A Double-Hurdle Quantification Model for Freezing of Gait of Parkinson's Patients.

Freezing of gait (FOG) leads to an increased risk of falls and limited mobility in individuals with Parkinson's disease (PD). However, existing research ignores the fine-grained quantitative assessment of FOG severity. This paper provides a double-hurdle model that uses typical spatiotemporal gait features to quantify the FOG severity in patients with PD. Moreover, a novel multi-output random forest algorithm is used as one hurdle of the double-hurdle model, further enhancing the model's performance. We conduct six experiments on a public PD gait database. Results demonstrate that the designed random forest algorithm in the double-hurdle model-hyperparameter independence framework achieves outstanding performances with the highest correlation coefficient (CC) of 0.972 and the lowest root mean square error (RMSE) of 2.488. Furthermore, we study the effect of drug state on the gait patterns of PD patients with or without FOG. Results show that "OFF" state amplifies the visibility of FOG symptoms in PD patients. Therefore, this study holds significant implications for the management and treatment of PD.

Corrigendum: The role of microtubules in pancreatic cancer: therapeutic progress.

[This corrects the article DOI: 10.3389/fonc.2021.640863.].

Beyond Traditional Medicine: EVs-Loaded Hydrogels as a Game Changer in Disease Therapeutics.

Extracellular vesicles (EVs), especially exosomes, have shown great therapeutic potential in the treatment of diseases, as they can target cells or tissues. However, the therapeutic effect of EVs is limited due to the susceptibility of EVs to immune system clearance during transport in vivo. Hydrogels have become an ideal delivery platform for EVs due to their good biocompatibility and porous structure. This article reviews the preparation and application of EVs-loaded hydrogels as a cell-free therapy strategy in the treatment of diseases. The article also discusses the challenges and future outlook of EVs-loaded hydrogels.

Design, Optimization, and Modeling of a Hydraulic Soft Robot for Chronic Total Occlusions.

Chronic total occlusion (CTO) is one of the most severe and sophisticated vascular stenosis because of complete blockage, greater operation difficulty, and lower procedural success rate. This study proposes a hydraulic-driven soft robot imitating the earthworm's locomotion to assist doctors or operators in actively opening thrombi in coronary or peripheral artery vessels. Firstly, a three-actuator bionic soft robot is developed based on earthworms' physiological structure. The soft robot's locomotion gait inspired by the earthworm's mechanism is designed. Secondly, the influence of structure parameters on actuator deformation, stress, and strain is explored, which can help us determine the soft actuators' optimal structure parameters. Thirdly, the relationship between hydraulic pressure and actuator deformation is investigated by performing finite element analysis using the bidirectional fluid-structure interaction (FSI) method. The kinematic models of the soft actuators are established to provide a valuable reference for the soft actuators' motion control.

Graph Reasoning Module for Alzheimer's Disease Diagnosis: A Plug-and-Play Method.

Recent advances in deep learning have led to increased adoption of convolutional neural networks (CNN) for structural magnetic resonance imaging (sMRI)-based Alzheimer's disease (AD) detection. AD results in widespread damage to neurons in different brain regions and destroys their connections. However, current CNN-based methods struggle to relate spatially distant information effectively. To solve this problem, we propose a graph reasoning module (GRM), which can be directly incorporated into CNN-based AD detection models to simulate the underlying relationship between different brain regions and boost AD diagnosis performance. Specifically, in GRM, an adaptive graph Transformer (AGT) block is designed to adaptively construct a graph representation based on the feature map given by CNN, a graph convolutional network (GCN) block is adopted to update the graph representation, and a feature map reconstruction (FMR) block is built to convert the learned graph representation to a feature map. Experimental results demonstrate that the insertion of the GRM in the existing AD classification model can increase its balanced accuracy by more than 4.3%. The GRM-embedded model achieves state-of-the-art performance compared with current deep learning-based AD diagnosis methods, with a balanced accuracy of 86.2%.

CuS@TA-Fe Nanoparticle-Doped Multifunctional Hydrogel with Peroxide-Like Properties and Photothermal Properties for Synergistic Antimicrobial Repair of Infected Wounds.

