bluuebunny/crossref_metadata_2025_split huggingface dataset:
Integrating human activity into food environments can better predict cardiometabolic diseases in the United States
Authors: Xu Ran , Huang Xiao , Zhang Kai , Lyu Weixuan , Ghosh Debarchana , Li Zhenlong , Chen Xiang 
Published: November 2023

AbstractThe prevalence of cardiometabolic diseases in the United States is presumably linked to an obesogenic retail food environment that promotes unhealthy dietary habits. Past studies, however, have reported inconsistent findings about the relationship between the two. One underexplored area is how humans interact with food environments and how to integrate human activity into scalable measures. In this paper, we develop the retail food activity index (RFAI) at the census tract level by utilizing Global Positioning System tracking data covering over 94 million aggregated visit records to approximately 359,000 food retailers across the United States over two years. Here we show that the RFAI has significant associations with the prevalence of multiple cardiometabolic diseases. Our study indicates that the RFAI is a promising index with the potential for guiding the development of policies and health interventions aimed at curtailing the burden of cardiometabolic diseases, especially in communities characterized by obesogenic dietary behaviors.
Intra- and inter-molecular regulation by intrinsically-disordered regions governs PUF protein RNA binding
Authors: Qiu Chen , Zhang Zihan , Wine Robert N. , Campbell Zachary T. , Zhang Jun , Hall Traci M. Tanaka 
Published: November 2023

AbstractPUF proteins are characterized by globular RNA-binding domains. They also interact with partner proteins that modulate their RNA-binding activities. Caenorhabditis elegans PUF protein fem-3 binding factor-2 (FBF-2) partners with intrinsically disordered Lateral Signaling Target-1 (LST-1) to regulate target mRNAs in germline stem cells. Here, we report that an intrinsically disordered region (IDR) at the C-terminus of FBF-2 autoinhibits its RNA-binding affinity by increasing the off rate for RNA binding. Moreover, the FBF-2 C-terminal region interacts with its globular RNA-binding domain at the same site where LST-1 binds. This intramolecular interaction restrains an electronegative cluster of amino acid residues near the 5′ end of the bound RNA to inhibit RNA binding. LST-1 binding in place of the FBF-2 C-terminus therefore releases autoinhibition and increases RNA-binding affinity. This regulatory mechanism, driven by IDRs, provides a biochemical and biophysical explanation for the interdependence of FBF-2 and LST-1 in germline stem cell self-renewal.
PI3K/AKT signaling activates HIF1α to modulate the biological effects of invasive breast cancer with microcalcification
Authors: Tian Yao , Zhao Lu , Gui Zhengwei , Liu Shiyang , Liu Chenguang , Yu Tianyao , Zhang Lin 
Published: November 2023

AbstractMicrocalcification (MC) is a valuable diagnostic indicator of breast cancer, and it is reported to be associated with increased tumor aggressiveness and poor prognosis. Nevertheless, the exact potential molecular mechanism is not completely understood. Here, we find that the mineralized invasive breast cancer (IBC) cells not only increased their proliferation and migration, but also showed the characteristic of doxorubicin resistance. The PI3K/AKT signaling pathway is associated with the generation of calcification in IBC, and it activates the transcription and translation of its downstream hypoxia-inducible factor 1α (HIF1α). Knockdown of HIF1α protein significantly downregulated cell proliferation and migration while calcification persists. Meanwhile, calcified breast cancer cells restored sensitivity to doxorubicin because of suppressed HIF1α expression. In addition, we provide initial data on the underlying value of HIF1α as a biomarker of doxorubicin resistance. These findings provide a new direction for exploring microcalcifications in IBC.
Laser pulse compression by a density gradient plasma for exawatt to zettawatt lasers
Authors: Hur Min Sup , Ersfeld Bernhard , Lee Hyojeong , Kim Hyunsuk , Roh Kyungmin , Lee Yunkyu , Song Hyung Seon , Kumar Manoj , Yoffe Samuel , Jaroszynski Dino A. , Suk Hyyong 
Published: November 2023

