A facile and smart strategy to enhance bone regeneration with efficient vitamin D3 delivery through sterosome technology.

The spontaneous healing of critical-sized bone defects is often limited, posing an increased risk of complications and suboptimal outcomes. Osteogenesis, a complex process central to bone formation, relies significantly on the pivotal role of osteoblasts. Despite the well-established osteogenic properties of vitamin D3 (VD3), its lipophilic nature confines administration to oral or muscle injection routes. Therefore, a strategic therapeutic approach involves designing a multifunctional carrier to enhance efficacy, potentially incorporating it into the delivery system. Here, we introduce an innovative sterosome-based delivery system, utilizing palmitic acid (PA) and VD3, aimed at promoting osteogenic differentiation and facilitating post-defect bone regeneration. The delivery system exhibited robust physical characteristics, including excellent stability, loading efficiency, sustained drug release and high cellular uptake efficiency. Furthermore, comprehensive investigations demonstrated outstanding biocompatibility and osteogenic potential in both 2D and 3D in vitro settings. A critical-sized calvarial defect model in mice recapitulated the notable osteogenic effects of the sterosomes in vivo. Collectively, our research proposes a clinically applicable strategy for bone healing, leveraging PA/VD3 sterosomes as an efficient carrier to deliver VD3 and enhance bone regenerative effects.

Aloperine-Type Alkaloids with Antiviral and Antifungal Activities from the Seeds of Sophora alopecuroides L.

As a continuous flow investigation of novel pesticides from natural quinolizidine alkaloids, the chemical compositions of the seeds of Sophora alopecuroides were thoroughly researched. Fifteen new aloperine-type alkaloids (1-15) as well as six known aloperine-type alkaloids (16-21) were obtained from the extract of S. alopecuroides. The structures of 1-21 were confirmed via HRESIMS, NMR, UV, IR, ECD calculations, and X-ray diffraction. The antiviral activities of 1-21 against tobacco mosaic virus (TMV) were detected following the improved method of half-leaf. Compared with ningnanmycin (protective: 69.7% and curative: 64.3%), 15 exhibited excellent protective (71.7%) and curative (64.6%) activities against TMV. Further biological studies illustrated that 15 significantly inhibited the transcription of the TMV-CP gene and increased the activities of polyphenol oxidase (PPO), peroxidase (POD), superoxide dismutase (SOD), and phenylalanine ammonia-lyase (PAL). The antifungal activities of 1-21 against Phytophythora capsica, Botrytis cinerea, Alternaria alternata, and Gibberella zeae were screened according to a mycelial inhibition test. Compound 13 displayed excellent antifungal activity against B. cinerea (EC50: 7.38 µg/mL). Moreover, in vitro antifungal mechanism studies displayed that 13 causes accumulation of reactive oxygen species and finally leads to mycelia cell membrane damage and cell death in vitro.

Polymerizable rotaxane of cucurbituril protecting dopamine based adhesive hydrogels.

The catechol moiety found within mussel proteins plays a pivotal role in enhancing their adhesive properties. Nonetheless, catechol compounds, such as dopamine (DOP) derivatives, are susceptible to oxidation, leading to the formation of quinone. This oxidation process poses a significant challenge in the development of DOP-based hydrogels, hampering their adhesion capabilities and hindering polymerization. To protect DOP moieties from oxidation, DOP and N-(3-aminopropyl)methacrylamide (AMA) moieties were grafted onto the side groups of biocompatible poly(glutamic acid) (PGA). Subsequently, the DOP unit, serving as a second guest, would be captured by a polymerizable rotaxane of cucurbituril (CB[n]), in which the host molecule CB[8] complexed with the first guest, polymerizable methyl viologen (MV), forming a protective function and dynamic cross-linking. Upon exposure to light curing, a composite network emerged through the synergy of covalent cross-linking and supramolecular host-guest complexation of DOP with CB[8]. The generated complexation between DOP and CB[8] could protect the DOP moieties, resulting in photocured hydrogels with exceptional adhesive strength and remarkable tensile capabilities. Moreover, 3D printing technology was used to create various models with these DOP-based hydrogels, demonstrating their promising applications in future.