Bacterial infection is a critical factor in wound healing. Due to the abuse of antibiotics, some pathogenic bacteria have developed resistance. Thus, there is an urgent need to develop a non-antibiotic-dependent multifunctional wound dressing for the treatment of bacteria-infected wounds. In this work, a multifunctional AOCuT hydrogel embedded with CuS@TA-Fe nanoparticles (NPs) through Schiff base reaction between gelatin quaternary ammonium salt - gallic acid (O-Gel-Ga) and sodium dialdehyde alginate (ADA) along with electrostatic interactions with CuS@TA-Fe NPs is prepared. These composite hydrogels possess favorable injectability, rapid shape adaptation, electrical conductivity, photothermal antimicrobial activity, and biocompatibility. Additionally, the doped NPs not only impart fast self-healing properties and excellent adhesion performance to the hydrogels, but also provide excellent peroxide-like properties, enabling them to scavenge free radicals and exhibit anti-inflammatory and antioxidant capabilities via photothermal (PTT) and photodynamic (PDT) effects. In an S. aureus infected wound model, the composite hydrogel effectively reduces the expression level of wound inflammatory factors and accelerates collagen deposition, epithelial tissue, and vascular regeneration, thereby promoting wound healing. This safe and synergistic therapeutic system holds great promise for clinical applications in the treatment of infectious wounds.

Orally Bioavailable 4-Phenoxy-quinoline Compound as a Potent Aurora Kinase B Relocation Blocker for Cancer Treatment.

We investigated a novel 4-phenoxy-quinoline-based scaffold that mislocalizes the essential mitotic kinase, Aurora kinase B (AURKB). Here, we evaluated the impact of halogen substitutions (F, Cl, Br, and I) on this scaffold with respect to various drug parameters. Br-substituted LXY18 was found to be a potent and orally bioavailable disruptor of cell division, at sub-nanomolar concentrations. LXY18 prevents cytokinesis by blocking AURKB relocalization in mitosis and exhibits broad-spectrum antimitotic activity in vitro. With a favorable pharmacokinetic profile, it shows widespread tissue distribution including the blood-brain barrier penetrance and effective accumulation in tumor tissues. More importantly, it markedly suppresses tumor growth. The novel mode of action of LXY18 may eliminate some drawbacks of direct catalytic inhibition of Aurora kinases. Successful development of LXY18 as a clinical candidate for cancer treatment could enable a new, less toxic means of antimitotic attack that avoids drug resistance mechanisms.

A Novel Spatial Position Prediction Navigation System Makes Surgery More Accurate.

During intravascular interventional surgery, the 3D surgical navigation system can provide doctors with 3D spatial information of the vascular lumen, reducing the impact of missing dimension caused by digital subtraction angiography (DSA) guidance and further improving the success rate of surgeries. Nevertheless, this task often comes with the challenge of complex registration problems due to vessel deformation caused by respiratory motion and high requirements for the surgical environment because of the dependence on external electromagnetic sensors. This article proposes a novel 3D spatial predictive positioning navigation (SPPN) technique to predict the real-time tip position of surgical instruments. In the first stage, we propose a trajectory prediction algorithm integrated with instrumental morphological constraints to generate the initial trajectory. Then, a novel hybrid physical model is designed to estimate the trajectory's energy and mechanics. In the second stage, a point cloud clustering algorithm applies multi-information fusion to generate the maximum probability endpoint cloud. Then, an energy-weighted probability density function is introduced using statistical analysis to achieve the prediction of the 3D spatial location of instrument endpoints. Extensive experiments are conducted on 3D-printed human artery and vein models based on a high-precision electromagnetic tracking system. Experimental results demonstrate the outstanding performance of our method, reaching 98.2% of the achievement ratio and less than 3 mm of the average positioning accuracy. This work is the first 3D surgical navigation algorithm that entirely relies on vascular interventional robot sensors, effectively improving the accuracy of interventional surgery and making it more accessible for primary surgeons.

Effects of the Marinating Process on the Quality Characteristics and Bacterial Community of Leisure Dried Tofu.

