bluuebunny/crossref_metadata_2025_split huggingface dataset:
Unraveling the Mechanisms of Income Inequality on Economic Growth in Ethiopia: Insights from Empirical Analysis
Authors: Hordofa Dereje Fedasa 
Published: March 2023

Abstract
The aim of this research was to investigate how income inequality impacts the economic growth of Ethiopia by analyzing the various ways in which it influences economic growth. The study gathered an exclusive dataset from diverse secondary sources that ranged from 1981 to 2016. To examine the link between transmission channels, inequality of income, and growth, the study utilized a stepwise regression autoregressive distributed lag (ARDL) approach. The research concluded with four lines of reasoning, including political economy, innovation, fertility, and saving channels. According to the findings, inequality of income has a positive impact on innovative activities and total savings as measured by gross fixed capital formation, but it only has a negative and significant effect on economic growth through the channels of innovation and savings. While caution should be taken when generalizing the findings to other countries, this study offers valuable insights into the intricate link between income inequality and economic growth specifically in Ethiopia. The study recommends that policymakers implement targeted policies to address the different transmission channels through which income inequality affects economic growth, to comprehensively tackle this issue.
Mapping Almond Stem Water Potential using Machine Learning
Authors: Savchik Peter , Nocco Mallika , Kisekka Isaya 
Published: March 2023

Abstract

Almonds are a major crop in California which produces 80% of all the world’s almonds. Widespread drought and strict groundwater regulations pose significant challenges to growers. Irrigation regimes based on observed crop water status can help to optimize water use efficiency, but consistent and accurate measurement of water status can prove challenging. In almonds, crop water status is best represented by midday stem water potential measured using a pressure chamber, which despite its accuracy is impractical for growers to measure on a regular basis. This study aimed to use machine learning (ML) models to predict stem water potential in an almond orchard based on canopy spectral reflectance, soil moisture, and daily evapotranspiration. Both artificial neural network and random forest models were trained and used to produce high resolution spatial maps of stem water potential covering the entire orchard. Also, for each ML model type, one model was trained to predict raw stem water potential values, while another was trained to predict baseline-adjusted values. Together, all models resulted in an average coefficient of correlation of R2=0.73 and an average root mean squared error (RMSE) of 2.5 bars. Prediction accuracy decreased significantly when models were expanded to spatial maps (R2=0.33, RMSE=3.31 [avg]). These results indicate that both artificial neural networks and random forest frameworks can be used to predict stem water potential, but both approaches were unable to fully account for the spatial variability observed throughout the orchard. Random forest models predicting raw stem water potential produced the most accurate maps. Overall, the most accurate maps were produced by the random forest model (raw stem water potential R2=0.47, RMSE=2.71). Being able to predict stem water potential spatially can aid in the implementation of variable rate irrigation. These results indicate that both artificial neural network and random forest frameworks can be used effectively to predict and map stem water potential, but that both approaches are unable to fully account for the spatial variability observed throughout the orchard. Future studies should examine the impact of utilizing stem water potential maps as an irrigation decision guide.
Pi calculation reinvented a Trigonometry
Authors: ALMUAIGEL SAMI I 
Published: March 2023

Abstract
In this paper, we present a novel method of determining the mathematical value of pi by utilizing the relationship between pi and the tangent function in trigonometry. By examining the relationship between the circumference of a circle and a right-angled triangle, we are able to derive a new equation for pi, which can be used to simplify mathematical and physical equations that involve pi.
On-going evidence on SARS-CoV-2 furin site arginine codon usage bias and new found PRRA-like insertions
Authors: Romeu Antonio R. 
Published: March 2023

