Capsaicin attenuates Porphyromonas gingivalis-suppressed osteogenesis of periodontal ligament stem cells via regulating mitochondrial function and activating PI3K/AKT/mTOR pathway.

BACKGROUND AND OBJECTIVE: Prevention of periodontal bone resorption triggered by Porphyromonas gingivalis (P. gingivalis) is crucial for dental stability. Capsaicin, known as the pungent ingredient of chili peppers, can activate key signaling molecules involved in osteogenic process. However, the effect of capsaicin on osteogenesis of periodontal ligament stem cells (PDLSCs) under inflammation remains elusive. METHODS: P. gingivalis culture suspension was added to mimic the inflammatory status after capsaicin pretreatment. The effects of capsaicin on the osteogenesis of PDLSCs, as well as mitochondrial morphology, Ca2+ level, reactive oxygen species (ROS), mitochondrial membrane potential (MMP), and osteogenesis-regulated protein expression levels were analyzed. Furthermore, a mouse experimental periodontitis model was established to evaluate the effect of capsaicin on alveolar bone resorption and the expression of osteogenesis-related proteins. RESULTS: Under P. gingivalis stimulation, capsaicin increased osteogenesis of PDLSCs. Not surprisingly, capsaicin rescued the damage to mitochondrial morphology, decreased the concentration of intracellular Ca2+ and ROS, enhanced MMP and activated phosphatidylinositol 3-kinase (PI3K)/protein kinase B (AKT)/mammalian target of rapamycin (mTOR) pathway. The in vivo results showed that capsaicin significantly attenuated alveolar bone loss and augmented the expression of bone associated proteins. CONCLUSION: Capsaicin increases osteogenesis of PDLSCs under inflammation and reduces alveolar bone resorption in mouse experimental periodontitis.

Impaired angiogenesis in ageing: the central role of the extracellular matrix.

Each step in angiogenesis is regulated by the extracellular matrix (ECM). Accumulating evidence indicates that ageing-related changes in the ECM driven by cellular senescence lead to a reduction in neovascularisation, reduced microvascular density, and an increased risk of tissue ischaemic injury. These changes can lead to health events that have major negative impacts on quality of life and place a significant financial burden on the healthcare system. Elucidating interactions between the ECM and cells during angiogenesis in the context of ageing is neceary to clarify the mechanisms underlying reduced angiogenesis in older adults. In this review, we summarize ageing-related changes in the composition, structure, and function of the ECM and their relevance for angiogenesis. Then, we explore in detail the mechanisms of interaction between the aged ECM and cells during impaired angiogenesis in the older population for the first time, discussing diseases caused by restricted angiogenesis. We also outline several novel pro-angiogenic therapeutic strategies targeting the ECM that can provide new insights into the choice of appropriate treatments for a variety of age-related diseases. Based on the knowledge gathered from recent reports and journal articles, we provide a better understanding of the mechanisms underlying impaired angiogenesis with age and contribute to the development of effective treatments that will enhance quality of life.

Sparse 2-D optical phased array with large grating-lobe-free steering range based on an aperiodic grid.

Two-dimensional (2-D) optical phased arrays (OPAs) usually suffer from limited scan ranges and small aperture sizes. To overcome these bottlenecks, we utilize an aperiodic 32 × 32 grid to increase the beam scanning range and furthermore distribute 128 grating antennas sparsely among 1024 grid points so as to reduce the array element number. The genetic algorithm is used to optimize the uneven grid spacings and the sparse distribution of grating antennas. With these measures, a 128-channel 2-D OPA operating at 1550 nm realizes a grating-lobe-free steering range of 53° × 16°, a field of view of 24° × 16°, a beam divergence of 0.31° × 0.49°, and a sidelobe suppression ratio of 9 dB.

The Role of Glycoside Hydrolases in S. gordonii and C. albicans Interactions.

