MHESMMR: a multilevel model for predicting the regulation of miRNAs expression by small molecules.

According to the expression of miRNA in pathological processes, miRNAs can be divided into oncogenes or tumor suppressors. Prediction of the regulation relations between miRNAs and small molecules (SMs) becomes a vital goal for miRNA-target therapy. But traditional biological approaches are laborious and expensive. Thus, there is an urgent need to develop a computational model. In this study, we proposed a computational model to predict whether the regulatory relationship between miRNAs and SMs is up-regulated or down-regulated. Specifically, we first use the Large-scale Information Network Embedding (LINE) algorithm to construct the node features from the self-similarity networks, then use the General Attributed Multiplex Heterogeneous Network Embedding (GATNE) algorithm to extract the topological information from the attribute network, and finally utilize the Light Gradient Boosting Machine (LightGBM) algorithm to predict the regulatory relationship between miRNAs and SMs. In the fivefold cross-validation experiment, the average accuracies of the proposed model on the SM2miR dataset reached 79.59% and 80.37% for up-regulation pairs and down-regulation pairs, respectively. In addition, we compared our model with another published model. Moreover, in the case study for 5-FU, 7 of 10 candidate miRNAs are confirmed by related literature. Therefore, we believe that our model can promote the research of miRNA-targeted therapy.

Identification of key regulatory molecules in the early development stage of Alzheimer's disease.

Alzheimer's disease (AD) is one of the most common neurodegenerative diseases, the incidence of which increases with age, and the pathological changes in the brain are irreversible. Recent studies have highlighted the essential role of long noncoding RNAs (lncRNAs) in AD by acting as competing endogenous RNAs (ceRNAs). Our aim was to construct lncRNA-associated ceRNA regulatory networks composed of potential biomarkers for the early stage of AD. AD related datasets come from AlzData and GEO databases. The R package 'Limma' identifies differentially expressed genes (DEGs), Kyoto Encyclopedia of Genes and Genomes (KEGG) and Gene Ontology (GO) databases for functional enrichment analysis. Protein-protein interactions (PPIs) in DEGs were constructed in the STRING database, and Cytoscape software identified DEGs. Convergent functional genomics (CFG) analysis of differentially expressed hub genes (referred to as early-DEGs) in the brain before the development of AD pathology. The AlzData database analyses the expression levels of early-DEGs in different nerve cells. The lncRNA-miRNA-mRNA regulatory network was established according to the ceRNA hypothesis. We identified four lncRNAs (XIST, NEAT1, KCNQ1OT1 and HCG18) and four miRNAs (hsa-let-7c-5p, hsa-miR-107, hsa-miR-129-2-3p and hsa-miR-214-3p) were preliminarily identified as potential biomarkers for early AD, competitively regulating Atp6v0b, Atp6v1e1 Atp6v1f and Syt1. This study indicates that NEAT1, XIST, HCG18 and KCNQ1OT1 act as ceRNAs in competitive binding with miRNAs to regulate the expression of Atp6v0b, Atp6v1e1, Atp6v1f and Syt1 before the occurrence of pathological changes in AD.

Neuregulin 4 (Nrg4) cooperates with melatonin to regulate the PRL expression via ErbB4/Erk signaling pathway as a potential prolactin (PRL) regulator.

Neuregulin-4 (Nrg4) and melatonin play vital roles in endocrine diseases. However, there is little discussion about the function and potential mechanism of Nrg4 and melatonin in prolactin (PRL) regulation. The human normal pituitary data from Gene Expression Profiling Interactive Analysis (GEPIA) database was used to explore the correlation between NRG4 and PRL. The expression and correlation of NRG4 and PRL were determined by Immunofluorescence staining (IF) and human normal pituitary tissue microarray. Western Blot (WB) was used to detect the expression of PRL, p-ErbB2/3/4, ErbB2/3/4, p-Erk1/2, Erk1/2, p-Akt and Akt in PRL-secreting pituitary GH3 and RC-4B/C cells treated by Nrg4, Nrg4-small interfering RNA, Erk1/2 inhibitor FR180204 and melatonin. The expression of NRG4 was significantly positively correlated with that of PRL in the GEPIA database and normal human pituitary tissues. Nrg4 significantly increased the expression and secretion of PRL and p-Erk1/2 expression in GH3 cells and RC-4B/C cells. Inhibition of Nrg4 significantly inhibited PRL expression. The increased levels of p-Erk1/2 and PRL induced by Nrg4 were abolished significantly in response to FR180204 in GH3 and RC-4B/C cells. Additionally, Melatonin promotes the expression of Nrg4, p-ErbB4, p-Erk1/2, and PRL and can further promote the expression of p-Erk1/2 and PRL in combination with Nrg4. Further investigation into the function of Nrg4 and melatonin on PRL expression and secretion may provide new clues to advance the clinical control of prolactinomas and hyperprolactinemia.

