Harnessing cerium-based biomaterials for the treatment of bone diseases.

Bone, an actively metabolic organ, undergoes constant remodeling throughout life. Disturbances in the bone microenvironment can be responsible for pathologically bone diseases such as periodontitis, osteoarthritis, rheumatoid arthritis and osteoporosis. Conventional bone tissue biomaterials are not adequately adapted to complex bone microenvironment. Therefore, there is an urgent clinical need to find an effective strategy to improve the status quo. In recent years, nanotechnology has caused a revolution in biomedicine. Cerium(III, IV) oxide, as an important member of metal oxide nanomaterials, has dual redox properties through reversible binding with oxygen atoms, which continuously cycle between Ce(III) and Ce(IV). Due to its special physicochemical properties, cerium(III, IV) oxide has received widespread attention as a versatile nanomaterial, especially in bone diseases. This review describes the characteristics of bone microenvironment. The enzyme-like properties and biosafety of cerium(III, IV) oxide are also emphasized. Meanwhile, we summarizes controllable synthesis of cerium(III, IV) oxide with different nanostructural morphologies. Following resolution of synthetic principles of cerium(III, IV) oxide, a variety of tailored cerium-based biomaterials have been widely developed, including bioactive glasses, scaffolds, nanomembranes, coatings, and nanocomposites. Furthermore, we highlight the latest advances in cerium-based biomaterials for inflammatory and metabolic bone diseases and bone-related tumors. Tailored cerium-based biomaterials have already demonstrated their value in disease prevention, diagnosis (imaging and biosensors) and treatment. Therefore, it is important to assist in bone disease management by clarifying tailored properties of cerium(III, IV) oxide in order to promote the use of cerium-based biomaterials in the future clinical setting. STATEMENT OF SIGNIFICANCE: In this review, we focused on the promising of cerium-based biomaterials for bone diseases. We reviewed the key role of bone microenvironment in bone diseases and the main biological activities of cerium(III, IV) oxide. By setting different synthesis conditions, cerium(III, IV) oxide nanostructures with different morphologies can be controlled. Meanwhile, tailored cerium-based biomaterials can serve as a versatile toolbox (e.g., bioactive glasses, scaffolds, nanofibrous membranes, coatings, and nanocomposites). Then, the latest research advances based on cerium-based biomaterials for the treatment of bone diseases were also highlighted. Most importantly, we analyzed the perspectives and challenges of cerium-based biomaterials. In future perspectives, this insight has given rise to a cascade of cerium-based biomaterial strategies, including disease prevention, diagnosis (imaging and biosensors) and treatment.

Response mechanisms of different Saccharomyces cerevisiae strains to succinic acid.

BACKGROUND: The production of succinic acid (SA) from biomass has attracted worldwide interest. Saccharomyces cerevisiae is preferred for SA production due to its strong tolerance to low pH conditions, ease of genetic manipulation, and extensive application in industrial processes. However, when compared with bacterial producers, the SA titers and productivities achieved by engineered S. cerevisiae strains were relatively low. To develop efficient SA-producing strains, it's necessary to clearly understand how S. cerevisiae cells respond to SA. RESULTS: In this study, we cultivated five S. cerevisiae strains with different genetic backgrounds under different concentrations of SA. Among them, KF7 and NBRC1958 demonstrated high tolerance to SA, whereas NBRC2018 displayed the least tolerance. Therefore, these three strains were chosen to study how S. cerevisiae responds to SA. Under a concentration of 20 g/L SA, only a few differentially expressed genes were observed in three strains. At the higher concentration of 60 g/L SA, the response mechanisms of the three strains diverged notably. For KF7, genes involved in the glyoxylate cycle were significantly downregulated, whereas genes involved in gluconeogenesis, the pentose phosphate pathway, protein folding, and meiosis were significantly upregulated. For NBRC1958, genes related to the biosynthesis of vitamin B6, thiamin, and purine were significantly downregulated, whereas genes related to protein folding, toxin efflux, and cell wall remodeling were significantly upregulated. For NBRC2018, there was a significant upregulation of genes connected to the pentose phosphate pathway, gluconeogenesis, fatty acid utilization, and protein folding, except for the small heat shock protein gene HSP26. Overexpression of HSP26 and HSP42 notably enhanced the cell growth of NBRC1958 both in the presence and absence of SA. CONCLUSIONS: The inherent activities of small heat shock proteins, the levels of acetyl-CoA and the strains' potential capacity to consume SA all seem to affect the responses and tolerances of S. cerevisiae strains to SA. These factors should be taken into consideration when choosing host strains for SA production. This study provides a theoretical basis and identifies potential host strains for the development of robust and efficient SA-producing strains.

