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This study aimed to investigate the characteristics of different varieties of camellia oils and their diacylglycerol (DAG)-enriched derivatives in terms of triacylglycerol (TAG) species, bioactive components, volatile compounds, and antioxidant activity. Six types of camellia oils, including C. oleifera (C.O), C. semiserrata (C.S), C. gauchowensis (C.G), along with commercially refined C. oleifera oil (C-C.O) and its DAG-enriched counterparts (at 40% and 80% enrichment), were analyzed and compared. Unique patterns of TAG profiles, fatty acid distributions on different glycerol backbones, tocopherol, squalene, total polyphenols, and volatile compounds were observed, suggesting that these characteristics can be utilized as a criterion to differentiate them. DAG-enriched oils exhibited increased levels of unsaturated fatty acids (UFAs) compared to C-C.O, albeit with decreased contents of tocopherol, squalene, and total polyphenols. Moreover, diverse volatile compounds were identified across all types of camellia oils, among which the DAG-enriched oils had distinct distribution characteristics compared with their crude oils, indicating the influence of the enrichment process on volatile compounds. Furthermore, DAG-enriched oils demonstrated reduced antioxidant activity abilities compared to their counterparts, with the highest activity observed in C.O, followed by C.G. Additionally, strong correlations were observed between antioxidant activity and tocopherol, as well as squalene content. [ABSTRACT FROM AUTHOR]

Objective: Pulmonary papillary adenoma is an extremely rare benign tumor. It is derived from type II lung cells and club cells, suggesting that it may originate from stem cells with two-way differentiation. Only one case has been reported with FGFR2-IIIb overexpression. Methods: Two cases of pulmonary papillary adenoma with available data on clinical features, histological morphology, immunophenotype and molecular characteristics were analyzed. Results: Both tumors were well-circumscribed unencapsulated nodules composed of papillary structures with fibrovascular cores lined by a single layer of cuboidal or columnar epithelium without necrosis, nuclear atypia and mitoses, or invasion. But malignant transformation features include complex branching structures and significantly enlarged, irregular, and crowded malignant cells in one case. Immunohistochemistry showed that the tumor cells were strongly positive for TTF1, NapsinA, EMA and CK7 and negative for CEA and P63, with a low Ki-67 proliferation index. The EGFR somatic mutation exon19:c.2236_2256delinsATC (p.E746_S752delinsI) was found in one case by next-generation sequencing (NGS) technology. Conclusion: Pulmonary papillary adenoma is very rare. Virtually all papillary adenomas are clinically silent and discovered incidentally. They are benign tumors, and resection is curative. An EGFR 19 exon deletion mutation in a patient with this tumor type was detected for the first time by NGS, and our results suggest that the malignant transformation of pulmonary papillary adenoma may be mediated by EGFR mutation. [ABSTRACT FROM AUTHOR]

Feeding is a critical process in aquaculture, as it has a direct impact on the quantity and quality of fish. With advances in convolutional neural network (CNN) and vision transformer (ViT), intelligent feeding has been widely adopted in aquaculture, as the real-time monitoring of fish behavior can lead to better feeding decisions. However, existing models still have the problem of insufficient accuracy in the fish behavior-recognition task. In this study, the largemouth bass (Micropterus salmoides) was selected as the research subject, and three categories (weakly, moderately, and strongly hungry) were defined. We applied the deformable attention to the vision transformer (DeformAtt-ViT) to identify the fish hunger degree. The deformable attention module was extremely powerful in feature extraction because it improved the fixed geometric structure of the receptive fields with data-dependent sparse attention, thereby guiding the model to focus on more important regions. In the experiment, the proposed DeformAtt-ViT was compared with the state-of-the-art transformers. Among them, DeformAtt-ViT achieved optimal performance in terms of accuracy, F1-score, recall, and precision at 95.50%, 94.13%, 95.87%, and 92.45%, respectively. Moreover, a comparative evaluation between DeformAtt-ViT and CNNs was conducted, and DeformAtt-ViT still dominated the others. We further visualized the important pixels that contributed the most to the classification result, enabling the interpretability of the model. As a prerequisite for determining the feed time, the proposed DeformAtt-ViT could identify the aggregation level of the fish and then trigger the feeding machine to be turned on. Also, the feeding machine will stop working when the aggregation disappears. Conclusively, this study was of great significance, as it explored the field of intelligent feeding in aquaculture, enabling precise feeding at a proper time. [ABSTRACT FROM AUTHOR]