GLUT1 Promotes NLRP3 Inflammasome Activation of Airway Epithelium in Lipopolysaccharide-Induced Acute Lung Injury.

Acute lung injury (ALI) is a devastating clinical disease caused by different factors, with high morbidity and mortality. It has been shown that lung injury and inflammation caused by lipopolysaccharide (LPS) can be modulated by NLRP3 inflammasome activation, yet its exact function within the airway epithelium is still unknown. Meanwhile, glucose transporter protein 1 (GLUT1) has been shown to contribute to a number of inflammatory illnesses, including ALI. The present study aimed to assess GLUT1's function in NLRP3 inflammasome activation of airway epithelium in LPS-induced acute lung injury. BALB/c mice and BEAS-2B cells were exposed to LPS (5 mg/kg and 200 µg/mL, respectively), with or without GLUT1 antagonists (WZB117 or BAY876). LPS up-regulated pulmonary expression of NLRP3 and GLUT1 in mice, which could be blocked by WZB117 or BAY876. Pharmacological inhibition of GLUT1 in vivo significantly attenuated lung tissue damage, neutrophil accumulation, and proinflammatory factors release (TNF-α, IL-6, and IL-1ß) in LPS-exposed mice. Meanwhile, the activation markers of NLRP3 inflammasome (ASC, caspase-1, IL-1ß, and IL-18) induced by LPS were also suppressed. In cultured BEAS-2B cells, LPS induced an increase in GLUT1 expression and triggered activation of the NLRP3 inflammasome, both of which were inhibited by GLUT1 antagonists. These results illustrate that GLUT1 participates in LPS-induced ALI and promotes the activation of the NLRP3 inflammasome in airway epithelial cells.

Genome-Wide Identification, Characterization, and Expression Analysis of the BES1 Family Genes under Abiotic Stresses in Phoebe bournei.

The BRI1 EMS suppressor 1(BES1) transcription factor is a crucial regulator in the signaling pathway of Brassinosteroid (BR) and plays an important role in plant growth and response to abiotic stress. Although the identification and functional validation of BES1 genes have been extensively explored in various plant species, the understanding of their role in woody plants-particularly the endangered species Phoebe bournei (Hemsl.) Yang-remains limited. In this study, we identified nine members of the BES1 gene family in the genome of P. bournei; these nine members were unevenly distributed across four chromosomes. In our further evolutionary analysis of PbBES1, we discovered that PbBES1 can be divided into three subfamilies (Class I, Class II, and Class IV) based on the evolutionary tree constructed with Arabidopsis thaliana, Oryza sativa, and Solanum lycopersicum. Each subfamily contains 2-5 PbBES1 genes. There were nine pairs of homologous BES1 genes in the synteny analysis of PbBES1 and AtBES1. Three segmental replication events and one pair of tandem duplication events were present among the PbBES1 family members. Additionally, we conducted promoter cis-acting element analysis and discovered that PbBES1 contains binding sites for plant growth and development, cell cycle regulation, and response to abiotic stress. PbBES1.2 is highly expressed in root bark, stem bark, root xylem, and stem xylem. PbBES1.3 was expressed in five tissues. Moreover, we examined the expression profiles of five representative PbBES1 genes under heat and drought stress. These experiments preliminarily verified their responsiveness and functional roles in mediating responses to abiotic stress. This study provides important clues to elucidate the functional characteristics of the BES1 gene family, and at the same time provides new insights and valuable information for the regulation of resistance in P. bournei.

Efficient automated high dynamic range 3D measurement via deep reinforcement learning.

High dynamic range 3D measurement technology, utilizing multiple exposures, is pivotal in industrial metrology. However, selecting the optimal exposure sequence to balance measurement efficiency and quality remains challenging. This study reinterprets this challenge as a Markov decision problem and presents an innovative exposure selection method rooted in deep reinforcement learning. Our approach's foundation is the exposure image prediction network (EIPN), designed to predict images under specific exposures, thereby simulating a virtual environment. Concurrently, we establish a reward function that amalgamates considerations of exposure number, exposure time, coverage, and accuracy, providing a comprehensive task definition and precise feedback. Building upon these foundational elements, the exposure selection network (ESN) emerges as the centerpiece of our strategy, acting decisively as an agent to derive the optimal exposure sequence selection. Experiments prove that the proposed method can obtain similar coverage (0.997 vs. 1) and precision (0.0263 mm vs. 0.0230 mm) with fewer exposures (generally 4) compared to the results of 20 exposures.