Unintentional Injection Into the Retrodural Space of Okada During Transforaminal Epidural Steroid Injection.

BACKGROUND: Transforaminal epidural steroid injection (TFESI) is commonly used for radicular pain, but can lead to an unintentional injection into the retrodural Space of Okada (RSO), an extradural space located dorsal to the ligamentum flavum, instead of the epidural space. OBJECTIVES: To determine the prevalence and describe the fluoroscopic imaging features of an unintentional injection into the RSO during a TFESI and to review the history of injections into the RSO. STUDY DESIGN: Observational study and original research. SETTING: This work was conducted at Jeju National University School of Medicine, Jeju, Republic of Korea. METHODS: A total of 5,429 lumbar TFESIs performed from the September 1, 2018 through October 31, 2021 were analyzed for unintentional RSO injections using fluoroscopic-guided contrast medium patterns. RESULTS: The rate of unintentional injection into the RSO was 0.20% (11 incidents). Contrast medium patterns in the RSO had a sigmoid or ovoid shape confined to the affected facet joint, or a butterfly-shaped pattern extending into the contralateral facet joint, but rarely extending beyond the upper or lower level. LIMITATION: The rarity of unintentional injection into the RSO prevented a randomized controlled study design. CONCLUSIONS: Careful fluoroscopic examination of contrast medium patterns during lumbar TFESI is crucial to identify needle placement in the RSO. If detected, the procedure can be corrected by slightly advancing the needle into the foramen.

Proteomic profile of tissue-derived extracellular vesicles from benign odontogenic lesions.

BACKGROUND: Benign odontogenic lesions (BOLs) can cause severe jaw bone defects and compromise the quality of life of patients. Extracellular vesicles (EVs) are well-established and versatile players in mediating pathophysiological events. EVs in the interstitial space (tissue-derived EVs or Ti-EVs) possess higher specificity and sensitivity in disease-related biomarker discovery. However, the role of Ti-EV-loaded proteins in mediating the development of BOLs has remained untapped. Herein, we aim to explore the contribution of Ti-EV-loaded proteins to the development of BOLs. METHODS: Samples were obtained from 3 with dental follicle, 3 with dentigerous cyst (DC), 7 with odontogenic keratocyst (OKC), and 3 patients with ameloblastoma (AM). Tissue-derived EVs were then extracted, purified, and validated using ultracentrifugation, transmission electron microscopy, and western blotting. Proteins from Ti-EVs were analyzed using LC-ESI tandem mass spectroscopy and differentially expressed proteins were screened, which was then validated by immunohistochemistry and immunofluorescence assays. RESULTS: The protein profile of Ti-EVs in each group was mapped by LC-MS analysis. The top 10 abundant proteins in BOL-derived Ti-EVs were COL6A3, COL6A1, ALB, HIST1H4A, HBB, ACTB, HIST1H2BD, ANXA2, COL6A2 and FBN1. Additionally, unique proteins in the Ti-EVs from various lesions were identified. Moreover, focal adhesion kinase (FAK) and myeloid differentiation primary response 88 (MyD88) showed higher expressions in Ti-EVs derived from OKC and AM, which were confirmed by immunohistochemistry and immunofluorescence staining. CONCLUSIONS: Ti-EVs containing FAK and MyD88 might be related to the development of OKC and AM, which can be potential therapeutic targets.

