bluuebunny/crossref_metadata_2025_split huggingface dataset:
Bobcat339, a specific TET family inhibitor, impaired oocyte maturation and early embryogenesis in pig
Authors: Chen Fan , Li Mingguo , Hua Zaidong , Ren Hongyan , Luo Anfeng , Gu Hao , Zhou Changfan , Zhu Zhe , Huang Tao , Bi Yanzhen 
Published: May 2023

Abstract
Background: Ten-eleven translocation (TET) enzyme family, which includes TET1/2/3, participates in active DNA demethylation in the eukaryotic genome; however, TET1/2/3 are functionally redundant. The effect of TET1/2/3 triple-gene knockdown or knockout on the porcine oocytes and embryos is unclear. In this study, using Bobcat339, a specific small-molecule inhibitor of the TET family, we explored the combined effects of TET enzymes on oocyte maturation and early embryogenesis in pigs.
Method: First, porcine cumulus oocyte complexes were cultured in the IVM medium with various concentrations of Bobcat339, and the effects on the expansion of cumulus cells and oocyte maturation were investigated. Further, the apoptotic level of oocytes was assessed using RT-PCR and Annexin-V staining. The spindle architecture and chromosomal alignment were investigated using immunofluorescence staining. Furthermore, the fluorescent signals of 5-methylcytosine (5mC) and 5-hydroxymethylcytosine (5hmC) were quantified. Subsequently, the effect of Bobcat339 on porcine parthenogenetic embryos was assessed. We recorded the blastocyst formation and developmental rates. Furthermore, the mRNA levels of zygotic gene activation (ZGA)- and pluripotency-related and imprinted genes were assessed using RT-PCR. Finally, RNA sequencing analysis was performed in the embryos at the 4-cell stage to identify differentially expressed genes.
Result: Our results revealed that Bobcat339 treatment blocked porcine oocyte maturation and triggered early apoptosis. Furthermore, in the Bobcat339-treated oocytes, spindle architecture and chromosome alignment were disrupted, probably due to huge loss of 5hmC and concurrent increase in 5mC. Furthermore, after Bobcat339 treatment, early parthenogenetic embryos exhibited abnormal 5mC and 5hmC levels, which resulted in compromised cleavage and blastocyst rate. The mRNA levels of EIF1A and DPPA2 (ZGA marker genes) were significantly decreased, which may explain why the embryos were arrested at the 4-cell stage after Bobcat339 treatment. In addition, the mRNA levels of pluripotency-related genes OCT4 and NANOG were declined after Bobcat339 treatment. RNA sequencing analysis revealed differentially expressed genes in Bobcat339-treated embryos at the 4-cell stage, which were significantly enriched in cell proliferation, cell component related to mitochondrion, and cell adhesion molecule binding.
Conclusion: Our results indicated that TET proteins are essential for porcine oocyte maturation and early embryogenesis, and they act by mediating 5mC/5hmC levels and gene transcription.
Synergistic antibacterial action of the iron complex and ampicillin against Staphylococcus aureus
Authors: Kosaristanova Ludmila , Rihacek Martin , Sucha Frantiska , Milosavljevic Vedran , Svec Pavel , Dorazilova Jana , Vojtova Lucy , Antal Peter , Kopel Pavel , Patocka Zdenek , Adam Vojtech , Zurek Ludek , Dolezelikova Kristyna 
Published: May 2023

