bluuebunny/crossref_metadata_2025_split huggingface dataset:
Recursive integration of synergised graph representations of multi-omics data for cancer subtypes identification
Authors: Madhumita  , Dwivedi Archit , Paul Sushmita 
Published: September 2022

AbstractCancer subtypes identification is one of the critical steps toward advancing personalized anti-cancerous therapies. Accumulation of a massive amount of multi-platform omics data measured across the same set of samples provides an opportunity to look into this deadly disease from several views simultaneously. Few integrative clustering approaches are developed to capture shared information from all the views to identify cancer subtypes. However, they have certain limitations. The challenge here is identifying the most relevant feature space from each omic view and systematically integrating them. Both the steps should lead toward a global clustering solution with biological significance. In this respect, a novel multi-omics clustering algorithm named RISynG (Recursive Integration of Synergised Graph-representations) is presented in this study. RISynG represents each omic view as two representation matrices that are Gramian and Laplacian. A parameterised combination function is defined to obtain a synergy matrix from these representation matrices. Then a recursive multi-kernel approach is applied to integrate the most relevant, shared, and complementary information captured via the respective synergy matrices. At last, clustering is applied to the integrated subspace. RISynG is benchmarked on five multi-omics cancer datasets taken from The Cancer Genome Atlas. The experimental results demonstrate RISynG’s efficiency over the other approaches in this domain.
A theory-based model of cumulative activity
Authors: Phillips Kole , Stanley Kevin , Fuller Daniel 
Published: September 2022

AbstractEnergy expenditure can be used to examine the health of individuals and the impact of environmental factors on physical activity. One of the more common ways to quantify energy expenditure is to process accelerometer data into some unit of measurement for this expenditure, such as Actigraph activity counts, and bin those measures into physical activity levels. However, accepted thresholds can vary between demographics, and some units of energy measurements do not currently have agreed upon thresholds. We present an approach which computes unique thresholds for each individual, using piecewise exponential functions to model the characteristics of their overall physical activity patterns corresponding to well established sedentary, light, moderate and vigorous activity levels from the literature. Models are fit using existing piecewise fitting techniques and software. Most participants’ activity intensity profile is exceptionally well modeled as piecewise exponential decay. Using this model, we find emergent groupings of participant behavior and categorize individuals into non-vigorous, consistent, moderately active, or extremely active activity intensity profiles. In the supplemental materials, we demonstrate that the parameters of the model correlate with demographics of age, household size, and level of education, inform behavior change under COVID lockdown, and are reasonably robust to signal frequency.
Determination of reference genes as a quantitative standard for gene expression analysis in mouse mesangial cells stimulated with TGF-β
Authors: dos Santos Bronel Bruno Aristides , Anauate Ana Carolina , Maquigussa Edgar , Boim Mirian Aparecida , da Silva Novaes Antônio 
Published: September 2022

AbstractReverse transcription-quantitative polymerase chain reaction (RT-PCR) is the gold standard technique for gene expression analysis, but the choice of quantitative reference genes (housekeeping genes, HKG) remains challenging. Identify the best HKG is essential for estimating the expression level of target genes. Therefore, the aim of this study was to determine the best HKG for an in vitro model with mouse mesangial cells (MMCs) stimulated with 5 ng/mL of TGF-β. Five candidates HKG were selected: Actb, Hprt, Gapdh, 18S and Ppia. After quantitative expression, the best combination of these genes was analyzed in silico using six software programs. To validate the results, the best genes were used to normalize the expression levels of fibronectin, vimentin and α-SMA. In silico analysis revealed that Ppia, Gapdh and 18S were the most stable genes between the groups. GenEX software and Spearman's correlation determined Ppia and Gapdh as the best HKG pair, and validation of the HKG by normalizing fibronectin, vimentin and α-SMA were consistent with results from the literature. Our results established the combination of Ppia and Gapdh as the best HKG pair for gene expression analysis by RT-PCR in this in vitro model using MMCs treated with TGF-β.
Regulation of human cortical interneuron development by the chromatin remodeling protein CHD2
Authors: Lewis E. M. A. , Chapman G. , Kaushik K. , Determan J. , Antony I. , Meganathan K. , Narasimhan M. , Gontarz P. , Zhang B. , Kroll K. L. 
Published: September 2022