Electronic Structure Modulation Via Iron-Incorporated NiO to Boost Urea Oxidation/Oxygen Evolution Reaction.

The urea-assisted water splitting not only enables a reduction in energy consumption during hydrogen production but also addresses the issue of environmental pollution caused by urea. Doping heterogeneous atoms in Ni-based electrocatalysts is considered an efficient means for regulating the electronic structure of Ni sites in catalytic processes. However, the current methodologies for synthesizing heteroatom-doped Ni-based electrocatalysts exhibit certain limitations, including intricate experimental procedures, prolonged reaction durations, and low product yield. Herein, Fe-doped NiO electrocatalysts were successfully synthesized using a rapid and facile solution combustion method, enabling the synthesis of 1.1107 g within a mere 5 min. The incorporation of iron atoms facilitates the modulation of the electronic environment around Ni atoms, generating a substantial decrease in the Gibbs free energy of intermediate species for the Fe-NiO catalyst. This modification promotes efficient cleavage of C-N bonds and consequently enhances the catalytic performance of UOR. Benefiting from the tunability of the electronic environment around the active sites and its efficient electron transfer, Fe-NiO electrocatalysts only needs 1.334 V to achieve 50 mA cm-2 during UOR. Moreover, Fe-NiO catalysts were integrated into a dual electrode urea electrolytic system, requiring only 1.43 V of cell voltage at 10 mA cm-2.

Prediction of anti-cancer drug synergy based on cross-matching network and cancer molecular subtypes.

At present, anti-cancer drug synergy therapy is one of the most important methods to overcome drug resistance and reduce drug toxicity in cancer treatment. High-throughput screening through deep learning can effectively improve the efficiency of discovering synergistic drugs. Nowadays, most of the existing deep learning algorithms for anti-cancer drug synergy prediction use deep neural networks and can only implicitly perform feature interaction. This study proposes a deep learning algorithm, named MolCross, which combines implicit feature interaction with explicit features to improve the accuracy of prediction of the anti-cancer drug synergy score. MolCross uses a deep autoencoder to extract features from high-dimensional input, uses the drug-specific subnetworks and cross-network to perform implicit feature interaction and explicit feature interaction respectively, and finally uses a synergy prediction network to combine the two feature interaction methods to obtain the final prediction results. We adopted a five-fold cross validation and compared MolCross with other four anti-cancer drug synergy prediction models. The results show that MolCross has better prediction performance than other models. MolCross also has good performance in terms of cross-cell line and cross-tissue type. Existing studies have demonstrated that cancer molecular subtypes have different sensitivities to targeted therapy. In this study, the features of cancer molecular subtype were introduced in the model using an embedding layer in MolCross to explore the effect of cancer molecular subtype on anti-cancer drug synergy. We also found that the cancer molecular subtype is one of the main factors affecting the synergy between drugs.

PEA-m6A: an ensemble learning framework for accurately predicting N6-methyladenosine modifications in plants.

N 6-methyladenosine (m6A), which is the mostly prevalent modification in eukaryotic mRNAs, is involved in gene expression regulation and many RNA metabolism processes. Accurate prediction of m6A modification is important for understanding its molecular mechanisms in different biological contexts. However, most existing models have limited range of application and are species-centric. Here we present PEA-m6A, a unified, modularized and parameterized framework that can streamline m6A-Seq data analysis for predicting m6A-modified regions in plant genomes. The PEA-m6A framework builds ensemble learning-based m6A prediction models with statistic-based and deep learning-driven features, achieving superior performance with an improvement of 6.7% to 23.3% in the area under precision-recall curve compared with state-of-the-art regional-scale m6A predictor WeakRM in 12 plant species. Especially, PEA-m6A is capable of leveraging knowledge from pretrained models via transfer learning, representing an innovation in that it can improve prediction accuracy of m6A modifications under small-sample training tasks. PEA-m6A also has a strong capability for generalization, making it suitable for application in within- and cross-species m6A prediction. Overall, this study presents a promising m6A prediction tool, PEA-m6A, with outstanding performance in terms of its accuracy, flexibility, transferability, and generalization ability. PEA-m6A has been packaged using Galaxy and Docker technologies for ease of use and is publicly available at https://github.com/cma2015/PEA-m6A.

