To develop new antimicrobial agents, a series of novel thiourea derivatives incorporated with different moieties 2-13 was designed and synthesized and their biological activities were evaluated. Compounds 7a, 7b and 8 exhibited excellent antimicrobial activity against all Gram-positive and Gram-negative bacteria, and the fungal Aspergillus flavus with minimum inhibitory concentration (MIC) values ranged from 0.95 ± 0.22 to 3.25 ± 1.00 μg/mL. Furthermore, cytotoxicity studies against MCF-7 cells revealed that compounds 7a and 7b were the most potent with IC50 values of 10.17 ± 0.65 and 11.59 ± 0.59 μM, respectively. On the other hand, the tested compounds were less toxic against normal kidney epithelial cell lines (Vero cells). The in vitro enzyme inhibition assay of 8 displayed excellent inhibitory activity against Escherichia coli DNA B gyrase and moderate one against E. coli Topoisomerase IV (IC50 = 0.33 ± 1.25 and 19.72 ± 1.00 µM, respectively) in comparison with novobiocin (IC50 values 0.28 ± 1.45 and 10.65 ± 1.02 µM, respectively). Finally, the molecular docking was done to position compound 8 into the E. coli DNA B and Topoisomerase IV active pockets to explore the probable binding conformation. In summary, compound 8 may serve as a potential dual E. coli DNA B and Topoisomerase IV inhibitor.The potential utilization of black soldier fly (Hermetia illucens) as food or feed is interesting due to the nutritive value and the sustainability of the rearing process. In the present study, larvae and prepupae of H. illucens were reared at 20, 27, and 33 °C, to determine whether temperature affects the whole insect microbiota, described using microbiological risk assessment techniques and 16S rRNA gene survey. The larvae efficiently grew across the tested temperatures. Higher temperatures promoted faster larval development and greater final biomass but also higher mortality. Viable Enterobacteriaceae, Bacillus cereus, Campylobacter, Clostridium perfringens, coagulase-positive staphylococci, Listeriaceae, and Salmonella were detected in prepupae. Campylobacter and Listeriaceae counts got higher with the increasing temperature. Necrostatin 1S clinical trial Based on 16S rRNA gene analysis, the microbiota of larvae was dominated by Providencia (>60%) and other Proteobateria (mainly Klebsiella) and evolved to a more complex composition in prepupae, with a bloom of Actinobacteria, Bacteroidetes, and Bacilli, while Providencia was still present as the main component. Prepupae largely shared the microbiota with the frass where it was reared, except for few lowly represented taxa. The rearing temperature was negatively associated with the amount of Providencia, and positively associated with a variety of other genera, such as Alcaligenes, Pseudogracilibacillus, Bacillus, Proteus, Enterococcus, Pediococcus, Bordetella, Pseudomonas, and Kerstersia. With respect to the microbiological risk assessment, attention should be paid to abundant genera, such as Bacillus, Myroides, Proteus, Providencia, and Morganella, which encompass species described as opportunistic pathogens, bearing drug resistances or causing severe morbidity.The extraction of buildings has been an essential part of the field of LiDAR point clouds processing in recent years. However, it is still challenging to extract buildings from huge amount of point clouds due to the complicated and incomplete structures, occlusions and local similarities between different categories in a complex environment. Taking the urban and campus scene as examples, this paper presents a versatile and hierarchical semantic-based method for building extraction using LiDAR point clouds. The proposed method first performs a series of preprocessing operations, such as removing ground points, establishing super-points and using them as primitives for subsequent processing, and then semantically labels the raw LiDAR data. In the feature engineering process, considering the purpose of this article is to extract buildings, we tend to choose the features extracted from super-points that can describe building for the next classification. There are a portion of inaccurate labeling results due to incomplete or overly complex scenes, a Markov Random Field (MRF) optimization model is constructed for postprocessing and segmentation results refinement. Finally, the buildings are extracted from the labeled points. Experimental verification was performed on three datasets in different scenes, our results were compared with the state-of-the-art methods. These evaluation results demonstrate the feasibility and effectiveness of the proposed method for extracting buildings from LiDAR point clouds in multiple environments.Antiphospholipid syndrome (APS) is the most common cause of acquired thrombophilia and recurrent spontaneous miscarriages associated with extended persistence of antiphospholipid antibodies (aPL). How circulating aPL and high-17β-estradiol (E2) environment contribute to the pregnancy complications in APS is poorly defined. Therefore, we aimed to analyse whether E2 could be responsible for the immune cell hyperactivation in aPL- positive (lupus anticoagulant, anti-cardiolipin, anti-β2-glycoprotein) in women. For this, peripheral blood mononuclear cells (PBMCs) from 14 aPL- positive and 13 aPL- negative women were cultured in the presence or absence of E2, LPS or E2+LPS and cell immunophenotype and cytokine release were analysed. In the aPL+ group, E2 presence markedly increased the percentage of NK cells positive for CD69 (p less then 0.05), monocytes positive for tissue factor (TF, CD142) (p less then 0.05), and B cells expressing PD-L1 (p less then 0.05), as well as the elevated production of IL-1β comparing to aPL- women (p less then 0.01). Regardless of aPL positivity, E2 augmented the procoagulatory response elicited by LPS in monocytes. Our findings show the ability of E2 to promote proinflammatory and procoagulatory phenotype of innate immune cells in individuals with aPL positivity. Our data highlights the significant impact of female hormones on the activation of immune cells in the presence of aPL.The relationship between caffeine and insulin resistance (IR) has been assessed only in terms of caffeine intake, and the association between caffeine and beta cell function (BCF) remains unclear. This study examines the association between urinary caffeine and its metabolites, IR, and BCF in nondiabetic, noninstitutionalized US adults in order to account for the inter-individual differences in caffeine metabolism. Data on urinary caffeine and its metabolites, IR and BCF from adults aged 20 years and older who participated in the 2009-2010 and 2011-2012 National Health and Nutrition Examination Surveys were analyzed (n for caffeine = 994). IR and BCF were assessed using homeostatic model assessment (HOMA) and urinary caffeine and its metabolites were measured using high-performance liquid chromatography-electrospray ionization-tandem quadrupole mass spectrometry. After adjusting for all covariates, increases in urinary 1,3-DMU, 1,7-DMU, 1,3,7-TMU, theophylline, paraxanthine, caffeine, and AAMU were significantly associated with increased HOMA-IR and HOMA-β (HOMA of insulin resistance and beta cell function).