AbstractMutations in the chromodomain helicase DNA binding protein 2 (CHD2) gene are associated with neurodevelopmental disorders. However, mechanisms by which CHD2 regulates human brain development remain largely uncharacterized. Here, we used a human embryonic stem cell model of cortical interneuron (hcIN) development to elucidate its roles in this process. We identified genome-wide CHD2 binding profiles during hcIN differentiation, defining direct CHD2 targets related to neurogenesis in hcIN progenitors and to neuronal function in hcINs. CHD2 bound sites were frequently coenriched with histone H3 lysine 27 acetylation (H3K27ac) and associated with high gene expression, indicating roles for CHD2 in promoting gene expression during hcIN development. Binding sites for different classes of transcription factors were enriched at CHD2 bound regions during differentiation, suggesting transcription factors that may cooperatively regulate stage-specific gene expression with CHD2. We also demonstrated that CHD2 haploinsufficiency altered CHD2 and H3K27ac coenrichment on chromatin and expression of associated genes, decreasing acetylation and expression of cell cycle genes while increasing acetylation and expression of neuronal genes, to cause precocious differentiation. Together, these data describe CHD2 direct targets and mechanisms by which CHD2 prevents precocious hcIN differentiation, which are likely to be disrupted by pathogenic CHD2 mutation to cause neurodevelopmental disorders.
Antigenic drift and epidemiological severity of seasonal influenza in Canada
Authors: Chen Zishu , Bancej Christina , Lee Liza , Champredon David 
Published: September 2022

AbstractSeasonal influenza epidemics circulate globally every year with varying levels of severity. One of the major drivers of this seasonal variation is thought to be the antigenic drift of influenza viruses, resulting from the accumulation of mutations in viral surface proteins. In this study, we aimed to investigate the association between the genetic drift of seasonal influenza viruses (A/H1N1, A/H3N2 and B) and the epidemiological severity of seasonal epidemics within a Canadian context. We obtained hemagglutinin protein sequences collected in Canada between the 2006/2007 and 2019/2020 flu seasons from GISAID and calculated Hamming distances in a sequence-based approach to estimating inter-seasonal antigenic differences. We also gathered epidemiological data on cases, hospitalizations and deaths from national surveillance systems and other official sources, as well as vaccine effectiveness estimates to address potential effect modification. These aggregate measures of disease severity were integrated into a single seasonal severity index. We performed linear regressions of our severity index with respect to the inter-seasonal antigenic distances, controlling for vaccine effectiveness. We did not find any evidence of a statistical relationship between antigenic distance and seasonal influenza severity in Canada. Future studies may need to account for additional factors, such as co-circulation of other respiratory pathogens, population imprinting, cohort effects and environmental parameters, which may drive seasonal influenza severity.
Fisher discriminant model based on LASSO logistic regression for computed tomography imaging diagnosis of pelvic rhabdomyosarcoma in children
Authors: Tian Lu , Li Xiaomeng , Zheng Helin , Wang Longlun , Qin Yong , Cai Jinhua 
Published: September 2022

AbstractComputed tomography (CT) has been widely used for the diagnosis of pelvic rhabdomyosarcoma (RMS) in children. However, it is difficult to differentiate pelvic RMS from other pelvic malignancies. This study aimed to analyze and select CT features by using least absolute shrinkage and selection operator (LASSO) logistic regression and established a Fisher discriminant analysis (FDA) model for the quantitative diagnosis of pediatric pelvic RMS. A total of 121 pediatric patients who were diagnosed with pelvic neoplasms were included in this study. The patients were assigned to an RMS group (n = 36) and a non-RMS group (n = 85) according to the pathological results. LASSO logistic regression was used to select characteristic features, and an FDA model was constructed for quantitative diagnosis. Leave-one-out cross-validation and receiver operating characteristic (ROC) curve analysis were used to evaluate the diagnostic ability of the FDA model. Six characteristic variables were selected by LASSO logistic regression, all of which were CT morphological features. Using these CT features, the following diagnostic models were established: (RMS group)$${G}_{1}=-14.283+6.613{x}_{1}+5.333{x}_{2}+5.753{x}_{3}+12.361{x}_{4}+8.095{x}_{5}-0.715{x}_{6}$$