Abstract
The origin of SARS-CoV-2 lies in the gain-of-function related to the PRRA spike glycoprotein polybasic furin cleavage site (FCS). The CGG-CGG arginine pair code is unique and rare in the virus. However, novel viruses found in Laos can be considered SARS-CoV-2 ancestors, but they do not have the PRRA. At this point, I have described: (i) the 100% match between the exogenous S gene fragmentencoding PRRA andhuman mRNA RefSeq transcripts; (ii) the related genes are highly expressed in virustarget tissues; (iii) PRRA arginine codon usage bias; (iv) PRRA-like insertions; and (v) the PRRA human origin hypothesis. The aim of this workis to provide further support tothishypothesis. Based on current SARS-CoV-2 sequences (January-March, 2023), here I show that 43 out of 10,644 (0.42 %) GISAID Africa, Asia, Europe and the USA complete genomes and 613 out of 134,022 (0.45 %) NCBI-Virus spike glycoprotein sequences had the CGG-CGG code optimized. The results are in agreement with those in previous works that reveal a viral FCS arginine codon usage bias. Here I also show new found spike glycoprotein PRRA-like insertions (100% match to human mRNA RefSeq transcripts and related genes virus target tissue specifics). In these PRRA-like insertions the human mRNA transcripts should be the origin of the coding S gene fragments. Human is the host of the involved SARS-CoV-2 specimens. They are human viruses isolated from infected human cells. The origin cannot be genetic material from other viruses. Regarding the mechanism, it would be the most common in viruses evolution: recombination. The evolutionary success of the PRRA-like insertions lies in the respect of the reading frame on S gene translation. Results suggest that PRRA spike glycoprotein insertion in a SARS-CoV- ancestor was not an isolated evolutionary event, but rather common in virus evolution.
Plasmodium falciparum Histo-Aspartic Protease (HAP) inhibitor: Toxicity Investigation and Docking Study of 2-(2-benzoyl-4-methylphenoxy)quinoline-3-carbaldehyde derivatives
Authors: Aina Oluwafemi S. , Bello Adebayo J. , Adams Luqman A. , Familoni Oluwole B. 
Published: March 2023

Abstract
Aspartic proteases possess catalytic sites for hydrolysis of peptide bonds which makes them potentials drug target in the malaria parasites. Inhibiting Histo-Aspartic Protease (HAP), aspartate (Asp215) and histidine (His32) residues of the P. falciparum disrupts the growth phase and ability to catalyse erythrocyte hemoglobin degradation. We synthesized compound 5; 2-(2-benzoyl-4-methylphenoxy)quinoline-3-carbaldehyde via Vilsmier-Hack and sp2 C-H activation protocols. We then designed fifty hypothetical compounds A1-A50 which were screened in-silico for their toxicity, pharmacokinetics, bioactivity score and binding affinities. Nine lead compounds showed no toxicity to human cells. Ten standard antimalarial drugs were used as reference. The lead compounds were generally within (-0.28 to 0.32) as highly or moderately bioactive for six bioactivity score parameters. Compounds A31 had (-11.3 kcal/mol) and A5 (-11.2 kcal/mol) binding energies. Mefloquine with (-9.6 kcal/mole) was best reference drug coming in position 9. Whilst compound A31 and mefloquine both showed no interactions with either Asp215 or His32 in the binding pockets, compound A5 showed π-π stacking interactions. . We opine therefore, that based on other drug-likeness parameters investigated, compound A5; 2-(2-benzoyl-4-methylphenoxy)-7-methylquinoline-3-carbaldehyde can be recommended as a possible candidate for new antimalarial drug development in line with SDG goal 3 on health and well-being.
Epidemiological Profile of Malaria in a Rural Community From the Amazon of Mato Grosso
Authors: De Oliveira Elaine Cristina , Santos Emerson Soares dos , Junior Paulo Antonio Ferreira , Atanaka-Santos Marina , Leite Maria Clara Pereira , Trettel Ana Cláudia Pereira Terças , Lemos Elba Regina Sampaio , Fontes Cor Jesus Fernandes 
Published: March 2023

