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Background: Head and neck squamous cell carcinoma (HNSCC) is a significant global health challenge. The identification of reliable prognostic biomarkers and construction of an accurate prognostic model are crucial. Methods: In this study, mRNA expression data and clinical data of HNSCC patients from The Cancer Genome Atlas were used. Overlapping candidate genes (OCGs) were identified by intersecting differentially expressed genes and prognosis-related genes. Best prognostic genes were selected using the least absolute shrinkage and selection operator Cox regression based on OCGs, and a risk score was developed using the Cox coefficient of each gene. The prognostic power of the risk score was assessed using Kaplan-Meier survival analysis and time-dependent receiver operating characteristic analysis. Univariate and multivariate Cox regression were performed to identify independent prognostic parameters, which were used to construct a nomogram. The predictive accuracy of the nomogram was evaluated using calibration plots. Functional enrichment analysis of risk score related genes was performed to explore the potential biological functions and pathways. External validation was conducted using data from the Gene Expression Omnibus and ArrayExpress databases. Results: FADS3, TNFRSF12A, TJP3, and FUT6 were screened to be significantly related to prognosis in HNSCC patients. The risk score effectively stratified patients into high-risk group with poor overall survival (OS) and low-risk group with better OS. Risk score, age, clinical M stage and clinical N stage were regarded as independent prognostic parameters by Cox regression analysis and used to construct a nomogram. The nomogram performed well in 1-, 2-, 3-, 5- and 10-year survival predictions. Functional enrichment analysis suggested that tight junction was closely related to the cancer. In addition, the prognostic power of the risk score was validated by external datasets. Conclusions: This study constructed a gene-based model integrating clinical prognostic parameters to accurately predict prognosis in HNSCC patients.

Background: Sepsis is a life-threatening disease characterized by multiple organ failure due to excessive activation of the inflammatory response and cytokine storm. Despite recent advances in the clinical use of anti-cytokine biologics, sepsis treatment efficacy and improvements in mortality remain unsatisfactory, largely due to the mechanistic complexity of immune regulation and cytokine interactions.Methods: In this study, a broad-spectrum anti-inflammatory and endotoxin neutralization strategy was developed based on autologous “cryo-shocked” neutrophils (CS-Neus) for the management of sepsis. Neutrophils were frozen to death using a novel liquid nitrogen “cryo-shock” strategy. The CS-Neus retained the source cell membrane structure and functions related to inflammatory site targeting, broad-spectrum inflammatory cytokines, and endotoxin (LPS) neutralizing properties. This strategy aimed to disable harmful pro-inflammatory functions of neutrophils, such as cytokine secretion. Autologous cell-based therapy strategies were employed to avoid immune rejection and enhance treatment safety.Results: In both LPS-induced sepsis mouse models and clinical patient-derived blood samples, CS-Neus treatment significantly ameliorated cytokine storms by removing inflammatory cytokines and endotoxin. The therapy showed notable anti-inflammatory therapeutic effects and improved the survival rate of mice.Discussion: The results of this study demonstrate the potential of autologous “cryo-shocked” neutrophils as a promising therapeutic approach for managing sepsis. By targeting inflammatory organs and exhibiting anti-inflammatory activity, CS-Neus offer a novel strategy to combat the complexities of sepsis treatment. Further research and clinical trials are needed to validate the efficacy and safety of this approach in broader populations and settings.

Abstract The future high-energy muon colliders, featuring both high energy and low background, could play a critical role in our searches for new physics. The smallness of neutrino mass is a puzzle of particle physics. Broad classes of solutions to the neutrino puzzles can be best tested by seeking the partners of SM light neutrinos, dubbed as heavy neutral leptons (HNLs), at muon colliders. We can parametrize HNLs in terms of the mass m N and the mixing angle with ℓ-flavor U ℓ . In this work, we focus on the regime m N > O(100) GeV and study the projected sensitivities on the |U ℓ |2 − m N plane with the full-reconstructable HNL decay into a hadronic W and a charged lepton. The projected reach in |U ℓ | 2 leads to the best sensitivities in the TeV realm.

