bluuebunny/crossref_metadata_2025_split huggingface dataset:
Deep learning–radiomics integrated noninvasive detection of epidermal growth factor receptor mutations in non-small cell lung cancer patients
Authors: Kim Seonhwa , Lim June Hyuck , Kim Chul-Ho , Roh Jin , You Seulgi , Choi Jeong-Seok , Lim Jun Hyeok , Kim Lucia , Chang Jae Won , Park Dongil , Lee Myung-won , Kim Sup , Heo Jaesung 
Published: January 2024

AbstractThis study focused on a novel strategy that combines deep learning and radiomics to predict epidermal growth factor receptor (EGFR) mutations in patients with non-small cell lung cancer (NSCLC) using computed tomography (CT). A total of 1280 patients with NSCLC who underwent contrast-enhanced CT scans and EGFR mutation testing before treatment were selected for the final study. Regions of interest were segmented from the CT images to extract radiomics features and obtain tumor images. These tumor images were input into a convolutional neural network model to extract 512 image features, which were combined with radiographic features and clinical data to predict the EGFR mutation. The generalization performance of the model was evaluated using external institutional data. The internal and external datasets contained 324 and 130 EGFR mutants, respectively. Sex, height, weight, smoking history, and clinical stage were significantly different between the EGFR-mutant patient groups. The EGFR mutations were predicted by combining the radiomics and clinical features, and an external validation dataset yielded an area under the curve (AUC) value of 0.7038. The model utilized 1280 tumor images, radiomics features, and clinical characteristics as input data and exhibited an AUC of approximately 0.81 and 0.78 during the primary cohort and external validation, respectively. These results indicate the feasibility of integrating radiomics analysis with deep learning for predicting EGFR mutations. CT-image-based genetic testing is a simple EGFR mutation prediction method, which can improve the prognosis of NSCLC patients and help establish personalized treatment strategies.
Shikonin alleviates doxorubicin-induced cardiotoxicity via Mst1/Nrf2 pathway in mice
Authors: Tuo Hu , Li Wenjing , Zhao Wei , Zhao Juan , Li Danni , Jin Lin 
Published: January 2024

AbstractDoxorubicin (DOX) is a popular and potent anticancer drug, but its cardiotoxicity limits its clinical application. Shikonin has a wide range of biological functions, including antioxidant and anti-inflammatory effects. The aim of this study was to investigate the effects of shikonin on DOX-induced cardiac injury and to identify the underlying mechanisms. Mice receiving shikonin showed reduced cardiac injury response and enhanced cardiac function after DOX administration. Shikonin significantly attenuated DOX-induced oxidative damage, inflammation accumulation and cardiomyocyte apoptosis. Shikonin protects against DOX-induced cardiac injury by inhibiting Mammalian sterile 20-like kinase 1 (Mst1) and oxidative stress and activating the nuclear factor erythroid 2-related factor 2 (Nrf2) pathway. In conclusion, shikonin alleviates DOX-induced cardiotoxicity by inhibiting Mst1 and activating Nrf2. Shikonin may be used to treat DOX-induced cardiac injury.
Metallo-supramolecular branched polymer protects particles from air-water interface in single-particle cryo-electron microscopy
Authors: Xu Yixin , Qin Yuqi , Wang Lang , Zhang Yingyi , Wang Yufeng , Dang Shangyu 
Published: January 2024

AbstractRecent technological breakthroughs in single-particle cryo-electron microscopy (cryo-EM) enable rapid atomic structure determination of biological macromolecules. A major bottleneck in the current single particle cryo-EM pipeline is the preparation of good quality frozen cryo-EM grids, which is mostly a trial-and-error process. Among many issues, preferred particle orientation and sample damage by air–water interface (AWI) are common practical problems. Here we report a method of applying metallo-supramolecular branched polymer (MSBP) in the cryo-sample preparation for high-resolution single-particle cryo-EM. Our data shows that MSBP keeps a majority of particles away from air–water interface and mitigates preferred orientation as verified by the analyses of apoferritin, hemagglutinin) trimer and various sample proteins. The use of MSBP is a simple method to improve particle distribution for high-resolution structure determination in single-particle cryo-EM.
Generating fine-grained surrogate temporal networks
Authors: Longa A. , Cencetti G. , Lehmann S. , Passerini A. , Lepri B. 
Published: January 2024

