Phytochemical screening of nonpolar fractions from the methanol extract of the Bamboo shoot skin Phyllostachys heterocycla var. pubescens resulted in the isolation of a new sterol-glucoside-fatty acid derivative (6′-O-octadeca-8”,11”-dienoyl)-sitosterol-3-O-β-d-glucoside (1), together with six known compounds. The chemical structures of the pure isolated compounds were deduced based on different spectral data. The isolated compounds were assessed to determine their cytotoxic activity, and the results were confirmed by determining their apoptotic activity. Compound 1 was more cytotoxic against the MCF-7 cells (IC50 = 25.8 µM) compared to Fluorouracil (5-FU) (26.98 µM), and it significantly stimulated apoptotic breast cancer cell death with 32.6-fold (16.63% compared to 0.51 for the control) at pre-G1 and G2/M-phase cell cycle arrest and blocked the progression of MCF-7 cells. Additionally, RT-PCR results further confirmed the apoptotic activity of compound 1 by the upregulation of proapoptotic genes (P53; Bax; and caspases 3, 8, and 9) and downregulation of the antiapoptotic genes (BCL2). Finally, the identified compounds, especially 1, were found to have high binding affinity towards both tyrosine-specific protein kinase (TPK) and vascular endothelial growth factor receptor (VEGFR-2) through the molecular docking studies that highlight its mode of action.The gut microbiota in sows is important for the health of the host, and potential benefits may also be transferred to piglets during pregnancy. Therefore, systematic studies investigating the changes in the gut microbiota of sows are needed to elucidate the microbial compositions and functions. This study was conducted at 12 time points to investigate the temporal variations in gut microbiota on Days 27, 46, 64, 81, 100, and 113 during gestation (G) and Days 3, 5, 7, 10, 14, and 21 during lactation (L). Results suggested that the gut microbiota changed across the perinatal period with microbial function and abundance varying between the prenatal and postnatal periods. The alpha diversity was higher in the postnatal period than in the prenatal period. Thirty-eight genera were distributed between the two periods with Methanobrevibacter, Desulfovibrio, Akkermansia, and Turicibacter being enriched in the prenatal period while Eubacterium, Actinobacillus, Paludibacter, Butyricimonas, Megasphaera, Succiniclasticum, Acidaminococcus, and Rummeliibacillus were enriched in the postnatal period. Analysis done at the different time points of the prenatal period suggested that Days 27 and 113 had more microbial biomarkers than other days. Bacteroidales, Bacteroidia, and Prevotella were enriched on the 27th day, while bacteria belonging to the Clostridium and Ruminococcaceae were enriched on the 113th day. On the other hand, Clostridiales, Ruminococcaceae, Clostridia, and unclassified Christensenellaceae were enriched three days after delivery. Predicted microbial KO functions were also more enriched on Day 27 of the gestation period and Day 3 of the lactation period. Random forest, a machine learning method, was used to identify the top five important genera of Megasphaera, Stenotrophomonas, Phyllobacterium, Catenibacterium, and Turicibacter, while the most important function was arginine and proline metabolism. These systematic results provide important information for the gut microbiota of sows.Short fibre reinforced polymers are getting more important for structural applications. Becasue of lightweight actions, components are designed for a specific application and lifetime. The bearable numbers of cycles can be estimated using material data and models for the consideration of influence factors. Further static loadings affect material behaviour, which influences the component lifetime. Commonly used models are not able to capture these effects. Therefore, material tests, with different load sequences, on 40% short glass fibre reinforced polypropylene have been performed. These sequences are combinations of cyclic and static loads at different, defined levels. Our research shows a lifetime elongation or reduction of a polymer, depending on the amount of static load time and quantity. For a certain stress level, the time to failure can be elongated or shortened more than a decade by another stress level, as compared to pure cyclic load. Additionally, the stiffness development of the composite is investigated in order to capture the damage course. Accordingly, these effects needed to be considered in lifetime prediction.Some lactic acid bacteria are able to produce exopolysaccharides that, based on localization, can be distinguished in free and capsular or cell-bound exopolysaccharides (CPS). Up to now, the former were the focus of current research, mainly because of the technofunctional benefits they exhibit on fermented dairy products. On the other hand, CPS affect the surface properties of bacteria cells and thus also the textural properties of fermented foods, but data are very scarce. As the cell surface properties are strongly strain dependent, we present a new approach to investigate the impact of CPS on cell surface hydrophobicity and moisture load. CPS positive and negative Streptococcus thermophilus and Weissella cibaria were subjected to ultrasonication suitable to detach CPS without cell damage. The success of the method was verified by scanning electron and light microscopy as well as by cultivation experiments. Before applying ultrasonication cells with CPS exhibiting an increased hydrophilic character, enhanced moisture load, and faster water adsorption compared to the