bluuebunny/crossref_metadata_2025_split huggingface dataset:
Impact of timing to initiate adjuvant therapy on survival of elderly glioblastoma patients using the SEER-Medicare and national cancer databases
Authors: Zhu Ping , Du Xianglin L. , Hwang Lu-yu , Lairson David , Li Ruosha , Esquenazi Yoshua , Zhu Jay-Jiguang 
Published: February 2023

AbstractThe optimal time to initiate adjuvant therapy (AT) in elderly patients with glioblastoma (GBM) remains unclear. We investigated the impact of timing to start AT on overall survival (OS) using two national-scale datasets covering elderly GBM populations in the United States. A total of 3159 and 8161 eligible elderly GBM patients were derived from the Surveillance, Epidemiology and End Results (SEER)—Medicare linked dataset (2004–2013) and the National Cancer Database (NCDB) (2004–2014), respectively. The intervals in days from the diagnosis to the initiation of AT were categorized based on two scenarios: Scenario I (quartiles), ≤ 15, 16–26, 27–37, and ≥ 38 days; Scenario II (median), < 27, and ≥ 27 days. The primary outcome was OS. We performed the Kaplan–Meier and Cox proportional hazards regression methods for survival analysis. A sensitivity analysis was performed using Propensity Score Matching (PSM) method to achieve well-balanced characteristics between early-timing and delayed-timing in Scenario II. Improved OS was observed among patients who underwent resection and initiated AT with either a modest delay (27–37 days) or a longer delay (≥ 38 days) compared to those who received AT immediately (≤ 15 days) from both the SEER-Medicare dataset [adjusted hazard ratio (aHR) 0.74, 95% CI 0.64–0.84, P < 0.001; and aHR 0.81, 95% CI 0.71–0.92, P = 0.002] and the NCDB (aHR 0.83, 95% CI 0.74–0.93, P = 0.001; and aHR 0.87, 95% CI 0.77–0.98, P = 0.017). The survival advantage is observed in delayed-timing group as well in Scenario II. For elderly patients who had biopsy only, improved OS was only detected in a longer delay (Scenario I: ≥ 38 days vs. ≤ 15 days) or the delayed-timing group (Scenario II: ≥ 27 days vs. < 27 days) in the NCDB while no survival difference was seen in SEER-Medicare population. For the best timing to start AT in elderly GBM patients, superior survivals were observed among those who had craniotomy and initiated AT with a modest (27–37 days) or longer delays (≥ 38 days) following diagnosis using both the SEER-Medicare and NCDB datasets (Scenario I). Such survival advantage was confirmed when categorizing delayed-timing vs. early-timing with the cut-off at 27 day in both datasets (Scenario II). The increased likelihood of receiving delayed AT (≥ 27 days) was significantly associated with tumor resection (STR/GTR), years of diagnosis after 2006, African American and Hispanics races, treatments at academic facilities, and being referred. There is no difference in timing of AT on survival among elderly GBM patients who had biopsy in the SEER-Medicare dataset. In conclusion, initiating AT with a modest delay (27–37 days) or a longer delay (≥ 38 days) after craniotomy may be the preferred timing in the elderly GBM population.
Horses discriminate human body odors between fear and joy contexts in a habituation-discrimination protocol
Authors: Jardat Plotine , Destrez Alexandra , Damon Fabrice , Menard--Peroy Zoé , Parias Céline , Barrière Philippe , Keller Matthieu , Calandreau Ludovic , Lansade Léa 
Published: February 2023