A biomedical knowledge graph-based method for drug-drug interactions prediction through combining local and global features with deep neural networks.

Drug-drug interactions (DDIs) prediction is a challenging task in drug development and clinical application. Due to the extremely large complete set of all possible DDIs, computer-aided DDIs prediction methods are getting lots of attention in the pharmaceutical industry and academia. However, most existing computational methods only use single perspective information and few of them conduct the task based on the biomedical knowledge graph (BKG), which can provide more detailed and comprehensive drug lateral side information flow. To this end, a deep learning framework, namely DeepLGF, is proposed to fully exploit BKG fusing local-global information to improve the performance of DDIs prediction. More specifically, DeepLGF first obtains chemical local information on drug sequence semantics through a natural language processing algorithm. Then a model of BFGNN based on graph neural network is proposed to extract biological local information on drug through learning embedding vector from different biological functional spaces. The global feature information is extracted from the BKG by our knowledge graph embedding method. In DeepLGF, for fusing local-global features well, we designed four aggregating methods to explore the most suitable ones. Finally, the advanced fusing feature vectors are fed into deep neural network to train and predict. To evaluate the prediction performance of DeepLGF, we tested our method in three prediction tasks and compared it with state-of-the-art models. In addition, case studies of three cancer-related and COVID-19-related drugs further demonstrated DeepLGF's superior ability for potential DDIs prediction. The webserver of the DeepLGF predictor is freely available at http://120.77.11.78/DeepLGF/.

Protein Corona-Directed Cellular Recognition and Uptake of Polyethylene Nanoplastics by Macrophages.

The widespread use of plastic products in daily life has raised concerns about the health hazards associated with nanoplastics (NPs). When exposed, NPs are likely to infiltrate the bloodstream, interact with plasma proteins, and trigger macrophage recognition and clearance. In this study, we focused on establishing a correlation between the unique protein coronal signatures of high-density (HDPE) and low-density (LDPE) polyethylene (PE) NPs with their ultimate impact on macrophage recognition and cytotoxicity. We observed that low-density and high-density lipoprotein receptors (LDLR and SR-B1), facilitated by apolipoproteins, played an essential role in PE-NP recognition. Consequently, PE-NPs activated the caspase-3/GSDME pathway and ultimately led to pyroptosis. Advanced imaging techniques, including label-free scattered light confocal imaging and cryo-soft X-ray transmission microscopy with 3D-tomographic reconstruction (nano-CT), provided powerful insights into visualizing NPs-cell interactions. These findings underscore the potential risks of NPs to macrophages and introduce analytical methods for studying the behavior of NPs in biological systems.

Chromium(VI) Adsorption and Reduction in Soils under Anoxic Conditions: The Relative Roles of Iron (oxyhr)oxides, Iron(II), Organic Matters, and Microbes.

