bluuebunny/crossref_metadata_2025_split huggingface dataset:
Exclusion of patients living with HIV from cancer immune checkpoint inhibitor trials
Authors: Vora Kruti B. , Ricciuti Biagio , Awad Mark M. 
Published: March 2021

AbstractEmerging retrospective and prospective studies indicate that immune checkpoint inhibitors (ICIs) can be safe and effective cancer treatments among people living with human immunodeficiency virus (PLWH), however this high-cancer-risk population has often been excluded from groundbreaking cancer ICI trials. Our study aimed to characterize the current rate of exclusion and conditional inclusion of PLWH in cancer ICI trials by tumor type, trial phase, and year. ClinicalTrials.gov cancer ICI trials with planned starts between 1/1/2019 and 10/20/2020 were identified. Based on trial eligibility criteria, trials were categorized as “excluded” if PLWH could not enroll, “conditionally included” if only PLWH with adequate immune function were allowed, or “included/not specified” if HIV was not mentioned in the eligibility criteria. Trials from 2014 were separately collected for comparison over time. The number of trials excluding PLWH were compared to the included/not specified group using Fisher’s exact test. Of 809 trials analyzed from 2019 to 2020, 74.4% excluded, 6.9% conditionally included, and 18.7% included/did not specify PLWH. Early phase trials excluded PLWH more frequently than late phase trials. The 2019–2020 trial cohort showed no significant change in exclusion of PLWH compared to 2014. Despite increasing evidence for safe and effective ICI use for PLWH, most cancer ICI trials exclude PLWH and few studies permit PLWH to participate, even if HIV is well-controlled.
Similar major cardiovascular outcomes between pure statin and ezetimibe-statin in comparable intensity for type 2 diabetes with extremely atherosclerotic risks
Authors: Kao Yu-Cheng , Chen Tien-Hsing , Liu Chi-Hung , Hwang Jawl-Shan , Hsiao Ching-Chung , Lin Yu-Sheng , Mao Chun-Tai , Hung Ming-Jui , Li Yan-Rong 
Published: March 2021

AbstractAtorvastatin 40 mg (ATOR 40) and ezetimibe 10 mg/simvastatin 20 mg (EZ-SIM 20) have similar reductions of low-density lipoprotein cholesterol (LDL-C) but cardiovascular (CV) outcomes between these two therapies are unclear. Our real-world cohort study is to test the hypothesis of pleiotropic effects of purely higher dose statin on CV outcomes beyond similar reductions of LDL-C, especially for extremely CV risk patients. Between January 1, 2007 and December 31, 2013, a total of 3,372 patients with type 2 diabetes mellitus (T2DM) admitted due to acute coronary syndrome (ACS) or acute ischemic stroke (AIS) were selected as the study cohort from the Taiwan National Health Insurance Research Database. Clinical outcomes were evaluated by ATOR 40 group (n = 1686) matched with EZ-SIM 20 group (n = 1686). Primary composite outcome includes CV death, non-fatal myocardial infarction, and non-fatal stroke. Secondary composite outcome includes hospitalization for unstable angina (HUA), percutaneous coronary intervention (PCI), and coronary artery bypass grafting (CABG). With a mean follow-up of 2.4 years, no significant difference of primary composite outcome was observed between ATOR 40 and EZ-SIM 20 groups (subdistribution hazard ratio [SHR], 1.09; 95% confidence interval [CI], 0.95–1.25). Nevertheless, ATOR 40 group had lower risks of HUA (SHR, 0.50; 95% CI, 0.35–0.72), PCI (SHR, 0.82; 95% CI, 0.69–0.97) and CABG (SHR, 0.62; 95% CI, 0.40–0.97) than EZ-SIM 20 group. For T2DM patients after ACS or AIS, ATOR 40 and EZ-SIM 20 had similar major CV outcomes, which still supported the main driver for CV risk reductions is LDL-C lowering.
Characterization of design grammar of peptides for regulating liquid droplets and aggregates of FUS
Authors: Kamagata Kiyoto , Chiba Rika , Kawahata Ichiro , Iwaki Nanako , Kanbayashi Saori , Maeda Kana , Takahashi Hiroto , Hirano Atsushi , Fukunaga Koji , Ikeda Keisuke , Kameda Tomoshi 
Published: March 2021