AbstractAnimals are widely believed to sense human emotions through smell. Chemoreception is the most primitive and ubiquitous sense, and brain regions responsible for processing smells are among the oldest structures in mammalian evolution. Thus, chemosignals might be involved in interspecies communication. The communication of emotions is essential for social interactions, but very few studies have clearly shown that animals can sense human emotions through smell. We used a habituation-discrimination protocol to test whether horses can discriminate between human odors produced while feeling fear vs. joy. Horses were presented with sweat odors of humans who reported feeling fear or joy while watching a horror movie or a comedy, respectively. A first odor was presented twice in successive trials (habituation), and then, the same odor and a novel odor were presented simultaneously (discrimination). The two odors were from the same human in the fear or joy condition; the experimenter and the observer were blinded to the condition. Horses sniffed the novel odor longer than the repeated odor, indicating they discriminated between human odors produced in fear and joy contexts. Moreover, differences in habituation speed and asymmetric nostril use according to odor suggest differences in the emotional processing of the two odors.
Radiogenomic classification for MGMT promoter methylation status using multi-omics fused feature space for least invasive diagnosis through mpMRI scans
Authors: Qureshi Shahzad Ahmad , Hussain Lal , Ibrar Usama , Alabdulkreem Eatedal , Nour Mohamed K. , Alqahtani Mohammed S. , Nafie Faisal Mohammed , Mohamed Abdullah , Mohammed Gouse Pasha , Duong Tim Q. 
Published: February 2023

AbstractAccurate radiogenomic classification of brain tumors is important to improve the standard of diagnosis, prognosis, and treatment planning for patients with glioblastoma. In this study, we propose a novel two-stage MGMT Promoter Methylation Prediction (MGMT-PMP) system that extracts latent features fused with radiomic features predicting the genetic subtype of glioblastoma. A novel fine-tuned deep learning architecture, namely Deep Learning Radiomic Feature Extraction (DLRFE) module, is proposed for latent feature extraction that fuses the quantitative knowledge to the spatial distribution and the size of tumorous structure through radiomic features: (GLCM, HOG, and LBP). The application of the novice rejection algorithm has been found significantly effective in selecting and isolating the negative training instances out of the original dataset. The fused feature vectors are then used for training and testing byk-NN and SVM classifiers. The 2021 RSNA Brain Tumor challenge dataset (BraTS-2021) consists of four structural mpMRIs, viz. fluid-attenuated inversion-recovery, T1-weighted, T1-weighted contrast enhancement, and T2-weighted. We evaluated the classification performance, for the very first time in published form, in terms of measures like accuracy, F1-score, and Matthews correlation coefficient. The Jackknife tenfold cross-validation was used for training and testing BraTS-2021 dataset validation. The highest classification performance is (96.84 ± 0.09)%, (96.08 ± 0.10)%, and (97.44 ± 0.14)% as accuracy, sensitivity, and specificity respectively to detect MGMT methylation status for patients suffering from glioblastoma. Deep learning feature extraction with radiogenomic features, fusing imaging phenotypes and molecular structure, using rejection algorithm has been found to perform outclass capable of detecting MGMT methylation status of glioblastoma patients. The approach relates the genomic variation with radiomic features forming a bridge between two areas of research that may prove useful for clinical treatment planning leading to better outcomes.
Movement characteristics impact decision-making and vice versa
Authors: Carsten Thomas , Fievez Fanny , Duque Julie 
Published: February 2023

AbstractPrevious studies suggest that humans are capable of coregulating the speed of decisions and movements if promoted by task incentives. It is unclear however whether such behavior is inherent to the process of translating decisional information into movements, beyond posing a valid strategy in some task contexts. Therefore, in a behavioral online study we imposed time constraints to either decision- or movement phases of a sensorimotor task, ensuring that coregulating decisions and movements was not promoted by task incentives. We found that participants indeed moved faster when fast decisions were promoted and decided faster when subsequent finger tapping movements had to be executed swiftly. These results were further supported by drift diffusion modelling and inspection of psychophysical kernels: Sensorimotor delays related to initiating the finger tapping sequence were shorter in fast-decision as compared to slow-decision blocks. Likewise, the decisional speed-accuracy tradeoff shifted in favor of faster decisions in fast-tapping as compared to slow-tapping blocks. These findings suggest that decisions not only impact movement characteristics, but that properties of movement impact the time taken to decide. We interpret these behavioral results in the context of embodied decision-making, whereby shared neural mechanisms may modulate decisions and movements in a joint fashion.
Short-term outcome of adrenal radiofrequency ablation of adrenal cysts: a single-center experience
Authors: Pak Shin Jeong , Lee Yu-mi , Kim Pyo Nyun , Kim Byung-Chang , Cho Jae Won , Kim Won Woong , Sung Tae-Yon , Chung Ki-wook , Hong Suck Joon 
Published: February 2023

