bluuebunny/crossref_metadata_2025_split huggingface dataset:
A dynamic Bayesian optimized active recommender system for
curiosity-driven partially “Human-in-the-loop” automated experiments
Authors: Biswas Arpan , Liu Yongtao , Creange Nicole , Liu Yu-Chen , Jesse Stephen , Yang Jan-Chi , Kalinin Sergei , Ziatdinov Maxim , Vasudevan Rama 
Published: July 2023

Abstract
Optimization of experimental materials synthesis and characterization through active learning methods has been growing over the last decade, with examples ranging from measurements of diffraction on combinatorial alloys at synchrotrons, to searches through chemical space with automated synthesis robots for perovskites. In virtually all cases, the target property of interest for optimization is defined apriori with the ability to shift the trajectory of the optimization based on human-identified findings during the experiment is lacking. Thus, to highlight the best of both human operators and AI-driven experiments, here we present the development of a new type of human-AI collaborated experimental workflow, via a Bayesian optimized active recommender system (BOARS), to shape targets on the fly with human real-time feedback. Here, the human guidance overpowers AI at early iteration when prior knowledge (uncertainty) is minimal (higher), while the AI overpowers the human during later iterations to accelerate the process with the human assessed goal. We showcase examples of this framework applied to pre-acquired piezoresponse force spectroscopy of a ferroelectric thin film, and in real time on an atomic force microscope, with human assessment to find symmetric hysteresis loops. It is found that such features appear more affected by subsurface defects than the local domain structure. This work shows the utility of human-AI approaches for curiosity-driven exploration of systems across experimental domains.
Inverse Dynamics and Energy Analyses of Wheelchair Locomotion in Subjects With Spinal Cord Injury: Differences Between Comfortable and Fast Speeds
Authors: Jaimes Kristy Alejandra Godoy , Duarte Marcos , Menegaldo Luciano Luporini 
Published: July 2023

Abstract
Manual wheelchair users are predisposed to overuse injuries resulting from repetitive movement. This study comprehensively evaluates kinematics, dynamics, and energy during manual wheelchair propulsion at two distinct speeds, utilizing OpenSim. Four participants with paraplegia were instructed to propel a wheelchair at self-selected comfortable and fast velocities. A SmartWheel device was used to measure hand reaction forces and propulsion torque. Kinematics was monitored using 18 reflective markers and two clusters, captured by a Motion Analysis system with 12 cameras. Joint angles and torque curves for rapid and comfortable conditions were compared employing Statistical Parametric Mapping (SPM). The average speed attained by the subjects for the comfortable and fast velocities were respectively 1.26 ± 0.18 m/s and 2.41 ± 0.32 m/s. The fast velocity necessitated a higher propulsive torque (7.91 vs. 26.17 Nm, p < 0.05), tangential (24.25 vs. 84.30 N, p < 0.05), and radial forces (28.62 vs. 63.58 N, p < 0.05) exerted on the wheel. Compared with slow, fast velocity average power input from the arm to the wheel (20.57 vs. 113.48 W, p < 0.05) and the average system’s power gain during the propulsion phase (20.30 vs. 114.88 W, p < 0.05) were larger. However, the mechanical efficiency, calculated as the ratio between the two powers, was similar.
6-gene machine learning-found signature for the differentiation of pancreatic ductal carcinoma and chronic pancreatitis patients on peripheral blood mononuclear cells RNA-Seq data
Authors: Carrillo-Perez Francisco , Caba Octavio , Jiménez-Luna Cristina , Ortuño Francisco , Castillo-Secilla Daniel , Herrera Luis Javier , Prados Jose , Rojas Ignacio 
Published: July 2023