Chromium (Cr) transformation in soils mediated by iron (Fe) (oxyhr)oxides, Fe(II), organic matter (OM), and microbes is largely unexplored. Here, their coupling processes and mechanisms were investigated during anoxic incubation experiments of four Cr(VI) spiked soil samples with distinct physicochemical properties from the tropical and subtropical regions of China. It demonstrates that easily oxidizable organic carbon (EOC, 55-84%) and microbes (16-48%) drive Cr(VI) reduction in soils enriched with goethite and/or hematite, among which in dryland soils microbial sulfate reduction may also be involved. In contrast, EOC (38 ± 1%), microbes (33 ± 1%), and exchangeable and poorly crystalline Fe (oxyhr)oxide-associated Fe(II) (29 ± 3%) contribute to Cr(VI) reduction in paddy soils enriched with ferrihydrite. Additionally, exogenous Fe(II) and microbes significantly enhance Cr(VI) reduction in ferrihydrite- and goethite-rich soils, and Fe(II) greatly promotes but microbes slightly inhibit Cr passivation. Both Fe(II) and microbes, especially the latter, promote OM mineralization and result in the most substantial OM loss in ferrihydrite-rich paddy soils. During the incubation, part of the ferrihydrite converts to goethite but microbes may hinder the transformation. These results provide deep insights into the geochemical fates of redox-sensitive heavy metals mediated by the complicated effects of Fe, OM, and microbes in natural and engineered environments.

Vascular smooth muscle-specific LRRC8A knockout ameliorates angiotensin II-induced cerebrovascular remodeling by inhibiting the WNK1/FOXO3a/MMP signaling pathway.

Hypertensive cerebrovascular remodeling involves the enlargement of vascular smooth muscle cells (VSMCs), which activates volume-regulated Cl- channels (VRCCs). The leucine-rich repeat-containing family 8 A (LRRC8A) has been shown to be the molecular identity of VRCCs. However, its role in vascular remodeling during hypertension is unclear. In this study, we used vascular smooth muscle-specific LRRC8A knockout (CKO) mice and an angiotensin II (Ang II)-induced hypertension model. The results showed that cerebrovascular remodeling during hypertension was ameliorated in CKO mice, and extracellular matrix (ECM) deposition was reduced. Based on the RNA-sequencing analysis of aortic tissues, the level of matrix metalloproteinases (MMPs), such as MMP-9 and MMP-14, were reduced in CKO mice with hypertension, which was further verified in vivo by qPCR and immunofluorescence analysis. Knockdown of LRRC8A in VSMCs inhibited the Ang II-induced upregulation of collagen I, fibronectin, and matrix metalloproteinases (MMPs), and overexpression of LRRC8A had the opposite effect. Further experiments revealed an interaction between with-no-lysine (K)-1 (WNK1), which is a "Cl--sensitive kinase", and Forkhead transcription factor O3a (FOXO3a), which is a transcription factor that regulates MMP expression. Ang II induced the phosphorylation of WNK1 and downstream FOXO3a, which then increased the expression of MMP-2 and MMP-9. This process was inhibited or potentiated when LRRC8A was knocked down or overexpressed, respectively. Overall, these results demonstrate that LRRC8A knockout in vascular smooth muscle protects against cerebrovascular remodeling during hypertension by reducing ECM deposition and inhibiting the WNK1/FOXO3a/MMP signaling pathway, demonstrating that LRRC8A is a potential therapeutic target for vascular remodeling-associated diseases such as stroke.

Associations between immune cell phenotypes and lung cancer subtypes: insights from mendelian randomization analysis.

INTRODUCTION: Lung cancer is a common malignant tumor, and different types of immune cells may have different effects on the occurrence and development of lung cancer subtypes, including lung squamous cell carcinoma (LUSC) and lung adenocarcinoma (LUAD). However, the causal relationship between immune phenotype and lung cancer is still unclear. METHODS: This study utilized a comprehensive dataset containing 731 immune phenotypes from the European Bioinformatics Institute (EBI) to evaluate the potential causal relationship between immune phenotypes and LUSC and LUAD using the inverse variance weighted (IVW) method in Mendelian randomization (MR). Sensitivity analyses, including MR-Egger intercept, Cochran Q test, and others, were conducted for the robustness of the results. The study results were further validated through meta-analysis using data from the Transdisciplinary Research Into Cancer of the Lung (TRICL) data. Additionally, confounding factors were excluded to ensure the robustness of the findings. RESULTS: Among the final selection of 729 immune cell phenotypes, three immune phenotypes exhibited statistically significant effects with LUSC. CD28 expression on resting CD4 regulatory T cells (OR 1.0980, 95% CI: 1.0627-1.1344, p < 0.0001) and CD45RA + CD28- CD8 + T cell %T cell (OR 1.0011, 95% CI: 1.0007; 1.0015, p < 0.0001) were associated with increased susceptibility to LUSC. Conversely, CCR2 expression on monocytes (OR 0.9399, 95% CI: 0.9177-0.9625, p < 0.0001) was correlated with a decreased risk of LUSC. However, no significant causal relationships were established between any immune cell phenotypes and LUAD. CONCLUSION: This study demonstrates that specific immune cell types are associated with the risk of LUSC but not with LUAD. While these findings are derived solely from European populations, they still provide clues for a deeper understanding of the immunological mechanisms underlying lung cancer and may offer new directions for future therapeutic strategies and preventive measures.

