bluuebunny/crossref_metadata_2025_split huggingface dataset:
Ketone body β-hydroxybutyrate (BHB) preserves mitochondrial bioenergetics
Authors: Llorente-Folch I. , Düssmann H. , Watters O. , Connolly N. M. C. , Prehn Jochen H. M. 
Published: November 2023

AbstractThe ketogenic diet is an emerging therapeutic approach for refractory epilepsy, as well as certain rare and neurodegenerative disorders. The main ketone body, β-hydroxybutyrate (BHB), is the primary energy substrate endogenously produced in a ketogenic diet, however, mechanisms of its therapeutic actions remain unknown. Here, we studied the effects of BHB on mitochondrial energetics, both in non-stimulated conditions and during glutamate-mediated hyperexcitation. We found that glutamate-induced hyperexcitation stimulated mitochondrial respiration in cultured cortical neurons, and that this response was greater in cultures supplemented with BHB than with glucose. BHB enabled a stronger and more sustained maximal uncoupled respiration, indicating that BHB enables neurons to respond more efficiently to increased energy demands such as induced during hyperexcitation. We found that cytosolic Ca2+ was required for BHB-mediated enhancement of mitochondrial function, and that this enhancement was independent of the mitochondrial glutamate-aspartate carrier, Aralar/AGC1. Our results suggest that BHB exerts its protective effects against hyperexcitation by enhancing mitochondrial function through a Ca2+-dependent, but Aralar/AGC1-independent stimulation of mitochondrial respiration.
Features extraction from multi-spectral remote sensing images based on multi-threshold binarization
Authors: Rusyn Bohdan , Lutsyk Oleksiy , Kosarevych Rostyslav , Maksymyuk Taras , Gazda Juraj 
Published: November 2023

AbstractIn this paper, we propose a solution to resolve the limitation of deep CNN models in real-time applications. The proposed approach uses multi-threshold binarization over the whole multi-spectral remote sensing image to extract the vector of discriminative features for classification. We compare the classification accuracy and the training time of the proposed approach with ResNet and Ensemble CNN models. The proposed approach shows a significant advantage in accuracy for small datasets, while keeping very close recall score to both deep CNN models for larger datasets. On the other hand, regardless of the dataset size, the proposed multi-threshold binarization provides approximately 5 times lower training and inference time than both ResNet and Ensemble CNN models.
Comparison of adaptive optical scanning holography based on new evaluation methods
Authors: Duan Jilu , Zhang Yaping , Yao Yongwei , Fu Qingyang , Zhang Bing , Tsang P. W. M. , Poon Ting-Chung 
Published: November 2023

AbstractAdaptive Optical Scanning Holography (AOSH) represents a powerful technique that employs an adaptive approach to selectively omit certain lines within holograms, guided by the utilization of Normalized-Mean-Error (NME) as a predictive measure. This approach effectively diminishes scanning time and conserves the storage space required for data preservation. However, there exists alternative methods superior to NME in terms of evaluating the model’s efficacy. This paper introduces two novel methods, namely Normalized-Root-Mean-Square-Error (NRMSE) and Normalized-Mean-Square-Error (NMSE), into the AOSH system, leading to the development of NRMSE-AOSH and NMSE-AOSH. These new systems aim to further minimize duration of holographic recording. Through a comparative analysis of hologram lines between the two newly proposed AOSH systems and the original AOSH, we demonstrate that both NRMSE-AOSH and NMSE-AOSH effectively reduce the number of hologram lines while maintaining the hologram’s informational content. Among the three methods, our two new methods exhibit better performance compared with the original method.
Record of 3H and 36Cl from the Fukushima nuclear accident recovered from soil water in the unsaturated zone at Koriyama
Authors: Ohta Tomoko , Fifield L. Keith , Palcsu László , Tims Stephen G. , Pavetich Stefan , Mahara Yasunori 
Published: November 2023

