bluuebunny/crossref_metadata_2025_split huggingface dataset:
Over-expression of ABCC5 indicates poor prognosis of ovarian cancer and contributes to paclitaxel resistance in ovarian cancer cells
Authors: Ting Shuang , Feng Wang Jin , Wei Yang Xiao 
Published: September 2022

Abstract
Aim:Chemo-resistance has been the main obstacle for the successful treatment of ovarian cancer. ABCC5 over-expression was reported in several tumors and was claimed to be associated with multi-drug resistance expect ovarian cancer. This study aimed to find if ABCC5 over-expression contributes to the chemo-resistance and poor prognosis of ovarian cancer.
Methods and results:Firstly, bioinformatics analysis was used for predicting the significance of ABCC5 mRNA over-expression in ovarian cancer. Bioinformatics analysis showed ABCC5 was significantly over-expressed in ovarian malignant tumors than in the ovarian surface epithelium, moreover it was significantly higher in the ovarian cancer patients with stage Ⅲ-IV than patients with stage I-II(P=0.00001) . The high expression of ABCC5 was correlated with less overall survival (OS) (P=0.012) but not disease free survival (DFS)(P=0. 91) for ovarian cancer patients.Then tissue microarray was applied for further confirmation of ABCC5 protein expression and location in clinical samples which indicated ABCC5 was positive expressed in the chemo-resistant EOC tissues and mainly located in the cytoplasm.The multivariate logistic regression analysis showed FIGO stage (P<0.001) and positive expression of ABCC5 (P<0.0001) were independent risk factors for chemo-resistance in serous EOC. Kaplan-Meier analysis indicated patients with the ABCC5 negative expression showed significantly higher OS (P=0.043) but not DFS (P=0.067) than the ABCC5 positive expression group. Finally, the cell proliferation, cell apoptosis, wounding healing assay and clone formation ability test was applied and pointed to the inhibited expression of ABCC5 in A2780/Taxol cells could facilitate paclitaxel sensitivity.
Conclusions: ABCC5 could be used for predicting the chemo-resistance and poor prognosis of ovarian cancer and might be the therapeutic target to the chemo-resistance.
Trend analysis for groundwater levels for Handri river basin, Andhra Pradesh, India
Authors: Peera D. Gouse , Bhavani R. 
Published: September 2022

Abstract
Trend of groundwater levels in the Handri river basin, Andhra Pradesh, India is analyzed using non parametric tests such as Mann Kendall method and Sen’s Slope method. This analysis is useful for development and management of agriculture problems, water supply problems, and to reduce to the scarcity of the drinking water problems. The groundwater levels for 17years are used in this study from 1997 to 2012. The Zvalues in the case of Mann Kendall method and Qmedian values in the case of Sen’s slope method, gives the trend in this study area. The plenty of groundwater is available to the regions in which the trend is increasing, if necessary, we can discharge the groundwater.
Treatment of patellar tendon avulsion at the tibial tubercle at subacute stage: a case report
Authors: Ahmadov Asim , Ozer Hamza , Ozel Tayfun , Duzgun Ramazan , Baki Gokberk , Erdem Salih 
Published: September 2022

Abstract
Rupture of patellar tendon is one of the rarest injuries of childhood which require acute repair to preserve extensor mechanism. In this report, we present 12-year-old male patient, otherwise healthy who admitted with a rupture of patellar tendon without bony involvement. Treatment involved end-to-end suture, support with anchors and patellar reinforcement with a cerclage wire, combination of which was not documented earlier for the pediatric group in the prior literature. Early range of motion exercises started with functional knee brace. Final follow-up showed improved functional outcome.
A Hybrid Ensemble Voting-based Residual Attention Network for Motor Imagery EEG Classification
Authors: Jindal Komal , Upadhyay Rahul , Singh Hari Shankar 
Published: September 2022

