bluuebunny/crossref_metadata_2025_split huggingface dataset:
Unraveling the effect of intra- and intercellular processes on acetaminophen-induced liver injury
Authors: Heldring M. M. , Shaw A. H. , Beltman J. B. 
Published: August 2022

AbstractIn high dosages, acetaminophen (APAP) can cause severe liver damage, but susceptibility to liver failure varies across individuals and is influenced by factors such as health status. Because APAP-induced liver injury and recovery is regulated by an intricate system of intra- and extracellular molecular signaling, we here aim to quantify the importance of specific modules in determining the outcome after an APAP insult and of potential targets for therapies that mitigate adversity. For this purpose, we integrated hepatocellular acetaminophen metabolism, DNA damage response induction and cell fate into a multiscale mechanistic liver lobule model which involves various cell types, such as hepatocytes, residential Kupffer cells and macrophages. Our model simulations show that zonal differences in metabolism and detoxification efficiency are essential determinants of necrotic damage. Moreover, the extent of senescence, which is regulated by intracellular processes and triggered by extracellular signaling, influences the potential to recover. In silico therapies at early and late time points after APAP insult indicated that prevention of necrotic damage is most beneficial for recovery, whereas interference with regulation of senescence promotes regeneration in a less pronounced way.
A multimodal psychological, physiological and behavioural dataset for human emotions in driving tasks
Authors: Li Wenbo , Tan Ruichen , Xing Yang , Li Guofa , Li Shen , Zeng Guanzhong , Wang Peizhi , Zhang Bingbing , Su Xinyu , Pi Dawei , Guo Gang , Cao Dongpu 
Published: August 2022

AbstractHuman emotions are integral to daily tasks, and driving is now a typical daily task. Creating a multi-modal human emotion dataset in driving tasks is an essential step in human emotion studies. we conducted three experiments to collect multimodal psychological, physiological and behavioural dataset for human emotions (PPB-Emo). In Experiment I, 27 participants were recruited, the in-depth interview method was employed to explore the driver’s viewpoints on driving scenarios that induce different emotions. For Experiment II, 409 participants were recruited, a questionnaire survey was conducted to obtain driving scenarios information that induces human drivers to produce specific emotions, and the results were used as the basis for selecting video-audio stimulus materials. In Experiment III, 40 participants were recruited, and the psychological data and physiological data, as well as their behavioural data were collected of all participants in 280 times driving tasks. The PPB-Emo dataset will largely support the analysis of human emotion in driving tasks. Moreover, The PPB-Emo dataset will also benefit human emotion research in other daily tasks.
Chromosome-level genome assembly of largemouth bass (Micropterus salmoides) using PacBio and Hi-C technologies
Authors: He Kuo , Zhao Liulan , Yuan Zihao , Canario Adelino , Liu Qiao , Chen Siyi , Guo Jiazhong , Luo Wei , Yan Haoxiao , Zhang Dongmei , Li Lisen , Yang Song 
Published: August 2022

AbstractThe largemouth bass (Micropterus salmoides) has become a cosmopolitan species due to its widespread introduction as game or domesticated fish. Here a high-quality chromosome-level reference genome of M. salmoides was produced by combining Illumina paired-end sequencing, PacBio single molecule sequencing technique (SMRT) and High-through chromosome conformation capture (Hi-C) technologies. Ultimately, the genome was assembled into 844.88 Mb with a contig N50 of 15.68 Mb and scaffold N50 length of 35.77 Mb. About 99.9% assembly genome sequences (844.00 Mb) could be anchored to 23 chromosomes, and 98.03% assembly genome sequences could be ordered and directed. The genome contained 38.19% repeat sequences and 2693 noncoding RNAs. A total of 26,370 protein-coding genes from 3415 gene families were predicted, of which 97.69% were functionally annotated. The high-quality genome assembly will be a fundamental resource to study and understand how M. salmoides adapt to novel and changing environments around the world, and also be expected to contribute to the genetic breeding and other research.
Towards seasonal forecasting of flood probabilities in Europe using climate and catchment information
Authors: Steirou Eva , Gerlitz Lars , Sun Xun , Apel Heiko , Agarwal Ankit , Totz Sonja , Merz Bruno 
Published: August 2022