For continuous steel–concrete composite girder bridges based on the post-combined method, the conventional rectangular group studs contribute to the isolation of the steel girder and the concrete slab before prestressing, leading to the majority of prestress forces being introduced to the concrete slab. However, rectangular-group stud holes cause the prestress forces to be unevenly distributed. In this study, a new type of bellow-sleeved stud (BSS) was developed to mitigate the weakening effects of rectangular group stud holes on the slab. A steel corrugated sleeve with a diameter of 60 mm was employed to cover the stud, which served as an internal formwork to prevent the concrete from bonding with the root of the stud. After prestressing was complete, the steel sleeve was filled with ultra-high-performance concrete (UHPC) to create a reliable combination between the concrete slab and the steel girder. To investigate the shear performance of this new type of connection, eight push-out test specimens were designed, and finite-element models were built. This study drew a comparison between the BSS and the ordinary headed stud (OHS). The research findings suggested that the BSS is subjected to less bending–shear coupling and offers a 4.5% increase in shear strength and a 31.9% increase in shear stiffness compared with the OHS. The study also analyzed the structural parameters influencing the shear performance of the BSS. It is found that the steel sleeve of the BSS has a negative effect on shear performance, but this can be mitigated by infusing high-strength material into the sleeve. Furthermore, the study examined the effect of construction quality on shear performance and suggested that sleeve deviation and grout leakage considerably reduced the shear performance of the BSS. Accordingly, strict control over the construction quality of the BSS is necessary.

Abstract Background Skull base chordoma is a rare and aggressive tumour of the bone that has a high likelihood of recurrence. The fundamental differences in single cells between primary and recurrent lesions remain poorly understood, impeding development of effective treatment approaches. Methods To obtain an understanding of the differences in single cells between primary and recurrent chordomas, we performed single‐cell RNA sequencing and T‐cell/B‐cell receptor (BCR) sequencing. This allowed us to delineate the differences between the two types of tumour cells, tumour‐infiltrating lymphocytes, myeloid cells, fibroblasts and B cells. Copy number variants (CNVs) were detected and compared between the tumour types to assess heterogeneity. Selected samples were subjected to immunohistochemistry to validate protein expression. Fluorescence in situ hybridisation experiments, Transwell assays and xenograft mouse models helped verify the role of fibronectin 1 (FN1) in chordoma. Results Promoting natural killer (NK) cell and CD8_GZMK T‐cell function or inhibiting the transformation of CD8_GZMK T cells to CD8_ZNF683 T cells and promoting the transformation of natural killer T (NKT) cells to NK cells are promising strategies for preventing chordoma recurrence. Additionally, inhibiting the M2‐like activity of tumour‐associated macrophages (TAMs) could be an effective approach. Antigen‐presenting cancer‐associated fibroblasts (apCAFs) and dendritic cells (DCs) with high enrichment of the antigen‐presenting signature were enriched in primary chordomas. There were fewer plasma cells and BCR clonotypes in recurrent chordomas. Remarkably, FN1 was upregulated, had more CNVs, and was more highly secreted by tumours, macrophages, CD4 T cells, CD8 T cells and fibroblasts in recurrent chordoma than in primary chordoma. Finally, FN1 enhanced the invasion and proliferation of chordomas in vivo and in vitro. Conclusion Our comprehensive picture of the microenvironment of primary and recurrent chordomas provides deep insights into the mechanisms of chordoma recurrence. FN1 is an important target for chordoma therapy.

