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Although inflammatory responses are a critical component in defense against pathogens, too much inflammation is harmful. Mechanisms have evolved to regulate inflammation, including modulation by the anti-inflammatory cytokine interleukin-10 (IL-10). Previously we have shown that taste buds express various molecules involved in innate immune responses, including the proinflammatory cytokine tumor necrosis factor (TNF). Here, using a reporter mouse strain, we show that taste cells also express the anti-inflammatory cytokine IL-10. Remarkably, IL-10 is produced by only a specific subset of taste cells, which are different from the TNF-producing cells in mouse circumvallate and foliatetaste buds: IL-10 expression was found exclusively inthe G-protein gustducin-expressing bitter receptor cells, while TNF was found in sweet and umami receptor cells as reported previously. In contrast, IL-10R1, the ligand-binding subunit of the IL-10 receptor, is predominantly expressed by TNF-producing cells, suggesting a novel cellular hierarchy for regulating TNF production and effects in taste buds. In response to inflammatory challenges, taste cells can increase IL-10 expression both in vivo and in vitro. These findings suggest that taste buds use separate populations of taste receptor cells that coincide with sweet/umami and bitter taste reception to modulate local inflammatory responses, a phenomenon that has not been previously reported. Furthermore, IL-10 deficiency in mice leads to significant reductions in the number and size of taste buds, as well as in the number of taste receptor cells per taste bud, suggesting that IL-10 plays critical roles in maintaining structural integrity of the peripheral gustatory system. [ABSTRACT FROM AUTHOR]

While our understanding of the molecular and cellular aspects of taste reception and signaling continues to improve, the aberrations in these processes that lead to taste dysfunction remain largely unexplored. Abnormalities in taste can develop in a variety of diseases, including infections and autoimmune disorders. In this study, we used a mouse model of autoimmune disease to investigate the underlying mechanisms of taste disorders. MRL/MpJ-Faslpr/J (MRL/lpr) mice develop a systemic autoimmunity with phenotypic similarities to human systemic lupus erythematosus and Sjögren's syndrome. Our results show that the taste tissues of MRL/lpr mice exhibit characteristics of inflammation, including infiltration of T lymphocytes and elevated levels of some inflammatory cytokines. Histological studies reveal that the taste buds of MRL/lpr mice are smaller than those of wild-type congenic control (MRL/+/+) mice. 5-Bromo-2'-deoxyuridine (BrdU) pulse-chase experiments show that fewer BrdU-labeled cells enter the taste buds of MRL/lpr mice, suggesting an inhibition of taste cell renewal. Real-time RT-PCR analyses show that mRNA levels of several type II taste cell markers are lower in MRL/lpr mice. Immunohistochemical analyses confirm a significant reduction in the number of gustducin-positive taste receptor cells in the taste buds of MRL/lpr mice. Furthermore, MRL/lpr mice exhibit reduced gustatory nerve responses to the bitter compound quinine and the sweet compound saccharin and reduced behavioral responses to bitter, sweet, and umami taste substances compared with controls. In contrast, their responses to salty and sour compounds are comparable to those of control mice in both nerve recording and behavioral experiments. Together, our results suggest that type II taste receptor cells, which are essential for bitter, sweet, and umami taste reception and signaling, are selectively affected in MRL/lpr mice, a model for autoimmune disease with chronic inflammation. [ABSTRACT FROM AUTHOR]

This study was conducted to investigate the pollution load index, fraction distributions, and mobility of Pb, Cd, Cu, and Zn in garden and paddy soils collected from a Pb/Zn mine in Chenzhou City, China. The samples were analyzed using Leleyter and Probst’s sequential extraction procedures. Total metal concentrations including Pb, Cd, Cu, and Zn exceeded the maximum permissible limits for soils set by the Ministry of Environmental Protection of China, and the order of the pollution index was Cd > Zn > Pb > Cu, indicating that the soils from both sites seriously suffered from heavy metal pollution, especially Cd. The sums of metal fractions were in agreement with the total contents of heavy metals. However, there were significant differences in fraction distributions of heavy metals in garden and paddy soils. The residual fractions of heavy metals were the predominant form with 43.0% for Pb, 32.3% for Cd, 33.5% for Cu, and 44.2% for Zn in garden soil, while 51.6% for Pb, 40.4% for Cd, 40.3% for Cu, and 40.9% for Zn in paddy soil. Furthermore, the proportions of water-soluble and exchangeable fractions extracted by the selected analytical methods were the lowest among all fractions. On the basis of the speciation of heavy metals, the mobility factor values of heavy metals have the following order: Cd (25.2–19.8%) > Cu (22.6–6.3%) > Zn (9.6–6.0%) > Pb (6.7–2.5%) in both contaminated soils. [ABSTRACT FROM AUTHOR]

