and safety.

Progressive encephalomyelitis with rigidity and myoclonus: a pediatric case report and literature review.

BACKGROUND: Progressive encephalomyelitis with rigidity and myoclonus (PERM) is a rare and life-threatening autoimmune disease of the central nervous system. So far, only ten cases of PERM have been reported in children worldwide, including the one in this study. CASE PRESENTATION: We report a case of an 11-year-old boy with PERM with an initial presentation of abdominal pain, skin itching, dysuria, urinary retention, truncal and limb rigidity, spasms of the trunk and limbs during sleep, deep and peripheral sensory disturbances, and dysphagia. A tissue-based assay using peripheral blood was positive, demonstrated by fluorescent staining of mouse cerebellar sections. He showed gradual and persistent clinical improvement after immunotherapy with intravenous immunoglobulin, steroids, plasmapheresis and rituximab. CONCLUSIONS: We summarized the diagnosis and treatment of a patient with PERM and performed a literature review of pediatric PERM to raise awareness among pediatric neurologists. A better comprehension of this disease is required to improve its early diagnosis, treatment, and prognosis.

Zinc oxide nanoparticles induces cell death and consequently leading to incomplete neural tube closure through oxidative stress during embryogenesis.

The implementation of Zinc oxide nanoparticles (ZnO NPs) raises concerns regarding their potential toxic effects on human health. Although more and more researches have confirmed the toxic effects of ZnO NPs, limited attention has been given to their impact on the early embryonic nervous system. This study aimed to explore the impact of exposure to ZnO NPs on early neurogenesis and explore its underlying mechanisms. We conducted experiments here to confirm the hypothesis that exposure to ZnO NPs causes neural tube defects in early embryonic development. We first used mouse and chicken embryos to confirm that ZnO NPs and the Zn2+ they release are able to penetrate the placental barrier, influence fetal growth and result in incomplete neural tube closure. Using SH-SY5Y cells, we determined that ZnO NPs-induced incomplete neural tube closure was caused by activation of various cell death modes, including ferroptosis, apoptosis and autophagy. Moreover, dissolved Zn2+ played a role in triggering widespread cell death. ZnO NPs were accumulated within mitochondria after entering cells, damaging mitochondrial function and resulting in the over production of reactive oxygen species, ultimately inducing cellular oxidative stress. The N-acetylcysteine (NAC) exhibits significant efficacy in mitigating cellular oxidative stress, thereby alleviating the cytotoxicity and neurotoxicity brought about by ZnO NPs. These findings indicated that the exposure of ZnO NPs in early embryonic development can induce cell death through oxidative stress, resulting in a reduced number of cells involved in early neural tube closure and ultimately resulting in incomplete neural tube closure during embryo development. The findings of this study could raise public awareness regarding the potential risks associated with the exposure and use of ZnO NPs in early pregnancy.

High-fidelity and high-speed wavefront shaping by leveraging complex media.

High-precision light manipulation is crucial for delivering information through complex media. However, existing spatial light modulation devices face a fundamental speed-fidelity tradeoff. Digital micromirror devices have emerged as a promising candidate for high-speed wavefront shaping but at the cost of compromised fidelity due to the limited control degrees of freedom. Here, we leverage the sparse-to-random transformation through complex media to overcome the dimensionality limitation of spatial light modulation devices. We demonstrate that pattern compression by sparsity-constrained wavefront optimization allows sparse and robust wavefront representations in complex media, improving the projection fidelity without sacrificing frame rate, hardware complexity, or optimization time. Our method is generalizable to different pattern types and complex media, supporting consistent performance with up to 89% and 126% improvements in projection accuracy and speckle suppression, respectively. The proposed optimization framework could enable high-fidelity high-speed wavefront shaping through different scattering media and platforms without changes to the existing holographic setups, facilitating a wide range of physics and real-world applications.

Evaluating three internal fixation techniques for Pauwels III femoral neck fractures via finite element analysis.