Mono-2-ethylhexyl phthalate-induced downregulation of MMP11 in foreskin fibroblasts contributes to the pathogenesis of hypospadias.

Hypospadias is one of the most common congenital anomalies of the male urogenital system, and di(2-ethylhexyl) phthalate (DEHP), a widely used endocrine-disrupting chemical (EDC), is considered a significant risk factor for this condition. Mono-2-ethylhexyl phthalate (MEHP), the toxic active metabolite of DEHP, has been proven to affect penile development and ultimately result in the hypospadias phenotype. However, while it is acknowledged that hypospadias arises from the aberrant development of multiple penile tissues, the specific impact of MEHP on human foreskin tissue development and its underlying molecular mechanisms of action remain unclear. In this study, we constructed an in vitro toxicity assay for MEHP using human foreskin fibroblasts and employed high-throughput RNA sequencing to investigate the molecular mechanisms subserving the defects in cellular function. We subsequently conducted multi-omics data analysis using public databases to analyze key target genes, and identified MMP11 as a chief downstream gene responsible for the effects of MEHP on HFF-1 cell migration. Through molecular docking analysis and molecular biology experiments, we further demonstrated that the nuclear receptor PPAR-gamma was activated upon binding with MEHP, leading to the suppression of MMP11 expression. Additionally, we found that epigenetic modifications induced by MEHP were also involved in its pathogenic effects on hypospadias. Our research highlights the crucial role of impaired cellular proliferation and migration in MEHP-induced hypospadias. We identified the MEHP/PPAR-gamma/MMP11 pathway as a novel pathogenic mechanism, providing important potential targets for future preventive strategies with respect to hypospadias.

A Robust Monocular and Binocular Visual Ranging Fusion Method Based on an Adaptive UKF.

Visual ranging technology holds great promise in various fields such as unmanned driving and robot navigation. However, complex dynamic environments pose significant challenges to its accuracy and robustness. Existing monocular visual ranging methods are susceptible to scale uncertainty, while binocular visual ranging is sensitive to changes in lighting and texture. To overcome the limitations of single visual ranging, this paper proposes a fusion method for monocular and binocular visual ranging based on an adaptive Unscented Kalman Filter (AUKF). The proposed method first utilizes a monocular camera to estimate the initial distance based on the pixel size, and then employs the triangulation principle with a binocular camera to obtain accurate depth. Building upon this foundation, a probabilistic fusion framework is constructed to dynamically fuse monocular and binocular ranging using the AUKF. The AUKF employs nonlinear recursive filtering to estimate the optimal distance and its uncertainty, and introduces an adaptive noise-adjustment mechanism to dynamically update the observation noise based on fusion residuals, thus suppressing outlier interference. Additionally, an adaptive fusion strategy based on depth hypothesis propagation is designed to autonomously adjust the noise prior of the AUKF by combining current environmental features and historical measurement information, further enhancing the algorithm's adaptability to complex scenes. To validate the effectiveness of the proposed method, comprehensive evaluations were conducted on large-scale public datasets such as KITTI and complex scene data collected in real-world scenarios. The quantitative results demonstrate that the fusion method significantly improves the overall accuracy and stability of visual ranging, reducing the average relative error within an 8 m range by 43.1% and 40.9% compared to monocular and binocular ranging, respectively. Compared to traditional methods, the proposed method significantly enhances ranging accuracy and exhibits stronger robustness against factors such as lighting changes and dynamic targets. The sensitivity analysis further confirmed the effectiveness of the AUKF framework and adaptive noise strategy. In summary, the proposed fusion method effectively combines the advantages of monocular and binocular vision, significantly expanding the application range of visual ranging technology in intelligent driving, robotics, and other fields while ensuring accuracy, robustness, and real-time performance.