Abstract
Objectives Resistance to antibiotics among bacteria of clinical importance, including Staphylococcus aureus, is a serious problem worldwide and the search for alternatives is needed. Some metal complexes have antibacterial properties and when combined with antibiotics, they may increase bacterial sensitivity to antimicrobials. In this study, we synthesized the iron complex and tested it in combination with ampicillin (Fe16 + AMP) against S. aureus.Methods An iron complex (Fe16) was synthesized and characterized using spectroscopy methods. Confirmation of the synergistic effect between the iron complex (Fe16) and ampicillin (AMP) was performed using ζ–potential, infrared spectra and FICI index calculated from minimum inhibitory concentration (MIC). Cytotoxic properties of combination Fe16 + AMP was evaluated on eukaryotic cell line. Impact of combination Fe16 + AMP on chosen genes of S. aureus were performed by Quantitative Real-Time PCR.Results The MIC of Fe16 + AMP was significantly lower than that of AMP and Fe16 alone. Furthermore, the infrared spectroscopy revealed the change in the ζ–potential of Fe16 + AMP. We demonstrated the ability of Fe16 + AMP to disrupt the bacterial membrane of S. aureus and that likely allowed for better absorption of AMP. In addition, the change in gene expression of bacterial efflux pumps at the sub-inhibitory concentration of AMP suggests an insufficient import of iron into the bacterial cell. At the same time, Fe16 + AMP did not have any cytotoxic effects on keratinocytes.Conclusions Combined Fe16 + AMP therapy demonstrated significant synergistic and antimicrobial effects against S. aureus. This study supports the potential of combination therapy and further research.
Factor mixture modelling of depression and anxiety: Associations with common mental health disorders, service use, and functional impairment
Authors: Brattmyr Martin , Lindberg Martin Schevik , Lundqvist Jakob , Solem Stian , Hjemdal Odin , Anyan Frederick , Havnen Audun 
Published: May 2023

Abstract
Background: Patient-reported outcome measures (PROM) provide clinicians with information about patients’ perceptions of distress. When linked with treatment and diagnostic registers, new information may be obtained, such as associations with prevalence and service use. This study aimed to examine psychological symptoms among psychiatric outpatients and to investigate treatment-relevant characteristics of symptom-homogeneous classes.
Methods: In a cohort study of 2473 (63% female) outpatients, factor mixture modelling (FMM) was used to analyse self-reported symptoms of anxiety and depression before treatment, and the classes association with functional impairment, the prevalence of common mental health disorders (CMHD) and the number of assessments and psychotherapy appointments one year after treatment start.
Results: Overall, 22% of patients with a CMHD had an additional comorbid mood/anxiety disorder. This comorbid group reported higher symptoms of anxiety and depression compared to patients with non-comorbid anxiety disorders. FMM revealed three classes: “anxiety and somatic depression” (33%), “mixed depression and anxiety” (40%), and “cognitive depression” (27%). The anxiety and somatic depression class was associated with older age, being single and on sick leave, higher probability of depressive-, anxiety-, and comorbid disorders, having more appointments and higher functional impairment. Although the cognitive depression class had less somatic distress than the mixed depression and anxiety class, they reported more functional impairment and had higher service use.
Conclusions: The results demonstrate the clinical relevance of applying FMM to PROM data of depression, anxiety, and functional impairment when linked with treatment registers. Three patient groups emerged, with different symptom patterns. Higher symptom severity did not necessarily imply more functional impairment and service use when subdimensions and latent patient groups were accounted for.
Development of a radiomic-clinical nomogram for prediction of survival in patients with diffuse large B-cell lymphoma treated with chimeric antigen receptor T cells
Authors: zhou yeye , Zhang Bin , Han Jiangqin , Dai Na , Jia Tongtong , Huang Haiwen , Deng Shengming , Sang Shibiao 
Published: May 2023

Abstract
Background In our current work, an 18F-FDG PET/CT radiomics-based model was developed to assess the progression-free survival (PFS) and overall survival (OS) of patients with relapsed or refractory (R/R) diffuse large B-cell lymphoma (DLBCL) who received chimeric antigen receptor (CAR)-T cell therapy.Methods A total of 61 DLBCL cases receiving 18F-FDG PET/CT before CAR-T cell infusion were included in the current analysis, and these patients were randomly assigned to a training cohort (n = 42) and a validation cohort (n = 19). Radiomic features from PET and CT images were obtained using LIFEx software, and radiomics signatures (R-signatures) were then constructed by choosing the optimal parameters according to their PFS and OS. Subsequently, the radiomics model and clinical model were constructed and validated.Results The radiomics model that integrated R-signatures and clinical risk factors showed superior prognostic performance compared with the clinical models in terms of both PFS (C-index: 0.710 vs. 0.716; AUC: 0.776 vs. 0.712) and OS (C-index: 0.780 vs. 0.762; AUC: 0.828 vs. 0.728). For validation, the C-index of the two approaches was 0.640 vs. 0.619 and 0.676 vs. 0.699 for predicting PFS and OS, respectively. Moreover, the AUC was 0.886 vs. 0.635 and 0.778 vs. 0.705, respectively. The calibration curves indicated good agreement, and the decision curve analysis suggested that the net benefit of radiomics models was higher than that of clinical models.Conclusions PET/CT-derived R-signature could be a potential prognostic biomarker for R/R DLBCL patients undergoing CAR-T cell therapy. Moreover, the risk stratification could be further enhanced when the PET/CT-derived R-signature was combined with clinical factors.
Active Control Time: An Objective Performance Metric For Trainee Participation in Robotic Surgery
Authors: Clanahan Julie M. , Yee Andrew , Awad Michael M. 
Published: May 2023

