bluuebunny/crossref_metadata_2025_split huggingface dataset:
Chikungunya virus time course infection of human macrophages reveals intracellular signaling pathways relevant to repurposed therapeutics
Authors: Gray Madison , Guerrero-Arguero Israel , Solis-Leal Antonio , Robison Richard A. , Berges Bradford K. , Pickett Brett E. 
Published: March 2022

Background
Chikungunya virus (CHIKV) is a mosquito-borne pathogen, within the Alphavirus genus of the Togaviridae family, that causes ~1.1 million human infections annually. CHIKV uses Aedes albopictus and Aedes aegypti mosquitoes as insect vectors. Human infections can develop arthralgia and myalgia, which results in debilitating pain for weeks, months, and even years after acute infection. No therapeutic treatments or vaccines currently exist for many alphaviruses, including CHIKV. Targeting the phagocytosis of CHIKV by macrophages after mosquito transmission plays an important role in early productive viral infection in humans, and could reduce viral replication and/or symptoms.

Methods
To better characterize the transcriptional response of macrophages during early infection, we generated RNA-sequencing data from a CHIKV-infected human macrophage cell line at eight or 24 hours post-infection (hpi), together with mock-infected controls. We then calculated differential gene expression, enriched functional annotations, modulated intracellular signaling pathways, and predicted therapeutic drugs from these sequencing data.

Results
We observed 234 pathways were significantly affected 24 hpi, resulting in six potential pharmaceutical treatments to modulate the affected pathways. A subset of significant pathways at 24 hpi includes AGE-RAGE, Fc epsilon RI, Chronic myeloid leukemia, Fc gamma R-mediated phagocytosis, and Ras signaling. We found that the MAPK1 and MAPK3 proteins are shared among this subset of pathways and that Telmisartan and Dasatinib are strong candidates for repurposed small molecule therapeutics that target human processes. The results of our analysis can be further characterized in the wet lab to contribute to the development of host-based prophylactics and therapeutics.
A machine learning approach for identification of gastrointestinal predictors for the risk of COVID-19 related hospitalization
Authors: Lipták Peter , Banovcin Peter , Rosoľanka Róbert , Prokopič Michal , Kocan Ivan , Žiačiková Ivana , Uhrik Peter , Grendar Marian , Hyrdel Rudolf 
Published: March 2022

Background and aim
COVID-19 can be presented with various gastrointestinal symptoms. Shortly after the pandemic outbreak, several machine learning algorithms were implemented to assess new diagnostic and therapeutic methods for this disease. The aim of this study is to assess gastrointestinal and liver-related predictive factors for SARS-CoV-2 associated risk of hospitalization.

Methods
Data collection was based on a questionnaire from the COVID-19 outpatient test center and from the emergency department at the University Hospital in combination with the data from internal hospital information system and from a mobile application used for telemedicine follow-up of patients. For statistical analysis SARS-CoV-2 negative patients were considered as controls in three different SARS-CoV-2 positive patient groups (divided based on severity of the disease). The data were visualized and analyzed in R version 4.0.5. The Chi-squared or Fisher test was applied to test the null hypothesis of independence between the factors followed, where appropriate, by the multiple comparisons with the Benjamini Hochberg adjustment. The null hypothesis of the equality of the population medians of a continuous variable was tested by the Kruskal Wallis test, followed by the Dunn multiple comparisons test. In order to assess predictive power of the gastrointestinal parameters and other measured variables for predicting an outcome of the patient group the Random Forest machine learning algorithm was trained on the data. The predictive ability was quantified by the ROC curve, constructed from the Out-of-Bag data. Matthews correlation coefficient was used as a one-number summary of the quality of binary classification. The importance of the predictors was measured using the Variable Importance. A 2D representation of the data was obtained by means of Principal Component Analysis for mixed type of data. Findings with the p-value below 0.05 were considered statistically significant.

Results
A total of 710 patients were enrolled in the study. The presence of diarrhea and nausea was significantly higher in the emergency department group than in the COVID-19 outpatient test center. Among liver enzymes only aspartate transaminase (AST) has been significantly elevated in the hospitalized group compared to patients discharged home. Based on the Random Forest algorithm, AST has been identified as the most important predictor followed by age or diabetes mellitus. Diarrhea and bloating have also predictive importance, although much lower than AST.