Background: Chronic rhinosinusitis (CRS) is a complex heterogeneous inflammatory disease that affects the nasal cavity, but the pathological examination of the olfactory mucosa (OM) in this disease has been limited. Methods: Nasal biopsy specimens were obtained from 20 control subjects and 50 CRS patients in conjunction with clinical assessments. Histopathology of these nasal biopsy specimens was performed and immunohistochemistry was used to characterize nonneuronal, neuronal, and inflammatory cells in the OM. These OM characteristics were then evaluated to determine the degree to which pathological features may be related to smell loss in CRS. Results: Histopathological examination of control and CRS OM revealed changes in the normal pseudostratified olfactory epithelium (OE): intermixing of goblet cells, metaplasia to squamous-like cells, and erosion of the OE. Lower percentages of normal epithelium and olfactory sensory neurons were found in CRS OE compared with controls. Relative to other CRS patients, those with anosmia had the greatest amount of OE erosion, the highest density of eosinophils infiltrating the OE, and exhibited the most extensive abnormalities on CT and endoscopic examination, including being significantly more likely to exhibit nasal polyposis. Conclusion: Our results suggest that OM pathology observed in nasal biopsy specimens can assist in understanding the degree of epithelial change and sensorineural damage in CRS and the potential for olfactory loss. [ABSTRACT FROM AUTHOR]

Abstract: The fraction distributions of heavy metals have attracted more attention because of the relationship between the toxicity and their speciation. Heavy-metal fraction distributions in soil contaminated with mine tailings (soil A) and in soil irrigated with mine wastewater (soil B), before and after treatment with disodium ethylenediaminetetraacetic acid (EDTA), were analyzed with Tessier's sequential extraction procedures. The total contents of lead (Pb), cadmium (Cd), copper (Cu), and zinc (Zn) exceeded the maximum permissible levels by 5.1, 33.3, 3.1, and 8.0 times in soil A and by 2.6, 12.0, 0.2, and 1.9 times in soil B, respectively. The results showed that both soils had high levels of heavy-metal pollution. Although the fractions were found in different distribution before extraction, the residual fraction was found to be the predominant fraction of the four heavy metals. There was a small amount of exchangeable fraction of heavy metals in both contaminated soils. Furthermore, in this study, the extraction efficiencies of Pb, Cd, and Cu were higher than those of Zn. After extraction, the concentrations of exchangeable Pb, Cd, Cu, and Zn increased 84.7 mg·kg-1, 0.3 mg·kg-1, 4.1 mg·kg-1, and 39.9 mg·kg-1 in soil A and 48.7 mg·kg-1, 0.6 mg·kg-1, 2.7 mg·kg-1, and 44.1 mg·kg-1 in soil B, respectively. The concentrations of carbonate, iron and manganese oxides, organic matter, and residue of heavy metals decreased. This implies that EDTA increased metal mobility and bioavailability and may lead to groundwater contamination. [ABSTRACT FROM AUTHOR]

Summary Many efforts have been made in developing bioinformatics algorithms to predict functional attributes of genes and proteins from their primary sequences. One challenge in this process is to intuitively analyze and to understand the statistical features that have been selected by heuristic or iterative methods. In this paper, we developed VisFeature, which aims to be a helpful software tool that allows the users to intuitively visualize and analyze statistical features of all types of biological sequence, including DNA, RNA and proteins. VisFeature also integrates sequence data retrieval, multiple sequence alignments and statistical feature generation functions. Availability and implementation VisFeature is a desktop application that is implemented using JavaScript/Electron and R. The source codes of VisFeature are freely accessible from the GitHub repository (https://github.com/wangjun1996/VisFeature). The binary release, which includes an example dataset, can be freely downloaded from the same GitHub repository (https://github.com/wangjun1996/VisFeature/releases). Supplementary information Supplementary data are available at Bioinformatics online. [ABSTRACT FROM AUTHOR]

Assesses the quality of nitric oxide (NO) released by macrophages in regulating Chlamydia-induced disease. Determination on the susceptibility of disease with NO production; Effects to differences in the innate immune responses; Analysis on the immunosuppressive mechanism for NO production.

