bluuebunny/crossref_metadata_2025_split huggingface dataset:
Anthropogenic pollen indicators: Global food plants and Latin American human indicators in the pollen record
Authors: Flantua Suzette G. A. , Hooghiemstra Henry 
Published: October 2023

AbstractPollen-based evidence of human presence is crucial for reconstructing human history. However, information on the morphology of pollen grains of global food plants and regional pollen-based human indicators is scattered in the literature, leading to the risk of overlooking important evidence of human presence. To address this issue, we first compiled a comprehensive overview of 354 major food plants worldwide, creating a paleoecology-friendly format that includes their family, vernacular name, earliest known use, environmental preference, and geographical region. Moreover, we identified the sources of illustrations of their pollen grains for 209 out of 273 different genera of globally relevant food plants in 10 selected pollen atlases. Secondly, we compiled all human indicators from pollen-based paleoecological literature in Latin America (based on 750 references), providing an overview of 212 single-pollen type indicators and identified 95 crucial combinations of pollen types as “human indices”, and their corresponding references. Our review datasets aids in distilling human evidence from numerous fossil pollen records worldwide.
Therapeutic potential of lactoferrin-coated iron oxide nanospheres for targeted hyperthermia in gastric cancer
Authors: Attri Komal , Chudasama Bhupendra , Mahajan Roop L. , Choudhury Diptiman 
Published: October 2023

AbstractLactoferrin (LF) is a non-heme iron-binding glycoprotein involved in the transport of iron in blood plasma. In addition, it has many biological functions, including antibacterial, antiviral, antimicrobial, antiparasitic, and, importantly, antitumor properties. In this study, we have investigated the potential of employing lactoferrin-iron oxide nanoparticles (LF-IONPs) as a treatment modality for gastric cancer. The study confirms the formation of LF-IONPs with a spherical shape and an average size of 5 ± 2 nm, embedded within the protein matrix. FTIR and Raman analysis revealed that the Fe–O bond stabilized the protein particle interactions. Further, we conducted hyperthermia studies to ascertain whether the proposed composite can generate a sufficient rise in temperature at a low frequency. The results confirmed that we can achieve a temperature rise of about 7 °C at 242.4 kHz, which can be further harnessed for gastric cancer treatment. The particles were further tested for their anti-cancer activity on AGS cells, with and without hyperthermia. Results indicate that LF-IONPs (10 µg/ml) significantly enhance cytotoxicity, resulting in the demise of 67.75 ± 5.2% of cells post hyperthermia, while also exhibiting an inhibitory effect on cell migration compared to control cells, with the most inhibition observed after 36 h of treatment. These findings suggest the potential of LF-IONPs in targeted hyperthermia treatment of gastric cancer.
The role of response conflict in concealed information detection with reaction times
Authors: klein Selle Nathalie , Or Barak , Van der Cruyssen Ine , Verschuere Bruno , Ben-Shakhar Gershon 
Published: October 2023

AbstractThe concealed information test (CIT) presents various probe (familiar) items amidst irrelevant (unfamiliar) items. When the probe items appear, reaction time (RT) slows down. This RT-CIT effect has been accounted for by a conflict resulting from the need to deny familiarity of the familiar probes. The present pre-registered study (n = 292) examined whether response conflict is sufficient to account for the RT-CIT effect, using city and name items. Specifically, we compared the common conflict condition, where the response buttons emphasized familiarity of CIT items (“unfamiliar” versus “familiar”), to a novel no conflict condition, where the buttons emphasized categorical membership (“city” versus “name”). In line with our expectations, the RT-CIT effect was substantially stronger in the conflict condition; yet, it remained significant even in the no conflict condition. This implies a critical role for response conflict, but also suggests that other mechanisms (e.g. orientation to significant stimuli) may contribute to the RT-CIT effect.
Relationship between body composition and pulmonary function in the general population—a cross-sectional study in Ningxia
Authors: Pi Yang-yang , Hu Wen-xuan , Jiao Zi-ming , Hou Peng-yi , Zhang Yu-hong , Zhao Yi , Li Xiao-xia , Yu Jing , Chen Fang , Jing Jin-yun , Wang Fa-xuan 
Published: October 2023

