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Abstract Three‐dimensional bioactive, antioxidant, and porous nanocomposite scaffolds are inevitable to avoid dependency and disability in the life cycle. Herein, we develop a facile fabrication protocol of nano porous zinc doped hydroxyapatite (Zn‐HAp) scaffold enhanced by polysaccharide polymeric structure for bone tissue engineering applications. The bioactive nano scaffold exhibit opens porous assembly that sustains its flexible and robust nature and promotes efficient linking capability. Moreover, nano scaffold geometry and its porosity were controlled efficiently in various concentrations of zinc doped hydroxyapatite (Zn‐HAp) nanoparticles. Indeed, the composite scaffolds are retained in a dry shape with a suitable load‐bearing strength adjacent to the cancellous bone. The presence of zinc doped hydroxyapatite in the polymeric matrix of nano scaffold regulates its antibacterial response against different bacterial strains owing to its oxidative stress nature. The antioxidant and biocompatibility of nano‐scaffolds were investigated by DPPH (1,1‐diphenyl‐2‐picrylhydrazyl) scavenging behavior, the scavenging activity of ABTS (2,2‐azino‐bis‐3‐ethylbenzthiazoline‐ 6‐sulphonic acid) radical, and iron‐chelating potential. The observed results reveal that polysaccharide‐dependent porous geometry possesses adequate biocompatibility, radical scavenging behavior, and excellent antibacterial properties that validate it as a suitable candidate material for bone tissue implantation. The unprecedented radical scavenging and antioxidant bioactive nanocomposite scaffold are all set to reshape the future bone tissue implantation.

Zirconium sheet has been widely used in various fields, e.g., chemistry and aerospace. The surface scratches on the zirconium sheets caused by complex processing environment have a negative impact on the performance, e.g., working life and fatigue fracture resistance. Therefore, it is necessary to detect the defect of zirconium sheets. However, it is difficult to detect such scratch images due to lots of scattered additive noise and complex interlaced structural texture. Hence, we propose a framework for adaptively detecting scratches on the surface images of zirconium sheets, including noise removing and texture suppressing. First, the noise removal algorithm, i.e., an optimized threshold function based on dual-tree complex wavelet transform, uses selected parameters to remove scattered and numerous noise. Second, the texture suppression algorithm, i.e., an optimized relative total variation enhancement model, employs selected parameters to suppress interlaced texture. Finally, by connecting disconnection based on two types of connection algorithms and replacing the Gaussian filter in the standard Canny edge detection algorithm with our proposed framework, we can more robustly detect the scratches. The experimental results show that the proposed framework is of higher accuracy.

Strain engineering is an effective way to adjust the sensing properties of two-dimensional materials. In this paper, lateral heterojunctions (LHSs) based on arsenic and antimony have been designed along the armchair (AC) or zigzag (ZZ) edges. The adsorption and sensing characteristics of As/Sb LHSs to NO2 before and after applying different types of strain are calculated by first principles. The band gaps of all As/Sb heterostructures are contributed by As-p and Sb-p orbitals. In addition, the adsorption energy of As/Sb ZZ-LHS with −4% compression strain is the largest. Furthermore, its work function changes significantly before and after the adsorption of NO2. Meanwhile, strong orbital hybridizations near the Fermi level are observed and a new state is yielded after applying compressive strain. These results indicate that the As/Sb LHS with ZZ interface under −4% compression strain possesses the best sensing properties to NO2. This work lays the foundation for the fabrication of high-performance NO2 gas sensors. High-performance gas sensors can be used to track and regulate NO2 exposure and emission, as well as to track NO2 concentrations in the atmosphere and support the assessment of air quality.

Seed germination is an important stage of growth and reproduction and plays an important role in the life cycle of spermatophyte. It is co-determined by both genetic and environmental factors, and plant hormone regulation may be a highly conservative mechanism. Coix lachryrma-jobi (coix) is a grain with balanced nutrition for medicine and food and has substantial production value. It is an important part of agricultural production, and the efficiency of seed germination after sowing is a key link. In this study, coix species “small white shell Xingren” was used as the experimental material, and changes in gene expression levels and metabolite enrichment in seeds were identified by transcriptome and metabonomic analysis before and after seed germination. A total of 599 metabolites, including those from amino acid metabolism, sugar metabolism, and fatty acid metabolism, were significantly increased in germinating coix. Simultaneously, 10,929 differentially expressed genes (DEGs) were identified, and functional clusters of genes were also significantly clustered in hormone-signaling and glucose and fatty acid metabolism. In addition, this study found that a considerable number of hormone-signaling genes were significantly up-regulated during seed germination, activating multiple metabolic processes. The results of our conjoint analysis of multi omics showed that glucose and fatty acid metabolism played an important role in seed germination under hormone regulation.