The clustered regularly interspaced short palindromic repeats (CRISPR)/associated protein (CRISPR/Cas) system has been exploited as an efficient gene editing tool with precise site specificity and high efficiency; the delivery of the CRISPR/Cas system is critical for the efficacy of therapeutics and remains challenging. DNA nanomaterials are widely utilized as promising delivery carriers for gene agents because of their excellent molecular recognition capabilities, sequence programmability, and biocompatibility. Herein, recent advances in DNA nanomaterials for the delivery of CRISPR/Cas systems are summarized. Based on their construction strategy, DNA nanomaterial‐based carriers are categorized as branched DNA‐based nanostructures or rolling circle amplification (RCA)‐based DNA nanostructures. Representative studies on the design of DNA nanomaterials as CRISPR/Cas system delivery carriers are highlighted. The current challenges and opportunities for the development of DNA nanomaterials for the delivery of CRISPR/Cas systems are also discussed. It is envisioned that with the development of DNA nanotechnology, DNA nanomaterials will open up new possibilities for CRISPR/Cas‐based therapeutics.

Nanomechanical resonator based on nanomaterials has great potential for high sensitive, high resolution and negligible energy consumed sensing devices. In this work, high frequency SiC nanobeam resonators with a diameter of ∼100 nm and with lengths of tens of micrometers were designed and demonstrated, which was produced based on the high quality monocrystal 3C-SiC nanowire material with high aspect ratio characteristics. The resonance behaviors of the nanobeam resonator was studied using an integrated mixing circuit measurement system with the pressure from 10−3 to 10−1 Torr. It was observed that the resonant frequency was up to 9.16 MHz, which was a distinguished essential feature for high sensitivity detection. The tunability of SiC nanobeam resonators was about 22%, which can be conveniently controlled by adjusting DC voltage on the gate. It was examined that the detection value of the SiC nanobeam resonator can be as low as zeptogram, which indicated its ultra-sensitive mass detection behaviors. The results show that the SiC nanobeam resonator has high resonant frequency, large tunability and high sensitivity, which is expected to be a high-performance device for biosensing and mechanical sensing.

The transcriptional network in TMJ disc development and injury remains poorly characterized. Here they generate a scRNA-seq atlas of mouse TMJ disc, and identify the resident progenitor population and how its transcriptional reprogramming contributes to disc repair.

Abstract Nanomechanical resonators are expected to be exceptional sensors for high‐performance mass detection, mechanical sensing, and signal processing. In this paper, zinc oxide nanobeam resonators are produced based on single‐crystal ZnO nanowire, which has a typical diameter down to a few nanometers and the length of hundreds of micrometers. This resonator has the characteristics of high aspect ratio nanobeam structure and reliable material. It is observed that the resonance frequency of ZnO nanobeam resonator is up to 1.47 MHz with a high quality factor of 2300 at room temperature, which will play a key role in high‐sensitivity mass detection. The mass detection of ZnO nanobeam resonator is demonstrated by depositing platinum atoms on the middle of the beam, which shows a sensitivity of 11.13 Hz fg−1 indicating its ultrasensitive mass detection capability. In addition, according to the experiment, the molecular dynamics simulations for the resonator is established, which shows that the detection resolution down to 0.2 yg at room temperature can be realized based on this resonator. The results show that the ZnO nanobeam resonator has enormous potential in ultrasensitive detection for biosensing and gas sensing.

Abstract Maxillofacial bone defects are commonly seen in clinical practice. A clearer understanding of the regulatory network directing maxillofacial bone formation will promote the development of novel therapeutic approaches for bone regeneration. The fibroblast growth factor (FGF) signalling pathway is critical for the development of maxillofacial bone. Klotho, a type I transmembrane protein, is an important components of FGF receptor complexes. Recent studies have reported the presence of Klotho expression in bone. However, the role of Klotho in cranioskeletal development and repair remains unknown. Here, we use a genetic strategy to report that deletion of Klotho in Osx-positive mesenchymal progenitors leads to a significant reduction in osteogenesis under physiological and pathological conditions. Klotho-deficient mensenchymal progenitors also suppress osteoclastogenesis in vitro and in vivo. Under conditions of inflammation and trauma-induced bone loss, we find that Klotho exerts an inhibitory function on inflammation-induced TNFR signaling by attenuating Rankl expression. More importantly, we show for the first time that Klotho is present in human alveolar bone, with a distinct expression pattern under both normal and pathological conditions. In summary, our results identify the mechanism whereby Klotho expressed in Osx+-mensenchymal progenitors controls osteoblast differentiation and osteoclastogenesis during mandibular alveolar bone formation and repair. Klotho-mediated signaling is an important component of alveolar bone remodeling and regeneration. It may also be a target for future therapeutics.

