bluuebunny/crossref_metadata_2025_split huggingface dataset:
Mechanistic Basis of Arsenic Induced Carcinogenesis: Differential miRNA Expression
Authors: John Placheril J. , Kumar Navneet 
Published: January 2022

Abstract
Arsenic, a toxic metalloid, provokes many detrimental consequences to human health. It is prevalent in earth's crust and poses a major threat to humans globally. Inorganic arsenic exposure occurs mainly via drinking water or food and is metabolized in mammals to form organic metabolites/ end products. Chronic exposure to arsenic causes lung, skin and urinary bladder cancers and increases the risks of liver, kidney and prostate cancers. Arsenic-induced ROS generation, disturbances in several signaling pathways, DNA repair inhibition, chromosomal aberrations, and epigenetic changes including alterations in DNA methylation, histone modifications and differential miRNA expression profiles are involved in cancer progression, and malignant transformation. However, details of arsenic-induced carcinogenesis and molecular mechanisms involved are still remaining obscure. MicroRNAs are post-transcriptional gene expression regulators and themselves may act as oncogenes and tumor suppressor genes. Differential miRNA expression is implicated in several human cancers. This review covers general mechanistic basis of arsenic-induced carcinogenesis, explores recent in-vitro, in-vivo and cohort studies on differential miRNA expression profiles and shares associated molecular mechanistic data on miRNA dysregulation and their functional consequences leading to arsenic induced tumorigenesis, metastasis and cancer, also discusses the future directions.
Brain Computer Interface-EEG based Imagined Word Prediction Using Convolutional Neural Network Visual Stimuli for Speech Disability
Authors: Chinta Babu , M Moorthi 
Published: January 2022

Abstract
Brain Computer Interface (BCI) is one of the fast-growing technological trends, which finds its applications in the field of the healthcare sector. In this work, 16 electrodes of Electroencephalography (EEG) placed according to the 10-20 electrode system are used to acquire the EEG signals. A BCI with EEG based imagined word prediction using Convolutional Neural Network (CNN) is modeled and trained to recognize the words imagined through the EEG brain signal, where the CNN model Alexnet and Googlenet are able to recognize the words due to visual stimuli namely, up, down, right, left and up to ten words. The performance metrics are improved with the Morlet Continuous wavelet transform applied at the pre-processing stage, with seven extracted features such as mean, standard deviation, skewness, kurtosis, bandpower, root mean square, and Shannon entropy. Based on the testing, Alexnet transfer learning model performed better as compared to Googlenet transfer learning model, as it achieved an accuracy of 90.3%, recall, precision, and F1 score of 91.4%, 90%, and 90.7% respectively for seven extracted features. However, the performance metrics decreased when the number of extracted features was reduced from seven to four, to 83.8%, 84.4%, 82.9%, and 83.6% respectively. This high accuracy further paves the way to future work on cross participant analysis, plan to involve a larger number of participants for testing and to enhance the deep learning neural networks to create the system developed to be suitable for EEG based mobile applications, which helps to identify what the words are imagined to be uttered by the speech-disabled persons.
The Effects of Inorganic Arsenic On Apoptosis and Autophagy in Human Hepatic Sellate Cells
Authors: Huang Fei , Hui Yu , Li Ang , Tayier Rishalaiti , Yaermaimaiti Dilinaer , Ding Guanxin , Wu Shunhua 
Published: January 2022

Abstract
Endemic arsenism is a major disease concern in China, with arsenic poisoning and induced potential lesions key issues on a global level. The liver is the main target organ where arsenic is metabolized; chronic exposure to arsenic-induced liver fibrosis is also closely related to autophagy, however, the exact mechanisms are remain unclear. In this study, we explored the effects of NaAsO2 on apoptosis and autophagy in human hepatic stellate cells(HSC). We established a fibrosis model in the HSC line, LX-2 which was exposed to NaAsO2 for 24h, 48h, and 72h. Cells were then transfected using an autophagy double-labeled RFP-GFP-LC3 adenoviral plasmid. Laser confocal microscopy indicated significant infection efficiencies and autophagy in LX-2. Flow cytometry was also used to investigate the effects of different NaAsO2 doses on apoptosis. NaAsO2 treatment upregulated the expression of autophagic markers, including microtubule-associated protein light chain A/B(LC3), ubiquitin binding protein(SQSTM-1/P62), autophagy related genes(ATGs), recombinant human autophagy effector protein (Beclin-1), and B cell lymphoma-2(BCL-2), but downregulated mammalian target of rapamycin(mTOR). Also, α-smooth muscle actin(α-SMA) expression was significantly upregulated in all NaAsO2 groups. Furthermore, mTOR silencing via 3-methyladenine(3-MA) altered NaAsO2 induced autophagy, LC3, Beclin-1, and SQSTM-1/P62 expression were all upregulated in both NaAsO2 and 3-MA-iAs groups. Altogether, NaAsO2 induced HSC autophagy via apoptotic pathways. 3-MA inhibited LX-2 activity and reduced NaAsO2-induced autophagy which may inhibit fibrosis progression caused by this toxin.
Fermatean Hesitant Fuzzy Sets with Medical Decision Making Application
Authors: Kirişci Murat 
Published: January 2022