Abstract The margins of protected areas are usually considered to have greater forest degradation, and given that most mammals live outside protected areas, researchers and conservation practitioners are increasingly recognizing that nonprotected areas must be incorporated into conservation strategy. However, the strategy used to manage these areas still involves increasing the size of protected areas, while not considering the habitat characteristics and requirements of the species. In this study, during a 3‐year period, camera trap and habitat characteristic surveys were used to estimate composition, diversity, and habitat characteristics of mammals to determine habitat characteristics or increase the size of protected areas what should be considered first for mammals’ conservation in a nonprotected area near the Huangshan Mountains in Anhui Province, China. From June 2017 to October 2019, 18 species of mammals were recorded, more than in any other protected area nearby. The linear model analysis results showed that habitat characteristics of mammals were different and showed a significant correlation with their relative abundance. Most species were related to vegetation characteristics, except primates (Macaca thibetana), and rodents (Leopoldamys edwardsi). Therefore, to establish conservation policies for nonprotected areas, habitat characteristics should be of prime concern, followed by increasing the size of protected areas to provide effective refuge areas for species conservation.

Deep learning technology has been extensively explored in pattern recognition and image processing areas. A multi-mode medical image fusion with deep learning will be proposed, according to the characters of multi-modal medical image, medical diagnostic technology and practical implementation, according to the practical needs for medical diagnosis. It cannot be only made up for the deficiencies of MRI, CT and SPECT image fusion, but also can be implemented in different types of multi-modal medical image fusion problems in batch processing mode, and can be effectively overcome the limitation of only one-page processing. The proposed method can greatly improve the fusion effect, image detail clarity and time efficiency. The experiments on multi-modal medical images are implemented to analyze performance, algorithm stability and so on. The experimental results prove the superiority of our proposed method in terms of visual quality and a variety of quantitative evaluation criteria.

Supplementation of magnesium (Mg2+) or its inclusion in biomaterials has beneficial effects for bone formation, but it has also been reported that it can have detrimental effects. Here, the authors analyse dose- and time-dependent effects of Mg2+ on bone regeneration and show that it can stimulate monocyte-macrophage lineage cells to support bone formation in the early phases of repair, but inhibit bone repair and mineralization in later stages by promoting a pro-inflammatory environment.

Aged hematopoietic stem cells (HSC) are characterised by reduced regenerative potential and a loss of quiescence. Here, the authors show nicotinamide riboside treatment shrinks the age-enlarged stem cell pool and shifts aged HSC functionally, metabolically and molecularly towards the young state.

ObjectivesClear cell renal cell carcinoma (ccRCC) is highly prevalent, prone to metastasis, and has a poor prognosis after metastasis. Therefore, this study aimed to develop a prognostic model to predict the individualized prognosis of patients with metastatic clear cell renal cell carcinoma (mccRCC).Patients and MethodsData of 1790 patients with mccRCC, registered from 2010 to 2015, were extracted from the Surveillance, Epidemiology and End Results (SEER) database. The included patients were randomly divided into a training set (n = 1253) and a validation set (n = 537) based on the ratio of 7:3. The univariate and multivariate Cox regression analyses were used to identify the important independent prognostic factors. A nomogram was then constructed to predict cancer specific survival (CSS). The performance of the nomogram was internally validated by using the concordance index (C-index), calibration plots, receiver operating characteristic curves, net reclassification improvement (NRI), integrated discrimination improvement (IDI), and decision curve analysis (DCA). We compared the nomogram with the TNM staging system. Kaplan–Meier survival analysis was applied to validate the application of the risk stratification system.ResultsDiagnostic age, T-stage, N-stage, bone metastases, brain metastases, liver metastases, lung metastases, chemotherapy, radiotherapy, surgery, and histological grade were identified as independent predictors of CSS. The C-index of training and validation sets are 0.707 and 0.650 respectively. In the training set, the AUC of CSS predicted by nomogram in patients with mccRCC at 1-, 3- and 5-years were 0.770, 0.758, and 0.757, respectively. And that in the validation set were 0.717, 0.700, and 0.700 respectively. Calibration plots also showed great prediction accuracy. Compared with the TNM staging system, NRI and IDI results showed that the predictive ability of the nomogram was greatly improved, and DCA showed that patients obtained clinical benefits. The risk stratification system can significantly distinguish the patients with different survival risks.ConclusionIn this study, we developed and validated a nomogram to predict the CSS rate in patients with mccRCC. It showed consistent reliability and clinical applicability. Nomogram may assist clinicians in evaluating the risk factors of patients and formulating an optimal individualized treatment strategy.

The band gap of lateral heterojunctions (LHSs) can be continuously tuned by changing the widths of their components. In this work, Sb/Bi LHSs based on monolayer Sb and Bi atoms with armchair and zigzag interfaces are constructed, respectively. It exhibits an atom’s number in planner-dependent tunable band gap and near-infrared range absorption characteristics. They are systematically studied by first-principles calculations. The widths are represented by the number (n) of Sb or Bi atom chains. When n increases from 2 to 8, the bandgaps of armchair Sbn/Bin LHSs decrease from 0.89 to 0.67 eV, and the band gaps of zigzag Sbn/Bin LHSs decrease from 0.92 to 0.76 eV. The partial density of states spectra indicate that the occupied states of the valence band are mainly provided by the Bi 6p orbitals. Additionally, the unoccupied states of the conduction band are always provided by the Sb 5p orbitals and Bi 6p orbitals. For Sbn/Bin LHSs, the absorption edge along XX and YY directions move toward the long wavelength direction. These results provide an approach for the applications of two-dimensional materials in near-infrared devices.

