Miracle-dz/UniFAR-FTUs huggingface dataset:
High Visceral Adipose Tissue Density Correlates With Unfavorable Outcomes in Patients With Intermediate-Stage Hepatocellular Carcinoma Undergoing Transarterial Chemoembolization

Objectives: This study aimed to evaluate the association between different body composition features with prognostic outcomes of intermediate stage hepatocellular carcinoma (HCC) patients treated with transarterial chemoembolization (TACE). Methods: The areas and density of skeletal muscle area (SM) and adipose tissue [subcutaneous (SAT); visceral (VAT)] were calculated on the pre-TACE CT scans. Overall survival (OS) and progression-free survival (PFS) curves were calculated using the Kaplan–Meier method and compared with log-rank test. The discrimination and performance of body composition features were measured by area under time-dependent receiver operating characteristic (ROC) curve. Univariate and multivariate Cox proportional hazard analyses were applied to identify the association between body composition parameters and outcomes. Results: A significant prolonged OS and PFS was displayed by Kaplan–Meier curve analysis for HCC patients with VAT HU below −89.1 (25.1 months, 95% CI: 18.1–32.1 vs. 17.6 months, 95% CI: 16.3–18.8, p < 0.0001, 15.4 months, 95% CI: 10.6–20.2 vs. 6.6 months, 95% CI: 4.9–8.3, p < 0.0001, respectively). The 1-, 2-, 3-, and 5-year OS area under the curve (AUC) values of the VAT HU were higher than the other body composition parameters. Meanwhile, it is also found that 3-, 6-, 9-, and 12-month PFS AUC values of VAT HU were the highest among all the parameters. Univariate and multivariate Cox-regression analysis suggested a significant association between VAT density and outcomes (OS, HR: 1.015, 95% CI: 1.004–1.025, p = 0.005, PFS, HR: 1.026, 95% CI: 1.016–1.036, p < 0.0001, respectively). Conclusion: The VAT density could provide prognostic prediction value and may be helpful to stratify the intermediate stage HCC patients.
Mapping Visual Field Defects With fMRI – Impact of Approach and Experimental Conditions

Current initiatives to restore vision emphasize the need for objective assessments of visual field (VF) defects as pursued with functional magnetic resonance imaging (fMRI) approaches. Here, we compared population receptive field (pRF) mapping-based VF reconstructions to an fMRI method that uses more robust visual stimulation (on-off block design) in combination with individualized anatomy-driven retinotopic atlas-information (atlas-based VF). We investigated participants with sizable peripheral VF-deficits due to advanced glaucoma (n = 4) or retinitis pigmentosa (RP; n = 2) and controls (n = 6) with simulated scotoma. We obtained (1) standard automated perimetry (SAP) data as reference VFs and 3T fMRI data for (2) pRF-mapping [8-direction bar stimulus, fixation color change task] and (3) block-design full-field stimulation [8-direction drifting contrast patterns during (a) passive viewing (PV) and (b) one-back-task (OBT; reporting successions of identical motion directions) to probe the impact of previously reported task-related unspecific visual cortex activations]. Correspondence measures between the SAP and fMRI-based VFs were accuracy, assisted by sensitivity and specificity. We found an accuracy of pRF-based VF from V1 in patients [median: 0.62] that was similar to previous reports and increased by adding V2 and V3 to the analysis [0.74]. In comparison to the pRF-based VF, equivalent accuracies were obtained for the atlas-based VF for both PV [0.67] and, unexpectedly, the OBT [0.59], where, however, unspecific cortical activations were reflected by a reduction in sensitivity [0.71 (PV) and 0.35 (OBT)]. In conclusion, in patients with peripheral VF-defects, we demonstrate that previous fMRI procedures to obtain VF-estimates might be enhanced by: (1) pooling V1-V3 to enhance accuracy; (2) reporting sensitivity and specificity measures to increase transparency of the VF-reconstruction metric; (3) applying atlas-based procedures, if pRF-based VFs are not available or difficult to obtain; and (4) giving, counter-intuitively, preference to PV. These findings are expected to provide guidance to overcome current limitations of translating fMRI-based methods to a clinical work-up.
A Survey on Label-Efﬁcient Information Extraction with Natural Language Guidance