Abstract
Multi-class motor imagery Electroencephalography (EEG) activity decoding has always been challenging for the development of Brain Computer Interface (BCI) system. Deep learning has recently emerged as a powerful approach for BCI system development using EEG activity. However, the EEG activity analysis and classification should be robust, automated and accurate. Currently, available BCI systems perform well for binary task identification whereas, multi-class classification of EEG activity for BCI applications is still a challenging task. In this work, a hybrid Residual Attention ensemble voting classifier model is developed for EEG-based Motor Imagery-Brain Computer Interface (MI-BCI) task classification. The Time-Frequency Representation (TFR) of the multi-class EEG activity is generated using Transient Extracting Transform (TET). The TFR spectrogram images are input to the designed Residual Attention ensemble voting classifier model for training and classification purposes. The model is evaluated using different fusion strategies viz. feature-level and score-level fusion of layers. The proposed model is evaluated on two MI-BCI datasets, BCI competition IV 2a and BCI competition III 3a, yielding the highest classification accuracies of 88.14 % and 93.13 %, respectively. The results obtained on a large multi-class MI-BCI dataset confirm that the proposed hybrid Residual Attention ensemble voting classifier model significantly outperforms the conventional algorithm and achieves significantly high classification accuracy for the feature-level fusion of layers. The developed framework aids in identifying different tasks for multi-class MI-BCI EEG activity.
Hard Optimization Problems have Soft Edges
Authors: Marino Raffaele , Kirkpatrick Scott 
Published: September 2022

Abstract
Finding a Maximum Clique is a classic property test from graph theory; find any one of the largest complete subgraphs in an Erdös-Rényi G(N, p) random graph. It is the simplest of many such problems in which algorithms requiring only a small power of N steps cannot reach solutions which probabilistic arguments show must exist, exposing an inherently "hard" phase within the solution space of the problem. Such "hard" phases are seen in many NP-Complete problems, in the limit when N → ∞. But optimization problems arise and must be solved at finite N. We use this simplest case, MaxClique, to explore the structure of the problem as a function of N and K, the clique size. It displays a complex phase boundary, a staircase of steps at each of which 2log2 N and Kmax, the maximum size of clique that can be found, increase by 1. Each of its boundaries have finite width, and these widths allow local algorithms to find cliques beyond the limits defined by the study of infinite systems. We explore the performance of a number of extensions of traditional fast local algorithms, and find that much of the "hard" space remains accessible at finite N.
The "hidden clique" problem embeds a clique somewhat larger than those which occur naturally in a G(N, p) random graph. Since such a clique is unique, we find that local searches which stop early, once evidence for the hidden clique is found, may outperform the best message passing or spectral algorithms.
Robotic Male and Laparoscopic Female Sphincter-Preserving Total Mesorectal Excision of Mid-Low Rectal Cancer Share Similar Specimen Quality, Complication Rates and Long-Term Oncological Outcomes
Authors: Aliyev Vusal , Piozzi Guglielmo Niccolò , Huseynov Elnur , Mustafayev Teuta Zoto , Kayku Vildan , Goksel Suha , Asoglu Oktar 
Published: September 2022

Abstract
Background: The aim of this study was to compare perioperative and long-term oncological outcomes between laparoscopic sphincter-preserving total mesorectal excision in female patients (F-Lap-TME) and robotic sphincter-preserving total mesorectal excision in male patients (M-Rob-TME) with mid-low rectal cancer (RC).
Methods: A retrospective analysis of a prospectively maintained database was performed. 170 cases (F-Lap-TME: 60 patients; M-Rob-TME: 110 patients) were performed by a single surgeon (January 2011 - January 2020).
Results: Clinical characteristics did not differ significantly between the two groups. Operating time was longer in M-Rob-TME than in F-Lap-TME group (185.3±28.4 vs 124.5±35.8 minutes, p<0.001). There was no conversion to open surgery in both groups. Quality of mesorectum was complete/near-complete in 58 (96.7%) and 107 (97.3%) patients of F-Lap-TME and M-Rob-TME (p=0.508), respectively. Circumferential radial margin involvement was observed in 2 (3.3%) and 3 (2.9%) in F-Lap-TME and M-Rob-TME patients (p=0.210), respectively. Median length of follow-up was 62 (24-108) months in the F-Lap-TME and 64 (24-108) months in the M-Rob-TME group. Five-year overall survival rates were 90.5% in the F-Lap-TME and 89.6% in the M-Rob-TME groups (p=0.120). Disease-free survival rates in F-Lap-TME and M-Rob-TME groups were 87.5% and 86.5% (p=0.145), respectively. Local recurrence rates were 5% (n=3) and 5.5% (n=6) (p=0.210), in the F-Lap-TME and M-Rob-TME groups, respectively.
Conclusion: The robotic technique can potentially overcome some technical challenges related to the pelvic anatomical difference between sex compared to laparoscopy. Laparoscopic and robotic approach, respectively in female and male patients provide similar surgical specimen quality, perioperative outcomes, and long-term oncological results.
Tracking Behavior of Scalar Fields in K = 0 Universe
Authors: Joshi Tanisha , Pathak S. D 
Published: September 2022