Leisure dried tofu (LD-tofu) was prepared using two different marinating processes: the repeated heating method (RHM) and the vacuum pulse method (VPM). The quality characteristics and bacterial community succession of LD-tofu and the marinade were evaluated. The results showed that the nutrients in LD-tofu were easily dissolved into the marinade during the marinating process, while the protein and moisture content of RHM LD-tofu changed most dramatically. With the increase in marinade recycling times, the springiness, chewiness and hardness of VPM LD-tofu increased significantly. The total viable count (TVC) of the VPM LD-tofu decreased from the initial value of 4.41 lg cfu/g to 2.51-2.67 lg cfu/g as a result of the marinating process, which had a significant inhibitory effect. Additionally, 26, 167 and 356 communities in the LD-tofu and marinade were detected at the phylum, family and genus levels, respectively. Pearson correlation analysis showed that Pseudomonadaceae, Thermaceae and Lactobacillaceae were closely related to the quality characteristics of LD-tofu, whereas Caulobacteriaceae, Bacillaceae and Enterobacteriae were closely related to the marinade. The present work provides a theoretical basis for the screening of functional strains and quality control in LD-tofu and marinade.

Surface modification for improving immunoassay sensitivity.

Immunoassays are widely performed in many fields such as biomarker discovery, proteomics, drug development, and clinical diagnosis. There is a growing need for high sensitivity of immunoassays to detect low abundance analytes. As a result, great effort has been made to improve the quality of surfaces, on which the immunoassay is performed. In this review article, we summarize the recent progress in surface modification strategies for improving the sensitivity of immunoassays. The surface modification strategies can be categorized into two groups: antifouling coatings to reduce background noise and nanostructured surfaces to amplify the signals. The first part of the review summarizes the common antifouling coating techniques to prevent nonspecific binding and reduce background noise. The techniques include hydrophilic polymer based self-assembled monomers, polymer brushes, and surface attached hydrogels, and omniphobicity based perfluorinated surfaces. In the second part, some common nanostructured surfaces to amplify the specific detection signals are introduced, including nanoparticle functionalized surfaces, two dimensional (2D) nanoarrays, and 2D nanomaterial coatings. The third part discusses the surface modification techniques for digital immunoassays. In the end, the challenges and the future perspectives of the surface modification techniques for immunoassays are presented.

Integrating a phenotypic screening with a structural simplification strategy to identify 4-phenoxy-quinoline derivatives to potently disrupt the mitotic localization of Aurora kinase B.

We combined a mechanism-informed phenotypic screening (MIPS) assay with a structural simplification strategy to guide the discovery of compounds that disrupt the localization of the mitotic regulator, Aurora kinase B (AURKB), rather than inhibiting its catalytic activity. An initial hit 4-(4-methylthiophen-2-yl)-N-(4-(quinolin-4-yloxy)phenyl)phthalazin-1-amine was identified after screening an in-house library of small molecules and phenocopied the loss of function mutations in AURKB without inhibiting its catalytic activity. We isolated this hit compound activity to its 4-phenoxy-quinoline moiety. The fragment was further optimized into a class of new chemical entities that potently disrupt the mitotic localization of AURKB at low nanomolar concentrations and consequently elicit severe growth inhibition in diverse human cancer cell lines. A lead compound, N-(3-methoxy-5-(6-methoxyquinolin-4-yl)oxy)phenyl)acetamide possessed desirable pharmacokinetic properties such as AUC0-∞: 227.15 [ng∙h/mL/(mg/kg)]; Cmax: 3378.52 ng/mL T1/2: 3.52 h; and F%: 42 % and produced the AURKB-inhibitory phenotypes in a mouse xenograft model. A lead compound is a powerful tool for interrogating the regulation of AURKB and has the potential to be further developed as a first-in-class oncology therapeutic.

2-Phenoxy-3, 4'-bipyridine derivatives inhibit AURKB-dependent mitotic processes by disrupting its localization.