Triphenyltin (TPT) is a widespread synthetic chemical used in many fields and its potential risk to organisms has been comprehensively investigated using different animal models and species. Currently, little is known about the effects of TPT exposure on microbial midgut diversity, therefore we explored these effects in the lepidopterous silkworm model using 16S rDNA sequencing. In total, 5273 and 5065 operational taxonomic units (OTUs) were identified in control and TPT-exposure group samples, ranging from 424 to 728 OTUs/sample. Alpha-diversity analyses revealed that TPT exposure induced the fluctuations of gut microbial diversity and abundance while beta-diversity analyses identified a distinct impact on major gut microbiota components. In our microbiome analyses, 23 phyla and 353 genera were recognized in the control group, while 20 phyla and 358 genera were recognized in the TPT exposure group. At the genus level, midgut microbiota were composed of several predominant bacterial genera, including Muribaculaceae, Lactobacillus, and UCG-010. In the TPT exposure group, o__Bacillales, f__Bacillaceae, and f__Caldicoprobacteraceae abundance was relatively high, while f__Oscillospiraceae, f__Fusobacteriaceae, and f__SCI84 abundance was relatively high in the control group. Gene function analyses in silkworm microbiota after TPT exposure showed that biosynthesis of ansamycins, fructose and mannose metabolism, glycerolipid metabolism, type II diabetes mellitus, glycolysis/gluconeogenesis, lipid metabolism, translation proteins, atrazine degradation, DNA repair and recombination proteins, nicotinate and nicotinamide metabolism were significantly increased. Collectively, our silkworm model identified gut microbial diversity risks and the adverse effects from TPT exposure, which were similar to other aquatic animals. Therefore, TPT levels in environmental samples must be monitored to prevent ecological harm. [ABSTRACT FROM AUTHOR]

Given the challenge of pear leaf disease recognition caused by uneven illumination, overlapping leaves, and other green plants in the background, a two‐stage strategy‐based framework for pear leaf segmentation and disease classification is proposed. Initially, a double branch polymerization net fusing features of the low‐level feature branch and semantic branch is constructed to extract the target diseased pear leaf and eliminate background interference. Then an improved lightweight neural network (Inverted‐Inception Efficient‐Excitation‐and‐Filtering‐Bottleneck MobileNet‐v2, I2EMv2) is used to capture multi‐scale lesion information and ainhibit invalid feature channels and filter redundant features for the final classification. The experimental results show that the proposed framework can accurately extract the pear leaf region with complete boundary from the complex background, maximize the retention of lesion information, and achieve high‐precision pear leaf disease identification. The mean absolute error, F‐measure, and intersection over union of leaf segmentation are 0.027, 0.947, and 0.880, respectively, and the average recognition accuracy of leaf disease is 92.05%. Compared with others, the method proposed in this paper has superior performance on segmentation and classification, which provides a reference for pear leaf disease classification under complex background. [ABSTRACT FROM AUTHOR]

The electrochemical CO2 reduction reaction (CO2RR) is a promising approach for mitigating the greenhouse effect arising from anthropogenic CO2 emission. Nonetheless, poor product selectivity associated with electrochemical catalysts is the main technical problem for the application of CO2RR technology. The catalytic performance of nano-catalysts is strongly dependent on their microstructural features. Anomalous small-angle X-ray scattering (ASAXS) is one of the most effective techniques for studying nanostructural change in an operando way, especially for complex systems and mixed-element catalyst situations. Furthermore, based on the research results of ASAXS, appropriate catalyst components and nanostructures can be designed to achieve stable catalytic performance of the catalyst, promote catalytic reaction rate, or improve catalytic reaction selectivity. In this paper, the basic concept, principle, and applications in different systems of ASAXS are reviewed thoroughly. Finally, the development prospect of ASAXS in the field of electrocatalysis is prospected. It is hoped that this review will further promote ASAXS technology to play a more far-reaching impact in the field of electrocatalytic CO2RR. [ABSTRACT FROM AUTHOR]

For stage III colorectal cancer (CRC) patients with a high risk of recurrence, intensified adjuvant chemotherapy can improve overall survival. We aimed to develop a circulating tumor DNA (ctDNA) methylation marker model for predicting the relapse risk of stage III CRC patients. Differentially methylated markers identified between 53 normal mucosa samples and 165 CRC tissue samples, as well as between plasma samples from 75 stage I/II (early‐stage) CRC patients and 55 stage IV (late‐stage) CRC patients, were analyzed using Student's t‐tests. The overlapping methylation markers shared by plasma and tissue samples were used to establish a methylation marker model to evaluate the tumor burden in the peripheral blood of CRC patients using the random forest method. This model was verified in the validation cohort (n = 44) and then applied to predict recurrence risk in 50 stage III CRC patients and monitor the clinical disease course in serial samples from four CRC patients. We built a five‐marker‐based ctDNA methylation model that had high sensitivity (84.21%) and specificity (84%) in identifying late‐stage CRC in a validation cohort containing 24 stage I/II CRC patients and 20 stage IV CRC patients. The model achieved high sensitivity (87.5%) and specificity (94.12%) in predicting tumor relapse in an independent cohort of 50 stage III CRC patients and could be an independent recurrence risk factor for stage III patients [Hazard ratio (HR), 60.4; 95% confidence interval (CI): 7.68–397; p = 9.73e−5]. Analysis of serial blood samples of CRC showed that the model could monitor disease relapse earlier than imaging examination and serum carcinoembryonic antigen (CEA) and so may provide an opportunity for the early adjustment of therapeutic strategies. Moreover, the model could potentially monitor the clinical course and treatment response dynamically. © 2022 The Authors. The Journal of Pathology published by John Wiley & Sons Ltd on behalf of The Pathological Society of Great Britain and Ireland. [ABSTRACT FROM AUTHOR]