Conclusion
SARS-CoV-2 positivity is connected with isolated AST elevation and the level is linked with the severity of the disease. Furthermore, using the machine learning Random Forest algorithm, we have identified the elevated AST as the most important predictor for COVID-19 related hospitalizations.
Relationship between circadian genes and memory impairment caused by sleep deprivation
Authors: Ke Peng , Zheng Chengjie , Liu Feng , Wu LinJie , Tang Yijie , Wu Yanqin , Lv Dongdong , Chen Huangli , Qian Lin , Wu Xiaodan , Zeng Kai 
Published: March 2022

Background
Sleep deprivation (SD)-induced cognitive impairment is highly prevalent worldwide and has attracted widespread attention. The temporal and spatial oscillations of circadian genes are severely disturbed after SD, leading to a progressive loss of their physiological rhythms, which in turn affects memory function. However, there is a lack of research on the role of circadian genes and memory function after SD. Therefore, the present study aims to investigate the relationship between circadian genes and memory function and provide potential therapeutic insights into the mechanism of SD-induced memory impairment.

Methods
Gene expression profiles of GSE33302 and GSE9442 from the Gene Expression Omnibus (GEO) were applied to identify differentially expressed genes (DEGs). Subsequently, both datasets were subjected to Gene Set Enrichment Analysis (GSEA) to determine the overall gene changes in the hippocampus and brain after SD. A Gene Oncology (GO) analysis and Protein-Protein Interaction (PPI) analysis were employed to explore the genes related to circadian rhythm, with their relationship and importance determined through a correlation analysis and a receiver operating characteristic curve (ROC), respectively. The water maze experiments detected behavioral changes related to memory function in SD rats. The expression of circadian genes in several critical organs such as the brain, heart, liver, and lungs and their correlation with memory function was investigated using several microarrays. Finally, changes in the hippocampal immune environment after SD were analyzed using the CIBERSORT in R software.

Results
The quality of the two datasets was very good. After SD, changes were seen primarily in genes related to memory impairment and immune function. Genes related to circadian rhythm were highly correlated with engagement in muscle structure development and circadian rhythm. Seven circadian genes showed their potential therapeutic value in SD. Water maze experiments confirmed that SD exacerbates memory impairment-related behaviors, including prolonged escape latencies and reduced numbers of rats crossing the platform. The expression of circadian genes was verified, while some genes were also significant in the heart, liver, and lungs. All seven circadian genes were also associated with memory markers in SD. The contents of four immune cells in the hippocampal immune environment changed after SD. Seven circadian genes were related to multiple immune cells.

Conclusions
In the present study, we found that SD leads to memory impairment accompanied by changes in circadian rhythm-related genes. Seven circadian genes play crucial roles in memory impairment after SD. Naïve B cells and follicular helper T cells are closely related to SD. These findings provide new insights into the treatment of memory impairment caused by SD.
Physicochemical and Microbiological Analysis of Ikogosi Warm Water Spring
Authors: Olaleye A. C. , Ilesanmi T. M. , Oladipo O. O. 
Published: March 2022