Abstract
Fermatean fuzzy set idea obtained by combining fermatean fuzzy sets and hesitant fuzzy sets can be used in practice to simplify the solution of complicated multi-criteria decision-making (MCDM) problems. Initially, the notion of fermatean hesitant fuzzy set is given and the operations related to this concept are presented. Aggregation operators according to fermatean hesitant fuzzy sets are given and basic properties of these operators are studied. To choose the best alternative in practice, a novel MCDM method that is obtained with operators has been created. Finally, an example of infectious diseases was examined to indicate the effectiveness of the suggested techniques.
“Can We Break Through the Identity Dilemma?”: The Multiple Governance, Identities Conflict, and Self-Managements for Chinese PWUD.
Authors: Song Apei , Ren Zhongyuan 
Published: January 2022

Abstract
Background: Exploring why the national drug policy failed is an important issue. Based on it, this study considers both the drug governance system and the voice of people who use drugs (PWUD) to analysis drug policy effects and the lives of PWUD in the Chinese context. Methods: This study takes PWUD living in urban communities as the research participants. Using qualitative research data, exploring how individual using drug experiences are identified and classified by structural forces and how individuals manage their daily life. Results: The study finds that law enforcement agencies (Narcotics Control Office (NCO), Police Station , and Community Assistance Group (CAG)) have different attitudes toward PWUD and generate different managements, forming multiple governance models, and then shaping the multiple identity dilemma. PWUD perceive the dilemma, and they adopt the strategies of spatial isolation (hidden flow), disconnection from experience (temporal isolation), and instrumental cooperation to continuously re-adjust and achieve identity recovery from the bottom-up. Conclusion/importance: Through evaluating the effectiveness of self-management strategies, this research integrates the Chinese drug rehabilitation situation, expands the specific performance of law enforcement system, and presents the limitations and positive value of self-management strategies.
Application of 2D Resistivity Modelling to Delineate Lamproites in Parts of North‑Eastern Dharwar Craton
Authors: Jonnalagadda Ravi , Mathur Ram Raj 
Published: January 2022

Abstract
Geophysical methods have extensively been used in exploration of Lamproite bodies. Lamproites are significant source rocks of primary diamond deposits other than Kimberlites. The Eastern Dharwar Craton is unique in the way that it hosts numerous Precambrian Lamproites confined to the crescent-shaped Paleo-Mesoproterozoic Cuddapah Basin and its north-western and north-eastern margins. In the present study electrical method was used as a tool for delineation of Lamproite bodies in contrast with country rocks in Gundrapally, Vattikode and Marepally regions in parts of the North Eastern Dharwar Craton in Telangana State, India. The electrical profiling method was conducted in different direction to identify the variation of the lithology of the area due to the anisotropic nature and smaller size of the 2-D intrusive bodies adopting the Wenner electrode configuration. The electrical properties of the Lamproites tended to change with their composition due to weathering and the presence of Olivine and K-Al rich composition. The electrical response on the Lamproite pipes is shows a decrease in resistivity concerning the country-rock in the area.
Endoscopic Dacryocystorhinostomy With Ologen Implant
Authors: El-Hayes Ali Abd El-Hakam Ali , Eldemerdash Ashraf Ali , Mandour Sameh Saad , Mazar Hesham Mohamed El 
Published: January 2022