Abstract

More than 95% of malaria transmission in Brazil occurs in the region called Legal Amazon constituted among other Brazilian states, including Mato Grosso, where, in 2015, 54% of the cases occurred in the municipality of Colniza, in the northwestern region of the state.
Objetive: To describe the epidemiological profile of malaria in a rural community in the northwestern region of Mato Grosso, emphasizing its spatial pattern of occurrence.
Methods: This is an ecological study covering information on the prevalence of plasmodium infection and on the use and occupation of soil by the population of the Três Fronteiras District, in the municipality of Colniza, Mato Grosso. Data were collected through a home visit in July 2011, with blood collection from the digital pulp for the preparation of a thick smear slide, completion of the SIVEP_Malaria notification form, for the construction of a georeferenced database with the software ArcGIS 9.2 (ESRI Corp.). The information was divided into use and occupation classes. In TerraView 3.14, a Kernel map was built to verify the density of cases and their location.
Results: Of the 621 respondents, 68(11%) had plasmodium infection, 39(57.4%) of them by P. vivax, 27(39.7%) by P. falciparum and two (2.9%) with mixed infection. Among infected individuals, 49(72.1%) were men and 19(27.9%), women. The distribution of prevalent cases of infection by overlaying the map of occupation and use of land showed that the cases of malaria are distributed over the entire length of the district, with greater occurrence of cases per household in open areas, close to the mining company/artisanal mining. The kernel method, from the characterization of the spatial distribution pattern of malaria cases, allowed identifying areas of greater intensity of cases, whose so-called “hot” areas were located in the gold mining region.
Conclusion: The transmission of malaria in the district of Três Fronteiras has a heterogeneous profile along its length, and the individuals residing in areas of mining, artisanal mining and timber extraction has increased frequency of infection by plasmodium, and its spatial pattern has a difference in the intensity of distribution of the disease.
Digitalisierung (nicht nur) im Dienst der Inklusion in der Lehramtsausbildung der sprachlichen Kernfächer
Authors: Blume Carolyn , Marci-Boehncke Gudrun 
Published: March 2023

Aufgrund der Relevanz der Medien- bzw. digitalen Kompetenz zur Teilhabe in der digital mediatisierten Gesellschaft sind das Wissen und die Einstellung von angehenden Lehrkräften in den sprachlichen Kernfächern diesbezüglich zentrale Fragen. In den wenigen vorhandenen Untersuchungen zur Medien- oder digitalen Kompetenz sind allerdings fachbezogene Unterschiede kaum repräsentiert. Ebenso fehlen empirische Analysen zur inklusiven Medienbildung und der wahrgenommenen Relevanz dieser Themen aus Sicht der Lehrenden. Anhand paralleler Befragungen von Lehramtsstudierenden und Lehrenden in den Fächern Deutsch und Englisch wird die selbstwahrgenommene (pädagogische) Medienkompetenz sowie die Relevanz von der Medien- bzw. digitalen Bildung für inklusive Schulsettings von Studierenden untersucht und mit der thematischen Vermittlung und Relevanzerkennung durch Lehrende verglichen. Es zeigt sich ein heterogenes Bild von Lehramtsstudierenden sowohl hinsichtlich der selbstwahrgenommenen (pädagogischen) Medienkompetenz als auch der Inklusionskompetenz. Bei einer hohen erkannten Relevanz identifizieren die Studierenden den Bedarf nach gezielten Lehr-/Lerngelegenheiten. Inwiefern diese flächendeckend angeboten werden, kann aufgrund einer limitierten Rücklaufquote der Lehrenden nur bedingt eruiert werden. Es drängt sich die Frage nach den Gründen für die niedrige Beteiligung auf und ob diese Tatsache mit den Einstellungen und Kompetenzen der Lehrenden in Verbindung gebracht werden muss. Diese Frage wird in diesem Artikel eruiert, bleibt allerdings unbeantwortet.

AbstractDue to the relevance of media or digital competence for participation in digitally mediatized society, the knowledge and attitudes of prospective teachers in the core language subjects are central issues. In the few existing studies in this area, however, subject-related differences are rarely represented. Similarly, there is a lack of empirical analyses on inclusive media education and the perceived relevance of these topics from the perspective of their teachers, the university lecturers. Parallel surveys of pre-service teachers and university lecturers in the subjects German and English were conducted to examine students’ self-perceived media (pedagogical) competence as well as the perceived relevance of media or digital education for inclusive school settings. This was compared with how university lecturers addressed these topics and assessed their relevance for future teachers. It was found that pre-service teachers’ self-perceived media (pedagogical) competence and inclusive competence vary widely. Recognizing these topics as highly relevant, the pre-service teachers identify the need for targeted teaching/learning opportunities. The extent to which these are offered across the board can only be limitedly determined, due to a limited response rate from the lecturers. The question arises as to what attitudes and competences these lecturers hold.
Anesthesia and Cancer: Something More than Avoiding Stress Response
Authors: Ruiz Juan Carlos Molina , Guerrero Orriach Jose Luis , Ponferrada Aida Raigon , Romero Molina Salvador , Josefa Gomez Maldonado 
Published: March 2023

Abstract:
Currently, an increasing prevalence has been reported in incidences of tumor pathologies.
The influence of anesthetics drugs has been the subject of numerous studies. It has been reported that
the use of certain drugs may have an impact on prognosis and survival. By investigating the action of
these drugs on different metabolic pathways and their mechanisms of action, we can better understand
how they influence various hallmarks of carcinogenesis and determine their potential impact on cancer
progression. Some of the action pathways are widely known within oncology, being targets of specific
treatments, such as PI3k/AKT/mTOR, EGFR, and Wnt/ β-catenin.