AbstractWe propose a new method of compressing laser pulses to ultrahigh powers based on spatially varying dispersion of an inhomogeneous plasma. Here, compression is achieved when a long, negatively frequency-chirped laser pulse reflects off the density ramp of an over-dense plasma slab. As the density increases longitudinally, high-frequency photons at the leading part of the laser pulse penetrate more deeply into the plasma region than lower-frequency photons, resulting in pulse compression in a similar way to that by a chirped mirror. Proof-of-principle simulations performed using particle-in-cell simulation codes predict compression of a 2.35 ps laser pulse to 10.3 fs—a ratio of 225. As plasma is robust and resistant to damage at high intensities—unlike solid-state gratings commonly used in chirped-pulse amplification—the method could be used as a compressor to reach exawatt or zettawatt peak powers.
Predicting multiple conformations via sequence clustering and AlphaFold2
Authors: Wayment-Steele Hannah K. , Ojoawo Adedolapo , Otten Renee , Apitz Julia M. , Pitsawong Warintra , Hömberger Marc , Ovchinnikov Sergey , Colwell Lucy , Kern Dorothee 
Published: November 2023

Abstract
AlphaFold2 (ref. 1) has revolutionized structural biology by accurately predicting single structures of proteins. However, a protein’s biological function often depends on multiple conformational substates2, and disease-causing point mutations often cause population changes within these substates3,4. We demonstrate that clustering a multiple-sequence alignment by sequence similarity enables AlphaFold2 to sample alternative states of known metamorphic proteins with high confidence. Using this method, named AF-Cluster, we investigated the evolutionary distribution of predicted structures for the metamorphic protein KaiB5 and found that predictions of both conformations were distributed in clusters across the KaiB family. We used nuclear magnetic resonance spectroscopy to confirm an AF-Cluster prediction: a cyanobacteria KaiB variant is stabilized in the opposite state compared with the more widely studied variant. To test AF-Cluster’s sensitivity to point mutations, we designed and experimentally verified a set of three mutations predicted to flip KaiB from Rhodobacter sphaeroides from the ground to the fold-switched state. Finally, screening for alternative states in protein families without known fold switching identified a putative alternative state for the oxidoreductase Mpt53 in Mycobacterium tuberculosis. Further development of such bioinformatic methods in tandem with experiments will probably have a considerable impact on predicting protein energy landscapes, essential for illuminating biological function.
Protein-based bandpass filters for controlling cellular signaling with chemical inputs
Authors: Shui Sailan , Scheller Leo , Correia Bruno E. 
Published: November 2023

AbstractBiological signal processing is vital for cellular function. Similar to electronic circuits, cells process signals via integrated mechanisms. In electronics, bandpass filters transmit frequencies with defined ranges, but protein-based counterparts for controlled responses are lacking in engineered biological systems. Here, we rationally design protein-based, chemically responsive bandpass filters (CBPs) showing OFF-ON-OFF patterns that respond to chemical concentrations within a specific range and reject concentrations outside that range. Employing structure-based strategies, we designed a heterodimeric construct that dimerizes in response to low concentrations of a small molecule (ON), and dissociates at high concentrations of the same molecule (OFF). The CBPs have a multidomain architecture in which we used known drug receptors, a computationally designed protein binder and small-molecule inhibitors. This modular system allows fine-tuning for optimal performance in terms of bandwidth, response, cutoff and fold changes. The CBPs were used to regulate cell surface receptor signaling pathways to control cellular activities in engineered cells.
Model-based predictions of protective HIV pre-exposure prophylaxis adherence levels in cisgender women
Authors: Zhang Lanxin , Iannuzzi Sara , Chaturvedula Ayyappa , Irungu Elizabeth , Haberer Jessica E. , Hendrix Craig W. , von Kleist Max 
Published: November 2023