Abstract

Background: Pancreatic ductal carcinoma (PDAC) has a poor prognosis given that it is usually found in a late stage. Finding a relevant and informative panel of biomarkers is crucial to diagnose the disease, and therefore, improving patient prognosis.In this work we explore the use of machine learning for finding a biologically relevant signature that can accurately differentiate between PDAC, chronic pancreatitis (CP), and control patients in peripheral blood mononuclear cells (PBMCs) RNA-Seq expression data.
Results: Patients data were collected from two different sources: extracellular vesicle long RNA (exLR) and PBMCs RNA-Seq data. The minimum Redundancy Maximum Relevance (mRMR) algorithm was used to find a significant gene signature and a support vector machine (SVM) was trained to classify the classes. We firstly leverage an important dataset of exLR samples using feature selection methodologies to find a 15-gene signature that accurately classifies the classes with an F1-Score of ≈ 80% in both the exLR and the PBMCs datasets. Furthermore, we select six genes from the 15-gene list that have significant biological relevance for PDAC description, and train a machine learning classifier that obtains an F1-Score of 71.0% in a Leave-One-Out CV validation.
Conclusion: We propose a relevant signature that can be used to accurately differentiate between the PDAC and CP in a non-invasive and cheap method, which can improve patient prognosis by providing an earlier diagnosis.
Assessing the impact of immersive virtual reality technology on the psychological recovery of patients with Parkinson’s disease depression: study protocol of a randomized controlled trial
Authors: Chen Xinyan , Chen Lina , Chen Xiaochun , Ye Qinyong , Cai Guoen , Zeng Yuqi 
Published: July 2023

Abstract
Background: Depression in Parkinson’s disease (DPD) has a high incidence rate in Parkinson's patients. It is common non-motor symptom of Parkinson's disease, which seriously affects patients’ quality of life. Thus, improving Parkinson's depression is important for improving patients’ quality of life. Psychotherapy for depression is limited for many reasons, and only a few patients are able to benefit. Many studies have proven that relaxation therapy, play, and exercise therapy are effective treatment for depression. VR has rapidly developed as a form of rehabilitation in recent years, due to its immersive characteristics and accessibility. Further, it has been applied to the psychological treatment of phobia and anxiety. However, there is no relevant research on the treatment of Parkinson's depression with VR, The aim of this study is to assess the effect of immersive VR-assisted training on DPD patients.
Methods: The study design is a single-blind randomized controlled trial. Seventy-four DPD patients will be recruited and chosen as subjects, then randomly allocated into two groups. The VR group (n=37) will accept VR-assisted training (40min) 3 times/week for 8 weeks. The non-VR training group (n= 37) will receive treatment as usual (TAU). The outcome measures will be measured before intervention, at 8 weeks, at 3 months, and at 6 months post-intervention. The primary outcomes will include Hamilton Depression Scale-24 (HAM-D24). The secondary outcomes will include the short-form 36 item health survey questionnaire (SF-36), neuroinflammation factors (BDNF, IL-6, CRP), and functional magnetic resonance imaging (fMRI).
Discussion: The traditional treatment of depression has limited resources and requires a lot of time and energy. It is not suitable for PD patients with mobility difficulties and in remote areas. VR is able to make up for limitations in traditional treatment methods. An advantage of VR is that it makes patients more invested in active participation. This study may provide an improved method for the clinical treatment of DPD patients, which is helpful for clinical decision-making and future practice.
Trial registration: The study has been registered in the Chinese Clinical Trial Registry ChiCTR2200065843, 16 November 2022.
The behavioural ecology of optimism: exploring potential consequences of judgement bias in mice
Authors: Bračić Marko , Bierbaum Louisa , Peng Maja , Nimalavachchlan Lavanja , Siewert Viktoria , Kaiser Sylvia , Sachser Norbert , Richter S. Helene 
Published: July 2023