[Mechanism of Puerariae Thomsonii Radix in treatment of mild dyslipidemia: based on clinical metabolomics and proteomics].

This study aims to explore the potential metabolic pathways and targets of Puerariae Thomsonii Radix in the clinical treatment of mild dyslipidemia. UPLC-Q-TOF-MS and EASY-nLC-timsTOF-Pro2 were employed to perform metabolomic and proteomic analyses of the plasma samples collected from the patients with mild dyslipidemia at baseline and after 12 weeks of treatment with Puerariae Thomsonii Radix. The multivariate statistical analysis was carried out for comparison between groups, and the correlation analysis was performed for the metabolites and proteins closely related to mild dyslipidemia with the blood lipid indexes. The possible pathways and targets for mitigating mild dyslipidemia were screened out by the Gene Ontology(GO) and Kyoto Encyclopedia of Genes and Genomes(KEGG) enrichment analysis. The results showed that 56 differential metabolites and 78 differential proteins in the plasma of patients were associated with Puerariae Thomsonii Radix treatment. In addition, changes were detected for the proteins or metabolites(ApoB-100, 9,10-DHOME, GAPDH, PGK1, PGAM1, ENO1, etc.) involved in lipoprotein, lipid, and glucose metabolism and the proteins or metabolites(oxidized phospholipid, PLA2G7, LTA4H, etc.) related to inflammation and oxidative stress. Puerariae Thomsonii Radix may down-regulate the overexpression of ApoB-100, activate the peroxisome proliferator-activated receptor α/γ(PPARα/γ), promote the catabolism of fat and glycerol, and alleviate the oxidative stress mediated by oxidized phospholipids and leukotriene B4(LTB4) in the treatment of mild dyslipidemia.

DeepMPF: deep learning framework for predicting drug-target interactions based on multi-modal representation with meta-path semantic analysis.

BACKGROUND: Drug-target interaction (DTI) prediction has become a crucial prerequisite in drug design and drug discovery. However, the traditional biological experiment is time-consuming and expensive, as there are abundant complex interactions present in the large size of genomic and chemical spaces. For alleviating this phenomenon, plenty of computational methods are conducted to effectively complement biological experiments and narrow the search spaces into a preferred candidate domain. Whereas, most of the previous approaches cannot fully consider association behavior semantic information based on several schemas to represent complex the structure of heterogeneous biological networks. Additionally, the prediction of DTI based on single modalities cannot satisfy the demand for prediction accuracy. METHODS: We propose a multi-modal representation framework of 'DeepMPF' based on meta-path semantic analysis, which effectively utilizes heterogeneous information to predict DTI. Specifically, we first construct protein-drug-disease heterogeneous networks composed of three entities. Then the feature information is obtained under three views, containing sequence modality, heterogeneous structure modality and similarity modality. We proposed six representative schemas of meta-path to preserve the high-order nonlinear structure and catch hidden structural information of the heterogeneous network. Finally, DeepMPF generates highly representative comprehensive feature descriptors and calculates the probability of interaction through joint learning. RESULTS: To evaluate the predictive performance of DeepMPF, comparison experiments are conducted on four gold datasets. Our method can obtain competitive performance in all datasets. We also explore the influence of the different feature embedding dimensions, learning strategies and classification methods. Meaningfully, the drug repositioning experiments on COVID-19 and HIV demonstrate DeepMPF can be applied to solve problems in reality and help drug discovery. The further analysis of molecular docking experiments enhances the credibility of the drug candidates predicted by DeepMPF. CONCLUSIONS: All the results demonstrate the effectively predictive capability of DeepMPF for drug-target interactions. It can be utilized as a useful tool to prescreen the most potential drug candidates for the protein. The web server of the DeepMPF predictor is freely available at http://120.77.11.78/DeepMPF/ , which can help relevant researchers to further study.