AbstractLiquid droplets of aggregation-prone proteins, which become hydrogels or form amyloid fibrils, are a potential target for drug discovery. In this study, we proposed an experiment-guided protocol for characterizing the design grammar of peptides that can regulate droplet formation and aggregation. The protocol essentially involves investigation of 19 amino acid additives and polymerization of the identified amino acids. As a proof of concept, we applied this protocol to fused in sarcoma (FUS). First, we evaluated 19 amino acid additives for an FUS solution and identified Arg and Tyr as suppressors of droplet formation. Molecular dynamics simulations suggested that the Arg additive interacts with specific residues of FUS, thereby inhibiting the cation–π and electrostatic interactions between the FUS molecules. Second, we observed that Arg polymers promote FUS droplet formation, unlike Arg monomers, by bridging the FUS molecules. Third, we found that the Arg additive suppressed solid aggregate formation of FUS, while Arg polymer enhanced it. Finally, we observed that amyloid-forming peptides induced the conversion of FUS droplets to solid aggregates of FUS. The developed protocol could be used for the primary design of peptides controlling liquid droplets and aggregates of proteins.
Different triggers for the two pulses of mass extinction across the Permian and Triassic boundary
Authors: Li Guoshan , Liao Wei , Li Sheng , Wang Yongbiao , Lai Zhongping 
Published: March 2021

AbstractWidespread ocean anoxia has been proposed to cause biotic mass extinction across the Permian–Triassic (P–Tr) boundary. However, its temporal dynamics during this crisis period are unclear. The Liangfengya section in the South China Block contains continuous marine sedimentary and fossil records. Two pulses of biotic extinction and two mass extinction horizons (MEH 1 & 2) near the P–Tr boundary were identified and defined based on lithology and fossils from the section. The data showed that the two pulses of extinction have different environmental triggers. The first pulse occurred during the latest Permian, characterized by disappearance of algae, large foraminifers, and fusulinids. Approaching the MEH 1, multiple layers of volcanic clay and yellowish micritic limestone occurred, suggesting intense volcanic eruptions and terrigenous influx. The second pulse occurred in the earliest Triassic, characterized by opportunist-dominated communities of low diversity and high abundance, and resulted in a structural marine ecosystem change. The oxygen deficiency inferred by pyrite framboid data is associated with biotic declines above the MEH 2, suggesting that the anoxia plays an important role.
Using deep learning to predict temporomandibular joint disc perforation based on magnetic resonance imaging
Authors: Kim Jae-Young , Kim Dongwook , Jeon Kug Jin , Kim Hwiyoung , Huh Jong-Ki 
Published: March 2021

AbstractThe goal of this study was to develop a deep learning-based algorithm to predict temporomandibular joint (TMJ) disc perforation based on the findings of magnetic resonance imaging (MRI) and to validate its performance through comparison with previously reported results. The study objects were obtained by reviewing medical records from January 2005 to June 2018. 299 joints from 289 patients were divided into perforated and non-perforated groups based on the existence of disc perforation confirmed during surgery. Experienced observers interpreted the TMJ MRI images to extract features. Data containing those features were applied to build and validate prediction models using random forest and multilayer perceptron (MLP) techniques, the latter using the Keras framework, a recent deep learning architecture. The area under the receiver operating characteristic (ROC) curve (AUC) was used to compare the performances of the models. MLP produced the best performance (AUC 0.940), followed by random forest (AUC 0.918) and disc shape alone (AUC 0.791). The MLP and random forest were also superior to previously reported results using MRI (AUC 0.808) and MRI-based nomogram (AUC 0.889). Implementing deep learning showed superior performance in predicting disc perforation in TMJ compared to conventional methods and previous reports.
Bio-multifunctional noncovalent porphyrin functionalized carbon-based nanocomposite
Authors: Rabiee Navid , Bagherzadeh Mojtaba , Ghadiri Amir Mohammad , Fatahi Yousef , Baheiraei Nafiseh , Safarkhani Moein , Aldhaher Abdullah , Dinarvand Rassoul 
Published: March 2021