BackgroundContinuously growing of HIV incidence among men who have sex with men (MSM), as well as the low rate of HIV testing of MSM in China, demonstrates a need for innovative strategies to improve the implementation of HIV prevention. The use of machine learning algorithms is an increasing tendency in disease diagnosis prediction. We aimed to develop and validate machine learning models in predicting HIV infection among MSM that can identify individuals at increased risk of HIV acquisition for transmission-reduction interventions.MethodsWe extracted data from MSM sentinel surveillance in Zhejiang province from 2018 to 2020. Univariate logistic regression was used to select significant variables in 2018–2019 data (P < 0.05). After data processing and feature selection, we divided the model development data into two groups by stratified random sampling: training data (70%) and testing data (30%). The Synthetic Minority Oversampling Technique (SMOTE) was applied to solve the problem of unbalanced data. The evaluation metrics of model performance were comprised of accuracy, precision, recall, F-measure, and the area under the receiver operating characteristic curve (AUC). Then, we explored three commonly-used machine learning algorithms to compare with logistic regression (LR), including decision tree (DT), support vector machines (SVM), and random forest (RF). Finally, the four models were validated prospectively with 2020 data from Zhejiang province.ResultsA total of 6,346 MSM were included in model development data, 372 of whom were diagnosed with HIV. In feature selection, 12 variables were selected as model predicting indicators. Compared with LR, the algorithms of DT, SVM, and RF improved the classification prediction performance in SMOTE-processed data, with the AUC of 0.778, 0.856, 0.887, and 0.942, respectively. RF was the best-performing algorithm (accuracy = 0.871, precision = 0.960, recall = 0.775, F-measure = 0.858, and AUC = 0.942). And the RF model still performed well on prospective validation (AUC = 0.846).ConclusionMachine learning models are substantially better than conventional LR model and RF should be considered in prediction tools of HIV infection in Chinese MSM. Further studies are needed to optimize and promote these algorithms and evaluate their impact on HIV prevention of MSM.

Objective: This study aimed to assess the occurrence of chemotherapy-induced nausea and vomiting (CINV) in acute phase (24 h after chemotherapy) and delayed phase (2–5 days after chemotherapy) after standard antiemetic therapy and to explore the risk factors of CINV in the acute and delayed phases. Methods: This prospective and observational study analyzed the data of 400 breast cancer patients scheduled for chemotherapy in two hospitals. The self-report survey was developed to assess the occurrence of CINV and their associated factors. On day 2 and day 6 of chemotherapy, CINV was evaluated by the Multinational Association of Supportive Care in Cancer Antiemetic Tool (MAT). The incidence of acute and delayed CINV was expressed as frequency and percentage. Results: Among 400 patients, 29.8% and 23.5% experienced acute and delayed CINV, respectively. Logistic regression analysis showed that the risk factors associated with acute CINV included pain/insomnia, history of CINV, and highly emetogenic chemotherapy. The history of motion sickness (MS), history of CINV, number of chemotherapy cycles completed, and the incidence of acute CINV were significant risk factors for delayed CINV (all P < 0.05). Conclusions: The results of this study are helpful for nurses to identify high-risk patients with CINV, formulate effective treatment plans, and reduce the incidence of CINV.

Objective(s): Apoptosis of pulmonary alveolar septal cells is a pathogenesis characteristic of chronic obstructive pulmonary disease (COPD). Endothelial cell specific molecule-1 (ESM-1) plays an important role in apoptosis of cells. Here, we aimed to determine whether ESM-1 can involve in cell apoptosis in emphysematous mice and stable COPD patients. The sample size of patients was small, so two separate models were studied.Materials and Methods: At day 0, 11, and 22, murine were injected IP with 0.3 ml of PBS/Cigarette smoke extract, and euthanized at day 28. Lung tissues from 20 stable COPD patients and 12 Controls were evaluated. Serum was obtained from 25 stable COPD patients and 12 healthy Controls. Pulmonary function, pathology, pulmonary apoptosis index (AI), expression of vascular endothelial growth factor (VEGF), hepatocyte growth factor (HGF) and ESM-1 in lung tissue, and concentration of ESM-1 in serum were tested. Results: Protein expression of ESM-1, VEGF and HGF were decreased significantly in emphysematous mice (p

Abstract Thermal demagnetization furnaces are widely used paleomagnetic facilities for progressive removal of naturally acquired magnetic remanence or the imparting of well-controlled laboratory magnetization. An ideal thermal demagnetizer should maintain “zero” magnetic field in the sample chamber during thermal treatments. However, magnetic field noises, including the residual magnetic fields of the construction material and the induced fields caused by the alternating current (AC) in the heating element are always present, which can contaminate the paleomagnetic results at the elevated temperatures or especially for the magnetically weak samples. Here, we designed a new structure of heating wire named “straight core solenoid” to develop a new demagnetization furnace with ultra-low magnetic field noise. Simulation and practical measurements show that the heating current magnetic field can be greatly reduced by using the new technology. Thermal demagnetization experiments demonstrate that the new demagnetizer can yield low noise results even for weakly magnetic samples.