AbstractStudies considering the relationship between non-obesity-related body composition and lung function are few; therefore, this study aimed to explore these correlations and effects. This cross-sectional study conducted in rural Qingtongxia City and Pingluo County, Ningxia, China, included 776 participants aged 30–75 years. Body composition and lung function were measured using direct segmental multifrequency bioelectrical impedance analysis and a digital spirometer, respectively. Their correlation was assessed using partial correlation analysis, controlling for age and smoking status, and the body composition effect on lung function was analyzed using binomial logistic regression analysis. The body components total body water content, protein content, mineral content, muscle mass, fat-free mass (FFM), skeletal muscle mass, basal metabolic volume, and chest circumference (CC) positively correlated with pulmonary function (forced vital capacity and forced expiratory volume in one second) in both sexes. Neck circumference and hip circumference positively correlated with pulmonary function in women. Additionally, lung function declines more slowly in women (odds ratio [OR] = 0.66, 95% confidence interval [CI] = 0.44–0.98, p =  0.04); CC (OR = 0.92, 95% CI = 0.86–0.98, p = 0.01) increased as a protective factor for decreased lung function. Increased waist circumference (OR = 1.04, 95% CI = 1.00–1.09, p = 0.04) was a risk factor for reduced lung function. FFM contains body composition indicators positively correlating with lung function, excluding fat-related body composition. Abdominal obesity increases the risk of decreased lung function.
Polydatin prevent lung epithelial cell from Carbapenem-resistant Klebsiella pneumoniae injury by inhibiting biofilm formation and oxidative stress
Authors: Guan Xiaodan , Jin Liang , Zhou Huifen , Chen Jing , Wan Haofang , Bao Yida , Yang Jiehong , Yu Daojun , Wan Haitong 
Published: October 2023

AbstractCarbapenem-resistant Klebsiella pneumoniae (CRKP) causes severe inflammation in various infectious diseases, such as bloodstream infections, respiratory and urinary tract infections, which leads to high mortality. Polydatin (PD), an active ingredient of Yinhuapinggan granule, has attracted worldwide attention for its powerful antioxidant, anti-inflammatory, antitumor, and antibacterial capacity. However, very little is known about the effect of PD on CRKP. In this research, we evaluated the inhibitory effects of PD on both the bacterial level and the bacterial-cell co-culture level on anti-biofilm and efflux pumps and the other was the inhibitory effect on apoptosis, reactive oxygen species (ROS), mitochondrial membrane potential (MMP) after CRKP induction. Additionally, we validated the mechanism of action by qRT-PCR and western blot in human lung epithelial cells. Firstly, PD was observed to have an inhibitory effect on the biofilm of CRKP and the efflux pump AcrAB-TolC. Mechanically, CRKP not only inhibited the activation of Nuclear Factor erythroid 2-Related Factor 2 (Nrf-2) but also increased the level of ROS in cells. These results showed that PD could inhibit ROS and activate Nrf-2 production. Together, our research demonstrated that PD inhibited bacterial biofilm formation and efflux pump AcrAB—TolC expression and inhibited CRKP-induced cell damage by regulating ROS and Nrf-2-regulated antioxidant pathways.
Developing anti-microbial peptide database version 1 to provide comprehensive and exhaustive resource of manually curated AMPs
Authors: Mondal Rajat Kumar , Sen Debarup , Arya Ankish , Samanta Sintu Kumar 
Published: October 2023

AbstractAnti-Microbial Peptide Database version 1 (AMPDB v1) is a meticulously curated resource that aims to address the limitations of existing databases in the field of antimicrobial research. We have utilized the latest technology and put our best efforts into adding all relevant tools to cater to the needs of our users. AMPDB v1 is a derived database, built upon information gathered from the available resources and boasts a significant size of 59,122 entries which are classified into 88 classes. All the information in this resource was curated manually. Sequence alignment and protein feature calculation tools were integrated into the database in the form of web applications, to make them easy to use, quick, and responsive in real-time. We have included multiple types of browsing and searching options to enhance the user experience, from simple text search to a completely customizable advanced search page with intuitive options that let the user combine multiple options together to make a powerful search query. The database is accessible by a web browser athttps://bblserver.org.in/ampdb/.
Prognostic visualization model for primary pulmonary sarcoma: a SEER-based study
Authors: Huang Qian , Li Wenqiang , He Xiaoyu , He Qian , Lai Qun , Yuan Quan , Deng Zhiping 
Published: October 2023