AbstractTemporal networks are essential for modeling and understanding time-dependent systems, from social interactions to biological systems. However, real-world data to construct meaningful temporal networks are expensive to collect or unshareable due to privacy concerns. Generating arbitrarily large and anonymized synthetic graphs with the properties of real-world networks, namely surrogate networks, is a potential way to bypass the problem. However, it is not easy to build surrogate temporal networks which do not lack information on the temporal and/or topological properties of the input network and their correlations. Here, we propose a simple and efficient method that decomposes the input network into star-like structures evolving in time, used in turn to generate a surrogate temporal network. The model is compared with state-of-the-art models in terms of similarity of the generated networks with the original ones, showing its effectiveness and its efficiency in terms of execution time. The simplicity of the algorithm makes it interpretable, extendable and scalable.
Gel-like mechanisms of durability and deformability in wet granular systems
Authors: Fujio Honoka , Yokota Hikari , Tani Marie , Kurita Rei 
Published: January 2024

AbstractIt is known empirically that dry granular materials tend to crumble and that wetting them greatly increases their strength. Although the mechanism of the macroscopic material strength is known in homogeneously wetted granular system, the material strength in heterogeneously wetted granular system is not known due to the lack of experimental studies. Here, we focus on sand grains coated with silicone oil, whose wettability is stable with respect to time, and constructed a model system that can control the heterogeneity of interaction by mixing coated sand grains. The results show that the rapid increase in Young’s modulus is due to a rigidity percolation transition, and that the recombination of the network makes the material more resistant to deformation. This system leads to understanding the properties of jamming systems such as glasses, emulsions, and foams, where the effects of attractive interactions and rigidity percolation have been still unclear.
Topological phase transitions of generalized Brillouin zone
Authors: Verma Sonu , Park Moon Jip 
Published: January 2024

AbstractIt has been known that the bulk-boundary correspondence (BBC) of the non-Hermitian skin effect is characterized by the topology of the complex eigenvalue spectra, while the topology of the wave function gives rise to Hermitian BBC with conventional boundary modes. In this work, we go beyond the known description of the non-Hermitian topological phase and find a different type of BBC that appears in generalized boundary conditions. The generalized Brillouin zone (GBZ) possesses non-trivial topological structures in the intermediate boundary condition between open and periodic boundary conditions. Unlike the conventional BBC, the topological phase transition is characterized by the generalized momentum touching of GBZ, which manifests as exceptional points. As a realization of our proposal, we suggest the non-reciprocal Kuramoto oscillator lattice, where phase slips accompany exceptional points as a signature of such topological phase transition. Our work establishes an understanding of non-Hermitian topological matter by complementing the non-Hermitian BBC as a general foundation of the non-Hermitian topological systems.
Indigenous Peoples and local communities report ongoing and widespread climate change impacts on local social-ecological systems
Authors: Reyes-García Victoria , García-del-Amo David , Álvarez-Fernández Santiago , Benyei Petra , Calvet-Mir Laura , Junqueira André B. , Labeyrie Vanesse , LI Xiaoyue , Miñarro Sara , Porcher Vincent , Porcuna-Ferrer Anna , Schlingmann Anna , Schunko Christoph , Soleymani Ramin , Tofighi-Niaki Adrien , Abazeri Mariam , Attoh Emmanuel M. N. A. N. , Ayanlade Ayansina , Ávila Julia Vieira Da Cunha , Babai Daniel , Bulamah Rodrigo C. , Campos-Silva Joao , Carmona Rosario , Caviedes Julián , Chakauya Rumbidzayi , Chambon Mouna , Chen Zhuo , Chengula Fasco , Conde Esther , Cuní-Sanchez Aida , Demichelis Christophe , Dudina Evgeniya , Fernández-Llamazares Álvaro , Galappaththi Eranga K. , Geffner-Fuenmayor Claudia , Gerkey Drew , Glauser Marcos , Hirsch Eric , Huanca Tomás , Ibarra José Tomás , Izquierdo Andrea E. , Junsberg Leneisja , Lanker Marisa , López-Maldonado Yolanda , Mariel Juliette , Mattalia Giulia , Miara Mohamed D. , Torrents-Ticó Miquel , Salimi Maedeh , Samakov Aibek , Seidler Reinmar , Sharakhmatova Victoria , Shrestha Uttam Babu , Sharma Alpy , Singh Priyatma , Ulambayar Tungalag , Wu Rihan , Zakari Ibrahim S. 
Published: January 2024

