bluuebunny/crossref_metadata_2025_split huggingface dataset:
Effect of ultrasound-assisted extraction of dietary fibre from the sweetest variety Queen Pineapple peel waste of Tripura (India)
Authors: Dhar Payel , Deka S. C. 
Published: June 2022

Abstract
The study aimed to assess the functional attributes of dietary fibre from the sweetest variety of Queen pineapple of Tripura Region (India) having high pleasant aroma and flavour. Queen pineapple peel waste was used to extract dietary fibre, which is one of the important bioactive compounds in the human diet and health. The ultrasound-assisted extraction method was compared to the traditional alkali extraction method for extracting dietary fibre from Queen pineapple peel waste. The extracted dietary fibre was further examined for its functional attributes. The parameters used for ultrasound-assisted extraction (UAE) of dietary fibre were optimised using response surface methodology (RSM). The results showed that Queen pineapple peel waste was having a significant amount of dietary fibre and had a high potential in food processing. The conventional alkaline extraction yielded 64.43% dietary fibre, whereas the UAE method yielded 86.67% after 22.35 min of sonication with a solid: liquid ratio of 1:27.5 g/mL and a 46.9% ultrasonic amplitude. UAE improved the functional attributes of dietary fibre by significantly increasing the water-holding and swelling capacities while decreasing the oil holding capacity. The cation exchange capacity, glucose adsorption capacity, and glucose dialysis retardation index were enhanced considerably by ultrasound-assisted extraction, whereas the emulsifying capacity decreased. These findings suggested that Queen pineapple waste extracted dietary fibre could be used as a potential hypoglycemic agent as a functional food ingredient in bread and bakery-based products, meat-based products, dairy-based beverages, and other products of food application.
Grace-AKO: A Novel and Stable Knockoff Filter for Variable Selection Incorporating Gene Network Structures
Authors: Tian Peixin , Hu Yiqian , Liu Zhonghua , Zhang Yan Dora 
Published: June 2022

Abstract
Motivation: Variable selection is a common statistical approach to detecting genes associated with clinical outcomes of scientific interest. There are thousands of genes in genomic studies, while only a limited number of individual samples are available. Therefore, it is important to develop a method to identify genes associated with outcomes of interest that can control finite-sample false discovery rate (FDR) in high-dimensional data settings.

Results: This article proposes a novel method named Grace-AKO for graph-constrained estimation (Grace), which incorporates aggregation of multiple knockoffs (AKO) with the network-constrained penalty. Grace-AKO can control FDR in finite sample settings and improve model stability simultaneously. Simulation studies show that Grace-AKO has better performance in FDR control in finite sample settings than the original Grace model. We apply Grace-AKO to the prostate cancer data in the The Cancer Genome Atlas (TCGA) program by incorporating prostate-specific antigen (PSA) pathways in the Kyoto Encyclopedia of Genes and Genomes (KEGG) as the prior information. Grace-AKO finally identifies 47 candidate genes associated with PSA level, and more than 75% of the detected genes can be validated.
Inversion of Generalized Flett Potentials Related to Wavelet-Like Transform
Authors: BAYRAKÇI SIMTEN , Yıldız Güldane , Kahraman Recep , Eryiğit Melih 
Published: June 2022

Abstract
We obtained the explicit inversion formulas for the generalized Flett potentials with the wavelet-like transform generated by the generalized Poisson integrals (semigroups). These integrals are defined as the relevant generalized translation operator associated with the Laplace-Bessel differential operator. Moreover, in this article we proved some essential properties of the generalized Poisson integrals.
USP10-mediated ZEB1 deubiquitination regulates MEK-ERK-induced colorectal cancer metastasis
Authors: Sinicrope Frank , Qin Bo , Sun Lei , yu Jia 
Published: June 2022