AbstractPrimary pulmonary sarcoma (PPS) is a rare and poor prognostic malignancy that results from current clinical studies are lacking. Our study aimed to investigate the prognostic factors of PPS and to construct a predictive nomogram that predict the overall survival (OS) rate. We extracted data on patients diagnosed with PPS from 2010 to 2019 in the SEER database. A total of 169 patients were included after screening by inclusion and exclusion criteria. Univariate and multivariate COX regression analyses showed that age, pathological grade, liver metastasis, surgical intervention, and chemotherapy influenced the prognosis. We constructed the prediction model nomogram based on these factors. Moreover, the results of the internal and external ROC curves, calibration curves, and DCA plots confirmed that the model has good discrimination, accuracy, and clinical practice efficacy. The present study is the first population-based study to explore the factors affecting the prognosis of PPS. We established a novel prognostic nomogram to predict the OS rate, which can help to make proper clinical decisions.
Ecological assessment of Iran’s terrestrial biomes for wildlife conservation
Authors: Ansari Amir , Ghorbanpour Mansour , Kazemi Ali , Kariman Khalil 
Published: October 2023

AbstractMan-made activities pose the greatest threats to wildlife in Iran's terrestrial biomes, causing significant habitat damage and fragmentation in recent years. To fully understand these threats, the present study was conducted to identify and map the Iran’s terrestrial biomes using the IDRISI TerrSet 18.31 Software, the Terrestrial Biomes Ecosystem Service Modeler on the InVEST toolkit (TBESMI), and comprehensive data sources including maps of roads, protected areas, terrestrial biomes, and country-wide land cover maps of 2017. The results showed that the largest terrestrial biome in Iran is deserts and xeric shrublands (DXS), while flooded grasslands and savannas (FGS) is the smallest biome. Roads, along with urban and agricultural developments are among the biggest threats and most destructive stressors in Iran’s terrestrial biomes. The results also revealed that there was a growth in destruction of habitats located in the temperate broadleaf and mixed forest (TBMF), temperate coniferous forest (TCF), and FGS, alongside a decrease in the DXS biome. Furthermore, we detected an increase in habitat landscape quality in the DXS, FGS and montane grasslands and shrub lands (MGS), and a decrease in the temperate grasslands, savannas and shrublands (TGSS) and TBMF biomes. Finally, the cumulative risk of habitat degradation increased in the FGS, TCF, TGSS, and TBMF biomes, whereas it decreased in the DXS biome. The FGS biome with the highest consequence cumulative score, and the MGS biome with the highest cumulative risk exposure score were found to be at the highest risk from man-made activities. Stressors associated with agriculture and urbanization had the highest cumulative exposure scores in the MGS, while roads had the highest exposure scores in the TBMF and DXS biomes. Our study underscores the critical importance of conserving Iran's terrestrial biomes and wildlife, especially in high-risk biomes like FGS and MGS, given the substantial threats posed by human activities.
Fast reconstruction algorithm based on HMC sampling
Authors: Lian Hang , Xu Jinchen , Zhu Yu , Fan Zhiqiang , Liu Yi , Shan Zheng 
Published: October 2023

AbstractIn Noisy Intermediate-Scale Quantum (NISQ) era, the scarcity of qubit resources has prevented many quantum algorithms from being implemented on quantum devices. Circuit cutting technology has greatly alleviated this problem, which allows us to run larger quantum circuits on real quantum machines with currently limited qubit resources at the cost of additional classical overhead. However, the classical overhead of circuit cutting grows exponentially with the number of cuts and qubits, and the excessive postprocessing overhead makes it difficult to apply circuit cutting to large scale circuits. In this paper, we propose a fast reconstruction algorithm based on Hamiltonian Monte Carlo (HMC) sampling, which samples the high probability solutions by Hamiltonian dynamics from state space with dimension growing exponentially with qubit. Our algorithm avoids excessive computation when reconstructing the original circuit probability distribution, and greatly reduces the circuit cutting post-processing overhead. The improvement is crucial for expanding of circuit cutting to a larger scale on NISQ devices.
Estimation of right lobe graft weight for living donor liver transplantation using deep learning-based fully automatic computed tomographic volumetry
Authors: Yang Xiaopeng , Park Seonyeong , Lee Seungyoo , Han Kyujin , Lee Mi Rin , Song Ji Soo , Yu Hee Chul , Do Yang Jae 
Published: October 2023