Candida albicans can coaggregate with Streptococcus gordonii and cocolonize in the oral cavity. Saliva provides a vital microenvironment for close interactions of oral microorganisms. However, the level of fermentable carbohydrates in saliva is not sufficient to support the growth of multiple species. Glycoside hydrolases (GHs) that hydrolyze glycoproteins are critical for S. gordonii growth in low-fermentable-carbohydrate environments such as saliva. However, whether GHs are involved in the cross-kingdom interactions between C. albicans and S. gordonii under such conditions remains unknown. In this study, C. albicans and S. gordonii were cocultured in heart infusion broth with a low level of fermentable carbohydrate. Planktonic growth, biofilm formation, cell aggregation, and GH activities of monocultures and cocultures were examined. The results revealed that the planktonic growth of cocultured S. gordonii in a low-carbohydrate environment was elevated, while that of cocultured C. albicans was reduced. The biomass of S. gordonii in dual-species biofilms was higher than that of monocultures, while that of cocultured C. albicans was decreased. GH activity was observed in S. gordonii, and elevated activity of GHs was detected in S. gordonii-C. albicans cocultures, with elevated expression of GH-related genes of S. gordonii. By screening a mutant library of C. albicans, we identified a tec1Δ/Δ mutant strain that showed reduced ability to promote the growth and GH activities of S. gordonii compared with the wild-type strain. Altogether, the findings of this study demonstrate the involvement of GHs in the cross-kingdom metabolic interactions between C. albicans and S. gordonii in an environment with low level of fermentable carbohydrates. IMPORTANCE Cross-kingdom interactions between Candida albicans and oral streptococci such as Streptococcus gordonii have been reported. However, their interactions in a low-fermentable-carbohydrate environment like saliva is not clear. The current study revealed glycoside hydrolase-related cross-kingdom communications between S. gordonii and C. albicans under the low-fermentable-carbohydrate condition. We demonstrate that C. albicans can promote the growth and metabolic activities of S. gordonii by elevating the activities of cell-wall-anchored glycoside hydrolases of S. gordonii. C. albicans gene TEC1 is critical for this cross-kingdom metabolic communication.

Polarization-independent fiber-chip grating couplers optimized by the adaptive genetic algorithm.

One-dimensional polarization-independent grating couplers are demonstrated with the aid of the adaptive genetic algorithm optimization. By adjusting the relative weight between the coupling efficiency and the bandwidth of the polarization-dependent loss (PDL), we control the evolution direction and customize the final performance of the device. Two specific designs are generated by giving more weight to the coupling efficiency and the PDL bandwidth, respectively. Coupling efficiencies of the first design are measured to be -7.6dB and -7.9dB at 1550 nm for TE and TM polarizations, respectively, while its 1.0 dB PDL bandwidth is 25.0 nm. In contrast, the second design presents higher coupling efficiencies of -7.6dB and -7.2dB at 1550 nm for TE and TM polarizations, respectively. However, its 1.0 dB PDL bandwidth is 22.0 nm.

Comprehensive role of prostate-specific antigen identified with proteomic analysis in prostate cancer.

Current treatments including androgen deprivation fail to prevent prostate cancer (PrCa) from progressing to castration-resistant PrCa (CRPC). Accumulating evidence highlights the relevance of prostate-specific antigen (PSA) in the development and progression of PrCa. The underlying mechanism whereby PSA functions in PrCa, however, has yet been elucidated. We demonstrated that PSA knockdown attenuated tumorigenesis and metastasis of PrCa C4-2 cells in vitro and in vivo, whereas promoted the apoptosis in vitro. To illuminate the comprehensive role of PSA in PrCa, we performed an isobaric tag for relative and absolute quantitation (iTRAQ)-based proteomic analysis to explore the proteomic change induced by PSA knockdown. Among 121 differentially expressed proteins, 67 proteins were up-regulated, while 54 proteins down-regulated. Bioinformatics analysis was used to explore the mechanism through which PSA exerts influence on PrCa. Protein-protein interaction analysis showed that PSA may mediate POTEF, EPHA3, RAD51C, HPGD and MCM4 to promote the initiation and progression of PrCa. We confirmed that PSA knockdown induced the up-regulation of MCM4 and RAD51C, while it down-regulated POTEF and EPHA3; meanwhile, MCM4 was higher in PrCa para-cancerous tissue than in cancerous tissue, suggesting that PSA may facilitate the tumorigenesis by mediating MCM4. Our findings suggest that PSA plays a comprehensive role in the development and progression of PrCa.

Fluphenazine antagonizes with fluconazole but synergizes with amphotericin B in the treatment of candidiasis.