ADP-ribosylation factors (Arfs) and Arf-like (Arl) GTPases are key regulators of intracellular vesicle trafficking and Golgi structure. Both Arf and Arl proteins cycle between active GTP-bound and inactive GDP-bound forms, where guanine nucleotide exchange factors (GEFs) regulate the exchange of GDP for GTP, whereas GTPase-activating proteins (GAPs) promote the hydrolysis of bound GTP. Human Arl1 is located at the trans-Golgi network (TGN) and regulates the function and structure of the Golgi complex. However, neither GEFs nor GAPs for human Arl1 have been identified. Here, we report that ArfGAP1, an Arf1 GAP, can promote GTP hydrolysis of Arl1. We show that ArfGAP1 directly interacts with GTP-bound Arl1 and exhibits GAP activity toward Arl1 in vitro. Exogenous expression of ArfGAP1, but not ArfGAP2 and ArfGAP3, causes dissociation of endogenous Arl1 from the TGN. In addition, GAP activity-deficient ArfGAP1 fails to regulate the Golgi localization of Arl1. Using an activity pull-down assay, we demonstrated that ArfGAP1 regulates the levels of Arl1-GTP in cells expressing ArfGAP1-myc or with ArfGAP1 knockdown. Finally, we observed that, similar to expression of putative active Arl1 (Arl1QL), ArfGAP1 knockdown impairs endosome-to-TGN retrograde transport of the Shiga toxin B-subunit. Thus, our findings support the idea that ArfGAP1 acts as an Arl1 GAP to regulate the function of Arl1 in vesicle trafficking at the TGN. [ABSTRACT FROM AUTHOR]

Drug repositioning provides a promising and efficient strategy to discover potential associations between drugs and diseases. Many systematic computational drug-repositioning methods have been introduced, which are based on various similarities of drugs and diseases. In this work, we proposed a new computational model, DDA-SKF (drug–disease associations prediction using similarity kernels fusion), which can predict novel drug indications by utilizing similarity kernel fusion (SKF) and Laplacian regularized least squares (LapRLS) algorithms. DDA-SKF integrated multiple similarities of drugs and diseases. The prediction performances of DDA-SKF are better, or at least comparable, to all state-of-the-art methods. The DDA-SKF can work without sufficient similarity information between drug indications. This allows us to predict new purpose for orphan drugs. The source code and benchmarking datasets are deposited in a GitHub repository (https://github.com/GCQ2119216031/DDA-SKF).

Long non-coding RNAs (lncRNAs) play an important role in serval biological activities, including transcription, splicing, translation, and some other cellular regulation processes. lncRNAs perform their biological functions by interacting with various proteins. The studies on lncRNA-protein interactions are of great value to the understanding of lncRNA functional mechanisms. In this paper, we proposed a novel model to predict potential lncRNA-protein interactions using the SKF (similarity kernel fusion) and LapRLS (Laplacian regularized least squares) algorithms. We named this method the LPI-SKF. Various similarities of both lncRNAs and proteins were integrated into the LPI-SKF. LPI-SKF can be applied in predicting potential interactions involving novel proteins or lncRNAs. We obtained an AUROC (area under receiver operating curve) of 0.909 in a 5-fold cross-validation, which outperforms other state-of-the-art methods. A total of 19 out of the top 20 ranked interaction predictions were verified by existing data, which implied that the LPI-SKF had great potential in discovering unknown lncRNA-protein interactions accurately. All data and codes of this work can be downloaded from a GitHub repository (https://github.com/zyk2118216069/LPI-SKF).