Inter-subunit energy transfer processes in a minimal plant photosystem II supercomplex.

Photosystem II (PSII) is an integral part of the photosynthesis machinery, in which several light-harvesting complexes rely on inter-complex excitonic energy transfer (EET) processes to channel energy to the reaction center. In this paper, we report on a direct observation of the inter-complex EET in a minimal PSII supercomplex from plants, containing the trimeric light-harvesting complex II (LHCII), the monomeric light-harvesting complex CP26, and the monomeric PSII core complex. Using two-dimensional (2D) electronic spectroscopy, we measure an inter-complex EET timescale of 50 picoseconds for excitations from the LHCII-CP26 peripheral antenna to the PSII core. The 2D electronic spectra also reveal that the transfer timescale is nearly constant over the pump spectrum of 600 to 700 nanometers. Structure-based calculations reveal the contribution of each antenna complex to the measured inter-complex EET time. These results provide a step in elucidating the full inter-complex energy transfer network of the PSII machinery.

NAMPT­NAD+ is involved in the senescence­delaying effects of saffron in aging mice.

As the proportion of the elderly population grows rapidly, the senescence-delaying effects of Traditional Chinese Medicine is being investigated. The aim of the present study was to investigate the senescence-delaying effects of saffron in naturally aging mice. The active ingredients in an aqueous saffron extract were determined using high-performance liquid chromatography (HPLC). Mice were divided into saffron (8- and 16-months-old) and control groups (3-, 8-, and 16-months-old), and saffron extract was administered to the former groups for 8 weeks. The open field test and Barnes maze test were used to evaluate the locomotor activity, learning and memory function of the mice. The levels of inflammatory factors in the brain were determined by ELISA. In addition, the activities of acetylcholinesterase (AChE) and superoxide dismutase, and the contents of malondialdehyde and nicotinamide adenine dinucleotide (NAD+) were detected by enzyme immunoassay, and the content of NAMPT was detected by ELISA, western blotting and reverse transcription-quantitative PCR. The cellular distribution of NAMPT and synaptic density were evaluated by immunofluorescence, and the pathological morphologies of the liver, skin, kidneys were observed by hematoxylin and eosin staining. HPLC revealed that the crocin and picrocrocin contents of the saffron extract were 19.56±0.14 and 12.00±0.13%, respectively. Saffron exhibited the potential to improve the learning and memory function in aging mice as it increased synaptic density and decreased AChE activity. Also, saffron ameliorated the pathological changes associated with organ aging, manifested by increasing the number of hepatocytes and the thickness of the skin, and preventing the aging-induced ballooning and bleeding in the kidneys. Furthermore, saffron increased the contents of NAMPT and NAD+ in the brain and decreased the content of NAMPT in the serum. In addition, it changed the cellular distribution of NAMPT in aging mice, manifested as reduced NAMPT expression in microglia and astrocytes, and increased NAMPT expression in neurons. Saffron also decreased the contents of proinflammatory cytokines and oxidative stress factors in aging mice. Altogether, these findings indicate that saffron exerts senescence-delaying effects in naturally aging mice, which may be associated with the NAMPT-NAD+ pathway.

Quinolizidine Alkaloids and Isoflavones from the Herb of Thermopsis lupinoides and Their Antiviral, Antifungal, and Insecticidal Activities.