Characterization of bacterial diversity and screening of cellulose-degrading bacteria in the gut system of Glenea cantor (Fabricius) larvae.

The intestinal bacteria of longhorn beetles would be ideal targets for pest control and lignocellulosic resources by destroying or exploiting their cellulose-degrading function. This article aims to investigate the diversity and community structure of intestinal bacteria the oligophagous longhorn beetle Glenea cantor. Additionally, it seeks to identify the presence of lignocellulose-degrading bacteria in the gut, and explore their role in consuming host kapok trees Bombax malabaricum. In this study, the bacterial community from G. cantor was examined by Illumina sequencing of 16S ribosomal RNA (rRNA) targeting the V3 and V4 regions. A total of 563,201 valid sequences and 814 OTUs were obtained. The dominant phyla were Proteobacteria, and the dominant genera were Acinetobacter and Lactococcus. The analysis of microbial diversity revealed a high bacterial diversity in the samples, with the gut bacteria playing a crucial role in the physiological activities of the host, particularly, 9 genera of intestinal bacteria with cellulose degradation function were found, highlighting their vital role in cellulose degradation. Five strains of cellulose-degrading bacteria, belonging to the genus Pseudomonas, were obtained from the intestinal tract of G. cantor larvae using traditional isolation and culture techniques as well as 16S rDNA sequencing. Among these strains, A4 exhibited a cellulase activity of 94.42 ± 0.42 U/mL, while A5 displayed the highest filter paper enzyme activity of 127.46 ± 3.54 U/mL. These results offered valuable insights into potential targets for pest control through internal attack digestion and cellulose-degrading bacteria in longhorn beetles.

A 6-Year Follow-up of a Chinese Child with Homozygous ß0-Thalaasemia and a Heterozygous KLF1 Mutation.

Patients with the genotype of ß0/ß0 for ß-thalassemia (ß-thal) usually behave as ß-thal major (ß-TM) phenotype which is transfusion-dependent. The pathophysiology of ß-thal is the imbalance between α/ß-globin chains. The degree of α/ß-globin imbalance can be reduced by the more effective synthesis of γ-globin chains, and increased Hb F levels, modifying clinical severity of ß-TM. We report a Chinese child who had homozygous ß0-thal and a heterozygous KLF1 mutation. The patient had a moderate anemia since 6 months old, keeping a baseline Hb value of 8.0-9.0 g/dL. She had normal development except for a short stature (3rd percentile) until 6 years old, when splenomegaly and facial bone deformities occurred. Although genetic alteration of KLF1 expression in ß0/ß0 patients can result in some degree of disease alleviation, our case shows that it is insufficient to ameliorate satisfactorily the presentation. This point should be borne in mind for physicians who provide the genetic counseling and prenatal diagnosis to at-risk families.

StructuralDPPIV: a novel deep learning model based on atom structure for predicting dipeptidyl peptidase-IV inhibitory peptides.

MOTIVATION: Diabetes is a chronic metabolic disorder that has been a major cause of blindness, kidney failure, heart attacks, stroke, and lower limb amputation across the world. To alleviate the impact of diabetes, researchers have developed the next generation of anti-diabetic drugs, known as dipeptidyl peptidase IV inhibitory peptides (DPP-IV-IPs). However, the discovery of these promising drugs has been restricted due to the lack of effective peptide-mining tools. RESULTS: Here, we presented StructuralDPPIV, a deep learning model designed for DPP-IV-IP identification, which takes advantage of both molecular graph features in amino acid and sequence information. Experimental results on the independent test dataset and two wet experiment datasets show that our model outperforms the other state-of-art methods. Moreover, to better study what StructuralDPPIV learns, we used CAM technology and perturbation experiment to analyze our model, which yielded interpretable insights into the reasoning behind prediction results. AVAILABILITY AND IMPLEMENTATION: The project code is available at https://github.com/WeiLab-BioChem/Structural-DPP-IV.