AbstractHerein, in a one-pot method, the reduced graphene oxide layers with the assistance of multiwalled carbon nanotubes were decorated to provide a suitable space for the in situ growth of CoNi2S4, and the porphyrins were incorporated into the layers as well to increase the sensitivity of the prepared nanostructure. The prepared nanocomposite can establish π–π interactions between the genetic material and on the surface of porphyrin rings. Also, hydrogen bonds between genetic domains and the porphyrin’ nitrogen and the surface hydroxyl groups are probable. Furthermore, the potential donor–acceptor relationship between the d7 transition metal, cobalt, and the genetic material provides a suitable way to increase the interaction and gene loading , and transfections. The reason for this phenomenon was optimized to increase the EGFP by up to 17.9%. Furthermore, the sensing ability of the nanocomposite towards H2O2 was investigated. In this regard, the limit of detection of the H2O2 obtained 10 µM. Also, the in situ biosensing ability in the HEK-293 and PC12 cell lines was evaluated by the addition of PMA. The nanocomposite showed the ability to detect the released H2O2 after adding the minimum amount of 120 ng/mL of the PMA.
Suggestion for a new deterministic model coupled with machine learning techniques for landslide susceptibility mapping
Authors: Min Dae-Hong , Yoon Hyung-Koo 
Published: March 2021

AbstractDeterministic models have been widely applied in landslide risk assessment (LRA), but they have limitations in obtaining various geotechnical and hydraulic properties. The objective of this study is to suggest a new deterministic method based on machine learning (ML) algorithms. Eight crucial variables of LRA are selected with reference to expert opinions, and the output value is set to the safety factor derived by Mohr–Coulomb failure theory in infinite slope. Linear regression and a neural network based on ML are applied to find the best model between independent and dependent variables. To increase the reliability of linear regression and the neural network, the results of back propagation, including gradient descent, Levenberg–Marquardt (LM), and Bayesian regularization (BR) methods, are compared. An 1800-item dataset is constructed through measured data and artificial data by using a geostatistical technique, which can provide the information of an unknown area based on measured data. The results of linear regression and the neural network show that the special LM and BR back propagation methods demonstrate a high determination of coefficient. The important variables are also investigated though random forest (RF) to overcome the number of various input variables. Only four variables—shear strength, soil thickness, elastic modulus, and fine content—demonstrate a high reliability for LRA. The results show that it is possible to perform LRA with ML, and four variables are enough when it is difficult to obtain various variables.
Herb-target virtual screening and network pharmacology for prediction of molecular mechanism of Danggui Beimu Kushen Wan for prostate cancer
Authors: Li Hong , Hung Andrew , Yang Angela Wei Hong 
Published: March 2021

AbstractProstate cancer (PCa) is a cancer that occurs in the prostate with high morbidity and mortality. Danggui Beimu Kushen Wan (DBKW) is a classic formula for patients with difficult urination including PCa. This study aimed to investigate the molecular mechanisms of DBKW for PCa. We obtained DBKW compounds from our previous reviews. We identified potential targets for PCa from literature search, currently approved drugs and Open Targets database and filtered them by protein–protein interaction network analysis. We selected 26 targets to predict three cancer-related pathways. A total of 621 compounds were screened via molecular docking using PyRx and AutoDock Vina against 21 targets for PCa, producing 13041 docking results. The binding patterns and positions showed that a relatively small number of tight-binding compounds from DBKW were predicted to interact strongly and selectively with three targets. The top five high-binding-affinity compounds were selected to generate a network, indicating that compounds from all three herbs had high binding affinity against the 21 targets and may have potential biological activities with the targets. DBKW contains multi-targeting agents that could act on more than one pathway of PCa simultaneously. Further studies could focus on validating the computational results via experimental studies.
A meta-analysis on heart rate variability biofeedback and depressive symptoms
Authors: Pizzoli Silvia F. M. , Marzorati Chiara , Gatti Daniele , Monzani Dario , Mazzocco Ketti , Pravettoni Gabriella 
Published: March 2021

AbstractHeart rate variability biofeedback (HRVB) has been used for a number of years to treat depressive symptoms, a common mental health issue, which is often comorbid with other psychopathological and medical conditions. The aim of the present meta-analysis is to test whether and to what extent HRVB is effective in reducing depressive symptoms in adult patients. We conducted a literature search on Pubmed, ProQuest, Ovid PsycInfo, and Embase up to October 2020, and identified 721 studies. Fourteen studies were included in the meta-analysis. Three meta-regressions were also performed to further test whether publication year, the questionnaire used to assess depressive symptoms, or the interval of time between T0 and T1 moderated the effect of HRVB. Overall, we analysed 14 RCTs with a total of 794 participants. The random effect analysis yielded a medium mean effect size g = 0.38 [95% CI = 0.16, 0.60; 95% PI =  − 0.19, 0.96], z = 3.44, p = 0.0006. The total heterogeneity was significant, QT = 23.49, p = 0.03, I2 = 45%, which suggested a moderate variance among the included studies. The year of publication (χ2(1) = 4.08, p = 0.04) and the questionnaire used to assess symptoms (χ2(4) = 12.65, p = 0.01) significantly moderated the effect of the interventions and reduced heterogeneity. Overall, results showed that HRVB improves depressive symptoms in several psychophysiological conditions in adult samples and should be considered as a valid technique to increase psychological well-being.
OMN6 a novel bioengineered peptide for the treatment of multidrug resistant Gram negative bacteria
Authors: Mandel Shira , Michaeli Janna , Nur Noa , Erbetti Isabelle , Zazoun Jonathan , Ferrari Livia , Felici Antonio , Cohen-Kutner Moshe , Bachnoff Niv 
Published: March 2021

