bluuebunny/crossref_metadata_2025_split huggingface dataset:
Analysis of the effect of cerium on the formation of non-metallic inclusions in low-carbon steel
Authors: Szucki Michał , Kalisz Dorota , Gerasin Sergii , Mrówka Natalia Maria , Iwanciw Jerzy , Semiryagin Sergey 
Published: May 2023

AbstractThe research focused on the influence of cerium on the chemical composition and morphology of non-metallic inclusions in pre-oxidised steel to which Al, Ca, and Ce was added in different amount and order. Calculations were carried out using our own computer program. The simulation results obtained according to two calculation models helped identify precipitates from the Ce–O–S system. The possibility of CeN formation was also identified. The trace amounts of these inclusions were also found in the results. Consideration of the physicochemical phenomena at the boundary, as well as the interfacial partitioning and the sulfur partition coefficient, influences the favourable chemical composition of the inclusions, limiting it mainly to compounds from the Al2O3, Ce2O3, and CaS systems. It was found that the addition of Ce before Ca causes the elimination of MnS precipitates and Ca-containing inclusions in the steel.
DELMEP: a deep learning algorithm for automated annotation of motor evoked potential latencies
Authors: Milardovich Diego , Souza Victor H. , Zubarev Ivan , Tugin Sergei , Nieminen Jaakko O. , Bigoni Claudia , Hummel Friedhelm C. , Korhonen Juuso T. , Aydogan Dogu B. , Lioumis Pantelis , Taherinejad Nima , Grasser Tibor , Ilmoniemi Risto J. 
Published: May 2023

AbstractThe analysis of motor evoked potentials (MEPs) generated by transcranial magnetic stimulation (TMS) is crucial in research and clinical medical practice. MEPs are characterized by their latency and the treatment of a single patient may require the characterization of thousands of MEPs. Given the difficulty of developing reliable and accurate algorithms, currently the assessment of MEPs is performed with visual inspection and manual annotation by a medical expert; making it a time-consuming, inaccurate, and error-prone process. In this study, we developed DELMEP, a deep learning-based algorithm to automate the estimation of MEP latency. Our algorithm resulted in a mean absolute error of about 0.5 ms and an accuracy that was practically independent of the MEP amplitude. The low computational cost of the DELMEP algorithm allows employing it in on-the-fly characterization of MEPs for brain-state-dependent and closed-loop brain stimulation protocols. Moreover, its learning ability makes it a particularly promising option for artificial-intelligence-based personalized clinical applications.
Feeding recycled food waste improved feed efficiency in laying hens from 24 to 43 weeks of age
Authors: Dao Hiep T. , Sharma Nishchal K. , Swick Robert A. , Moss Amy F. 
Published: May 2023

AbstractThere is renewed interest in utilizing food waste as animal feed due to its potential benefits in reducing feed cost and environmental impact while improving global food security. This study was conducted to examine the efficacy of recycled food waste-based feed for laying hen performance, egg quality, and nutrient digestibility. Hy-Line Brown hens (n = 150) were randomly distributed to three dietary treatments with 50 replicate cages of a single bird per treatment from 24 to 43 weeks of age. The treatments were: a standard/control feed based on wheat, sorghum, and soybean meal; a recycled food waste based-feed; and a 50:50 blend of control and food waste based-feed. Hens offered the food waste-based diets had similar egg weight, hen day egg production, and egg mass, but lower feed intake and higher feed efficiency, compared to those fed the control diets (P < 0.001). Hens fed the food waste diets exhibited lower shell breaking strength and shell thickness at week 34, and higher yolk color score and higher fat digestibility compared to the control treatment at week 43 (P < 0.001). Thus, feeding the recycled food waste based-feed maintained egg production while improving feed efficiency compared to the control feed.
ACCT is a fast and accessible automatic cell counting tool using machine learning for 2D image segmentation
Authors: Kataras Theodore J. , Jang Tyler J. , Koury Jeffrey , Singh Hina , Fok Dominic , Kaul Marcus 
Published: May 2023

