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The used software allows to trace the solar rays of the concentrator, in order to assess the effect of the defects caused by corrosion due to the ambient circumstances. After it, experimental results will help to analyse this effect and to prove simulation ones.Networked systems emerge and subsequently evolve. Although several models describe the process of network evolution, researchers know far less about the initial process of network emergence. Here, we report temporal survey results of a real-world social network starting from its point of inception. We find that individuals' ties undergo an initial cycle of rapid expansion and contraction. This process helps to explain the eventual interactions and working structure in the network (in this case, scientific collaboration). We propose a stylized concept and model of "churn" to describe the process of network emergence and stabilization. Our empirical and simulation results suggest that these network emergence dynamics may be instrumental for explaining network details, as well as behavioral outcomes at later time periods.Ancient statues are usually fragile and have a tendency to deteriorate over time, developing cracks, corrosion, and losing color. Before any intervention on the object of art, a conservator must map degradation and take measurements. Deterioration mapping is an extremely long process, as the conservator or restorer must locate and digitize the damages manually and collect physical measurements from the artwork. Extracting and measuring the deterioration automatically from images is less expensive and aids the digital documentation process, thus reducing the time cost of manual deterioration mapping. In this paper, we propose an effective approach named Missing Color Area Extraction in order to extract and measure missing color areas from high-resolution imagery statues, using a thresholding technique. The conversion from RGB color space to HSV color space is applied, in addition to morphological operations to remove the dust and small objects.Olfactomedin 4 (OLFM4) is expressed in normal prostate epithelial cells and immortalized normal human prostate epithelial cells (RWPE1), but the identity of OLFM4-expressing cells within these populations and OLFM4's physiological functions in these cells have not been elucidated. Using single-cell RNA sequencing analysis, we found here that OLFM4 was expressed in multiple stem/progenitor-like cell populations in both the normal prostate epithelium and RWPE1 cells and was frequently co-expressed with KRT13 and LY6D in RWPE1 cells. Functionally, OLFM4-knockout RWPE1 cells exhibited enhanced proliferation of the stem/progenitor-like cell population, shifts stem/progenitor-like cell division to favor symmetric division and differentiated into higher levels PSA expression cells in organoid assays compared with OLFM4-wild RWPE1 cells. Bulk-cell RNA sequencing analysis pinpointed that cMYC expression were enhanced in the OLFM4-knockout RWPE1 cells compared with OLFM4-wild cells. Molecular and signaling pathway studies revealed an increase in the WNT/APC/MYC signaling pathway gene signature, as well as that of MYC target genes that regulate multiple biological processes, in OLFM4-knockout RWPE1 cells. These findings indicated that OLFM4 is co-expressed with multiple stem/progenitor cell marker genes in prostate epithelial cells and acts as a novel mediator in prostate stem/progenitor cell proliferation and differentiation.A signalling pathway involving PLEKHG5 (guanine exchange factor) for the Ras superfamily member RAB26 to transcription factor NF-κB was discovered in autophagy. PLEKHG5 was reported in glioblastoma multiforme (GBM) and correlates with patient survival. Thus, the generation of a cellular model for understanding PLEKHG5 signalling is the study purpose. We generated a CRISPR/Cas9-mediated knockout of PLEKHG5 in U251-MG glioblastoma cells and analysed resulting changes. Next, we used a mRFP-GFP-LC3+ reporter for visualisation of autophagic defects and rescued the phenotype of PLEKHG5 wildtype via transduction of a constitutively active RAB26QL-plasmid. Effects of overexpressing RAB26 were investigated and correlated with the O6-methylguanine-DNA methyltransferase (MGMT) and cellular survival. PLEKHG5 knockout showed changes in morphology, loss of filopodia and higher population doubling times. Accumulation of autolysosomes was resulted by decreased LAMP-1 in PLEKHG5-deficient cells. Rescue of PLEKHG5-/- restored the downregulation of RhoA activity, showed faster response to tumour necrosis factor and better cellular fitness. MGMT expression was activated after RAB26 overexpression compared to non-transduced cells. Survival of PLEKHG5 knockout was rescued together with sensitivity to temozolomide by RAB26QL. This study provides new insights in the PLEKHG5/RAB26 signalling within U251-MG cells, which suggests potential therapeutic strategies in other glioma cells and further in primary GBM.The pure alpha emitter 148Gd may have a significant radiological impact in terms of internal dose to exposed humans in case of accidental releases from a spallation source using a tungsten target, such as the one to be used in the European Spallation Source (ESS). In this work we aim to present an approach to indirectly estimate the whole-body burden of 148Gd and the associated committed effective dose in exposed humans, by means of high-resolution gamma spectrometry of the gamma-emitting radiogadolinium isotopes 146Gd and 153Gd that are accompanied by 148Gd generated from the operation of the tungsten target. Theoretical minimum detectable whole-body activity (MDA) and associated internal doses from 148Gd are calculated using a combination of existing biokinetic models and recent computer simulation studies on the generated isotope ratios of 