AbstractWe investigate whether the distribution of maximum seasonal streamflow is significantly affected by catchment or climate state of the season/month ahead. We fit the Generalized Extreme Value (GEV) distribution to extreme seasonal streamflow for around 600 stations across Europe by conditioning the GEV location and scale parameters on 14 indices, which represent the season-ahead climate or catchment state. The comparison of these climate-informed models with the classical GEV distribution, with time-constant parameters, suggests that there is a substantial potential for seasonal forecasting of flood probabilities. The potential varies between seasons and regions. Overall, the season-ahead catchment wetness shows the highest potential, although climate indices based on large-scale atmospheric circulation, sea surface temperature or sea ice concentration also show some skill for certain regions and seasons. Spatially coherent patterns and a substantial fraction of climate-informed models are promising signs towards early alerts to increase flood preparedness already a season ahead.
Investigating calcification-related candidates in a non-symbiotic scleractinian coral, Tubastraea spp.
Authors: Capasso Laura , Aranda Manuel , Cui Guoxin , Pousse Melanie , Tambutté Sylvie , Zoccola Didier 
Published: August 2022

AbstractIn hermatypic scleractinian corals, photosynthetic fixation of CO2and the production of CaCO3are intimately linked due to their symbiotic relationship with dinoflagellates of the Symbiodiniaceae family. This makes it difficult to study ion transport mechanisms involved in the different pathways. In contrast, most ahermatypic scleractinian corals do not share this symbiotic relationship and thus offer an advantage when studying the ion transport mechanisms involved in the calcification process. Despite this advantage, non-symbiotic scleractinian corals have been systematically neglected in calcification studies, resulting in a lack of data especially at the molecular level. Here, we combined a tissue micro-dissection technique and RNA-sequencing to identify calcification-related ion transporters, and other candidates, in the ahermatypic non-symbiotic scleractinian coralTubastraeaspp. Our results show thatTubastraeaspp. possesses several calcification-related candidates previously identified in symbiotic scleractinian corals (such as SLC4-γ, AMT-1like, CARP, etc.). Furthermore, we identify and describe a role in scleractinian calcification for several ion transporter candidates (such as SLC13, -16, -23, etc.) identified for the first time in this study. Taken together, our results provide not only insights about the molecular mechanisms underlying non-symbiotic scleractinian calcification, but also valuable tools for the development of biotechnological solutions to better control the extreme invasiveness of corals belonging to this particular genus.
Developing machine learning algorithms for dynamic estimation of progression during active surveillance for prostate cancer
Authors: Lee Changhee , Light Alexander , Saveliev Evgeny S. , van der Schaar Mihaela , Gnanapragasam Vincent J. 
Published: August 2022

AbstractActive Surveillance (AS) for prostate cancer is a management option that continually monitors early disease and considers intervention if progression occurs. A robust method to incorporate “live” updates of progression risk during follow-up has hitherto been lacking. To address this, we developed a deep learning-based individualised longitudinal survival model using Dynamic-DeepHit-Lite (DDHL) that learns data-driven distribution of time-to-event outcomes. Further refining outputs, we used a reinforcement learning approach (Actor-Critic) for temporal predictive clustering (AC-TPC) to discover groups with similar time-to-event outcomes to support clinical utility. We applied these methods to data from 585 men on AS with longitudinal and comprehensive follow-up (median 4.4 years). Time-dependent C-indices and Brier scores were calculated and compared to Cox regression and landmarking methods. Both Cox and DDHL models including only baseline variables showed comparable C-indices but the DDHL model performance improved with additional follow-up data. With 3 years of data collection and 3 years follow-up the DDHL model had a C-index of 0.79 (±0.11) compared to 0.70 (±0.15) for landmarking Cox and 0.67 (±0.09) for baseline Cox only. Model calibration was good across all models tested. The AC-TPC method further discovered 4 distinct outcome-related temporal clusters with distinct progression trajectories. Those in the lowest risk cluster had negligible progression risk while those in the highest cluster had a 50% risk of progression by 5 years. In summary, we report a novel machine learning approach to inform personalised follow-up during active surveillance which improves predictive power with increasing data input over time.
The evolution of conglobation in Ceratocanthinae
Authors: Lu Yuanyuan , Ballerio Alberto , Wang Shuo , Zou Zhengting , Gorb Stanislav N. , Wang Tao , Li Lulu , Ji Shen , Zhao Zhengyu , Li Sheng , Tong Yijie , Chen Yandong , Zhuo De , Luo Cihang , Zhang Weiwei , Liu Ning , Gu Qi , Bai Ming 
Published: August 2022