The selection of implants for fixing unstable femoral neck fractures (FNF) remains contentious. This study employs finite element analysis to examine the biomechanics of treating Pauwels type III femoral neck fractures using cannulated compression screws (3CS), biplane double-supported screw fixation (BDSF), and the femoral neck system (FNS). A three-dimensional model of the proximal femur was developed using computed tomography scans. Fracture models of the femoral neck were created with 3CS, BDSF, and FNS fixations. Von Mises stress on the proximal femur, fracture ends, internal fixators, and model displacements were assessed and compared across the three fixation methods (3CS, BDSF, and FNS) during the heel strike of normal walking. The maximum Von Mises stress in the proximal fragment was significantly higher with 3CS fixation compared to BDSF and FNS fixations (120.45 MPa vs. 82.44 MPa and 84.54 MPa, respectively). Regarding Von Mises stress distribution at the fracture ends, the highest stress in the 3CS group was 57.32 MPa, while BDSF and FNS groups showed 51.39 MPa and 49.23 MPa, respectively. Concerning implant stress, the FNS model exhibited greater Von Mises stress compared to the 3CS and BDSF models (236.67 MPa vs. 134.86 MPa and 140.69 MPa, respectively). Moreover, BDSF displayed slightly lower total displacement than 3CS fixation (7.19 mm vs. 7.66 mm), but slightly higher displacement than FNS (7.19 mm vs. 7.03 mm). This study concludes that BDSF outperforms 3CS fixation in terms of biomechanical efficacy and demonstrates similar performance to the FNS approach. As a result, BDSF stands as a dependable alternative for treating Pauwels type III femoral neck fractures.

The emerging role of herbal medicines in cancer by interfering with post-translational modification.

SIGNIFICANCE: Herbal medicines demonstrate clinical promise for cancer treatment. Protein post translational modifications (PTMs) regulate tumorigenesis and cancer progression. While PTMs contributing to cancer are well-studied, the precise mechanisms and defined targets of herbal medicines on PTM-associated carcinogenesis remain unclear. Hence, comprehensively understanding how PTMs regulate cancer hallmarks is crucial to elucidate the pharmacological mechanisms of herbal medicines for cancer treatment. RECENT ADVANCES: Advanced development in highly sensitive mass spectrometry (MS)-based techniques has helped utilize PTM-focused studies on cancers. Accumulating evidence has been achieved in laboratory to ascertain the biological mechanism of herbal medicines in cancer therapy. Implication of the strong association between cancer and PTM makes new perspective to comprehend the intricate dialogues between herbal medicines and cellular contexts. CRITICAL ISSUES: Complex components of herbal medicines limit the benefits of herbal-based cancer therapies. In this review, we address that PTMs add a layer of proteomic complexity to the cancer through altering the protein structure, expression, function, and localization. Elaborating PTM implicated in cell signaling, apoptosis and transcriptional regulation function, and the possible cellular signaling, have provided important information about the mechanism of many herbal therapies. Continued optimization of proteomic strategies for PTM analysis in herbal medicines are also discussed. FUTURE DIRECTIONS: Rigorous evaluations of herbal medicines and the chemoproteomic strategies are necessary to explore the aberrant regulation of PTM dynamics contributed to the cancer development and herbal associated pharmacological issues. These efforts will eventually help develop more herbal drugs as modern therapeutic agents.

BI-7273, a BRD9 inhibitor, reduces lipid accumulation by downregulating the AKT/mTOR/SREBP1 signaling pathway.

Increases in de novo lipogenesis that disturb lipid homeostasis and caused lipid accumulation are a major cause of NAFLD and obesity. SREBP1 is a crucial regulatory factor controlling the expression of rate-limiting enzymes of lipid synthesis. A reduction in SREBP1expression can reduce lipid accumulation. Thus, we utilized an SREBP1-luciferase-KI HEK293 cell line constructed by our lab to screen 200 kinds of epigenetic drugs for their ability to downregulate SREBP1expression. BI-7273, an inhibitor of bromodomain-containing protein 9 (BRD9), was screened and found to decrease SREBP1 expression. What is more, BI-7273 has been confirmed that it could reduce lipid accumulation in HepG2 cells by BODIPY staining, and significantly decrease the protein expression of SREBP1 and FASN. To explore the potential mechanism BI-7273 reducing lipid accumulation, RNA sequencing (RNA-seq) was performed and demonstrated that BI-7273 reduced lipid accumulation by downregulating the AKT/mTOR/SREBP1 pathway in vitro. Finally, these results were verified in NAFLD and obesity mouse model induced by high fat diet (HFD). The results indicated that BI-7273 could decrease mouse body weight and improve insulin sensitivity, but also exhibited a strong negative correlation with serum lipid levels, and also demonstrated that BI-7273 reduced lipid accumulation via AKT/mTOR/SREBP1 pathway in vivo. In conclusion, our results revealed that BI-7273 decreases lipid accumulation by downregulating the AKT/mTOR/SREBP1 pathway in vivo and in vitro. This is the first report demonstrating the protective effect of this BRD9 inhibitor against NAFLD and obesity. BRD9 may be a novel target for the discovery of effective drugs to treat lipid metabolism disorders.