AbstractMost human immunodeficiency virus (HIV) infections occur in cisgender women in resource-limited settings. In women, self-protection with emtricitabine/tenofovir disoproxil fumarate pre-exposure prophylaxis (FTC/TDF-PrEP) constitutes a major pillar of HIV prevention. However, clinical trials in women had inconsistent outcomes, sparking uncertainty about adherence requirements and reluctance in evaluating on-demand regimens. We analyzed data from published FTC/TDF-PrEP trials to establish efficacy ranges in cisgender women. In a ‘bottom-up’ approach, we modeled hypotheses in the context of risk-group-specific, adherence–efficacy profiles and challenged those hypotheses with clinical data. We found that different clinical outcomes were related to the proportion of women taking the product, allowing coherent interpretation of the data. Our analysis showed that 90% protection was achieved when women took some product. We found that hypotheses of putative male/female differences were either not impactful or statistically inconsistent with clinical data. We propose that differing clinical outcomes could arise from pill-taking behavior rather than biological factors driving specific adherence requirements in cisgender women.
Meta-reinforcement learning via orbitofrontal cortex
Authors: Hattori Ryoma , Hedrick Nathan G. , Jain Anant , Chen Shuqi , You Hanjia , Hattori Mariko , Choi Jun-Hyeok , Lim Byung Kook , Yasuda Ryohei , Komiyama Takaki 
Published: November 2023

AbstractThe meta-reinforcement learning (meta-RL) framework, which involves RL over multiple timescales, has been successful in training deep RL models that generalize to new environments. It has been hypothesized that the prefrontal cortex may mediate meta-RL in the brain, but the evidence is scarce. Here we show that the orbitofrontal cortex (OFC) mediates meta-RL. We trained mice and deep RL models on a probabilistic reversal learning task across sessions during which they improved their trial-by-trial RL policy through meta-learning. Ca2+/calmodulin-dependent protein kinase II-dependent synaptic plasticity in OFC was necessary for this meta-learning but not for the within-session trial-by-trial RL in experts. After meta-learning, OFC activity robustly encoded value signals, and OFC inactivation impaired the RL behaviors. Longitudinal tracking of OFC activity revealed that meta-learning gradually shapes population value coding to guide the ongoing behavioral policy. Our results indicate that two distinct RL algorithms with distinct neural mechanisms and timescales coexist in OFC to support adaptive decision-making.
Soil organic carbon stocks increased across the tide-induced salinity transect in restored mangrove region
Authors: Zou Huimin , Li Xianglan , Li Sen , Xu Zhe , Yu Zhitong , Cai Houcai , Chen Wandong , Ni Xiaopin , Wu Erwei , Zeng Guihou 
Published: November 2023

AbstractBlue carbon in mangrove ecosystems contributes significantly to the global carbon cycle. However, large uncertainties maintain in the soil organic carbon (SOC) storage throughout the tide-induced salinity and alkalinity transect in the mangrove restoration region in Southern China. Total 125 soil samples were obtained to detect the SOC content and physicochemical properties. The mean SOC content of each layer ranged from 6.82 to 7.86 g kg−1, while the SOC density ranged from 2.99 to 11.41 kg m−2, increasing with soil depths. From different land covers in the study region, the SOC content varied from 4.63 to 9.71 g kg−1, increasing across the salinity and alkalinity transect, while the SOC density fluctuated from 3.01 kg m−2 in mudflats to 10.05 kg m−2 in mangrove forests. SOC concentration was favorably linked with total nitrogen (r = 0.95), and total phosphorus (r = 0.74), and negatively correlated with Cl− (r = − 0.95), electrical conductivity (r = − 0.24), and total dissolved solids (r = − 0.08). There were significant logarithmic relationships between SOC content and the concentrations of clay (r = 0.76), fine silt (r = 0.81), medium silt (r = − 0.82), and coarse silt (r = − 0.78). The spatial patterns of SOC concentration were notably affected by soil texture, physicochemical properties, and land-cover type, providing essential reference for future investigations of blue carbon budget in restored mangrove forests.
Influence of the pesticide flupyradifurone on mobility and physical condition of larval green lacewings
Authors: Scheibli Leonie , Elsenhans Tabita , Wolf Harald , Stemme Torben , Pfeffer Sarah Elisabeth 
Published: November 2023

