bluuebunny/crossref_metadata_2025_split huggingface dataset:
Impact of an online reference system on the diagnosis of rare or atypical abdominal tumors and lesions
Authors: Woeltjen Matthias Michael , Niehoff Julius Henning , Saeed Saher , Mendorf Alexander , Roggel Ruth , Michael Arwed Elias , Surov Alexey , Moenninghoff Christoph , Borggrefe Jan , Kroeger Jan Robert 
Published: July 2024

AbstractThe purpose of the present study is to evaluate whether an online reference system (ORS, STATdx Elsevier, Amsterdam, Netherlands) impacts finding the histologically confirmed diagnosis of rare or atypical abdominal tumors and lesions in radiologic imaging. In total, 101 patients with rare tumor entities or lesions and atypical manifestations of common tumors were enrolled retrospectively. Blinded readings were performed by four radiologists with varying levels of experience, who reported on: (a) correct diagnosis (CD), (b) time needed to find the diagnosis, and (c) diagnostic confidence, initially without followed by the assistance of the ORS. The experienced reader (3 years of experience post-residency, CD 49.5%), as well as the advanced reader with 1 year of experience post-residency (CD 43.6%), and a resident with 5 years of experience (CD 46.5%) made the correct diagnosis more frequently compared to the less experienced reader (CD 25.7%). A significant improvement in making the correct diagnosis was only achieved by the advanced reader, the resident with 5 years of experience (CD with ORS 58.4%; p < 0.001). The advanced reader with 1 year of experience post-residency improved slightly (CD ORS 47.5%). The experienced reader (CD ORS 50.5%) and the less experienced reader (CD ORS 27.7%) did not improve significantly. The overall subjective confidence increased significantly when ORS was used (3.2 ± 0.9 vs. 3.8 ± 0.9; p < 0.001). While the ORS had a positive impact on making the correct diagnosis throughout all readers, it favored radiologists with more clinical experience rather than inexperienced residents. Moreover, the ORS increased the diagnostic confidence of all radiologists significantly. In conclusion, the ORS had no significant impact on the diagnosis of rare or atypical abdominal tumors and lesions except for one reader. The greatest benefit is the increase in diagnostic confidence.
Body part categorical matching in chimpanzees (Pan troglodytes)
Authors: Gao Jie , Adachi Ikuma 
Published: July 2024

AbstractHumans categorize body parts, reflecting our knowledge about bodies, and this could be useful in higher-level activities involving bodies. We tested whether humans’ closest living relatives—chimpanzees—have the same ability using touchscreen tasks, focusing on the major parts: heads, torsos, arms, and legs. Six chimpanzees were trained to perform a body part matching-to-sample task using sets of pictures of chimpanzee bodies, where in each trial, the sample and choice pictures were the same. Five passed the training and received the test sessions, where three trial types were mixed: trained same-individual picture pairs; novel same-individual picture pairs; and novel different-individual picture pairs. All participants performed better than the chance level in all conditions and for all body parts. Further analyses showed differences in performance when the samples were different body parts. For example, the results revealed better performances for heads and torsos than arms and legs in “novel different-individual pairs”. The study showed that chimpanzees can visually match and categorize body parts in this experiment setting, even across different chimpanzees’ bodies, suggesting potential biological understanding. Different performances for body parts suggested a deviated categorization from humans. We hope this study will inspire future research on the evolution of body perception.
Unbiased analysis of spatial learning strategies in a modified Barnes maze using convolutional neural networks
Authors: Illouz Tomer , Ascher Lyn Alice Becker , Madar Ravit , Okun Eitan 
Published: July 2024