Natural language explanations (NLE), as additional information provided by the annotator, are informative and effortless (i.e. requiring only tripled annotation time since the annotator already knows the instance well). Recent work in relation extraction, common-sense QA and visual QA utilize these explanations and achieve competitive performances efficiently (i.e., with fewer labeling effort). One way to leverage NLE is to construct labeling rules from explanations, which help relieve annotation burden, while such method usually adopt hard matching and suffer from low coverage issue. The proposed work aims to further improve the efficiency by constructing a joint bootstrapping framework for both instances and rules, so that rule coverage in unlabeled corpora is further expanded. In this survey we discuss related work on natural language explanations and machine executable forms.
EcoDes-DK15: High-resolution ecological descriptors of vegetation and terrain derived from Denmark's national airborne laser scanning data set

Abstract. Biodiversity studies could strongly benefit from three-dimensional data on ecosystem structure derived from contemporary remote sensing technologies, such as Light Detection and Ranging (LiDAR). Despite the increasing availability of such data at regional and national scales, the average ecologist has been limited in accessing them due to high requirements on computing power and remote-sensing knowledge. We processed Denmark's publicly available national Airborne Laser Scanning (ALS) data set acquired in 2014/15 together with the accompanying elevation model to compute 70 rasterized descriptors of interest for ecological studies. With a grain size of 10 m, these data products provide a snapshot of high-resolution measures including vegetation height, structure and density, as well as topographic descriptors including elevation, aspect, slope and wetness across more than forty thousand square kilometres covering almost all of Denmark's terrestrial surface. The resulting data set is comparatively small (~ 87 GB, compressed 16.4 GB) and the raster data can be readily integrated into analytical workflows in software familiar to many ecologists (GIS software, R, Python). Source code and documentation for the processing workflow are openly available via a code repository, allowing for transfer to other ALS data sets, as well as modification or re-calculation of future instances of Denmark’s national ALS data set. We hope that our high-resolution ecological vegetation and terrain descriptors (EcoDes-DK15) will serve as an inspiration for the publication of further such data sets covering other countries and regions and that our rasterized data set will provide a baseline of the ecosystem structure for current and future studies of biodiversity, within Denmark and beyond.
Role of Chemical Structure of Support in Enhancing the Catalytic Activity of a Single Atom Catalyst Toward NRR: A Computational Study

Using the periodic density functional theory–based methodology, we propose a potential catalytic system for dinitrogen activation, viz., single metal atoms (Mo, Fe, and V) supported on graphene-based sheets. Graphene-based sheets show an excellent potential toward the anchoring of single atoms on them (Mo, Fe, and V) with adsorption energies ranging between 1.048 and 10.893 eV. Factors such as defects and BN doping are noted to enhance the adsorption energies of single metal atoms on the support. The adsorption of a dinitrogen molecule on metal atom–anchored graphene-based supports is seen to be highly favorable, ranging between 0.620 and 2.278 eV. The adsorption is driven through a direct hybridization between the d orbitals of the metal atom (Mo, Fe, and V) on the support and the p orbital of the molecular nitrogen. Noticeably, BN-doped graphene supporting a single metal atom (Mo, Fe, and V) activates the N2 molecule with a red shift in the N–N stretching frequency (1,597 cm−1 as compared to 2,330 cm−1 in the free N2 molecule). This red shift is corroborated by an increase in the N–N bond length (1.23 Å from 1.09 Å) and charge transfer to an N2 molecule from the catalyst.
Direct and Indirect Reduction of Cr(VI) by Fermentative Fe(III)-Reducing Cellulomonas sp. Strain Cellu-2a

