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Because of the recognized health benefits of breast milk, it is recommended as the sole nutrition source during the first 6 months of life. Among the bioactive components are human milk oligosaccharides (HMOs) that exert part of their activity via the gut microbiota. Here, we investigated the gut microbiota fermentation of HMO 2'fucosyllactose (2'-FL), using two in vitro models (48 h fecal incubations and the long-term mucosal simulator of the human intestinal microbial ecosystem [M-SHIME®]) with fecal samples from 3-month-old breastfed (BF) infants as well as 2-3 year old toddlers. The short-term model allowed the screening of five donors for each group and provided supportive data for the M-SHIME® study. A key finding was the strong and immediate increase in the relative abundance of Bifidobacteriaceae following 2'-FL fermentation by both the BF infant and toddler microbiota in the M-SHIME®. At the metabolic level, while decreasing branched-chain fatty acids, 2'-FL strongly increased acetate production together with increases in the health-related propionate and butyrate whilst gas production only mildly increased. Notably, consistently lower gas production was observed with 2'-FL fermentation as compared to lactose, suggesting that reduced discomfort during the dynamic microbiome establishment in early life may be an advantage along with the bifidogenic effect observed.Continuous hemodynamic monitoring is important for long-term cardiovascular healthcare, especially in hypertension. The impedance plethysmography (IPG) based carotid pulse sensing is a non-invasive diagnosis technique for measuring pulse signals and further evaluating the arterial conditions of the patient such as continuous blood pressure (BP) monitoring. To reach the high-resolution IPG-based carotid pulse detection for cardiovascular applications, this study provides an optimized measurement parameter in response to obvious pulsation from the carotid artery. The influence of the frequency of excitation current, electrode cross-sectional area, electrode arrangements, and physiological site of carotid arteries on IPG measurement resolution was thoroughly investigated for optimized parameters. In this study, the IPG system was implemented and installed on the subject's neck above the carotid artery to evaluate the measurement parameters. The measurement results within 6 subjects obtained the arterial impedance variation of 2137 mΩ using the optimized measurement conditions, including excitation frequency of 50 kHz, a smaller area of 2 cm2, electrode spacing of 4 cm and 1.7 cm for excitation and sensing functions, and location on the left side of the neck. The significance of this study demonstrates an optimized measurement methodology of IPG-based carotid pulse sensing that greatly improves the measurement quality in cardiovascular monitoring.Currently, extracellular vesicles (EVs) have been implicated in the etiopathogenesis of many diseases, including lung disorders, with the possibility of diagnostic and therapeutic applications. The analysis of EV in respiratory tract diseases faces many obstacles, including material collection from airways, standardization of isolation techniques, detection methods, the analysis of their content, etc. This review focuses on the role of extracellular vesicles in the pathogenesis of atopic respiratory diseases, especially asthma, with a special focus on their clinical applicability as a diagnostic tool. We also summarize available laboratory techniques that enable the detection of EVs in various biological materials, with particular emphasis on flow cytometry. The opportunities and limitations of detecting EV in bronchoalveolar lavage fluid (BALF) were also described.The recent explosion of large volume of standard dataset of annotated images has offered promising opportunities for deep learning techniques in effective and efficient object detection applications. However, due to a huge difference of quality between these standardized dataset and practical raw data, it is still a critical problem on how to maximize utilization of deep learning techniques in practical agriculture applications. Here, we introduce a domain-specific benchmark dataset, called AgriPest, in tiny wild pest recognition and detection, providing the researchers and communities with a standard large-scale dataset of practically wild pest images and annotations, as well as evaluation procedures. During the past seven years, AgriPest captures 49.7K images of four crops containing 14 species of pests by our designed image collection equipment in the field environment. All of the images are manually annotated by agricultural experts with up to 264.7K bounding boxes of locating pests. [https://www.selleckchem.com/products/gsk-lsd1-2hcl.html https://www.selleckchem.com/products/gsk-lsd1-2hcl.html] This paper also offers a detailed analysis of AgriPest where the validation set is split into four types of scenes that are common in practical pest monitoring applications. We explore and evaluate the performance of state-of-the-art deep learning techniques over AgriPest. We believe that the scale, accuracy, and diversity of AgriPest can offer great opportunities to researchers in computer vision as well as pest monitoring applications.Diagnosis in an advanced state is a major hallmark of ovarian cancer and recurrence after first line treatment is common. With upcoming novel therapies, tumor markers that support patient stratification are urgently needed to prevent ineffective therapy. Therefore, the transcription factor FOXM1 is a promising target in ovarian cancer as it is frequently overexpressed and associated with poor prognosis. In this study, fresh tissue specimens of 10 ovarian cancers were collected to investigate tissue cultures in their ability to predict individual treatment susceptibility and to identify the benefit of FOXM1 inhibition. FOXM1 inhibition was induced by thiostrepton (3 µM). Carboplatin (0.2, 2 and 20 µM) and olaparib (10 µM) were applied and tumor susceptibility was analyzed by tumor cell proliferation and apoptosis in immunofluorescence microscopy. Resistance mechanisms were investigated by determining the gene expression of FOXM1 and its targets BRCA1/2 and RAD51. Ovarian cancer tissue was successfully maintained for up to 14 days ex vivo, preserving morphological characteristics of the native specimen.