It is an emerging trend to adopt cholesterol analogues from botanical sterols as membrane stabilizers of liposomes. This work investigated the potential of using purified sterol from camellia oil deodorant distillate as the membrane stabilizer for vitamin C liposomes. At the same time, β-sitosterol, stigmasterol, and cholesterol served as the control. The effect of sterols on vesicle properties, liposomes stability, vitamin C release, and bioavailability was assessed. When purified sterol was incorporated, the properties of these vesicles were comparable to those of the vesicles with β-sitosterol incorporated. However, the incorporation of stigmasterol was not conducive to vesicles dispersion. The storage, thermal, and pH stability, encapsulation efficiency, and bioavailability of vitamin C in liposomes were improved with purified sterol incorporated. In addition, the vitamin C in liposomes containing purified sterol showed a slower release. The release of vitamin C from liposomes containing purified sterols followed a first-order kinetic model. Fickian diffusion governed the release mechanism. The results suggested that purified sterol was a potential replacer for cholesterol as the stabilizer for liposomes, which was beneficial for developing low-cholesterol liposomes. [ABSTRACT FROM AUTHOR]

Smoke detection in video is a challenging task because of the irregular shape of smoke, its complex motion state, which is affected by temperature, wind and other external factors, and background disturbances. Pixel-based foreground modeling method is a crucial step in many smoke detection systems and can be applied to efficiently focus on a certain object or a specific region to detect movements or anomalies. In video analysis, it is a natural idea to move the focus from the pixel-level foreground to the feature-level foreground. In this paper, the feature foreground is generated by the middle layer of a convolutional neural network (CNN) to guide the temporal modeling process for smoke objects. A novel temporal module called the Feature Foreground Module (FFM) is proposed to boost learning of a smoke temporal representation. Consider the problem of smoke analysis in video, we present a novel unifying approach, named an enhanced feature foreground network (EFFNet), that performs both smoke source prediction and detection. Efficient branch networks are designed in EFFNet, to predict the source mask and bounding boxes of smoke plumes in video. To the best of our knowledge, this is the first paper to study the source of smoke using deep learning methods. Finally, experiments on a realistic smoke dataset and a public dataset show that EFFNet method performs much better than do previous state-of-the-art methods. [ABSTRACT FROM AUTHOR]

The purpose of this study was to isolate tea saponin from defatted C. oleifera cake and explore its potential antifungal activity and mechanism. UHPLC–MS/MS identified the compounds, and the antibacterial activity of tea saponin was determined by the inhibition zone method and double dilution method. In addition, the influence of tea saponin on the cell membrane, hyphae, and biofilm was studied to explore the antifungal mechanism of tea saponin. The results showed that the purity of tea saponin was 90.61%, and the main components of C. oleifera saponins were oleiferasaponin D3. Tea saponin has an apparent inhibitory effect on fungus. The minimum inhibitory concentrations (MIC) of the tea saponin against C. albicans, S. cerevisiae, and Penicillium were 0.078, 0.156, and 0.156 mg/mL, while the minimum fungicidal concentrations (MFC) were 0.312, 0.625, and 0.625 mg/mL, respectively. Tea saponin could destroy the cell membrane structure, which led to the leakage of cell contents and inhibited the growth of mycelium, reduced cell adhesion and aggregation, and effectively inhibited the formation of biofilm of C. albicans. Transcriptomic analyses indicated that tea saponin could down-regulate the expression of several hyphae- and biofilm-related genes (ALS3, ECE1, HWP1, EFG1, and UME6). This study confirmed that tea saponin from C. oleifera cake can be used as an effective source of natural antifungal agents and provide guidance on their utilization in the field of food safety. [ABSTRACT FROM AUTHOR]