AbstractThe opportunity to measure the concentrations of 3H and 36Cl released by the Fukushima nuclear accident in 2011 directly in rain was lost in the early stage of the accident. We have, however, been able to reconstruct the deposition record of atmospheric 3H and 36Cl following the accident using a bore hole that was drilled in 2014 at Koriyama at a distance of 60 km from the accident. The contributions of 3H and 36Cl from the accident are 1.4 × 1013 and 2.0 × 1012 atoms m−2 respectively at this site. Very high concentrations of both 3H (46 Bq L−1) and 36Cl (3.36 × 1011 atoms L−1) were found in the unsaturated soil at depths between 300 and 350 cm. From these, conservative estimates for the 3H and 36Cl concentrations in the precipitation in the ~ 6 weeks following the accident were 607 Bq L−1 and 4.74 × 1010 atoms L−1, respectively. A second hole drilled in 2016 showed that 3H concentrations in the unsaturated soil and shallow groundwater had returned to close to natural levels, although the 36Cl concentrations were still significantly elevated above natural levels.
Temporal hierarchy of observed goal-directed actions
Authors: Aberbach-Goodman Shahar , Mukamel Roy 
Published: November 2023

AbstractDuring social interactions, we continuously integrate current and previous information over varying timescales to infer other people's action intentions. Motor cognition theories argue for a hierarchical organization of goal-directed actions based on temporal scales. Accordingly, transient motor primitives are represented at lower levels of the hierarchy, a combination of primitives building motor sequences at subordinate levels, and more stable overarching action goals at superordinate levels. A neural topography of hierarchal timescales for information accumulation was previously shown in the visual and auditory domains. However, whether such a temporal hierarchy can also account for observed goal-directed action representations in motor pathways remains to be determined. Thus, the current study examined the neural architecture underlying the processing of observed goal-directed actions using inter-subject correlation (ISC) of fMRI activity. Observers (n = 24) viewed sequential hand movements presented in their intact order or piecewise scrambled at three timescales pertaining to goal-directed action evolution (Primitives: ± 1.5 s, Sub-Goals: ± 4 s, and High-Goals: ± 10 s). The results revealed differential intrinsic temporal capacities for integrating goal-directed action information across brain areas engaged in action observation. Longer timescales (> ± 10 s) were found in the posterior parietal and dorsal premotor compared to the ventral premotor (± 4 s) and anterior parietal (± 1.5 s) cortex. Moreover, our results revealed a hemispheric bias with more extended timescales in the right MT+, primary somatosensory, and early visual cortices compared to their homotopic regions in the left hemisphere. Our findings corroborate a hierarchical neural mapping of observed actions based on temporal scales of goals and provide further support for a ubiquitous time-dependent neural organization of information processing across multiple modalities.
The zebrafish paralog six2b is required for early proximal pronephros morphogenesis
Authors: Belcher Beau , Vestal Justin , Lane Samuel , Kell Margaret , Smith Luke , Camarata Troy 
Published: November 2023

AbstractThe transcription factor Six2 plays a crucial role in maintaining self-renewing nephron progenitor cap mesenchyme (CM) during metanephric kidney development. In mouse and human, expression at single-cell resolution has detected Six2 in cells as they leave the CM pool and differentiate. The role Six2 may play in these cells as they differentiate remains unknown. Here, we took advantage of the zebrafish pronephric kidney which forms directly from intermediate mesoderm to test six2b function during pronephric tubule development and differentiation. Expression of six2b during early zebrafish development was consistent with a role in pronephros formation. Using morpholino knock-down and CRISPR/Cas9 mutagenesis, we show a functional role for six2b in the development of proximal elements of the pronephros. By 48 h post-fertilization, six2b morphants and mutants showed disrupted pronephric tubule morphogenesis. We observed a lower-than-expected frequency of phenotypes in six2b stable genetic mutants suggesting compensation. Supporting this, we detected increased expression of six2a in six2b stable mutant embryos. To further confirm six2b function, F0 crispant embryos were analyzed and displayed similar phenotypes as morphants and stable mutants. Together our data suggests a conserved role for Six2 during nephrogenesis and a role in the morphogenesis of the proximal tubule.
Characteristics of lactate metabolism phenotype in hepatocellular carcinoma
Authors: Zhang Jiacheng , Dong Keshuai , Zhang Xin , Li Chunlei , Yu Jia , Wang Weixing 
Published: November 2023

