bluuebunny/crossref_metadata_2025_split huggingface dataset:
Discovery of diarylpyrimidine derivatives bearing piperazine sulfonyl as potent HIV-1 nonnucleoside reverse transcriptase inhibitors
Authors: Jiang Xiangyi , Huang Boshi , Rumrill Shawn , Pople David , Zalloum Waleed A. , Kang Dongwei , Zhao Fabao , Ji Xiangkai , Gao Zhen , Hu Lide , Wang Zhao , Xie Minghui , De Clercq Erik , Ruiz Francesc X. , Arnold Eddy , Pannecouque Christophe , Liu Xinyong , Zhan Peng 
Published: April 2023

AbstractHIV-1 reverse transcriptase is one of the most attractive targets for the treatment of AIDS. However, the rapid emergence of drug-resistant strains and unsatisfactory drug-like properties seriously limit the clinical application of HIV-1 non-nucleoside reverse transcriptase inhibitors (NNRTIs). Here we show that a series of piperazine sulfonyl-bearing diarylpyrimidine-based NNRTIs were designed to improve the potency against wild-type and NNRTI-resistant strains by enhancing backbone-binding interactions. Among them, compound 18b1 demonstrates single-digit nanomolar potency against the wild-type and five mutant HIV-1 strains, which is significantly better than the approved drug etravirine. The co-crystal structure analysis and molecular dynamics simulation studies were conducted to explain the broad-spectrum inhibitory activity of 18b1 against reverse transcriptase variants. Besides, compound 18b1 demonstrates improved water solubility, cytochrome P450 liability, and other pharmacokinetic properties compared to the currently approved diarylpyrimidine (DAPY) NNRTIs. Therefore, we consider compound 18b1 a potential lead compound worthy of further study.
Waypoint selection for unmanned aerial vehicle‐aided calibration in wireless positioning networks
Authors: Wu Zhen , Yao Zheng , Lu Mingquan 
Published: April 2023

AbstractDeploying an unmanned aerial vehicle (UAV) to scatter positioning beacons and further calibrate their positions by obtaining range measurements enables the establishment of a wireless positioning network in GNSS‐denied environments where hand placement is not an option. The influence of the UAV trajectory on the calibration quality is investigated and methods to find optimal waypoints at which the UAV makes observations are determined. A Fisher information matrix‐based metric is devised and two waypoint selection algorithms are proposed to optimise calibration quality, one‐off waypoint selection, and iterative and incremental waypoint selection. Numerical results show that optimised waypoints provide more information about beacon positions and therefore produce a more accurate wireless positioning network.
Transition of social organisations driven by gift relationships
Authors: Itao Kenji , Kaneko Kunihiko 
Published: April 2023

AbstractAnthropologists have observed that gifts bring goods to the recipient and honour to the donor in many human societies. The totality of such social relationships constitutes a network. Social networks characterise different types of social organisations including bands of small kin groups, tribal unions of families, and hierarchically organised chiefdoms. However, the factors and mechanisms that cause the transition between these types have hardly been explained. Here, we focus on gifts as the driving force for such changes. We build the model by idealising gift interactions and simulating the consequent social changes due to long-term massive interactions. In the model, people give their wealth to each other, produce wealth, and reciprocate for the gift. Gifts and reciprocation strengthen relationships. Through simulation, we demonstrate that, as the frequency and scale of gifts increase, economic and social disparities successively arise. Simultaneously, network structures shift from bands to tribes and then, chiefdoms. Statistical analysis using the Standard Cross-Cultural Sample, a global ethnographic database, empirically verifies the theoretical results. The constructive simulation study, as presented here, explains how people’s interactions shape various social structures in response to environmental conditions. It provides the basic mechanistic explanation for social evolution and integrates microscopic and macroscopic theories in social sciences.
Association Between Prenatal and Early Postnatal Exposure to Perfluoroalkyl Substances and IQ Score in 7-Year-Old Children From the Odense Child Cohort
Authors: Beck Iben Have , Bilenberg Niels , Möller Sören , Nielsen Flemming , Grandjean Philippe , Højsager Frederik Damsgaard , Halldorsson Thorhallur Ingi , Nielsen Christel , Jensen Tina Kold 
Published: April 2023