Background: CMTM6 is a novel key regulator of PD-L1. High expression of both CMTM6 and PD-L1 may predict the benefit of PD-1 axis blockade in lung cancer. We aimed to investigate the expression pattern of CMTM6 between mismatch repair-defective (dMMR) and mismatch repair-proficient (pMMR) colorectal cancer (CRC) tissues and assess its correlation with the response to PD-1/PD-L1 pathway blockade. Methods: Immunohistochemistry (IHC) was used to analyze CMTM6 and PD-L1 expression and immune cell density in dMMR/pMMR CRC. Quantitative multiplex immunofluorescence (IF) was performed to detect CMTM6, PD-L1, CD4, CD8, CD68 and CD163 expression in CRC patients treated with PD-1/PD-L1 inhibitors. Result: IHC analysis showed that CMTM6 and PD-L1 were both expressed in tumor cells (TCs) and invasion front immune cells (ICs). CMTM6 and PD-L1 expression and CD4+, CD8+, CD68+ or CD163+ cell density were significantly higher in dMMR CRC patients than in pMMR CRC patients. CMTM6 expression was positively correlated with PD-L1 expression and CD163+ M2 macrophage density in dMMR CRC. IF analysis showed that the coexpression rate of CMTM6/PD-L1 and the expression rate of CMTM6 in CD8+ T cells and CD163+ M2 macrophages were significantly increased in the group that exhibited clinical benefit. CMTM6 expression in M2 macrophages was identified as the best biomarker for predicting the responsiveness to PD-1/PD-L1 inhibitors. Conclusions: CMTM6 expression in M2 macrophages may predict the PD-1/PD-L1 inhibitor response rate in CRC patients more accurately than dMMR/microsatellite instability-high (MSI-H) status. It can also identify pMMR CRC patients who could benefit from PD-1/PD-L1 inhibitors. [ABSTRACT FROM AUTHOR]

In this study, Camellia nitidissima Chi leaf extract was investigated for its compounds and pancreatic lipase inhibitory potentials. The interaction was determined using ultraviolet (UV) spectroscopy, circular dichroism (CD), fluorescence spectroscopy (FS), and molecular docking to understand the inhibiton, kinetic, and conformation of extraction–pancreatic lipase complex. C. nitidissima Chi leaf extraction inhibited the pancreatic lipase activity in a dose‐dependent manner at the concentration of 1–12 mg/ml. The Lineweaver–Burk plots indicated that the inhibition on pancreatic lipase by extraction was noncompetitive. In addition, the decrease in α‐helix contents, increase in β‐sheet and β‐turn, and decrease in fluorescence intensity after extraction treatment indicated that the conformation of pancreatic lipase was changed. This work revealed that C. nitidissima Chi leaf extraction played a significant role in inhibiting pancreatic lipase activity and brought out a solution of delay fat accumulation. Practical applications: This study reports the components in the extract of C. nitidissima Chi leaf and its inhibitory effect and mechanism of pancreatic lipase. C. nitidissima Chi leaf is a good source of bioactive components, including multiflorin B, kaempferol‐3‐O‐rutinoside, vicenin‐2, apigenin‐6‐C‐pentosyl‐8‐C‐hexosyl, vitexin, kaempferol, and other ingredients. It can inhibit pancreatic lipase and be used to control obesity and treat hyperlipidemia. This study also revealed the structure changes of C. nitidissima Chi leaf extract on pancreatic lipase, and further revealed the inhibitory mechanism of C. nitidissima Chi leaf extract on lipase, which provides a theoretical basis for C. nitidissima Chi leaf as a lipase inhibitor. [ABSTRACT FROM AUTHOR]

Fire smoke detection in forest faces much more challenges than in local areas or indoors. Conventional fire smoke methods using static features extracted form single image directly cannot handle some disturbed factors exist in forest, such as shaking trees and fog/haze. On the other hand, it is difficult to capture the dynamic features of fire smoke while they are vital for fire smoke detection. This paper proposes an effective method of extracting features based on sequential images for smoke detection, quasi-dynamic features are extracted using on pixel-block arranged image sets. First, consecutive frames are rearranged into a new big image based on a pixel-block rule, so that the new image still keep the whole structure of original image on block level, and the change of different pixels in the same block, which comes from the same position of each frame, can reflect the dynamic features by special process. Second, to process the new arranged big image, driven by single image wavelet transform for denoting local signal characteristics, Dual Tree-Complex Wavelet Transform is utilized to decompose the new big image into eight images with the same size of the source image after several level-decomposition, including four directions (HH, HL, LH, LL) with two decomposed images in each direction, so that the changes from smoke in different orientation can be extracted and depicted in these subbands. Third, a multi-scale dictionary learning method is proposed to learn dictionaries of each group images. Furthermore, elastic net is introduced for sparse coding and feature coefficients extraction. All operations above contribute to a significant improvement for smoke detection in this paper. Extensive experiments are performed to validate the effectiveness of the proposed approach. [ABSTRACT FROM AUTHOR]

