bluuebunny/crossref_metadata_2025_split huggingface dataset:
Extreme drought along the tropic of cancer (Yunnan section) and its impact on vegetation
Authors: Zhang Yanke , Gu Tengfei , He Suling , Cheng Feng , Wang Jinliang , Ye Hui , Zhang Yunfeng , Su Huai , Li Qinglei 
Published: March 2024

AbstractThe frequent occurrence of extreme weather events is one of the future prospects of climate change, and how ecosystems respond to extreme drought is crucial for response to climate change. Taking the extreme drought event in the Tropic of Cancer (Yunnan section) during 2009–2010 as a case study, used the standardized precipitation evapotranspiration index to analyse the impact of extreme drought on enhanced vegetation index (EVI), leaf area index (LAI) and gross primary productivity (GPP), and to analyzed the post extreme drought vegetation recovery status. The results indicate the following: (1) Due to the cumulative effects of drought and vegetation phenology, vegetation growth in the months of March to May in 2010 was more severely affected. (2) Compared to EVI and LAI, GPP is more sensitive to drought and can accurately indicate areas where drought has impacted vegetation. (3) Following an extreme drought event, 70% of the vegetation can recover within 3 months, while 2.87–6.57% of the vegetation will remain unrecovered after 6 months. (4) Cropland and grassland show the strongest response, with longer recovery times, while woodland and shrubland exhibit weaker responses and shorter recovery times. This study provides a reference for the effects of extreme drought on vegetation.
Cooperative nucleic acid binding by Poly ADP-ribose polymerase 1
Authors: Melikishvili Manana , Fried Michael G. , Fondufe-Mittendorf Yvonne N. 
Published: March 2024

AbstractPoly (ADP)-ribose polymerase 1 (PARP1) is an abundant nuclear protein well-known for its role in DNA repair yet also participates in DNA replication, transcription, and co-transcriptional splicing, where DNA is undamaged. Thus, binding to undamaged regions in DNA and RNA is likely a part of PARP1’s normal repertoire. Here we describe analyses of PARP1 binding to two short single-stranded DNAs, a single-stranded RNA, and a double stranded DNA. The investigations involved comparing the wild-type (WT) full-length enzyme with mutants lacking the catalytic domain (∆CAT) or zinc fingers 1 and 2 (∆Zn1∆Zn2). All three protein types exhibited monomeric characteristics in solution and formed saturated 2:1 complexes with single-stranded T20 and U20 oligonucleotides. These complexes formed without accumulation of 1:1 intermediates, a pattern suggestive of positive binding cooperativity. The retention of binding activities by ∆CAT and ∆Zn1∆Zn2 enzymes suggests that neither the catalytic domain nor zinc fingers 1 and 2 are indispensable for cooperative binding. In contrast, when a double stranded 19mer DNA was tested, WT PARP1 formed a 4:1 complex while the ∆Zn1Zn2 mutant binding saturated at 1:1 stoichiometry. These deviations from the 2:1 pattern observed with T20 and U20 oligonucleotides show that PARP’s binding mechanism can be influenced by the secondary structure of the nucleic acid. Our studies show that PARP1:nucleic acid interactions are strongly dependent on the nucleic acid type and properties, perhaps reflecting PARP1’s ability to respond differently to different nucleic acid ligands in cells. These findings lay a platform for understanding how the functionally versatile PARP1 recognizes diverse oligonucleotides within the realms of chromatin and RNA biology.
Climate control on the channel morphodynamics of the Sittaung River, Myanmar
Authors: Bisson Luke Stefan , Choi Kyungsik 
Published: March 2024