146Gd/148Gd and 153Gd/148Gd in the ESS target. Of the two gamma-emitting gadolinium isotopes, 146Gd is initially the most sensitive indicator of the presence of 148Gd ifaluation method, and which impact needs to be further studied in future safety assessments of accidental target releases.Maize/soybean relay intercropping system (MSR) is a popular cultivation method to obtain high yields of both crops with reduced inputs. However, in MSR, the effects of different strip widths on competitive strengths and grain yields of intercrop species are still unclear. Therefore, in a two-year field experiment, soybean was relay-intercropped with maize in three different strip-width arrangements (narrow-strips, 180 cm; medium-strips, 200 cm; and wide-strips, 220 cm), and all intercropping results were compared with sole maize (SM) and sole soybean (SS). Results showed that the optimum strip-width for obtaining high grain yields of maize and soybean was 200 cm (medium-strips), which improved the competitive-ability of soybean by maintaining the competitive-ability of maize in MSR. On average, maize and soybean produced 98% and 77% of SM and SS yield, respectively, in medium-strips. The improved grain yields of intercrop species in medium-strips increased the total grain yield of MSR by 15% and land equivalent ratio by 22%, which enhanced the net-income of medium-strips (by 99%, from 620 US $ ha-1 in wide-strips to 1233 US $ ha-1 in medium-strips). Overall, these findings imply that following the optimum strip-width in MSR, i. e., strip-width of 200 cm, grain yields, and competitive interactions of intercrop species can be improved.Fast and accurate confirmation of metastasis on the frozen tissue section of intraoperative sentinel lymph node biopsy is an essential tool for critical surgical decisions. However, accurate diagnosis by pathologists is difficult within the time limitations. Training a robust and accurate deep learning model is also difficult owing to the limited number of frozen datasets with high quality labels. To overcome these issues, we validated the effectiveness of transfer learning from CAMELYON16 to improve performance of the convolutional neural network (CNN)-based classification model on our frozen dataset (N = 297) from Asan Medical Center (AMC). Among the 297 whole slide images (WSIs), 157 and 40 WSIs were used to train deep learning models with different dataset ratios at 2, 4, 8, 20, 40, and 100%. The remaining, i.e., 100 WSIs, were used to validate model performance in terms of patch- and slide-level classification. An additional 228 WSIs from Seoul National University Bundang Hospital (SNUBH) were used as an external validation. Three initial weights, i.e., scratch-based (random initialization), ImageNet-based, and CAMELYON16-based models were used to validate their effectiveness in external validation. In the patch-level classification results on the AMC dataset, CAMELYON16-based models trained with a small dataset (up to 40%, i.e., 62 WSIs) showed a significantly higher area under the curve (AUC) of 0.929 than those of the scratch- and ImageNet-based models at 0.897 and 0.919, respectively, while CAMELYON16-based and ImageNet-based models trained with 100% of the training dataset showed comparable AUCs at 0.944 and 0.943, respectively. For the external validation, CAMELYON16-based models showed higher AUCs than those of the scratch- and ImageNet-based models. Model performance for slide feasibility of the transfer learning to enhance model performance was validated in the case of frozen section datasets with limited numbers.Inositol-Requiring Enzyme 1 (IRE1) is an essential component of the Unfolded Protein Response. IRE1 spans the endoplasmic reticulum membrane, comprising a sensory lumenal domain, and tandem kinase and endoribonuclease (RNase) cytoplasmic domains. Excess unfolded proteins in the ER lumen induce dimerization and oligomerization of IRE1, triggering kinase trans-autophosphorylation and RNase activation. Known ATP-competitive small-molecule IRE1 kinase inhibitors either allosterically disrupt or stabilize the active dimeric unit, accordingly inhibiting or stimulating RNase activity. Previous allosteric RNase activators display poor selectivity and/or weak cellular activity. In this study, we describe a class of ATP-competitive RNase activators possessing high selectivity and strong cellular activity. This class of activators binds IRE1 in the kinase front pocket, leading to a distinct conformation of the activation loop. Our findings reveal exquisitely precise interdomain regulation within IRE1, advancing the mechanistic understanding of this important enzyme and its investigation as a potential small-molecule therapeutic target.Polygenic risk scores (PRS) for breast cancer have potential to improve risk prediction, but there is limited information on their utility in various clinical situations. Here we show that among 122,978 women in the FinnGen study with 8401 breast cancer cases, the PRS modifies the breast cancer risk of two high-impact frameshift risk variants. Similarly, we show that after the breast cancer diagnosis, individuals with elevated PRS have an elevated risk of developing contralateral breast cancer, and that the PRS can considerably improve risk assessment among their female first-degree relatives. In more detail, women with the c.1592delT variant in PALB2 (242-fold enrichment in Finland, 336 carriers) and an average PRS (10-90th percentile) have a lifetime risk of breast cancer at 55% (95% CI 49-61%), which increases to 84% (71-97%) with a high PRS ( > 90th percentile), and decreases to 49% (30-68%) with a low PRS ( less then 10th percentile). Similarly, for c.1100delC in CHEK2 (3.7-fold enrichment; 1648 carriers), the respective lifetime risks are 29% (27-32%), 59% (52-66%), and 9% (5-14%).
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