Buzz, squeak and rattle (BSR) noise has become apparent in vehicles due to the significant reductions in engine noise and road noise. The BSR often occurs in driving condition with many interference signals. Thus, the automatic BSR detection remains a challenge for vehicle engineers. In this paper, a rattle signal denoising and enhancing method is proposed to extract the rattle components from in-vehicle background noise. The proposed method combines the advantages of wavelet packet decomposition and mathematical morphology filter. The critical frequency band and the information entropy are introduced to improve the wavelet packet threshold denoising method. A rattle component enhancing method based on multi-scale compound morphological filter is proposed, and the kurtosis values are introduced to determine the best parameters of the filter. To examine the feasibility of the proposed algorithm, synthetic brake caliper rattle signals with various SNR ratios are prepared to verify the algorithm. In the validation analysis, the proposed method can well remove the disturbance background noise in the signal and extract the rattle components with well SNR ratios. It is believed that the algorithm discussed in this paper can be further applied to facilitate the detection of the vehicle rattle noise in industry.

Introduction: The SARS-CoV-2 pandemic has endangered global health, the world economy, and societal values. Despite intensive measures taken around the world, morbidity and mortality remain high as many countries face new waves of infection and the spread of new variants. Worryingly, more and more variants are now being identified, such as 501Y.V1 (B.1.1.7) in the UK, 501Y.V2 (B.1.351) in South Africa, 501Y.V3 in Manaus, Brazil, and B.1.617/B.1.618 in India, which could lead to a severe epidemic rebound. Moreover, some variants have a stronger immune escape ability. To control the new SARS-CoV-2 variant, we may need to develop and redesign new vaccines repeatedly. So it is important to investigate how our immune system combats and responds to SARS-CoV-2 infection to develop safe and effective medical interventions. Objectives: In this study, we performed a longitudinal and proteome-wide analysis of antibodies in the COVID-19 patients to revealed some immune processes of COVID-19 patients against SARS-CoV-2 and found some dominant epitopes of a potential vaccine. Methods: Microarray assay, Antibody depletion assays, Neutralization assay. Results: We profiled a B-cell linear epitope landscape of SARS-CoV-2 and identified the epitopes specifically recognized by either IgM, IgG, or IgA. We found that epitopes more frequently recognized by IgM are enriched in non-structural proteins. We further identified epitopes with different immune responses in severe and mild patients. Moreover, we identified 12 dominant epitopes eliciting antibodies in most COVID-19 patients and identified five key amino acids of epitopes. Furthermore, we found epitope S-82 and S-15 are perfect immunogenic peptides and should be considered in vaccine design. Conclusion: This data provide useful information and rich resources for improving our understanding of viral infection and developing a novel vaccine/neutralizing antibodies for the treatment of SARS-CoV-2.

The effect of aftershocks on the function recovery process of damaged structures after large earthquakes cannot be ignored in the resilience evaluation of buildings and communities. Based on the Monte Carlo simulation method, this paper proposes an approach to evaluate the seismic resilience of reinforced concrete frame considering the effect of mainshock-aftershock sequences. The findings of this study can provide a reference for the seismic performance evaluation of reinforced concrete frame structures under aftershocks.