Abstract
Perfluoroalkyl substances (PFAS) are persistent chemicals capable of crossing the placenta and passing into breast milk. Evidence suggests that PFAS exposure may affect brain development. We investigated whether prenatal or early postnatal PFAS exposure was associated with intelligence quotient (IQ) scores in schoolchildren from the Odense Child Cohort (Denmark, 2010–2020). We assessed concentrations of perfluorooctane sulfonic acid (PFOS), perfluorooctanoic acid (PFOA), perfluorohexane sulfonic acid (PFHxS), perfluorononanoic acid (PFNA), and perfluorodecanoic acid (PFDA) in maternal serum collected during the first trimester of pregnancy and in child serum at age 18 months. At 7 years of age, children completed an abbreviated version of the Wechsler Intelligence Scale for Children, Fifth Edition, from which Full Scale Intelligence Quotient (FSIQ) and Verbal Comprehension Index scores were estimated. In multiple linear regression analyses conducted among 967 mother-child pairs, a doubling in maternal PFOS and PFNA concentrations was associated with a lower FSIQ score, while no significant associations were observed for PFOA, PFHxS, or PFDA. PFAS concentrations at age 18 months and duration of breastfeeding were strongly correlated, and even in structural equation models it was not possible to differentiate between the opposite effects of PFAS exposure and duration of breastfeeding on FSIQ. PFAS exposure is ubiquitous; therefore, an association with even a small reduction in IQ is of public health concern.
Plant diversity increases above- and below-ground biomass by regulating multidimensional functional trait characteristics
Authors: Wang Chao , Hou Yanhui , Hu Yanxia , Zheng Ruilun , Li Xiaona 
Published: April 2023

AbstractBackground and AimsNitrogen enrichment affects biodiversity, plant functional traits and ecosystem functions. However, the direct and indirect effects of nitrogen addition and biodiversity on the links between plant traits and ecosystem functions have been largely overlooked, even though multidimensional characteristics of plant functional traits are probably critical predictors of ecosystem functions.MethodsTo investigate the mechanism underlying the links between plant trait identity, diversity, network topology and above- and below-ground biomass along a plant species richness gradient under different nitrogen addition levels, a common garden experiment was conducted in which those driving factors were manipulated.Key ResultsThe study found that nitrogen addition increased above-ground biomass but not below-ground biomass, while species richness was positively associated with above- and below-ground biomass. Nitrogen addition had minor effects on plant trait identity and diversity, and on the connectivity and complexity of the trait networks. However, species richness increased above-ground biomass mainly by increasing leaf trait diversity and network modularity, and enhanced below-ground biomass through an increase in root nitrogen concentration and network modularity.ConclusionsThe results demonstrate the mechanistic links between community biomass and plant trait identity, diversity and network topology, and show that the trait network architecture could be an indicator of the effects of global changes on ecosystem functions as importantly as trait identity and diversity.
Spatiotemporal variation of chasmogamy and cleistogamy in a native perennial grass: fecundity, reproductive allocation and allometry
Authors: Cheplick Gregory P 
Published: April 2023