Abstract Background Prostate cancer (PCa) is a kind of malignancy occurring in the prostate gland. Substantial researches have proved the major role of long noncoding RNAs (lncRNAs) in PCa. However, the role of long intergenic non-protein coding RNA 1006 (LINC01006) in PCa has not been investigated yet. Methods RT-qPCR was used to examine the expression levels of LINC01006 and its downstream targets. The function of LINC01006 in PCa was tested by in vitro and in vivo assays. With application of RNA pull down, RNA immunoprecipitation (RIP) and luciferase reporter assays, the interaction among LINC01006, miR-34a-5p and disheveled associated activator of morphogenesis 1 (DAAM1) were verified. Results LINC01006 expression presented high in PCa cell lines. LINC01006 silencing suppressed cell proliferative, migratory, invasive capacities while accelerated apoptotic rate. Besides, LINC01006 knockdown also suppressed tumor growth and metastasis in vivo. Furthermore, miR-34a-5p, a tumor suppressor in PCa, was sponged by LINC01006. Moreover, DAAM1 was targeted by miR-34a-5p and promoted PCa progression. More intriguingly, rescue assays suggested that the inhibitory effect of LINC01006 knockdown on PCa development was offset by DAAM1 overexpression. Conclusions LINC01006 promoted PCa progression by sponging miR-34a-5p to up-regulate DAAM1, providing a novel target for PCa therapy.

Cardiac lymphomas have an extremely low incidence, with primary cardiac lymphomas accounting for only 0.5% of all extranodal lymphomas and 2% of primary cardiac tumors. Early diagnosis is critical for these tumors, which can proliferate rapidly. Here, we report a rare case of a 66-year-old man with primary cardiac lymphomas in the right atrium and right ventricle. This case establishes that two- and three-dimensional echocardiography is instructive in establishing the relationship of the mass and surrounding tissues and providing relevant hemodynamic information.

There is a growing attention regarding the toxic effect of microplastics pollutants. However, comprehensive phenotyping- and omics-based strategies for the toxicity evaluation of microplastics on the host remain to be established. To this end, we designed an encompassing phenotyping and multi-omics analysis method to detect the molecular interference of nanopolystyrene (PS)-exposed mice. The exposure time was 28 days with 1000 μg/L PS. We found that PS induced microbial alteration and metabolic disorders, which was closely related to immune disturbances. In addition, the altered expression of some genes related to immune dysregulation was observed. Interestingly, Bifidobacterium breve M-16V (B. breve M-16V) significantly inhibited Th2 and Th17 lymphocyte subset. Simultaneously, B.breve M-16V may activate MyD88 expression and promote Th1-related cytokine IL-12 production. In addition, B. breve M-16V may partially restore the gut microbiota dysbiosis. In summary, we demonstrated that the combined phenotyping and omics-based profiling established a practical framework that allowed us to gain a deeper understanding of the maladaptive consequences of PS exposure. It can be utilized to evaluate the toxicity of other environmental microplastics pollutants. Meanwhile, we found that B. breve M-16V has certain anti-inflammatory and immunomodulatory functions through host-microbiome interactions.

The olive tree (Olea europaea L.) is the most iconic fruit crop of the Mediterranean Basin. Since the plant was introduced to China in the 1960s, the summer rain climate makes it susceptible to pathogens, leading to some olive diseases. Olea europaea L. subsp. cuspidata is natively distributed in the Yunnan province of China. It has a smaller fruit size, lower oil content, and higher resistance compared to subsp. europaea, which makes subsp. cuspidata a critical germplasm resource to be investigated. Here, a high-quality genome of subsp. cuspidata with 1.38 Gb in size was assembled and anchored onto 23 pseudochromosomes with a mounting rate of 85.57%. It represents 96.6% completeness [benchmarking universal single-copy orthologs (BUSCO)] with a contig N50 of 14.72 Mb and a scaffold N50 of 52.68 Mb, which shows a significant improvement compared with other olive genomes assembled. The evaluation of the genome assembly showed that 92.31% of resequencing reads and an average of 96.52% of assembled transcripts could be aligned to the assembled genome. We found that a positively selected gene, evm.model.Chr16.1133, was shared with the results of transcriptome analysis. This gene belongs to the susceptible gene and negatively regulates the disease resistance process. Furthermore, we identified the Cercospora genus which causes the leaf spot disease in the infected leaves. The high-quality chromosome-level genomic information presented here may facilitate the conservation and utilization of germplasm resources of this subspecies and provide an essential genetic basis for further research into the differences in oil content and resistance between subsp. cuspidata and europaea.

Neuronal injury and apoptosis are important causes of the occurrence and development of many neurodegenerative diseases, such as cerebral ischemia, Alzheimer’s disease, and Parkinson’s disease. Although the detailed mechanism of some diseases is unknown, the loss of neurons in the brain is still the main pathological feature. By exerting the neuroprotective effects of drugs, it is of great significance to alleviate the symptoms and improve the prognosis of these diseases. Isoquinoline alkaloids are important active ingredients in many traditional Chinese medicines. These substances have a wide range of pharmacological effects and significant activity. Although some studies have suggested that isoquinoline alkaloids may have pharmacological activities for treating neurodegenerative diseases, there is currently a lack of a comprehensive summary regarding their mechanisms and characteristics in neuroprotection. This paper provides a comprehensive review of the active components found in isoquinoline alkaloids that have neuroprotective effects. It thoroughly explains the various mechanisms behind the neuroprotective effects of isoquinoline alkaloids and summarizes their common characteristics. This information can serve as a reference for further research on the neuroprotective effects of isoquinoline alkaloids.