AbstractAssessment of spatial learning abilities is central to behavioral neuroscience and a useful tool for animal model validation and drug development. However, biases introduced by the apparatus, environment, or experimentalist represent a critical challenge to the test validity. We have recently developed the Modified Barnes Maze (MBM) task, a spatial learning paradigm that overcomes inherent behavioral biases of animals in the classical Barnes maze. The specific combination of spatial strategies employed by mice is often considered representative of the level of cognitive resources used. Herein, we have developed a convolutional neural network-based classifier of exploration strategies in the MBM that can effectively provide researchers with enhanced insights into cognitive traits in mice. Following validation, we compared the learning performance of female and male C57BL/6J mice, as well as that of Ts65Dn mice, a model of Down syndrome, and 5xFAD mice, a model of Alzheimer’s disease. Male mice exhibited more effective navigation abilities than female mice, reflected in higher utilization of effective spatial search strategies. Compared to wildtype controls, Ts65Dn mice exhibited delayed usage of spatial strategies despite similar success rates in completing this spatial task. 5xFAD mice showed increased usage of non-spatial strategies such as Circling that corresponded to higher latency to reach the target and lower success rate. These data exemplify the need for deeper strategy classification tools in dissecting complex cognitive traits. In sum, we provide a machine-learning-based strategy classifier that extends our understanding of mice’s spatial learning capabilities while enabling a more accurate cognitive assessment.
Immunoinformatics and structural aided approach to develop multi-epitope based subunit vaccine against Mycobacterium tuberculosis
Authors: Sethi Guneswar , Varghese Rinku Polachirakkal , Lakra Avinash Kant , Nayak Subhashree Subhasmita , Krishna Ramadas , Hwang Jeong Ho 
Published: July 2024

AbstractTuberculosis is a highly contagious disease caused by Mycobacterium tuberculosis (Mtb), which is one of the prominent reasons for the death of millions worldwide. The bacterium has a substantially higher mortality rate than other bacterial diseases, and the rapid rise of drug-resistant strains only makes the situation more concerning. Currently, the only licensed vaccine BCG (Bacillus Calmette–Guérin) is ineffective in preventing adult pulmonary tuberculosis prophylaxis and latent tuberculosis re-activation. Therefore, there is a pressing need to find novel and safe vaccines that provide robust immune defense and have various applications. Vaccines that combine epitopes from multiple candidate proteins have been shown to boost immunity against Mtb infection. This study applies an immunoinformatic strategy to generate an adequate multi-epitope immunization against Mtb employing five antigenic proteins. Potential B-cell, cytotoxic T lymphocyte, and helper T lymphocyte epitopes were speculated from the intended proteins and coupled with 50 s ribosomal L7/L12 adjuvant, and the vaccine was constructed. The vaccine’s physicochemical profile demonstrates antigenic, soluble, and non-allergic. In the meantime, docking, molecular dynamics simulations, and essential dynamics analysis revealed that the multi-epitope vaccine structure interacted strongly with Toll-like receptors (TLR2 and TLR3). MM-PBSA analysis was performed to ascertain the system’s intermolecular binding free energies accurately. The immune simulation was applied to the vaccine to forecast its immunogenic profile. Finally, in silico cloning was used to validate the vaccine’s efficacy. The immunoinformatics analysis suggests the multi-epitope vaccine could induce specific immune responses, making it a potential candidate against Mtb. However, validation through the in-vivo study of the developed vaccine is essential to assess its efficacy and immunogenicity profile, which will assure active protection against Mtb.
Sparse transformer with local and seasonal adaptation for multivariate time series forecasting
Authors: Zhang Yifan , Wu Rui , Dascalu Sergiu M. , Harris Frederick C. 
Published: July 2024

AbstractTransformers have achieved remarkable performance in multivariate time series(MTS) forecasting due to their capability to capture long-term dependencies. However, the canonical attention mechanism has two key limitations: (1) its quadratic time complexity limits the sequence length, and (2) it generates future values from the entire historical sequence. To address this, we propose a Dozer Attention mechanism consisting of three sparse components: (1) Local, each query exclusively attends to keys within a localized window of neighboring time steps. (2) Stride, enables each query to attend to keys at predefined intervals. (3) Vary, allows queries to selectively attend to keys from a subset of the historical sequence. Notably, the size of this subset dynamically expands as forecasting horizons extend. Those three components are designed to capture essential attributes of MTS data, including locality, seasonality, and global temporal dependencies. Additionally, we present the Dozerformer Framework, incorporating the Dozer Attention mechanism for the MTS forecasting task. We evaluated the proposed Dozerformer framework with recent state-of-the-art methods on nine benchmark datasets and confirmed its superior performance. The experimental results indicate that excluding a subset of historical time steps from the time series forecasting process does not compromise accuracy while significantly improving efficiency. Code is available at https://github.com/GRYGY1215/Dozerformer.
Effects of copper, and aluminium in ionic, and nanoparticulate form on growth rate and gene expression of Setaria italica seedlings
Authors: Kulasza Mateusz , Sielska Anna , Szenejko Magdalena , Soroka Marianna , Skuza Lidia 
Published: July 2024