Abstract
Objective: To compare the effectiveness of endoscopic dacryocystorhinostomy with ologen implant versus endoscopic dacryocystorhinostomy with silicon tube implantation.Background: Chronic dacryocystitis is an inflammatory disorder of the lacrimal sac that is mostly accompanied by partial or total nasolacrimal duct obstruction. Watering and discharge are the most common symptoms, however some cases can escalate to serious ocular and extraocular complications. It can result in severe ocular morbidity and loss of productivity at work, as it can temporarily obscure vision, prevent a person from concentrating on their task, and be socially uncomfortable. The goal of this research is to find a way to reduce recurrence after DCR surgery.Methods: We conducted a prospective controlled study to evaluate effectiveness of endoscopic dacryocystorhinostomy with ologen implant versus endoscopic dacryocystorhinostomy with silicon tube implantation. A total of 40 patients underwent primary endoscopic DCR surgery in Menoufia University Hospital from march 2020 till march 2021. A total of 20 cases did endoscopic DCR using ologen implant (group A) and the other 20 cases did endoscopic DCR using silicon tube (group B). Results: The success rate, which was evaluated by MUNK score and syringing test, was compared between both groups also rate of complications like epistaxis, implant complications and post surgery synechiae was compared. Success rates was 75% in ologen group and 85%in the other group. Epistaxis, infection and post sugery synechiae were statistically in significant between the two groups but implant complications was more in ologen group than the other group.Conclusion: Endoscopic DCR with ologen implantation is not superior to endoscopic DCR with silicon stenting due to the challenging ologen implantation procedure and the high cost relative to silicon stenting.
Energy Dispersive X-Ray Microanalysis in conjunction with Scanning Electron Micrography to establish nematodes as bioindicators in marine fish environment
Authors: Yadav Anita , Kapoor Neerja , Arif Amin , MALHOTRA SANDEEP K 
Published: January 2022

Abstract
Energy Dispersive X-Ray Microanalysis (EDXMA) has been used as the non-invasive technique on Indian helminthes to explore the role of nematode parasites as bioindicators in the marine ecosystem of Central West coast of India for the first time. The investigation incorporates assertions on the possible benefit of such technology to elucidate bioremediating prospects that could be helpful to establish helminth parasites as a tool representing Bioindicators. The accumulation of Sulphur and Iron were analysed from a raphidascaridoid roundworm, Rostellascaris spinicaudatum (Malhotra and Anas) parasitizing marine catfish, Arius maculatus from the Central west coast of India at Goa. Quantitatively, the cuticle on oral armature comprised as much as ten times more Sulphur than iron content in the roundworm under study. However, only Carbon and Oxygen were detected over caudal papillae, where no metals or other elements were recorded.
Aspirin with Low-Dose Ticagrelor or with Low-Dose Rivaroxaban for Secondary Prevention: A Cost Per Outcome Analysis
Authors: Tsaban Gal , Alnsasra Hilmi , Nasasra Aref El , Abu-Salman Amjad , Abu-Dogosh Ala , Weissberg Itay , Golan Yael Ben-Baruch , Barrett Orit , Westreich Roi , Aboalhasan Enis , Azuri Joseph , Hammerman Ariel , Arbel Ronen 
Published: January 2022

Abstract
Introduction: Secondary prevention of cardiovascular events among patients with diagnosed cardiovascular disease and high ischemic risk poses a significant challenge in clinical practice. The combinations of aspirin with low dose (LD) Ticagrelor or LD-Rivaroxaban have shown superiority in preventing major adverse cardiovascular events (MACE) than aspirin treatment alone. The comparative value for money of these two regimens remains unexplored.Methods: We analyzed each regimen's annual cost needed to treat (CNT) by multiplying the annualized number needed to treat (aNNT) by the annual cost of each drug. The aNNTs were based on outcome data from PEGASUS TIMI-54 and COMPASS trials. Scenario analyses were performed to overcome variances in terms of population risk. Costs were based on 2021 US prices. The primary outcome was defined as CNT to prevent one MACE across the two regimens. Secondary value analysis was performed for myocardial infarction (MI), stroke, and CV death as separate outcomes. Results: The aNNTs to prevent MACE with LD-Ticagrelor and with LD-Rivaroxaban were 229 [95% confidence interval (CI):141-734] and 147 (95%CI:104-252), respectively. At an annual cost of 3,618$ versus 4,308$, the corresponding CNTs were 828,478$ (95%CI:510,111$-2,655,471$) with LD-Ticagrelor and 633,270$ (95%CI:448,028$-1,085,607$) with LD-Rivaroxaban. LD-Rivaroxaban.Conclusion: Combining aspirin with LD-Rivaroxaban provides better value for money than with LD-Ticagrelor for secondary prevention of MACE.
On Maintenance and Metabolisms in Soil Microbial Communities
Authors: Dijkstra Paul , Wu Weichao , Dippold Michaela , Schwartz Egbert , Hungate Bruce , Megonigal Patrick , Thomas Scott , Seymour Cale , Martinez Ayla 
Published: January 2022