In modern civil aeroengines, the hot streak and swirl at the exit of the combustor have a significant impact on the aerothermal performance of the high-pressure turbine (HPT). Due to the different design purposes of the combustor and the turbine, hot streak (HS) and swirl (SW) have different spatial distributions at the turbine inlet. This paper conducts a transient simulation of the GE E3 first-stage HPT, considering the swirl and hot streak facing the middle of the passage and the leading edge of the nozzle guide vane, respectively, and also explores the impact of positive and negative swirl. The results show that different clocking positions and swirl directions will change the incident angle and streamline distribution of the vane, thereby affecting the migration of the hot streak, the temperature and the Nusselt number distribution on the stator surface. In positive cases, the hot streak gathers in the upper part of the passage, and in negative cases, it is in the lower part. In middle cases, high-temperature areas appear in both vanes, and the distributions are opposite. Affected by the swirl, when facing the passage center, the pressure side stagnation lines of the two vanes are also different, so the Nusselt number distribution is opposite. When facing the leading edge, only one vane appears. Due to the insensitive interference of the rotor–stator, the transient migration of the hot streak in the rotor is mainly affected by the inherent secondary flow and the temperature at the inlet of the rotor (especially the conditions facing the leading edge), while the upstream residual swirl is less affected. Unlike the middle case, in leading edge cases, the hot streak is separated and needs to be re-mixed before entering the blade passage, so the temperature change in the blade cascade is relatively gentle. Based on this, the Nusselt number distribution on the surface of the blade is similar. In order to obtain the most favorable operating conditions for the engine, the turbine efficiency is used to compare the aerothermal performance under different conditions. Ultimately, it was found that the turbine with the hot streak and positive swirl directly facing the leading edge was the most efficient.

To study the mechanical behavior and energy-absorption capability, different lattices structures were designed and fabricated by using SLS technology with a raw material of Nylon. The quasi-static compression experiment and finite element simulation revealed the mechanical response and deformation mechanism of these structures. Meanwhile, the energy absorption capacity of the lattices structure was assessed by the impact resistance and corresponding calculations of specific energy absorption. The different design schemes were compared and analyzed under the same conditions. The results show that a minimal surface structure (MSS) has the best performance of compression properties. The designed composite scheme composed of the MSS and the BCC structures effectively enhances the impacting-bearing capability and improves the energy absorption performances.

At present, in the application of Bayesian network (BN) structure learning algorithm for structure learning, the network scale increases with the increase of number of nodes, resulting in a large scale of structure search space, which is difficult to calculate, and the existing learning algorithms are inefficient, making BN structure learning difficulty increase. To solve this problem, a BN structure optimization method based on local information is proposed. Firstly, it proposes to construct an initial network framework with local information and uses the Max-Min Parents and Children (MMPC) algorithm to construct an undirected network framework to reduce the search space. Then the particle swarm optimization (PSO) algorithm is used to strengthen the algorithm’s optimization ability by constructing a new position and velocity update rule and improve the efficiency of the algorithm. Experimental results show that under the same sample data set, the algorithm can obtain a more accurate BN structure while converging quickly, which verifies the correctness and effectiveness of the algorithm.

Mature vasculature is important for the survival of bioengineered tissue constructs, both in vivo and in vitro; however, the fabrication of fully vascularized tissue constructs remains a great challenge in tissue engineering. Indirect three-dimensional (3D) bioprinting refers to a 3D printing technique that can rapidly fabricate scaffolds with controllable internal pores, cavities, and channels through the use of sacrificial molds. It has attracted much attention in recent years owing to its ability to create complex vascular network-like channels through thick tissue constructs while maintaining endothelial cell activity. Biodegradable materials play a crucial role in tissue engineering. Scaffolds made of biodegradable materials act as temporary templates, interact with cells, integrate with native tissues, and affect the results of tissue remodeling. Biodegradable ink selection, especially the choice of scaffold and sacrificial materials in indirect 3D bioprinting, has been the focus of several recent studies. The major objective of this review is to summarize the basic characteristics of biodegradable materials commonly used in indirect 3D bioprinting for vascularization, and to address recent advances in applying this technique to the vascularization of different tissues. Furthermore, the review describes how indirect 3D bioprinting creates blood vessels and vascularized tissue constructs by introducing the methodology and biodegradable ink selection. With the continuous improvement of biodegradable materials in the future, indirect 3D bioprinting will make further contributions to the development of this field.