Abstract
Background Trainee participation and progression in robotic general surgery remains poorly defined. Computer-assisted technology offers the potential to provide and track objective performance metrics. In this study, we aimed to validate the use of a novel metric—active control time (ACT)—for assessing trainee participation in robotic-assisted cases.Materials and Methods Performance data from da Vinci Surgical Systems was retrospectively analyzed for all robotic cases involving trainees with a single minimally invasive surgeon over 10 months. The primary outcome metric was percent ACT—the amount of trainee console time spent in active system manipulations over total active time from both consoles. Kruskal-Wallis and Mann-Whitney U statistical tests were applied in analyses.Results A total of 123 robotic cases with 18 general surgery residents and 1 fellow were included. Of these, 56 were categorized as complex. Median %ACT was statistically different between trainee levels for all case types taken in aggregate (PGY1s 3.0% [IQR 2–14%], PGY3s 32% [IQR 27–66%], PGY4s 42% [IQR 26–52%], PGY5s 50% [IQR 28–70%], fellow 61% [IQR 41–85%], p = < 0.0001). When stratified by complexity, median %ACT was higher in standard versus complex cases for PGY5 (60% v 36%, p = 0.0002) and fellow groups (74% v 47%, p = 0.0045).Conclusions In this study, we demonstrated an increase in %ACT with trainee level and with standard versus complex robotic cases. These findings are consistent with hypotheses, providing validity evidence for ACT as an objective measurement of trainee participation in robotic-assisted cases. Future studies will aim to define task-specific ACT to guide further robotic training and performance assessments.
Phosphorus fertilization affects litter quality and enzyme activity in a semiarid grassland
Authors: Gong Jirui , Dong Xuede , Li Xiaobing , Yue Kexin , Shi Jiayu , Song Liangyuan , Zhang Zihe , Zhang Weiyuan , Li Ying 
Published: May 2023

Abstract
Aims Litter decomposition affects soil organic carbon storage, and nutrient addition alters exogenous nutrient availability in soil, thereby affecting the endogenous nutrient concentration and extracellular enzyme activity in litter. However, how above- and belowground litter decomposition responds to nutrient addition is not fully understood.
Methods We conducted a 7-yr field experiment with 5 levels (0, 1, 2.5, 5, and 12.5 g P m-2 yr-1) of phosphorus fertilization (P). Starting in the 6th year, we determine litter decomposition, nutrient elements, and enzyme activity to explore the response mechanisms of above- and belowground litter decomposition to P addition.
Results All levels of P addition increased the rate of aboveground litter decomposition, but only 2.5 g P m−2 yr−1 increased that of belowground litter. P addition increased the litter initial P and Mn contents, while decreased the C/P and N/P ratios of aboveground litter, which stimulated the activities of β-1,4-glucosidase and β-1,4-N-acetylglucosaminidase, thereby increasing the aboveground litter decomposition rate. The belowground litter decomposition was mainly inhibited by lignin content, and 2.5 g P m−2 yr−1 addition significantly decreased lignin content and increased the phenol oxidase activity, thereby accelerating the decomposition. P addition promoted the accumulation of P and the release of cellulose in aboveground litter and promoted the accumulation of calcium and the release of carbon in belowground litter.
Conclusions The different mechanisms of above- and belowground litter decomposition under P addition were driven by litter quality and enzyme activity, facilitating the understanding of the soil and plant interaction mechanisms in grassland ecosystems.
Source Rock Characterisation and Petroleum System Modelling a Review of Marginal Marine Deposit in the Permo-Triassic Sydney Basin, Australia
Authors: Garba Terfa Elijah , Mustapha Khairul Azlan 
Published: May 2023