AbstractThe effects of climate change depend on specific local circumstances, posing a challenge for worldwide research to comprehensively encompass the diverse impacts on various local social-ecological systems. Here we use a place-specific but cross-culturally comparable protocol to document climate change indicators and impacts as locally experienced and analyze their distribution. We collected first-hand data in 48 sites inhabited by Indigenous Peoples and local communities and covering all climate zones and nature-dependent livelihoods. We documented 1,661 site-agreed reports of change corresponding to 369 indicators. Reports of change vary according to climate zone and livelihood activity. We provide compelling evidence that climate change impacts on Indigenous Peoples and local communities are ongoing, tangible, widespread, and affect multiple elements of their social-ecological systems. Beyond potentially informing contextualized adaptation plans, our results show that local reports could help identify economic and non-economic loss and damage related to climate change impacts suffered by Indigenous Peoples and local communities.
Assessment of methane emissions from oil, gas and coal sectors across inventories and atmospheric inversions
Authors: Tibrewal Kushal , Ciais Philippe , Saunois Marielle , Martinez Adrien , Lin Xin , Thanwerdas Joel , Deng Zhu , Chevallier Frederic , Giron Clément , Albergel Clément , Tanaka Katsumasa , Patra Prabir , Tsuruta Aki , Zheng Bo , Belikov Dmitry , Niwa Yosuke , Janardanan Rajesh , Maksyutov Shamil , Segers Arjo , Tzompa-Sosa Zitely A. , Bousquet Philppe , Sciare Jean 
Published: January 2024

AbstractEmissions from fossil fuel exploitation are a leading contributor to global anthropogenic methane emissions, but are highly uncertain. The lack of reliable estimates hinders monitoring of the progress on pledges towards methane reductions. Here we analyze methane emissions from exploitation of coal, oil and gas for major producing nations across a suite of bottom-up inventories and global inversions. Larger disagreement in emissions exists for the oil/gas sector across the inventories compared to coal, arising mostly from disparate data sources for emission factors. Moreover, emissions reported to the United Nations Framework Convention on Climate Change are lower than other bottom-up and inversion estimates, with many countries lacking reporting in the past decades. Finally, comparison with previous global inversions, revealed a strong influence of the prior inventory on the inferred sub-sectoral emissions magnitude. This study highlights the need to improve consensus on the methodological inputs among the bottom-up inventories in order to obtain more consistent inverse modelling results at the sub-sectoral level.
Biogeochemical explanations for the world’s most phosphate-rich lake, an origin-of-life analog
Authors: Haas Sebastian , Sinclair Kimberly Poppy , Catling David C. 
Published: January 2024

AbstractEnvironmental phosphate concentrations are typically much lower (~10−6 M) than needed for prebiotic phosphorylation of nucleosides, critical for the origin of life. Here, we tested hypotheses explaining highly concentrated dissolved phosphate in carbonate-rich “soda” lakes by examining phosphorus and nitrogen cycling in Last Chance Lake and Goodenough Lake, Canada. We find a lack of geochemical phosphorus precipitation, that sedimentary calcium is in dolomite rather than apatite, and that N2-fixation rates, probably suppressed by high salinity, are too low to create significant biological phosphate demand. Thus, nitrogen-limitation of biological production and precipitation of calcium-rich carbonate instead of apatite combine to allow unimpeded evaporative phosphate buildup in Last Chance Lake to the highest known natural levels (37 mM) due to small biological and geochemical phosphorus sinks. Forming on basaltic rock, which was likely common on early Earth, evaporative soda lakes were consequently plausible origin-of-life settings with sufficient phosphate for prebiotic synthesis.
Time-series forecasting through recurrent topology
Authors: Chomiak Taylor , Hu Bin 
Published: January 2024

AbstractTime-series forecasting is a practical goal in many areas of science and engineering. Common approaches for forecasting future events often rely on highly parameterized or black-box models. However, these are associated with a variety of drawbacks including critical model assumptions, uncertainties in their estimated input hyperparameters, and computational cost. All of these can limit model selection and performance. Here, we introduce a learning algorithm that avoids these drawbacks. A variety of data types including chaotic systems, macroeconomic data, wearable sensor recordings, and population dynamics are used to show thatForecasting throughRecurrentTopology (FReT) can generate multi-step-ahead forecasts of unseen data. With no free parameters or even a need for computationally costly hyperparameter optimization procedures in high-dimensional parameter space, the simplicity of FReT offers an attractive alternative to complex models where increased model complexity may limit interpretability/explainability and impose unnecessary system-level computational load and power consumption constraints.
Clinical trainee performance on task‐based AR/VR‐guided surgical simulation is correlated with their 3D image spatial reasoning scores
Authors: Eagleson Roy , Kikinov Denis , Bilbie Liam , de Ribaupierre Sandrine 
Published: January 2024