Although magnesium phosphate cement (MPC) is conventionally deemed effective in heavy metal-contaminated soil remediation, the variations of its mechanical and leaching characteristics under the action of dry-wet cycles remain unclear as yet. This paper primarily addressed the effect of dry-wet cycles and fly ash on MPC-solidified zinc-contaminated soil via a disparate group of experiments. In this study, solidified cylindrical samples were subjected to different drying-wetting cycles ranging in times from 0 to 10 with varying content of fly ash. We then measured the mass loss, the unconfined compressive strength, and the Zn2+ leaching concentration of the leachate for the samples undergoing specified cycles. In addition, X-ray diffraction (XRD) and scanning electron microscopy (SEM) tests were conducted to explore the mechanism of MPC-solidified zinc-contaminated soil with fly ash. The results indicate that the Zn2+ concentration in the leaching solution increases rapidly with the number of cycles for 0–3 cycles and then tends to flatten out. Moreover, the unconfined compressive strength of the samples without fly ash decreases with an increasing dry-wet cycles. For the samples with various fly ash contents, in contrast, their unconfined compressive strength experiences an initial rise and a subsequent decline owing to the development of dry-wet cycles. With the purpose of facilitating practical applications, the appropriate fly ash content (approximately 20%) was estimated in terms of the enhanced dry-wet cycles durability of the solidified soil and unconfined compressive strength, according to the limited experimental measurements undertaken (for the Zn2+ concentration of 0.5). The role of dry-wet cycles in the physical and leaching properties of MPC-solidified soil may be of major practical significance. [ABSTRACT FROM AUTHOR]

Mass transfer usually affects the rate of chemical reactions in coal. The effect of internal diffusion on char gasification with CO2 in the temperature range from 1123 K to 1273 K was investigated via thermogravimetric analysis and assessment of char morphology features. The results revealed that the effect of internal diffusion on the initial reaction rate was more significant with an increase of particle size, due to the concentration gradient of the gasification agent within the solid particles. In the early stage of gasification, the generation of new micropores and the opening of closed pores led to an increase in specific surface area. As the reaction proceeded, the openings were gradually expanded and the specific surface area continued to increase. However, with further reaction, disappearance of edge pores, melting and collapse of the pore structure led to a decrease in specific surface area. The intrinsic activation energy and reaction order based on the nth-order model were 157.67 kJ·mol−1 and 0.36, respectively. Thus, temperature zones corresponding to chemical reaction and diffusion control were identified. Moreover, the calculated effectiveness factor provided a quantitative estimation of internal diffusion in the initial stage. [ABSTRACT FROM AUTHOR]

In this study, volatile compounds of camellia seed oil (CSO) prepared by different preheat treatments (microwave, frying, roasting, and steaming) were identified by headspace solid‐phase microextraction combined with gas chromatography‐mass spectrometry (HS‐SPME/GC‐MS). A total of 107 volatile compounds were identified in CSO samples, including aldehydes (16), alcohols (6), ketones (3), heterocyclic compounds (26), esters (23), hydrocarbons (15), and others (17). Among them, untreated CSO is mainly hydrocarbons, roasting and steaming CSO are mainly aldehydes and alcohols, while microwave and roasting CSO are dominated by aldehydes and heterocyclic compounds. Fourteen volatile compounds with high relative odor activity value (ROAV ≥ 1) were selected as key aroma compounds (KACs). Principal Component Analysis (PCA) and Cluster Analysis (CA) were performed on 14 KACs, which determined that there were 3, 3, 3, 7, and 6 characteristic aroma compounds (CACs) in untreated, microwaved, frying, roasting, and steaming CSO. Additionally, the potential formation pathways and mechanism of KACs were discussed. Practical applications: Flavor is an important factor for consumers to choose edible oils, and it is also one of the indicators of oil quality. Different flavors of CSO can cater to the needs of different consumers. CSO manufactories can choose different preheat treatments to produce CSO with various flavors to meet different customers' need. CSO with new flavor can extend its market share and increase its value. [ABSTRACT FROM AUTHOR]

Most video-based detection systems rely on extracting visual features directly from divided original frames or detected motion regions achieved using conventional background subtraction. However, these approaches are not effective for smoke detection because conventional motion detection methods are sensitive to non-salient motion regions like waves, shaking tree leaves, camera jitter an so on. This tiny motion regions can be easily misclassified as smoke. Second, in the case of light smoke the background is visible with or without motion detection, such that it will deteriorate the feature quality. These regions usually occur far from smoke centers and present unstable and non-salient characteristics. This paper proposes an approach to separate the smoke region based on motion and lightness saliency detection. A low-rank and structured sparse decomposition method is used to extract the foreground regions. Saliency of smoke is then computed for further separation. These aforementioned measures ensure a reliable smoke component extraction. We propose a saliency measurement for group-sparse robust orthonormal subspace and learning (ROSL) in virtue of adaptive parameters. Experiments on challenging data sets demonstrate that the proposed method can work well on a wide range of smoke videos and give better smoke detection results. [ABSTRACT FROM AUTHOR]