Introduction: Water is one of the indispensable natural resources for the continued existence of all living things including man.
Aims: This study investigated the bacterial diversity in Ikogosi warm spring in Ekiti State, Nigeria.
Methodology: Water samples were taken for analyses from Ikogosi warm spring and analyses were made of the hot stream, cold stream, and meeting point region. Twenty isolates were characterized by morphological, biochemical, physiological characteristics and thermophilic screening was carried out.
Results: The results revealed that electrical conductivity was 215.050 μmS/cm, (cold); 320.500 μmS/cm (warm), and 305 μmS/cm (meeting point), temperature was close (24.5oC, cold to 37oC, warm). pH, total dissolved solids and chlorine were all far below the WHO guideline values. Average ranges of the heavy metals in water samples were: 1.080, 0.424 and 0.343 ppm iron (Fe) in hot, cold and meeting point samples respectively, 0.010, 0.006 and 0.004 ppm lead (Pb) in hot, cold and meeting point samples respectively; and 0.006, 0.010 and 0.019 ppm chromium (Cr) in hot, cold and meeting point samples respectively. Nickel (Ni), Arsenic (As) and Cadmium (Cd) were not detected. Bacteria majorly found in water samples were Bacillus spp., Escherichia coli, Klebsiella spp. and Staphylococcus spp. Out of the twenty (20) isolates screened at high temperature range of 45oC to 65oC, all grew at 45oC and 50oC while nine (9) grew at 55oC. Only two isolates were able to survive at 60oC, while none grew at 65oC.
Conclusion: These isolates can be in the production of thermostable enzymes which can be used in biotechnology.
Determination of Seroprevalence and Associated Factors of Helicobacter Pylori Infection among Bangladeshi and Somalian Students
Authors: Nahar Ferdous Rabeya , Abubakar Mohamud Bashir , Md. Zahurul Haque Asna Shah , Moniruzzaman Mohammad 
Published: March 2022

Helicobacter pylori (H. pylori) infections are the prime health concern nowadays as this may lead to peptic ulcer diseases and several types of stomach cancer. Factors including genetic, socioeconomic, ecological, personal hygiene and sanitation, and bacterial features are accountable for the predominance and development of disease. This study aimed to determine the prevalence of H. pylori and their association with age, sex, food habits and source, irregular meals, and physical activities among Bangladeshi and Somalian students. Cross-sectional structured questionnaires were used to collect demographic, food habits and lifestyle data. A total 80 Bangladeshi (32) and Somalian (48) students participated in this study. Selected students were invited to the laboratory to provide blood samples for H. pylori IgG antibody detection through Enzyme Linked Immuno-sorbent Assay (ELISA) method. Data from the survey and laboratory were analyzed using SPPS v.26. Multivariate logistic regression analysis was conducted to find an association between H. pylori infection and factors. Around 55% of the participants were found seropositive. Among them Somalian students were prevalently higher than Bangladeshi students. Mostly younger males were found seropositive regardless of age and educational level. Multivariate analysis revealed gender (OR:4.524, CI:1.526-13.407), ethnic origin (OR:4.200, CI:1.622-10.872), skipping of meals (OR:8.600, CI:0.984-75.151) and breakfast (OR:11.205, CI: 3.740-33.568) and physical activity levels (OR:0.286, CI:0.113-0.721) were significantly linked with H. pylori infections. More than two-third Somalian students (68.7%) were infected with H. pylori whereas one-third of Bangladeshi students were found positive. Somalian students were found to be less active and the pattern of skipping meals and breakfast was higher compared to Bangladeshi counterparts. Somalian students probably carried H. pylori infection from their native land, and less physical activity and mistiming of taking meals enhanced the infection. Communication barriers and food preferences could be other reasons. To prevent this infection, we suggest cleanliness, a healthy life style and nutritious meals with adequate physical activities are obligatory.
Bharat’s Solar Energy: An Analysis Using Porters Diamond Model with a Brief on Ancient Past for Environmentally Sustainable Competitive Advantage
Authors: Kokku Randheer 
Published: March 2022

Objective of this paper is to analyze solar energy as environmentally sustainable area of competitive advantage for Bharat using diamond model with a brief on its ancient past. Bharat is time tested philosophy and culture. Ancient genesis of Bharat was scientifically strong, economically prosperous and socially enlighten with Sun being the centripetal force. Bharat’s solar energy industry is in developing stage. Its ancient vedic school system explored “Pancha Bhuta” (five elements) as sun, space, water, air and earth giving knowledge to conduct life cordially in coexistence with these elements. Upon analyzing environmentally sustainable areas using diamond model it is found that Bharat is in advantageous position in area of solar energy.
On solar energy front it is found Bharat has taken big leap with an objective of achieving 175 GW installation by 2025 of which 100 GW was achieved by 2020. Technological factor conditions PV and CSP of Bharat are highest in world and it stood second in 2017 on “Renewable Energy Attractiveness Index”. Geographical condition of four to seven kWh/m2 per day of solar energy is very favorable. Huge demand growth of 1118 Mtoe by 2025 to 1921 Mtoe by 2040 is driven by large solar energy corporations as front runners. Challenges to be addressed are grid connectivity, de-centralized production and consumption. To counter the perils of global warming, exploring solar energy as one of the environmentally sustainable areas is mandatory. Bharat can lead this race by creating competitive advantage derived from active support of government, innovation of low-cost solar technologies, present technologies and vedic history footing towards a sustainable future.
Development & Validation of RP-HPLC Method for Quantitative Estimation of Dasatinib and its Impurities in Pharmaceutical Dosage Form
Authors: Jogarao Y. S. R. V. S. , Bharath Ponnuri , Ramakrishna V. Siva , Ramachandran D. 
Published: March 2022