Abstract
Zinc finger E-box binding homeobox 1 (ZEB1) is a transcription factor regulating epithelial to mesenchymal transition (EMT). To date, regulation of ZEB1 by key signaling pathways including RAS/RAF/MEK/ERK remains unclear, and few studies have focused on molecular associations or functional alterations of ZEB1 by post-translational modification. Here, we report an interaction of ZEB1 with the deubiquitinase USP10 that is regulated by MEK-ERK signaling. USP10 removes the K27 linkage ubiquitination chain on ZEB1 that enhances K48 polyubiquitination and promotes ZEB1 proteasomal degradation. However, constitutive activation of ERK can phosphorylate USP10 at Ser236 to impair its interaction with ZEB1 and, thereby, stabilize ZEB1 protein shown to promote colorectal cancer metastasis in mice. Conversely, inhibition of MEK-ERK blocks USP10 phosphorylation to enhance the USP10-ZEB1 interaction which can suppress ZEB1-mediated tumor cell migration and metastasis in vivo. Together, these data demonstrate a novel function of USP10 in the regulation of ZEB1 ubiquitination and protein stability that can inhibit ZEB1-mediated tumor metastasis.
Cloning, sequence analysis, and three-dimensional structure prediction of Universal stress protein A from Salmonella Typhimurium Isolated from the Poultry
Authors: Nabi Bilkees , Kumawat Manoj , Ahlawat Sushma , kumar Manoj , Ahlawat Neeraj , Yadav Pramod Kumar , Mir Manzoor Ahmad 
Published: June 2022

Abstract
Background
Salmonella Typhimurium is a zoonotic pathogen responsible for food and waterborne gastroenteritis in humans. Salmonella Typhimurium expresses Universal stress proteins (USPs) when subjected to different biotic and abiotic stresses. This class of proteins is becoming widely recognizedfor its role in bacterial stress resistance and protracted growth arrest. USPs possesses versatile structures arising from the fusion of the USP domain with various other catalytic motifs; they are possibly involved in a variety of reactions and cellular activities under stressful conditions.
Objective
The aim of this study is to obtain the universal stress protein A (uspA) gene of Salmonella Typhimurium and clone it into the pET28C plasmid for nucleotide sequencing. And also 3D structure prediction of USPA protein and to evaluate its phylogenetic gene tree model.
Methods
In this study, we constructed a recombinant clone of the uspA (pET28c_uspA) gene from Salmonella Typhimurium, and various methods, including sequencing, did conformation to the clone. The sequence was subsequently submitted to the NCBI GenBank database. Besides, the Three-dimensional structure for USPA protein was predicted by comparative modeling. A phylogenetic gene tree was also constructed to trace the evolutionary history of the uspA gene of Salmonella Typhimurium.
Results
The uspA gene of 435 bp in length was successfully cloned. Comparing the uspA gene sequence with that reported in GenBank showed that identities were 100%. Furthermore, Sequence analysis also revealed the uspA gene is 435 bp long, encodes a protein of 144 amino acids with a calculated molecular mass of 16 kDa, and belongs to the USP family. Predicted 3D structure and sequence alignments of USPA showed that all residues’ sites are highly similar among the genome. The stereo-chemical property of the 3D structure of USPA was found to be of good quality.
Conclusion
A confirmed uspA gene from Salmonella Typhimurium was reported in this study. This study laid a solid foundation for recombination and research of genes. Moreover, the results of this study would help to detect the functional domains of the protein to elucidate their structural/functional characteristics.
An Improved Recommendation Based on Graph Convolutional Network
Authors: He Yichen , Mao Yijun , Xie Xianfen , Gu Wanrong 
Published: June 2022

Abstract
Graph convolutional network is a recently developed artificial neural network method commonly used in recommendation system research. This paper points out three shortcomings of existing recommendation systems based on the graph convolutional network. 1. Existing models that take the one-hot encoding based on node ordinal numbers in the graph or encoding based on original entity attributes as input may not fully utilize the information carried by the attribute interactions. 2. Previous models update the node embeddings only by the first-order neighbors in the graph convolution layer, which is easily affected by noise. 3. Existing models do not take into account differences in user opinions. We propose an improved graph convolutional network-based collaborative filtering model to address these drawbacks. We identify inner and cross interaction between user attributes and item attributes, and then we take the vector representations of aggregated attributes graph as input. In the convolutional layer, we aggregate the second-order collaborative signals and incorporate the different user opinions. The experiments on three public datasets show that our model outperforms state-of-the-art models. Compared with baselines, it shows an improved performance (2.1% ∼ 4.3%).
Objective Performance Indicators of Cardiothoracic Residents Are Associated with Vascular Injury During Robotic-Assisted Lobectomy on Porcine Models
Authors: Lazar John F. , Brown Kristen , Yousaf Sadia , Jarc Anthony , Metchik Ariana , BSN Hayley Henderson , Feins Richard H , Sancheti Manu S , Lin Jules , Yang Stephen , Nesbitt Jonathan , D’Souza Desmond , Oh Daniel S 
Published: June 2022