AbstractHepatocellular carcinoma (HCC) is a highly heterogeneous cancer, and more effective prognostic markers are needed. Lactic acid has been proved to be an important metabolite involved in cancer development, metastasis, and the tumor microenvironment, affecting the prognosis of patients. The role of lactic acid metabolism regulators (LAMRs) in HCC is still unclear. In this study, we analyzed the status of LAMRs, a gene list containing lactate from Molecular Signatures database, in HCC and consensus clustering was performed based on these LAMRs. Cluster B showed higher infiltrations of immune cells, higher TME scores, and a poorer prognosis. We further constructed a risk score based on DEGs using LASSO and COX regression analysis between two clusters, which could effectively predict the prognosis of TCGA-LIHC patients. The GSE14520 cohort confirmed the result. We also examined the correlation of risk scores with clinical characteristics, genetic mutations, drug sensitivity, immune checkpoint inhibitors(ICIs), and immunotherapy. In conclusion, our findings will facilitate a further understanding of the role of partial lactate metabolism related genes in HCC and suggest a new risk score to predict prognosis.
Development of a potency assay for CD34+ cell-based therapy
Authors: Aries Anne , Vignon Christine , Zanetti Céline , Goubaud Aurélien , Cormier Arthur , Diederichs Anne , Lahlil Rachid , Hénon Philippe , Garitaonandia Ibon 
Published: November 2023

AbstractWe have previously shown that intracardiac delivery of autologous CD34+ cells after acute myocardial infarction (AMI) is safe and leads to long term improvement. We are now conducting a multicenter, randomized, controlled Phase I/IIb study in post-AMI to investigate the safety and efficacy of intramyocardial injection of expanded autologous CD34+ cells (ProtheraCytes) (NCT02669810). Here, we conducted a series of in vitro studies characterizing the growth factor secretion, exosome secretion, gene expression, cell surface markers, differentiation potential, and angiogenic potential of ProtheraCytes clinical batches to develop a potency assay. We show that ProtheraCytes secrete vascular endothelial growth factor (VEGF) and its concentration is significantly correlated with the number of CD34+ cells obtained after expansion. ProtheraCytes also secrete exosomes containing proangiogenic miRNAs (126, 130a, 378, 26a), antiapoptotic miRNAs (21 and 146a), antifibrotic miRNAs (133a, 24, 29b, 132), and miRNAs promoting myocardial regeneration (199a and 590). We also show that ProtheraCytes have in vitro angiogenic activity, express surface markers of endothelial progenitor cells, and can differentiate in vitro into endothelial cells. After the in vitro characterization of multiple ProtheraCytes clinical batches, we established that measuring the concentration of VEGF provided the most practical, reliable, and consistent potency assay.
Efficacy of pretreatment with remimazolam on prevention of propofol-induced injection pain in patients undergoing gastroscopy
Authors: Yuan Ruimei , Wen Jing , Xing Qingfei , Chao Lei , Hu Chunhai , Ren Jie , Meng Fanjun 
Published: November 2023