AbstractPercutaneous thermal ablation is a minimally invasive treatment for liver, kidney, lung, bone, and thyroid tumors. This treatment also has been used to treat adrenal tumors in patients, but there is no evidence for the efficacy of thermal ablation of adrenal cysts. The present study was performed to analyze the experience of a single center with percutaneous radiofrequency ablation (RFA) of adrenal cysts and to evaluate its efficacy. The present study enrolled all patients who underwent percutaneous RFA for unilateral adrenal cysts from 2019 to 2021. All patients underwent USG-guided percutaneous aspiration of cystic fluid, followed by RFA. A total nine patients with adrenal cysts were included in this study. All of them underwent technically successful percutaneous RFA, with no immediate complication. Follow-up CT 3 months after RFA showed that six of the nine adrenal cysts showed good responses, with reductions in cyst volume ranging from 86.4 to 97.9%. One patient had poor response in the cyst size (volume reduction rate 11.2%). She underwent secondary RFA with resulting that the cyst volume reduced by 91.1%. After a median follow-up period of 17.2 months, eight patients showed no evidence of regrowth. The patient, who showed evidence of regrowth, declined any other treatment and has been under regular surveillance. None of the nine patients developed adrenal insufficiency during the follow-up period. In conclusion, percutaneous RFA is a safe and effective minimally invasive treatment for adrenal cysts, suggesting that percutaneous RFA may be a good alternative option in selected patients.
Spatio-temporal visualization and forecasting of $${\text {PM}}_{10}$$ in the Brazilian state of Minas Gerais
Authors: da Silva Kim Leone Souza , López-Gonzales Javier Linkolk , Turpo-Chaparro Josue E. , Tocto-Cano Esteban , Rodrigues Paulo Canas 
Published: February 2023

AbstractAir pollution due to air contamination by gases, liquids, and solid particles in suspension, is a great environmental and public health concern nowadays. An important type of air pollution is particulate matter with a diameter of 10 microns or less ($${\text {PM}}_{10}$$

PM
10

) because one of the determining factors that affect human health is the size of particles in the atmosphere due to the degree of permanence and penetration they have in the respiratory system. Therefore, it is extremely interesting to monitor and understand the behavior of $${\text {PM}}_{10}$$

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concentrations so that they do not exceed the established critical levels. In this work, we will study the $${\text {PM}}_{10}$$

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concentrations in all available monitoring stations in the Brazilian state of Minas Gerais. To better understand its behavior, we will provide a spatio-temporal visualization of the $${\text {PM}}_{10}$$

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10

concentrations. Besides the descriptive and visualization analysis, we consider six standard and advanced time series models that will be used to fit and forecast $${\text {PM}}_{10}$$

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10

concentrations, with application to three locations, one in Belo Horizonte, the Minas Gerais state capital, and the monitoring stations with the lowest and highest average $${\text {PM}}_{10}$$

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concentration levels.
Influence of aldo–keto reductase 1C3 polymorphisms in early-onset female psoriasis patients
Authors: Nojiri Yuka , Nakamura Motoki , Magara Tetsuya , Yamamoto Aya , Ikumi Kyoko , Nakamura Reiko , Nishida Emi , Haarmann-Stemmann Thomas , Morita Akimichi 
Published: February 2023

AbstractThe principal pathology of psoriasis is impaired skin barrier function, epidermal thickening, and granular layer loss. Exposure to extrinsic factors such as tobacco smoke and air pollutants is associated with the development of psoriasis. Aryl hydrocarbon receptors (AHRs) are activated by extrinsic factors associated with the development of psoriasis and act as transcriptional regulators. Expression of aldo–keto reductase (AKR) 1C3 in the epidermal spinous layer regulates epidermal keratinocyte differentiation via the AHR signaling pathway. We investigated whether single nucleotide polymorphisms (SNPs) in AKR1C3 are associated with the pathogenesis of psoriasis. The proportions of rs12529 G/C, C/C variants, and rs12387 A/A, A/G variants were twofold higher in Japanese psoriasis patients (n = 231) compared with a Japanese healthy cohort. The SNPs were significantly more common than the majority variants in female patients with disease onset ≤ 22 years of age. Patients with rs12529 G > C and rs12387 A > G SNPs exhibited significantly lower AKR1C3 expression and higher expression of late differentiation markers. In conclusion, AKR1C3 downregulation caused by rs12529 G > C and rs12387 A > G SNPs in the epidermis induces abnormal early differentiation of keratinocytes and skin barrier dysfunction, which may contribute to the genetic pathogenesis of psoriasis in young females.
Cross-platform normalization enables machine learning model training on microarray and RNA-seq data simultaneously
Authors: Foltz Steven M. , Greene Casey S. , Taroni Jaclyn N. 
Published: February 2023