Abstract
In this paper, we investigate various scalar field potentials using the scalar field cosmological model. We analyze the tracking parameter for each potential in K = 0 universe. The tracking parameter is taken into account because the dynamics of tracking depend on the variation of this particular parameter during cosmic evolution. This parameter is applied to each potential, and the resulting behavior is displayed. The behavior is plotted, and a comparison is made between the behavior shown by the tracking parameter and the behavior shown by the corrected tracking parameter.
TRPM2 Regulates Neutrophil Extracellular Traps Formation and Delays Resolution of Neutrophil-driven Sterile Inflammation
Authors: Cao Xue , Li Yanhong , Luo Yubin , Chu Tianshu , Yang Hang , Wen Ji , Liu Yi , Zhao Yi , Herrmann Martin 
Published: September 2022

Abstract
The formation of neutrophil extracellular traps (NETs) is a process releasing into the extracellular space networks of chromatin fibers decorated with granular proteins. It is implicated in infection-related as well as sterile inflammation. Monosodium urate (MSU) crystals serve as damage-associated molecular pattern (DAMP) in various conditions of disease. Formation of NETs or aggregated NETs (aggNETs) orchestrates initiation and resolution of MSU crystals-triggered inflammation, respectively. Elevated intracellular calcium levels and the generation of reactive oxygen species (ROS) are crucial for the formation of MSU crystal-induced NETs. However, the exact signaling pathways involved are still elusive. Herein, we demonstrate that the ROS-sensing, non-selective calcium-permeable channel transient receptor potential cation channel subfamily M member 2 (TRPM2) is required for a full-blown MSU crystal-induced NET formation. Primary neutrophils from TRPM2-/- mice showed reduced calcium influx and ROS production and, consequently a reduced formation of MSU crystal-induced NETs and aggNETs. Furthermore, in TRPM2-/- mice the infiltration of inflammatory cells into infected tissues and their production of inflammatory mediators was suppressed. Taken together these results describe an inflammatory role of TRPM2 for neutrophil-driven inflammation and identify TRPM2 as potential target for therapeutic intervention.
WITHDRAWN: On Testing Constancy of Speed of Photons
Authors: Peng Hui 
Published: September 2022

Abstract

Special Relativity (SR) is a cornerstone for modern physics and for variety of applications. SR is based on two postulations, the principle of relativity and the principle of constancy of the propagation speed of light wave. However, up to now, the second postulate has not been confirmed experimentally yet. Recently we have shown that light propagate as particles even in “pure” wave experiments. In this article we propose doable modified Michelson’s rotating mirror experiments to test the second postulate for photons.
If the experiments show that the constancy of the speed of light propagating as photons holds, then we, the first time, experimentally confirm the second postulation of SR. If the experiments show that the propagation speed of photons is not constant, then, the second postulate of SR is disproved. Either negative result or positive results would be profoundly significant.
Measuring income inequality via percentile relativities
Authors: Greselin Francesca , Brazauskas Vytaras , Zitikis Ricardas 
Published: September 2022