As part of our ongoing investigation of natural bioactive substances from the genus Thermopsis of the tribe Fabaceae for agricultural protection, the chemical constituents of the herb Thermopsis lupinoides were systematically investigated, which led to the isolation of 39 quinolizidine alkaloids (QAs) (1-39), including 14 new QAs (1-14) and 14 isoflavones (40-53). Their structures were elucidated through comprehensive spectroscopic data analysis (IR, UV, NMR, HRESIMS), ECD calculations, and X-ray crystallography. The antitomato spotted wilt virus (TSWV) and antifungal (against Botrytis cinerea, Gibberella zeae, Phytophythora capsica, and Alternaria alternata) and insecticidal (against Aphis fabae and Tetranychus urticae) activities of the isolated compounds were screened using the lesion counting method, mycelial inhibition assay, and spray method, respectively. The bioassay results showed that 34 exhibited excellent protective activity against TSWV, with an EC50 value of 36.04 µg/mL, which was better than that of the positive control, ningnanmycin (86.03 µg/mL). The preliminary mechanistic exploration illustrated that 34 induced systemic acquired resistance in the host plant by acting on the salicylic acid signaling pathway. Moreover, 1 showed significant antifungal activity against B. cinerea (EC50 value of 20.83 µg/mL), while 2 exhibited good insecticidal activity against A. fabae (LC50 value of 24.97 µg/mL). This research is promising for the invention of novel pesticides from QAs with high efficiency and satisfactory ecological compatibility.

Artificial Intelligence-based Amide-II Infrared Spectroscopy Simulation for Monitoring Protein Hydrogen Bonding Dynamics.

The structurally sensitive amide II infrared (IR) bands of proteins provide valuable information about the hydrogen bonding of protein secondary structures, which is crucial for understanding protein dynamics and associated functions. However, deciphering protein structures from experimental amide II spectra relies on time-consuming quantum chemical calculations on tens of thousands of representative configurations in solvent water. Currently, the accurate simulation of amide II spectra for whole proteins remains a challenge. Here, we present a machine learning (ML)-based protocol designed to efficiently simulate the amide II IR spectra of various proteins with an accuracy comparable to experimental results. This protocol stands out as a cost-effective and efficient alternative for studying protein dynamics, including the identification of secondary structures and monitoring the dynamics of protein hydrogen bonding under different pH conditions and during protein folding process. Our method provides a valuable tool in the field of protein research, focusing on the study of dynamic properties of proteins, especially those related to hydrogen bonding, using amide II IR spectroscopy.

In Situ Cas12a-Based Allele-Specific PCR for Imaging Single-Nucleotide Variations in Foodborne Pathogenic Bacteria.

In situ profiling of single-nucleotide variations (SNVs) can elucidate drug-resistant genotypes with single-cell resolution. The capacity to directly "see" genetic information is crucial for investigating the relationship between mutated genes and phenotypes. Fluorescence in situ hybridization serves as a canonical tool for genetic imaging; however, it cannot detect subtle sequence alteration including SNVs. Herein, we develop an in situ Cas12a-based amplification refractory mutation system-PCR (ARMS-PCR) method that allows the visualization of SNVs related to quinolone resistance inside cells. The capacity of discriminating SNVs is enhanced by incorporating optimized mismatched bases in the allele-specific primers, thus allowing to specifically amplify quinolone-resistant related genes. After in situ ARMS-PCR, we employed a modified Cas12a/CRISPR RNA to tag the amplicon, thereby enabling specific binding of fluorophore-labeled DNA probes. The method allows to precisely quantify quinolone-resistant Salmonella enterica in the bacterial mixture. Utilizing this method, we investigated the survival competition capacity of quinolone-resistant and quinolone-sensitive bacteria toward antimicrobial peptides and indicated the enrichment of quinolone-resistant bacteria under colistin sulfate stress. The in situ Cas12a-based ARMS-PCR method holds the potential for profiling cellular phenotypes and gene regulation with single-nucleotide resolution at the single-cell level.

[Corrigendum] PRIMA­1met induces autophagy in colorectal cancer cells through upregulation of the mTOR/AMPK­ULK1­Vps34 signaling cascade.

Following the publication of the above article, the authors contacted the Editorial Office to explain that the strips of ß­actin, LC3 and p62 proteins of the RKO cell line shown in Fig. 2A and B, and those of the SW620 cell line shown in Fig. 3A and B, were assembled in these figures incorrectly. To rectify the presentation of these two figures, the authors proposed that they replace the strips of ß­actin and p62 proteins in the original Figs. 2B and 3B with the ß­actin bands from one of the repeated western blotting experiments.  The revised and corrected versions of Figs. 2 and 3 are shown on the next page. The authors wish to emphasize that these corrections do not grossly affect either the results or the conclusions reported in this work. The authors all agree to the publication of this Corrigendum, and are grateful to the Editor of Oncology Reports for granting them the opportunity to correct the errors that were made during the assembly of these figures. Lastly, the authors apologize to the readership for any inconvenience these errors may have caused. [Oncology Reports 45: 86, 2021; DOI: 10.3892/or.2021.8037].