G
1

=
-
14.283
+
6.613

x
1

+
5.333

x
2

+
5.753

x
3

+
12.361

x
4

+
8.095

x
5

-
0.715

x
6

; (Non-RMS group)$${G}_{2}=-2.008+3.539{x}_{1}+1.080{x}_{2}+1.154{x}_{3}+2.307{x}_{4}+1.656{x}_{5}+1.380{x}_{6}$$

G
2

=
-
2.008
+
3.539

x
1

+
1.080

x
2

+
1.154

x
3

+
2.307

x
4

+
1.656

x
5

+
1.380

x
6

, where $${x}_{1}$$

x
1

, $${x}_{2}$$

x
2

, … and $${x}_{6}$$

x
6

are lower than normal muscle density (1 = yes; 0 = no), multinodular fusion (1 = yes; 0 = no), enhancement at surrounding blood vessels (1 = yes; 0 = no), heterogeneous progressive centripetal enhancement (1 = yes; 0 = no), ring enhancement (1 = yes; 0 = no), and hemorrhage (1 = yes; 0 = no), respectively. The calculated area under the ROC curve (AUC) of the model was 0.992 (0.982–1.000), with a sensitivity of 94.4%, a specificity of 96.5%, and an accuracy of 95.9%. The calculated sensitivity, specificity and accuracy values were consistent with those from cross-validation. An FDA model based on the CT morphological features of pelvic RMS was established and could provide an easy and efficient method for the diagnosis and differential diagnosis of pelvic RMS in children.
Latent class analysis of behavior across dog breeds reveal underlying temperament profiles
Authors: Zapata Isain , Eyre Alexander W. , Alvarez Carlos E. , Serpell James A. 
Published: September 2022

AbstractLatent class analysis (LCA) is a type of modeling analysis approach that has been used to identify unobserved groups or subgroups within multivariate categorical data. LCA has been used for a wide array of psychological evaluations in humans, including the identification of depression subtypes or PTSD comorbidity patterns. However, it has never been used for the assessment of animal behavior. Our objective here is to identify behavioral profile-types of dogs using LCA. The LCA was performed on a C-BARQ behavioral questionnaire dataset from 57,454 participants representing over 350 pure breeds and mixed breed dogs. Two, three, and four class LCA models were developed using C-BARQ trait scores and environmental covariates. In our study, LCA is shown as an effective and flexible tool to classify behavioral assessments. By evaluating the traits that carry the strongest relevance, it was possible to define the basis of these grouping differences. Groupings can be ranked and used as levels for simplified comparisons of complex constructs, such as temperament, that could be further exploited in downstream applications such as genomic association analyses. We propose this approach will facilitate dissection of physiological and environmental factors associated with psychopathology in dogs, humans, and mammals in general.
Evaluation of animal and plant diversity suggests Greenland’s thaw hastens the biodiversity crisis
Authors: Ureta Carolina , Ramírez-Barahona Santiago , Calderón-Bustamante Óscar , Cruz-Santiago Pedro , Gay-García Carlos , Swingedouw Didier , Defrance Dimitri , Cuervo-Robayo Angela P. 
Published: September 2022

AbstractRising temperatures can lead to the occurrence of a large-scale climatic event, such as the melting of Greenland ice sheet, weakening the AMOC and further increasing dissimilarities between current and future climate. The impacts of such an event are still poorly assessed. Here, we evaluate those impacts across megadiverse countries on 21,146 species of tetrapods and vascular plants using the pessimistic climate change scenario (RCP 8.5) and four different scenarios of Greenland’s ice sheet melting. We show that RCP 8.5 emission scenario would lead to a widespread reduction in species’ geographic ranges (28–48%), which is projected to be magnified (58–99%) with any added contribution from the melting of Greenland. Also, declines in the potential geographical extent of species hotspots (12–89%) and alterations of species composition (19–91%) will be intensified. These results imply that the influence of a strong and rapid Greenland ice sheet melting, resulting in a large AMOC weakening, can lead to a faster collapse of biodiversity across the globe.
Low power design of explicit‐pulsed dual‐edge‐triggered level‐converting flip‐flop based on carbon nanotubes field‐effect transistors
Authors: Dai Yanyun , Yang Yanfei , Jiang Lurong , Tong Jijun , Gao Faqin 
Published: September 2022