Eukaryotic cells contain numerous components, which are known as subcellular compartments or subcellular organelles. Proteins must be sorted to proper subcellular compartments to carry out their molecular functions. Mis-localized proteins are related to various cancers. Identifying mis-localized proteins is important in understanding the pathology of cancers and in developing therapies. However, experimental methods, which are used to determine protein subcellular locations, are always costly and time-consuming. We tried to identify cancer-related mis-localized proteins in three different cancers using computational approaches. By integrating gene expression profiles and dynamic protein-protein interaction networks, we established DPPN-SVM (Dynamic Protein-Protein Network with Support Vector Machine), a predictive model using the SVM classifier with diffusion kernels. With this predictive model, we identified a number of mis-localized proteins. Since we introduced the dynamic protein-protein network, which has never been considered in existing works, our model is capable of identifying more mis-localized proteins than existing studies. As far as we know, this is the first study to incorporate dynamic protein-protein interaction network in identifying mis-localized proteins in cancers.

Long non-coding RNAs (lncRNAs) play important roles in various biological processes, where lncRNA–protein interactions are usually involved. Therefore, identifying lncRNA–protein interactions is of great significance to understand the molecular functions of lncRNAs. Since the experiments to identify lncRNA–protein interactions are always costly and time consuming, computational methods are developed as alternative approaches. However, existing lncRNA–protein interaction predictors usually require prior knowledge of lncRNA–protein interactions with experimental evidences. Their performances are limited due to the number of known lncRNA–protein interactions. In this paper, we explored a novel way to predict lncRNA–protein interactions without direct prior knowledge. MiRNAs were picked up as mediators to estimate potential interactions between lncRNAs and proteins. By validating our results based on known lncRNA–protein interactions, our method achieved an AUROC (Area Under Receiver Operating Curve) of 0.821, which is comparable to the state-of-the-art methods. Moreover, our method achieved an improved AUROC of 0.852 by further expanding the training dataset. We believe that our method can be a useful supplement to the existing methods, as it provides an alternative way to estimate lncRNA–protein interactions in a heterogeneous network without direct prior knowledge. All data and codes of this work can be downloaded from GitHub (https://github.com/zyk2118216069/LncRNA-protein-interactions-prediction).

BACKGROUND Exposure to air pollution (AP) during pregnancy is associated with pre-labor rupture of membranes (PROM). However, there is limited research on this topic, and the sensitive exposure windows remain unclear. The present study assessed the association between AP exposure and the risk of PROM, as well as seeking to identify the sensitive time windows. MATERIAL AND METHODS This retrospective study analyzed 4276 pregnant women's data from Tongling Maternal and Child Health Hospital from 2020 to 2022. We obtained air pollution data, including particulate matter (PM) with an aerodynamic diameter of ≤2.5 μm (PM₂․₅), particulate matter with an aerodynamic diameter of ≤10 μm (PM₁₀), nitrogen dioxide (NO₂), and ozone (O₃), from the Tongling Ecology and Environment Bureau. Demographic information was extracted from medical records. We employed a distributed lag model to identify the sensitive exposure windows of prenatal AP affecting the risk of PROM. We conducted a sensitivity analysis based on pre-pregnancy BMI. RESULTS We found a significant association between prenatal exposure to AP and increased PROM risk after adjusting for confounders, and the critical exposure windows of AP were the 6th to 7th months of pregnancy. In the underweight group, an increase of 10 µg/m³ in PM₂․₅ was associated with a risk of PROM, with an odds ratio (OR) of 1.48 (95% CI: 1.16, 1.89). Similarly, a 10 µg/m³ increase in PM₁₀ was associated with a risk of PROM, with an OR of 1.45 (95% CI: 1.05, 1.77). CONCLUSIONS Prenatal exposure to AP, particularly during months 6-7 of pregnancy, is associated with an increased risk of PROM. This study extends and strengthens the evidence on the association between prenatal exposure to AP and the risk of PROM, specifically identifying the critical exposure windows.

Long non-coding RNAs (LncRNAs) are a type of RNA with little or no protein-coding ability. Their length is more than 200 nucleotides. A large number of studies have indicated that lncRNAs play a significant role in various biological processes, including chromatin organizations, epigenetic programmings, transcriptional regulations, post-transcriptional processing, and circadian mechanism at the cellular level. Since lncRNAs perform vast functions through their interactions with proteins, identifying lncRNA-protein interaction is crucial to the understandings of the lncRNA molecular functions. However, due to the high cost and time-consuming disadvantage of experimental methods, a variety of computational methods have emerged. Recently, many effective and novel machine learning methods have been developed. In general, these methods fall into two categories: semisupervised learning methods and supervised learning methods. The latter category can be further classified into the deep learning-based method, the ensemble learning-based method, and the hybrid method. In this paper, we focused on supervised learning methods. We summarized the state-of-the-art methods in predicting lncRNA-protein interactions. Furthermore, the performance and the characteristics of different methods have also been compared in this work. Considering the limits of the existing models, we analyzed the problems and discussed future research potentials., (Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.net.)