Activity-based drug screens have successfully led to the development of various inhibitors of the catalytic activity of aurora kinases (AURKs), major regulatory kinases of cell division. Disrupting the localization of AURKB, rather than its catalytic activity, represents a largely unexplored alternative approach to disabling AURKB-dependent processes. Localization disruptors could be just as specific as direct inhibitors of AURKB activity, may bypass their off-target and select on-target toxicities, and are likely less susceptible to drug resistance resulting from mutations of the AURKB catalytic site. In this study, we demonstrate that the pan-AURK inhibitor AMG900 works at a low concentration not by inhibiting the phosphorylation of H3 at Ser10, an AURKB substrate, but by disrupting the mitotic localization of AURKB. Structural deletion studies pinpoint this undescribed activity to the 2-phenoxy-3,4'-bipyridine moiety of AMG900. Guided by a mechanism-informed phenotypic screening (MIPS) assay, the drug fragment is optimized into a novel class of inhibitors that, at low nanomolar concentrations, can disable AURKB through disruption of its mitotic localization and have desirable oral PK properties. Hierarchical clustering of cell fitness profiles reveals that these compounds cluster with each other, rather than with known AURK inhibitors such as AMG900 and VX-680. Validation studies in mice demonstrate that compound 15a elicits mitotic arrest and apoptosis in NCI-H23 human lung adenocarcinoma xenografts, resulting in a pronounced suppression of tumor growth. The discovery and optimization of compounds that disrupt AURKB localization are successfully facilitated by MIPS. Our findings suggest that 2-phenoxy-3, 4'-bipyridine derivatives have the potential to be further developed as effective therapeutics for the treatment of malignancy by delocalizing AURKB.

Learning Skill Characteristics From Manipulations.

Percutaneous coronary intervention (PCI) has increasingly become the main treatment for coronary artery disease. The procedure requires high experienced skills and dexterous manipulations. However, there are few techniques to model PCI skill so far. In this study, a learning framework with local and ensemble learning is proposed to learn skill characteristics of different skill-level subjects from their PCI manipulations. Ten interventional cardiologists (four experts and six novices) were recruited to deliver a medical guidewire to two target arteries on a porcine model for in vivo studies. Simultaneously, translation and twist manipulations of thumb, forefinger, and wrist are acquired with electromagnetic (EM) and fiber-optic bend (FOB) sensors, respectively. These behavior data are then processed with wavelet packet decomposition (WPD) under 1-10 levels for feature extraction. The feature vectors are further fed into three candidate individual classifiers in the local learning layer. Furthermore, the local learning results from different manipulation behaviors are fused in the ensemble learning layer with three rule-based ensemble learning algorithms. In subject-dependent skill characteristics learning, the ensemble learning can achieve 100% accuracy, significantly outperforming the best local result (90%). Furthermore, ensemble learning can also maintain 73% accuracy in subject-independent schemes. These promising results demonstrate the great potential of the proposed method to facilitate skill learning in surgical robotics and skill assessment in clinical practice.

MLN2238 exerts its anti-tumor effects via regulating ROS/JNK/mitochondrial signaling pathways in intrahepatic cholangiocarcinoma.

Background: Intrahepatic Cholangiocarcinoma (iCCA) is a highly malignant tumor with limited treatment options that contributes largely to cancer-related deaths worldwide. Compared with traditional transcriptomic analysis, single-cell RNA sequencing (scRNA-seq) is emerging as a more advanced and popular tool for the in-depth exploration of cellular diversity and molecular complexity. As a next-generation proteasome inhibitor, MLN2238 presents better pharmacodynamics, pharmacokinetics, and therapeutic responses in various cancers. However, its effects and mechanisms of action in iCCA remain unknown. Methods: iCCA tumor heterogeneity was determined based on 4,239 qualified scRNA-seq data from 10 iCCA samples. The potential biological roles of proteasome-related genes in iCCA were investigated using a pseudo-trajectory reconstruction. The effect of MLN2238 on iCCA cell proliferation was estimated using the CCK-8, EdU, and clone formation assays. Flow cytometry was used to examine the effect of added MLN2238 on cell cycle and apoptosis levels. Autophagic flux was detected using AdPlus-mCherry-GFP-LC3B cells. ROS levels and mitochondrial membrane potential were determined using DCFH-DA probing and JC-1 staining. JNK activation and mitochondrial apoptosis were observed using western blotting and immunofluorescence microscopy, respectively. Finally, we used a tumor-bearing mouse model to validate its efficacy in vivo for iCCA treatment. Results: Proteasome-related genes were dysregulated in iCCA progression and expressed at higher levels in tumor tissues. MLN2238 suppressed cell proliferation, blocked the cell cycle in the G2/M phase, promoted apoptosis, and induced cytoprotective autophagy in iCCA cells. Furthermore, MLN2238 increased ROS levels and activated the JNK signaling pathway. Inhibition of ROS and JNK activation by NAC and SP600125 significantly reversed MLN2238-induced apoptosis. MLN2238 also suppressed the growth of iCCA tumors in vivo. Conclusion: Proteasome-related genes play pivotal roles in iCCA development. MLN2238, as a proteasome inhibitor, induces apoptosis in iCCA cells through ROS/JNK/mitochondrial signaling pathways, and hence, making MLN2238 a potential therapeutic choice for iCCA.