ConPep: Prediction of peptide contact maps with pre-trained biological language model and multi-view feature extracting strategy.

The accurate prediction of peptide contact maps remains a challenging task due to the difficulty in obtaining the interactive information between residues on short sequences. To address this challenge, we propose ConPep, a deep learning framework designed for predicting the contact map of peptides based on sequences only. To sufficiently incorporate the sequential semantic information between residues in peptide sequences, we use a pre-trained biological language model and transfer prior knowledge from large scale databases. Additionally, to extract and integrate sequential local information and residue-based global correlations, our model incorporates Bidirectional Gated Recurrent Unit and attention mechanisms. They can obtain multi-view features and thus enhance the accuracy and robustness of our prediction. Comparative results on independent tests demonstrate that our proposed method significantly outperforms state-of-the-art methods even with short peptides. Notably, our method exhibits superior performance at the sequence level, suggesting the robust ability of our model compared with the multiple sequence alignment (MSA) analysis-based methods. We expect it can be meaningful research for facilitating the wide use of our method.

Prediction of cancer recurrence based on compact graphs of whole slide images.

Cancer recurrence is one of the primary causes of patient mortality following treatment, indicating increased aggressiveness of cancer cells and difficulties in achieving a cure. A critical step to improve patients' survival is accurately predicting recurrence status and giving appropriate treatment. Whole Slide Images (WSIs) are a common type of image data in the field of digital pathology, containing high-resolution tissue information. Furthermore, WSIs of primary tumors contain microenvironmental information directly associated with the growth of tumor cells. To effectively utilize this microenvironmental information. Firstly, we represented microenvironmental features of histopathological images as compact graphs. Secondly, this work aims to develop an enhanced lightweight graph neural network called the Adaptive Graph Clustering Network (AGCNet) for predicting cancer recurrence. Experiments are conducted on three cancer datasets from The Cancer Genome Atlas (TCGA), and AGCNet achieved an accuracy of 81.81% in BLCA, 69.66% in PAAD, and 81.96% in STAD. These results indicated that AGCNet is an effective model for predicting cancer recurrence and is expected to be applied in clinical applications.

Retrosynthesis prediction with an interpretable deep-learning framework based on molecular assembly tasks.

Automating retrosynthesis with artificial intelligence expedites organic chemistry research in digital laboratories. However, most existing deep-learning approaches are hard to explain, like a "black box" with few insights. Here, we propose RetroExplainer, formulizing the retrosynthesis task into a molecular assembly process, containing several retrosynthetic actions guided by deep learning. To guarantee a robust performance of our model, we propose three units: a multi-sense and multi-scale Graph Transformer, structure-aware contrastive learning, and dynamic adaptive multi-task learning. The results on 12 large-scale benchmark datasets demonstrate the effectiveness of RetroExplainer, which outperforms the state-of-the-art single-step retrosynthesis approaches. In addition, the molecular assembly process renders our model with good interpretability, allowing for transparent decision-making and quantitative attribution. When extended to multi-step retrosynthesis planning, RetroExplainer has identified 101 pathways, in which 86.9% of the single reactions correspond to those already reported in the literature. As a result, RetroExplainer is expected to offer valuable insights for reliable, high-throughput, and high-quality organic synthesis in drug development.

Effects of the Oat Hay Feeding Method and Compound Probiotic Supplementation on the Growth, Antioxidant Capacity, Immunity, and Rumen Bacteria Community of Dairy Calves.