AbstractNew antimicrobial agents are urgently needed, especially to eliminate multidrug resistant Gram-negative bacteria that stand for most antibiotic-resistant threats. In the following study, we present superior properties of an engineered antimicrobial peptide, OMN6, a 40-amino acid cyclic peptide based on Cecropin A, that presents high efficacy against Gram-negative bacteria with a bactericidal mechanism of action. The target of OMN6 is assumed to be the bacterial membrane in contrast to small molecule-based agents which bind to a specific enzyme or bacterial site. Moreover, OMN6 mechanism of action is effective on Acinetobacter baumannii laboratory strains and clinical isolates, regardless of the bacteria genotype or resistance-phenotype, thus, is by orders-of-magnitude, less likely for mutation-driven development of resistance, recrudescence, or tolerance. OMN6 displays an increase in stability and a significant decrease in proteolytic degradation with full safety margin on erythrocytes and HEK293T cells. Taken together, these results strongly suggest that OMN6 is an efficient, stable, and non-toxic novel antimicrobial agent with the potential to become a therapy for humans.
Impact of high dietary cornstarch level on growth, antioxidant response, and immune status in GIFT tilapia Oreochromis niloticus
Authors: Han Haojun , Wang Zhen , Wang Jiting , Wang Tingting , Li Yang , Guan Dongyan , Sun Huiwen 
Published: March 2021

AbstractThis study was conducted to investigate the relationship between different cornstarch levels in tilapia diet and immune function. All test fish were fed with three cornstarch levels: low-cornstarch (0, LS), medium-cornstarch (18%, MS) and high-cornstarch (36%, HS) diets. Three hundred and sixty fish (initial mean body weight 31.73 ± 1.36 g) were randomly allocated into twelve water-circulated tanks, and thirty fish per tank. Compared with the low and medium cornstarch diets, the results of growth showed that the high cornstarch diet significantly decreased the FBW, WGR, and SGR, and increased the FCR of tilapia (P < 0.05). The high cornstarch diet significantly decreased the content of crude protein and increased the content of crude lipid in whole body composition (P < 0.05). Moreover, the VSI and CF in HS diet were significantly higher than those of LS diet (P < 0.05). The results of blood biochemical index exhibited that the HS diet significantly increased the content of blood glucose, and liver/muscle glycogen (P < 0.05). The results of antioxidant experiments demonstrated that the content of SOD and T-AOC in MS diet were significantly higher than those of HS diet (P < 0.05). Meanwhile, the content of MDA in MS diet was significantly lower than that of HS diet (P < 0.05). The results of immune index test showed that the lysozyme activities in the serum, liver, and gill, and the phagocytic activity and index in MS diet were significantly higher than those of HS diet (P < 0.05). The challenge assay results revealed that the mortality rate of HS diet was higher than those of LS and MS diets, but the difference was not significant (P > 0.05). In conclusion, the overall results suggested that the 36% cornstarch diet reduced not only the growth performance, but also body immunity. Under this experimental condition, GIFT tilapia could tolerate 18% cornstarch, but not 36% cornstarch.
On the impact of vessel wall stiffness on quantitative flow dynamics in a synthetic model of the thoracic aorta
Authors: Zimmermann Judith , Loecher Michael , Kolawole Fikunwa O. , Bäumler Kathrin , Gifford Kyle , Dual Seraina A. , Levenston Marc , Marsden Alison L. , Ennis Daniel B. 
Published: March 2021