:
This review performs a thorough dissection of the interaction between anesthetic drugs and oncological
cell lines through cell signaling pathways and genetic, immune, and transcriptomic pathways.
Through these underlying mechanisms, it aims to clarify the effect of the choice of anesthetic drug and
its potential influence on the prognosis of oncological surgery.
MT1G Regulates c-MYC/P53 Signal to Inhibit Proliferation, Invasion
and Migration and Promote Apoptosis in Colon Cancer Cells
Authors: Li Jie , Hu Qiaozhen , Li Zhongyan , Feng Kaiyu , Li Kangbao 
Published: March 2023

Introduction::
Colon cancer is a common and malignant cancer featuring high
morbidity and poor prognosis.

Aim::
This study was performed to explore the regulatory role of MT1G in colon cancer
as well as its unconcealed molecular mechanism.

Methods::
The expressions of MT1G, c-MYC, and p53 were assessed with the
application of RT-qPCR and western blot. The impacts of MT1G overexpression on the
proliferative ability of HCT116 and LoVo cells were measured by CCK-8 and BrdU
incorporation assays. Additionally, transwell wound healing, and flow cytometry assays
were employed to evaluate the invasive and migrative capacities as well as the
apoptosis level of HCT116 and LoVo cells. Moreover, the activity of the P53 promoter
region was assessed with the help of a luciferase reporter assay.

Results::
It was found that the expressions of MT1G at both mRNA and protein levels
were greatly decreased in human colon cancer cell lines, particularly in HCT116 and
LoVo cell lines. After transfection, it was discovered that the MT1G overexpression
suppressed the proliferation, migration and invasion but promoted the apoptosis of
HCT116 and LoVo cells, which were then partially reversed after overexpressing c-MYC.
Additionally, MT1G overexpression reduced c-MYC expression but enhanced the p53
expression, revealing that the MT1G overexpression could regulate c-MYC/P53 signal.
Elsewhere, it was also shown that c-MYC overexpression suppressed the regulatory
effects of MT1G on P53.

Conclusion::
To conclude, MT1G was verified to regulate c-MYC/P53 signal to repress
the proliferation, migration and invasion but promote the apoptosis of colon cancer cells,
which might offer a novel targeted-therapy for the improvement of colon cancer.
HDAC4-mediated Deacetylation of Glutaminase Facilitates Glioma
Stemness
Authors: Xu Gang , Qu Jianqiang , Zhang Ming 
Published: March 2023

Background:
Inhibiting cancer metabolism via glutaminase (GLS) is a promising strategy
to disrupt tumor progression. However, the mechanism regarding GLS acetylation remains largely unknown.

Methods:
Mitochondrial protein isolation and glutaminase activity assay were used to examine GLS
activity. RT-qPCR, western blot, sphere-formation, ALDH activity, and tumor-initiating assays were
performed to evaluate the alteration of cell stemness. Co-IP and rescuing experiments were conducted
to explore the underlying mechanisms.

Results:
In this study, we demonstrated that GLS acetylation is a vital post-translational modification
that inhibits GLS activity in glioma. We identified GLS as deacetylated by HDAC4, a class II deacetylase.
GLS acetylation stimulated the interaction between GLS and SIRT5, thereby promoting GLS
ubiquitination and inhibiting GLS activity. Furthermore, GLS overexpression suppressed the stemness
of glioma cells, which was rescued by the deacetylation of GLS.