AbstractThe spatio–temporal development of a meandering river is controlled by its channel morphodynamics. In regions of rapid channel evolution, understanding the driving factors of meander migration is crucial in forecasting the rate and extent of morphological change. Sediment supply and fluvial discharge are the primary influences on migration rate, however climate oscillations are also integral in indirectly regulating migration rate through their control of regional precipitation, as well as the monsoon season of sub-tropical Asia. Despite this, an in-depth investigation into the impact of climate oscillations on meander bend migration remains undocumented. This study presents a satellite-based analysis of multi-decadal climatic forcing on the migration rate of the Sittaung River in Myanmar, through interpretation of the El Niño Southern Oscillation (ENSO). The mode of ENSO exerts significant climatic control on the migration rate of the meandering channels of the Sittaung River, with low-to-average migration rates recorded during dry El Niño events and peak migration rates observed during wet La Niña events. However, this climatic signal may have been obscured by certain local environmental conditions. In cases where meanders faced geological basement, the basement rock inhibited their migration through extension, forcing more rapid migration by way of seaward translation. Consequently, these translating meanders developed to be more elongate, with lower curvatures. Meanders downstream of the approximate tidal limit were less downstream skewed, indicative of tidal modulation, potentially obscuring the impact of fluvially driven climate forcing. Additionally, downstream of a major confluence, the input of sediment and fluvial discharge may have been regulated by upstream anthropogenic activities such as mining and dam construction, leading to greater variability in migration rate downstream of this confluence and further obfuscation of the climate signal.
LC–MS/MS, GC–MS and molecular docking analysis for phytochemical fingerprint and bioactivity of Beta vulgaris L.
Authors: Üst Özge , Yalçin Emine , Çavuşoğlu Kültiğin , Özkan Burak 
Published: March 2024

AbstractThe plants that we consume in our daily diet and use as a risk preventer against many diseases have many biological and pharmacological activities. In this study, the phytochemical fingerprint and biological activities of Beta vulgaris L. leaf extract, which are widely consumed in the Black Sea region, were investigated. The leaf parts of the plant were dried in an oven at 35 °C and then ground into powder. The main constituents in B. vulgaris were identified by LC–MS/MS and GC–MS analyses. Phenolic content, betaxanthin and betacyanin levels were investigated in the extracts obtained using three different solvents. The biological activity of the extract was investigated by anti-microbial, anti-mutagenic, anti-proliferative and anti-diabetic activity tests. Anti-diabetic activity was investigated by in vitro enzyme inhibition and in-silico molecular docking was performed to confirm this activity. In the LC–MS analysis of B. vulgaris extract, a major proportion of p_coumaric acid, vannilin, protecatechuic aldehyde and sesamol were detected, while the major essential oils determined by GC–MS analysis were hexahydrofarnesyl acetone and phytol. Among the solvents used, the highest extraction efficiency of 2.4% was obtained in methanol extraction, and 36.2 mg of GAE/g phenolic substance, 5.1 mg/L betacyanin and 4.05 mg/L betaxanthin were determined in the methanol extract. Beta vulgaris, which exhibited broad-spectrum anti-microbial activity by forming a zone of inhibition against all tested bacteria, exhibited anti-mutagenic activity in the range of 35.9–61.8% against various chromosomal abnormalities. Beta vulgaris extract, which did not exhibit mutagenic, sub-lethal or lethal effects, exhibited anti-proliferative activity by reducing proliferation in Allium root tip cells by 21.7%. 50 mg/mL B. vulgaris extract caused 58.9% and 55.9% inhibition of α-amylase and α-glucosidase activity, respectively. The interactions of coumaric acid, vanniline, hexahydrofarnesyl acetone and phytol, which are major compounds in phytochemical content, with α-amylase and α-glucosidase were investigated by in silico molecular docking and interactions between molecules via various amino acids were determined. Binding energies between the tested compounds and α-amylase were obtained in the range of − 4.3 kcal/mol and − 6.1 kcal/mol, while for α-glucosidase it was obtained in the range of − 3.7 kcal/mol and − 5.7 kcal/mol. The biological activities of B. vulgaris are closely related to the active compounds it contains, and therefore studies investigating the phytochemical contents of plants are very important. Safe and non-toxic plant extracts can help reduce the risk of various diseases, such as diabetes, and serve as an alternative or complement to current pharmaceutical practices.
Artificial intelligence in neuro-oncology: advances and challenges in brain tumor diagnosis, prognosis, and precision treatment
Authors: Khalighi Sirvan , Reddy Kartik , Midya Abhishek , Pandav Krunal Balvantbhai , Madabhushi Anant , Abedalthagafi Malak 
Published: March 2024