AbstractCounting cells is a cornerstone of tracking disease progression in neuroscience. A common approach for this process is having trained researchers individually select and count cells within an image, which is not only difficult to standardize but also very time-consuming. While tools exist to automatically count cells in images, the accuracy and accessibility of such tools can be improved. Thus, we introduce a novel tool ACCT: Automatic Cell Counting with Trainable Weka Segmentation which allows for flexible automatic cell counting via object segmentation after user-driven training. ACCT is demonstrated with a comparative analysis of publicly available images of neurons and an in-house dataset of immunofluorescence-stained microglia cells. For comparison, both datasets were manually counted to demonstrate the applicability of ACCT as an accessible means to automatically quantify cells in a precise manner without the need for computing clusters or advanced data preparation.
A comprehensive signature based on endoplasmic reticulum stress-related genes in predicting prognosis and immunotherapy response in melanoma
Authors: Liu Longqing , Yao Dilang , Chen Zhiwei , Duan Shidong 
Published: May 2023

AbstractMelanoma is considered as one of the most invasion types of skin cancer with high mortality rates. Although combination of immune checkpoint therapy with local surgical excision provide a novel promising therapeutic strategies, the overall prognosis of melanoma patients remains unsatisfactory. Endoplasmic reticulum (ER) stress, a process of protein misfolding and undue accumulation, has been proven to play an indispensable regulatory role in tumor progression and tumor immunity. However, whether the signature based ER genes has predictive value for the prognosis and immunotherapy of melanoma has not been systematically manifested. In this study, the LASSO regression and multivariate Cox regression were applied to construct a novel signature for predicting melanoma prognosis both in the training and testing set. Intriguingly, we found that patients endowed with high- and low-risk scores displayed differences in clinicopathologic classification, immune cell infiltration level, tumor microenvironment, and immune checkpoint treatment response. Subsequently, based on molecular biology experiments, we validated that silencing the expression of RAC1, an ERG composed of the risk signature, could restrain the proliferation and migration, promote apoptosis, as well as increase the expression of PD-1/PD-L1 and CTLA4 in melanoma cells. Taken together, the risk signature was regarded as promising predictors for melanoma prognosis and might provide prospective strategies to ameliorate patients’ response to immunotherapy.
In vitro studies of factors affecting debridement of dental implants by tricalcium phosphate powder abrasive treatment
Authors: Chen I-Cheng , Su Chen-Ying , Tu Jia-Jun , Kao Daniel Wenkai , Fang Hsu-Wei 
Published: May 2023

AbstractPeri-implantitis is a common complication characterized by inflammation in tissues surrounding dental implants due to plaque accumulation, which can lead to implant failure. While air flow abrasive treatment has been found to be effective for debriding implant surfaces, little is known about the factors that affect its cleaning capacity. This study systematically examined the cleaning capacity of air powder abrasive (APA) treatment with β-tricalcium phosphate (β-TCP) powder, using various powder jetting strengths and different particle sizes. Three sizes of β-TCP powder (S, M, and L) were prepared, and different powder settings (low, medium, and high) were tested. The cleaning capacity was determined by quantifying ink removal, which simulated biofilm removal from the implant surfaces at different time points. The results of the systematic comparisons showed that the most efficient cleaning of implant surfaces was achieved using size M particles with medium setting. Additionally, the amount of powder consumed was found to be critical to cleaning efficiency, and the implant surfaces were altered in all tested groups. These systematically analyzed outcomes may provide insights into the development of potential non-surgical strategies for treating peri-implant diseases.
Novel genetically engineered mouse models for clear cell renal cell carcinoma
Authors: van der Mijn Johannes C. , Laursen Kristian B. , Fu Leiping , Khani Francesca , Dow Lukas E. , Nowak Dawid G. , Chen Qiuying , Gross Steven S. , Nanus David M. , Gudas Lorraine J. 
Published: May 2023