Abstract
When confronted with ambiguous information, some individuals respond as expecting positive and others as expecting negative outcomes. Based on such decisions in ambiguous situations, a behavioural test was developed in animal welfare science that allows researchers to characterise animals as more “optimistic” or “pessimistic”. Recent studies using this judgement bias test detected consistent individual differences in “optimism levels”. However, the ecological and evolutionary relevance of these differences is not yet clear. In this proof-of-principle study with laboratory mice, we aimed to explore the potential ecological consequences of being more optimistic or pessimistic. Specifically, we investigated whether “optimists” make different foraging choices under predation risk than “pessimists”. To address this, we first characterised female mice (C57BL/6J) as more optimistic or pessimistic by using two established judgement bias tests. Then we assessed individual differences in the tendency to choose high-risk/high-reward or low-risk/low-reward conditions by using a newly developed test based on predator cues (rat odour). We show that this novel test is a suitable tool to investigate individual differences in ecologically relevant risk-taking: First, the test imposed a risk-foraging trade-off for mice because the risky condition clearly induced more avoidance and risk assessment. Second, individuals showed highly repeatable differences in their choice of the risky or safe option. Considering our main aim, we did not find evidence that optimistic and pessimistic mice make different foraging decisions under predation risk. A potential explanation is that optimists, although expecting positive outcomes, might not take more risks when it can jeopardise their survival.
A Broad-spectrum Gas Sensor based on Correlated Two-Dimensional Electron Gas
Authors: Liao Zhaoliang , Hong Yuhao , Wei Long , Zhang Qinghua , Deng Zhixiong , Liao Xiaxia , Zhou Yangbo , Wang Lei , Li Tongrui , Liu Junhua , Xiao Wen , Hu Shilin , Wang Lingfei , Li Lin , Huijben Mark , Chen Kai , Koster Gertjan , Rijnders Guus 
Published: July 2023

Abstract
Designing a broad-spectrum gas sensor capable of identifying gas components in complex environments, such as mixed atmospheres or extreme temperatures, is a significant concern for various technologies, including energy, geological science, and planetary exploration. The main challenge lies in finding materials that exhibit high chemical stability and wide working temperature range. Materials that amplify signals through non-chemical methods could open up new sensing avenues. Here, we present the discovery of a broad-spectrum gas sensor utilizing correlated two-dimensional gas (C-2DEG) at a delta-doped LaAlO3/SrTiO3 interface with LaFeO3. Our study revealed that a back-gating on this 2DEG can induce a non-volatile metal to insulator transition, which consequently can activate the 2DEG to sensitively and quantitatively probe very broad gas species, no matter whether these are polar, non-polar, or inert gases. Such C-2DEG sensor remains stable in almost any atmosphere within a wide temperature range, and its readout is a simple measurement of electric resistance change, thus providing a very low-cost and high-efficient sensing technique.
A molecular analysis of substituted phenylethylamines as potential microtubule targeting agents through in-vitro microtubule-polymerization activity
Authors: De Abreu Isadora Rocha , Barkdull Allison , Munoz James R. , Smith Robert P. , Craddock Travis J. A. 
Published: July 2023

AbstractNatural phenethylamines are trace amine neurotransmitters associated with dopamine transmission and related illnesses such Parkinson’s disease, and addiction. Synthetic phenethylamines can have psychoactive and hallucinogenic effects due to their high affinity with the 5-HT2Areceptor. Evidence indicates phenethylamines can directly alter the microtubule cytoskeleton being structurally similar to the microtubule destabilizing agent colchicine, however little work has been done on this interaction. As microtubules provide neuron structure, intracellular transport, and influence synaptic plasticity the interaction of phenethylamines with microtubules is important for understanding the potential harms, or potential pharmaceutical use of phenethylamines. We investigated 110 phenethylamines and their interaction with microtubules. Here we performed molecular docking of these compounds at the colchicine binding site and ranked them via binding energy. The top 10% of phenethylamines were further screened based on pharmacokinetic and physicochemical properties derived from SwissADME and LightBBB. Based on these properties 25B-NBF, 25C-NBF, and DMBMPP were tested in in-vitro microtubule polymerization assays showing that they alter microtubule polymerization dynamics in a dose dependent manner. As these compounds can rapidly cross the blood brain barrier and directly affect cytoskeletal dynamics, they have the potential to modulate cytoskeletal based neural plasticity. Further investigations into these mechanisms are warranted.
Novel Hyperchaotic Image Encryption Method Using Machine Learning-RBF
Authors: Zhou Shuang , Zhang Hongling , Zhang Yingqian , Zhang Hao 
Published: July 2023

Abstract

In this paper, we put forward a novel hyperchaotic image encryption method using machine learning-RBF. First, a new 4D continuous hyperchaotic system in light of the weak resistance of low-dimensional continuous chaotic systems to degradation is designed, which has a simpler structure, wider chaotic range, better distribution, and higher complexity compared with other chaotic systems based on Hopfield-type neural networks. Additionally, it has good randomness and is implemented on the hardware digital signal processing. Then, based on this system, we put forward a new image encryption method using machine learning-radial basis function (RBF) neural network and true random numbers. Results show that compared with some other algorithms, our method is more secure and withstand common attacks.
A systematic review of the drug-drug interaction between Statins and Quinolones
Authors: Zhou Jifang , Yu Lixia , Xu Huimin 
Published: July 2023