We present three stages of a novel backgrounds subtraction method in this paper: a new pixel-block based randomized arrangement is utilized to preprocess all the frame images, so that low-rank property of background and sparsity of foreground can be separated more easily; different foreground regions have different sparsity, we use a set of adaptive parameters for subtracting foregrounds according to the variances of frame pixels; finally, background model is built via an improved low-rank and block-sparse matrix decomposition based on the proposed adaptive pixel-block background subtraction. All these key measurements guarantee the considerable performance in background subtraction, which are also demonstrated in our experimental results. [ABSTRACT FROM AUTHOR]

Bone repair involves bone resorption through osteoclastogenesis and the stimulation of neovascularization and osteogenesis by endothelial progenitor cells (EPCs). However, the role of EPCs in osteoclastogenesis is unclear. In this study, we assess the effects of EPC‐derived exosomes on the migration and osteoclastic differentiation of primary mouse bone marrow‐derived macrophages (BMMs) in vitro using immunofluorescence, western blotting, RT‐PCR and Transwell assays. We also evaluated the effects of EPC‐derived exosomes on the homing and osteoclastic differentiation of transplanted BMMs in a mouse bone fracture model in vivo. We found that EPCs cultured with BMMs secreted exosomes into the medium and, compared with EPCs, exosomes had a higher expression level of LncRNA‐MALAT1. We confirmed that LncRNA‐MALAT1 directly binds to miR‐124 to negatively control miR‐124 activity. Moreover, overexpression of miR‐124 could reverse the migration and osteoclastic differentiation of BMMs induced by EPC‐derived exosomes. A dual‐luciferase reporter assay indicated that the integrin ITGB1 is the target of miR‐124. Mice treated with EPC‐derived exosome‐BMM co‐transplantations exhibited increased neovascularization at the fracture site and enhanced fracture healing compared with those treated with BMMs alone. Overall, our results suggest that EPC‐derived exosomes can promote bone repair by enhancing recruitment and differentiation of osteoclast precursors through LncRNA‐MALAT1. [ABSTRACT FROM AUTHOR]

Background/Aims: Bone resorption mediated by osteoclasts plays an important role in bone healing. Endothelial progenitor cells (EPCs) promote bone repair by stimulating neovascularization and osteogenesis. However, the role of EPCs in osteoclast formation and function is not well defined. The aim of this study was to elucidate mechanisms of EPCs in osteoclast formation and function. Methods: In this study, we examined the effects of EPCs on the proliferation, migration and osteoclastic differentiation of primary mouse bone marrow-derived macrophages (BMMs) in a co-culture system in vitro. We also evaluated the effects of EPC co-transplantation on the homing and osteoclastic differentiation of transplanted BMMs in a mouse bone fracture model in vivo. The technology of immunofluorescence, immunohistochemical, western blot, Rt-PCR, cell co-culture and Transwell were used in this study. Results: EPCs secreted TGF-β1 in the EPC-BMM co-culture medium and increased Talin-1 expression in the co-cultured BMMs. Treatment with a TGF-β1 neutralizing antibody or Talin-1 silencing in BMMs completely inhibited BMM osteoclastic differentiation in the co-culture system. These results indicated that the osteoclastogenic effects of EPCs were mediated by TGF-β1-mediated Talin-1 expression in BMMs. In the femur fracture model, BMMs co-transplanted with EPCs exhibited enhanced engraftment into the fracture site and osteoclastic differentiation compared with those transplanted alone. Mice treated with EPC-BMM co-transplantation exhibited increased neovascularization at the fracture site and accelerated fracture healing compared with those treated with BMMs alone. Conclusion: Taken together, the results suggest that EPCs can promote bone repair by enhancing recruitment and differentiation of osteoclast precursors. [ABSTRACT FROM AUTHOR]

Long-term static leaching experiments were conducted to investigate characteristics of magnesium phosphate cement (MPC) solidified/stabilized Zn-contaminated soil under impact of acid rain. Effects of initial pH values of acid rain, binder agent types and compositions, as well as curing age on strength and leaching characteristics of the sample were analyzed. Standard sand was used as raw material, with the content of cement at 15%. Our study used two types of MPC with MgO/KH2PO4(M/P) ratio of 3:1 and 6:1 (respectively referred to as M3 and M6), and also ordinary Portland cement with content at 15% (referred to as C15) as test control. Experimental results show that acid rain with pH = 2 has the greatest weakening effect on unconfined compressive strength (qu) of the sample, while with pH = 4 and 7 such weakening effects on quare similar. Research findings also indicate that M6 is the most effective in immobilizing Zn-spiked soils, M3 is next and C15 is the least. The effect of Zn2+on hydration of MPC is much lower than that of C15. Precuring method can improve quof the MPC-solidified samples and its resistance to acid rain. Compared with non-renewal, replacing acid rain leachant at designated intervals decreases quof the sample. [ABSTRACT FROM AUTHOR]