AbstractThis study aims to determine the effects of copper, copper oxide nanoparticles, aluminium, and aluminium oxide nanoparticles on the growth rate and expression of ACT-1, CDPK, LIP, NFC, P5CR, P5CS, GR, and SiZIP1 genes in five days old seedling of Setaria italica ssp. maxima, cultivated in hydroponic culture. Depending on their concentration (ranging from 0.1 to 1.8 mg L−1), all tested substances had both stimulating and inhibiting effects on the growth rate of the seedlings. Copper and copper oxide-NPs had generally a stimulating effect whereas aluminium and aluminium oxide-NPs at first had a positive effect but in higher concentrations they inhibited the growth. Treating the seedlings with 0.4 mg L−1 of each tested toxicant was mostly stimulating to the expression of the genes and reduced the differences between the transcript levels of the coleoptiles and roots. Increasing concentrations of the tested substances had both stimulating and inhibiting effects on the expression levels of the genes. The highest expression levels were usually noted at concentrations between 0.4 and 1.0 mg/L of each metal and metal nanoparticle, except for SiZIP1, which had the highest transcript amount at 1.6 mg L−1 of Cu2+ and at 0.1–0.8 mg L−1 of CuO-NPs, and LIP and GR from the seedling treated with Al2O3-NPs at concentrations of 0.1 and 1.6 mg L−1, respectively.
Preparation of environmentally responsive PDA&DOX@LAC live drug carrier for synergistic tumor therapy
Authors: Liu Lu , Zhao Xuefen 
Published: July 2024

AbstractThe development of intelligent, environmentally responsive and biocompatible photothermal system holds significant importance for the photothermal combined therapy of tumors. In this study, inspired by Lactobacillus (LAC), we prepared a biomimetic nanoplatform PDA&DOX@LAC for tumor photothermal-chemotherapy by integrating the chemotherapeutic drug doxorubicin (DOX) with dopamine through oxidative polymerization to form polydopamine (PDA) on the surface of LAC. The PDA&DOX@LAC nanoplatform not only achieves precise and controlled release of DOX based on the slightly acidic microenvironment of tumor tissues, but also exhibits enzyme-like properties to alleviate tumor hypoxia. Under near-infrared light irradiation, it effectively induces photothermal ablation of tumor cells, enhances cellular uptake of DOX with increasing temperature, and thus efficiently inhibits tumor cell growth. Moreover, it is further confirmed in vivo experiments that photothermal therapy combined with PDA&DOX@LAC induces tumor cells apoptosis, releases tumor-associated antigens, which is engulfed by dendritic cells to activate cytotoxic T lymphocytes, thereby effectively suppressing tumor growth and prolonging the survival period of 4T1 tumor-bearing mice. Therefore, the PDA&DOX@LAC nanoplatform holds immense potential in precise tumor targeting as well as photothermal combined therapy and provides valuable insights and theoretical foundations for the development of novel tumor treatment strategies based on endogenous substances within the body.
The empirical effect of agricultural social services on pesticide inputs
Authors: Na Hui , Yan Xiumei , Xing Rui , Jiang Anyin 
Published: July 2024

AbstractAgricultural social services (ASS) play an important role in improving the efficiency of agricultural operations, reducing agricultural production costs, and promoting sustainable agricultural development. Using data from the 2020 China Rural Revitalization Survey, this study analyzes the impact of ASS on reducing pesticide inputs. The results show: (1) ASS play a significantly positive role in reducing pesticide inputs. (2) Heterogeneity analyses show that ASS’ role in reducing pesticide inputs is stronger for farming households with small farms, which participate in cooperatives, and do not have members involved in non-farm employment than that for farming households with large farms, which do not participate in cooperatives, and have members involved in non-farm employment. (3) Mechanism analysis shows that ASS’ green perception and demonstration-led effects contribute to reducing pesticide inputs by 148.6% and 36.8%, respectively, at the 1% level. Finally, this study proposes relevant policy recommendations for promoting ASS, promoting the continuous operation of farmland, and encouraging farmers to participate in ASS.
Chromosomal abnormalities detected by chromosomal microarray analysis and pregnancy outcomes of 4211 fetuses with high-risk prenatal indications
Authors: Li Huafeng , Hu Juan , Wu Qingyu , Qiu Jigang , Zhang Li , Zhu Jinping 
Published: July 2024