Multileg roundabout intersections are widely used in urban areas worldwide. However, its traffic organization and signal control are very complicated in the case of large traffic flow, and the signal optimization methods for conventional intersections are not suitable for applying directly to roundabouts due to the complexity of the operating process. Therefore, many scholars have focused on dedicated signal timing schemes for roundabouts, especially through tuning key parameters such as signal cycle and green light time. However, research and applications regarding variable phases at roundabouts are quite rare. To address this gap, this paper analyzes the traffic flow characteristics and capacity of multileg roundabouts and proposed a combined phase design model to achieve the maximum utilization of road capacity at roundabouts, which can generate the optimal phase scheme based on real-time traffic data. The feasibility of the combined phase design model is verified by a case study in Jinhua, China. The results indicate that the proposed combined phase design model can improve the applicability of actuated signal control and the reasonableness of signal timing for multileg roundabouts and thus further improve the roundabout efficiency.

The photovoltaic (PV) industry boom and increased PV applications call for better planning based on accurate and updated data on the installed capacity. Compared with the manual statistical approach, which is often time-consuming and labor-intensive, using satellite/aerial images to estimate the existing PV installed capacity offers a new method with cost-effective and data-consistent features. Previous studies investigated the feasibility of segmenting PV panels from images involving machine learning technologies. However, due to the particular characteristics of PV panel semantic-segmentation, the machine learning tools need to be designed and applied with careful considerations of the issue formulation, data quality, and model explainability. This paper investigated the characteristics of PV panel semantic-segmentation from the perspective of computer vision. The results reveal that the PV panel image data has several specific characteristics: highly class-imbalance and non-concentrated distribution; homogeneous texture and heterogenous color features; and the notable resolution threshold for effective semantic-segmentation. Moreover, this paper provided recommendations for data obtaining and model design, aiming at each observed character from the viewpoints of recent solutions in computer vision, which can be helpful for future improvement of the PV panel semantic-segmentation.

Parathyroid hormone (PTH) and parathyroid hormone-related protein (PTHrP) are two peptides that regulate mineral ion homeostasis, skeletal development, and bone turnover by activating parathyroid hormone 1 receptor (PTH1R). PTH1R signaling is of profound clinical interest for its potential to stimulate bone formation and regeneration. Recent pre-clinical animal studies and clinical trials have investigated the effects of PTH and PTHrP analogs in the orofacial region. Dental mesenchymal stem cells (MSCs) are targets of PTH1R signaling and have long been known as major factors in tissue repair and regeneration. Previous studies have begun to reveal important roles for PTH1R signaling in modulating the proliferation and differentiation of MSCs in the orofacial region. A better understanding of the molecular networks and underlying mechanisms for modulating MSCs in dental diseases will pave the way for the therapeutic applications of PTH and PTHrP in the future. Here we review recent studies involving dental MSCs, focusing on relationships with PTH1R. We also summarize recent basic and clinical observations of PTH and PTHrP treatment to help understand their use in MSCs-based dental and bone regeneration.