Abstract
Biochemistry is an essential yet often undervalued aspect of soil ecology, especially in soil C cycling. We assume based on tradition, intuition or hope that the complexity of biochemistry is confined to the microscopic world, and can be ignored when dealing with whole soil systems. This opinion paper draws attention to patterns caused by basic biochemical processes that permeate the world of ecosystem processes. From these patterns, we can estimate activities of the biochemical reactions of the central C metabolic network and gain insights into the ecophysiology of microbial biosynthesis and growth and maintenance energy requirements; important components of Carbon Use Efficiency (CUE).The biochemical pathways used to metabolize glucose vary from soil to soil, with mostly glycolysis in some soils, and pentose phosphate or Entner-Doudoroff pathways in others. However, notwithstanding this metabolic diversity, glucose use efficiency is high and thus substrate use for maintenance energy and overflow respiration is low in these three soils. These results contradict current dogma based on four decades of research in soil ecology. We identify three main shortcomings in our current understanding of substrate use efficiency: 1) in numeric and conceptual models, we lack appreciation of the strategies that microbes employ to quickly reduce energy needs in response to starvation; 2) production of exudates and microbial turnover affect whole-soil CUE more than variation in maintenance energy demand; and 3) whether tracer experiments can be used to measure the long-term substrate use efficiency of soil microbial communities depends critically on the ability of non-growing cells to take up tracer substrates, how biosynthesis responds to these substrates, as well as on how cellular activities scale to the community level.To move the field of soil ecology forward, future research must consider the details of microbial ecophysiology and develop new tools that enable direct measurement of microbial functioning in intact soils. We submit that 13C metabolic flux analysis is one of those new tools.
Causal and Putative Pathogenic Mutations Identified in 38.6% of Children with Primary SRNS in South Africa
Authors: Nandlal Louansha , Winkler Cheryl A. , Bhimma Rajendra , Cho Sungkweon , Nelson George W. , Haripershad Sudesh , Naicker Thajasvarie 
Published: January 2022

Abstract
The aim was to identify causal mutations in genes implicated in steroid resistant nephrotic syndrome (SRNS) within a South African population. We enrolled 119 children with primary NS; 71 SRNS and 48 steroid-sensitive NS. All children with SRNS underwent kidney biopsy. We first genotyped the NPHS2 gene for the p.V260E variant in all NS cases (n= 119) and controls (n= 219). To further identify additional variants, we performed whole-exome sequencing and interrogated ten genes (NPHS1, NPHS2, WT1, LAMB2, ACTN4, TRPC6, INF2, CD2AP, PLCE1, MYO1E) implicated in SRNS/FSGS in 56 SRNS cases and 29 controls; we also performed exome sequencing on two patients carrying the NPHS2 p.V260E mutation as positive controls. The overall detection rate of pathogenic mutations in children with SRNS was 27/70(38.57%): 15(21.43%) carried the NPHS2 p.V260E mutation and 12(17.14%) carried a pathogenic mutation in the heterozygous state in INF2 (n=8), CD2AP (n=3) or TRPC6 (n=1) genes. NPHS2 p.V260E homozygosity was specifically associated with biopsy-proven FSGS, accounting for 23.81% of Black children (15 of 63) with SR-FSGS. No causal mutations were identified in NPHS1, WT1, LAMB2, PLCE1, MYO1E and ACTN4. We report four novel variants in INF2, PLCE1, ACTN4 and TRPC6.Conclusion: The NPHS2 p.V260E mutation is a prevalent cause of SR-FSGS among Black South African children occurring in 23.81% of children with SRNS. Screening all Black African children presenting with NS for NPHS2 p.V260E will provide a precision diagnosis of SR-FSGS and inform clinical management.
Determinants of Therapy Failure Among Adults on First-line Antiretroviral Therapy in Asmara, Eritrea: A Multicenter Retrospective Matched Case-control Study
Authors: Mengistu Samuel Tekle , Ghebremeskel Ghirmay Ghebrekidan , Ghebrat Hermon Berhe , Achila Oliver Okoth , Yohannes Nahom Asmerom , Ghebrenegus Amon Solomon , Gebretsadik Filimon , Yeibyo Naod , Andegiorgish Amanuel Kidane , Mesfn Araya Berhane , Leake Negassi 
Published: January 2022