AbstractGenetically engineered mouse models (GEMMs) are important immunocompetent models for research into the roles of individual genes in cancer and the development of novel therapies. Here we use inducible CRISPR-Cas9 systems to develop two GEMMs which aim to model the extensive chromosome p3 deletion frequently observed in clear cell renal cell carcinoma (ccRCC). We cloned paired guide RNAs targeting early exons of Bap1, Pbrm1, and Setd2 in a construct containing a Cas9D10A (nickase, hSpCsn1n) driven by tetracycline (tet)-responsive elements (TRE3G) to develop our first GEMM. The founder mouse was crossed with two previously established transgenic lines, one carrying the tet-transactivator (tTA, Tet-Off) and one with a triple-mutant stabilized HIF1A-M3 (TRAnsgenic Cancer of the Kidney, TRACK), both driven by a truncated, proximal tubule-specific γ-glutamyltransferase 1 (ggt or γGT) promoter, to create triple-transgenic animals. Our results indicate that this model (BPS-TA) induces low numbers of somatic mutations in Bap1 and Pbrm1 (but not in Setd2), known tumor suppressor genes in human ccRCC. These mutations, largely restricted to kidneys and testis, induced no detectable tissue transformation in a cohort of 13 month old mice (N = 10). To gain insights into the low frequencies of insertions and deletions (indels) in BPS-TA mice we analyzed wild type (WT, N = 7) and BPS-TA (N = 4) kidneys by RNAseq. This showed activation of both DNA damage and immune response, suggesting activation of tumor suppressive mechanisms in response to genome editing. We then modified our approach by generating a second model in which a ggt-driven, cre-regulated Cas9WT(hSpCsn1) was employed to introduce Bap1, Pbrm1, and Setd2 genome edits in the TRACK line (BPS-Cre). The BPS-TA and BPS-Cre lines are both tightly controlled in a spatiotemporal manner with doxycycline (dox) and tamoxifen (tam), respectively. In addition, whereas the BPS-TA line relies on paired guide RNAs (gRNAs), the BPS-Cre line requires only single gRNAs for gene perturbation. In the BPS-Cre we identified increased Pbrm1 gene-editing frequencies compared to the BPS-TA model. Whereas we did not detect Setd2 edits in the BPS-TA kidneys, we found extensive editing of Setd2 in the BPS-Cre model. Bap1 editing efficiencies were comparable between the two models. Although no gross malignancies were observed in our study, this is the first reported GEMM which models the extensive chromosome 3p deletion frequently observed in kidney cancer patients. Further studies are required (1) to model more extensive 3p deletions, e.g. impacting additional genes, and (2) to increase the cellular resolution, e.g. by employing single-cell RNAseq to ascertain the effects of specific combinatorial gene inactivation.
Uncovering the impact of AM fungi on wheat nutrient uptake, ion homeostasis, oxidative stress, and antioxidant defense under salinity stress
Authors: Huang Shoucheng , Gill Sidra , Ramzan Musarrat , Ahmad Muhammad Zaheer , Danish Subhan , Huang Ping , Al Obaid Sami , Alharbi Sulaiman Ali 
Published: May 2023

AbstractThe growth of wheat (Triticum aestivum) is constrained by soil salinity, although some fungal species have been shown to enhance production in saline environments. The yield of grain crops is affected by salt stress, and this study aimed to investigate how arbuscular mycorrhizal fungus (AMF) mitigates salt stress. An experiment was conducted to assess the impact of AMF on wheat growth and yield in conditions of 200 mM salt stress. Wheat seeds were coated with AMF at a rate of 0.1 g (108spores) during sowing. The results of the experiment demonstrated that AMF inoculation led to a significant improvement in the growth attributes of wheat, including root and shoot length, fresh and dry weight of root and shoot. Furthermore, a significant increase in chlorophyll a, b, total, and carotenoids was observed in the S2 AMF treatment, validating the effectiveness of AMF in enhancing wheat growth under salt stress conditions. Additionally, AMF application reduced the negative effects of salinity stress by increasing the uptake of micronutrients such as Zn, Fe, Cu, and Mn while regulating the uptake of Na (decrease) and K (increase) under salinity stress. In conclusion, this study confirms that AMF is a successful strategy for reducing the negative effects of salt stress on wheat growth and yield. However, further investigations are recommended at the field level under different cereal crops to establish AMF as a more effective amendment for the alleviation of salinity stress in wheat.
Inferring origin-destination distribution of agent transfer in a complex network using deep gated recurrent units
Authors: Saw Vee-Liem , Vismara Luca , Suryadi  , Yang Bo , Johansson Mikael , Chew Lock Yue 
Published: May 2023

AbstractPredicting the origin-destination (OD) probability distribution of agent transfer is an important problem for managing complex systems. However, prediction accuracy of associated statistical estimators suffer from underdetermination. While specific techniques have been proposed to overcome this deficiency, there still lacks a general approach. Here, we propose a deep neural network framework with gated recurrent units (DNNGRU) to address this gap. Our DNNGRU is network-free, as it is trained by supervised learning with time-series data on the volume of agents passing through edges. We use it to investigate how network topologies affect OD prediction accuracy, where performance enhancement is observed to depend on the degree of overlap between paths taken by different ODs. By comparing against methods that give exact results, we demonstrate the near-optimal performance of our DNNGRU, which we found to consistently outperform existing methods and alternative neural network architectures, under diverse data generation scenarios.
Performance analyses of highly efficient inverted all-perovskite bilayer solar cell
Authors: Gholami-Milani Alireza , Ahmadi-Kandjani Sohrab , Olyaeefar Babak , Kermani Mir Hojjat 
Published: May 2023