The active ingredients of Ficus hirta and Hypericum perforatum were collected from Traditional Chinese Medicine Database and Analysis Platform(TCMSP) and related papers. The potential targets of these two medicinal herbs were searched from HERB database, and those associated with microvascular angina were screened out from GeneCards, Online Mendelian Inheritance in Man(OMIM), Therapeutic Target Database(TTD), and HERB. Cytoscape was used to construct a protein-protein interaction(PPI) network of the common targets shared by the two herbs and microvascular angina based on the data of String platform. Metascape was employed to identify the involved biological processes and pathways enriched with the common targets. Cytoscape was used to draw the "active ingredient-target-pathway" network. AutoDock Vina was used to dock the core ingredients with the key targets. A total of 19 potential active ingredients and 71 potential targets were identified to be associated with microvascular angina. Bioinformatics analysis showed that phosphatidylinositol-3-kinase/protein kinase B(PI3 K-AKT), interleukin-17(IL17), hypoxia-inducible factor 1(HIF-1) and other signaling pathways were related to the treatment of microvascular angina by F. hirta and H. perforatum. Molecular docking results showed that β-sitosterol, luteolin and other ingredients had strong affinity with multiple targets including mitogen-associated protein kinase 1(MAPK1), epidermal growth factor receptor(EGFR) and so on. These findings indicated that F. hirta and H. perforatum may regulate PI3 K-AKT, IL17, HIF-1 and other signaling pathways by acting on multiple targets to alleviate oxidative stress, inhibit inflammatory response, regulate angiogenesis, and improve vascular endothelium and other functions. This study provides reference for in vitro and in vivo studies of the treatment of microvascular angina.

Long non-coding RNAs (lncRNAs) play an important role in serval biological activities, including transcription, splicing, translation, and some other cellular regulation processes. lncRNAs perform their biological functions by interacting with various proteins. The studies on lncRNA-protein interactions are of great value to the understanding of lncRNA functional mechanisms. In this paper, we proposed a novel model to predict potential lncRNA-protein interactions using the SKF (similarity kernel fusion) and LapRLS (Laplacian regularized least squares) algorithms. We named this method the LPI-SKF. Various similarities of both lncRNAs and proteins were integrated into the LPI-SKF. LPI-SKF can be applied in predicting potential interactions involving novel proteins or lncRNAs. We obtained an AUROC (area under receiver operating curve) of 0.909 in a 5-fold cross-validation, which outperforms other state-of-the-art methods. A total of 19 out of the top 20 ranked interaction predictions were verified by existing data, which implied that the LPI-SKF had great potential in discovering unknown lncRNA-protein interactions accurately. All data and codes of this work can be downloaded from a GitHub repository (https://github.com/zyk2118216069/LPI-SKF)., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2020 Zhou, Hu, Shen, Zhang and Du.)

Eukaryotic cells contain numerous components, which are known as subcellular compartments or subcellular organelles. Proteins must be sorted to proper subcellular compartments to carry out their molecular functions. Mis-localized proteins are related to various cancers. Identifying mis-localized proteins is important in understanding the pathology of cancers and in developing therapies. However, experimental methods, which are used to determine protein subcellular locations, are always costly and time-consuming. We tried to identify cancer-related mis-localized proteins in three different cancers using computational approaches. By integrating gene expression profiles and dynamic protein-protein interaction networks, we established DPPN-SVM (Dynamic Protein-Protein Network with Support Vector Machine), a predictive model using the SVM classifier with diffusion kernels. With this predictive model, we identified a number of mis-localized proteins. Since we introduced the dynamic protein-protein network, which has never been considered in existing works, our model is capable of identifying more mis-localized proteins than existing studies. As far as we know, this is the first study to incorporate dynamic protein-protein interaction network in identifying mis-localized proteins in cancers., (Copyright © 2020 Li, Du, Shen, Liu and Luo.)