Hexavalent chromium (Cr(VI)) is recognized to be carcinogenic and toxic and registered as a contaminant in many drinking water regulations. It occurs naturally and is also produced by industrial processes. The reduction of Cr(VI) to Cr(III) has been a central topic for chromium remediation since Cr(III) is less toxic and less mobile. In this study, fermentative Fe(III)-reducing bacterial strains (Cellu-2a, Cellu-5a, and Cellu-5b) were isolated from a groundwater sample and were phylogenetically related to species of Cellulomonas by 16S rRNA gene analysis. One selected strain, Cellu-2a showed its capacity of reduction of both soluble iron (ferric citrate) and solid iron (hydrous ferric oxide, HFO), as well as aqueous Cr(VI). The strain Cellu-2a was able to reduce 15 μM Cr(VI) directly with glucose or sucrose as a sole carbon source under the anaerobic condition and indirectly with one of the substrates and HFO in the same incubations. The heterogeneous reduction of Cr(VI) by the surface-associated reduced iron from HFO by Cellu-2a likely assisted the Cr(VI) reduction. Fermentative features such as large-scale cell growth may impose advantages on the application of bacterial Cr(VI) reduction over anaerobic respiratory reduction.
Identification of Emotion Using Electroencephalogram by Tunable Q-Factor Wavelet Transform and Binary Gray Wolf Optimization

Emotional brain-computer interface based on electroencephalogram (EEG) is a hot issue in the field of human-computer interaction, and is also an important part of the field of emotional computing. Among them, the recognition of EEG induced by emotion is a key problem. Firstly, the preprocessed EEG is decomposed by tunable-Q wavelet transform. Secondly, the sample entropy, second-order differential mean, normalized second-order differential mean, and Hjorth parameter (mobility and complexity) of each sub-band are extracted. Then, the binary gray wolf optimization algorithm is used to optimize the feature matrix. Finally, support vector machine is used to train the classifier. The five types of emotion signal samples of 32 subjects in the database for emotion analysis using physiological signal dataset is identified by the proposed algorithm. After 6-fold cross-validation, the maximum recognition accuracy is 90.48%, the sensitivity is 70.25%, the specificity is 82.01%, and the Kappa coefficient is 0.603. The results show that the proposed method has good performance indicators in the recognition of multiple types of EEG emotion signals, and has a better performance improvement compared with the traditional methods.
Genome-Wide Analysis of the HSP20 Gene Family and Expression Patterns of HSP20 Genes in Response to Abiotic Stresses in Cynodon transvaalensis

African bermudagrass (Cynodon transvaalensis Burtt–Davy) is an important warm-season turfgrass and forage grass species. Heat shock protein 20 (HSP20) is a diverse, ancient, and important protein family. To date, HSP20 genes have not been characterized genome-widely in African bermudagrass. Here, we confirmed 41 HSP20 genes in African bermudagrass genome. On the basis of the phylogenetic tree and cellular locations, the HSP20 proteins were classified into 12 subfamilies. Motif composition was consistent with the phylogeny. Moreover, we identified 15 pairs of paralogs containing nine pairs of tandem duplicates and six pairs of WGD/segmental duplicates of HSP20 genes. Unsurprisingly, the syntenic genes revealed that African bermudagrass had a closer evolutionary relationship with monocots (maize and rice) than dicots (Arabidopsis and soybean). The expression patterns of HSP20 genes were identified with the transcriptome data under abiotic stresses. According to the expression profiles, HSP20 genes could be clustered into three groups (Groups I, II, and III). Group I was the largest, and these genes were up-regulated in response to heat stress as expected. In Group II, one monocot-specific HSP20, CtHSP20-14 maintained higher expression levels under optimum temperature and low temperature, but not high temperature. Moreover, a pair of WGD/segmental duplicates CtHSP20-9 and CtHSP20-10 were among the most conserved HSP20s across different plant species, and they seemed to be positively selected in response to extreme temperatures during evolution. A total of 938 cis-elements were captured in the putative promoters of HSP20 genes. Almost half of the cis-elements were stress responsive, indicating that the expression pattern of HSP20 genes under abiotic stresses might be largely regulated by the cis-elements. Additionally, three-dimensional structure simulations and protein–protein interaction networks were incorporated to resolve the function mechanism of HSP20 proteins. In summary, the findings fulfilled the HSP20 family analysis and could provide useful information for further functional investigations of the specific HSP20s (e.g., CtHSP20-9, CtHSP20-10, and CtHSP20-14) in African bermudagrass.
Narratives are Persuasive Because They are Easier to Understand: Examining Processing Fluency as a Mechanism of Narrative Persuasion