AbstractThis review delves into the most recent advancements in applying artificial intelligence (AI) within neuro-oncology, specifically emphasizing work on gliomas, a class of brain tumors that represent a significant global health issue. AI has brought transformative innovations to brain tumor management, utilizing imaging, histopathological, and genomic tools for efficient detection, categorization, outcome prediction, and treatment planning. Assessing its influence across all facets of malignant brain tumor management- diagnosis, prognosis, and therapy- AI models outperform human evaluations in terms of accuracy and specificity. Their ability to discern molecular aspects from imaging may reduce reliance on invasive diagnostics and may accelerate the time to molecular diagnoses. The review covers AI techniques, from classical machine learning to deep learning, highlighting current applications and challenges. Promising directions for future research include multimodal data integration, generative AI, large medical language models, precise tumor delineation and characterization, and addressing racial and gender disparities. Adaptive personalized treatment strategies are also emphasized for optimizing clinical outcomes. Ethical, legal, and social implications are discussed, advocating for transparency and fairness in AI integration for neuro-oncology and providing a holistic understanding of its transformative impact on patient care.
Foundation metrics for evaluating effectiveness of healthcare conversations powered by generative AI
Authors: Abbasian Mahyar , Khatibi Elahe , Azimi Iman , Oniani David , Shakeri Hossein Abad Zahra , Thieme Alexander , Sriram Ram , Yang Zhongqi , Wang Yanshan , Lin Bryant , Gevaert Olivier , Li Li-Jia , Jain Ramesh , Rahmani Amir M. 
Published: March 2024

AbstractGenerative Artificial Intelligence is set to revolutionize healthcare delivery by transforming traditional patient care into a more personalized, efficient, and proactive process. Chatbots, serving as interactive conversational models, will probably drive this patient-centered transformation in healthcare. Through the provision of various services, including diagnosis, personalized lifestyle recommendations, dynamic scheduling of follow-ups, and mental health support, the objective is to substantially augment patient health outcomes, all the while mitigating the workload burden on healthcare providers. The life-critical nature of healthcare applications necessitates establishing a unified and comprehensive set of evaluation metrics for conversational models. Existing evaluation metrics proposed for various generic large language models (LLMs) demonstrate a lack of comprehension regarding medical and health concepts and their significance in promoting patients’ well-being. Moreover, these metrics neglect pivotal user-centered aspects, including trust-building, ethics, personalization, empathy, user comprehension, and emotional support. The purpose of this paper is to explore state-of-the-art LLM-based evaluation metrics that are specifically applicable to the assessment of interactive conversational models in healthcare. Subsequently, we present a comprehensive set of evaluation metrics designed to thoroughly assess the performance of healthcare chatbots from an end-user perspective. These metrics encompass an evaluation of language processing abilities, impact on real-world clinical tasks, and effectiveness in user-interactive conversations. Finally, we engage in a discussion concerning the challenges associated with defining and implementing these metrics, with particular emphasis on confounding factors such as the target audience, evaluation methods, and prompt techniques involved in the evaluation process.
A MOF-supported Pd1–Au1 dimer catalyses the semihydrogenation reaction of acetylene in ethylene with a nearly barrierless activation energy
Authors: Ballesteros-Soberanas Jordi , Martín Nuria , Bacic Matea , Tiburcio Estefanía , Mon Marta , Hernández-Garrido Juan Carlos , Marini Carlo , Boronat Mercedes , Ferrando-Soria Jesús , Armentano Donatella , Pardo Emilio , Leyva-Pérez Antonio 
Published: March 2024

AbstractThe removal of acetylene from ethylene streams is key in industry for manufacturing polyethylene. Here we show that a well-defined Pd1–Au1 dimer, anchored to the walls of a metal–organic framework (MOF), catalyses the selective semihydrogenation of acetylene to ethylene with ≥99.99% conversion (≤1 ppm of acetylene) and >90% selectivity in extremely rich ethylene streams (1% acetylene, 89% ethylene, 10% H2, simulated industrial front-end reaction conditions). The reaction proceeds with an apparent activation energy of ∼1 kcal mol–1, working even at 35 °C, and with operational windows (>100 °C) and weight hourly space velocities ($$66{,}000\,{\mathrm{ml}}\,{\mathrm{g}}^{-1}_{\mathrm{cat}}\,{\mathrm{h}}^{-1}$$

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) within industrial specifications. A combined experimental and computational mechanistic study shows the cooperativity between both atoms, and between atoms and support, to enable the barrierless semihydrogenation of acetylene.
Learning to stand with sensorimotor delays generalizes across directions and from hand to leg effectors
Authors: Rasman Brandon G. , Blouin Jean-Sébastien , Nasrabadi Amin M. , van Woerkom Remco , Frens Maarten A. , Forbes Patrick A. 
Published: March 2024