Abstract
"The rich are getting richer" implies that the population income distributions are getting more right-skewed and heavy-tailed. For such distributions, the mean is not the best measure of the center, but the classical indices of income inequality, including the celebrated Gini index, are all mean-based. In view of this, Professor Gastwirth sounded an alarm back in 2014 by suggesting to incorporate the median into the definition of the Gini index, although noted a few shortcomings of his proposed index. In the present paper we make a further step in the modification of classical indices and, to acknowledge the possibility of differing viewpoints, arrive at three median-based indices of inequality. They avoid the shortcomings of the previous indices and can be used even when populations are ultra-heavy tailed, that is, when their first moments are infinite. The new indices are illustrated both analytically and numerically using parametric families of income distributions, and further illustrated using a real data set of capital incomes of  fifteen countries. We also discuss the performance of the indices from the perspective of the Pigou-Dalton principle of transfers.
Genetic Polymorphism and Intravenous Immunoglobulin Resistance Relationship in Kawasaki Disease
Authors: Varli Yusuf Ziya , Caglayan Ahmet Okay , Bilguvar Kaya , Gunel Murat , Oztarhan Kazim 
Published: September 2022

Abstract
Background
Kawasaki disease (CD) is an acute febrile systemic vasculitis that is the most common cause of coronary artery aneurysm (CAA) in children. Resistance to IVIG, which is used to reduce the risk of developing CAA, is an important risk factor, and risk scoring systems used to predict the development of this resistance gave different results in different breeds. We planned our study to investigate the effect of genetic factors on the development of IVIG resistance.
Methods
Patients diagnosed with CD by whole exome gene analysis were analyzed retrospectively. Blood samples were obtained from a randomized subgroup (n:97). Previously reported IVIG resistance-associated exonic SNPs at five different gene loci (IL16,TNFSF14, NFATC2,DERL3,SAMD9L) were evaluated by whole-exome sequencing(WES).
Results
259 patients (male/female: 1.67) with CD were included in the study. The rates of CAA and IVIG resistance in our patients were 11.6% and 21.6%, respectively. The risk of developing CAA was significantly increased in patients with IVIG resistance (p < 0.001). As a result, IVIG resistance frequency increased in the presence of three SNPs (the IL16,TNFSF14, NFATC2 genes, respectively).
Conclusion
The development of resistance at different rates in different races against IVIG, which is used in the treatment of CD, has led to genetic studies. In our study, we found mutations in three genes (IL16, TNFSF14, NFATC) that play a role in T lymphocyte activation in patients with IVIG resistance. We think that the role of genetic factors in the resistance mechanism will become clear with the increase in genetic studies to be done.
SPOP could play a potential inhibitory role in human renal cell carcinoma
Authors: Chen Zhi , Li Zuan , Li Chunlin , Li Bingcai , Wang Haojian , Nong Deyong , Li Ximing , Huang Guihai , Lin Junhao , Li Wei 
Published: September 2022

Abstract
SPOP, a substrate adaptor of Cul3 ubiquitin ligase, plays crucial roles in solid neoplasms by promoting the ubiquitination and degradation of substrates. Limited studies have shown that SPOP is overexpressed in human renal cell carcinoma (RCC) tissue. However, the exact role of SPOP in RCC remains unclear and needs to be further elucidated. We found that overexpression of SPOP inhibited cell proliferation, migration and invasion and increased apoptosis. Interestingly, sunitinib and IFN-α2b at several concentrations increased the proliferation inhibitory rate and total apoptosis rate of cells overexpressing SPOP. The findings of the present study showed that the SPOP protein was significantly expressed at low levels in most clear cell RCC (ccRCC) tissues and at relatively high levels in the majority of adjacent normal and kidney tissues. In conclusion, in contrast to previous studies, our findings demonstrated that overexpression of SPOP might suppress the progression of RCC cells, which was supported by cell experiments and immunohistochemical staining. SPOP could be a potential tumour inhibitor in RCC.
Multi-fault diagnosis of rolling bearing using two-dimensional feature vector of WP-VMD and PSO-KELM algorithm
Authors: jiang tingyu , Li Yakun , Li Shen 
Published: September 2022