Abstract

The marginal marine deposits signature is evident in the Permo-Triassic basins, the Sydney Basin is not an exception, and has not been subjected to source rock characterisation and petroleum system modelling designed at determining the potentials of hydrocarbon resources and its prospectivity. The economic potentials of the marginal marine environment are great, with enormous information in the literature that deals with the development of these deposits. The wide use of major, trace, and rare earth elements for basin analysis studies to unravel the geochemical signatures of sedimentary succession using the discriminatory diagrams fall short of addressing discriminate sediments from different geotectonic environments consequently a lag in source rock characterisation and petroleum system model of the marginal marine deposits. This review provides new insight into source rock, sediment supply, and depositional patterns of the marginal marine deposits in the Permo-Triassic Sydney Basin and its implication to the dearth in petroleum prospectivity.
A new deep neural network for forecasting: Deep dendritic artificial neural network
Authors: Egrioglu Erol , Bas Eren 
Published: May 2023

Abstract

Deep artificial neural networks have become a good alternative to classical forecasting methods in solving forecasting problems. Popular deep neural networks classically use additive aggregation functions in their cell structures. It is available in the literature that the use of multiplicative aggregation functions in shallow artificial neural networks produces successful results for the forecasting problem. A type of high-order shallow artificial neural network that uses multiplicative aggregation functions is the dendritic neuron model artificial neural network, which has successful forecasting performance. The first contribution of this work is the transformation of the dendritic neuron model, which works with a single output in the literature, into a multi-output architecture. The second contribution is to propose a new dendritic cell based on the multi-output dendritic neuron model for use in deep artificial neural networks. The other most important contribution of the study is to propose a new deep artificial neural network, a deep dendritic artificial neural network, based on the dendritic cell. The training of the deep dendritic artificial neural network is carried out with the differential evolution algorithm. The forecasting performance of the deep dendritic artificial neural network is compared with basic classical forecasting methods and some recent shallow and deep artificial neural networks over stock market time series. As a result, it has been observed that deep dendritic artificial neural network produces very successful forecasting results for the forecasting problem.
Latent Class Analysis of Mathematics/Science Students Metacognitive Learning Strategies in College of Education in Volta Region, Ghana
Authors: Kumah Maxwell Seyram 
Published: May 2023

Abstract
Metacognitive learning refers to the process of being aware of and taking control of one's own learning. Research has shown that effective use of metacognitive learning strategies can lead to improved student learning outcomes. It helps student to set SMART goal, monitor their own progress, encouraging students to reflect on their own learning and providing feedback that is specific, constructive, and timely can help students to identify areas where they need to improve. The study focused on mathematics/science student’s metacognition utilization in Colleges of Education in Volta region of Ghana. Of 323 population, 139 were purposively and randomly sampled for the study using quantitative exploratory cross – sectional survey design. Twenty – five question items using Metacognitive Learning Utilization Questionnaire (MLUQ) relating to planning, monitoring, evaluation, self-regulation and comprehension was used for data collection. The latent class analysis (LCA) suggests the three-class solution as the accepted best fitting model, based on statistical fit indicators AIC, BIC, entropy, Gsq, and Chsq. The result revealed that comprehension, monitoring and evaluation were very good, and averagely good respectively utilised by majority while self – regulation and planning were satisfactorily and poorly utilised by students. The variables were tested using one way ANOVA with high, moderate and low-level utilization. It was found that there was a statistically significant difference between all three-class based on the mean difference. The study indicate that comprehension was highly utilized while planning was the lowest utilized component of metacognitive learning strategy. Is therefore, recommended student should be supported with metacognitive learning awareness with focus on planning and self-regulation. Other implications of the findings are discussed.
Macromolecular crowding affects protein diffusion in stress fibers as revealed by fluorescence correlation spectroscopy
Authors: Buenaventura Aria , Saito Takumi , Kanao Taiga , Matsunaga Daiki , Matsui Tsubasa S. , Deguchi Shinji 
Published: May 2023