The specific structure and diverse properties of hybrid organic–inorganic perovskite materials make them suitable for use in photovoltaic and sensing fields. In this study, environmentally stable organic–inorganic hybrid perovskite luminescent materials using Pb–MOF as a particular lead source were prepared using a mechanochemical method. Based on the fluorescence intensity of the MAPbBr3/MOF composite, the mechanized chemical preparation conditions of Pb–MOF were optimized using response surface methodology. Then, the morphological characteristics of the MAPbBr3/MOF composite at different stages were analyzed using electron microscopy to explore its transformation and growth process. Furthermore, the composite form of MAPbBr3 with Pb–MOF was studied using XRD and XPS, and the approximate content of MAPbBr3 in the composite material was calculated. Benefiting from the increase in reaction sites generated from the crush of Pb–MOF during mechanical grinding, more MAPbBr3 was generated with a particle size of approximately 5.2 nm, although the morphology of the composite was significantly different from the initial Pb–MOF. Optimal performance of MAPbBr3/MOF was obtained from Pb–MOF prepared under solvent-free conditions, with a milling time of 30 min, milling frequency of 30 Hz and ball–material of 35:1. It was also confirmed that the mechanochemical method had a good universality in preparing organic–inorganic hybrid perovskite/MOF composites.

With the goal of automatic sea ice mapping during the summer sea ice melt cycle, this study involved designing a fully automatic sea ice segmentation method based on a deep learning semantic segmentation network applicable to summer SAR images, which achieved high accuracy and the fully automatic extraction of sea ice segmentation during the summer ice melt cycle by optimizing the process, improving the pixel-level semantic segmentation network, and introducing high-resolution sea ice concentration features. Firstly, a convolution-based, high-resolution sea ice concentration calculation method is proposed and was applied to the deep learning task. Secondly, the proposed DF-UHRNet network was improved upon by designing high- and low-level fusion modules, introducing an attention mechanism, and reducing the number of convolution layers and other operations, and it can effectively fuse high- and low-scale semantic features and global contextual information based on reducing the overall number of network parameters, enabling it to achieve pixel-level classification. The results show that this method meets the needs associated with the automatic mapping and high-precision classification of thin ice, one-year ice, open water, and multi-year ice and effectively reduces the model size.

In order to prevent the problem of freezing pipe fracture in the process of artificial freezing construction, taking the main shaft freezing project of Shandong Yuncheng Mine as the background and based on the similarity theory, the similarity model test of freezing pipe in the composite stratum of the active freezing section is carried out. The test results show that the distribution of freezing temperature field in sand layer and clay layer is “W”-shape, and the temperature at the interface of outer ring pipe is slightly higher than that of the inner ring pipe. The change rate of freezing temperature can be divided into three stages: rapid decreasing section, slow decreasing section, and stable section. Compared with the clay layer, the sand layer has the shorter freezing closure time and the lower freezing average temperature. The frozen pipe is always in the state of vertical compression in the clay layer, while in the state of vertical compression first and then vertical tension in the sand layer. The maximum compressive strain in the clay layer is −305 με, which is equal to the vertical compressive stress of 64.1 MPa. The maximum tensile strain in the sand layer is 406 με, which is equivalent to the tensile stress of 85.2 MPa. The bending direction of different freezing pipes is different in the different soil layers. The maximum bending strain of the frozen pipe in the clay layer is 779 με, which is 2.6 times the vertical strain at the same location, corresponding to the bending stress of 163.4 MPa and reaching 0.69 times of the yield limit of frozen pipe, while the bending strain in the sand layer is very small. The vertical strain and bending strain of freezing pipes at the interface of soil layers are very small, but the bending strain is still dominant.

Deteriorated bone quality in osteoporosis challenges the success of implants, which are in urgent need for better early osseointegration as well as antibacterial property for long-term stability. As osteoporotic bone formation tangles with angiogenic clues, the relationship between osteogenesis and angiogenesis has been a novel therapy target for osteoporosis. However, few designs of implant coatings take the compromised osteoporotic angiogenic microenvironment into consideration. Here, we investigated the angiogenic effects of bioactive strontium ions of different doses in HUVECs only and in a co-culture system with BMSCs. A proper dose of strontium ions (0.2–1 mM) could enhance the secretion of VEGFA and Ang-1 in HUVECs as well as in the co-culture system with BMSCs, exhibiting potential to create an angiogenic microenvironment in the early stage that would be beneficial to osteogenesis. Based on the dose screening, we fabricated a bioactive titanium surface doped with zinc and different doses of strontium by plasma electrolytic oxidation (PEO), for the establishment of a microenvironment favoring osseointegration for osteoporosis. The dual bioactive elements augmented titanium surfaces induced robust osteogenic differentiation, and enhanced antimicrobial properties. Augmented titanium implant surfaces exhibited improved bone formation and bone–implant contact under comprehensive assessment of an in vivo bone–implant interface. In conclusion, zinc- and strontium-augmented titanium surface benefits the osseointegration in osteoporosis via promoting osteogenic differentiation, exerting antibacterial efficacy, and stimulating early angiogenesis.