Candida albicans causes a high mortality rate in immunocompromised individuals, but the increased drug resistance challenges the current antifungal therapeutics. Fluphenazine (FPZ), a commonly used antipsychotic medication, can induce the expression of drug efflux pumps in C. albicans and, thus, may interfere with the therapeutic efficacy of antifungals, such as fluconazole (FLC) and amphotericin B (AmB). Here, we investigated the combined effects of FLC/FPZ and AmB/FPZ against C. albicans in vitro and in a systemic candidiasis mouse model. The antifungal activity of FLC was significantly reduced when supplemented with FPZ. The inhibitory effects of FLC on the expression of the Candida virulence-related genes ALS3 and HWP1 were antagonized by FPZ. However, FPZ enhanced the susceptibility of C. albicans to AmB and further downregulated the expression of ALS3 and HWP1 in a synergistic manner with AmB. FPZ also enhanced the gene expression of ERG11, a key gene of the ergosterol biosynthesis pathway that has been associated with the activities of both FLC and AmB. In our mammalian infection model, mice treated with FLC/FPZ showed notably poor living status and increased fungal burden in their kidneys and brains compared with those treated with FLC alone. Conversely, the combined application of AmB/FPZ significantly improved the survival rate, attenuated the weight loss and reduced the organ fungal burdens of the infected mice. These data suggest that FPZ antagonized the therapeutic efficacy of FLC but enhanced the antifungal activity of AmB in the treatment of candidiasis.

A Novel Illumination Compensation Technique for Multi-Spectral Imaging in NDVI Detection.

To overcome the dependence on sunlight of multi-spectral cameras, an active light source multi-spectral imaging system was designed and a preliminary experimental study was conducted at night without solar interference. The system includes an active light source and a multi-spectral camera. The active light source consists of four integrated LED (Light Emitting Diode) arrays and adjustable constant current power supplies. The red LED arrays and the near-infrared LED arrays are each driven by an independently adjustable constant current power supply. The center wavelengths of the light source are 668 nm and 840 nm, which are consistent with that of filter lens of the Rededge-M multi-spectral camera. This paper shows that the radiation intensity measured is proportional to the drive current and is inversely proportional to the radiation distance, which is in accordance with the inverse square law of light. Taking the inverse square law of light into account, a radiation attenuation model was established based on the principle of image system and spatial geometry theory. After a verification test of the radiation attenuation model, it can be concluded that the average error between the radiation intensity obtained using this model and the actual measured value using a spectrometer is less than 0.0003 w/m2. In addition, the fitting curve of the multi-spectral image grayscale digital number (DN) and reflected radiation intensity at the 668 nm (Red light) is y = -3484230x2 + 721083x + 5558, with a determination coefficient of R2 = 0.998. The fitting curve with the 840 nm (near-infrared light) is y = 491469.88x + 3204, with a determination coefficient of R2 = 0.995, so the reflected radiation intensity on the plant canopy can be calculated according to the grayscale DN. Finally, the reflectance of red light and near-infrared light can be calculated, as well as the Normalized Difference Vegetation Index (NDVI) index. Based on the above model, four plants were placed at 2.85 m away from the active light source multi-spectral imaging system for testing. Meanwhile, NDVI index of each plant was measured by a Greenseeker hand-held crop sensor. The results show that the data from the two systems were linearly related and correlated with a coefficient of 0.995, indicating that the system in this article can effectively detect the vegetation NDVI index. If we want to use this technology for remote sensing in UAV, the radiation intensity attenuation and working distance of the light source are issues that need to be considered carefully.

Recognition of the Duration and Prediction of Insect Prevalence of Stored Rough Rice Infested by the Red Flour Beetle (Tribolium castaneum Herbst) Using an Electronic Nose.