OmpR (TCS response regulator) of Aeromonas veronii plays a major role in drug resistance, stress resistance and virulence by regulating biofilm formation.

Aeromonas veronii (A. veronii), a highly pathogenic bacteria with a wide range of hosts, widely exists in the environment of humans, animals and aquatic animals, and can cause a variety of diseases. In this study, the receptor regulator ompR in the envZ/ompR of two-component system was selected to construct a mutant strain (Δ ompR) and a complement strain (C-ompR) to explore the regulatory effect of ompR on the biological characteristics and virulence of TH0426. The results showed that the ability of biofilm formation and osmotic stress of TH0426 were significantly reduced (P < 0.001), the resistance to ceftriaxone and neomycin were slightly down-regulate when the ompR gene was deleted. At the same time, animal pathogenicity experiments showed that the virulence of TH0426 was significantly down-regulated (P < 0.001). These results indicated that ompR gene regulates the biofilm formation of TH0426, and regulates some biological characteristics of TH0426, including drug sensitivity, resistance to osmotic stress, and also affects its virulence.

Panaxadiol targeting IL2 inducible T cell kinase promotes T cell immunity in radiotherapy.

Ginseng, as a traditional Chinese medicine, has a good protective effect against radiotherapy, but its mechanism in radiotherapy still needs to be further explored. The active ingredients of Ginseng were analyzed according to pharmacodynamics in the Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform (TCMSP) database, and the target genes of active ingredients were screened by UniProt, PubChem and Swiss target prediction database. The differentially expressed genes of GSE6871 and GSE20162 were analyzed from the GEO database. Further, cluster analysis and enrichment analysis were carried out through protein-protein interaction network to determine hub gene. Next, build the drug-disease target network, conduct molecular docking simulation, and determine the key ingredients and targets of Ginseng on radiotherapy. We screened 16 active ingredients of Ginseng and 747 target genes from the TCMSP database. Eighty-two common differentially expressed genes were obtained by the GEO database. After topological analysis, we finally determined CD28, FYN, IL2 inducible T cell kinase (ITK), MYC and CD247 as hub genes. After integrating the drug-disease target network and molecular docking, we found that Panaxadiol, as an active ingredient of Ginseng, can target ITK to participate in T cell signal receptor pathway and act on radiotherapy. Panaxadiol can act on the key target ITK of radiotherapy, participate in T cell signal receptor pathway, and then affect the proliferation, differentiation and immune response of radiotherapy T cells, so as to reduce the side effects of radiotherapy.

Leisingera thetidis sp. nov., isolated from coastal water.

A Gram-strain-negative, strictly aerobic, rod-shaped, catalase-positive, oxidase-positive and pinkish beige colony-forming bacterial strain designated as BMJM1T was isolated from a marine sample collected from coastal water near Tongyeong, Republic of Korea. The results of phylogenetic analysis based on 16S rRNA gene sequences indicated that BMJM1T represents a member of the genus Leisingera as it is closely related to Leisingera daeponensis KCTC 12794T (98.27%), Leisingera caerulea DSM 24564T (97.98%), Leisingera aquaemixtae KCTC 32538T (97.91%), Leisingera methylohalidivorans DSM 14336T (97.26%) and Leisingera aquimarina DSM 24565T (97.25%). Optimal growth occurred at 25-30°C, pH 7.0 and with 2% NaCl. Digital DNA-DNA hybridisation (dDDH) and average nucleotide identity (ANI) values between strain BMJM1T and the closely related species of the genus Leisingera were below 40 and 90%, respectively, which are far below the thresholds to delineate a novel species. The predominant fatty acids (>10%) are summed feature 8 (C18:1ω7c and/or C18:1ω6c) (68.4%) and C14:1iso E (11.6%). The major polar lipids were phosphatidylethanolamine and phospholipid. The major isoprenoid quinone was ubiquinone-10. The DNA G+C content was 64.0%. On the basis of the results of the polyphasic taxonomic characterisation, BMJM1T represents a novel species of the genus Leisingera, for which the name is Leisingera thetidis sp. nov. is proposed, with that type strain BMJM1T (= KCTC 92110T = GDMCC 1.2992T).