Biohybrid micro- and nanorobots are integrated tiny machines from biological components and artificial components. They can possess the advantages of onboard actuation, sensing, control, and implementation of multiple medical tasks such as targeted drug delivery, single-cell manipulation, and cell microsurgery. This review paper is to give an overview of biohybrid micro- and nanorobots for smart drug delivery applications. First, a wide range of biohybrid micro- and nanorobots comprising different biological components are reviewed in detail. Subsequently, the applications of biohybrid micro- and nanorobots for active drug delivery are introduced to demonstrate how such biohybrid micro- and nanorobots are being exploited in the field of medicine and healthcare. Lastly, key challenges to be overcome are discussed to pave the way for the clinical translation and application of the biohybrid micro- and nanorobots.

Identification of the right parental combinations to maximize heterosis is the major goal of hybrid breeding, which could be achieved through identification of heterotic groups. The main objective of this study was to identify promising heterotic groups for future rice breeding programs. A collection of 359 rice genotypes of diverse origins of China and abroad, composed of inbreds, maintainers, restorers, and temperature-sensitive genic male sterile (TGMS) lines were genotyped using 10K SNP chips. The SNP data set was subjected to genomic analyses for estimation of genetic divergence and diversity. Significant variations were observed in the germplasm with the identification of six different genetic groups. These lines were assigned to the genetic groups independent of their origin. Taking an account of commercially used heterotic groups present in each cluster, three cytoplasmic male sterile (CMS) lines and 14 inbred and restorer lines with moderate to high genetic distances selected from five heterotic patterns were crossed and obtained 42 F1 hybrids. A total of 14 hybrids were found with significant maximum mid- and better-parent heterosis, namely, TaifengA × Guang122, TaifengA × Wushansimiao, and TaifengA × Minghui63 for earliness; Guang8A × Huazhan for dwarf stature; and Guang8A × Huanghuzhan-1, TaifengA × Yuexiangzhan, Guang8A × Minhui3301, TianfengA × Guang122, Guang8A × Yahui2115, TianfengA × Huanghuazhan, TianfengA × Minghui63, TianfengA × Minhui3301, TaifengA × Gui99, and Guang8A × Yuenongsimiao for yield and yield-related traits. Mid-parent and better-parent heterotic F1 hybrids were in positive correlation with the genetic distances as that manifested by commercially used heterotic groups, encouraging the use of genotypic data for identification of heterotic groups. Our study provides an informative strategy for the development of early maturing, lodging resistant and high-yielding commercial hybrids and cultivars in future heterosis breeding programs.

ObjectivesTo investigate the clinical and non-clinical characteristics that may affect the prognosis of patients with renal collecting duct carcinoma (CDC) and to develop an accurate prognostic model for this disease.MethodsThe characteristics of 215 CDC patients were obtained from the U.S. National Cancer Institute’s surveillance, epidemiology and end results database from 2004 to 2016. Univariate Cox proportional hazard model and Kaplan-Meier analysis were used to compare the impact of different factors on overall survival (OS). 10 variables were included to establish a machine learning (ML) model. Model performance was evaluated by the receiver operating characteristic curves (ROC) and calibration plots for predictive accuracy and decision curve analysis (DCA) were obtained to estimate its clinical benefits.ResultsThe median follow-up and survival time was 16 months during which 164 (76.3%) patients died. 4.2, 32.1, 50.7 and 13.0% of patients were histological grade I, II, III, and IV, respectively. At diagnosis up to 61.9% of patients presented with a pT3 stage or higher tumor, and 36.7% of CDC patients had metastatic disease. 10 most clinical and non-clinical factors including M stage, tumor size, T stage, histological grade, N stage, radiotherapy, chemotherapy, age at diagnosis, surgery and the geographical region where the care delivered was either purchased or referred and these were allocated 95, 82, 78, 72, 49, 38, 36, 35, 28 and 21 points, respectively. The points were calculated by the XGBoost according to their importance. The XGBoost models showed the best predictive performance compared with other algorithms. DCA showed our models could be used to support clinical decisions in 1-3-year OS models.ConclusionsOur ML models had the highest predictive accuracy and net benefits, which may potentially help clinicians to make clinical decisions and follow-up strategies for patients with CDC. Larger studies are needed to better understand this aggressive tumor.