AbstractPower consumption and performance are the two main concerns in designing pulse‐triggered level‐converting flip‐flops (LCFF). In this letter, through the research on the level conversion circuits, an explicit‐pulsed dual‐edge triggered LCFF based on the carbon nanotubes field‐effect transistors (CNTFETs) is proposed by using the multi‐source voltage technology. The proposed flip‐flop increases the speed by reducing the number of transistors in the charge/discharge path. The characteristics of the CNTFETs are used to obtain transistors with different threshold voltages by changing the chiral vector to optimize the circuit structure and further reduce the power consumption. In addition, the power consumption is further reduced due to the small on‐current of the CNTFETs. The proposed novel structure is simulated in HSPICE using the Stanford model. Simulation results indicate that our proposed flip‐flop reduces 62.9% to 72.4% of power consumption and 73.6% to 89.1% of delay in comparison with other flip‐flops proposed in the references at 50% data switching activity.
A transformer‐less high‐boosting common‐grounded multi‐phase DC–DC converter with continuous input‐current favourable for low‐power applications
Authors: Varesi Kazem , Padmanaban Sanjeevikumar 
Published: September 2022

AbstractThe traditional dc–dc converters have limited boosting ability. Significant voltage gains can be accomplished only at extreme duty ratios, where the high voltage/current stress and losses occur on semiconductors. This work proposes a common‐ground multi‐phase boost dc–dc converter that benefits from high boosting factor at low duty ratios, continuous input‐current and minimum operational modes (only two at CCM) regardless of number of phases. Due to the presence of common‐ground point, the proposed converter can efficiently remove the leakage current while using the PV as the input source. Also, because of multi‐phase nature, the proposed converter has low current stress on its input devices, which leads to lower voltage drops and better efficiencies. The number of phases can freely be selected based on required boosting factor or converter efficiency. To assure of proper performance of proposed converter, the three‐phase (n = 3) version has been investigated in detail and its steady‐state analysis as well as real‐gain and loss calculations have been presented. The competitiveness of the suggested converter has been verified by performing comprehensive comparative analysis. The experimental results (for n = 3) have also been provided to certify the correct performance of suggested converter.
Three-dimensional Volume Changes of the Reconstructed Breast Following DIEP Flap Breast Reconstruction
Authors: Lee Mi Kyung , Park Hae Yeon , Park Jin-Woo , Mun Goo-Hyun , Woo Kyong-Je 
Published: September 2022

Abstract
Background This study aimed to assess whether the reconstructed breast volume changed postoperatively following a deep inferior epigastric artery perforator (DIEP) flap.
Methods Patients were included if they had undergone unilateral breast reconstruction with a DIEP flap at the two selected centers between April 2017 and September 2019. Serial 3-D surface imaging of both breasts was taken at 1, 3, 6, and 12 months postoperatively. The primary outcome was a volume ratio of the reconstructed to the contralateral breast. A linear mixed-effect model was used to evaluate whether the DIEP flap volume changed according to the postoperative time.
Results A total of 74 patients were included in the analysis. The mean volume ratio of the reconstructed side compared with the contralateral breast at 1, 3, 6, and 12 months postoperatively were 106.9%, 105.9%, 108.7%, and 107.6%, respectively. In the linear mixed effect model, the volume ratio of the reconstructed breast did not change over time for immediate reconstructions (p = 0.376). However, there was an increase over time in delayed reconstructions (p = 0.043). Adjuvant radiation, chemotherapy, and hormone therapy did not influence the volume ratio of the reconstruced breast. Correlation analysis using repeatedly measured values showed that both reconstruced and healthy breast volumes had positive correlation with the patient's body weight (p < 0.001). On the other hand, volume ratio of the breasts was not influenced by the patient's body weight (p = 0.493). The volume ratio of the reconstructed breast significantly decreased in the upper inner (p = 0.003) and the upper outer (p = 0.006) quadrants, while increasing in the lower outer (p = 0.002) quadrant throughout the first-year postoperative period.
Conclusion The volume ratio of the reconstructed to the contralateral breast does not decrease postoperatively following DIEP flap breast reconstruction.
Extended reaction kinetics model for non-thermal argon plasmas and its test against experimental data
Authors: Stankov M , Becker M M , Hoder T , Loffhagen D 
Published: September 2022