The Quantitative Evaluation of Automatic Segmentation in Lumbar Magnetic Resonance Images.

OBJECTIVE: This study aims to overcome challenges in lumbar spine imaging, particularly lumbar spinal stenosis, by developing an automated segmentation model using advanced techniques. Traditional manual measurement and lesion detection methods are limited by subjectivity and inefficiency. The objective is to create an accurate and automated segmentation model that identifies anatomical structures in lumbar spine magnetic resonance imaging scans. METHODS: Leveraging a dataset of 539 lumbar spinal stenosis patients, the study utilizes the residual U-Net for semantic segmentation in sagittal and axial lumbar spine magnetic resonance images. The model, trained to recognize specific tissue categories, employs a geometry algorithm for anatomical structure quantification. Validation metrics, like Intersection over Union (IOU) and Dice coefficients, validate the residual U-Net's segmentation accuracy. A novel rotation matrix approach is introduced for detecting bulging discs, assessing dural sac compression, and measuring yellow ligament thickness. RESULTS: The residual U-Net achieves high precision in segmenting lumbar spine structures, with mean IOU values ranging from 0.82 to 0.93 across various tissue categories and views. The automated quantification system provides measurements for intervertebral disc dimensions, dural sac diameter, yellow ligament thickness, and disc hydration. Consistency between training and testing datasets assures the robustness of automated measurements. CONCLUSION: Automated lumbar spine segmentation with residual U-Net and deep learning exhibits high precision in identifying anatomical structures, facilitating efficient quantification in lumbar spinal stenosis cases. The introduction of a rotation matrix enhances lesion detection, promising improved diagnostic accuracy, and supporting treatment decisions for lumbar spinal stenosis patients.

Imbalance of mitochondrial quality control regulated by STING and PINK1 affects cyfluthrin-induced neuroinflammation.

Nervous system diseases are a global health problem, and with the increase in the elderly population around the world, their incidence will also increase. Harmful substances in the environment are closely related to the occurrence of nervous system diseases. China is a large agricultural country, and thus the insecticide cyfluthrin has been widely used. Cyfluthrin is neurotoxic, but the mechanism of this injury is not clear. Inflammation is an important mechanism for the occurrence of nervous system diseases. Mitochondria are the main regulators of the inflammatory response, and various cellular responses, including autophagy, directly affect the regulation of inflammatory processes. Mitochondrial damage is related to mitochondrial quality control (MQC) and PTEN-induced kinase 1 (PINK1). As an anti-inflammatory factor, stimulator of interferon genes (STING) participates in the regulation of inflammation. However, the relationship between STING and mitochondria in the process of cyfluthrin-induced nerve injury is unclear. This study established in vivo and in vitro models of cyfluthrin exposure to explore the role of MQC and to clarify the mechanism of action of STING and PINK1. Our results showed that cyfluthrin can increase the reactive oxygen species (ROS) level, resulting in mitochondrial damage and inflammation. In this process, an imbalance in MQC leads to the aggravation of mitochondrial damage, and high STING expression drives the occurrence of inflammation. We established a differential expression model of STING and PINK1 to further determine the underlying mechanism and found that the interaction between STING and PINK1 regulates MQC to affect the levels of mitochondrial damage and inflammation. When STING and PINK1 expression are downregulated, mitochondrial damage and STING-induced inflammation are significantly alleviated. In summary, a synergistic effect between STING and PINK1 on cyfluthrin-induced neuroinflammation may exist, which leads to an imbalance in MQC by inhibiting mitochondrial biogenesis and division/fusion, and PINK1 can reduce STING-driven inflammation.