Abstract
Background
Statins are widely used in cardiovascular disease (CVD) as a common lipid-lowering drug, while quinolones are widely used for the treatment of infectious diseases. It is common to see CVD in combination with infectious diseases, therefore it is often the case that statins and quinolones are used in combination. Data suggest combinations of statin and quinolone may be associated with potentially life-threatening myopathy, rhabdomyolysis and acute hepatitis. This systematic review aims to characterize data regarding patients affected by the statin-quinolone interaction.
Methods
The purpose of this systematic review was to collect and evaluate the evidence surrounding statin-quinolone drug interactions and to discuss related risk mitigation strategies. The following databases were searched: PubMed (Medline), Embase, Scopus, and Cochrane Library. The systematic electronic literature search was conducted with the following search terms:"statins" AND "quinolones" AND "drug interactions".
Results
There were 16 case reports that met the criteria for qualitative analysis. Patients were involved in the following adverse reactions: rhabdomyolysis (n = 12), acute hepatitis (n = 1), muscle weakness (n = 1), hip tendinopathy (n = 1), or myopathy (n = 1). In the included literature, patients vary in the dose and type of statins they take, including simvastatin (n = 10) at a dose range of 20–80 mg/d and atorvastatin (n = 4) at a dose of 80 mg/d. There were 2 patients with unspecified statin doses, separately using simvastatin and atorvastatin. The quinolones in combination were ciprofloxacin (n = 9) at a dose range of 800–1500 mg/d, levofloxacin (n = 6) at a dose range of 250–1000 mg/d, and norfloxacin (n = 1) in an unspecified dose range. Eighty-one percent of the case patients were over 60 years of age, and about 1/3 had kidney-related diseases such as diabetic nephropathy, post-transplantation, and severe glomerulonephritis. Nearly two-third of the patients were on concomitant cytochrome P450 3A4 (CYP3A4) inhibitors, P-glycoprotein (P-gp) inhibitors, or organic anion transporting polypeptide 1B1 (OATP1B1) inhibitors.
Conclusion
Patients treated with statin-quinolone combination should be monitored more closely for changes in aspartate aminotransferase or creatine kinase (CK) levels, and muscle symptoms, especially in patients with ciprofloxacin or levofloxacin, with simvastatin and high-dose atorvastatin, over 60 years of age, with kidney-related diseases, and on concomitant CYP3A4 inhibitors.
Data navigation on the ENCODE Portal
Authors: Hitz Benjamin , Kagda Meenakshi , Lam Bonita , Litton Casey , Small Corinn , Sloan Cricket , Spragins Emma , Tanaka Forrest , Whaling Ian , Gabdank Idan , Youngworth Ingrid , Strattan J. Seth , Hilton Jason , Jou Jennifer , Au Jessica , Lee Jin-Wook , Andreeva Kalina , Graham Keenan , Lin Khine , Simison Matt , Jolanki Otto , Sud Paul , Assis Pedro , Adenekan Philip , Miyasato Stuart , Zhong Weiwei , Luo Yunhai , Myers Zachary , Cherry J. 
Published: July 2023