This study aimed to investigate the effects of the oat hay feeding method and compound probiotics (CMP) on the growth, health, serum antioxidant and immune indicators, rumen fermentation, and bacteria community of dairy calves from 3 to 5 months of age. Forty-eight female Holstein calves (80 ± 7 days of age, 93.71 ± 5.33 kg BW) were selected and randomly divided into four groups. A 2 × 2 factorial design was adopted for the experiment, with the factors of the oat hay feeding method (fed as free-choice or 16.7% in the diet) and compound probiotics (CMP) inclusion (0.15% or 0%) in the pelleted starter. The results showed that, compared with giving oat hay as free-choice, feeding a diet of 16.7% oat hay increased the pelleted starter intake at 1-84 d (p < 0.05), with an average daily gain (ADG) at 61-84 d (p = 0.02); adding CMP to the pelleted starter did not significantly affect body weight, and reduced the fecal index (p < 0.05). Feeding 16.7% oat hay increased the concentration of IgA, IgG, and IgM (p < 0.01), while adding CMP increased the catalase (p < 0.01) and decreased the concentration of malondialdehyde (p < 0.01) in serum. Feeding 16.7% oat hay increased the ruminal concentration of propionic acid (p < 0.05) and isobutyric acid (p = 0.08), and decreased the ruminal pH (p = 0.08), the concentration of acetic acid (p < 0.05), and the ratio of acetic acid to propionic acid (p < 0.01). Feeding 16.7% oat hay reduced the relative abundance of ruminal Firmicutes, Unidentified-Bacteria, Actinobacteria, Prevotella, NK4A214-group, Olsenella, and Actinobacteriota (p < 0.05); adding CMP increased the relative abundance of ruminal Prevotella, Rikenellaceae-RC9-gut-group, Ruminococcus, NK4A214-group, and Ruminococcus (p < 0.05), and decreased the abundance of Desulfobacterora, Prevotella-7, and Erysipelotricaceae-UCG-002 (p < 0.05). In conclusion, feeding a diet of 16.7% oat hay increased the pelleted starter intake and average daily gain, while slightly reducing the ruminal pH values; adding CMP to the pelleted starter resulted in reduced diarrhea incidence, increased serum antioxidant capacity and immunity, as well as ruminal richness and diversity of microorganisms in dairy calves from 3 to 5 months of age.

Design, synthesis, and antimicrobial evaluation of 2-aminothiazole derivatives bearing the 4-aminoquinazoline moiety against plant pathogenic bacteria and fungi.

BACKGROUND: To find more effective agricultural antibiotics, a class of new 2-aminothiazole derivatives containing the 4-aminoquinazoline moiety were synthesized and evaluated for their antimicrobial properties against phytopathogenic bacteria and fungi of agricultural importance. RESULTS: All the target compounds were fully characterized by 1 H NMR, 13 C NMR, and high-resolution mass spectrometry. The bioassay results showed that compound F29 with a 2-pyridinyl substituent exhibited an outstanding antibacterial effect against Xanthomonas oryzae pv. oryzicola (Xoc) in vitro, having an half-maximal effective concentration (EC50 ) value as low as 2.0 µg/mL (over 30-fold more effective than the commercialized agrobactericide bismerthiazol, with an EC50 value of 64.3 µg/mL). In addition, compound F8 with a 2-fluorophenyl group demonstrated a good inhibitory activity toward the bacterium Xanthomonas axonopodis pv. citri (Xac), around twofold more active than bismerthiazol in terms of their EC50 values (22.8 versus 71.5 µg/mL). Interestingly, this compound also demonstrated a notable fungicidal effect against Phytophthora parasitica var. nicotianae, with an EC50 value largely comparable with that of the commercialized fungicide carbendazim. Finally, mechanistic studies revealed that compound F29 exerted its antibacterial effects by increasing the permeability of bacterial membranes, reducing the release of extracellular polysaccharides, and triggering morphological changes of bacterial cells. CONCLUSION: Compound F29 has promising potential as a lead compound for developing more efficient bactericides to fight against Xoc. © 2023 Society of Chemical Industry.

Identification of Immune Infiltration in Odontogenic Keratocyst by Integrated Bioinformatics Analysis.