Betaine alleviates cognitive impairment induced by homocysteine through attenuating NLRP3-mediated microglial pyroptosis in an m6A-YTHDF2-dependent manner.

Dementia, with homocysteine (Hcy) as an important risk factor, is a severe public health problem in the aging society. Betaine serves as a methyl donor and plays an important role in reducing Hcy. However, the effects and mechanisms of betaine on Hcy-induced cognitive impairment remain unclear. Firstly, SD rats were injected with Hcy (400 µg/kg) through vena caudalis, and betaine (2.5 % w/v) was supplemented via drinking water for 14 days. Betaine supplementation could attenuate Hcy-induced cognitive impairment in the Y maze and novel object recognition tests by repairing brain injury. Meanwhile, microglial activation was observed to be inhibited by betaine supplementation using immunofluorescence and sholl analysis. Secondly, HMC3 cells were treated with betaine, which was found to decrease the ROS level, ameliorate cell membrane rupture, reduce the release of LDH, IL-18 and IL-1ß, and attenuate the damage of microglia to neurons. Mechanistically, betaine alleviates cognitive impairment by inhibiting microglial pyroptosis via reducing the expressions of NLRP3, ASC, pro-caspase-1, cleaved-caspase-1, GSDMD, GSDMD-N, IL-18 and IL-1ß. Betaine treatment can increase SAM/SAH ratio, confirming its enhancement on methylation capacity. Furthermore, betaine treatment was found to enhance N6-methyladenosine (m6A) modification of NLRP3 mRNA, and reduced the NLRP3 mRNA stability through increasing the expression of the m6A reader YTH N6-methyladenosine RNA binding protein 2 (YTHDF2). Finally, silencing YTHDF2 could reverse the inhibitory effect of betaine on pyroptosis. Our data demonstrated that betaine attenuated Hcy-induced cognitive impairment by suppressing microglia pyroptosis via inhibiting the NLRP3/caspase-1/GSDMD pathway in an m6A-YTHDF2-dependent manner.

MMDTA: A Multimodal Deep Model for Drug-Target Affinity with a Hybrid Fusion Strategy.

The prediction of the drug-target affinity (DTA) plays an important role in evaluating molecular druggability. Although deep learning-based models for DTA prediction have been extensively attempted, there are rare reports on multimodal models that leverage various fusion strategies to exploit heterogeneous information from multiple different modalities of drugs and targets. In this study, we proposed a multimodal deep model named MMDTA, which integrated the heterogeneous information from various modalities of drugs and targets using a hybrid fusion strategy to enhance DTA prediction. To achieve this, MMDTA first employed convolutional neural networks (CNNs) and graph convolutional networks (GCNs) to extract diverse heterogeneous information from the sequences and structures of drugs and targets. It then utilized a hybrid fusion strategy to combine and complement the extracted heterogeneous information, resulting in the fused modal information for predicting drug-target affinity through the fully connected (FC) layers. Experimental results demonstrated that MMDTA outperformed the competitive state-of-the-art deep learning models on the widely used benchmark data sets, particularly with a significantly improved key evaluation metric, Root Mean Square Error (RMSE). Furthermore, MMDTA exhibited excellent generalization and practical application performance on multiple different data sets. These findings highlighted MMDTA's accuracy and reliability in predicting the drug-target binding affinity. For researchers interested in the source data and code, they are accessible at http://github.com/dldxzx/MMDTA.

Simvastatin ameliorates synaptic plasticity impairment in chronic mild stress-induced depressed mice by modulating hippocampal NMDA receptor.