Abstract
Spanning two decades, the Encyclopaedia of DNA Elements (ENCODE) is a collaborative research project that aims to identify all the functional elements in the human and mouse genomes. To best serve the scientific community, all data generated by the consortium is shared through a web-portal (https://www.encodeproject.org/) with no access restrictions. The fourth and final phase of the project added a diverse set of new samples (including those associated with human disease), and a wide range of new assays aimed at detection, characterization and validation of functional genomic elements. The ENCODE data portal hosts results from over 23,000 functional genomics experiments, over 800 functional elements characterization experiments (including in vivo transgenic enhancer assays, reporter assays and CRISPR screens) along with over 60,000 results of computational and integrative analyses (including imputations, predictions and genome annotations). The ENCODE Data Coordination Center (DCC) is responsible for development and maintenance of the data portal, along with the implementation and utilisation of the ENCODE uniform processing pipelines to generate uniformly processed data. Here we report recent updates to the data portal. Specifically, we have completely redesigned the home page, improved search interface, added several new pages to highlight collections of biologically related data (deeply profiled cell lines, immune cells, Alzheimer’s Disease, RNA-Protein interactions, degron matrix and a matrix of experiments organised by human donors), added single-cell experiments, and enhanced the cart interface for visualisation and download of user-selected datasets. Along with this, we also provide a brief summary of data generated using the ENCODE uniform processing pipelines. Finally we have added extensive help pages, tutorials and documentation to assist researchers from a variety of backgrounds in exploring the universe of ENCODE data.
The Association between Normal Weight Obesity and Metabolic Syndrome in Older Korean Adults
Authors: Kim Jeonghyeon , Kang Seamon , Kang Hyunsik 
Published: July 2023

Abstract
Background: Body mass index (BMI) has its drawback in that it is unable to distinguish between the distribution and quantity of fat mass and lean mass. Normal weight obesity (NWO) refers to a special phenotype of having excessive body fat despite a normal BMI. This cross-sectional study examined the association between NWO and metabolic syndrome in older Korean adults aged ³65 years.
Methods: Data for the current study (612 men and 479 women) was obtained from the 2008-2011 Korea National Health and Nutrition Examination Survey. NWO was defined as a BMI between 18.5 and 24.9 kg/m2 and body fat of ³26.0% in men and body fat of ³36.0% in women. Metabolic syndrome was defined according to the revised National Cholesterol Education Program definition, with a modified waist circumference threshold of >90 cm for Korean men or >85 cm for Korean women.
Results: People with NWO had an increased risk for metabolic syndrome (odds ratio, OR=2.531, 95% confidence interval, CI=1.287~4.980, p=0.007 in men; OR=1.970, 95% CI=1.020~3.850, p=0.043 in women) compared to people with NWNO (OR=1). When all covariates, including age, sex, education, income, smoking, heavy alcohol intake, serum vitamin D, physical activity, and nutrient intake of carbohydrates, fats, and proteins, and fat-to-lean mass ratio, were controlled, however, the risk of NWO for metabolic syndrome was no longer significant in both genders.
Conclusions: The current findings suggest that older adults with NWO should be monitored in clinical settings for early intervention.
Analysis of UGT Gene Family and Functional Involvement in Drought and Salt Stress Tolerance in Phoebe bournei
Authors: Zhu Zhening , Zhang Yanzi , Li Jingshu , Yang Sijia , Pan Jinxi , Guan Hengfeng , Bakari Almas , Chen Shipin , Cao Shijiang 
Published: July 2023

Abstract
Background
Uridine diphosphate glycosyltransferases (UDP-GTs, UGTs), regulated by UGT genes, play a pivotal role in glycosylation, a prevalent compound modification pathway observed in plant secondary metabolism. Glycosylation is known to contribute significantly to hormone homeostasis, plant detoxification processes, and secondary metabolite production in plants. Despite extensive studies on the UGT gene family in numerous species, a comprehensive investigation of the UGT family in Phoebe bournei remains unreported. Thus, we conducted a systematic analysis to identify 156 PbUGT genes and provide a comprehensive examination of this family by investigating homology, conserved protein regions, gene structure, chromosomal location, and tissue-specific expression patterns.
Results
We identified 156 UGT genes within the entire P. bournei genome, all of which contained the PSPG box. The PbUGT family consists of 14 subfamilies, consistent with Arabidopsis thaliana. We observed varying expression levels of PbUGT genes across different tissues in P. bournei, with the following average expression hierarchy: leaf > stem xylem > stem bark > root xylem > root bark. Covariance analysis revealed stronger covariance between P. bournei and closely related species. Additionally, PbUGT genes exhibited differential expression under drought and salt stresses, with specific expression patterns observed under each stress condition.
Conclusions
Our findings shed light on the transcriptional response of PbUGT factors to drought and salt stresses, thereby establishing a foundation for future investigations into the role of PbUGT transcription factors.