Aim: The primary objective of the research work is to develop a effective, sensitive, economical and simple reverse phase HPLC method for the separation and quantification of Dasatinib and its impurities are described in tablet formulations.
Study Design: HPLC based quantification studies.
Place and Duration of Study: Department of Chemistry, Acharya Nagarjuna University, Guntur, Andhra Pradesh between April 2021 and August 2021.
Methodology: Separation and quantification of Dasatinib and its impurities are done by using an Inertsil ODS-3V, 250 x 4.6 mm, 5µm and the mobile phase consists of two Channels A and B. Channel-A: pH 5.80 phosphate buffer : acetonitrile (90:10 v/v) and Channel-B: acetonitrile : water (90:10 v/v). The flow rate is 1.0 ml/min. The column temperature was maintained at 25°C and sample temperature was maintained at 25°C, injection volume 10 µL and wavelength fixed at 320nm UV-detection.
Results: There is no interference of diluent and placebo at Dasatinib and impurities peaks. The elution order and the retention times of impurities and Dasatinib obtained from individual standard preparations and mixed standard preparations are comparable.
The limit of detection (LOD) and limit of quantitation (LOQ) for Dasatinib standard 0.147&0.048 µg/mL, impurity-A 0.334&0.110 µg/mL, impurity-C 0.184&0.061 µg/mL, impurity-D 0.136&0.045 µg/mL, impurity-E 0.089&0.029 µg/mL and impurity-F 0.222 & 0.073 µg/mL respectively.
The linearity results for Dasatinib and all the impurities in the specified concentration range are found satisfactory, with a correlation coefficient greater than 0.99.Calibration curve was plotted and correlation co-efficient for Dasatinib and its impurities found to be 1.000, 0.9999, 0.9912, 1.000, 0.9932 and 0.9922 respectively.
The accuracy studies were shown as % recovery for Dasatinib and its impurities at specification level. The limit of % recovered shown is in the range of 80 and 120% and the results obtained were found to be within the limits. Hence the method was found to be accurate.
The method has validated as per ICH guidelines and all the validation parameters are satisfy the ICH Q2 specification acceptance limits
Conclusion: The developed LC method was validated with respect to specificity, precision, linearity, ruggedness and robustness. Therefore this method has high probability to adopt in pharmaceutical industry for regular analysis of Dasatinib tablet formulations.
Fast finite‐time adaptive fuzzy control for quantized stochastic uncertain nonlinear systems
Authors: Ren Pengxu , Wang Fang 
Published: March 2022

SummaryThe issue of fast finite‐time adaptive control is studied for quantized stochastic nonlinear systems. Unlike the existing works about fast finite‐time control, the input signals are quantized, and the stochastic disturbances and nonlinear functions are unknown. According to universal approximation capacity of fuzzy logic system, combined with backstepping technique, a novel fast finite‐time adaptive fuzzy control strategy of quantized stochastic nonlinear system is proposed. The nonlinear decomposition method is introduced to set up the relationship among the control signals and the quantization signals, which overcomes the technical difficulties result from the piecewise quantization input. The proposed tactics can assure the tracking error situate in a neighborhood of the origin point and the closed‐loop system signals keep bounded. Finally, an algorithm simulation is conducted to test the validity of the method.
Bearing‐based autonomous communication relay positioning under field‐of‐view constraints
Authors: Fabris Marco , Zelazo Daniel 
Published: March 2022