BACKGROUND: Odontogenic keratocyst (OKC) is a relatively common odontogenic lesion characterized by local invasion in the maxillary and mandibular bones. In the pathological tissue slices of OKC, immune cell infiltrations are frequently observed. However, the immune cell profile and the molecular mechanism for immune cell infiltration of OKC are still unclear. We aimed to explore the immune cell profile of OKC and to explore the potential pathogenesis for immune cell infiltration in OKC. METHODS: The microarray dataset GSE38494 including OKC and oral mucosa (OM) samples were obtained from the Gene Expression Omnibus (GEO) database. The differentially expressed genes (DEGs) in OKC were analyzed by R software. The hub genes of OKC were performed by protein-protein interaction (PPI) network. The differential immune cell infiltration and the potential relationship between immune cell infiltration and the hub genes were performed by single-sample gene set enrichment analysis (ssGSEA). The expression of COL1A1 and COL1A3 were confirmed by immunofluorescence and immunohistochemistry in 17 OKC and 8 OM samples. RESULTS: We detected a total of 402 differentially expressed genes (DEGs), of which 247 were upregulated and 155 were downregulated. DEGs were mainly involved in collagen-containing extracellular matrix pathways, external encapsulating structure organization, and extracellular structure organization. We identified ten hub genes, namely FN1, COL1A1, COL3A1, COL1A2, BGN, POSTN, SPARC, FBN1, COL5A1, and COL5A2. A significant difference was observed in the abundances of eight types of infiltrating immune cells between the OM and OKC groups. Both COL1A1 and COL3A1 exhibited a significant positive correlation with natural killer T cells and memory B cells. Simultaneously, they demonstrated a significant negative correlation with CD56dim natural killer cells, neutrophils, immature dendritic cells, and activated dendritic cells. Immunohistochemistry analysis showed that COL1A1 (P = 0.0131) and COL1A3 (P < 0.001) were significantly elevated in OKC compared with OM. CONCLUSIONS: Our findings provide insights into the pathogenesis of OKC and illuminate the immune microenvironment within these lesions. The key genes, including COL1A1 and COL1A3, may significantly impact the biological processes associated with OKC.

Engineering Sub-Nanometer Hafnia-Based Ferroelectrics to Break the Scaling Relation for High-Efficiency Piezocatalytic Water Splitting.

Reversible control of ferroelectric polarization is essential to overcome the heterocatalytic kinetic limitation. This can be achieved by creating a surface with switchable electron density; however, owing to the rigidity of traditional ferroelectric oxides, achieving polarization reversal in piezocatalytic processes remains challenging. Herein, sub-nanometer-sized Hf0.5 Zr0.5 O2 (HZO) nanowires with a polymer-like flexibility are synthesized. Oxygen K-edge X-ray absorption spectroscopy and negative spherical aberration-corrected transmission electron microscopy reveal an orthorhombic (Pca21 ) ferroelectric phase of the HZO sub-nanometer wires (SNWs). The ferroelectric polarization of the flexible HZO SNWs can be easily switched by slight external vibration, resulting in dynamic modulation of the binding energy of adsorbates and thus breaking the "scaling relationship" during piezocatalysis. Consequently, the as-synthesized ultrathin HZO nanowires display superb water-splitting activity, with H2 production rate of 25687 µmol g-1  h-1 under 40 kHz ultrasonic vibration, which is 235 and 41 times higher than those of non-ferroelectric hafnium oxides and rigid BaTiO3 nanoparticles, respectively. More strikingly, the hydrogen production rates can reach 5.2 µmol g-1  h-1 by addition of stirring exclusively.

The N-degron pathway mediates lipophagy: The chemical modulation of lipophagy in obesity and NAFLD.