The rapid development of medical micromotors draws a beautiful blueprint for the noninvasive or minimally invasive diagnosis and therapy. By combining stimuli-sensitive hydrogel materials, micromotors are bestowed with new characteristics such as stimuli-responsive shape transformation/morphing, excellent biocompatibility and biodegradability, and drug loading ability. Actuated by chemical fuels or external fields (e.g., magnetic field, ultrasound, light, and electric field), hydrogel-based stimuli-responsive (HBSR) micromotors can be utilized to load therapeutic agents into the hydrogel networks or directly grip the target cargos (e.g., drug-loaded particles, cells, and thrombus), transport them to sites of interest (e.g., tumor area and diseased tissues), and unload the cargos or execute a specific task (e.g., cell capture, targeted sampling, and removal of blood clots) in response to a stimulus (e.g., change of temperature, pH, ion strength, and chemicals) in the physiological environment. The high flexibility, adaptive capacity, and shape morphing property enable the HBSR micromotors to complete specific medical tasks in complex physiological scenarios, especially in confined, hard-to-reach tissues, and vessels of the body. Herein, this review summarizes the current progress in hydrogel-based medical micromotors with stimuli responsiveness. The thermo-responsive, photothermal-responsive, magnetocaloric-responsive, pH-responsive, ionic-strength-responsive, and chemoresponsive micromotors are discussed in detail. Finally, current challenges and future perspectives for the development of HBSR micromotors in the biomedical field are discussed.

A carbon dot-functionalized solution-gated graphene transistor (CD-SGGT) was designed and prepared via the modification of CDs on the gate of SGGT. The above CDs were hydrothermally synthesized using DL-thioctic acid and triethylenetramine as C, N and S sources. The average size of CDs was ~6.2 nm, and there were many amino and carboxyl groups on the CDs’ surfaces. The CDs was then used as a probe for preparation of CD-SGGT sensor for the cobalt(II) (Co2+) ions detection. The CD-SGGT sensor showed excellent sensitivity and high selectivity. Remarkably, the limit of detection (LOD) reached 10−19 M. The linear detection range was obtained from 10−19 to 10−15 M. Additionally, the CD-SGGT also showed fast response and good stability.

In network management, network measuring is crucial. Accurate network measurements can increase network utilization, network management, and the ability to find network problems promptly. With extensive technological advancements, the difficulty for network measurement is not just the growth in users and traffic but also the increasingly difficult technical problems brought on by the network’s design becoming more complicated. In recent years, network feature measurement issues have been extensively solved by the use of ML approaches, which are ideally suited to thorough data analysis and the investigation of complicated network behavior. However, there is yet no favored learning model that can best address the network measurement issue. The problems that ML applications in the field of network measurement must overcome are discussed in this study, along with an analysis of the current characteristics of ML algorithms in network measurement. Finally, network measurement techniques that have been used as ML techniques are examined, and potential advancements in the field are explored and examined.

The abuse and residues of antibiotics have a great impact on the environment and organisms, and their determination has become very important. Due to their low contents, varieties and complex matrices, effective recognition, separation and enrichment are usually required prior to determination. Molecularly imprinted polymers (MIPs), a kind of highly selective polymer prepared via molecular imprinting technology (MIT), are used widely in the analytical detection of antibiotics, as adsorbents of solid-phase extraction (SPE) and as recognition elements of sensors. Herein, recent advances in MIPs for antibiotic residue analysis are reviewed. Firstly, several new preparation techniques of MIPs for detecting antibiotics are briefly introduced, including surface imprinting, nanoimprinting, living/controlled radical polymerization, and multi-template imprinting, multi-functional monomer imprinting and dummy template imprinting. Secondly, several SPE modes based on MIPs are summarized, namely packed SPE, magnetic SPE, dispersive SPE, matrix solid-phase dispersive extraction, solid-phase microextraction, stir-bar sorptive extraction and pipette-tip SPE. Thirdly, the basic principles of MIP-based sensors and three sensing modes, including electrochemical sensing, optical sensing and mass sensing, are also outlined. Fourthly, the research progress on molecularly imprinted SPEs (MISPEs) and MIP-based electrochemical/optical/mass sensors for the detection of various antibiotic residues in environmental and food samples since 2018 are comprehensively reviewed, including sulfonamides, quinolones, β-lactams and so on. Finally, the preparation and application prospects of MIPs for detecting antibiotics are outlined.

Brucellosis is a highly contagious zoonosis chronic infectious disease with a strong latent capability to endanger human health and economic development via direct or indirect ways. However, the existing methods for brucellosis diagnosis are time-consuming and expensive as they require a tedious experimental procedure and a sophisticated experimental device and performance. To overcome these defects, it is truly necessary to establish a real-time, on-site, and rapid detection method for human brucellosis. Here, a lateral flow immunoassay (LFIA) with a rapid, sensitive, and alternative diagnostic procedure for human brucellosis with a high degree of accuracy was developed based on blue silica nanoparticles (SiNPs), Staphylococcal protein A (SPA), and surface Lipopolysaccharide of Brucella spp. (LPS), which can be applied for rapid and feasible detection of human brucellosis. To our knowledge, this is the first report that uses blue SiNPs as a signal probe of LFIA for the rapid diagnosis of human brucellosis. The precursor of blue SiNPs@SPA such as colorless SiNPs and blue SiNPs was synthesized at first and then coupled with SPA onto the surface of blue SiNPs by covalent bond to prepare blue SiNPs@SPA as a capture signal to catch the antibody in the brucellosis-positive serum. When SPA was combined with the antibodies in the brucellosis-positive serum, it was captured by LPS on the test line, forming an antigen–antibody sandwich structure, resulting in the T line turning blue. Finally, the results showed that it is acceptable to use blue SiNPs as visible labels of LFIA, and standard brucellosis serum (containing Brucella spp. antibody at 1,000 IU/ml) could be detected at a dilution of 10−5 and the detection limit of this method was 0.01 IU/ml. Moreover, it also demonstrated good specificity and accuracy for the detection of real human serum samples. Above all, the blue SiNPs-based LFIA that we developed provides a rapid, highly accurate, and inexpensive on-site diagnosis of human brucellosis, and shows great promise in clinical diagnostics for other diseases.

