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Fracture nonunion remains a great challenge for orthopedic surgeons. Fracture repair comprises of three phases, the inflammatory, repair and remodeling stage. Extensive advancements have been made in the field of bone repair, including development of strategies to balance the M1/M2 macrophage populations, and to improve osteogenesis and angiogenesis. However, such developments focused on only one or the latter two phases, while ignoring the inflammatory phase during which cell recruitment occurs. In this study, we combined Stromal Cell-Derived Factor-1α (SDF-1α) and M2 macrophage derived exosomes (M2D-Exos) with a hyaluronic acid (HA)-based hydrogel precursor solution to synthesize an injectable, self-healing, adhesive HA@SDF-1α/M2D-Exos hydrogel. The HA hydrogel demonstrated good biocompatibility and hemostatic ability, with the 4% HA hydrogels displaying great antibacterial activity against gram-negative E. coli and gram-positive S. aureus and Methicillin-resistant Staphylococcus aureus (MRSA). Synchronously and sustainably released SDF-1α and M2D-Exos from the HA@SDF-1α/M2D-Exos hydrogel enhanced proliferation and migration of human bone marrow mesenchymal stem cell (HMSCs) and Human Umbilical Vein Endothelial Cells (HUVECs), promoting osteogenesis and angiogenesis both in vivo and in vitro. Overall, the developed HA@ SDF-1α/M2D-Exos hydrogel was compatible with the natural healing process of fractures and provides a new modality for accelerating bone repair by coupling osteogenesis, angiogenesis, and resisting infection at all stages.

The past two decades have witnessed the surge of smartphones and mobile applications. When going out, people will naturally open the map application (such as Google Maps) to find their current location (i.e., localization) and the way to their destination (i.e., navigation). At the same time, many people rely on their smartphones for localization when they walk into shopping malls, especially in large shopping centers. In outdoor environments, we usually leverage GPS to estimate our location. However, satellite signals are oftentimes weak inside buildings, resulting in large positioning errors and thus a poor navigation experience for users.

Total kidney volume (TKV) is a valuable readout in preclinical studies for autosomal dominant and autosomal recessive polycystic kidney diseases (ADPKD and ARPKD). Since conventional TKV assessment by manual contouring of kidney areas in all images is time-consuming, we developed a template-based semiautomatic image segmentation method (SAM) and validated it in three commonly used ADPKD and ARPKD models. SAM-based TKV measurements were fast, highly reproducible, and accurate across mouse and rat ARPKD and ADPKD models.

Xijier Qiaolongbatu,1,* Wenjuan Zhao,1,* Xucong Huang,2,3,* Feng Qian,1 Xinyi Yang,1 Jiaqi Wu,2 Cui Ma,2 Han Qu,1,2 Li Wang,3 Guorong Fan,2 Zhenghua Wu2 1Engineering Research Center of Cell & Therapeutic Antibody, Ministry of Education, Pharm-X Center, School of Pharmacy, Shanghai Jiao Tong University, Shanghai, People’s Republic of China; 2Department of Clinical Pharmacy, Shanghai General Hospital, Shanghai Jiaotong University School of Medicine, Shanghai, People’s Republic of China; 3School of Pharmacy, Chongqing Medical University, Chongqing, People’s Republic of China*These authors contributed equally to this workCorrespondence: Zhenghua Wu; Guorong Fan, Department of Clinical Pharmacy, Shanghai General Hospital, School of Medicine, Shanghai Jiaotong University, No. 85 Wujin Road, Shanghai, 200080, People’s Republic of China, Tel +86-133-0177-7863 ; +86-21-36123711, Email zhenghua.wu@shgh.cn; fanguorong@sjtu.edu.cnBackground: Schisandrol A (Sch A) is the main active ingredient of Schisandra chinensis (Turcz.) Baill. Our previous study showed that Sch A has anti-pulmonary fibrosis (PF) activity, but its metabolic-related mechanisms of action are not clear.Methods: Here, we explored the therapeutic mechanisms of Sch A on PF by ultra-high performance liquid chromatography coupled with tandem mass spectrometry (UPLC-MS/MS) metabolomics approach and network analysis. The metabolites of Sch A in mice (bleomycin + Sch A high-dose group) plasma were identified based on ultra-high performance liquid chromatography-quadrupole time-of-flight mass spectrometry (UPLC-Q-TOF/MS).Results: 32 metabolites were detected reversed to normal level after treating bleomycin (BLM)-induced PF mice with Sch A. The 32 biomarkers were enriched in energy metabolism and several amino acid metabolisms, which was the first report on the therapeutic effects of Sch A on PF through rescuing the disordered energy metabolism. The UPLC-Q-TOF/MS analysis identified 17 possible metabolites (including isomers) of Sch A in mice plasma. Network analysis revealed that Sch A and 17 metabolites were related to 269 genes, and 1109 disease genes were related to PF. The construction of the Sch A/metabolites-target-PF network identified a total of 79 intersection genes and the TGF-β signaling pathway was determined to be the main signaling pathway related to the treatment of PF by Sch A. The integrated approach involving metabolomics and network analysis revealed that the TGF-β 1-ID3-creatine pathway, TGF-β 1-VIM-carnosine pathway were two of the possible pathways Sch A regulated to modulate metabolic disorders, especially energy metabolism, and the metabolite of Sch A M5 was identified as a most likely active metabolite.Conclusion: The results suggested the feasibility of combining metabolomics and network analysis to reflect the effects of Sch A on the biological network and the metabolic state of PF and to evaluate the drug efficacy of Sch A and its related mechanisms.Graphical Abstract: Keywords: schisandrol A, pulmonary fibrosis, mechanism of action, network analysis, metabonomics