The purpose of this research is to explore the feasibility of applying an electronic nose for the intelligent monitoring of injurious insects in a stored grain environment. In this study, we employed an electronic nose to sample rough rice that contained three degrees of red flour beetle (Tribolium castaneum Herbst) infestation for different durations-light degree (LD), middle degree (MD), and heavy degree (HD)-and manually investigated the insect situation at the same time. Manual insect situation investigation shows that, in all three rice treatments, the insect amounts gradually decreased after infestation. When the insect population of stored rough rice was under 13 insects per 60 g of rough rice, the natural speed of decrease of the insect population became very slow and reached the best artificial insect killing period. Linear discriminant analysis (LDA) provided good performance for MD and HD insect harm duration identification, but performed poorly for LD insect harm duration identification. Both k-means clustering analysis (K-means) and fuzzy c-means analysis (FCM) effectively identified the insect harm duration for stored rough rice. The results from the back-propagation artificial neural network (BPNN) insect prevalence prediction for the three degrees of rough rice infestation demonstrated that the electronic nose could effectively predict insect prevalence in stored grain (fitting coefficients were larger than 0.89). The predictive ability was best for LD, second best for MD, and least accurate for HD. This experiment demonstrates the feasibility of electronic noses for detecting both the duration and prevalence of an insect infestation in stored grain and provides a reference for the intelligent monitoring of an insect infestation in stored grains.

Quality Detection of Litchi Stored in Different Environments Using an Electronic Nose.

The purpose of this paper was to explore the utility of an electronic nose to detect the quality of litchi fruit stored in different environments. In this study, a PEN3 electronic nose was adopted to test the storage time and hardness of litchi that were stored in three different types of environment (room temperature, refrigerator and controlled-atmosphere). After acquiring data about the hardness of the sample and from the electronic nose, linear discriminant analysis (LDA), canonical correlation analysis (CCA), BP neural network (BPNN) and BP neural network-partial least squares regression (BPNN-PLSR), were employed for data processing. The experimental results showed that the hardness of litchi fruits stored in all three environments decreased during storage. The litchi stored at room temperature had the fastest rate of decrease in hardness, followed by those stored in a refrigerator environment and under a controlled-atmosphere. LDA has a poor ability to classify the storage time of the three environments in which litchi was stored. BPNN can effectively recognize the storage time of litchi stored in a refrigerator and a controlled-atmosphere environment. However, the BPNN classification of the effect of room temperature storage on litchi was poor. CCA results show a significant correlation between electronic nose data and hardness data under the room temperature, and the correlation is more obvious for those under the refrigerator environment and controlled-atmosphere environment. The BPNN-PLSR can effectively predict the hardness of litchi under refrigerator storage conditions and a controlled-atmosphere environment. However, the BPNN-PLSR prediction of the effect of room temperature storage on litchi and global environment storage on litchi were poor. Thus, this experiment proved that an electronic nose can detect the quality of litchi under refrigeratored storage and a controlled-atmosphere environment. These results provide a useful reference for future studies on nondestructive and intelligent monitoring of fruit quality.

Improved algorithms for the classification of rough rice using a bionic electronic nose based on PCA and the Wilks distribution.

Principal Component Analysis (PCA) is one of the main methods used for electronic nose pattern recognition. However, poor classification performance is common in classification and recognition when using regular PCA. This paper aims to improve the classification performance of regular PCA based on the existing Wilks Λ-statistic (i.e., combined PCA with the Wilks distribution). The improved algorithms, which combine regular PCA with the Wilks Λ-statistic, were developed after analysing the functionality and defects of PCA. Verification tests were conducted using a PEN3 electronic nose. The collected samples consisted of the volatiles of six varieties of rough rice (Zhongxiang1, Xiangwan13, Yaopingxiang, WufengyouT025, Pin 36, and Youyou122), grown in same area and season. The first two principal components used as analysis vectors cannot perform the rough rice varieties classification task based on a regular PCA. Using the improved algorithms, which combine the regular PCA with the Wilks Λ-statistic, many different principal components were selected as analysis vectors. The set of data points of the Mahalanobis distance between each of the varieties of rough rice was selected to estimate the performance of the classification. The result illustrates that the rough rice varieties classification task is achieved well using the improved algorithm. A Probabilistic Neural Networks (PNN) was also established to test the effectiveness of the improved algorithms. The first two principal components (namely PC1 and PC2) and the first and fifth principal component (namely PC1 and PC5) were selected as the inputs of PNN for the classification of the six rough rice varieties. The results indicate that the classification accuracy based on the improved algorithm was improved by 6.67% compared to the results of the regular method. These results prove the effectiveness of using the Wilks Λ-statistic to improve the classification accuracy of the regular PCA approach. The results also indicate that the electronic nose provides a non-destructive and rapid classification method for rough rice.