AbstractLarge compendia of gene expression data have proven valuable for the discovery of novel biological relationships. Historically, most available RNA assays were run on microarray, while RNA-seq is now the platform of choice for many new experiments. The data structure and distributions between the platforms differ, making it challenging to combine them directly. Here we perform supervised and unsupervised machine learning evaluations to assess which existing normalization methods are best suited for combining microarray and RNA-seq data. We find that quantile and Training Distribution Matching normalization allow for supervised and unsupervised model training on microarray and RNA-seq data simultaneously. Nonparanormal normalization and z-scores are also appropriate for some applications, including pathway analysis with Pathway-Level Information Extractor (PLIER). We demonstrate that it is possible to perform effective cross-platform normalization using existing methods to combine microarray and RNA-seq data for machine learning applications.
Dissociation kinetics of small-molecule inhibitors in Escherichia coli is coupled to physiological state of cells
Authors: Le Dai , Akiyama Tatsuya , Weiss David , Kim Minsu 
Published: February 2023

AbstractBioactive small-molecule inhibitors represent a treasure chest for future drugs. In vitro high-throughput screening is a common approach to identify the small-molecule inhibitors that bind tightly to purified targets. Here, we investigate the inhibitor-target binding/unbinding kinetics in E. coli cells using a benzimidazole-derivative DNA inhibitor as a model system. We find that its unbinding rate is not constant but depends on cell growth rate. This dependence is mediated by the cellular activity, forming a feedback loop with the inhibitor’s activity. In accordance with this feedback, we find cell-to-cell heterogeneity in inhibitor-target interaction, leading to co-existence of two distinct subpopulations: actively growing cells that dissociate the inhibitors from the targets and non-growing cells that do not. We find similar heterogeneity for other clinical DNA inhibitors. Our studies reveal a mechanism that couples inhibitor-target kinetics to cell physiology and demonstrate the significant effect of this coupling on drug efficacy.
Atroposelective desymmetrization of 2-arylresorcinols via Tsuji-Trost allylation
Authors: Kim Sangji , Kim Aram , Lee Chanhee , Moon Junsoo , Hong Eun Jeong , Lee Duck-Hyung , Kwon Yongseok 
Published: February 2023

AbstractPalladium-catalyzed asymmetric allylic alkylation has proven to be a powerful method for the preparation of a wide variety of chiral molecules. However, the catalytic and atroposelective allylic alkylation is still rare and challenging, especially for biaryl substrates. Herein, we report the palladium-catalyzed desymmetric and atroposelective allylation, in which the palladium complex with a chiral phosphoramidite ligand enables desymmetrization of nucleophilic 2-arylresorcinols in a highly enantioselective manner. With the aid of the secondary kinetic resolution effect, a wide variety of substrates containing a hydroxymethyl group at the bottom aromatic ring are able to provideO-allylated products up to 98:2 er. Computational studies show an accessible quadrant of the allylpalladium complex and provide three plausible transition states with intra- or intermolecular hydrogen bonding. The energetically favorable transition state is in good agreement with the observed enantioselectivity and suggests that the catalytic reaction would proceed with an intramolecular hydrogen bond.
Energy and environmental impacts of shared autonomous vehicles under different pricing strategies
Authors: Zhong Shaopeng , Liu Ao , Jiang Yu , Hu Simon , Xiao Feng , Huang Hai-Jun , Song Yan 
Published: February 2023