AbstractConglobation is an adaptive behaviour occurring independently in various animal groups. Here, we study the evolution of conglobation in Ceratocanthinae, a beetle group with the ability to roll three body segments into a tight ball. It is here implied that this ability evolved only once in the Mesozoic. Evidence is offered suggesting that the high defensive strength of Ceratocanthinae is due not only to the spherical body shape but also to the thickness and stronger mechanical properties of the dorsal cuticle. We further validate five adaptive characters including the allometrically thickened body wall and find that the specific adaptation of different body segments are likely separate evolutionary events. Finally, we propose an “attackers stress” hypothesis to explain the origin of conglobation behaviours. This work contributes to understanding how and why conglobation behaviour may have evolved in this group.
Alpine shrub growth follows bimodal seasonal patterns across biomes – unexpected environmental controls
Authors: Dobbert Svenja , Albrecht Eike Corina , Pape Roland , Löffler Jörg 
Published: August 2022

AbstractUnder climate change, cold-adapted alpine ecosystems are turning into hotspots of warming. However, the complexity of driving forces of growth, associated biomass gain and carbon storage of alpine shrubs is poorly understood. We monitored alpine growth mechanisms of six common shrub species across contrasting biomes, Mediterranean and tundra, using 257 dendrometers, recording stem diameter variability at high temporal resolution. Linking shrub growth to on-site environmental conditions, we modelled intra-annual growth patterns based on distributed lag non-linear models implemented with generalized additive models. We found pronounced bimodal growth patterns across biomes, and counterintuitively, within the cold-adapted biome, moisture, and within the drought-adapted biome, temperature was crucial, with unexpected consequences. In a warmer world, the Mediterranean alpine might experience strong vegetation shifts, biomass gain and greening, while the alpine tundra might see less changes in vegetation patterns, minor modifications of biomass stocks and rather browning.
Variational quantum eigensolver techniques for simulating carbon monoxide oxidation
Authors: Sapova Mariia D. , Fedorov Aleksey K. 
Published: August 2022

AbstractVariational Quantum Eigensolver (VQE) methods aim to maximize the resources of existing noisy devices. However, they encounter difficulties in simulating molecules of industrially-relevant sizes, such as constructing the efficient ansatz. Adaptive variational algorithms (ADAPT-VQE) can solve this problem but with a significant increase in the number of measurements. Here, we reduce the measurement overhead of ADAPT-VQE via adding operator batches to the ansatz while keeping it compact. We reformulate the previously proposed qubit pool completeness criteria for the tapered qubit space and propose an automated pool construction procedure. Our numerical results indicate that reducing the qubit pool size from polynomial to linear conversely increases the number of measurements. We simulate a set of molecules, participating in the carbon monoxide oxidation processes using the statevector simulator and compare the results with VQE-UCCSD and classical methods. Our results pave the way towards usage of variational approaches for solving practically relevant chemical problems.
DFT insights into superelectrophilic activation of α,β-unsaturated nitriles and ketones in superacids
Authors: Genaev Alexander M. , Salnikov George E. , Koltunov Konstantin Yu. 
Published: August 2022

Density functional theory studies have confirmed that N,C-diprotonation of α,β-unsaturated nitriles, and likewise O,C-diprotonation of isoelectronic ketones, provide the best rationale for their electrophilic reactions with weak nucleophiles, such as benzene.
Stochastic stability and stabilization of positive Markov jump linear impulsive systems with time delay
Authors: Zhao Ping , Kang Yu , Niu Ben , Wang Xinjun 
Published: August 2022