A novel semi-flexible coaxial nozzle based on fluid dynamics effects and its self-centering performance study.

Coaxial nozzles are widely used to produce fibers with core-shell structures. However, conventional coaxial nozzles cannot adjust the coaxiality of the inner and outer needles in real-time during the fiber production process, resulting in uneven fiber wall thickness and poor quality. Therefore, we proposed an innovative semi-flexible coaxial nozzle with a dynamic self-centering function. This new design addresses the challenge of ensuring the coaxiality of the inner and outer needles of the coaxial nozzle. First, based on the principles of fluid dynamics and fluid-structure interaction, a self-centering model for a coaxial nozzle is established. Second, the influence of external fluid velocity and inner needle elastic modulus on the centering time and coaxiality error is analyzed by finite element simulation. Finally, the self-centering performance of the coaxial nozzle is verified by observing the coaxial extrusion process online and measuring the wall thickness of the formed hollow fiber. The results showed that the coaxiality error increased with the increase of Young's modulus E and decreased with the increase of flow velocity. The centering time required for the inner needle to achieve force balance decreases with the increase of Young's modulus ( E ) and fluid velocity ( v f ). The nozzle exhibits significant self-centering performance, dynamically reducing the initial coaxiality error from 380 to 60 µm within 26 s. Additionally, it can mitigate the coaxiality error caused by manufacturing and assembly precision, effectively controlling them within 8 µm. Our research provides valuable references and solutions for addressing issues such as uneven fiber wall thickness caused by coaxiality errors.

De novo transcriptome profiling reveals the patterns of gene expression in plum fruits with bud mutations.

Bud mutation is a common technique for plant breeding and can provide a large number of breeding materials. Through traditional breeding methods, we obtained a plum plant with bud mutations (named "By") from an original plum variety (named "B"). The ripening period of "By" fruit was longer than that of "B" fruit, and its taste was better. In order to understand the characteristics of these plum varieties, we used transcriptome analysis and compared the gene expression patterns in fruits from the two cultivars. Subsequently, we identified the biological processes regulated by the differentially expressed genes (DEGs). Gene ontology (GO) analysis revealed that these DEGs were highly enriched for "single-organism cellular process" and "transferase activity". KEGG analysis demonstrated that the main pathways affected by the bud mutations were plant hormone signal transduction, starch and sucrose metabolism. The IAA, CKX, ARF, and SnRK2 genes were identified as the key regulators of plant hormone signal transduction. Meanwhile, TPP, the beta-glucosidase (EC3.2.1.21) gene, and UGT72E were identified as candidate DEGs affecting secondary metabolite synthesis. The transcriptome sequencing (RNA-seq) data were also validated using RT-qPCR experiments. The transcriptome analysis demonstrated that plant hormones play a significant role in extending the maturity period of plum fruit, with IAA, CKX, ARF, and SnRK2 serving as the key regulators of this process. Further, TPP, beta-glucosidase (EC3.2.1.21), and UGT72E appeared to mediate the synthesis of various soluble secondary metabolites, contributing to the aroma of plum fruits. The expression of BAG6 was upregulated in "B" as the fruit matured, but it was downregulated in "By". This indicated that "B" may have stronger resistance, especially fungal resistance. Supplementary Information: The online version contains supplementary material available at 10.1007/s12298-024-01472-3.

Kinetic Monte Carlo simulations on electroforming in nanomanipulated conductive bridge random access memory devices.

Conductive bridge random access memory (CBRAM) devices exhibit great potential as the next-generation nonvolatile memory devices. However, they suffer from two major disadvantages, namely relatively high power consumption and large cycle-to-cycle and device-to-device variations, which hinder their more extensive commercialization. To learn how to enhance their device performance, kinetic Monte Carlo (KMC) simulations were employed to illustrate the variation of electroforming processes in nanomanipulated CBRAM devices by introducing an ion-blocking layer with scalable nanopores and tuning the microstructures of dielectric layers. Both the size of nanopores and the inhomogeneity of dielectric layers have significant impacts on the forming processes of conductive filaments. The dielectric layer with a high-content loose texture plus the scalable nanopore-containing ion-blocking layer leads to the formation of size-controlled and uniform filaments, which remarkably contributes to miniaturizable and stable CBRAM devices. Our study provides insights into nanomanipulation strategies to realize high-performance CBRAM devices, still awaiting future experimental confirmation.