AbstractThis paper describes a methodology for the assessment of training simulator‐based computer‐assisted intervention skills on an AR/VR‐guided procedure making use of CT axial slice views for a neurosurgical procedure: external ventricular drain (EVD) placement. The task requires that trainees scroll through a stack of axial slices and form a mental representation of the anatomical structures in order to subsequently target the ventricles to insert an EVD. The process of observing the 2D CT image slices in order to build a mental representation of the 3D anatomical structures is the skill being taught, along with the cognitive control of the subsequent targeting, by planned motor actions, of the EVD tip to the ventricular system to drain cerebrospinal fluid (CSF). Convergence is established towards the validity of this assessment methodology by examining two objective measures of spatial reasoning, along with one subjective expert ranking methodology, and comparing these to AR/VR guidance. These measures have two components: the speed and accuracy of the targeting, which are used to derive the performance metric. Results of these correlations are presented for a population of PGY1 residents attending the Canadian Neurosurgical “Rookie Bootcamp” in 2019.
Autism spectrum disorder detection using facial images: A performance comparison of pretrained convolutional neural networks
Authors: Ahmad Israr , Rashid Javed , Faheem Muhammad , Akram Arslan , Khan Nafees Ahmad , Amin Riaz ul 
Published: January 2024

AbstractAutism spectrum disorder (ASD) is a complex psychological syndrome characterized by persistent difficulties in social interaction, restricted behaviours, speech, and nonverbal communication. The impacts of this disorder and the severity of symptoms vary from person to person. In most cases, symptoms of ASD appear at the age of 2 to 5 and continue throughout adolescence and into adulthood. While this disorder cannot be cured completely, studies have shown that early detection of this syndrome can assist in maintaining the behavioural and psychological development of children. Experts are currently studying various machine learning methods, particularly convolutional neural networks, to expedite the screening process. Convolutional neural networks are considered promising frameworks for the diagnosis of ASD. This study employs different pre‐trained convolutional neural networks such as ResNet34, ResNet50, AlexNet, MobileNetV2, VGG16, and VGG19 to diagnose ASD and compared their performance. Transfer learning was applied to every model included in the study to achieve higher results than the initial models. The proposed ResNet50 model achieved the highest accuracy, 92%, compared to other transfer learning models. The proposed method also outperformed the state‐of‐the‐art models in terms of accuracy and computational cost.
A novel efficient wildlife detecting method with lightweight deployment on UAVs based on YOLOv7
Authors: Mou Chao , Zhu Chengcheng , Liu Tengfei , Cui Xiaohui 
Published: January 2024

AbstractEfficient animal detection is essential for biodiversity protection. Unmanned aerial vehicles (UAVs) have been widely used because of their low costs and minimal environmental intrusion. However, using UAVs for practical animal detection poses two challenges: (a) the UAV's fly highly to avoid disturbing animals, resulting in small object detection problems; (b) the limited processing power of UAVs makes large state‐of‐the‐art (SOTA) methods (e.g., You Only Look Once V7, YOLOv7) difficult to deploy. This work proposes the WILD‐YOLO based on YOLOv7 to deal with the two problems. To detect small objects, WILD‐YOLO improves upon YOLOv7 by adding a small object detection head in the head part. To enable real‐time animal detection in field environments with UAVs, the lighten FasterNet and GhostNet have been used to significantly reduce the model size. Compared to YOLOv7, WILD‐YOLO significantly reduces the number of parameters, making it suitable for lightweight deployment on UAVs. Additionally, comparisons with other lightweight models such as YOLOv7‐tiny, YOLOv5‐s, YOLOv4‐s and MobilenetV2 on the datasets are conducted. The experimental results demonstrate that this proposed WILD‐YOLO method outperforms other approaches and has great potential for effective detection of wildlife in complex environments encountered by UAVs.
FAPI PET/CT provides higher uptake and better target to back ground in recurrent and metastatic tumors of patients with Iodine refractory papillary thyroid cancer compared with FDG PET CT
Authors: Nourbakhsh Shaghayegh , Salehi Yalda , Farzanehfar Saeed , Ghaletaki Reza , Bakhshi Kashi Mohsen , Abbasi Mehrshad 
Published: January 2024