AbstractGlobal pesticide use in agriculture is one reason for the rapid insect decline in recent years. The relatively new pesticide flupyradifurone is neurotoxic to pest insects but considered harmless to bees according to previous risk assessments. With this study, we aim to investigate lethal and sublethal effects of flupyradifurone on larvae of the beneficial arthropod Chrysoperla carnea. We treated the animals orally with field-realistic concentrations of flupyradifurone and examined lethality as well as effects on condition, mobility and locomotion. For the lethal dose 50, we determined a value of > 120–200 ng/mg (corresponding to a mean amount of 219 ng/larva) after 168 h. Abnormal behaviors such as trembling and comatose larvae were observed even at the lowest concentration applied (> 0–20 ng/mg, 59 ng/larva). Mobility analysis showed impaired activity patterns, resulting in acute hypoactivity at all pesticide concentrations and time-delayed hyperactivity in larvae treated with > 40–60 ng/mg (100 ng/larva) and > 80–100 ng/mg (120 ng/larva), respectively. Even locomotion as a fundamental behavioral task was negatively influenced throughout larval development. In conclusion, our results demonstrate that flupyradifurone impacts life and survival of lacewing larvae and may pose—despite its status as bee-friendly—a major threat to insect fauna and environment.
Detecting continuous structural heterogeneity in single-molecule localization microscopy data
Authors: Haghparast Sobhan , Stallinga Sjoerd , Rieger Bernd 
Published: November 2023

AbstractFusion of multiple chemically identical complexes, so-called particles, in localization microscopy, can improve the signal-to-noise ratio and overcome under-labeling. To this end, structural homogeneity of the data must be assumed. Biological heterogeneity, however, could be present in the data originating from distinct conformational variations or (continuous) variations in particle shapes. We present a prior-knowledge-free method for detecting continuous structural variations with localization microscopy. Detecting this heterogeneity leads to more faithful fusions and reconstructions of the localization microscopy data as their heterogeneity is taken into account. In experimental datasets, we show the continuous variation of the height of DNA origami tetrahedrons imaged with 3D PAINT and of the radius of Nuclear Pore Complexes imaged in 2D with STORM. In simulation, we study the impact on the heterogeneity detection pipeline of Degree Of Labeling and of structural variations in the form of two independent modes.
Occurrence of tardigrades and morphometric and chemical conditions in rock pools by the Baltic Sea
Authors: Troell Sofia , Jönsson K. Ingemar 
Published: November 2023

AbstractRock pools are eroded depressions in bedrock providing temporary aquatic habitats with varying morphometric and chemical conditions. Tardigrades have adapted to many habitats with varying and extreme abiotic conditions, including desiccation, but their occurrence in rock pools have rarely been investigated. This study investigated the occurrence of tardigrades and the morphometric and chemical conditions in rock pools by the Baltic Sea in southeast Sweden. Samples of benthic material were collected from rock pools at three sites near the town Karlshamn together with measurements of pool size, pH, temperature, salinity, and dissolved oxygen of the water. Tardigrades occurred in about one fifth of the rock pools and included five eutardigrade genera. Also rotifers and nematodes were observed in the samples. The morphometric and chemical variables varied both within and among the three sites but with few differences between rock pools with or without tardigrades. However, rock pools with tardigrades tended to be overall shallower than pools without tardigrades, indicating that more desiccating-prone rock pools may be more favourable habitats for tardigrades. The study shows that tardigrades are part of the micro-invertebrate fauna in rock pools and this habitat deserves more investigations into the occurrence of this animal group.
Biostimulation of green microalgae Chlorella sorokiniana using nanoparticles of MgO, Ca10(PO4)6(OH)2, and ZnO for increasing biodiesel production
Authors: Faried Maryam , Khalifa Amany , Samer Mohamed , Attia Yasser A. , Moselhy Mohamed A. , El-Hussein Ahmed , Yousef Rania S. , Abdelbary Khaled , Abdelsalam Essam M. 
Published: November 2023