AbstractTo evaluate the efficacy of remimazolam pretreatment in preventing propofol-induced injection pain (PIP) in patients undergoing gastroscopy. One hundred and forty patients (ASA I–II, aged 18–65 years, BMI 18–28 kg/m2) who were to undergo gastroscopy were randomized into either a saline group (group S) or a remimazolam group (group R) (n = 70 for each) on a computer-generated random number basis. The patients in group S received normal saline (0.1 ml/kg) and those in group R were administered remimazolam (0.1 mg/kg) via intravenous infusion for 60 s. 30 s after the injection of normal saline or remimazolam, patients received intravenously propofol (0.5 ml/s) until loss of consciousness. A different anesthesiologist who was unaware of the pretreatment was responsible for maintaining the outcome. The primary endpoint of our study was the incidence of PIP, which was measured using a 4-point scale. Secondary endpoints include the intensity of PIP, vital signs, characteristics of surgery and recovery, and adverse events. The incidence of PIP was significantly lower in group R than in group S (13 vs 51%, p < 0.001), and a lower percentage of patients presented with moderate PIP (3 vs 20%, p < 0.001). Moreover, lower consumption of propofol, shorter recovery time, and greater patient satisfaction were observed in group R than in group S. Pretreatment with remimazolam can effectively reduce the incidence and intensity of PIP in gastroscopy and shorten the recovery time without severe adverse effects.Clinical Trials Registration: Trial Registration: Chinese Clinical Trial Registry (identifier: ChiCTR2200063793). Registry time: 16/09/2022. Registry name: Efficacy of Pre-Treatment with Remimazolam on Prevention of Propofol-Induced Injection Pain in Patients Undergoing Gastroscopy. The date of patient enrollment began from 2022-9-17 to 2022-10-10. The link to the registration: https://www.chictr.org.cn/showproj.html?proj=176004.
Natureness‐preserving tone mapping operator based on improved guided filter and adaptive Gamma curve
Authors: Hu Chaoxuan , Liu Peipei , Qin Weifeng , Wang Shuo 
Published: November 2023

AbstractMapping high dynamic range (HDR) images to low dynamic range (LDR) display devices while performing enhancement processing is a challenging task. To address the issues of chromatic drift, the imbalance between preserving naturalness and enhancing details during the mapping process, this paper proposed a tone mapping operator (TMO) based on an improved guided filter with multi‐layered processing. Firstly, the operator tackled the problem of insufficient extraction of detail layer information in complex scene images by redefining the formula of the guided filter and introducing adaptive regularization parameters. This enhancement enabled more effective extraction of details compared to traditional fixed‐parameter guided filters. Secondly, the algorithm employed a centre‐surround approach to subdivide and processed the detail layers individually, effectively suppressing halos and artefacts. Thirdly, image entropy was utilized to guide the fusion and enhancement processing of the detail layers, preventing excessive or insufficient enhancement. Finally, this paper proposed an adaptive gamma correction algorithm and a chromatic consistency algorithm to improve overall contrast and hue saturation. The results demonstrate convincing performance in terms of subjective visual evaluation and image quality assessment.
Image restoration with group sparse representation and low‐rank group residual learning
Authors: Cai Zhaoyuan , Xie Xianghua , Deng Jingjing , Dou Zengfa , Tong Bo , Ma Xiaoke 
Published: November 2023

AbstractImage restoration, as a fundamental research topic of image processing, is to reconstruct the original image from degraded signal using the prior knowledge of image. Group sparse representation (GSR) is powerful for image restoration; it however often leads to undesirable sparse solutions in practice. In order to improve the quality of image restoration based on GSR, the sparsity residual model expects the representation learned from degraded images to be as close as possible to the true representation. In this article, a group residual learning based on low‐rank self‐representation is proposed to automatically estimate the true group sparse representation. It makes full use of the relation among patches and explores the subgroup structures within the same group, which makes the sparse residual model have better interpretation furthermore, results in high‐quality restored images. Extensive experimental results on two typical image restoration tasks (image denoising and deblocking) demonstrate that the proposed algorithm outperforms many other popular or state‐of‐the‐art image restoration methods.
A real‐time critical‐scenario‐generation framework for defect detection of autonomous driving system
Authors: Xie Yizhou , Zhang Yong , Dai Kunpeng , Yin Chengliang 
Published: November 2023