Emticicia fluvialis sp. nov., a potential hormone-degrading bacterium isolated from Nakdong River, Republic of Korea.

A novel species of the genus Emticicia, designated BHSR1T, was isolated from a water sample that was collected from the Nakdong River, Republic of Korea, and its taxonomic affiliation was studied using a polyphasic approach. This bacterium was Gram-stain-negative, non-motile, aerobic, curved, rod-shaped, and oxidase- and catalase-negative. The bacterium grew optimally at 37 °C, pH 7.5 and 0% (w/v) NaCl. Phylogenetic analyses based on 16S rRNA gene sequences indicated that strain BHSR1T should be affiliated with the genus Emticicia, with a high similarity to Emticicia fontis KCTC 52248T (98.10%). Phylogenomic analysis also suggested that the strain represents a novel species in the genus Emticicia. The genomic G + C content was 41.9%. The average nucleotide identity, average amino acid identity and digital DNA-DNA hybridization between strain BHSR1T and its closely related relatives in the genus Emticicia were in ranges of 71.1-75.8%, 69.4-77.5% and 18.6-19.9%, respectively. The gene cluster within BHSR1T contained genes encoding enzymes that could be involved in hormone degradation. The major cellular fatty acids (> 10%) were summed feature 3 (comprising C16:1ω6c and/or C16:1ω7c) and iso-C15:0. With regards to the polar lipid profile, phosphatidylethanolamine (PE), two unidentified aminolipids and three unidentified lipids were identified as the major compounds. The major respiratory quinone was menaquinone (MK)-7. Based on its phylogenetic, phenotypic, chemotaxonomic, and genomic features, strain BHSR1T should be considered a novel species in the genus Emticicia of the family Spirosomaceae, for which the name Emticicia fluvialis sp. nov. is proposed. The type strain was considered BHSR1T (= KCTC 92622T = GDMCC 1.3740T).

The preparation, characterization, and application of porous core-shell composite particles produced with laboratory-scale spray dryer.

OBJECTIVE: To prepare porous core-shell composite particles (PCPs) in order to improve the flowability and compactibility of powder materials for direct compaction (DC), as well as the dissolution of tablets. SIGNIFICANCE: The results obtained are meaningful to boosting the development and further research of PCPs on DC. Methods: In this study, hydroxypropyl methylcellulose (HPMC E3) and polyvinylpyrrolidone (PVP K30) were selected as shell materials, the Xiao Er Xi Shi formulation powder (XEXS) was used as the core materials, ammonium bicarbonate (NH4HCO3), and sodium bicarbonate (NaHCO3) were employed as pore-forming agent. Using co-spray drying method to prepare composite particles (CPs). Then, the physical properties and comparison between different CPs were characterized comprehensively. Finally, the different CPs were directly compacted as tablets to explore the effect on the dissolution behavior of DC tablets, respectively. RESULTS: (i) The XEXS PCPs were prepared successfully by co-spray drying, and the yield of PCPs is almost 80%; (ii) The TS values of PCP-X-P-Na, PCP-X-P-NH4, PCP-X-H-Na and PCP-X-P-Na were 5.70, 7.56, 3.98, and 6.88 times higher than that of raw material (X); (iii) The disintegration time of PCPs tablets decreased 10-25% when compared with CPs tablets; (iv) The values of Carr's index (CI), Hausner ratio (HR), Caking strength (CS), and Cohesion index (CoI) of PCP-X-H-NH4 were 19.16%, 19.29%, 40.14%, and 6.39% lower than that of X, respectively. CONCLUSIONS: The PCPs prepared by co-spray drying did improve the flowability and compactibility of powder, as well as the dissolution of tablets.

Lung, Liver and Skin Changes in an Infant with Positive Methamphetamine.