Abstract
In order to achieve accurate fault diagnosis of rolling bearing under random noise, a new fault diagnosis method based on wavelet packet-variational mode decomposition (WP-VMD) and kernel extreme learning machine (KELM) optimized by particle swarm optimization (PSO) is proposed in this paper. Firstly, the time-frequency domain feature vectors of the original rolling bearing fault signals are effectively obtained by preprocessing of WMD and decomposition and reconstruction of VMD. Then, the extracted two-dimensional feature vector is input into the KELM neural network for fault identification, and combined with PSO, KELM parameters were optimized. The experimental results show that the proposed method can effectively diagnose the rolling bearing under random noise, with the features of fast speed, stable performance and high accuracy. By comparison, this paper obtains better accuracy and real-time performance with fewer features, which provides a simple and efficient solution for fault diagnosis of rolling bearings.
Formative Evaluation Prior to Implementation of a Brief Treatment for Posttraumatic Stress Disorder in Primary Care
Authors: Valentine Sarah E. , Fuchs Cara , Sarkisova Natalya , Olesinski Elyse A. , Elwy A. Rani 
Published: September 2022

Abstract
Background
Successful implementation of evidence-based treatments (EBT) for posttraumatic stress disorder (PTSD) in primary care may address treatment access and quality gaps by providing care in novel and less stigmatized settings. Yet, PTSD treatments are largely unavailable in safety net primary care. We aimed to collect clinician stakeholder data on organizational, attitudinal, and contextual factors relevant to EBT implementation.
Methods
Our developmental formative evaluation was guided by the Consolidated Framework for Implementation Research (CFIR), including (a) surveys assessing implementation climate and attitudes towards EBTs and behavioral health integration and (b) semi-structured interviews to identify barriers and facilitators to implementation and need for augmentation. Participants were hospital employees (N = 22), including primary care physicians (n = 6), integrated behavioral health clinicians (n = 8), community wellness advocates (n = 3), and clinic leadership (n = 5). We report frequency and descriptives of survey data and findings from directed content analysis of interviews. We used a concurrent mixed-methods approach, integrating survey and interview data collected simultaneously using a joint display approach. A primary care community advisory board (CAB) helped to refine interview guides and interpret findings.
Results
Stakeholders described implementation determinants of the EBT related to the CFIR domains of the intervention (relative advantage, adaptability), outer setting (patient needs and resources), inner setting (networks and communication, relative priority, leadership engagement, available resources), and individuals involved (knowledge and beliefs, cultural considerations). Stakeholders described strong attitudinal support (relative advantage), yet therapist time and capacity restraints are major PTSD treatment implementation barriers (available resources). Changes in hospital management were perceived as potentially allowing for greater access to behavioral health services, including EBTs. Patient engagement barriers such as stigma, mistrust, and care preferences were also noted (patient needs and resources). Recommendations included tailoring the intervention to meet existing workflows (adaptability), system alignment efforts focused on improving detection, referral, and care coordination processes (networks and communication), protecting clinician time for training and consultation (leadership engagement), and embedding a researcher in the practice (available resources).
Conclusions
Our evaluation identified key CFIR determinents of implementation of PTSD treatments in safety net integrated primary care settings. Our project also demonstrates that successful implementation necessitates strong stakeholder engagement.
Relationship between drug targets and drug-signature networks: a network- based genome-wide landscape
Authors: Lee Chae Won , Kim Sung Min , Sa Soonok , Nam Sang-Min , Han Hyun Wook 
Published: September 2022

Abstract
Drugs produce pharmaceutical and adverse effects that arise from the complex relationship between drug targets and signatures; by considering such relationships, we can begin to understand the cellular mechanisms of drugs. In this study, we selected 463 genes from the DSigDB database corresponding to targets and signatures for 382 FDA-approved drugs with both protein binding information for a drug-target score (KDTN, i.e., the degree to which the protein encoded by the gene binds to a number of drugs) and microarray signature information for a drug-sensitive score (KDSN, i.e., the degree to which gene expression is stimulated by the drug). Accordingly, we constructed two drug–gene bipartite network models, a drug-target network and drug-signature network, which were merged into a multidimensional model. Analysis revealed that the KDTN and KDSN were in mutually exclusive and reciprocal relationships in terms of their biological network structure and gene function. A symmetric balance between the KDTN and KDSN of genes facilitates the possibility of therapeutic drug effects in living organisms. These results provide new insights into the relationship between drugs and genes, specifically drug targets and drug signatures.