AbstractTo find the most‐likely‐failure scenarios given a certain operation domain, a critical‐scenario‐based test is supposed as an effective method. However, for the state of the art, critical‐scenario‐generation approaches commonly based on random‐search and take amounts of computing resource, some of them are also inapplicable in real time. Moreover, the approaches sometimes fail to obtain critical results, which are strongly relevant to the choice of initial condition. In order to address the above challenges, the authors proposed a Real‐time Critical‐scenario‐generation framework in this paper. The authors proposed an aggressive‐driving algorithm based on the model predictive control method to lead the agent vehicle. The agent vehicle will be controlled to directly create critical scenarios for a black‐box target under test, and the real‐time critical‐scenario test can be brought into reality. A specially designed cost function is presented that guides scenarios to evolve towards the interested conditions, and a self‐adaptive coefficient iteration is designed that enables the approach to be applied within a wider range of initial conditions. The authors carried out both simulation and Vehicle‐in‐the‐Loop (VIL) test; in the VIL test, the authors’ approach improves 15.45% criticality of scenarios with around 9.7 times of efficiency, or improves 38.67% criticality with still around 1.7 times of efficiency with further iterations.
LSTM‐based deep learning framework for adaptive identifying eco‐driving on intelligent vehicle multivariate time‐series data
Authors: Yan Lixin , Jia Le , Lu Shan , Peng Liqun , He Yi 
Published: November 2023

AbstractIn the context of automated driving, the connected and automated vehicles (CAVs) technology unlock the energy saving potential. This paper develops an LSTM‐based deep learning framework for eco‐driving adaptive identification on Intelligent vehicle multivariate time series data. The framework can be adapted for Driver Assistance Systems (DAS) to reduce fuel consumption. Specifically, considering overtaking on rural road is a critical maneuver for operation and has potential to reduce consumption, a simulated driving experiment with 30 participants was conducted to collect the multivariate time series data of the overtaking operation behaviors in conditional automation driving. Driving behaviors were classified into eco‐driving operation behaviors and high fuel consumption operation behaviors based on fuel consumption calculated by using vehicle specific power (VSP). Significance analysis based on linear regression was adopted to identify operation behaviors, and an eco‐driving behavior identification model was established with the use of long short‐term memory (LSTM) for multivariate classification theory. Meanwhile, the other four classification algorithms were used to establish identification models for comparison. The results indicated that the gear position, lane position, the acceleration pedal depth, the clutch pedal depth, and the brake pedal depth had a significant influence on fuel consumption. The eco‐driving behavior identification model of overtaking demonstrated a high classification power and robustness with a classification accuracy of 89.16%. According to the simulation results, the developed adaptive identification model is with promising performance. The conclusions provide theoretical support for developing an adaptive strategy for connected eco‐driving.
Wireless sensing charging based on multi‐drone cooperation
Authors: Xu Guoxin , Zhao Jiawen , Wang Xuehe 
Published: November 2023

AbstractIn recent years, wireless charging technology is widely used for sensor charging. Though carts equipped with wireless charging tools were able to reach sensor nodes and continuously recharge them, their applications are limited and could not be used in many territories such as rugged mountainous terrain and severely damaged disaster areas. With the significant cost reduction of UAVs due to the mature technology, using UAVs to replace charging carts for wireless sensor networks is a future trend. In this study, the problem of energy replenishment and path planning for large‐scale wireless sensor networks by multiple UAVs is considered. First, sensor nodes are distributed evenly by using an improved k‐means clustering algorithm, modelling the problem of the UAV traversal over a certain range of sensors as a travelling salesman problem. Then, a heuristic algorithm is proposed to solve the path planning of UAVs and the hovering time at each sensor. The simulations show the effect of different charging ratios r on the number of non‐functional nodes and the loss of the UAV. The experimental results show that the proposed algorithm is able to plan a sensible path for the UAV, which leads to a smaller UAV energy loss and a smaller number of non‐functional nodes.
Pediatric Craniofacial Tumor Reconstruction
Authors: Parham Matthew J. , Ding Yang , Wang Daniel S. , Jiang Austin Y. , Buchanan Edward P. 
Published: November 2023

AbstractEffective management of pediatric craniofacial tumors requires coordinated input from medical, oncologic, and surgical specialties. Reconstructive algorithms must consider limitations in pediatric donor tissue and account for future growth and development. Immediate reconstruction is often focused on filling dead space, protecting underlying structures, and ensuring skeletal symmetry. Staged reconstruction occurs after the patient has reached skeletal maturity and is focused on restoring permanent dentition. Reconstructive options vary depending on the location, size, and composition of resected tissue. Virtual surgical planning (VSP) reduces the complexity of pediatric craniofacial reconstruction and ensures more predictable outcomes.