AbstractMicroalgae have the potential to become the primary source of biodiesel, catering to a wide range of essential applications such as transportation. This would allow for a significant reduction in dependence on conventional petroleum diesel. This study investigates the effect of biostimulation techniques utilizing nanoparticles of Magnesium oxide MgO, Calcium hydroxyapatite Ca10(PO4)6(OH)2, and Zinc oxide ZnO to enhance the biodiesel production of Chlorella sorokiniana. By enhancing cell activity, these nanoparticles have demonstrated the ability to improve oil production and subsequently increase biodiesel production. Experimentally, each nanomaterial was introduced at a concentration of 15 mg L−1. The results have shown that MgO nanoparticles yielded the highest biodiesel production, with a recorded yield of 61.5 mg L−1. Hydroxyapatite nanoparticles, on the other hand, facilitated lipid accumulation. ZnO nanoparticles showcased a multifaceted advantage by enhancing both growth and lipid content. Thus, it is suggested that these nanoparticles can be used effectively to increase the lipid content of microalgae. These findings highlight the potential of biostimulation strategies utilizing MgO, hydroxyapatite, and zinc oxide nanoparticles to bolster biodiesel production.
Targeting the Schistosoma mansoni nutritional mechanisms to design new antischistosomal compounds
Authors: Pavani Thaís F. A. , Cirino Maria E. , Teixeira Thainá R. , de Moraes Josué , Rando Daniela G. G. 
Published: November 2023

AbstractThe chemical classes of semicarbazones, thiosemicarbazones, and hydrazones are present in various compounds, each demonstrating diverse biological activities. Extensive studies have revealed their potential as schistosomicidal agents. Thiosemicarbazones, in particular, have shown inhibitory effects on Schistosoma mansoni's cathepsin B1 enzyme (SmCB1), which plays a crucial role in hemoglobin degradation within the worm's gut and its nutrition processes. Consequently, SmCB1 has emerged as a promising target for novel schistosomiasis therapies. Moreover, chloroquinoline exhibits characteristics in its aromatic structure that hold promise for developing SmCB1 inhibitors, along with its interaction with hemoglobin's heme group, potentially synergizing against the parasite's gut. In this context, we report the synthesis of 22 hybrid analogs combining hydrazones and quinolines, evaluated against S. mansoni. Five of these hybrids demonstrated schistosomicidal activity in vitro, with GPQF-8Q10 being the most effective, causing worm mortality within 24 h at a concentration of 25 µM. GPQF-8Q8 proved to be the most promising in vivo, significantly reducing egg presence in feces (by 52.8%) and immature eggs in intestines (by 45.8%). These compounds exhibited low cytotoxicity in Vero cells and an in in vivo animal model (Caenorhabditis elegans), indicating a favorable selectivity index. This suggests their potential for the development of new schistosomiasis therapies. Further studies are needed to uncover specific target mechanisms, but these findings offer a promising starting point.
Adaptive walking control for quadruped robot by using oscillation patterns
Authors: Zhang Yong , Qian Yijia , Ding Yi , Hou Beiping , Wang Rongyang 
Published: November 2023

AbstractTo improve the adaptability of quadruped robot in multiple scenarios, an adaptive locomotive system based on the double-layered central pattern generator (CPG) is proposed. The novel CPG network consists of double master units and subsets of slave units based on gyroscope signals including yaw and pitch angle. The response of master units provides the ability to control the 1st joins of quadruped robot, while slave units can generate the symmetry signals to control the 2nd and 3rd joints. The CPG network enables the seamless switching of locomotion gaits to stops and starts by using an ultrasonic sensor. Through adjusting the mutually dependent parameters, joints can generate the joint angles to achieve steering behavior. For adaptive movement on an irregular surface, stable ranges of the robot body yaw and pitch angles are proposed by using gyroscope signals. The experimental results verify that the quadruped robot with the proposed double-layered CPG network can perform stable trot pattern in a complex environment.
A computational approach to investigating facial attractiveness factors using geometric morphometric analysis and deep learning
Authors: Sano Takanori , Kawabata Hideaki 
Published: November 2023

AbstractNumerous studies discuss the features that constitute facial attractiveness. In recent years, computational research has received attention because it can examine facial features without relying on prior research hypotheses. This approach uses many face stimuli and models the relationship between physical facial features and attractiveness using methods such as geometric morphometrics and deep learning. However, studies using each method have been conducted independently and have technical and data-related limitations. It is also difficult to identify the factors of actual attractiveness perception using only computational methods. In this study, we examined morphometric features important for attractiveness perception through geometric morphometrics and impression evaluation. Furthermore, we used deep learning to analyze important facial features comprehensively. The results showed that eye-related areas are essential in determining attractiveness and that different racial groups contribute differently to the impact of shape and skin information on attractiveness. The approach used in this study will contribute toward understanding facial attractiveness features that are universal and diverse, extending psychological findings and engineering applications.