Abstract
Background Information on treatment failure (TF) in People living with HIV in data-poor jurisdictions is necessary to counter the rapidly escalating epidemic of TF to first-line combined anti-retroviral therapies (cART) in sub-Saharan Africa (SSA). In this study, we examined the risk factors associated with TF in Asmara, Eritrea.Methods: A multicenter, retrospective 1:2 matched (by age and gender) case-control study was conducted in four major hospitals in Asmara, Eritrea on adults aged >15 years who were on treatment for at least 6 months. Cases were patients with viral load ≥1000 copies/mL anytime between 2019-2021 and/or patients switched to second line cART. Controls were randomly selected from patients on first-line ART with viral load < 1000 copies/mL. Data was extracted using a checklist from the master data set and analyzed using SPSS version 26. Multivariable logistic regression analysis was conducted to identify risk factors for TF. All p-values were 2-sided and the level of significance was set at p < 0.05 for all analyses.Results: Of the 1068 participants, 585 (54.7%) were females. The median age at treatment initiation was 46 years (interquartile range (IQR): 39–51). Median time to combined antiretroviral therapy (cART) failure was 37 months (IQR =24–47). In multivariate analysis factors associated with increased likelihood of virologic failure (VF) were the type of initially used nucleoside reverse transcriptase inhibitors (NRTI) backbone ( (Zidovudine+Lamivudine (AZT+3TC): adjusted odds ratio (aOR): 2.70; 95% Confidence interval (CI): 1.65-4.41, p-value<0.001), (Abacavir+lamivudine (ABC+3TC): aOR: 4.73; 95%CI: 1.18-18.92, p-value=0.028), and (Stavudine+Lamivudine (D4T+3TC): aOR: 5.00; 95% CI: 3.03-8.20, p-value<0.001), prior exposure to ART (aOR: 2.28; 95%CI:1.35–3.86; p=0.002), record of sub-optimal drug adherence (aOR: 3.08; 95%CI: 2.22–4.28; p<0.001), ambulatory/bedridden at presentation (aOR:1.61; 95%CI: 1.12-4.28; p-value=0.010), presence of comorbidities (aOR: 2.37; 95%CI: 1.36-4.10, p-value=0.002), duration of cART (<5 years: aOR: 5.90; 95% CI: 3.95-8.73, p-value<0.001), and use of SMX-TMP prophylaxis ( aOR : 2.00, 95%CI, 1.44-2.78, p-value<0.001). Conclusion: Our findings underscore the importance of optimizing cART adherence, diversification of cART regimens, and interventions directed at enhancing early HIV diagnosis, prompt initiations of treatment and improved patient focused monitoring of treatment response.
Feature Data-driven Reinforced Fuzzy Radial Basis Function Neural Network Classifier With the Aid of Preprocessing Techniques and Particle Swarm Optimization
Authors: Park Sang-Beom , Oh Sung-Kwun , Pedrycz Witold 
Published: January 2022

Abstract
In this study, reinforced fuzzy radial basis function neural networks (FRBFNN) classifier driven by feature extracted data completed with the aid of effectively preprocessing techniques and evolutionary optimization, and its comprehensive design methodology are introduced. An Overall structure of the reinforced FRBFNN comprises the preprocessing part, the premise part and the consequence part of fuzzy rules of the network. In the preprocessing part, four types of preprocessing algorithms such as principal component analysis (PCA), linear discriminant analysis (LDA), combination of PCA and LDA (Hybrid PCA) and fuzzy transform (FT) are considered. To extract feature data suitable to characterize signal data, the feature extraction of information data is carried out through the dimensionality reduction done by the preprocessing technique, and then the reduced data are used as the input to the FRBFNN classifier. In the premise part of fuzzy rules of the network, the number of fuzzy rules is determined according to the number of clusters by fuzzy c-means (FCM) clustering. The fitness values of individual fuzzy rules are obtained based on data distribution. In the consequence part of fuzzy rules of the network, the parameters of connection weights located between the hidden layer and the output layer of FRBFNN classifier are estimated by means of the least square estimation (LSE). Particle swarm optimization (PSO) is exploited for structural as well as parametric optimization in the FRBFNN classifier. The parameters to be optimized by PSO are related to six factors such as the determination of whether to use data preprocessing, the type of data preprocessing technique, the number of input variables reduced by the preprocessing technique, fuzzification coefficient (FC) and the number of fuzzy rules used in fuzzy c-means (FCM) clustering, and the type of connection weights. By using diverse benchmark dataset obtained from UCI repository, the classification performance of the reinforced FRBFNN classifier was evaluated. Through a variety of classification algorithms existed in the Weka data mining software (Weka), the classification performance of the reinforced FRBFNN classifier was compared as well. The superiority of the proposed classifier is demonstrated through Friedman test. Furthermore, we assessed the classification performance of the reinforced FRBFNN classifier applied to black plastic wastes spectral data acquired from Raman and Laser induced breakdown spectroscopy (LIBS) equipment for the practical application of the material sorting system of the black plastic wastes.