AbstractIt is difficult to assess the relative variability or stability of chasmogamous (CH) and cleistogamous (CL) reproduction in perennial herbs with mixed mating because long-term data in natural populations are unavailable. Here, the aim was to quantify and compare spatial (between-habitat) and temporal (among-year) variation in CH and CL reproduction over 5 years in two subpopulations of the native perennial grass Danthonia compressa. This species produces CH spikelets on terminal panicles in early summer, while axillary CL spikelets, including a basal cleistogene, mature into the autumn. Flowering tillers were collected from a sunny woodland edge and an adjacent shady interior habitat for 5 consecutive years (2017–21). Seed set, fecundity, seed mass and biomass allocation were recorded for the two floral types along with tiller vegetative mass. Bivariate line fitting was used for allometric analysis of CH and CL fecundity. Seed set, fecundity, mass per seed and allocation to seeds differed between floral types and showed significant variation between habitats and among years. Seed set and fecundity in CH panicles were greater than that of axillary CL panicles in most years. Tiller mass positively affected axillary CL seed production and mass of the basal cleistogene. Fecundity and allocation among years were more variable for CH compared to CL reproduction. High seed set and fecundity of CH spikelets suggest that pollination does not limit reproduction via chasmogamy. Late maturation of axillary CL spikelets provides additional fecundity, especially in larger plants along sunny woodland edges. The heavy cleistogene at the tiller base could be important to population persistence, analogous to the axillary bud bank of other perennial grasses that are not cleistogamous. The spatiotemporal stability of CL reproduction underscores the ecological significance of cleistogamy to reproductive fitness.
Relationships of the competitor, stress tolerator, ruderal functional strategies of grass species with lifespan, photosynthetic type, naturalization and climate
Authors: Wingler Astrid , Sandel Brody 
Published: April 2023

Abstract
Grass species (family Poaceae) are globally distributed, adapted to a wide range of climates and express a diversity of functional strategies. We explored the functional strategies of grass species using the competitor, stress tolerator, ruderal (CSR) system and asked how a species’ strategy relates to its functional traits, climatic distribution and propensity to become naturalized outside its native range. We used a global set of trait data for grass species to classify functional strategies according to the CSR system based on leaf traits. Differences in strategies in relation to lifespan (annual or perennial), photosynthetic type (C3 or C4), or naturalisation (native or introduced) were investigated. In addition, correlations with traits not included in the CSR classification were analyzed, and a model was fitted to predict a species’ average mean annual temperature and annual precipitation across its range as a function of CSR scores. Values for competitiveness were higher in C4 species than in C3 species, values for stress tolerance were higher in perennials than in annuals, and introduced species had more pronounced competitive-ruderal strategies than native species. Relationships between the CSR classification, based on leaf traits, and other functional traits were analyzed. Competitiveness was positively correlated with height, while ruderality was correlated with specific root length, indicating that both above- and belowground traits underlying leaf and root economics contribute to realized CSR strategies. Further, relationships between climate and CSR classification showed that species with competitive strategies were more common in warm climates and at high precipitation, whereas species with stress tolerance strategies were more common in cold climates and at low precipitation. The findings presented here demonstrate that CSR classification of functional strategies based on leaf traits matches expectations for the adaptations of grass species that underlie lifespan, photosynthetic type, naturalization and climate.
Machine learning applications on intratumoral heterogeneity in glioblastoma using single-cell RNA sequencing data
Authors: Arteaga-Arteaga Harold Brayan , Candamil-Cortés Mariana S , Breaux Brian , Guillen-Rondon Pablo , Orozco-Arias Simon , Tabares-Soto Reinel 
Published: April 2023