AbstractWith the gradual liberalization of the three-child policy and the development of assisted reproductive technology in China, the number of women with high-risk pregnancies is gradually increasing. In this study, 4211 fetuses who underwent chromosomal microarray analysis (CMA) with high-risk prenatal indications were analysed. The results showed that the overall prenatal detection rate of CMA was 11.4% (480/4211), with detection rates of 5.82% (245/4211) for abnormal chromosome numbers and 5.58% (235/4211) for copy number variants. Additionally, the detection rates of clinically significant copy number variants were 3.78% (159/4211) and 1.8% (76/4211) for variants of uncertain significance. The detection rates of fetal chromosomal abnormalities were 6.42% (30/467) for pregnant women with advanced maternal age (AMA), 6.01% (50/832) for high-risk maternal serum screening (MSS) results, 39.09% (224/573) with abnormal non-invasive prenatal testing (NIPT) results, 9.21% (127/1379) with abnormal ultrasound results, and 5.1% (49/960) for other indications. Follow-up results were available for 4211 patients, including 3677 (3677/4211, 87.32%) whose infants were normal after birth, 462 (462/4211, 10.97%) who terminated their pregnancy, 51 (51/4211, 1.21%) whose infants were abnormal after birth, and 21 (21/4211, 0.50%) who refused follow-up. The results of this study demonstrate significant variation in the diagnostic rate of chromosomal microarray analysis across different indications, providing valuable guidance for clinicians to assess the applicability of CMA technology in prenatal diagnosis.
Mechanism insight into the conversion between COS and thiophene during CO2 gasification of carbon-based fuels
Authors: Xian Shengxian , Xie Ye , Xu Qing , Yang Zhisi , Li Haowei , Wu Yujian 
Published: July 2024

AbstractThiophene is the organic sulfur with good thermal stability in carbon-based fuel, clarifying the conversion mechanism between thiophene and COS is beneficial for achieving in-situ sulfur fixation during CO2 gasification of carbon-based fuels, but the mechanism has rarely been reported. Therefore, calculations based on density functional theory were performed and 16 reaction paths were proposed in this research, clarifying the decomposition mechanism of thiophene and re-fixation mechanism of COS. The attachment of CO2 will lead to the destruction of the thiophene ring and the generation of COS, and CO2 adsorption is the rate-determined step, while the carbon atom that adjacent sulfur atom is the reaction active site. However, the energy barriers of CO2 addition reactions are lower than those of CO2 adsorption reactions, and the energy barrier of reactions occurring on the aliphatics are lower than that occurring on the aromatics. The combination of CO2 and thiophene will thermodynamically lead to the generation of COS and CO. Moreover, gaseous sulfur generated from thiophene decomposition will be converted mutually, while H2S will not be converted into COS. Furthermore, COS will be captured by char, forming solid organic sulfur. The re-fixation of COS will occur on aliphatic chains from the decomposition of aromatics.
Spores of Clostridioides difficile are toxin delivery vehicles
Authors: Cassona Carolina P. , Ramalhete Sara , Amara Khira , Candela Thomas , Kansau Imad , Denève-Larrazet Cécile , Janoir-Jouveshomme Claire , Mota Luís Jaime , Dupuy Bruno , Serrano Mónica , Henriques Adriano O. 
Published: July 2024