Abstract
Objective
Surgical training relies on subjective feedback on resident technical performance by attending surgeons. A novel data recorder connected to a robotic-assisted surgical platform captures synchronized kinematic and video data during an operation to calculate quantitative, objective performance indicators (OPIs). The aim of this study was to determine if OPIs during initial task of a resident’s robotic-assisted lobectomy (RL) correlated with bleeding during the procedure.
Methods
Forty-six residents from the 2019 Thoracic Surgery Directors Association Resident Boot Camp completed RL on an ex-vivo perfused porcine model while continuous video and kinematic data was recorded. For this pilot study RL was segmented into 12 tasks and OPIs were calculated for the initial major task. Cases were reviewed for major bleeding events and OPIs of bleeding cases were compared to those who did not.
Results
Data from 42 residents were complete and included in the analysis. 10/42 residents (23.8%) encountered bleeding: 10/40 residents who started with superior pulmonary vein exposure and 0/2 residents who started with pulmonary artery exposure. Twenty OPIs for both hands were assessed during the initial task. Six OPIs related to instrument usage or smoothness of motion were significant for bleeding. Differences were statistically significant for both hands (p < 0.05). OPIs showing bimanual asymmetry indicated lower proficiency.
Conclusion
This study demonstrates that kinematic and video analytics can establish a correlation between objective performance metrics and bleeding events in an ex vivo perfused lobectomy. Further study could assist in the development of focused exercises and simulation on objective domains to help improve overall performance and reducing complications during RL.
Novel Bimolecular Fluorescence Complementation (BiFC) assay for in vivo visualization of the protein-protein interactions and cellular protein complex localizations
Authors: Shi Zhonggang , Gao Xing , Zhang Wenrui , Chen Binghong , Wang Mengying , Liao Keman , Wang Zhihan , Ren Li , Qiu Yongming , lin yingying 
Published: June 2022

Abstract
Background
The study of protein-protein interactions (PPIs) is critical for understanding cellular processes within biological systems. The bimolecular fluorescence complementation (BiFC) assay provides a convenient approach for visualization of protein-protein interactions in living cells. Though a series of fluorescence proteins have been introduced into BiFC system, new fluorescent proteins need to be brought in this assay.
Results
Here, we applied TagBFP2 into BiFC for the first time to verify the interaction between two proteins, and EYFP was set as a positive control. Both fluorescent proteins performed well in our study. Compared to EYFP, the BiFC system based on TagBFP2 showed higher signal-to-noise ratio, which help us distinguish the signal of PPIs from noise.
Conclusion
With the joining of TagBFP2, we have another color option when we conduct BiFC assay. Especially, the green or yellow channel was occupied by a fluorescent secondary antibody in immunofluorescence application, or an interest protein tagged with a fluorescent protein. BiFC assay presented here is quite easy-to-follow, reliable, and reproducible, which can be completed within 1 week without using costly instruments and technologies that demand a high skill set.
Hybrid Cuckoo Finch Optimization based Machine Learning Classifier for Seizure Prediction Using EEG Signals in IoT Network
Authors: Kapoor Bhaskar , Nagpal Bharti 
Published: June 2022

Abstract
The Internet of Things (IoT) is an indispensable part of the healthcare system since it creates a link between the doctor and the patient for remote medical consultations. IoT-based seizure prediction detects the seizures and monitors the health of patients remotely. The disease seizure is categorized with the sudden and repeated malfunction of the neurons of the brain. To protect patient's lives, it's critical to recognise the risk of an epileptic seizure. In this research a hybrid cuckoo finch optimization is proposed tuned Deep-CNN (Deep-Convolutional Neural Network) classifier recognize and predict the occurrence of epileptic seizure using the electroencephalogram (EEG) signal data obtained through IoT. Initially, the gathered data is pre-processed and subjected to frequency band generation. Then there are the notable characteristics, such as Statistical features, Wavelet features, Entropy-based features, Spectral features, CPR (Common Spatial Patterns) and Logarithmic band power are extracted and concatenated. The optimal electrode selection is done by using the proposed hybrid cuckoo finch optimization that inherits characteristics of the intrusive and attentive search agents. The data is finally normalized and fed to proposed hybrid cuckoo finch optimization tuned Deep-CNN to classify the seizure disease. The specificity, accuracy and sensitivity of the proposed model is attained as 92.5212%, 97.7648%, and 95.6324%, which demonstrates efficient performance of the proposed seizure prediction model.
Conjugacy Classification of Bicomplex Möbius transformations
Authors: Li Zekun , Dai Binlin 
Published: June 2022