Estimation of the age and amount of brown rice plant hoppers based on bionic electronic nose use.

The brown rice plant hopper (BRPH), Nilaparvata lugens (Stal), is one of the most important insect pests affecting rice and causes serious damage to the yield and quality of rice plants in Asia. This study used bionic electronic nose technology to sample BRPH volatiles, which vary in age and amount. Principal component analysis (PCA), linear discrimination analysis (LDA), probabilistic neural network (PNN), BP neural network (BPNN) and loading analysis (Loadings) techniques were used to analyze the sampling data. The results indicate that the PCA and LDA classification ability is poor, but the LDA classification displays superior performance relative to PCA. When a PNN was used to evaluate the BRPH age and amount, the classification rates of the training set were 100% and 96.67%, respectively, and the classification rates of the test set were 90.67% and 64.67%, respectively. When BPNN was used for the evaluation of the BRPH age and amount, the classification accuracies of the training set were 100% and 48.93%, respectively, and the classification accuracies of the test set were 96.67% and 47.33%, respectively. Loadings for BRPH volatiles indicate that the main elements of BRPHs' volatiles are sulfur-containing organics, aromatics, sulfur-and chlorine-containing organics and nitrogen oxides, which provide a reference for sensors chosen when exploited in specialized BRPH identification devices. This research proves the feasibility and broad application prospects of bionic electronic noses for BRPH recognition.

Salicin alleviates periodontitis via Tas2r143/gustducin signaling in fibroblasts.

Introduction: Cells expressing taste signaling elements in non-gustatory tissues have been described as solitary chemosensory cells (SCCs) or tuft cells. These "taste-like" cells play a critical role in the maintenance of tissue homeostasis. Although the expression of SCC markers and taste signaling constituents has been identified in mouse gingivae, their role in periodontal homeostasis is still unclear. Methods: Public RNA sequencing datasets were re-analyzed and further validated with RT-PCR/qRT-PCR and immunofluorescent staining to explore the expression of TAS2Rs and downstream signaling constituents in mouse gingival fibroblasts (MGFs). The specific action of salicin on MGFs via Tas2r143 was validated with RNA silence, heterologous expression of taste receptor/Gα-gustducin and calcium imaging. The anti-inflammatory effects of salicin against LPS-induced MGFs were investigated in cell cultures, and were further validated with a ligature-induced periodontitis mouse model using Ga-gustducin-null (Gnat3-/-) mice. Results: The expression of Tas2r143, Gnat3, Plcb2, and TrpM5 was detected in MGFs. Moreover, salicin could activate Tas2r143, elicited taste signaling and thus inhibited LPS-induced chemokines expression (CXCL1, CXCL2, and CXCL5) in MGFs. Consistently, salicin-treatment inhibited periodontal bone loss, inflammatory/chemotactic factors expression, and neutrophil infiltration in periodontitis mice, while these effects were abolished in Gnat3-/- mice. Discussion: Gingival fibroblasts play a critical role in the maintenance of periodontal homeostasis via "SCC-like" activity. Salicin can activate Tas2r143-mediated bitter taste signaling and thus alleviate periodontitis in mouse, indicating a promising approach to the resolution of periodontal inflammation via stimulating the "SCC-like" function of gingival fibroblasts.

Genomic Analysis of Kitasatospora setae to Explore Its Biosynthetic Potential Regarding Secondary Metabolites.

Actinomycetes have long been recognized as important sources of clinical antibiotics. However, the exploration of rare actinomycetes, despite their potential for producing bioactive molecules, has remained relatively limited compared to the extensively studied Streptomyces genus. The extensive investigation of Streptomyces species and their natural products has led to a diminished probability of discovering novel bioactive compounds from this group. Consequently, our research focus has shifted towards less explored actinomycetes, beyond Streptomyces, with particular emphasis on Kitasatospora setae (K. setae). The genome of K. setae was annotated and analyzed through whole-genome sequencing using multiple bio-informatics tools, revealing an 8.6 Mbp genome with a 74.42% G + C content. AntiSMASH analysis identified 40 putative biosynthetic gene clusters (BGCs), approximately half of which were recessive and unknown. Additionally, metabolomic mining utilizing mass spectrometry demonstrated the potential for this rare actinomycete to generate numerous bioactive compounds such as glycosides and macrolides, with bafilomycin being the major compound produced. Collectively, genomics- and metabolomics-based techniques confirmed K. setae's potential as a bioactive secondary metabolite producer that is worthy of further exploration.