Ionizing radiation (IR)-induced vascular disorders slow down tissue regeneration. Exosomes derived from plasma exhibit potential to promote angiogenesis; meanwhile, the immune microenvironment plays a significant role in the process. This study aimed to test the hypothesis that plasma exosomes promote angiogenesis in irradiated tissue by mediating the immune microenvironment. First, we explored the impact of IR on macrophages. We found that cell viability and capacity for promoting angiogenesis were decreased in irradiated macrophages compared to control macrophages. Then, we isolated and characterized rat plasma-derived exosomes (RP-Exos) which were defined as 40–160 nm extracellular vesicles extracted from rat plasma. Afterward, we evaluated the effects of RP-Exos on the behaviors of irradiated macrophages. Our results show that RP-Exos promoted cell proliferation. More importantly, we found that RP-Exos stimulated the immune microenvironment in a manner that improved the angiogenesis-related genes and proteins of irradiated macrophages. The supernatant of macrophage cell cultures was used as conditioned medium to treat human primary umbilical vein endothelial cells, further confirming the pro-angiogenic ability of macrophages receiving RP-Exo intervention. RP-Exos were used in vivo to treat irradiated skin or calvarial defects in irradiated Sprague-Dawley male rats. The results indicated the ability of RP-Exos to enhance angiogenesis and promote tissue regeneration. Our research suggested the potential of plasma exosomes to be used as immunomodulatory agents with angiogenic capacity to treat radiation-associated vascular disorders and facilitate tissue repair.

Temporomandibular disorders (TMD) are diseases involving the temporomandibular joint (TMJ), masticatory muscles, and osseous components. TMD has a high prevalence, with an estimated 4.8% of the U.S. population experiencing signs and symptoms, and represents a financial burden to both individuals and society. During TMD progression, the most frequently affected site is the condylar cartilage. Comprising both fibrous and cartilaginous tissues, condylar cartilage has restricted cell numbers but lacks a vascular supply and has limited regenerative properties. In 2016, a novel stem cell niche containing a reservoir of fibrocartilage stem cells (FCSCs) was discovered in the condylar cartilage of rats. Subsequently, FCSCs were identified in mouse, rabbit, and human condylar cartilage. Unlike mesenchymal stem cells or other tissue-specific stem/progenitor cells, FCSCs play a unique role in the development and regeneration of fibrocartilage. More importantly, engraftment treatment of FCSCs has been successfully applied in animal models of TMD. In this context, FCSCs play a major role in the regeneration of newly formed cartilage. Furthermore, FCSCs participate in the regeneration of intramembranous bone by interacting with endothelial cells in bone defects. This evidence highlights the potential of FCSCs as an ideal stem cell source for the regeneration of oral maxillofacial tissue. This review is intended to detail the current knowledge of the characteristics and function of FCSCs in the TMJ, as well as the potential therapeutic applications of FCSCs. A deep understanding of the properties of FCSCs can thus inform the development of promising, biologically based strategies for TMD in the future.

The attitude tracking synchronization control of an orbit-predetermined leader–follower spacecraft swarm for the space moving target is discussed in this paper. The information exchange between all spacecraft is assumed to be discrete in time and on the undirected connected graph. Moreover, due to the demand for saving communication resources, wireless interference has been utilized, which allows all the neighbors of a spacecraft to access the same channel frequency spectrum simultaneously. Then the backstepping control algorithm is designed to let the spacecraft (β,A)-practically stably synchronize their states and track a time-varying trajectory in the presence of unknown fading channels. Finally, simulation is provided to verify that using the proposed control scheme, the attitude tracking synchronization can be achieved with high precision.

Osteoarthritis (OA) is a chronic degenerative joint disease and the major cause of joint pain and disability in the elderly. It is mainly characterized by articular cartilage degradation and subchondral bone remodeling. There are two main types of OA: natural occurring OA and secondary OA, mainly associated with aging and trauma, respectively. In this study, we established two OA models in rat knee joints to simulate the two types of OA, using the type II collagenase injection (CI) and anterior cruciate ligament transection (ACLT), respectively. After intervention for 2–6 weeks, cartilage and subchondral bone changes were detected in histological staining, immunochemistry, and micro-CT. Results showed that both models with typical pathology changes of OA were successfully induced, while the development and severity of OA process in the models were different. In ACLT rats, the cartilage damage was milder, lasted for a shorter time, and subchondral bone reconstruction occurred earlier, compared with the changes in CI rats. The cartilage damage was secondary to subchondral bone change in ACLT rats, while subchondral bone change was secondary to cartilage degeneration in CI rats. In conclusion, the interaction between cartilage and subchondral bone is different between the natural-occurring and secondary OA models. These two models not only suggest potential different mechanisms of the two types of OA, but also provide new directions for OA treatment and prevention.