AbstractHumans receive sensory information from the past, requiring the brain to overcome delays to perform daily motor skills such as standing upright. Because delays vary throughout the body and change over a lifetime, it would be advantageous to generalize learned control policies of balancing with delays across contexts. However, not all forms of learning generalize. Here, we use a robotic simulator to impose delays into human balance. When delays are imposed in one direction of standing, participants are initially unstable but relearn to balance by reducing the variability of their motor actions and transfer balance improvements to untrained directions. Upon returning to normal standing, aftereffects from learning are observed as small oscillations in control, yet they do not destabilize balance. Remarkably, when participants train to balance with delays using their hand, learning transfers to standing with the legs. Our findings establish that humans use experience to broadly update their neural control to balance with delays.
Omics-based construction of regulatory variants can be applied to help decipher pig liver-related traits
Authors: Ling Ziqi , Li Jing , Jiang Tao , Zhang Zhen , Zhu Yaling , Zhou Zhimin , Yang Jiawen , Tong Xinkai , Yang Bin , Huang Lusheng 
Published: March 2024

AbstractGenetic variants can influence complex traits by altering gene expression through changes to regulatory elements. However, the genetic variants that affect the activity of regulatory elements in pigs are largely unknown, and the extent to which these variants influence gene expression and contribute to the understanding of complex phenotypes remains unclear. Here, we annotate 90,991 high-quality regulatory elements using acetylation of histone H3 on lysine 27 (H3K27ac) ChIP-seq of 292 pig livers. Combined with genome resequencing and RNA-seq data, we identify 28,425 H3K27ac quantitative trait loci (acQTLs) and 12,250 expression quantitative trait loci (eQTLs). Through the allelic imbalance analysis, we validate two causative acQTL variants in independent datasets. We observe substantial sharing of genetic controls between gene expression and H3K27ac, particularly within promoters. We infer that 46% of H3K27ac exhibit a concomitant rather than causative relationship with gene expression. By integrating GWAS, eQTLs, acQTLs, and transcription factor binding prediction, we further demonstrate their application, through metabolites dulcitol, phosphatidylcholine (PC) (16:0/16:0) and published phenotypes, in identifying likely causal variants and genes, and discovering sub-threshold GWAS loci. We provide insight into the relationship between regulatory elements and gene expression, and the genetic foundation for dissecting the molecular mechanism of phenotypes.
Origin of charge density wave in topological semimetals SrAl4 and EuAl4
Authors: Wang Lin-Lin , Nepal Niraj K. , Canfield Paul C. 
Published: March 2024

AbstractTopological semimetals in BaAl4-type structure show many interesting behaviors, such as charge density wave (CDW) in SrAl4 and EuAl4, but not the isostructural and isovalent BaAl4, SrGa4, and BaGa4. Here using Wannier functions based on density functional theory, we calculate the susceptibility functions with millions of k-points to reach the small q-vector and study the origin and driving force behind the CDW. Our comparative study reveals that the origin of the CDW in SrAl4 and EuAl4 is the strong electron-phonon coupling interaction for the transverse acoustic mode at small q-vector along the Γ-Z direction besides the maximum of the real part of the susceptibility function from the nested Fermi surfaces of the Dirac-like bands, which explains well the absence of CDW in the other closely related compounds in a good agreement with experiment. We also connect the different CDW behaviors in the Al compounds to the macroscopic elastic properties.
Noise-resilient single-pixel compressive sensing with single photon counting
Authors: Li Lili , Kumar Santosh , Sua Yong Meng , Huang Yu-Ping 
Published: March 2024

AbstractThe fast expansion of photon detection technology has fertilized the rapid growth of single-photon sensing and imaging techniques. While promising significant advantages over their classical counterparts, they suffer from ambient and quantum noises whose effects become more pronounced at low light levels, limiting the quality of the acquired signal. Here, we study how photon-counting noises degrade a single-pixel optical classifier via compressive sensing, and how its performance can be restored by using quantum parametric mode sorting. Using modified National Institute of Standards and Technology (MNIST) handwritten digits as an example, we examine the effects of detector dark counts and in-band background noises and demonstrate the effectiveness of mode filtering and upconversion detection in addressing those issues. We achieve 94% classification accuracy in the presence of 500 times stronger in-band noise than the signal received. Our results suggest a robust and efficient approach to single photon sensing in a practical environment, where sunlight, ambient, and multiscattering noises can easily dominate the weak signal.
Invalid SMILES are beneficial rather than detrimental to chemical language models
Authors: Skinnider Michael A. 
Published: March 2024