Osteomyelitis is a common manifestation of invasive Staphylococcus aureus infection characterized by widespread bone loss and destruction. Phagocytes possess various receptors to detect pathogens, including the Toll-like receptors (TLRs). Previous studies have demonstrated that the S. aureus protein SpA binds directly to pre-osteoblastic cells via tumor necrosis factor receptor-1 (TNFR-1). In our present study, we investigated the relationship between TLR2 and TNFR-1 in S. aureus-infected osteoblasts. Our results showed that cell viability decreased, and apoptosis, expression of TLR2, and the secretion of inflammatory cytokines (TNF-α and IL-6) increased with increasing concentrations of S. aureus. The JNK pathway was also activated in response to S. aureus infection. Knockdown of TNFR1 not only inhibited the JNK pathway but also reduced TLR2 protein and RANKL levels in S. aureus-infected cells. Inhibition of the JNK pathway reduced the protein level of TLR2 and reduced TNF-α and IL-6 secretion in S. aureus-infected cells. [ABSTRACT FROM AUTHOR]

Background and Aims:Osteomyelitis is a common manifestation of invasive Staphylococcus aureus infection characterized by bone loss and destruction. We investigated the role of toll-like receptor 2 (TLR2) in bacterial recognition and clearance in response to infection with an osteomyelitis isolate of S. aureus. Methods:Apoptosis was assessed in the osteoblastic cell line MC3T3-E1 by Annexin V-FITC/PI staining and flow cytometry. The expression of TLR2 and apoptosis-related and mitogen-activated protein kinase pathway proteins was assessed by qRT-PCR and western blotting. Alkaline phosphatase (ALP) activity and calcium deposition were assessed by ALP activity assay and Alizarin red staining. Results:S. aureus induced apoptosis, upregulated TLR2 expression, and activated mitogen-activated protein kinase pathways in a time dependent manner. Inhibition of the c-Jun N-terminal kinase (JNK) pathway downregulated TLR2 and suppressed the S. aureus induced activation of pro-apoptotic pathways. Short-hairpin RNA mediated silencing of TLR2 reversed S. aureus induced apoptosis and decrease in ALP activity and calcium deposition, and inhibition of JNK had a similar effect. Conclusion:We showed that osteoblast apoptosis and osteogenic differentiation in response to bacterial invasion are dependent on TLR2 expression and JNK activation, suggesting novel potential therapeutic targets for the treatment of osteomyelitis. © 2015 S. Karger AG, Basel [ABSTRACT FROM AUTHOR]

Purpose: This study focuses on nanoscale self-assembly peptides (SAP) modified demineralized bone matrix (DBM) which provided a more effective osteogenesis and regeneration for critically-sized femur defects in goats using the selective cell retention (SCR) strategy. Methods: RADA16-I peptide was used to modify DBM and formed a composite scaffold (SAP/DBM). The morphological change and dynamic expression of osteogenic genes of mesenchymal stem cells (MSCs) derived from marrow in SAP/DBM was observed. The cells and factors in bone marrow were enriched into SAP/DBM by technology of selective cells retension (SCR). The construct was transplanted into 20-mm femur defects in goats and their osteogenesis was evaluated. Results: The SAP/DBM scaffold formed a three-dimensional interweaving nanofiber in pores of DBM. MSCs exhibited better morphology in SAP/DBM than that in only DBM, and the levels of expression of ALP ,OCN and Runx2 gene in SAP/DBM samples was significantly higher than that of DBM at 14 days in vitro ( P < 0.05). Compared with marrow-enriched DBM, the volume of newly formed bone from marrow-enriched SAP/DBM is higher in goats ( P < 0.05). Conclusion: Our study may not only have a significant impact on the construction method of tissue engineering but also provide a viable, simple and effective method for clinical bone construction. [ABSTRACT FROM AUTHOR]

To date, various types of cells for seeding regenerative scaffolds have been used for bone tissue engineering. Among seed cells, the mesenchymal stem cells derived from human umbilical cord Wharton’s jelly (hUCMSCs) represent a promising candidate and hold potential for bone tissue engineering due to the the lack of ethical controversies, accessibility, sourced by non-invasive procedures for donors, a reduced risk of contamination, osteogenic differentiation capacities, and higher immunomodulatory capacity. However, the current culture methods are somewhat complicated and inefficient and often fail to make the best use of the umbilical cord (UC) tissues. Moreover, these culture processes cannot be performed on a large scale and under strict quality control. As a result, only a small quantity of cells can be harvested using the current culture methods. To solve these problems, we designed and evaluated an UC Wharton’s jelly repeated culture device. Using this device, hUCMSCs were obtained from the repeated cultures and their quantities and biological characteristics were compared. We found that using our culture device, which retained all tissue blocks on the bottom of the dish, the total number of obtained cells increased 15–20 times, and the time required for the primary passage was reduced. Moreover, cells harvested from the repeated cultures exhibited no significant difference in their immunophenotype, potential for multilineage differentiation, or proliferative, osteoinductive capacities, and final osteogenesis. The application of the repeated culture frame (RCF) not only made full use of the Wharton’s jelly but also simplified and specified the culture process, and thus, the culture efficiency was significantly improved. In summary, abundant hUCMSCs of dependable quality can be acquired using the RCF. [ABSTRACT FROM AUTHOR]