Abstract
An extended reaction kinetics model (RKM) suitable for the analysis of weakly ionised, non-thermal argon plasmas with gas temperatures around 300 K at sub-atmospheric and atmospheric pressures is presented. It considers 23 different species including electrons as well as the ground state atom, an atomic and molecular ion, four excited molecular states, and 15 excited atomic states of argon, where all individual 1s and 2p states (in Paschen notation) are included as a separate species. This 23-species RKM involves 409 collision processes and radiative transitions and recent electron collision cross section data. It is evaluated by means of results of time- and space-dependent fluid modelling of argon discharges and their comparison with measured data for two different dielectric barrier discharge configurations as well as a micro-scaled atmospheric-pressure plasma jet setup. The results are also compared with those obtained by use of a previously established 15-species RKM involving only the two lumped 2p states 2p10…5 and

2

p

4
…
1

′

. It is found that the 23-species RKM shows generally better agreement with experimental data and provides more options for direct comparison with measurements than the frequently used 15-species RKM.
The intricate geometry of zero-determinant strategies underlying evolutionary adaptation from extortion to generosity
Authors: Chen Xingru , Wang Long , Fu Feng 
Published: September 2022

Abstract
The advent of zero-determinant (ZD) strategies has reshaped the study of reciprocity and cooperation in the iterated prisoner’s dilemma games. The ramification of ZD strategies has been demonstrated through their ability to unilaterally enforce a linear relationship between their own average payoff and that of their co-player. Common practice conveniently represents this relationship by a straight line in the parametric plot of pairwise payoffs. Yet little attention has been paid to studying the actual geometry of the strategy space of all admissible ZD strategies. Here, our work offers intuitive geometric relationships between different classes of ZD strategies as well as nontrivial geometric interpretations of their specific parameterizations. Adaptive dynamics of ZD strategies further reveals the unforeseen connection between general ZD strategies and the so-called equalizers that can set any co-player’s payoff to a fixed value. We show that the class of equalizers forming a hyperplane is the critical equilibrium manifold, only part of which is stable. The same hyperplane is also a separatrix of the cooperation-enhancing region where the optimum response is to increase cooperation for each of the four payoff outcomes. Our results shed light on the simple but elegant geometry of ZD strategies that is previously overlooked.
Simulation study of the influence of upstream density and power in the scrape-off layer on the double-peaked density profile at the divertor target
Authors: Guo Jin , Mao Shifeng , Jia Guozhang , Meng Lingyi , Li Ang , Xu Jichan , Xu Guosheng , Ye Minyou 
Published: September 2022

Abstract
The double-peaked distribution of particle deposition at divertor targets has been observed in various tokamaks, and is considered a potential approach for mitigating divertor particles and heat load in future fusion reactors. Recently, the systematical analysis of the double-peaked distribution behavior during EAST experiments shows that the appearance of the double-peaked profile is related to the line-average density and heating power. In order to understand general trends and related mechanisms, the influences of the upstream density (n
e,sep) and power in the scrape-off layer (P
SOL) on the double-peaked density profile are investigated by SOLPS-ITER simulations with full drifts and currents. It is found that the n
e peak near the strike point is mainly contributed by the strong ionization source close to the target, and the n
e peak in the far-SOL region is caused by the synergetic effects of poloidal and radial E × B drifts along the SOL. The double-peaked distribution is affected by the P
SOL and impurity seeding by increasing or decreasing the whole profile of the electron temperature at the target (T
et). When the peak value of T
et (T
et,peak) is fixed, the density peak in the far-SOL is increased for higher n
e,sep by reducing the T
et in the far-SOL region on the lower-field side under unfavorable B
T and by the upstream-extended ionization source due to the geometry effect on the high-field side under favorable B
T. Statistical analysis of the simulated results shows that the scaling expression of the peak ratio is ∼

T

e
t
,
p
e
a
k

−

(

1.4
∼
2.1

)

n

e
,
s
e
p

1.6
∼
1.8

. In addition to the upper boundary found in the analysis of EAST experiments, a lower boundary of the region where the double-peaked feature appears on the P
SOL-n
e,sep plane is identified by simulations and preliminarily confirmed according to the measurements in several EAST discharges.