Objective: To systematically evaluate the clinical effect and safety of acupuncture in the treatment of cardiac neurosis., Methods: Chinese databases (including SinoMed, VIP, CNKI, and Wanfang Data) and English databases (including PubMed and The Cochrane Library) were searched for randomized controlled trials (RCTs) on acupuncture in the treatment of cardiac neurosis published up to March 2019. Two reviewers independently screened the literature, extracted data, and assessed the risk of bias of included studies, and then RevMan 5.3 was used to perform a meta-analysis., Results: A total of 7 RCTs were included, with 491 patients with cardiac neurosis. The results of the meta-analysis showed that compared with the conventional western medicine group, the acupuncture group had a significantly higher total effective rate (risk ratio ［ RR ］=1.16, 95% CI ［1.05,1.28］, P =0.005) and had significantly greater improvements in Hamilton Anxiety Scale score (mean difference ［ MD ］=-3.22, 95% CI［-6.05, -0.39］, P =0.03). There were no significant differences between the two groups in Hamilton Depression Scale score ( MD =-1.92, 95% CI ［-4.76, -0.91］, P =0.18)，traditional Chinese medicine symptom score ( MD =-5.49, 95% CI ［-11.55, 0.56］, P =0.08), somatization symptom score ( MD =-0.91, 95% CI ［-3.28, 1.46］, P =0.45), and adverse reactions ( RR =0.67, 95% CI ［0.26,1.78］, P =0.42)., Conclusion: Acupuncture can alleviate the symptoms and is safe in the treatment of cardiac neurosis.

Systematic evaluation of the effectiveness and safety of Xiaoer Xiaoji Zhike Oral Liqud combined with azithromycin in the treatment of mycoplasma pneumonia in children. Clinical literatures were retrieved from PubMed, Cochrane Library, EMbase, VIP, CNKI, SinoMed, WanFang from inception to September 2019. Two reviewers independently screened out the literatures, extracted data and assessed the risk of bias of the included studies. Then, Meta-analysis was performed by RevMan 5.3 software. A total of 17 RCT were included, involving 1 712 patients. In this study, there were two subgroups by the application approach of azithromycin: oral azithromycin subgroup and intravenous azithromycin subgroup. According to Meta-analysis results, in terms of the alleviation of clinical symptoms and signs, such as shortening of antifebrile time, cough disappeared time, rales disappearance time, and lung X-ray infiltrating shadow disappearance time, Xiaoer Xiaoji Zhike Oral Liquid combined with oral azithromycin or intravenous azithromycin were better than single-dose azithromycin; in the aspect of the improvement of the overall effective rate, the two combination subgroups were better than the single-use azithromycin; In terms of the decline of IgM, the combination subgroups were also more efficient than the single-use azithromycin, with statistically significant differences. In terms of the incidence of adverse reactions, there was no significant difference between the two combination subgroups and the single-use azithromycin in children, and no serious adverse reactions were found. In inclusion, Xiaoer Xiaoji Zhike Oral Liquid combined with azithromycin can improve the clinical efficacy in treating pediatric mycoplasma pneumonia, with a high safety. Due to the limited quantity and quality of the included studies, more high-quality studies are needed to verify the above conclusion.

Long non-coding RNAs (lncRNAs) play important roles in various biological processes, where lncRNA-protein interactions are usually involved. Therefore, identifying lncRNA-protein interactions is of great significance to understand the molecular functions of lncRNAs. Since the experiments to identify lncRNA-protein interactions are always costly and time consuming, computational methods are developed as alternative approaches. However, existing lncRNA-protein interaction predictors usually require prior knowledge of lncRNA-protein interactions with experimental evidences. Their performances are limited due to the number of known lncRNA-protein interactions. In this paper, we explored a novel way to predict lncRNA-protein interactions without direct prior knowledge. MiRNAs were picked up as mediators to estimate potential interactions between lncRNAs and proteins. By validating our results based on known lncRNA-protein interactions, our method achieved an AUROC (Area Under Receiver Operating Curve) of 0.821, which is comparable to the state-of-the-art methods. Moreover, our method achieved an improved AUROC of 0.852 by further expanding the training dataset. We believe that our method can be a useful supplement to the existing methods, as it provides an alternative way to estimate lncRNA-protein interactions in a heterogeneous network without direct prior knowledge. All data and codes of this work can be downloaded from GitHub (https://github.com/zyk2118216069/LncRNA-protein-interactions-prediction)., (Copyright © 2020 Zhou, Shen, Yu, Luo, Gao and Du.)