AbstractThis study aimed at developing a fully automatic technique for right lobe graft weight estimation using deep learning algorithms. The proposed method consists of segmentation of the full liver region from computed tomography (CT) images, classification of the entire liver region into the right and left lobes, and estimation of the right lobe graft weight from the CT-measured right lobe graft volume using a volume-to-weight conversion formula. The first two steps were performed with a transformer-based deep learning model. To train and evaluate the model, a total of 248 CT datasets (188 for training, 40 for validation, and 20 for testing and clinical evaluation) were used. The Dice similarity coefficient (DSC), mean surface distance (MSD), and the 95th percentile Hausdorff distance (HD95) were used for evaluating the segmentation accuracy of the full liver region and the right liver lobe. The correlation coefficient (CC), percentage error (PE), and percentage absolute error (PAE) were used for the clinical evaluation of the estimated right lobe graft weight. The proposed method achieved high accuracy in segmentation for DSC, MSD, and HD95 (95.9% ± 1.0%, 1.2 ± 0.4 mm, and 5.2 ± 1.9 mm for the entire liver region; 92.4% ± 2.7%, 2.0 ± 0.7 mm, and 8.8 ± 2.9 mm for the right lobe) and in clinical evaluation for CC, PE, and PAE (0.859, − 1.8% ± 9.6%, and 8.6% ± 4.7%). For the right lobe graft weight estimation, the present study underestimated the graft weight by − 1.8% on average. A mean difference of − 21.3 g (95% confidence interval: − 55.7 to 13.1, p = 0.211) between the estimated graft weight and the actual graft weight was achieved in this study. The proposed method is effective for clinical application.
Temporal changes in intensity and volume of external training loads during a 1 × 1 short-bout, small-sided games in elite youth soccer players
Authors: Kryściak Jakub , Tomczak Maciej , Podgórski Tomasz , Chmura Paweł , Konefał Marek , Chmura Jan , Maly Tomas , Modric Toni , Andrzejewski Marcin 
Published: October 2023

AbstractThis study compared external training load (ETL) and its temporal changes across repetitions during a speed endurance production (SEP) training comprised of 1 × 1 short-bout, small-sided games (SSGs) in elite youth soccer players. Twenty U18 players were divided into two groups (SEP1 and SEP2) performing six 30 s and 45 s bouts of SSG (work-to-rest ratio 1:4) on a 10 by 15 m field. ETL was characterized by the total distance covered, Player Load, the total number of accelerations/decelerations, and their relative values (per minute). Significant overall decreases in the ETL parameter values across six repetitions in both SSG groups were observed relative to the measurement in the first set beginning in 3rd (SEP1) or 4th (SEP2) repetitions. Significant greater decreases in Player Load (F(5.90) = 2.99, p < 0.05, η P2 = 0.14), Player Load per minute (F(5,90) = 11.32, p < 0.001, η P2 = 0.39), total distance per minute (F(3.43,61.73) = 7.72, p < 0.001, η P2 = 0.30) and accelerations per minute (F(5,90) = 2.59, p < 0.05, η P2 = 0.13) were observed in the 30-s games than in the 45-s games. In conclusion, the use of SSGs in SEP training is associated with a decrease in the effectiveness of physical work performed across repetitions. In practice, due to the decrease in the measured ETL indicators already in the 3rd or 4th repetition (especially in the SEP1 group), the work-to-rest ratio could be increased from the applied 1:4 to 1:6.
High-dimensional deconstruction of pancreatic cancer identifies tumor microenvironmental and developmental stemness features that predict survival
Authors: Storrs Erik P. , Chati Prathamesh , Usmani Abul , Sloan Ian , Krasnick Bradley A. , Babbra Ramandeep , Harris Peter K. , Sachs Chloe M. , Qaium Faridi , Chatterjee Deyali , Wetzel Chris , Goedegebuure S. Peter , Hollander Thomas , Anthony Hephzibah , Ponce Jennifer , Khaliq Ateeq M. , Badiyan Shahed , Kim Hyun , Denardo David G. , Lang Gabriel D. , Cosgrove Natalie D. , Kushnir Vladimir M. , Early Dayna S. , Masood Ashiq , Lim Kian-Huat , Hawkins William G. , Ding Li , Fields Ryan C. , Das Koushik K. , Chaudhuri Aadel A. 
Published: October 2023