AbstractClostridioides difficile causes a wide range of intestinal diseases through the action of two main cytotoxins, TcdA and TcdB. Ingested spores germinate in the intestine establishing a population of cells that produce toxins and spores. The pathogenicity locus, PaLoc, comprises several genes, including those coding for TcdA/B, for the holin-like TcdE protein, and for TcdR, an auto-regulatory RNA polymerase sigma factor essential for tcdA/B and tcdE expression. Here we show that tcdR, tcdA, tcdB and tcdE are expressed in a fraction of the sporulating cells, in either the whole sporangium or in the forespore. The whole sporangium pattern is due to protracted expression initiated in vegetative cells by σD, which primes the TcdR auto-regulatory loop. In contrast, the forespore-specific regulatory proteins σG and SpoVT control TcdR production and tcdA/tcdB and tcdE expression in this cell. We detected TcdA at the spore surface, and we show that wild type and ΔtcdA or ΔtcdB spores but not ΔtcdR or ΔtcdA/ΔtcdB spores are cytopathic against HT29 and Vero cells, indicating that spores may serve as toxin-delivery vehicles. Since the addition of TcdA and TcdB enhance binding of spores to epithelial cells, this effect may occur independently of toxin production by vegetative cells.
Multi-scale lidar measurements suggest miombo woodlands contain substantially more carbon than thought
Authors: Demol Miro , Aguilar-Amuchastegui Naikoa , Bernotaite Gabija , Disney Mathias , Duncanson Laura , Elmendorp Elise , Espejo Andres , Furey Allister , Hancock Steven , Hansen Johannes , Horsley Harold , Langa Sara , Liang Mengyu , Locke Annabel , Manjate Virgílio , Mapanga Francisco , Omidvar Hamidreza , Parsons Ashleigh , Peneva-Reed Elitsa , Perry Thomas , Puma Vilca Beisit L. , Rodríguez-Veiga Pedro , Sutcliffe Chloe , Upham Robin , de Walque Benoît , Burt Andrew 
Published: July 2024

AbstractMiombo woodlands are integral to livelihoods across southern Africa, biodiversity in the region, and the global carbon cycle, making accurate and precise monitoring of their state and change essential. Here, we assembled a terrestrial and airborne lidar dataset covering 50 kha of intact and degraded miombo woodlands, and generated aboveground biomass estimates with low uncertainty via direct 3D measurements of forest structure. We found 1.71 ± 0.09 TgC was stored in aboveground biomass across this landscape, between 1.5 and 2.2 times more than the 0.79–1.14 TgC estimated by conventional methods. This difference is in part owing to the systematic underestimation of large trees by allometry. If these results were extrapolated across Africa’s miombo woodlands, their carbon stock would potentially require an upward revision of approximately 3.7 PgC, implying we currently underestimate their carbon sequestration and emissions potential, and disincentivise their protection and restoration.
Complex‐step derivative‐based extended Kalman filter for state estimation in twin rotor MIMO system
Authors: Mucuk İbrahim , Özdemir Ayhan 
Published: July 2024

AbstractThis paper presents the design of a complex‐step extended Kalman filter (CS‐EKF) to estimate the states of the twin‐rotor MIMO system (TRMS) which is a non‐linear system. Since the model of TRMS is quite complex and contains discontinuous functions, it is very difficult to calculate the Jacobian matrix in the TRMS analytically by hand. This makes it difficult to implement control methods that require Jacobian matrix calculation for TRMS. Herein, to calculate the Jacobian matrix, the CS‐EKF uses the complex‐step derivative approach, which is a numerical technique and offers near‐analytical accuracy in a single function evaluation. The effectiveness of the CS‐EKF is demonstrated through simulation and real‐time experiments. Also, The CS‐EKF is compared to the finite‐difference extended Kalman filter (FD‐EKF) and the unscented Kalman filter (UKF) in terms of estimation accuracy, computational load, and ease of implementation.
A compensation method for PMSM sensorless control with parameter identification considering SMO observation error
Authors: Guan Ruizhi , Liu Jinglin , Li Mengqi , Xiao Minglang , Shi Xinran 
Published: July 2024

AbstractSensorless control of permanent magnet synchronous motor (PMSM) can increase the reliability of electric actuators of more electrical aircraft. Numerical online parameter estimation method will enhance the performance for sensorless control methods based on sliding mode observer (SMO). However, numerical online parameter identification methods typically assume zero rotor position estimation error to ensure full rank of the identification equation set. This assumption actually leads to errors in parameter identification, resulting in steady‐state errors in rotor position estimation. This paper focuses on a compensation method for PMSM online parameter identification that takes into account rotor position estimation error. This method is used for sensorless control based on SMO, using model reference adaptive systems for online parameter identification, and no additional parameter adjustment required. Validation is conducted on a PMSM experimental platform with maximum load of 15kW. The experimental results of 1000 r/min steady state operation proved the effectiveness of the method, and the dynamic experiments with 5 and 15kW loads proved that the method has no significant adverse effect on the system dynamics.