Abstract
Artificial intelligence is revolutionizing all fields that affect people’s lives and health. One of the most critical applications is in the study of tumors. It is the case of glioblastoma (GBM) that has behaviors that need to be understood to develop effective therapies. Due to advances in single-cell RNA sequencing (scRNA-seq), it is possible to understand the cellular and molecular heterogeneity in the GBM. Given that there are different cell groups in these tumors, there is a need to apply Machine Learning (ML) algorithms. It will allow extracting information to understand how cancer changes and broaden the search for effective treatments. We proposed multiple comparisons of ML algorithms to classify cell groups based on the GBM scRNA-seq data. This broad comparison spectrum can show the scientific-medical community which models can achieve the best performance in this task. In this work are classified the following cell groups: Tumor Core (TC), Tumor Periphery (TP) and Normal Periphery (NP), in binary and multi-class scenarios. This work presents the biomarker candidates found for the models with the best results. The analyses presented here allow us to verify the biomarker candidates to understand the genetic characteristics of GBM, which may be affected by a suitable identification of GBM heterogeneity. This work obtained for the four scenarios covered cross-validation results of $93.03\% \pm 5.37\%$, $97.42\% \pm 3.94\%$, $98.27\% \pm 1.81\%$ and $93.04\% \pm 6.88\%$ for the classification of TP versus TC, TP versus NP, NP versus TP and TC (TPC) and NP versus TP versus TC, respectively.
Accurate prediction and key protein sequence feature identification of cyclins
Authors: Yu Shaoyou , Liao Bo , Zhu Wen , Peng Dejun , Wu Fangxiang 
Published: April 2023

Abstract
Cyclin proteins are a group of proteins that activate the cell cycle by forming complexes with cyclin-dependent kinases. Identifying cyclins correctly can provide key clues to understanding the function of cyclins. However, due to the low similarity between cyclin protein sequences, the advancement of a machine learning-based approach to identify cycles is urgently needed. In this study, cyclin protein sequence features were extracted using the profile-based auto-cross covariance method. Then the features were ranked and selected with maximum relevance-maximum distance (MRMD) 1.0 and MRMD2.0. Finally, the prediction model was assessed through 10-fold cross-validation. The computational experiments showed that the best protein sequence features generated by MRMD1.0 could correctly predict 98.2% of cyclins using the random forest (RF) classifier, whereas seven-dimensional key protein sequence features identified with MRMD2.0 could correctly predict 96.1% of cyclins, which was superior to previous studies on the same dataset both in terms of dimensionality and performance comparisons. Therefore, our work provided a valuable tool for identifying cyclins. The model data can be downloaded from https://github.com/YUshunL/cyclin.
Building a Research Community to Bring Evidence into Practice: Case Study
Authors: McGlade Anne , Pollock Elaine , Bunting Lisa , Taylor Brian , McGuckin Sonya , Patton Sonia , Burns Patricia , Wilson Emily , Devlin Tricia , Alkiviadou Andriana 
Published: April 2023

Abstract
This case study drawn from our collective experience in Northern Ireland presents a relatively unique approach that considers the role of wider contextual and organisational factors in supporting or inhibiting research into social work and social care practice. It has been written by members of the Building A Research Community Group (hereafter referred to as Research Community) established in 2019. The Research Community was built on the premise that partnership and co-production working between service delivery organisations, researchers and academia, and service users and carers is an essential underpinning to effective ‘practitioner research’, just as it is to the development of robust practitioner-relevant education and training. Using our experience over the last decade, we argue that bridging the gap between scientific evidence and practice requires leadership and the development of a supportive organisational culture that is receptive to learning and change. Highlighting both successes and challenges, along a journey spanning from 2014, we focus on the importance of developing a research strategy and realistic implementation plan accompanied by resource allocation. By sharing our journey in this case study, we hope that others across other geographical contexts can learn from our experience and are encouraged to share their own experiences.
Exposure to smoky coal combustion emissions and leukocyte Alu retroelement copy number
Authors: Blechter Batel , Wong Jason Y Y , Hu Wei , Cawthon Richard , Downward George S , Portengen Lützen , Zhang Yongliang , Ning Bofu , Rahman Mohammad L , Ji Bu-Tian , Li Jihua , Yang Kaiyun , Dean Hosgood H , Silverman Debra T , Huang Yunchao , Rothman Nathaniel , Vermeulen Roel , Lan Qing 
Published: April 2023