Abstract
Purpose The role of fibroblast activation protein inhibitor (FAPI) PET CT scan is not well documented in papillary thyroid cancer (PTC) patients. Patients with radioiodine refractory PTC and high thyroglobulin levels need PET/CT scan which is generally done by 18F FDG. In the current study, the diagnostic performance of 68Ga FAPI and FDG PET/CT scans were compared head to head in patients with radioiodine refractory PTC.
Method Fourteen patients with negative whole body Iodine scans and high thyroglobulin levels underwent whole body PET scans with, respectively, 120–310 and 145–370 MBq 68Ga FAPI-46 and 18F FDG. SUVmax of the back ground in the blood pool and liver and the hottest, largest and average neck, mediastinum, lung and bone lesions were calculated and compared.
Result Ten patients had at least one active (SUVmax>blood pool) lesion similarly in two scans. The liver and blood pool SUVmax values were 1.25(0.2) and 1.7(0.2) in FAPI and 2.65(0.2) and 2.0(0.2) in FDG PET images, respectively. The difference was significant (p=0.001). Standard SUV of the hottest lesion to liver was above 3 in all FAPI scans but in half of FDG scans. Target lesion number and intensity were similar between two PET studies but in a patient out of 5 pulmonary metastatic patients, pulmonary nodules were negative (SUVmax=0.9) in FDG while positive (SUVmax= 3.8) in FAPI images (i.e. 20% patient upstaged).
Conclusion FAPI accumulates in the recurrent and metastatic lesions of patients with Iodine refractory PTC at least as well as FDG with particular privileges as lower injected activity and lower back ground.
Letter to the Editor on: “Running Critical Power: A
Comparison Of Different Theoretical Models”
Authors: Mentzoni F. 
Published: January 2024

Dear Editor,I read with interest the study by Ruiz-Alias et al. on different critical power
models in running 1. The study offers valuable
insights into the application of critical power in running, highlighting
considerable discrepancies between different methods of estimation. While the work
is commendable, it leaves room for questions regarding the methodology applied and
the interpretation of the results. The omission of each participant’s mean
power of the trials in the study, in combination with a reluctance to share it upon
request, makes it impossible for the reader to verify the results. At a bare
minimum, in studies of this nature, each individual’s CP and
W’, calculated using the different methods, should be made
available as it offers valuable information for readers. I elaborate on my main
concerns in the following. Accompanying figures are provided in an external
repository 2.
A safe and effective endoscopic treatment method for simple hepatic cysts (with video)
Authors: Chen Congying , Han Xiao , Xiao Wenqin , Xu Gang , Cai Xiaobo , Hu Guoyong , Wan Rong 
Published: January 2024

Abstract
Background and study aims Symptomatic simple hepatic cysts
require treatment, with several guidelines recommending laparoscopic deroofing. However, cysts
located in the posterosuperior segments are considered poor candidates for this procedure.
Gastrointestinal endoscopes are more flexible and able to reach less accessible areas than
laparoscopes. This study aimed to evaluate the utility of endoscopic transgastric hepatic cyst
deroofing (ETGHCD) for treatment of simple hepatic cysts.
Patients and methods Seven patients with simple hepatic cysts
were evaluated between June 2021 and October 2023. The success rate, procedure time,
post-procedure length of hospital stays, complications, pathologic diagnosis, and efficacy
were recorded.
Results Eleven cysts in seven patients (5 men; mean age 65.5
(standard deviation [SD] 8.5) years) were successfully treated without any complications. The
mean procedure time was 65.6 minutes (SD 17.2). Mean post-procedure hospitalization was 4.4
days (SD 1.0). The pathologic diagnosis of 11 cysts showed simple hepatic cysts. The size of
the cysts was significantly decreased from 337.0 cm3 (SD 528.8) to 5.2
cm3 (SD 6.3) 1 month after ETGHCD. During the median 12.7-month follow-up in
seven patients, the cysts showed a 99.6% reduction with no recurrence.
Conclusions ETGHCD provided a feasible, safe, effective, and
minimal invasive alternative approach for the treatment of simple hepatic cysts.