BACKGROUND AND AIMS: Central to the pathogenesis of nonalcoholic fatty liver disease (NAFLD) is the accumulation of lipids in the liver and various fat tissues. We aimed to elucidate the mechanisms by which lipid droplets (LDs) in the liver and adipocytes are degraded by the autophagy-lysosome system and develop therapeutic means to modulate lipophagy, i.e., autophagic degradation of LDs. METHODS: We monitored the process in which LDs are pinched off by autophagic membranes and degraded by lysosomal hydrolases in cultured cells and mice. The autophagic receptor p62/SQSTM-1/Sequestosome-1 was identified as a key regulator and used as a target to develop drugs to induce lipophagy. The efficacy of p62 agonists was validated in mice to treat hepatosteatosis and obesity. RESULTS: We found that the N-degron pathway modulates lipophagy. This autophagic degradation initiates when the molecular chaperones including BiP/GRP78, retro-translocated from the endoplasmic reticulum, is N-terminally (Nt-) arginylated by ATE1 R-transferase. The resulting Nt-arginine (Nt-Arg) binds the ZZ domain of p62 associated with LDs. Upon binding to Nt-Arg, p62 undergoes self-polymerization and recruits LC3+ phagophores to the site of lipophagy, leading to lysosomal degradation. Liver-specific Ate1 conditional knockout mice under high fat diet developed severe NAFLD. The Nt-Arg was modified into small molecule agonists to p62 that facilitate lipophagy in mice and exerted therapeutic efficacy in obesity and hepatosteatosis of wild-type but not p62 knockout mice. CONCLUSIONS: Our results show that the N-degron pathway modulates lipophagy and provide p62 as a drug target to treat NAFLD and other diseases related with metabolic syndrome.

Targeted degradation of ⍺-synuclein aggregates in Parkinson's disease using the AUTOTAC technology.

BACKGROUND: There are currently no disease-modifying therapeutics for Parkinson's disease (PD). Although extensive efforts were undertaken to develop therapeutic approaches to delay the symptoms of PD, untreated α-synuclein (α-syn) aggregates cause cellular toxicity and stimulate further disease progression. PROTAC (Proteolysis-Targeting Chimera) has drawn attention as a therapeutic modality to target α-syn. However, no PROTACs have yet shown to selectively degrade α-syn aggregates mainly owing to the limited capacity of the proteasome to degrade aggregates, necessitating the development of novel approaches to fundamentally eliminate α-syn aggregates. METHODS: We employed AUTOTAC (Autophagy-Targeting Chimera), a macroautophagy-based targeted protein degradation (TPD) platform developed in our earlier studies. A series of AUTOTAC chemicals was synthesized as chimeras that bind both α-syn aggregates and p62/SQSTM1/Sequestosome-1, an autophagic receptor. The efficacy of Autotacs was evaluated to target α-syn aggregates to phagophores and subsequently lysosomes for hydrolysis via p62-dependent macroautophagy. The target engagement was monitored by oligomerization and localization of p62 and autophagic markers. The therapeutic efficacy to rescue PD symptoms was characterized in cultured cells and mice. The PK/PD (pharmacokinetics/pharmacodynamics) profiles were investigated to develop an oral drug for PD. RESULTS: ATC161 induced selective degradation of α-syn aggregates at DC50 of ~ 100 nM. No apparent degradation was observed with monomeric α-syn. ATC161 mediated the targeting of α-syn aggregates to p62 by binding the ZZ domain and accelerating p62 self-polymerization. These p62-cargo complexes were delivered to autophagic membranes for lysosomal degradation. In PD cellular models, ATC161 exhibited therapeutic efficacy to reduce cell-to-cell transmission of α-syn and to rescue cells from the damages in DNA and mitochondria. In PD mice established by injecting α-syn preformed fibrils (PFFs) into brain striata via stereotaxic surgery, oral administration of ATC161 at 10 mg/kg induced the degradation of α-syn aggregates and reduced their propagation. ATC161 also mitigated the associated glial inflammatory response and improved muscle strength and locomotive activity. CONCLUSION: AUTOTAC provides a platform to develop drugs for PD. ATC161, an oral drug with excellent PK/PD profiles, induces selective degradation of α-syn aggregates in vitro and in vivo. We suggest that ATC161 is a disease-modifying drug that degrades the pathogenic cause of PD.