Abstract
We investigate the Conjugacy Classification in the framework of bicomplex numbers, which are pairs of complex numbers making up a commutative ring with zero-divisors. In this paper, we first classify bi-complex Möbius transformation in terms of fixed points in BC. Then we have a discussion of the iterates of a bicomplex Möbius transformation and study the attractive and repulsive fixed points in bicomplex setting. Mathematics Subject Classification (2010). Primary 30G35; Secondary 32A30.
Description of a new Coniochaeta species isolated from clinical sample
Authors: Kabtani Jihane , Militello Muriel , Ranque Stephane 
Published: June 2022

Abstract
Coniochaeta is a teleomorphic genus belonging to the Ascomycota class and Coniochaetaceae family. Some of the Coniochaeta species are plant and animal pathogens, while others are known to be primarily involved in human disease. In the last decades, case reports of human infections with Coniochaeta have increased, mainly in immunocompromised hosts. We have described and characterised a new species in the Coniochaeta genus, here named Coniochaeta massiliensis (PMML0158) that was isolated from a clinical sample. Species identification and thorough description were based on apposite and reliable phylogenetic and phenotypic approaches. The phylogenetic methods included a multilocus nucleotide analysis of four genomic regions: ITS (rRNA internal transcribed spacers 1 and 2), TEF-1α (translation elongation factor-1alpha), TUB2 (β-tubulin2), and D1/D2 domains (28S LSU rRNA). The phenotypic characterisation first consisted of a physiological analysis using both EDX (Energy-Dispersive X-ray Spectroscopy) and Biolog™ advanced phenotypic technology for fixing the chemical mapping and carbon source oxidation/assimilation profiles. Afterwards, morphological characteristics were highlighted by optical microscopy and scanning electron microscopy. The in vitro antifungal susceptibility profile was characterised using the E-test™ exponential gradient method. The molecular analysis revealed the genetic distance between the novel species Coniochaeta massiliensis (PMML0158) and other known taxa, and the phenotypic analysis confirmed its unique chemical and physiological profile when compared to all other species of this genus.
Searching for the ground state of complex spin-ice systems using deep learning techniques
Authors: Kwon Hee Young , Yoon Han Gyu , Park Seong Min , Lee Doo Bong , Shi Dong , Wu Yizheng , Choi Jun Woo , Won Changyeon 
Published: June 2022

Abstract
Searching for the ground state of a given system is one of the most fundamental and classical questions in scientific research fields. However, when the system is complex and large, it often becomes an intractable problem; there is essentially no possibility of finding a global energy minimum state with reasonable computational resources. Recently, a novel method based on deep learning techniques was devised as an innovative optimization method to estimate the ground state. We apply this method to one of the most complicated spin-ice systems, aperiodic Penrose P3 patterns. From the results, we discover new configurations of topologically induced emergent frustrated spins, different from those previously known. Additionally, a candidate of the ground state for a still unexplored type of Penrose P3 spin-ice system is first proposed through this study. We anticipate that the capabilities of the deep learning techniques will not only improve our understanding on the physical properties of artificial spin-ice systems, but also bring about significant advances in a wide range of scientific research fields requiring computational approaches for optimization.
Lessons from the COVID-19 pandemic for substance misuse services: Findings from a peer-led study
Authors: Holloway Katy , Murray Shannon , Buhociu Marian , Arthur Alisha , Molinaro Rondine , Chicken Sian , Thomas Elwyn 
Published: June 2022