Staphylococcus aureus invades cells and persists intracellularly, causing persistent inflammation that is notoriously difficult to treat. Here we investigated host-pathogen interactions underlying intracellular S. aureus infection in macrophages and discovered that the endoplasmic reticulum (ER) is an important cellular compartment for intracellular S. aureus infection. Using CRISPR-Cas9 guide RNA library screening, we determined that the autocrine motility factor receptor (AMFR), an ER-resident E3 ubiquitin ligase, played an essential role in mediating intracellular S. aureus-induced inflammation. AMFR directly interacted with TAK1-binding protein 3 (TAB3) in the ER, inducing K27-linked polyubiquitination of TAB3 on lysine 649 and promoting TAK1 activation. Moreover, the virulence factor γ-haemolysin B (HIgB) of S. aureus bound to the AMFR and regulated TAB3. Our findings highlight an unknown role of AMFR in intracellular S. aureus infection-induced pneumonia and suggest that pharmacological interruption of AMFR-mediated TAB3 signalling cascades and HIgB targeting may prevent invasive staphylococci-mediated pneumonia.

TiO2 loaded with zinc oxide (ZnO/TiO2) catalysts were prepared and showed good catalytic performance of the transesterification of diphenyl carbonate (DPC) with 1,4-butanediol (BDO) to produce polycarbonate diol (PCDL).

Inferential modeling has been of significance for modern manufacturing in estimating the quality-related process variables. As an effective inferential model, probabilistic slow feature analysis (PSFA) has gained attention in regression tasks to interpret dynamic properties with a slowness preference. However, PSFA is often challenged by the nonlinear sequential data due to its linear state-space structure. In this study, a new nonlinear extension of PSFA is proposed under the deep learning framework to enhance the dynamic feature extraction with limited labels, incorporating variational inference and Monte Carlo inference to derive the objective function. The proposed model considers the relevance of inputs with outputs as the input weights to upgrade prediction performance. The proposed model is verified through an industrial hydrocracking process to predict diesel yield with missing labels ranged from 0% to 50%, and the root mean squared error is reduced by at least 8.78% compared to PSFA.

Access to anticancer drugs has been a critical health issue in China for many years. We retrospectively analyzed the novel anticancer drugs approved in the United States (US) between 2010 and 2021 to assess the evolving landscape of the drug lags in China by taking Japan and the European Union (EU) as comparisons. The absolute and relative lags of drug initial approval (DIA) and indication approval were calculated between China (or Japan/European Union) and the US based on the US approval date of novel agents, the duration was divided into 2010-2015 and 2016-2021. Overall, 123 (244 indications) new molecular entities (NMEs) approved in the United States were included, of which 58 (94 indications), 72 (128 indications), and 99 (170 indications) NMEs were also approved in China, Japan, and the European Union, respectively. The absolute lags of DIA and indications for approval in China improved dramatically in 2016-2021 compared with 2010-2015. Similarly, the relative DIA and indication approval lags in China decreased significantly in 2016-2021. The median review lags for DIA of China in 2016-2021 were comparable to Japan but dramatically lower than that of the European Union. Nevertheless, China had significantly longer median submission lags for DIA (28 months) in 2016-2021 than that of Japan (6 months) and the European Union (1 month). Although the absolute and relative lags of anticancer drugs in China had been initially addressed, 53% of NMEs and 61% of indications were still not approved for cancers in China compared with the United States. Therefore, China should adopt steps to further reduce drug lags.