AbstractNumerous cell states are known to comprise the pancreatic ductal adenocarcinoma (PDAC) tumor microenvironment (TME). However, the developmental stemness and co-occurrence of these cell states remain poorly defined. Here, we performed single-cell RNA sequencing (scRNA-seq) on a cohort of treatment-naive PDAC time-of-diagnosis endoscopic ultrasound-guided fine needle biopsy (EUS-FNB) samples (n = 25). We then combined these samples with surgical resection (n = 6) and publicly available samples to increase statistical power (n = 80). Following annotation into 25 distinct cell states, cells were scored for developmental stemness, and a customized version of the Ecotyper tool was used to identify communities of co-occurring cell states in bulk RNA-seq samples (n = 268). We discovered a tumor microenvironmental community comprised of aggressive basal-like malignant cells, tumor-promoting SPP1+ macrophages, and myofibroblastic cancer-associated fibroblasts associated with especially poor prognosis. We also found a developmental stemness continuum with implications for survival that is present in both malignant cells and cancer-associated fibroblasts (CAFs). We further demonstrated that high-dimensional analyses predictive of survival are feasible using standard-of-care, time-of-diagnosis EUS-FNB specimens. In summary, we identified tumor microenvironmental and developmental stemness characteristics from a high-dimensional gene expression analysis of PDAC using human tissue specimens, including time-of-diagnosis EUS-FNB samples. These reveal new connections between tumor microenvironmental composition, CAF and malignant cell stemness, and patient survival that could lead to better upfront risk stratification and more personalized upfront clinical decision-making.
Structure of human TRPM8 channel
Authors: Palchevskyi Sergii , Czarnocki-Cieciura Mariusz , Vistoli Giulio , Gervasoni Silvia , Nowak Elżbieta , Beccari Andrea R. , Nowotny Marcin , Talarico Carmine 
Published: October 2023

AbstractTRPM8 is a non-selective cation channel permeable to both monovalent and divalent cations that is activated by multiple factors, such as temperature, voltage, pressure, and changes in osmolality. It is a therapeutic target for anticancer drug development, and its modulators can be utilized for several pathological conditions. Here, we present a cryo-electron microscopy structure of a human TRPM8 channel in the closed state that was solved at 2.7 Å resolution. Our structure comprises the most complete model of the N-terminal pre-melastatin homology region. We also visualized several lipids that are bound by the protein and modeled how the human channel interacts with icilin. Analyses of pore helices in available TRPM structures showed that all these structures can be grouped into different closed, desensitized and open state conformations based on the register of the pore helix S6 which positions particular amino acid residues at the channel constriction.
Computing the relative binding affinity of ligands based on a pairwise binding comparison network
Authors: Yu Jie , Li Zhaojun , Chen Geng , Kong Xiangtai , Hu Jie , Wang Dingyan , Cao Duanhua , Li Yanbei , Huo Ruifeng , Wang Gang , Liu Xiaohong , Jiang Hualiang , Li Xutong , Luo Xiaomin , Zheng Mingyue 
Published: October 2023

AbstractStructure-based lead optimization is an open challenge in drug discovery, which is still largely driven by hypotheses and depends on the experience of medicinal chemists. Here we propose a pairwise binding comparison network (PBCNet) based on a physics-informed graph attention mechanism, specifically tailored for ranking the relative binding affinity among congeneric ligands. Benchmarking on two held-out sets (provided by Schrödinger and Merck) containing over 460 ligands and 16 targets, PBCNet demonstrated substantial advantages in terms of both prediction accuracy and computational efficiency. Equipped with a fine-tuning operation, the performance of PBCNet reaches that of Schrödinger’s FEP+, which is much more computationally intensive and requires substantial expert intervention. A further simulation-based experiment showed that active learning-optimized PBCNet may accelerate lead optimization campaigns by 473%. Finally, for the convenience of users, a web service for PBCNet is established to facilitate complex relative binding affinity prediction through an easy-to-operate graphical interface.
Tribological characteristics of dimpled surfaces filled with dopamine‐modified MoS2
Authors: Qin Tuo , Yu Aibing , Zhao Shuo , Li Kefan , Qi Shaochun , Ye Jiawang 
Published: October 2023

AbstractTo improve the tribological characteristics of dimples on the surface of 45 steel, the dimples were filled with MoS2 and MoS2 modified by dopamine (MoS2 @ DA), and ball‐disk friction and wear tests were conducted. Specifically, the dimple filling gap, abrasion depth, and surface cross‐sectional area of 45 steel were measured. The wear morphology of the friction ball and exfoliation of MoS2 in the dimples and the bending characteristics of the specimens were studied. The surface friction coefficient of MoS2 @ DA‐filled specimen was 17.9% lower than MoS2‐filled specimen, and the dimple filling gap was 70.1% lower, the surface abrasion depth was 5.8% lower, and the abrasion cross‐sectional area was 17.7% smaller. Moreover, the bending strength of the MoS2 @ DA specimen was 3.27 times greater than that of the MoS2 specimen, and the exfoliation of MoS2 was slowed by filling with the MoS2 @ DA. Finally, the tribological characteristics were also superior for the specimens prepared with MoS2 @ DA.