cells after CPS removal, emphasizing the importance of CPS on the textural properties of fermented products. The ultrasonic treatment did not alter the cell surface properties of the CPS negative strains.Measuring bone mineral density (BMD) is important for surveying osteopenia in premature infants. However, the clinical availability of dual-energy X-ray absorptiometry (DEXA) for standard BMD measurement is very limited, and it is not a practical technique for critically premature infants. Developing alternative approaches for DEXA might improve clinical care for bone health. This study aimed to measure the BMD of premature infants via routine chest X-rays in the intensive care unit. A convolutional neural network (CNN) for humeral segmentation and quantification of BMD with calibration phantoms (QRM-DEXA) and soft tissue correction were developed. There were 210 X-rays of premature infants evaluated by this system, with an average Dice similarity coefficient value of 97.81% for humeral segmentation. The estimated humerus BMDs (g/cm3; mean ± standard) were 0.32 ± 0.06, 0.37 ± 0.06, and 0.32 ± 0.09, respectively, for the upper, middle, and bottom parts of the left humerus for the enrolled infants. To our knowledge, this is the first pilot study to apply a CNN model to humerus segmentation and to measure BMD in preterm infants. These preliminary results may accelerate the progress of BMD research in critical medicine and assist with nutritional care in premature infants.Halophilic and halotolerant microorganisms represent promising sources of salt-tolerant enzymes that could be used in various biotechnological processes where high salt concentrations would otherwise inhibit enzymatic transformations. Considering the current need for more efficient biocatalysts, the present study aimed to explore the microbial diversity of five under- or uninvestigated salty lakes in Romania for novel sources of hydrolytic enzymes. Bacteria, archaea and fungi were obtained by culture-based approaches and screened for the production of six hydrolases (protease, lipase, amylase, cellulase, xylanase and pectinase) using agar plate-based assays. Moreover, the phylogeny of bacterial and archaeal isolates was studied through molecular methods. From a total of 244 microbial isolates, 182 (74.6%) were represented by bacteria, 22 (9%) by archaea, and 40 (16.4%) by fungi. While most bacteria synthesized protease and lipase, the most frequent hydrolase produced by fungi was pectinase. The archaeal isolates had limited hydrolytic activity, being able to produce only amylase and cellulase. Among the taxonomically identified isolates, the best hydrolytic activities were observed in halotolerant bacteria belonging to the genus Bacillus and in extremely halophilic archaea of the genera Haloterrigena and Halostagnicola. Therefore, the present study highlights that the investigated lakes harbor various promising species of microorganisms able to produce industrially valuable enzymes.The present study aimed at evaluating the influences of different concentrate feed proportions in the ration offered to dairy cows post partum with different body condition scores (BCS) before calving. Therefore, 60 pluriparous cows were divided 42 days before expected calving into two groups with a higher or an adequate BCS. After calving, both groups were further subdivided into a group fed a ration with either a low concentrate feed proportion (C, 35% at dry matter basis) or a high (60% at dry matter basis) one. It was hypothesized that different BCS would lead to different reactions concerning varying concentrate feed proportions. Isolated BCS effects were detected in the white blood profile only before calving. Neither low nor high concentrate feed proportions affected hematological, blood immune cell phenotypes and inflammatory markers consistently irrespective of BCS group. It was concluded, that the assessed BCS span covered a range in which the capability of cows to cope with different dietary post partum energy supply remained unchanged.Process monitoring at industrial sites contributes to system stability by detecting and diagnosing unexpected changes in a system. Today, as the infrastructure of industrial sites is advancing because of the development of communication technology, vast amounts of data are generated, and the importance of a way to effectively monitor such data in order to diagnose a system is increasing daily. Because a method based on a deep neural network can effectively extract information from a large amount of data, methods have been proposed to monitor processes using such networks to detect system faults and abnormalities. Neural-network-based process monitoring is effective in detecting faults, but has difficulty in diagnosing because of the limitations of the black-box model. Therefore, in this paper we propose a process-monitoring framework that can detect and diagnose faults. The proposed method uses a class activation map that results from diagnosis of faults and abnormalities, and verifies the diagnosis by post-processing the class activation map. This improves the detection of faults and abnormalities and generates a class activation map that provides a more verified diagnosis to the end user. In order to evaluate the performance of the proposed method, we did a simulation using publicly available industrial motor datasets. In addition, after establishing a system that can apply the proposed method to actual manufacturing companies that produce sapphire nozzles, we carried out a case study on whether fault detection and diagnosis were possible.