AbstractGenerative machine learning models have attracted intense interest for their ability to sample novel molecules with desired chemical or biological properties. Among these, language models trained on SMILES (Simplified Molecular-Input Line-Entry System) representations have been subject to the most extensive experimental validation and have been widely adopted. However, these models have what is perceived to be a major limitation: some fraction of the SMILES strings that they generate are invalid, meaning that they cannot be decoded to a chemical structure. This perceived shortcoming has motivated a remarkably broad spectrum of work designed to mitigate the generation of invalid SMILES or correct them post hoc. Here I provide causal evidence that the ability to produce invalid outputs is not harmful but is instead beneficial to chemical language models. I show that the generation of invalid outputs provides a self-corrective mechanism that filters low-likelihood samples from the language model output. Conversely, enforcing valid outputs produces structural biases in the generated molecules, impairing distribution learning and limiting generalization to unseen chemical space. Together, these results refute the prevailing assumption that invalid SMILES are a shortcoming of chemical language models and reframe them as a feature, not a bug.
Photosynthetic co‐culture system of algae and human umbilical vein endothelial cells: The effect on alleviating hypoxia and hypoxia/reoxygenation injury
Authors: Lin Donghu , Chen Yuanyuan , Tao Xinyu , Che Xin , Li Shiyu , Cheng Shiyu , Qu Shuxin 
Published: March 2024

AbstractIt is a developed photosynthetic co‐culture system to alleviate the hypoxia and hypoxia/reoxygenation (H/R)‐injured human umbilical vein endothelial cells (HUVECs). The algae, Chlorella vulgaris, were encapsulated to slow their growth while not affecting the photosynthetic oxygen‐producing capacity by Layer‐by‐layer (LbL) using gelatin and sodium alginate as the positive and negative charges materials, respectively. Then, the photosynthetic co‐culture system of HUVECs and self‐oxygenating alginate hydrogel (Algae‐gel) was constructed in which the optimal ratios between algae and HUVECs were 5:1 and 20:1 for a 2D or 3D co‐cultured manner, respectively. It indicated that the 3D co‐cultured manner of HUVECs needed more O2 by the production of algae than it did in a 2D co‐cultured manner. The co‐cultured Algae‐gel could alleviate hypoxia and the oxidative stress injury of hypoxia and hypoxia/reoxygenation (H/R)‐treated HUVECs in the proliferation, intracellular ROS and cellular migratory ability. In addition, the Algae‐gel could downregulate the expression of hypoxia‐inducible factors 1α (HIF‐1α) and vascular endothelial growth factor (VEGF) of hypoxia and H/R‐injured HUVECs due to the improvement of hypoxia and H/R injury. This photosynthetic co‐culture system could offer a promising approach for repairing hypoxia and H/R‐injured cells or tissue by providing safe and stable O2.
Mixed reality based teleoperation and visualization of surgical robotics
Authors: Ai Letian , Kazanzides Peter , Azimi Ehsan 
Published: March 2024

AbstractSurgical robotics has revolutionized the field of surgery, facilitating complex procedures in operating rooms. However, the current teleoperation systems often rely on bulky consoles, which limit the mobility of surgeons. This restriction reduces surgeons' awareness of the patient during procedures and narrows the range of implementation scenarios. To address these challenges, an alternative solution is proposed: a mixed reality‐based teleoperation system. This system leverages hand gestures, head motion tracking, and speech commands to enable the teleoperation of surgical robots. The implementation focuses on the da Vinci research kit (dVRK) and utilizes the capabilities of Microsoft HoloLens 2. The system's effectiveness is evaluated through camera navigation tasks and peg transfer tasks. The results indicate that, in comparison to manipulator‐based teleoperation, the system demonstrates comparable viability in endoscope teleoperation. However, it falls short in instrument teleoperation, highlighting the need for further improvements in hand gesture recognition and video display quality.