Abstract
Household air pollution (HAP) from indoor combustion of solid fuel is a global health burden that has been linked to multiple diseases including lung cancer. In Xuanwei, China, lung cancer rate for non-smoking women is among the highest in the world and largely attributed to high levels of polycyclic aromatic hydrocarbons (PAHs) that are produced from combustion of smoky (bituminous) coal. Alu retroelements, repetitive mobile DNA sequences that can somatically multiply and promote genomic instability have been associated with risk of lung cancer and diesel engine exhaust exposure. We conducted analyses for 160 non-smoking women in an exposure assessment study in Xuanwei, China with a repeat sample from 49 subjects. Quantitative PCR was used to measure Alu repeat copy number relative to albumin gene copy number (Alu/ALB ratio). Associations between clusters derived from predicted levels of 43 HAP constituents, 5-methylchrysene (5-MC), a PAH previously associated with lung cancer in Xuanwei and was selected a priori for analysis, and Alu repeats were analyzed using generalized estimating equations. A cluster of 31 PAHs reflecting current exposure was associated with increased Alu copy number (β:0.03 per standard deviation change; 95% confidence interval (CI):0.01,0.04; P-value = 2E-04). One compound within this cluster, 5-MC, was also associated with increased Alu copy number (P-value = 0.02). Our findings suggest that exposure to PAHs due to indoor smoky coal combustion may contribute to genomic instability. Additionally, our study provides further support for 5-MC as a prominent carcinogenic component of smoky coal emissions. Further studies are needed to replicate our findings.
Spike-based coupling between single neurons and populations across rat sensory cortices, perirhinal cortex, and hippocampus
Authors: Dorman Reinder , Bos Jeroen J , Vinck Martin A , Marchesi Pietro , Fiorilli Julien , Lorteije Jeanette A M , Reiten Ingrid , Bjaalie Jan G , Okun Michael , Pennartz Cyriel M A 
Published: April 2023

Abstract
Cortical computations require coordination of neuronal activity within and across multiple areas. We characterized spiking relationships within and between areas by quantifying coupling of single neurons to population firing patterns. Single-neuron population coupling (SNPC) was investigated using ensemble recordings from hippocampal CA1 region and somatosensory, visual, and perirhinal cortices. Within-area coupling was heterogeneous across structures, with area CA1 showing higher levels than neocortical regions. In contrast to known anatomical connectivity, between-area coupling showed strong firing coherence of sensory neocortices with CA1, but less with perirhinal cortex. Cells in sensory neocortices and CA1 showed positive correlations between within- and between-area coupling; these were weaker for perirhinal cortex. All four areas harbored broadcasting cells, connecting to multiple external areas, which was uncorrelated to within-area coupling strength. When examining correlations between SNPC and spatial coding, we found that, if such correlations were significant, they were negative. This result was consistent with an overall preservation of SNPC across different brain states, suggesting a strong dependence on intrinsic network connectivity. Overall, SNPC offers an important window on cell-to-population synchronization in multi-area networks. Instead of pointing to specific information-coding functions, our results indicate a primary function of SNPC in dynamically organizing communication in systems composed of multiple, interconnected areas.
Distributed and hierarchical neural encoding of multidimensional biological motion attributes in the human brain
Authors: Wang Ruidi , Lu Xiqian , Jiang Yi 
Published: April 2023

Abstract
The human visual system can efficiently extract distinct physical, biological, and social attributes (e.g. facing direction, gender, and emotional state) from biological motion (BM), but how these attributes are encoded in the brain remains largely unknown. In the current study, we used functional magnetic resonance imaging to investigate this issue when participants viewed multidimensional BM stimuli. Using multiple regression representational similarity analysis, we identified distributed brain areas, respectively, related to the processing of facing direction, gender, and emotional state conveyed by BM. These brain areas are governed by a hierarchical structure in which the respective neural encoding of facing direction, gender, and emotional state is modulated by each other in descending order. We further revealed that a portion of the brain areas identified in representational similarity analysis was specific to the neural encoding of each attribute and correlated with the corresponding behavioral results. These findings unravel the brain networks for encoding BM attributes in consideration of their interactions, and highlight that the processing of multidimensional BM attributes is recurrently interactive.