AbstractNumerical simulation of an all-perovskite bilayer solar cell has been conducted by the SCAPS-1D. The presented structure employs MAPbI3 as a relatively wide bandgap (1.55 eV) top absorber and FA0.5MA0.5Pb0.5Sn0.5I3 as a narrow bandgap (1.25 eV) bottom absorber. The viability of the proposed design is accomplished in two steps. First, to validate this study, two inverted solar cells in standalone conditions are simulated and calibrated to fit previously reported state-of-the-art results. Second, both these devices are appraised for the bilayer configuration to boost their performances. Affecting parameters such as the thickness of perovskite absorbers, the work function of front and rear contacts, and the effect of temperature have been studied because solar cells are temperature-sensitive devices, and also carrier concentration and their mobility get overwhelmingly influenced as temperature increases. It is manifested that using bilayer structures could easily widen the absorption spectrum to the near-infrared region and significantly enhance the performance of the device which is mainly affected by the thickness of the FA0.5MA0.5Pb0.5Sn0.5I3 layer. Also, it has been found that the work function of the front contact has a prominent role with its optimal values being above 5 eV. Finally, the optimized inverted all-perovskite bilayer solar cell delivers a power conversion efficiency of 24.83%, fill factor of 79.4%, open circuit voltage of 0.9 V, and short circuit current density of 34.76 mA/cm2 at 275 K and a thickness of 100 nm and 600 nm for MAPbI3 and FA0.5MA0.5Pb0.5Sn0.5I3, respectively.
Evaluation of the anterior acetabular coverage with a false profile radiograph considering appropriate range of positioning
Authors: Kokubu Yasuhiko , Kawahara Shinya , Kitamura Kenji , Hamai Satoshi , Motomura Goro , Ikemura Satoshi , Sato Taishi , Yamaguchi Ryosuke , Hara Daisuke , Fujii Masanori , Nakashima Yasuharu 
Published: May 2023

AbstractThis study aimed to (1) set a reference value for anterior center edge angle (ACEA) for preoperative planning of periacetabular osteotomy (PAO), (2) investigate the effects of pelvic rotation and inclination from false profile (FP) radiographs on the measured ACEA, and (3) determine the “appropriate range of positioning” for FP radiograph. This single-centered, retrospective study analyzed 61 patients (61 hips) who underwent PAO from April 2018 and May 2021. ACEA was measured in each digitally reconstructed radiography (DRR) image of the FP radiograph reconstructed in different degrees of pelvic rotation. Detailed simulations were performed to determine the “appropriate range of positioning” (0.67 < ratio of the distance between the femoral heads to the diameter of the femoral head < 1.0). The vertical-center-anterior (VCA) angle was measured on the CT sagittal plane considering the patient-specific standing positions, and its correlation with the ACEA was investigated. The reference value of ACEA was determined by receiver operating characteristic (ROC) curve analysis. The ACEA measurement increased by 0.35° for every 1° pelvic rotation approaching the true lateral view. The pelvic rotation with the “appropriate range of positioning” was found at 5.0° (63.3–68.3°). The ACEA on the FP radiographs showed a good correlation with the VCA angle. The ROC curve revealed that an ACEA < 13.6° was associated with inadequate anterior coverage (VCA < 32°). Our findings suggest that during preoperative PAO planning, an ACEA < 13.6° on FP radiographs indicates insufficient anterior acetabular coverage. Images with the “appropriate positioning” can also have a measurement error of 1.7° due to the pelvic rotation.
Suppression of the human malic enzyme 2 modifies energy metabolism and inhibits cellular respiration
Authors: Hsieh Ju-Yi , Chen Kun-Chi , Wang Chun-Hsiung , Liu Guang-Yaw , Ye Jie-An , Chou Yu-Tung , Lin Yi-Chun , Lyu Cheng-Jhe , Chang Rui-Ying , Liu Yi-Liang , Li Yen-Hsien , Lee Mau-Rong , Ho Meng-Chiao , Hung Hui-Chih 
Published: May 2023