Theory suggests that people are more persuaded by information presented within a narrative. We argue there is room for greater understanding about why this may be the case. Accordingly, we 1) examine whether narratives are indeed more persuasive than non-narratives and 2) evaluate two theoretical mechanisms that could be responsible for these effects. Results from a laboratory-based, preregistered experiment (N = 554) support our primary argument that narratives are processed more fluently (easily) than non-narratives, and when processing is eased, persuasion becomes more likely. This work offers a parsimonious and powerful explanation for the advantages of providing persuasive information within a narrative format and advances theory in narrative persuasion.
The Effects of Non-Directional Online Behavior on Students' Learning Performance: A User Profile Based Analysis Method

Network behavior analysis is an effective method to outline user requirements, and can extract user characteristics by constructing machine learning models. To protect the privacy of data, the shared information in the model is limited to non-directional network behavior information, such as online duration, traffic, etc., which also hides users’ unconscious needs and habits. However, the value density of this type of information is low, and it is still unclear how much student performance is affected by online behavior; in addition there is a lack of methods for analyzing the correlation between non-directed online behavior and academic performance. In this article, we propose a model for analyzing the correlation between non-directed surfing behavior and academic performance based on user portraits. Different from the existing research, we mainly focus on the public student behavior information in the campus network system and conduct in-depth research on it. The experimental results show that online time and online traffic are negatively correlated with academic performance, respectively, and student’s academic performance can be predicted through the study of non-directional online behavior.
Safety and efficacy of indocyanine green fluorescence imaging-guided radical gastrectomy: a systematic review and meta-analysis

ABSTRACT Background The clinical value of indocyanine green (ICG) in laparoscopic radical gastrectomy remains controversial. We performed this meta-analysis to investigate the safety and efficacy of ICG fluorescence imaging-guided radical gastrectomy. Methods All relevant studies published until 30 October 2020 were retrieved from several databases. Fixed- and random-effects models were used to analyze the results based on different heterogeneity levels. Data were expressed as odds ratios or weighted mean differences along with 95% confidence intervals. The Grading of Recommendations, Assessment, Development, and Evaluation system scale was used for quality of evidence evaluation. Results This meta-analysis included six cohort studies that investigated 622 patients. Compared with conventional radical gastrectomy, ICG fluorescence imaging-guided gastrectomy facilitates complete lymph node dissection, reduces intraoperative blood loss, and shortens the length of postoperative hospitalization. Moreover, we observed no significant intergroup differences in the operative time, first exhaust time, and postoperative complications. Conclusion ICG fluorescence imaging-guided radical gastrectomy scores over conventional gastrectomy and appears to be a promising approach in patients who require radical gastrectomy. However, further research is warranted to explore the potential long-term survival benefit of ICG fluorescence imaging in patients with gastric cancer.
Barriers to Help Seeking among Victims of Elder Abuse: A Scoping Review and Implications for Public Health Policy in Canada

Abstract Elder abuse is a serious public health concern requiring immediate intervention; however, the under-reporting of elder abuse by victims to formal and informal networks remains a major obstacle. This scoping review aims to identify barriers to help seeking that older adults experiencing abuse confront. The goal is to inform public policies and practices in the Canadian context and identify research gaps in the extant literature. Seven scholarly databases were searched from which 12 articles met the inclusion criteria and were extracted for analysis. The findings from this scoping review revealed three levels at which barriers exist: individual focused, abuser/family focused, and community/culture focused barriers. The results suggest that there are several complex obstacles that older adults face when contemplating disclosure of abuse. Future research into help seeking in the Canadian context should more readily incorporate the voices of elder abuse victim-survivors to develop effective assessment strategies and responsive service provisions.
Identification and epidemiological evaluation of gastric cancer risk factors: based on a field synopsis and meta-analysis in Chinese population