AbstractThis paper investigates the stochastic stability and stabilization of positive Markov jump linear impulsive systems (PMJLIS) with time delay. First, by choosing appropriate co‐positive Lyapunov–Krasovskii functional and using the impulsive average dwell‐time method, a stochastic stability criterion is provided for PMJLIS with time delay. Based on this criterion, for PMJLIS with time delay, the stabilization conditions are given using state feedback and impulse feedback, respectively. According to this criteria, the stochastic stability of the systems can be judged and the controllers can be designed only from some relations of the coefficient matrices, Markov jump parameters and delay. To illustrate the main results, a simulation example is provided at the end with a state‐feedback controller and an impulsive controller is designed, respectively, which makes the corresponding closed‐loop systems be positive, globally asymptotically stable in probability and globally asymptotically stable in mean.
The impact of analyst forecast errors on fundamental indexation: the Australian evidence
Authors: Casavecchia Lorenzo , Hambusch Gerhard , Hitchen Justin 
Published: August 2022

AbstractEvidence from many developed markets suggests that fundamental indices outperform capitalisation-weighted indices. Existing studies suspect a story of market mispricing, yet a mechanism has not been identified. Using Australian data, we study the relation between analyst forecast errors and the performance of various fundamental indices. We find that fundamental indices contain a relatively higher exposure to stocks with low analyst long-term growth forecasts. Valuations for these stocks are ex ante overly pessimistic and drive the statistical significance of alphas produced by fundamental indexation. We show how hedging against analyst forecast errors can generate additional alpha for investors using fundamental indexation.
Recognition Awards in Pathology Specialty Societies: Gender Analysis Among Physician Recipients
Authors: Wobker Sara E , Ginter Paula S , Parra-Herran Carlos , Schwartz Lauren E , Booth Garrett S , Fitzhugh Valerie A , Silver Julie K , Khani Francesca 
Published: August 2022

Abstract

Objectives
Recognition awards build physician reputation and facilitate career advancement. We hypothesize women physicians are underrepresented as award recipients by pathology medical societies compared with representation in the specialty.

Methods
We analyzed publicly available online information about physician recipients (January 2015 to December 2021) from three general pathology society websites. Recipient gender was determined by pronoun use, first name, and photograph. Representation was compared with Association of American Medical Colleges (AAMC) specialty data from 2015 and 2019, which showed a minimum of 36.7% women pathologists in 2015 and up to 43.4% in 2019.

Results
Twenty-six awards and 230 physician recipients were included in the analysis. A total of 159 (69.1%) men physicians and 71 (30.9%) women physicians received awards. Overall, women physicians were underrepresented in recognition awards compared with AAMC benchmarks. Prestigious awards (defined as those that recognize a person’s body of work over time) showed a similar disparity with 22 (30.1%) of 73 recipients being women. Men physicians were more likely to receive multiple awards.

Conclusions
Women physicians are underrepresented overall for recognition awards by pathology medical societies. Disparities are greater for prestigious awards. Further research is needed to better understand the reasons for these findings and how they affect women physicians’ careers.
Dynamic regulation of lipid metabolism in the placenta of in vitro and in vivo models of gestational diabetes mellitus
Authors: Kim So Young , Lee Young Joo , An Sung-Min , Kim Min Jae , Jeong Jea Sic , Kim Da Som , Lim Yong , Jung Eui-Man , Kim Seung-Chul , An Beum-Soo 
Published: August 2022