Effects of Nanomaterials on Synthesis and Degradation of the Extracellular Matrix.

Extracellular matrix (ECM) remodeling is accompanied by the continuous synthesis and degradation of the ECM components. This dynamic process plays an important role in guiding cell adhesion, migration, proliferation, and differentiation, as well as in tissue development, body repair, and maintenance of homeostasis. Nanomaterials, due to their photoelectric and catalytic properties and special structure, have garnered much attention in biomedical fields for use in processes such as tissue engineering and disease treatment. Nanomaterials can reshape the cell microenvironment by changing the synthesis and degradation of ECM-related proteins, thereby indirectly changing the behavior of the surrounding cells. This review focuses on the regulatory role of nanomaterials in the process of cell synthesis of different ECM-related proteins and extracellular protease. We discuss influencing factors and possible related mechanisms of nanomaterials in ECM remodeling, which may provide different insights into the design and development of nanomaterials for the treatment of ECM disorder-related diseases.

Overexpression of immunoglobulin G prompts cell proliferation and inhibits cell apoptosis in human urothelial carcinoma.

Only B lymphocytes can express immunoglobulins according to the traditional immunological theories, and the expression of immunoglobulin G (IgG) messenger RNA (mRNA) and protein was found in certain human cancer cells recently. However, the expression pattern of IgG and its possible role in human urothelial carcinoma are still elusive. In this study, we investigated the expression of IgG in two human urothelial carcinoma cell lines, T24 and BIU-87, and in 56 cases of clinical urothelial carcinoma tissues. The mRNA of IgG was positively detected by in situ hybridization and reverse transcription PCR; furthermore, IgG protein was also positively detected by immunohistochemistry and Western blot. Moreover, blockade of tumor-derived IgG by either antihuman IgG antibody or antisense oligonucleotides increased cell apoptosis and inhibited cell growth in bladder cancer cell lines in vitro, and antihuman IgG antibody could suppress the growth of xenotransplant tumor in vivo. In addition, either antihuman IgG antibody or antisense oligonucleotides enhanced the sensitivity to mitomycin C in bladder cancer cell line T24. Furthermore, blockade of IgG in bladder cancer cell T24 resulted in upregulation of cleaved caspase-3 and cleaved poly(ADP-ribose) polymerase. Our results indicated that bladder cancer cells were capable of expressing IgG, and blockade of IgG expression induced cell apoptosis through activation of caspase-dependent pathway. A novel potential targeted therapy for bladder cancer will be possibly developed based on these data.

Occurrence Characteristics of Water in Nano-Slit Pores under Different Solution Conditions: A Case Study on Kaolinite.

The presence of water in narrow pore spaces affects the occurrence and flow of methane, which in turn affects shale gas production. Therefore, studying the occurrence and distribution characteristics of water is of great significance to predict gas production. Based on molecular dynamics simulations, this study investigated the occurrence characteristics and influencing variables of liquid water in kaolinite nanopores in situ. Owing to its widespread distribution, kaolinite is the most prevalent clay mineral with two surfaces with different characteristics. Three systems of pure water, a CaCl2 solution, and a H2O/CH4 mixed phase were created at varied temperatures (80-120 °C) and pressures (70-120 MPa). The presence of gas and water in the nanopores was investigated thoroughly. The results showed that the adsorption of water on the Al-O octahedral surface of kaolinite was not affected by external conditions under in situ conditions, whereas the adsorption of water on the Si-O tetrahedral surface decreased with increasing temperature, but the change was small. When ions were present in the system, the water capacity decreased. Based on the aforementioned results, external conditions, such as temperature and pressure do not affect the basic state of water. However, if there are more than two fluid types in the system, the adsorption of water on the mineral surface is reduced owing to competitive adsorption. In addition, a CH4-H2O mixed system was simulated, in which methane molecules were distributed in clusters. There are two types of adsorptions in pores: gas-solid interactions and solid-liquid-gas interactions. CH4 molecules are thought to be clustered in water molecules because of the strong hydrogen bonding interactions among the water.