Conclusion:
Our findings reveal a novel mechanism of GLS regulation by acetylation and ubiquitination
that participate in glioma stemness.
Exploring the Molecular Structural Requirements of Flavonoids as Beta-
Secretase-1 Inhibitors Using Molecular Modeling Studies
Authors: More Uttam A. , Noolvi Malleshappa N. , Kumar Devendra , Tripathi Avanish 
Published: March 2023

Background::
BACE1 (beta-site amyloid precursor protein (APP) cleaving enzyme) is a key
target for Alzheimer's disease research because it catalyses the rate-limiting step in the formation of
amyloid protein (Aβ). Natural dietary flavonoids have gained a lot of interest as potential Alzheimer's
therapy candidates because of their anti-amyloidogenic, antioxidative, and anti-inflammatory properties.
More research is needed, however, to learn more about the specific routes through which flavonoids
may have neuroprotective benefits in Alzheimer's disease.

Objective::
Here, we report an in silico molecular modeling study for natural compounds, particularly
flavonoids, as BACE-1 inhibitors.

Methods::
The interactions of flavonoids with the BACE-1 catalytic core were disclosed by demonstrating
the predicted docking pose of flavonoids with BACE-1. The stability of flavonoids BACE-1
complex was analyzed by molecular dynamic simulation (standard dynamic cascade).

Results::
Our findings imply that these flavonoids, which have methoxy group instead of hydroxy may
be promising BACE1 inhibitors that could reduce Aβ formation in Alzheimer's disease. The molecular
docking study revealed that flavonoids e bind with the BACE1’s wide active site along with the catalytic
residues Asp32 and Asp228. Further molecular dynamic investigation revealed that the average
RMSD for all complexes ranged from 2.05 to 2.32 Å, indicating that the molecules were relatively
stable during MD simulation. The RMSD analyses demonstrate that the flavonoids were structurally
stable during the MD simulation. The RMSF was utilised to study the time-dependent fluctuation of
the complexes. The N-terminal (~2.5 Å) fluctuates less than the C-terminal (~6.5 Å). Rutin and Hesperidin
were highly stable in the catalytic region as compared to other flavonoids like Rhoifolin, Hesperidin,
Methylchalcone, Phlorizin and Naringin.

Conclusion::
We were able to justify the flavonoids' selectivity for BACE-1 and crossing BBB for the
treatment of Alzheimer's disease by using a combination of molecular modelling tools.
Biomarkers for Diabetic Nephropathy with a Focus on Kidney Injury
Molecule-1 (KIM-1)
Authors: Khonsha Fatemeh , Valilo Mohammad , Nejabati Hamid-Reza , Rahmati-Yamchi Mohammad , Mota Ali 
Published: March 2023

Abstract:
Diabetic Nephropathy (DN), with an increasing rate of mortality and morbidity, is considered
the main cause of End-Stage Renal Disease (ESRD). A wide spectrum of biomarkers exist
for early detection of DN, but they suffer from low specificity and sensitivity, indicating the urgent
demand for finding more effective biomarkers. Also, the pathophysiology of tubular damage and
its relation to DN are not yet completely understood. Kidney Injury Molecule-1 (KIM-1) is a protein
that is expressed at substantially low contents in the kidney under physiological conditions. A
number of reports have demonstrated the close relationship between urine and tissue KIM-1 levels
and kidney disorders. KIM-1 is known as a biomarker for diabetic nephropathy and renal injury. In
this study, we aim to review the potential clinical and pathological roles of KIM-1 in diabetic
nephropathy.
Computer-aided Drug Discovery Approaches in the Identification of
Natural Products against SARS-CoV-2: A Review
Authors: Junqueira Ribeiro Mariana Martinelli 
Published: March 2023

Abstract:
The COVID-19 pandemic is raising a worldwide search for compounds that could act
against the disease, mainly due to its mortality. With this objective, many researchers invested in
the discovery and development of drugs of natural origin. To assist in this search, the potential of
computational tools to reduce the time and cost of the entire process is known. Thus, this review
aimed to identify how these tools have helped in the identification of natural products against
SARS-CoV-2. For this purpose, a literature review was carried out with scientific articles with
this proposal where it was possible to observe that different classes of primary and, mainly, secondary
metabolites were evaluated against different molecular targets, mostly being enzymes and
spike, using computational techniques, with emphasis on the use of molecular docking. However,
it is noted that in silico evaluations still have much to contribute to the identification of an anti-
SARS-CoV-2 substance, due to the vast chemical diversity of natural products, identification and
use of different molecular targets and computational advancement.