Dental follicle progenitor/stem cells (DFPCs) are a group of dental mesenchyme stem cells that lie in the dental follicle and play a critical role in tooth development and maintaining function. Originating from neural crest, DFPCs harbor a multipotential differentiation capacity. More importantly, they have superiorities, including the easy accessibility and abundant sources, active self-renewal ability and noncontroversial sources compared with other stem cells, making them an attractive candidate in the field of tissue engineering. Recent advances highlight the excellent properties of DFPCs in regeneration of orofacial tissues, including alveolar bone repair, periodontium regeneration and bio-root complex formation. Furthermore, they play a unique role in maintaining a favorable microenvironment for stem cells, immunomodulation and nervous related tissue regeneration. This review is intended to summarize the current knowledge of DFPCs, including their stem cell properties, physiological functions and clinical application potential. A deep understanding of DFPCs can thus inspire novel perspectives in regenerative medicine in the future.

Pancreatic ductal adenocarcinoma (PDAC) elicits a dense stromal response that blocks vascular access because of pericyte coverage of vascular fenestrations. In this way, the PDAC stroma contributes to chemotherapy resistance, and the small-sized nanocarrier loaded with platinum has been adopted to address this problem which is not suitable for loading docetaxel (DTX). In the present study, we used the poly(d,l-lactide)-b-polyethylene glycol-methoxy (mPEG-b-PDLLA) to encapsulate DTX and got a small-sized polymeric micelle (SPM); meanwhile we functionalized the SPM’s surface with TAT peptide (TAT-PM) for a higher permeability. The diameters of both SPM and TAT-PM were in the range of 15–26 nm. In vitro experiments demonstrated that TAT-PM inhibited Capan-2 Luc PDAC cells growth more efficiently and induced more apoptosis compared to SPM and Duopafei. The in vivo therapeutic efficiencies of SPM and TAT-PM compared to free DTX was investigated on the orthotopic transplantation model of Capan-2 Luc. SPM exerted better therapeutic efficiency than free DTX, however, TAT-PM didn’t outperformed SPM. Overall, these results disclosed that SPM could represent a new therapeutic approach against pancreatic cancer, but its permeability to PDAC was not the only decisive factor.

To obtain the optimal Bayesian network (BN) structure, researchers often use the hybrid learning algorithm that combines the constraint-based (CB) method and the score-and-search (SS) method. This hybrid method has the problem that the search efficiency could be improved due to the ample search space. The search process quickly falls into the local optimal solution, unable to obtain the global optimal. Based on this, the Particle SwarmOptimization (PSO) algorithm based on the search space constraint process is proposed. In the first stage, the method uses dynamic adjustment factors to constrain the structure search space and enrich the diversity of the initial particles. In the second stage, the update mechanism is redefined, so that each step of the update process is consistent with the current structure which forms a one-to-one correspondence. At the same time, the "self-awakened" mechanism is added to prevent precocious particles frombeing part of the best. After the fitness value of the particle converges prematurely, the activation operation makes the particles jump out of the local optimal values to prevent the algorithm from converging too quickly into the local optimum. Finally, the standard network dataset was compared with other algorithms. The experimental results showed that the algorithmcould find the optimal solution at a small number of iterations and a more accurate network structure to verify the algorithm's effectiveness. [ABSTRACT FROM AUTHOR]