Objective To explore whether the variants in non MHC proteasome gene are associated with AS and explain the role of the variant in the disease. Material and methods Case-control analysis to identify AS predisposition genes; dual-luciferase reporter assay, immunoblot analysis and osteoclastogenesis assays to detect the function of the positive variant. Affected individuals were diagnosed according to the modified New York Criteria by at least two experienced rheumatologists, and rechecked by another rheumatologist. Results The study included 1037 AS patients and 1014 no rheumatic and arthritis disease controls. The main age of AS onset is between 16 and 35 years old. HLA-B27-positive subjects comprised 90.0% of patients. A nonsynonymous SNP rs12717 in proteasome gene PSMB1 significantly associated with AS. Individuals with CC genotype had a higher onset risk compared with those with GG/GC genotypes (OR = 1.89, P = 0.0047). We also discovered that PSMB1 regulates the receptor activator of nuclear factor-κB (RANK)/RANK ligand (RANKL) signalling pathway and the disease-associated variant PSMB1-Pro11 significantly inhibits RANKL-induced NF-κB pathway in osteoclast differentiation via the degradation of IKK-β compared with PSMB1-Ala11. RANKL induced osteoclast differentiation was significantly lower in primary monocyte osteoclast precursor from individuals with genotype PSMB131C/31C compared with individuals with genotype PSMB131G/31G. Conclusions These results reveal a novel understanding of the bone formation and reabsorbing imbalance in AS. The new bone formation phenotype can be attributed to the inhibition of osteoclast differentiation by a more functional PSMB1 gene.

Dissipative state and output estimation for continuous time-delay systems pose a significant challenge when an unlimited number of pointwise and general distributed delays (DDs) are concerned. We propose an effective solution to this open problem using the Krasovski\u{\i} functional (KF) framework in conjunction with a quadratic supply rate function, where both the plant and the estimator can accommodate an unlimited number of pointwise and general DDs. All DDs can contain an unlimited number of square-integrable kernel functions, which are treated by an equivalent decomposition-approximation scheme. This novel approach allows for the factorization or approximation of any kernel function without introducing conservatism, and facilitates the construction of a complete-type KF with integral kernels that can encompass any number of differentiable (weak derivatives) and linearly independent functions. Our proposed solution is expressed as convex semidefinite programs presented in two theorems along with an iterative algorithm, which eliminates the need of nonlinear solvers. We demonstrate the effectiveness of our method using two challenging numerical experiments, including a system stabilized by a non-smooth controller., Comment: submitting to TAC

Graves' disease (GD) is an autoimmune disease, the incidence of which is increasing yearly. GD requires long-life therapy. Therefore, the potential immune-related biomarkers of GD need to be studied.In our study, differentially expressed genes (DEGs) were derived from the online Gene Expression Omnibus (GEO) microarray expression dataset GSE71956. Protein‒protein interaction (PPI) network analyses were used to identify hub genes, which were validated by qPCR. GSEA was used to screen potential pathways and related immune cells. Next, CIBERSORT analysis was used to further explore the immune subtype distribution pattern among hub genes. ROC curves were used to analyze the specificity and sensitivity of hub genes.44 DEGs were screened from the GEO dataset. Two hub genes, EEF1A1 and EIF4B, were obtained from the PPI network and validated by qPCR (p 0.05). GSEA was conducted to identify potential pathways and immune cells related to these the two hub genes. Immune cell subtype analysis revealed that hub genes had extensive associations with many different types of immune cells, particularly resting memory CD4Our study revealed two hub genes, EEF1A1 and EIF4B, that are associated with resting memory CD4

Several Chinese universities are setting up systems to anticipate students’ academic performance and to offer them academic early notifications to boost their students’ performance effectively. Chinese-Foreign Cooperation in Running Schools (CFCRS) is one of China’s fastest-growing sectors of education. The academic achievement of CFCRS students is lower than that of students in noncooperatively organized programs. A realistic and timely academic prediction is critical to identifying students at risk of academic failure and providing them with the support they demand. A unique CNN-BiLSTM-AM approach will be used in this study to forecast the academic achievement of CFCRS learners more accurately and efficiently. Convolutional neural networks (CNN), bidirectional long-short-term memory (Bi-LSTM), and attention mechanism (AM) form the basis of this technique. The characteristics of the input information are extracted using a CNN. For good forecasting accuracy, AM is employed to obtain the contribution of characteristic levels on student results in various teaching methods. Initially, the Chinese students’ datasets are gathered from the big data for this investigation and are partitioned into 4 different groups. Four teaching methods are provided in groups. The proposed approach is used to forecast the performance of the students. Finally, the performance of the proposed approach is examined and compared with certain existing approaches to obtain the proposed approach with maximum correctness. The findings of this research are indicated in chart formations by employing the Origin tool.