The purpose of this study was to evaluate the effect of different frequencies of pulsed electromagnetic fields on the osteogenic differentiation of human mesenchymal stem cells. Third-generation human mesenchymal stem cells were irradiated with different frequencies of pulsed electromagnetic fields, including 5, 25, 50, 75, 100, and 150 Hz, with a field intensity of 1.1 mT, for 30 minutes per day for 21 days. Changes in human mesenchymal stem cell morphology were observed using phase contrast microscopy. Alkaline phosphatase activity and osteocalcin expression were also determined to evaluate human mesenchymal stem cell osteogenic differentiation. Different effects were observed on human mesenchymal stem cell osteoblast induction following exposure to different pulsed electromagnetic field frequencies. Levels of human mesenchymal stem cell differentiation increased when the pulsed electromagnetic field frequency was increased from 5 hz to 50 hz, but the effect was weaker when the pulsed electromagnetic field frequency was increased from 50 Hz to 150 hz. The most significant effect on human mesenchymal stem cell differentiation was observed at of 50 hz. The results of the current study show that pulsed electromagnetic field frequency is an important factor with regard to the induction of human mesenchymal stem cell differentiation. Furthermore, a pulsed electromagnetic field frequency of 50 Hz was the most effective at inducing human mesenchymal stem cell osteoblast differentiation in vitro. [ABSTRACT FROM AUTHOR]

Simple Summary: Serum biochemical parameters and hormones play a role in directly reflecting the physiological state and modulating the milk performance of dairy cows. However, the variability of the serum biochemical parameters and hormones in multiparous mid-lactation cows have not drawn much attention due to their supposedly stable states, especially for those cows under the same nutrition and management condition. The aim of this study was to evaluate the effects of days-in-milk (DIM, within the mid-lactation) and parity (ranging from 2–6) on serum biochemical parameters and hormone profiles based on a large cohort of dairy cows. The results showed that DIM and parity contribute to the variations in serum biochemical parameters and hormones related to protein status, energy supply, liver and kidney function, and oxidative stress of mid-lactation dairy cows, with the effect of DIM being dominant over parity. Our result suggested that the DIM periods and parity should be taken into consideration to optimize nutritional strategies in order to improve the milk performance traits more precisely. It is well known that serum biochemical parameters and hormones contribute greatly to the physiological and metabolic status of dairy cows. However, few studies have focused on the variation of these serum parameters in multiparous mid-lactation cows without the interference of diet and management. A total of 287 Holstein dairy cows fed the same diet and maintained under the same management regime were selected from a commercial dairy farm to evaluate the effects of days-in-milk (DIM) and parity on serum biochemical parameters and hormone profiles. Milk yield and milk protein content were affected by DIM and parity (p < 0.05). Milk protein yield showed a numerically decreasing trend with parity, and it was relatively constant in cows with parities between 2 and 4 but lower in cows with parity 6 (p = 0.020). Ten and five serum biochemical parameters related to protein status, energy metabolism, liver and kidney function, and oxidative stress were affected by DIM and parity, respectively (p < 0.05). Glucagon, insulin-like growth factor 1 concentration, and the revised quantitative insulin sensitivity check index were significantly different (p < 0.05) among cows with different DIM. Parity had no effect on hormone concentrations. An interaction between DIM and parity effect was only detected for glucagon concentration (p = 0.015), which showed a significantly increasing trend with DIM and overall decreasing trend with parity. In summary, DIM and parity played an important role in affecting the serum biochemical parameters and/or hormones of dairy cows, with serum parameters affected more by DIM than parity. [ABSTRACT FROM AUTHOR]

This work considers using camera sensors to detect fire smoke. Static features including texture, wavelet, color, edge orientation histogram, irregularity, and dynamic features including motion direction, change of motion direction and motion speed, are extracted from fire smoke to train and test with different combinations. A robust AdaBoost (RAB) classifier is proposed to improve training and classification accuracy. Extensive experiments on well known challenging datasets and application for fire smoke detection demonstrate that the proposed fire smoke detector leads to a satisfactory performance. [ABSTRACT FROM AUTHOR]