PINC: A Tool for Non-Coding RNA Identification in Plants Based on an Automated Machine Learning Framework.

There is evidence that non-coding RNAs play significant roles in the regulation of nutrient homeostasis, development, and stress responses in plants. Accurate identification of ncRNAs is the first step in determining their function. While a number of machine learning tools have been developed for ncRNA identification, no dedicated tool has been developed for ncRNA identification in plants. Here, an automated machine learning tool, PINC is presented to identify ncRNAs in plants using RNA sequences. First, we extracted 91 features from the sequence. Second, we combined the F-test and variance threshold for feature selection to find 10 features. The AutoGluon framework was used to train models for robust identification of non-coding RNAs from datasets constructed for four plant species. Last, these processes were combined into a tool, called PINC, for the identification of plant ncRNAs, which was validated on nine independent test sets, and the accuracy of PINC ranged from 92.74% to 96.42%. As compared with CPC2, CPAT, CPPred, and CNIT, PINC outperformed the other tools in at least five of the eight evaluation indicators. PINC is expected to contribute to identifying and annotating novel ncRNAs in plants.

nHA-loaded gelatin/alginate hydrogel with combined physical and bioactive features for maxillofacial bone repair.

Critical-sized maxillofacial bone defects have been a tough clinical challenge considering their requirements for functional and structural repair. In this study, an injectable in-situ forming double cross-linked hydrogel was prepared from gelatin (Gel), 20 mg/mL alginate dialdehyde (ADA), 4.5 mg/mL Ca2+ and borax. Improved properties of composite hydrogel might well fit and cover irregular geometric shape of facial bone defects, support facial structures and conduct masticatory force. We innovatively constructed a bioactive poly-porous structure by decoration with nano-sized hydroxyapatite (nHA). The highly ordered, homogeneous and size-confined porous surface served as an interactive osteogenic platform for communication and interplay between macrophages and bone marrow derived stem cells (BMSCs). Effective macrophage-BMSC crosstalk well explained the remarkable efficiency of nHA-loaded gelatin/alginate hydrogel (nHA@Gel/ADA) in the repair of critical-size skull bone defect. Collectively, the composite hydrogel constructed here might serve as a promising alternative in repair process of complex maxillofacial bone defects.

Functionality of Pea-Grass Carp Co-Precipitated Dual-Protein as Affected by Extraction pH.

Isoelectric solubilisation/co-precipitation (ISP) has been proven to be a better method than blending for preparing plant-animal dual-proteins, which can achieve synergies in the functional properties of heterologous proteins. This paper aims to investigate the effect of extraction pH on the functional properties of co-precipitated dual-protein. The basic composition, subunit composition, solubility, surface hydrophobicity, emulsification and gel properties of co-precipitated dual-protein (Co) prepared from pea and grass carp with pH (2.0, 3.0, 9.0, 10.0 and 11.0) were analysed in this study using ISP. The results showed that the functional properties of Co (Co9, Co10, Co11) prepared by alkali extraction were generally better than those prepared by acid extraction (Co2, Co3). Among them, Co10 has the highest vicilin/legumin α + ß value and solubility, while having the lowest surface hydrophobicity, making its emulsification and gel properties superior to other extraction pH values. This study provides an important method reference for preparing plant-animal Co with exceptional functional properties.