To explore the effects of high cervical spinal cord electrical stimulation (cSCS) on the recovery of neurological function and its possible mechanism in rats with traumatic brain injury (TBI). 72 rats were randomly divided into: (1) a sham group; (2) a traumatic brain injury (TBI) group; (3) a TBI+cSCS group; (4) a LY294002+TBI+cSCS group. The degree of neurological dysfunction was evaluated by modified Neurological severity score (mNSS). The pathological changes of the brain tissue in the injured area were observed by HE staining, and the apoptosis of neuron cells were observed by TUNEL staining. The expressions of BDNF and VEGFmRNA were detected by polymerase chain reaction (PCR), and the expressions of p-AKT, AKT, Bcl-2, Bax and caspase-3 proteins were detected by western blot. Compared with that of the TBI and LY294002+TBI+cSCS groups, the mNSS of the TBI+cSCS group were significantly lower on day 3 and 7 ( P0.05). Compared with that in the TBI and LY294002+TBI+cSCS groups, the apoptosis of neuron cells in the TBI+cSCS group decreased significantly ( P0.05). Compared with the TBI and LY294002+TBI+cSCS group, the expression of Bcl-2 protein increased and the expressions of Bax and Caspase-3 proteins decreased in the TBI+cSCS group ( P0.05). Compared with that in the TBI and LY294002+TBI+cSCS groups, the intensity of p-Akt/Akt in the TBI+cSCS group increased ( P0.05). We found that cSCS had a protective effect on neuron cells after craniocerebral injury and could improve neurological dysfunction in rats, the mechanism of which might be that cSCS made the PI3K/Akt pathway more active after TBI.

Individuals with autosomal dominant polycystic kidney disease have a higher incidence of stone formation than the general population. However, there are no cystic animal models known to develop stones. Cystic mice compound heterozygous for hypomorphic Pkd1(V) and Pkd1(RC) alleles develop cystic kidneys within a few weeks of birth but live beyond 20 wk of age, allowing for the study of cystic comorbidities including stone formation. Cystic Pkd1(V)(/)(RC) mice were euthanized at 3, 13, or 26 wk of age, and their kidneys were analyzed by microcomputed tomography (µCT) for stone formation. Mice had occasional mineral aggregates that could be detected by µCT analysis at 3 wk of age. At 13 or 26 wk of age, numerous white masses were visible beneath the kidney surface. µCT analysis confirmed the masses to be large mineral stone deposits throughout the renal cortex, with mineral content increasing with age. Staining of histological sections with alizarin red and von Kossa suggested that the stone deposits were composed primarily of calcium and phosphate. Microdissection confirmed stones localized within cyst lumens. Analysis of individual stones by µCT and infrared spectroscopy confirmed apatite mineral composition. Urinalysis revealed elevated levels of phosphate and citrate at 3 wk of age and lower pH and elevated levels of calcium and citrate at 13 wk of age, suggesting altered phosphate and calcium homeostasis as a potential cause of mineralization and renal stone formation. This is the first animal model exhibiting overt kidney stone formation in the context of cystic kidney disease. NEW & NOTEWORTHY Compound heterozygous Pkd1(V/RC) mice were found to form calcium phosphate-containing stones within cysts of the renal cortex by 13 wk of age. This is the first polycystic kidney disease animal model exhibiting spontaneous stone formation. A growing body of evidence suggests a link between renal stone formation and cystic kidney disease. This mouse model may be useful for studying the interplay between stone and cyst formation and the functional role of polycystins in mineral homeostasis.

Glucocorticoid-induced TNF receptor-related (GITR) can act as a co-stimulatory receptor, representing a potential target for safely enhancing immunotherapy efficacy. GITR is triggered by a GITR ligand or an agonist antibody and activates CD8

Multi-agent systems (MASs) provide an effective means for coordinating a large number of spatially distributed and networked agents (or nodes, subsystems) such that the desired cooperative tasks can be accomplished with promising reliability, manipulability, scalability, and efficiency. One core issue in the study of MASs is the distributed control protocol design that depends on the local and real-time information exchanges among interacting agents over networks to achieve the anticipated cooperative control objectives. However, network-enabled information sharing and increasing connectivity in practical MASs present several attack factors for malicious adversaries, thereby rendering secure control of MASs fundamentally significant. This paper provides a brief survey of systems and control technologies that have been available for addressing various secure control problems of MASs in the face of various malicious attacks. First, system models that have been commonly adopted to achieve the distributed cooperative control design of MASs are outlined. Second, attacks are classified based on different configuration layers. Then, the existing attack models and countermeasures on communication layer and agent layer are systematically examined, respectively. Also the secure control methods for MASs that have been adequately employed to handle these attacks are surveyed. Finally, several challenging issues are envisioned for potential future research.