Abstract
BackgroundThe measures implemented to contain the spread of the COVID-19 virus disrupted the provision of substance misuse treatment and support. However, little is known about the impact of this disruption on service users. This study aimed to help substance misuse services learn lessons and identify ways of optimising delivery and minimising harm in the event of any future lockdowns or global crises.MethodsThe study was co-produced by a team of peer researchers, practitioners, policy makers and academics. Telephone interviews were conducted with 202 substance misuse service users over a six-month period commencing June 2020. The interviews were conducted by a small group of seven peer researchers each with lived experience of substance use problems. The interview data were recorded by the peers in an anonymous online questionnaire survey and analysed using standard quantitative and qualitative methods.ResultsService users responded to the COVID-19 pandemic in a variety of ways. Diverse responses were noted in relation to their substance use patterns, their personal lives and their substance misuse treatment experiences. For some the pandemic acted as a new risk environment factor that increased their vulnerability to substance-related harm. For others, it facilitated aspects of the enabling environment thereby reducing the risk of harm. ConclusionsService users are not a homogenous group and an individualised approach to treatment that recognises the potential for varied responses to the same stimuli is needed. The findings suggest that service users would benefit from having a choice in how they access treatment and from greater access to outreach programmes that take treatments and harm reduction tools such as naloxone into the community. The research also supports the involvement of people with lived experience in substance use research, policy and practice.
Pulmonary artery diameter on chest CT predicts in-hospital mortality in patients with COVID-19 pneumonia
Authors: Baytugan Nart Zafer , Çelik Aziz İnan , Çağdaş Metin , Bezgin Tahir , Kandemir Hasan Çağlayan 
Published: June 2022

Abstract
Background: Enlargement of pulmonary artery (PA) trunk diameter could be helpful in risk stratification by the chest CT on the admission of COVID-19 patients.Methods: The aim was to investigate the association between pulmonary artery enlargement and overall mortality in COVID-19 pneumonia. We conducted a single-center, retrospective, observational study between January 2021 and May 2021 in tertiary level hospitals in Gebze, Turkey. According to their survivor status, subjects were divided into two groups (survivors and non-survivors). Then biochemical, demographic, and clinical parameters were compared via the two groups to assess the predictive value of PA diameter on chest CT images.Results: In the enrolled 594 COVID-19 in-hospital patients (median age was 45 (34-58) years, and 263 patients (44.3%) were female), 44 patients (7.4%) died during their hospitalization. The time-dependent multivariate Cox-proportion regression model yielded main PA ≥ 29 mm on admission showed that as independent predictors of subsequent death (long rank <0.001, median survival time 28 days). Cumulative survival rates were MPAD ≥ 29 mm 45% and < 29 mm 90% respectively (p < 0.001).Conclusions: PA dilatation is strongly associated with in-hospital mortality in hospitalized patients with COVID-19 pneumonia. Thus increased PA diameter on chest CT at admission may guide rapid and early diagnosis of high-risk patients.
Indapamine effects on hypercalciuria and bone mineral density
Authors: Spivacow Francisco Rodolfo , Niedlich Griselda , Rey Paula 
Published: June 2022

Abstract
Idiopathic hypercalciuria is associated to urinary stone formation and bone loss and should be treated not only to prevent kidney stone formation but also to prevent fragility fractures. Thiazide diuretics are traditionally used to control hypercalciuria. Indapamine, a sulfonamide thiazide diuretic, with some differences in structure is similar in its mechanisms of action such as its hypocalciuric effect, and bone density protection, with less adverse metabolic consequences than thiazides such as less hypokalemia and hypotension. We evaluated efficacy and adverse effects of Indapamine in 88 idiopathic hypercalciuric consecutive patients and those who reached normal calciuria in the first 9 months, were followed during two years. Changes in bone turn-over markers and bone density were evaluated. Since year one, there was a significant lowering of urine calcium to normal values in 77 patients, with no change in sodium excretion. There were changes in bone turn over markers and gains in bone mineral density according to the groups analyzed. In 25 hypercalciuric osteoporotic patients, there was a significant increment in lumbar spine bone density at year 2 of follow-up, (p<0.05). Those hypercalciuric osteoporotic stone former patients had a significant increase in femoral neck bone density since year one. Adverse effects were not significant, no changes found in blood pressure, glycaemia, cholesterol, serum uric acid, sodium and potassium. Two patients needed potassium supplementation for mild hypokalemia and did not stop Indapamine. In conclusion Indapamine is an effective alternative treatment to Idiopathic hypercalciuria, controlling calcium loss and bone density for at least two years.