Abstract
The purpose of this study was to investigate lipid metabolism in the placenta of gestational diabetes mellitus individuals and to evaluate its effect on the fetus. We examined the expression of lipogenesis- and lipolysis-related proteins in the in vitro and in vivo gestational diabetes mellitus placenta models. The levels of sterol regulatory element binding protein-1c were increased, and fat accumulated more during early hyperglycemia, indicating that lipogenesis was stimulated. When hyperglycemia was further extended, lipolysis was activated due to the phosphorylation of hormone-sensitive lipase and expression of adipose triglyceride lipase. In the animal model of gestational diabetes mellitus and in the placenta of gestational diabetes mellitus patients during the extended stage of gestational diabetes mellitus, the expression of sterol regulatory element binding protein-1c decreased and the deposition of fat increased. Similar to the results obtained in the in vitro study, lipolysis was enhanced in the animal and human placenta of extended gestational diabetes mellitus. These results suggest that fat synthesis may be stimulated by lipogenesis in the placenta when the blood glucose level is high. Subsequently, the accumulated fat can be degraded by lipolysis and more fat and its metabolites can be delivered to the fetus when the gestational diabetes mellitus condition is extended at the late stage of gestation. Imbalanced fat metabolism in the placenta and fetus of gestational diabetes mellitus patients can cause metabolic complications in the fetus, including fetal macrosomia, obesity, and type 2 diabetes mellitus.
Body and peripersonal space representations in chronic stroke patients with upper limb motor deficits
Authors: Bassolino Michela , Franza Matteo , Guanziroli Eleonora , Sorrentino Giuliana , Canzoneri Elisa , Colombo Maria , Crema Andrea , Bertoni Tommaso , Mastria Giulio , Vissani Matteo , Sokolov Arseny A , Micera Silvestro , Molteni Franco , Blanke Olaf , Serino Andrea 
Published: August 2022

AbstractThe continuous stream of multisensory information between the brain and the body during body–environment interactions is crucial to maintain the updated representation of the perceived dimensions of body parts (metric body representation) and the space around the body (the peripersonal space). Such flow of multisensory signals is often limited by upper limb sensorimotor deficits after stroke. This would suggest the presence of systematic distortions of metric body representation and peripersonal space in chronic patients with persistent sensorimotor deficits. We assessed metric body representation and peripersonal space representation in 60 chronic stroke patients with unilateral upper limb motor deficits, in comparison with age-matched healthy controls. We also administered a questionnaire capturing explicit feelings towards the affected limb. These novel measures were analysed with respect to patients’ clinical profiles and brain lesions to investigate the neural and functional origin of putative deficits. Stroke patients showed distortions in metric body representation of the affected limb, characterized by an underestimation of the arm length and an alteration of the arm global shape. A descriptive lesion analysis (subtraction analysis) suggests that these distortions may be more frequently associated with lesions involving the superior corona radiata and the superior frontal gyrus. Peripersonal space representation was also altered, with reduced multisensory facilitation for stimuli presented around the affected limb. These deficits were more common in patients reporting pain during motion. Explorative lesion analyses (subtraction analysis, disconnection maps) suggest that the peripersonal space distortions would be more frequently associated with lesions involving the parietal operculum and white matter frontoparietal connections. Moreover, patients reported altered feelings towards the affected limb, which were associated with right brain damage, proprioceptive deficits and a lower cognitive profile. These results reveal implicit and explicit distortions involving metric body representation, peripersonal space representation and the perception of the affected limb in chronic stroke patients. These findings might have important clinical implications for the longitudinal monitoring and the treatments of often-neglected deficits in body perception and representation.
The Conceptual and Methodological Characteristics of Ageism During COVID-19: A Scoping Review of Empirical Studies
Authors: Werner Perla , AboJabel Hanan 
Published: August 2022

Abstract

Background and Objectives
Printed and social media, as well as professional and scholarly platforms, have extensively discussed the proliferation of ageism during the coronavirus disease 2019 (COVID-19) pandemic. However, no study has systematically examined the body of knowledge on the topic. Framed around the characteristics of ageism in general, the aim of this review was to identify and characterize the conceptual and methodological underpinnings of the global, peer-reviewed, and empirical literature on ageism during COVID-19.

Research Design and Methods
We conducted a scoping review in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, using PubMed, CINAHL, AgeLine, and PsycINFO. Quantitative and/or qualitative, English-language, and peer-reviewed articles were included. Data were tabulated and synthesized.

Results
Thirty six articles examining ageism during the COVID-19 pandemic met inclusion criteria. Most were quantitative (64%) and cross-sectional (81%). The level, correlates, and consequences of ageism during the pandemic were similar to the ones reported before it. Studies about ageism during COVID-19 had similar conceptualization and measurement problems to those before the pandemic.

Discussion and Implications
Empirical studies did not find ageism during COVID-19 to be a unique phenomenon, as suggested by the media. More theoretically sound and methodologically rigorous studies, using longitudinal designs and validated unique measures are needed to examine this unique phenomenon.