AbstractAortic wall stiffening is a predictive marker for morbidity in hypertensive patients. Arterial pulse wave velocity (PWV) correlates with the level of stiffness and can be derived using non-invasive 4D-flow magnetic resonance imaging (MRI). The objectives of this study were twofold: to develop subject-specific thoracic aorta models embedded into an MRI-compatible flow circuit operating under controlled physiological conditions; and to evaluate how a range of aortic wall stiffness impacts 4D-flow-based quantification of hemodynamics, particularly PWV. Three aorta models were 3D-printed using a novel photopolymer material at two compliant and one nearly rigid stiffnesses and characterized via tensile testing. Luminal pressure and 4D-flow MRI data were acquired for each model and cross-sectional net flow, peak velocities, and PWV were measured. In addition, the confounding effect of temporal resolution on all metrics was evaluated. Stiffer models resulted in increased systolic pressures (112, 116, and 133 mmHg), variations in velocity patterns, and increased peak velocities, peak flow rate, and PWV (5.8–7.3 m/s). Lower temporal resolution (20 ms down to 62.5 ms per image frame) impacted estimates of peak velocity and PWV (7.31 down to 4.77 m/s). Using compliant aorta models is essential to produce realistic flow dynamics and conditions that recapitulated in vivo hemodynamics.
Modulation of optical absorption in m-Fe1−xRuxS2 and exploring stability in new m-RuS2
Authors: Joshi H. , Ram M. , Limbu N. , Rai D. P. , Thapa B. , Labar K. , Laref A. , Thapa R. K. , Shankar A. 
Published: March 2021

AbstractA first-principle computational method has been used to investigate the effects of Ru dopants on the electronic and optical absorption properties of marcasite FeS2. In addition, we have also revealed a new marcasite phase in RuS2, unlike most studied pyrite structures. The new phase has fulfilled all the necessary criteria of structural stability and its practical existence. The transition pressure of 8 GPa drives the structural change from pyrite to orthorhombic phase in RuS2. From the thermodynamical calculation, we have reported the stability of new-phase under various ranges of applied pressure and temperature. Further, from the results of phonon dispersion calculated at Zero Point Energy, pyrite structure exhibits ground state stability and the marcasite phase has all modes of frequencies positive. The newly proposed phase is a semiconductor with a band gap comparable to its pyrite counterpart but vary in optical absorption by around 106 cm−1. The various Ru doped structures have also shown similar optical absorption spectra in the same order of magnitude. We have used crystal field theory to explain high optical absorption which is due to the involvement of different electronic states in formation of electronic and optical band gaps. Lӧwdin charge analysis is used over the customarily Mulliken charges to predict 89% of covalence in the compound. Our results indicate the importance of new phase to enhance the efficiency of photovoltaic materials for practical applications.
Weighted gene co-expression network analysis identifies specific modules and hub genes related to coronary artery disease
Authors: Zheng Peng-Fei , Chen Lu-Zhu , Guan Yao-Zong , Liu Peng 
Published: March 2021

AbstractThis investigation seeks to dissect coronary artery disease molecular target candidates along with its underlying molecular mechanisms. Data on patients with CAD across three separate array data sets, GSE66360, GSE19339 and GSE97320 were extracted. The gene expression profiles were obtained by normalizing and removing the differences between the three data sets, and important modules linked to coronary heart disease were identified using weighted gene co-expression network analysis (WGCNA). Gene Ontology (GO) functional and Kyoto Encyclopedia of Genes and genomes (KEGG) pathway enrichment analyses were applied in order to identify statistically significant genetic modules with the Database for Annotation, Visualization and Integrated Discovery (DAVID) online tool (version 6.8;http://david.abcc.ncifcrf.gov). The online STRING tool was used to construct a protein–protein interaction (PPI) network, followed by the use of Molecular Complex Detection (MCODE) plug-ins in Cytoscape software to identify hub genes. Two significant modules (green-yellow and magenta) were identified in the CAD samples. Genes in the magenta module were noted to be involved in inflammatory and immune-related pathways, based on GO and KEGG enrichment analyses. After the MCODE analysis, two different MCODE complexes were identified in the magenta module, and four hub genes (ITGAM, degree = 39;CAMP, degree = 37;TYROBP, degree = 28;ICAM1, degree = 18) were uncovered to be critical players in mediating CAD. Independent verification data as well as our RT-qPCR results were highly consistent with the above finding.ITGAM,CAMP,TYROBPandICAM1are potential targets in CAD. The underlying mechanism may be related to the transendothelial migration of leukocytes and the immune response.