Background: The endoplasmic reticulum (ER) is an important organelle in eukaryotic cells. It is involved in many important biological processes, such as cell metabolism, protein synthesis, and post-translational modification. The proteins that reside within the ER are called ER-resident proteins. These proteins are closely related to the biological functions of the ER. The difference between the ER-resident proteins and other non-resident proteins should be carefully studied. Methods: We developed a support vector machine (SVM)-based method. We developed a U-shaped weight-transfer function and used it, along with the positional-specific physiochemical properties (PSPCP), to integrate together sequence order information, signaling peptides information, and evolutionary information. Result: Our method achieved over 86% accuracy in a jackknife test. We also achieved roughly 86% sensitivity and 67% specificity in an independent dataset test. Our method is capable of identifying ER-resident proteins., (Copyright © 2019 Miao, Zhao, Li, Gao and Du.)

The multimedia fugacity model (Ⅲ) was used to simulate the distribution, transfer and fate of typical polybrominated diphenyl ethers (PBDEs) in air, water, soil and sediment in an electrical equipment dismantling area in eastern China. The modeling data were compared with monitored values in air, soil and sediment for validation purpose. Moreover, the transfer fluxes between different compartments were analyzed in order to infer the main transfer process. Parameters of the model were tested and the key parameters were identified using sensitivity analysis method for BDE47 and BDE209.The results of sensitivity analysis indicated that vapor pressure, the lg K ow value and half-life had significant influence on concentrations of PBDEs in different media. The results showed that when the system reached equilibrium, most of the PBDEs would be accumulated in soil and sediment. The air advection outflow and soil degradation were the major routes for PBDEs to disappear in the area. The results will provide the basis for the risk management of PBDEs contamination.

Objective: To observe preventive and therapeutic effects and the mechanism of actions on Zishen Yutai pill combined with progesterone on threatened abortion in rats., Methods: After pregnancy, 50 SPF female SD rats were selected and divided into control group, model group, progesterone group, Zishen Yutai pill group, and progesterone plus Zishen Yutai pill group (combination group), with 10 rats in each group. The rats of control group and abortion model group were lavaged with 2 mL/kg normal saline on pregnancy day 1 for continuous 10 days. Rats in Zishen Yutai pill group were given 1.575 g/kg/d of Zishen Yutai pill for intragastric administration for continuous 10 days. Rats in progesterone group were given intramuscular injection treatment of 0.1 mL/d progestin, continuous for 10 days. Rats in combination group were given injection therapy of aqueous solution of Zishen Yutai pill for continuous 10 days, and other treatments were the same as previous two groups. Abortion model were established then and live births, numbers of abortion and average rate of abortion were compared between the five groups. Peripheral blood was collected to detect the estradiol (E2) and progestational hormone (P), and obtain ratio of Th1/Th2 cytokines (IL-2, INF-γ, IL-4, IL-10)., Results: Significant more live births of rats were found in the control group compared with other four groups (P < 0.05) (P < 0.05). The numbers of live births of the rats in abortion model group were significantly less than that of progesterone group, Zishen Yutai pill group and joint group (P < 0.05). The numbers of live births of rats in joint group were significant more than that of progesterone group and Zishen Yutai pill group. The serum E2 level of P of rats in the control group, progesterone group, Zishen Yutai pill group and joint group were significant higher than that of abortion model group (P < 0.05). Serum levels of E2 and P of rats in the control group, progesterone group, Zishen Yutai pill group and joint group were not significant different (P > 0.05) but these levels in the control group and Zishen Yutai pill group were significant lower than that of progesterone group and joint group (P < 0.05). The maternal-fetal interface IL - 4/IL - 2, IL - 10/IL - 2 of model group were balanced deviating to Th1, while the IL-4/IL-2, IL-10/IL-2 of progesterone group, Zishen Yutai pill group and joint group were balanced deviating to Th2, and joint group' deviation was better than progesterone group and Zishen Yutai pill group (P < 0.05)., Conclusions: Zishen Yutai pill combined with progesterone has a significant control effect for threatened abortion, which can obviously increase contents of maternal serums E2 and P, and regulate the Th1/Th2 balance with a remarkable effect., (Copyright © 2016 Hainan Medical College. Production and hosting by Elsevier B.V. All rights reserved.)