BACKGROUND: The increased use of illicit drugs continues to lead to the discovery of various unexpected pathologies. CASE PRESENTATION: This 7-month-old infant died suddenly at home. Pulmonary artery fibrinoid necrosis, diffuse fatty liver changes, and skin rash were the main histologic postmortem findings. Postmortem urine contained traces of methamphetamine. Methamphetamine was smoked by the parents. CONCLUSIONS: Fibrinoid necrosis has been described with inhaling methamphetamine and can result in fibrinoid angiitis such as in this case. Although this did not result in pulmonary hemorrhage or could be directly related to death, it does suggest that pulmonary artery fibrinoid necrosis may develop with passive inhalation of methamphetamines.

[Preparation and in vitro property evaluation of ß-cyclodextrin-daidzein/PEG_(20000)/Carbomer_(940) nanocrystals].

This study aims to improve the solubility and bioavailability of daidzein by preparing the ß-cyclodextrin-daidzein/PEG_(20000)/Carbomer_(940) nanocrystals. Specifically, the nanocrystals were prepared with daidzein as a model drug, PEG_(20000), Carbomer_(940), and NaOH as a plasticizer, a gelling agent, and a crosslinking agent, respectively. A two-step method was employed to prepare the ß-cyclodextrin-daidzein/PEG_(20000)/Carbomer_(940) nanocystals. First, the insoluble drug daidzein was embedded in ß-cyclodextrin to form inclusion complexes, which were then encapsulated in the PEG_(20000)/Carbomer_(940) nanocrystals. The optimal mass fraction of NaOH was determined as 0.8% by the drug release rate, redispersability, SEM morphology, encapsulation rate, and drug loading. The inclusion status of daidzein nanocrystals was determined by Fourier transform infrared spectroscopy(FTIR), thermogravimetric analysis(TGA), and X-ray diffraction(XRD) analysis to verify the feasibility of the preparation. The prepared nanocrystals showed the average Zeta potential of(-30.77±0.15)mV and(-37.47±0.64)mV and the particle sizes of(333.60±3.81)nm and(544.60±7.66)nm before and after daidzein loading, respectively. The irregular distribution of nanocrystals before and after daidzein loading was observed under SEM. The redispersability experiment showed high dispersion efficiency of the nanocrystals. The in vitro dissolution rate of nanocrystals in intestinal fluid was significantly faster than that of daidzein, and followed the first-order drug release kinetic model. XRD, FTIR, and TGA were employed to determine the polycrystalline properties, drug loading, and thermal stability of the nanocrystals before and after drug loading. The nanocrystals loaded with daidzein demonstrated obvious antibacterial effect. The nanocrystals had more significant inhibitory effects on Staphylococcus aureus, Escherichia coli, and Pseudomonas aeruginosa than daidzein because of the improved solubility of daidzein. The prepared nanocrystals can significantly increase the dissolution rate and oral bioavailability of the insoluble drug daidzein.

[Modern research progress in external application of traditional Chinese medicine to acupoints].

Traditional Chinese medicine(TCM) has a long history and abundant experience in external therapy, which marks human wisdom. In the early history of human, people found that fumigation, coating, and sticking of some tree branches and herb stems can help alleviate scabies and remove parasites in productive labor, which indicates the emergence of external therapy. Pathogen usually enters the body through the surface, so external therapy can be used to treat the disease. External therapy is among the major characteristic of surgery of TCM. As one of the external therapies in TCM, external application to acupoints smooths the zang-fu organs through meridians and collaterals, thereby harmonizing yin and yang. This therapy emerged in the early society, formed the Spring and Autumn Period and the Warring States Period, improved in the Song and Ming dynasties, and matured in the Qing dynasty. With the efforts of experts in history, it has had a mature theory. According to modern research, it can avoid the first-pass effect of liver and the gastrointestinal irritation and improve the bioavailability of Chinese medicine. Based on the effect of Chinese medicine and the theory of meridian and collateral, it can stimulate the acupoints, exert regulatory effect on acupoints, and give full play to the efficacy of TCM and the interaction of the two. Thereby, it can regulate qi and blood and balance yin and yang, thus being widely used in the treatment of diseases. In this paper, the use of external application to acupoints, the effect on skin immunity, the regulation of neuro-inflammatory mechanism, the relationship between acupoint application and human circulation network, and the development of its dosage form were summarized through literature review. On this basis, this study is expected to lay a foundation for further research.