Abstract
The diffusion of cell components such as proteins is crucial to the function of all living cells. The abundance of macromolecules in the cell is likely to cause a state of macromolecular crowding, but its effects on the extent of diffusion remain poorly understood. Here we investigate the diffusion rate in three distinct locations in mesenchymal cell types, namely the cytoplasm, the stress fibers, and those below the nucleus using three kinds of inert green fluorescent proteins (GFPs), namely a monomer, dimer, and trimer GFP. Fluorescence correlation spectroscopy (FCS) was used to determine the diffusion coefficients. We show that diffusion tends to be lowered on average in stress fibers and is significantly lower in those located below the nucleus. Our data suggests that the diffusive properties of GFPs, and potentially other molecules as well, are hindered by macromolecular crowding. However, although the size dependence on protein diffusion was also studied for monomer, dimer, and trimer GFPs, there was no significant difference in the diffusion rates among the GFPs of these sizes. These results could be attributed to the lack of significant change in protein size among the selected GFP multimers. Nevertheless, the data presented here would provide a basis for better understanding of complicated protein diffusion in the nonuniform cytoplasm and in turn of cellular responses to mechanical stress as well as their local mechanical properties.
Enhancing Heliostat Calibration on Low Data by Fusing Robotic Rigid Body Kinematics with Neural Networks
Authors: Pargmann Max , Leibauer Moritz , Nettelroth Vincent , Quinto Daniel Maldonado , Pitz-Paal Robert 
Published: May 2023

Abstract
Solar tower power plants rely on precise calibrations of their heliostats for efficient operation. Open-loop calibration procedures are the most common type due to their cost-effectiveness. Two main approaches to these algorithms exist: geometry-based robotic kinematics and neural network-based models. While the former is reliable and requires little data, it only yields moderate accuracy. The latter, however, promises higher accuracies but is data-hungry and unreliable. In this study, we propose a 2-layer coarse-to-fine hybrid model that combines the strengths of both approaches. Our model uses a rigid-body model for prealignment, then phases in a neural network disturbance model through a regularization sweep. This approach ensures that the prediction accuracy is, in the worst-case, equivalent to that of the rigid-body model. Moreover, it helps to identify deficiencies that may have been overlooked by the physical approach. It especially is capable to compute deviation from the geometry models averaged optimum. For testing, we used real measurement data from daily heliostat calibration at the solar tower in Jülich. We also employed a training/validation data split for evaluation, which allows for a conservative performance assumption over the entire year. Our results demonstrate that the hybrid-model outperforms rigid-body models starting from the first measurement, achieving a top performance below 0.7 milliradians. In conclusion, our proposed hybrid model provides a cost effective in-situ solution for heliostat calibration with highest accuracies on low data in solar tower power plants for all open loop calibration methods.
Le droit suisse des sociétés en 2021 : Modifications législatives et jurisprudence
Authors: Canapa Damiano , Grisoni Arthur , Antonoff Marine 
Published: May 2023

Cette contribution propose un aperçu des principales modifications législatives et de la jurisprudence du Tribunal fédéral [TF] de l'année 2021 en droit suisse des sociétés. La section consacrée aux modifications législatives (chiffre I) revient sur l'entrée en vigueur des modifications du CO et d'autres lois relatives au droit commercial tandis que les résumés de jurisprudence font l'objet de la section suivante (chiffre II) ; les arrêts y sont classés par forme de société et les arrêts publiés au recueil des ATF précèdent les autres arrêts, qui sont classés par ordre chronologique.
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Dieser Beitrag bietet einen Überblick über die wichtigsten Gesetzesänderungen und die Rechtsprechung des Bundesgerichts für das Jahr 2021 im Schweizer Gesellschaftsrecht. Der Abschnitt über die Gesetzesänderungen (Ziffer I) geht auf das Inkrafttreten der Änderungen des OR und anderer handelsrechtlicher Gesetze ein, während die Zusammenfassungen der Rechtsprechung Gegenstand des darauffolgenden Abschnitts (Ziffer II) sind. Die Urteile sind dort nach Gesellschaftsform geordnet und die in der amtlichen Sammlung des Bundesgerichts publizierten Leitentscheide (BGE) gehen den anderen Urteilen, die chronologisch geordnet sind, voraus.