In situ research was conducted on the response of mercury enrichment in rice organs to elevated gaseous elemental mercury (GEM) with open-top chambers (OTCs) fumigation experiment and soil Hg enriched experiment. The results showed that Hg concentrations in roots were generally correlated with soil Hg concentrations (R = 0.9988, P < 0.05) but insignificantly correlated with air Hg concentrations (P > 0.05), indicating that Hg in rice roots was mainly from soil. Hg concentrations in stems increased linearly (R(B) = 0.9646, R(U) = 0.9831, P < 0.05) with elevated GEM, and Hg concentrations in upper stems were usually higher than those in bottom stems in OTCs experiment. Hg concentrations in bottom stems were generally correlated with soil Hg concentrations (R = 0.9901, P < 0.05) and second-order polynomial (R = 0.9989, P < 0.05) was fitted for Hg concentrations in upper stems to soil Hg concentrations, and Hg concentrations in bottom stems were usually higher than those in upper stems in soil Hg enriched experiment, indicating the combining impact of Hg from air and soil on the accumulation of mercury in stems. Hg concentrations in foliage were significantly correlated (P < 0.05) with air Hg and linearly correlated with soil Hg (R = 0.9983, P = 0.0585), implying that mercury in foliage was mainly from air and some of Hg in root from soil was transferred to foliage through stem. Based on the function in these filed experiments, it was estimated that at least 60%-94% and 56%-77% of mercury in foliage and upper-stem of rice was from the atmosphere respectively, and yet only 8%-56% of mercury in bottom-stem was attributed to air. Therefore, mercury in rice aboveground biomass was mainly from the atmosphere, and these results will provide theoretical basis for the regional atmospheric mercury budgets and the model of mercury cycling.

The surface sediments in western lakeside belt of Taihu Lake were collected. The spatial distribution of nutrients and pollution evaluation were studied. The results showed that concentration of the nitrogen, phosphorus and organic matter in the surface sediments had an increasing tendency from inshore to the far shore. The concentration of organic matter in the sediments ranged from 2261.78 mg x kg(-1) to 11963.10 mg x kg(-1), with the average of 7 124.00 mg x kg(-1). Total nitrogen concentration in the sediments ranged from 343.20 mg x kg(-1) to 1 390.12 mg x kg(-1), with the average of 819.20 mg x kg(-1). The total phosphorus concentration in the sediments ranged from 197.46 mg x kg(-1) to 570.85 mg x kg(-1), with the average of 379.39 mg x kg(-1). The C/N ratio in the lake sediment was 9.5. Organic matter and nutrient were from alga and aquatic plant in lake. Based on the organic index and organic nitrogen, we can concluded that the surface sediments in western lakeside belt of Taihu Lake still belong to less clean category. The average values of organic index and organic nitrogen were 0.037% and 0.044%, respectively. The organic index and organic nitrogen in offshore were high, which indicated the risk of organic pollution.

This study was conducted to investigate the pollution load index, fraction distributions, and mobility of Pb, Cd, Cu, and Zn in garden and paddy soils collected from a Pb/Zn mine in Chenzhou City, China. The samples were analyzed using Leleyter and Probst's sequential extraction procedures. Total metal concentrations including Pb, Cd, Cu, and Zn exceeded the maximum permissible limits for soils set by the Ministry of Environmental Protection of China, and the order of the pollution index was Cd > Zn > Pb > Cu, indicating that the soils from both sites seriously suffered from heavy metal pollution, especially Cd. The sums of metal fractions were in agreement with the total contents of heavy metals. However, there were significant differences in fraction distributions of heavy metals in garden and paddy soils. The residual fractions of heavy metals were the predominant form with 43.0% for Pb, 32.3% for Cd, 33.5% for Cu, and 44.2% for Zn in garden soil, while 51.6% for Pb, 40.4% for Cd, 40.3% for Cu, and 40.9% for Zn in paddy soil. Furthermore, the proportions of water-soluble and exchangeable fractions extracted by the selected analytical methods were the lowest among all fractions. On the basis of the speciation of heavy metals, the mobility factor values of heavy metals have the following order: Cd (25.2-19.8%) > Cu (22.6-6.3%) > Zn (9.6-6.0%) > Pb (6.7-2.5%) in both contaminated soils.