BACKGROUND: In our previous study, we showed simvastatin exerts an antidepressant effect and inhibits neuroinflammation. Given the role of synaptic impairment in depression development, we investigate the effect of simvastatin on synaptic plasticity in depression and the related mechanisms. METHODS: Electrophysiological analysis, Golgi staining, and transmission electron microscope were performed to analyze the effect of simvastatin on synaptic impairment in depression. In addition, the localization and reactivity of N-methyl-D-aspartate receptor (NMDAR) subunits and the downstream signaling were investigated to explore the mechanism of simvastatin's effect on synaptic plasticity. RESULTS: Simvastatin ameliorated the reduction of the magnitude of long-term potentiation (LTP) in Schaffer collateral-CA1, restored hippocampal dendritic spine density loss, improved the number of spine synapses, reversed the reduction in BrdU-positive cells in chronic mild stress (CMS)-induced depressed mice, and ameliorated NMDA-induced neurotoxicity in hippocampal neurons. Dysfunction of NMDAR activity in the hippocampus is associated with depression. Simvastatin treatment reversed the surface expression and phosphorylation changes of NMDAR subunits in NMDA-treated hippocampal neurons and depressed mice. In addition, simvastatin further increased the levels of mature BDNF, activating TrkB-Akt-mTOR signaling, which is critical for synaptic plasticity. CONCLUSIONS: These findings suggest that simvastatin can improve the dysfunction of NMDAR and ameliorate hippocampal synaptic plasticity impairment in depressed mice.

GHGPR-PPIS: A graph convolutional network for identifying protein-protein interaction site using heat kernel with Generalized PageRank techniques and edge self-attention feature processing block.

Accurately pinpointing protein-protein interaction site (PPIS) on the molecular level is of utmost significance for annotating protein function and comprehending the mechanisms underpinning various diseases. While numerous computational methods for predicting PPIS have emerged, they have indeed mitigated the labor and time constraints associated with traditional experimental methods. However, the predictive accuracy of these methods has yet to reach the desired threshold. In this context, we proposed a groundbreaking graph-based computational model called GHGPR-PPIS. This innovative model leveraged a graph convolutional network using heat kernel (GraphHeat) in conjunction with Generalized PageRank techniques (GHGPR) to predict PPIS. Additionally, building upon the GHGPR framework, we devised an edge self-attention feature processing block, further augmenting the performance of the model. Experimental findings conclusively demonstrated that GHGPR-PPIS surpassed all competing state-of-the-art models when evaluated on the benchmark test set. Impressively, on two distinct independent test sets and a specific protein chain, GHGPR-PPIS consistently demonstrated superior generalization performance and practical applicability compared to the comparative model, AGAT-PPIS. Lastly, leveraging the t-SNE dimensionality reduction algorithm and clustering visualization technique, we delved into an interpretability analysis of the effectiveness of GHGPR-PPIS by meticulously comparing the outputs from different stages of the model.

Deep learning-assisted preclinical MR fingerprinting for sub-millimeter T1 and T2 mapping of entire macaque brain.

PURPOSE: Preclinical MR fingerprinting (MRF) suffers from long acquisition time for organ-level coverage due to demanding image resolution and limited undersampling capacity. This study aims to develop a deep learning-assisted fast MRF framework for sub-millimeter T1 and T2 mapping of entire macaque brain on a preclinical 9.4 T MR system. METHODS: Three dimensional MRF images were reconstructed by singular value decomposition (SVD) compressed reconstruction. T1 and T2 mapping for each axial slice exploited a self-attention assisted residual U-Net to suppress aliasing-induced quantification errors, and the transmit-field (B1 + ) measurements for robustness against B1 + inhomogeneity. Supervised network training used MRF images simulated via virtual parametric maps and a desired undersampling scheme. This strategy bypassed the difficulties of acquiring fully sampled preclinical MRF data to guide network training. The proposed fast MRF framework was tested on experimental data acquired from ex vivo and in vivo macaque brains. RESULTS: The trained network showed reasonable adaptability to experimental MRF images, enabling robust delineation of various T1 and T2 distributions in the brain tissues. Further, the proposed MRF framework outperformed several existing fast MRF methods in handling the aliasing artifacts and capturing detailed cerebral structures in the mapping results. Parametric mapping of entire macaque brain at nominal resolution of 0.35 × $$ \times $$ 0.35 × $$ \times $$ 1 mm3 can be realized via a 20-min 3D MRF scan, which was sixfold faster than the baseline protocol. CONCLUSION: Introducing deep learning to MRF framework paves the way for efficient organ-level high-resolution quantitative MRI in preclinical applications.