AbstractHuman mitochondrial NAD(P)+-dependent malic enzyme (ME2) is well-known for its role in cell metabolism, which may be involved in cancer or epilepsy. We present potent ME2 inhibitors based on cyro-EM structures that target ME2 enzyme activity. Two structures of ME2-inhibitor complexes demonstrate that 5,5’-Methylenedisalicylic acid (MDSA) and embonic acid (EA) bind allosterically to ME2’s fumarate-binding site. Mutagenesis studies demonstrate that Asn35 and the Gln64-Tyr562 network are required for both inhibitors’ binding. ME2 overexpression increases pyruvate and NADH production while decreasing the cell’s NAD+/NADH ratio; however, ME2 knockdown has the opposite effect. MDSA and EA inhibit pyruvate synthesis and thus increase the NAD+/NADH ratio, implying that these two inhibitors interfere with metabolic changes by inhibiting cellular ME2 activity. ME2 silence or inhibiting ME2 activity with MDSA or EA decreases cellular respiration and ATP synthesis. Our findings suggest that ME2 is crucial for mitochondrial pyruvate and energy metabolism, as well as cellular respiration, and that ME2 inhibitors could be useful in the treatment of cancer or other diseases that involve these processes.
Ultra-high field fMRI identifies an action-observation network in the common marmoset
Authors: Zanini Alessandro , Dureux Audrey , Selvanayagam Janahan , Everling Stefan 
Published: May 2023

AbstractThe observation of others’ actions activates a network of temporal, parietal and premotor/prefrontal areas in macaque monkeys and humans. This action-observation network (AON) has been shown to play important roles in social action monitoring, learning by imitation, and social cognition in both species. It is unclear whether a similar network exists in New-World primates, which separated from Old-Word primates ~35 million years ago. Here we used ultra-high field fMRI at 9.4 T in awake common marmosets (Callithrix jacchus) while they watched videos depicting goal-directed (grasping food) or non-goal-directed actions. The observation of goal-directed actions activates a temporo-parieto-frontal network, including areas 6 and 45 in premotor/prefrontal cortices, areas PGa-IPa, FST and TE in occipito-temporal region and areas V6A, MIP, LIP and PG in the occipito-parietal cortex. These results show overlap with the humans and macaques’ AON, demonstrating the existence of an evolutionarily conserved network that likely predates the separation of Old and New-World primates.
Impact of noise on spinodal dewetting of liquid-liquid films
Authors: Shiri Roghayeh , Schmeller Leonie , Peschka Dirk , Seemann Ralf , Wagner Barbara 
Published: May 2023

AbstractSpinodal dewetting provides fundamental insights into the physics at interfaces, such as van der Waals forces driving dewetting, dissipation processes or thermal fluctuations. The dewetting process of liquid bilayer systems still raises open problems involving two coupled moving interfaces. Comparison of experimental results of spinodally dewetting liquid polystyrene films from liquid polymethylmethacrylate substrates, with predictions from linear stability analysis, we demonstrate that both the spinodal wavelength and the rupture times show significant differences. Key for this discrepancy is the altered mode selection process due to the initial surface roughness of the liquid-air and liquid-liquid interfaces, which is perturbed by partially correlated colored noise in the linearly unstable region. The strong effect of noise on mode selection and rupture time is confirmed by comparing experimental results with numerical solutions of the full dynamic nonlinear model and suggest new strategies to include thermal fluctuations into modeling these processes.
Thermodynamic and dynamical predictions for bifurcations and non-equilibrium phase transitions
Authors: Yan Han , Zhang Feng , Wang Jin 
Published: May 2023

Abstract“Critical transitions”, in which systems switch abruptly from one state to another are ubiquitous in physical and biological systems. Such critical transitions in complex systems are commonly described as dynamical processes within the framework of nonlinear dynamics and the bifurcation theory. However, systematic treatment from the global thermodynamic perspective is still challenging. Furthermore, from the previous established dynamical framework, a universal early-warning signal for predicting such transitions is still not very clear and complete. Here we developed a non-equilibrium thermodynamic and dynamical framework for general complex systems. Our approach used the analogy to the conventional statistical mechanical treatment for the equilibrium phase transitions, while the nature of the non-equilibrium dynamics is still captured and reflected. Applying this framework to two well-known non-equilibrium systems, we found warning signals based on thermodynamic quantities and the time-reversal symmetry breaking nature of non-equilibrium systems can be detected much earlier than those explored in the previous works based on nonlinear dynamics and the bifurcation theory. Irreversibility of the observed time series strongly correlates to the behavior of these thermodynamic quantities and provides a practical way for predicting transitions. Our work provides a general yet practical approach for exploring collective behaviors in complex systems.