Metatranscriptomics-guided genome-scale metabolic reconstruction reveals the carbon flux and trophic interaction in methanogenic communities.

BACKGROUND: Despite rapid advances in genomic-resolved metagenomics and remarkable explosion of metagenome-assembled genomes (MAGs), the function of uncultivated anaerobic lineages and their interactions in carbon mineralization remain largely uncertain, which has profound implications in biotechnology and biogeochemistry. RESULTS: In this study, we combined long-read sequencing and metatranscriptomics-guided metabolic reconstruction to provide a genome-wide perspective of carbon mineralization flow from polymers to methane in an anaerobic bioreactor. Our results showed that incorporating long reads resulted in a substantial improvement in the quality of metagenomic assemblies, enabling the effective recovery of 132 high-quality genomes meeting stringent criteria of minimum information about a metagenome-assembled genome (MIMAG). In addition, hybrid assembly obtained 51% more prokaryotic genes in comparison to the short-read-only assembly. Metatranscriptomics-guided metabolic reconstruction unveiled the remarkable metabolic flexibility of several novel Bacteroidales-affiliated bacteria and populations from Mesotoga sp. in scavenging amino acids and sugars. In addition to recovering two circular genomes of previously known but fragmented syntrophic bacteria, two newly identified bacteria within Syntrophales were found to be highly engaged in fatty acid oxidation through syntrophic relationships with dominant methanogens Methanoregulaceae bin.74 and Methanothrix sp. bin.206. The activity of bin.206 preferring acetate as substrate exceeded that of bin.74 with increasing loading, reinforcing the substrate determinantal role. CONCLUSION: Overall, our study uncovered some key active anaerobic lineages and their metabolic functions in this complex anaerobic ecosystem, offering a framework for understanding carbon transformations in anaerobic digestion. These findings advance the understanding of metabolic activities and trophic interactions between anaerobic guilds, providing foundational insights into carbon flux within both engineered and natural ecosystems. Video Abstract.

RiboDiffusion: tertiary structure-based RNA inverse folding with generative diffusion models.

MOTIVATION: RNA design shows growing applications in synthetic biology and therapeutics, driven by the crucial role of RNA in various biological processes. A fundamental challenge is to find functional RNA sequences that satisfy given structural constraints, known as the inverse folding problem. Computational approaches have emerged to address this problem based on secondary structures. However, designing RNA sequences directly from 3D structures is still challenging, due to the scarcity of data, the nonunique structure-sequence mapping, and the flexibility of RNA conformation. RESULTS: In this study, we propose RiboDiffusion, a generative diffusion model for RNA inverse folding that can learn the conditional distribution of RNA sequences given 3D backbone structures. Our model consists of a graph neural network-based structure module and a Transformer-based sequence module, which iteratively transforms random sequences into desired sequences. By tuning the sampling weight, our model allows for a trade-off between sequence recovery and diversity to explore more candidates. We split test sets based on RNA clustering with different cut-offs for sequence or structure similarity. Our model outperforms baselines in sequence recovery, with an average relative improvement of 11% for sequence similarity splits and 16% for structure similarity splits. Moreover, RiboDiffusion performs consistently well across various RNA length categories and RNA types. We also apply in silico folding to validate whether the generated sequences can fold into the given 3D RNA backbones. Our method could be a powerful tool for RNA design that explores the vast sequence space and finds novel solutions to 3D structural constraints. AVAILABILITY AND IMPLEMENTATION: The source code is available at https://github.com/ml4bio/RiboDiffusion.

Identification of chronic non-atrophic gastritis and intestinal metaplasia stages in the Correa's cascade through machine learning analyses of SERS spectral signature of non-invasively-collected human gastric fluid samples.