One of the primary purposes of seismic stratigraphy is to evaluate the components of seismic layer relationships within a depositional chronology. Prestack seismic images contain a wealth of information, such as variations in the offset and azimuth of a seismic event, and naturally produce higher-resolution seismic facies analysis results than poststack data. However, prestack data usually suffer from potential unreliability issues due to low signal-to-noise ratios. As this is often overlooked, the present facies analysis methods sometimes fail to extract accurate features from prestack images, which inevitably influences the facies analysis results. To address this issue, this article provides a robust data-driven technique for extracting offset-temporal features via shearlet transform-based deep convolution autoencoders (STCAEs). Unlike the present facies analysis in the time domain, STCAE can optimally represent prestack images at multiple scales and directions through the two-dimensional shearlet transform, which preserves fine edges while suppressing noise in prestack images. Subsequently, robust features are extracted from prestack images in a data-driven manner through a contractive convolutional autoencoder network. We compare our method with other advanced methods and demonstrate the advantages of the proposed approach in classifying seismic layers in prestack data.

The core challenges to automatic full-horizon tracking are how to establish a potential local connection relationship between the horizon points, conduct accurate global diffusion in a three-dimensional space, and finally, how to form a complex horizon surface. The existing attribute-based horizon-tracking methods based on waveform similarity, dip guidance, and RGT (relative geological time) can not solve the problems of local connection and global diffusion at the same time. In view of this challenge, this paper proposes an automatic 3D seismic horizon-tracking method based on global corrugated diffusion, which can completely integrate local connection and global diffusion so that all horizons in the whole data volume can be interpreted simultaneously. For the problem of local horizon-point connection, this paper uses the correlation between seismic trace pairs based on DTW (dynamic time warping) correlation to mine the connection mode between horizon points. For the global diffusion problem, this paper proposes the realization of global modeling based on the relationship between seismic samples, constructing a complex 3D horizon through a central ripple-diffusion process. The example shows that the horizon tracked by this method well reflects the original stratum occurrence and stratum-contact relationship, retains the structural details, accurately reflects the structural shape, and realizes automatic tracking across faults.

Mechanical properties are among the crucial parameters for multilayer hybrid perovskite-based devices. Here, the mechanical properties of the high-quality single-crystalline MAPbX3 (MA = CH3NH3, X = Cl, Br, I), including the hardness (H) and Young’s modulus (E), are systematically studied using the three-dimensional nanoindentation (3D nanoindentation) method. In the sequence of Cl, Br, and I, the hardness and Young’s modulus of MAPbX3 decrease gradually. The hardness of MAPbX3 ranges from 0.31 to 0.57 GPa, and Young’s modulus values are less than 30 GPa. The low hardness and Young’s modulus are attributed to the weak lattice framework composed of Pb-X and the weak hydrogen bond between CH3NH3+ and the octahedron. The relationship between the hardness and Young’s modulus of MAPbX3 is also described. Generally, this work provides the favorable parameters required to further support the design and modification of investigations regarding perovskite-based devices.

In computer vision, the detection and tracking of moving objects has become a hot topic today. The target tracking technology in this paper refers to the visual tracking of the ground moving target by the aircraft during the flight. Since both the aircraft and the target are moving, there are background and two motion vectors composed of the target and the background in the acquired image. Therefore, this paper proposed a research on the location and tracking of environmental pollution sources under multi-UAV vision based on the target motion model. This paper first introduced the UAV target tracking technology, and analyzed the development history and types of UAVs in detail. Then, based on the increasingly serious environmental pollution, this paper proposed to use UAV sensing technology to locate the pollution source. Finally, in the experimental part, this paper tested the UAV flight platform, and carried out the actual operation and positioning of the pollution source. The final experimental results showed that within 0 ~ 360 s, the attitude angle obtained by the gradient descent method had no divergence phenomenon, which could effectively reduce the error caused by the integration; the inclination angle deviation of the two groups of experimental equipment was within ±2.5°, the roll angle deviation was within ±3°, and the deviation angle was relatively large at some moments, but the average deviation was only 0.8°.