Hepatocellular carcinoma-derived exosomal miRNA-761 regulates the tumor microenvironment by targeting the SOCS2/JAK2/STAT3 pathway.

BACKGROUND: Exosomes and exosomal microRNAs have been implicated in tumor occurrence and metastasis. Our previous study showed that microRNA-761 (miR-761) is overexpressed in hepatocellular carcinoma (HCC) tissues and that its inhibition affects mitochondrial function and inhibits HCC metastasis. The mechanism by which exosomal miR-761 modulates the tumor microenvironment has not been elucidated. METHODS: Exosomal miR-761 was detected in six cell lines. Cell counting kit-8 (CCK-8) and transwell migration assays were performed to determine the function of exosomal miR-761 in HCC cells. The luciferase reporter assay was used to analyze miR-761 target genes in normal fibroblasts (NFs). The inhibitors AZD1480 and C188-9 were employed to determine the role of the Janus kinase 2/signal transducer and activator of transcription 3 (JAK2/STAT3) signaling pathway in the transformation of cancer-associated fibroblasts (CAFs). RESULTS: In this study, we characterized the mechanism by which miR-761 reprogrammed the tumor microenvironment. We found that HCC-derived exosomal miR-761 was taken up by NFs. Moreover, HCC exosomes affected the tumor microenvironment by activating NFs via suppressor of cytokine signaling 2 (SOCS2) and the JAK2/STAT3 signaling pathway. CONCLUSIONS: These results demonstrated that exosomal miR-761 modulated the tumor microenvironment via SOCS2/JAK2/STAT3 pathway-dependent activation of CAFs. Our findings may inspire new strategies for HCC prevention and therapy.

Elaboration of Cationic Soluble Soybean Polysaccharides-Epigallocatechin Gallate Nanoparticles with Sustained Antioxidant and Antimicrobial Activities.

Epigallocatechin gallate (EGCG) is easily oxidized by environmental stress elements, including light, heat, and oxygen; thus, its biological activities can be reduced or even lost when exposed to a natural environment. Here, soluble soybean polysaccharide (SSPS) was successfully etherized by 3-chloro-2-hydroxypropyl trimethylammonium chloride (CHPTAC), positively charged to extract cationic SSPS (CSSPS). Nanoparticles based on CSSPS can improve the encapsulation efficiency (EE) and sustained bioactivity of EGCG. The EE of EGCG by CSSPS was improved significantly as compared with that of SSPS due to the electrostatic interactions. Furthermore, the protective and sustained-release effects of CSSPS on EGCG in the EGCG-CSSPS nanoparticles (EGCG-CSSPS-NPs) markedly improved the sustained antioxidant and antimicrobial activities of EGCG, which was confirmed by the results of a salmon-preservation experiment. In addition, cytotoxicity tests showed that EGCG-CSSPS-NPs could effectively inhibit the proliferation of tumor cells but had no obvious toxicity to normal cells.

A systematic pan-cancer analysis of PXDN as a potential target for clinical diagnosis and treatment.

Peroxidasin (PXDN), also known as vascular peroxidase-1, is a newly discovered heme-containing peroxidase; it is involved in the formation of extracellular mesenchyme, and it catalyzes various substrate oxidation reactions in humans. However, the role and specific mechanism of PXDN in tumor are unclear, and no systematic pan-cancer studies on PXDN have been reported to date. This study employed data from multiple databases, including The Cancer Genome Atlas and The Genotype-Tissue Expression, to conduct a specific pan-cancer analysis of the effects of PXDN expression on cancer prognosis. Further, we evaluated the association of PXDN expression with DNA methylation status, tumor mutation burden, and microsatellite instability. Additionally, for the first time, the relationship of PXDN with the tumor microenvironment and infiltration of fibroblasts and different immune cells within different tumors was explored, and the possible molecular mechanism of the effect was also discussed. Our results provide a comprehensive understanding of the carcinogenicity of PXDN in different tumors and suggest that PXDN may be a potential target for tumor immunotherapy, providing a new candidate that could improve cancer clinical diagnosis and treatment.