To summarize and assess the credibility and strength of non-genetic factors and genetic variation on gastric cancer risk, we performed a field synopsis and meta-analysis to identify the risk of gastric cancer in Chinese population. Cumulative evidence was graded according to the Venice criteria, and attributable risk percentage (ARP) and population attributable risk percentage (PARP) were used to evaluate the epidemiological effect. A total of 956 studies included non-genetic (404 studies) and genetic factors (552 studies) were quantified, and data on 1161 single nucleotide polymorphisms (SNPs) were available. We identified 14 non-genetic factors were significantly associated with gastric cancer risk. For the analysis of time trends, H. pylori infection rate in gastric cancer and population showed a downward trend. Meanwhile 22 variants were identified significantly associated with gastric cancer: 3 (PLCE1 rs2274223, PSCA rs2976392, MUC1 rs4072037) were high and 19 SNPs were intermediate level of summary evidence, respectively. For non-genetic factors, the top three for ARP were 54.75% (pickled food), 65.87% (stomach disease), and 49.75% (smoked and frying). For PARP were 34.22% (pickled food), 34.24% (edible hot food) and 23.66%(H. pylori infection). On the basis of ARP and PARP associated with SNPs of gastric cancer, the top three for ARP were 53.91% (NAT2, rs1799929),53.05% (NAT2 phenotype), and 42.85% (IL-10, rs1800896). For PARP (Chinese Han in Beijing) were 36.96% (VDR, rs731236), 25.58% (TGFBR2, rs3773651) and 20.56% (MUC1, rs4072037). Our study identified non-genetic risk factors and high-quality biomarkers of gastric cancer susceptibility and their contribution to gastric cancer.
Maxacalcitol Pharmacokinetic–Pharmacodynamic Modeling and Simulation for Secondary Hyperparathyroidism in Patients Receiving Maintenance Hemodialysis

Abstract Background Maxacalcitol was approved in Taiwan in 2018 as the first active vitamin D3 injection for secondary hyperparathyroidism (SHPT) in patients on maintenance hemodialysis. However, no data from any clinical study with maxacalcitol in Taiwanese patients is available. Objectives This analysis aimed to evaluate the profiles of parathyroid hormone (PTH) and calcium (Ca) concentrations in Taiwanese SHPT patients on hemodialysis and maxacalcitol. Methods We developed population pharmacokinetic (PK) and pharmacodynamic (PD) models using a modeling and simulation approach. The data for these analyses were obtained from two studies: a clinical pharmacology study in Japanese patients and an ethnic comparison study in healthy Japanese and -Taiwanese volunteers. We then conducted a simulation study with a PK-PD model comprising the PK and PD models developed here. Results Serum maxacalcitol concentration profile was modeled using a two-compartment model that took into consideration the distribution of concentrations below the lower limit of quantification. An ethnic difference in clearance was included in the PK model as a covariate. A PD model that used a PTH/Ca feedback loop best described the observed data. There were no significant differences in Ca or PTH concentrations between Taiwanese and Japanese based on the simulation results from our PK-PD model, even though maxacalcitol exposure was approximately 40% higher in Taiwanese than in Japanese. Conclusions On the basis of these population PK and PD analyses and the clinical study conducted in Japan, there is no clinically relevant difference between Taiwanese and Japanese in terms of serum Ca or PTH levels.
Long-Term Desynchronization by Coordinated Reset Stimulation in a Neural Network Model With Synaptic and Structural Plasticity

Several brain disorders are characterized by abnormal neuronal synchronization. To specifically counteract abnormal neuronal synchrony and, hence, related symptoms, coordinated reset (CR) stimulation was computationally developed. In principle, successive epochs of synchronizing and desynchronizing stimulation may reversibly move neural networks with plastic synapses back and forth between stable regimes with synchronized and desynchronized firing. Computationally derived predictions have been verified in pre-clinical and clinical studies, paving the way for novel therapies. However, as yet, computational models were not able to reproduce the clinically observed increase of desynchronizing effects of regularly administered CR stimulation intermingled by long stimulation-free epochs. We show that this clinically important phenomenon can be computationally reproduced by taking into account structural plasticity (SP), a mechanism that deletes or generates synapses in order to homeostatically adapt the firing rates of neurons to a set point-like target firing rate in the course of days to months. If we assume that CR stimulation favorably reduces the target firing rate of SP, the desynchronizing effects of CR stimulation increase after long stimulation-free epochs, in accordance with clinically observed phenomena. Our study highlights the pivotal role of stimulation- and dosing-induced modulation of homeostatic set points in therapeutic processes.