AbstractThe introduction of vehicle automation, shared mobility, and vehicle electrification will bring about changes in urban transportation, land use, energy, and the environment. The accurate estimation of these effects is therefore essential for sustainable urban development. However, existing research on estimating the energy and environmental effects of shared autonomous electric vehicles generally ignores the interaction between land-use and transportation systems. This study, therefore, analyzes the long-term effects of shared autonomous vehicles (SAVs) from the perspective of land use and transportation integration. Different SAV pricing scenarios are also developed to explore the optimal pricing strategy for low carbon–oriented SAVs. Moreover, the study has further assessed the effect of vehicle electrification on vehicle emissions and energy consumption. The results have shown a nonlinear relationship between SAV fares and their transportation, land-use, energy, and environmental effects. Under an appropriate pricing strategy, SAV deployment could reduce PM2.5 emission and energy consumption by 56–64% and 53–61%, respectively. With the further introduction of vehicle electrification, these can rise to 76% and 74%.
Ice nucleation catalyzed by the photosynthesis enzyme RuBisCO and other abundant biomolecules
Authors: Alsante Alyssa N. , Thornton Daniel C. O. , Brooks Sarah D. 
Published: February 2023

AbstractAtmospheric aerosol and the cloud droplets and ice crystals that grow on them remain major sources of uncertainty in global climate models. A subset of aerosol, ice nucleating particles, catalyze the freezing of water droplets at temperatures warmer than −38 °C. Here we show that RuBisCO, one of the most abundant proteins in plants and phytoplankton, is one of the most efficient known immersion ice nucleating particles with a mean freezing temperature of −7.9 ± 0.3 °C. Further, we demonstrate RuBisCO is present in ambient continental aerosol where it can serve as an ice nucleating particle. Other biogenic molecules act as immersion ice nucleating particles, in the range of −19 to −26 °C. In addition, our results indicate heat denaturation is not a universal indicator of the proteinaceous origin of ice nucleating particles, suggesting current studies may fail to accurately quantify biological ice nucleating particle concentrations and their global importance.
Decentralized high‐resolution direction finding in partly calibrated arrays
Authors: Zhang Guangbin , Huang Tianyao , Chen Chengzeng , Liu Yimin , Wang Xiqin , Eldar Yonina C. 
Published: February 2023

AbstractThe problem of high‐resolution direction finding is considered using a distributed array network with array position errors, called partly calibrated array. These errors are common in practice, and significantly affect high angular resolution. Existing calibration methods rely on centralized data transmission, which requires all the measurements to be transmitted to a computation center. This centralized mode leads to communication bottlenecks and system inflexibility. Here, a decentralized mode is designed, where each sensor only communicates locally with their neighboring sensors. Based on this mode, a corresponding direction‐finding approach is proposed using sequential methods that process data one by one, which corresponds to the decentralized signal processing sensor by sensor. Simulations verify that the proposed method achieves decentralization with minor cost in estimation accuracy.
Classification of voltage sags causes in industrial power networks using multivariate time‐series
Authors: Veizaga Maria , Delpha Claude , Diallo Demba , Bercu Sophie , Bertin Ludovic 
Published: February 2023

AbstractVoltage sags are the most frequent and impactful disturbances in industrial power grids, leading to high financial losses for industrial clients. The identification of the cause and its relative location is crucial for the contractual relation between the energy provider and the industrial customers. This paper proposes a methodology to identify the origins of voltage sags based on instantaneous symmetrical components and dynamic time warping. Short‐Time Fourier and Fortescue transform are implemented in the pre‐processing step using the voltage and current waveforms. Then, a distance‐based classification strategy to identify the sources of voltage sags is used. It relies on a four‐dimension time‐series signature used as features. Moreover, a confidence index associated with the classification output is provided. The proposal offers an easy implementation in industrial applications with no previous recorded data. It has the benefit of using a reduced‐size reference database entirely composed of synthetic data. The main advantages of the proposed method are its generalization capabilities and the possibility of raising an alert based on the confidence index. The obtained classification accuracy on synthetic data with seven causes is 100%. The method reaches a classification F1‐score higher than 99% with field measurements representing five classes obtained from three different industrial sites.