Cardiovascular disease is the leading cause of human death worldwide. Drug thrombolysis, percutaneous coronary intervention, coronary artery bypass grafting and other methods are used to restore blood perfusion for coronary artery stenosis and blockage. The treatments listed prolong lifespan, however, rate of mortality ultimately remains the same. This is due to the irreversible damage sustained by myocardium, in which millions of heart cells are lost during myocardial infarction. The lack of pragmatic methods of myocardial restoration remains the greatest challenge for effective treatment. Exosomes are small extracellular vesicles (EVs) actively secreted by all cell types that act as effective transmitters of biological signals which contribute to both reparative and pathological processes within the heart. Exosomes have become the focus of many researchers as a novel drug delivery system due to the advantages of low toxicity, little immunogenicity and good permeability. In this review, we discuss the progress and challenges of EVs in myocardial repair, and review the recent development of extracellular vesicle-loading systems based on their unique nanostructures and physiological functions, as well as the application of engineering modifications in the diagnosis and treatment of myocardial repair.

Abstract Background Exposure to cigarette smoke (CS) is a major threat to human health worldwide. It is well established that smoking increases the risk of respiratory diseases, cardiovascular diseases and different forms of cancer, including lung, liver, and colon. CS-triggered inflammation is considered to play a central role in various pathologies by a mechanism that stimulates the release of pro-inflammatory cytokines. During this process, epigenetic alterations are known to play important roles in the specificity and duration of gene transcription. Main text Epigenetic alterations include three major modifications: DNA modifications via methylation; various posttranslational modifications of histones, namely, methylation, acetylation, phosphorylation, and ubiquitination; and non-coding RNA sequences. These modifications work in concert to regulate gene transcription in a heritable fashion. The enzymes that regulate these epigenetic modifications can be activated by smoking, which further mediates the expression of multiple inflammatory genes. In this review, we summarize the current knowledge on the epigenetic alterations triggered by CS and assess how such alterations may affect smoking-mediated inflammatory responses. Conclusion The recognition of the molecular mechanisms of the epigenetic changes in abnormal inflammation is expected to contribute to the understanding of the pathophysiology of CS-related diseases such that novel epigenetic therapies may be identified in the near future.

Abstract Soft cable-driven systems have been employed in many assembled mechanisms, such as industrial robots, parallel kinematic mechanism machines, medical devices, and humaniform hands. A pre-stretching process is necessary to guarantee the quality of cable-driven systems during the assembly process. However, the stress relaxation of cables becomes a critical concern during long-term operation. This study investigates the effects of non-uniform deformation and long-term stress relaxation of the driven cables owing to moving parts in the system. A simple closed-loop cable-driven system is built and an alternating load is applied to it to replicate the operation of transmission cables. Under different experimental conditions, the cable tension is recorded and the boundary data are selected to be curve-fitted. Based on the fitted results, a formula is presented to estimate the stress relaxation of cables to evaluate the assembly performance. Further experimental results show that the stress relaxation is mainly caused by cable creep and the assembly procedure. To remove the influence of the assembly procedure, a modified pre-stretching assembly method based on the stress relaxation theory is proposed and verification experiments are performed. Finally, the assembly performance is optimized using a cable-driven surgical robot as an example. This paper proposes a dual stretching method instead of the pre-stretching method to assemble the cable-driven system to improve its performance and prolong its service life.

Traditional Chinese medicine (TCM) is one of the most internationally competitive industries. In the context of TCM modernization and internationalization, TCM-related research studies have entered a fast track of development. At the same time, research of TCM is also faced with challenges, such as matrix complexity, component diversity and low level of active components. As an interdisciplinary technology, molecular imprinting technology (MIT) has gained popularity in TCM study, owing to the produced molecularly imprinted polymers (MIPs) possessing the unique features of structure predictability, recognition specificity and application universality, as well as physical robustness, thermal stability, low cost and easy preparation. Herein, we comprehensively review the recent advances of MIT for TCM studies since 2017, focusing on two main aspects including extraction/separation and purification and detection of active components, and identification analysis of hazardous components. The fundamentals of MIT are briefly outlined and emerging preparation techniques for MIPs applied in TCM are highlighted, such as surface imprinting, nanoimprinting and multitemplate and multifunctional monomer imprinting. Then, applications of MIPs in common active components research including flavonoids, alkaloids, terpenoids, glycosides and polyphenols, etc. are respectively summarized, followed by screening and enantioseparation. Related identification detection of hazardous components from TCM itself, illegal addition, or pollution residues (e.g., heavy metals, pesticides) are discussed. Moreover, the applications of MIT in new formulation of TCM, chiral drug resolution and detection of growing environment are summarized. Finally, we propose some issues still to be solved and future research directions to be expected of MIT for TCM studies.