[Vertical Pollution Characteristics and Source Analysis of Soil PAHs in Different Land Use Types].

In order to study the vertical pollution characteristics of polycyclic aromatic hydrocarbons (PAHs) in soils of different land use types in suburban areas of Nanjing, 15 types of controlled PAHs were studied in each section (0-100 cm) of soils from six different land use types, including a vegetable field, forestland, residential area, urban land, paddy field, and industrial area. The vertical distribution and composition characteristics, influencing factors, and sources of PAHs were analyzed. The results showed that:the total concentrations of Σ15PAHs in the six sampling site profiles were as follows:vegetable field (69.3-299.2 µg·kg-1), forestland (20.8-128.3 µg·kg-1), residential area (30.7-142.1 µg·kg-1), urban land (185.6-1728.7 µg·kg-1), paddy field (208.3-693.0 µg·kg-1), and industrial area (165.6-739.2 µg·kg-1). There was no pollution in the residential area or forestland and a light pollution level in the vegetable field, medium pollution level in the paddy field and industrial area, and more serious pollution in the urban land. Soil PAHs were mainly distributed in the surface or subsurface layer, except in the residential area and urban land; however, they were still detected in the deep layers, and high-molecular-weight PAHs were dominant in most depths and sampling sites. The vertical distribution and migration of PAHs in soils were affected by molecular characteristics and component concentrations of PAHs, soil physical and chemical properties, and land use types. PMF source analysis indicated that coke sources, traffic sources, and coal combustion sources from human activities were the main sources of PAHs in this study region.

Crop pest image classification based on improved densely connected convolutional network.

Introduction: Crop pests have a great impact on the quality and yield of crops. The use of deep learning for the identification of crop pests is important for crop precise management. Methods: To address the lack of data set and poor classification accuracy in current pest research, a large-scale pest data set named HQIP102 is built and the pest identification model named MADN is proposed. There are some problems with the IP102 large crop pest dataset, such as some pest categories are wrong and pest subjects are missing from the images. In this study, the IP102 data set was carefully filtered to obtain the HQIP102 data set, which contains 47,393 images of 102 pest classes on eight crops. The MADN model improves the representation capability of DenseNet in three aspects. Firstly, the Selective Kernel unit is introduced into the DenseNet model, which can adaptively adjust the size of the receptive field according to the input and capture target objects of different sizes more effectively. Secondly, in order to make the features obey a stable distribution, the Representative Batch Normalization module is used in the DenseNet model. In addition, adaptive selection of whether to activate neurons can improve the performance of the network, for which the ACON activation function is used in the DenseNet model. Finally, the MADN model is constituted by ensemble learning. Results: Experimental results show that MADN achieved an accuracy and F1Score of 75.28% and 65.46% on the HQIP102 data set, an improvement of 5.17 percentage points and 5.20 percentage points compared to the pre-improvement DenseNet-121. Compared with ResNet-101, the accuracy and F1Score of MADN model improved by 10.48 percentage points and 10.56 percentage points, while the parameters size decreased by 35.37%. Deploying models to cloud servers with mobile application provides help in securing crop yield and quality.

AID-induced CXCL12 upregulation enhances castration-resistant prostate cancer cell metastasis by stabilizing ß-catenin expression.

Prostate cancer (PCa) is one of the most common malignant diseases of urinary system and has poor prognosis after progression to castration-resistant prostate cancer (CRPC), and increased cytosine methylation heterogeneity is associated with the more aggressive phenotype of PCa cell line. Activation-induced cytidine deaminase (AID) is a multifunctional enzyme and contributes to antibody diversification. However, the dysregulation of AID participates in the progression of multiple diseases and related with certain oncogenes through demethylation. Nevertheless, the role of AID in PCa remains elusive. We observed a significant upregulation of AID expression in PCa samples, which exhibited a negative correlation with E-cadherin expression. Furthermore, AID expression is remarkably higher in CRPC cells than that in HSPC cells, and AID induced the demethylation of CXCL12, which is required to stabilize the Wnt signaling pathway executor ß-catenin and EMT procedure. Our study suggests that AID drives CRPC metastasis by demethylation and can be a potential therapeutic target for CRPC.