The progression of gastric cancer involves a complex multi-stage process, with gastroscopy and biopsy being the standard procedures for diagnosing gastric diseases. This study introduces an innovative non-invasive approach to differentiate gastric disease stage using gastric fluid samples through machine-learning-assisted surface-enhanced Raman spectroscopy (SERS). This method effectively identifies different stages of gastric lesions. The XGBoost algorithm demonstrates the highest accuracy of 96.88% and 91.67%, respectively, in distinguishing chronic non-atrophic gastritis from intestinal metaplasia and different subtypes of gastritis (mild, moderate, and severe). Through blinded testing validation, the model can achieve more than 80% accuracy. These findings offer new possibilities for rapid, cost-effective, and minimally invasive diagnosis of gastric diseases.

Strategy to Efficient Photodynamic Therapy for Antibacterium: Donor-Acceptor Structure in Hydrogen-Bonded Organic Framework.

While the construction of a donor-acceptor (D-A) structure has gained great attention across various scientific disciplines, such structures are seldomly reported within the field of hydrogen-bonded organic frameworks (HOFs). Herein, a D-A based HOF is synthesized, where the adjacent D-A pairs are connected by hydrogen bonds instead of the conventionally employed covalent bonds. This structural feature imparts material with a reduced energy gap between excited state and triplet state, thereby facilitating the intersystem crossing (ISC) and boosting the generation rate of single oxygen (quantum yield = 0.98). Consequently, the resulting material shows high performance for antimicrobial photodynamic therapy (PDT). The impact of D-A moiety is evident when comparing this finding to a parallel study conducted on an isoreticular HOF without a D-A structure. The study presented here provides in-depth insights into the photophysical properties of D-A pair in a hydrogen-bonded network, opening a new avenue to the design of innovative materials for efficient PDT.

ifDEEPre: large protein language-based deep learning enables interpretable and fast predictions of enzyme commission numbers.

Accurate understanding of the biological functions of enzymes is vital for various tasks in both pathologies and industrial biotechnology. However, the existing methods are usually not fast enough and lack explanations on the prediction results, which severely limits their real-world applications. Following our previous work, DEEPre, we propose a new interpretable and fast version (ifDEEPre) by designing novel self-guided attention and incorporating biological knowledge learned via large protein language models to accurately predict the commission numbers of enzymes and confirm their functions. Novel self-guided attention is designed to optimize the unique contributions of representations, automatically detecting key protein motifs to provide meaningful interpretations. Representations learned from raw protein sequences are strictly screened to improve the running speed of the framework, 50 times faster than DEEPre while requiring 12.89 times smaller storage space. Large language modules are incorporated to learn physical properties from hundreds of millions of proteins, extending biological knowledge of the whole network. Extensive experiments indicate that ifDEEPre outperforms all the current methods, achieving more than 14.22% larger F1-score on the NEW dataset. Furthermore, the trained ifDEEPre models accurately capture multi-level protein biological patterns and infer evolutionary trends of enzymes by taking only raw sequences without label information. Meanwhile, ifDEEPre predicts the evolutionary relationships between different yeast sub-species, which are highly consistent with the ground truth. Case studies indicate that ifDEEPre can detect key amino acid motifs, which have important implications for designing novel enzymes. A web server running ifDEEPre is available at https://proj.cse.cuhk.edu.hk/aihlab/ifdeepre/ to provide convenient services to the public. Meanwhile, ifDEEPre is freely available on GitHub at https://github.com/ml4bio/ifDEEPre/.

Natural aromatic extract of black tea improved the water retention of pork meat batter.

The effect of varying proportions (w/w) of natural aromatic extract of black tea (NAEBT) with pre-emulsification on the water-holding capacity (WHC) of pork meat batter was investigated. The addition of NAEBT significantly reduced the cooking loss (CL) of pork meat batter from 23.95 % to 18.30 % (P < 0.05). Furthermore, NAEBT with pre-emulsification significantly improved the color stability and increased the springiness (P < 0.05). The results of TBARS and carbonyls indicated that NAEBT with pre-emulsification significantly alleviated oxidative damage to proteins (P < 0.05), resulting in an increased level of ß-sheet (P < 0.05), as confirmed by FT-IR analysis. As a result, the water mobility of pork meat batter was restricted (P < 0.05), resulting in an increase in the energy storage modulus (P < 0.05) and a decrease in the pore size. In summary, the WHC of pork meat batter was improved by the antioxidant effect of the NAEBT.