AbstractThis article investigates the problem of communication relay establishment for multiple agent‐based mobile units using a relay vehicle. The objective is to drive autonomously the relay vehicle to attain a position for communication relay establishment while maintaining the other vehicles inside of its field‐of‐view. A bearing‐based control law is proposed for the relay drone and designed for both single and multiple agents. We also provide a collision avoidance scheme that ensures no collisions between the relay and other agents. Numerical simulations and experimental results are reported as well to show the efficacy of the proposed approach.
“Drug‐Carrier” Synergy Therapy for Amyloid‐β Clearance and Inhibition of Tau Phosphorylation via Biomimetic Lipid Nanocomposite Assembly
Authors: Han Guochen , Bai Kaiwen , Yang Xiaoyu , Sun Chenhua , Ji Yi , Zhou Jianping , Zhang Huaqing , Ding Yang 
Published: March 2022

AbstractAmyloid‐β (Aβ) toxicity is considered to be companioned by Tau phosphorylation in Alzheimer's disease (AD). The clinical AD therapy is usually subjected to low blood‐brain barrier (BBB) penetration and complex interaction mechanisms between Aβ and phosphorylated Tau. A “Drug‐Carrier” synergy therapy is herein designed to simultaneously target Aβ and Tau‐associated pathways for AD treatment. To imitate natural nanoparticle configuration, the endogenous apolipoprotein A‐I and its mimicking peptide 4F fused angiopep‐2 (Ang) are sequentially grafted onto lipid nanocomposite (APLN), providing liberty of BBB crossing and microglia targeted Aβ clearance. For synergy treatment, methylene blue (MB) is further assembled into APLN (APLN/MB) for Tau aggregation inhibition. After intravenous administration, the optimized density (5 wt%) of Ang ligands dramatically enhances APLN/MB intracerebral shuttling and accumulation, which is 2.15‐fold higher than that Ang absent‐modification. The site‐specific release of MB collaborates APLN to promote Aβ capture for microglia endocytosis clearance and reduce p‐Tau level by 25.31% in AD pathogenesis. In AD‐Aβ–Tau bearing mouse models, APLN/MB can relieve AD symptoms, rescue neuron viability and cognitive functions. Collectively, it is confirmed that “Drug‐Carrier” synergy therapy of APLN/MB is a promising approach in the development of AD treatments.
Mixed‐Dimensional Formamidinium Bismuth Iodides Featuring In‐Situ Formed Type‐I Band Structure for Convolution Neural Networks
Authors: Yang June‐Mo , Lee Ju‐Hee , Jung Young‐Kwang , Kim So‐Yeon , Kim Jeong‐Hoon , Kim Seul‐Gi , Kim Jeong‐Hyeon , Seo Seunghwan , Park Dong‐Am , Lee Jin‐Wook , Walsh Aron , Park Jin‐Hong , Park Nam‐Gyu 
Published: March 2022

AbstractFor valence change memory (VCM)‐type synapses, a large number of vacancies help to achieve very linearly changed dynamic range, and also, the low activation energy of vacancies enables low‐voltage operation. However, a large number of vacancies increases the current of artificial synapses by acting like dopants, which aggravates low‐energy operation and device scalability. Here, mixed‐dimensional formamidinium bismuth iodides featuring in‐situ formed type‐I band structure are reported for the VCM‐type synapse. As compared to the pure 2D and 0D phases, the mixed phase increases defect density, which induces a better dynamic range and higher linearity. In addition, the mixed phase decreases conductivity for non‐paths despite a large number of defects providing lots of conducting paths. Thus, the mixed phase‐based memristor devices exhibit excellent potentiation/depression characteristics with asymmetricity of 3.15, 500 conductance states, a dynamic range of 15, pico ampere‐scale current level, and energy consumption per spike of 61.08 aJ. A convolutional neural network (CNN) simulation with the Canadian Institute for Advanced Research‐10 (CIFAR‐10) dataset is also performed, confirming a maximum recognition rate of approximately 87%. This study is expected to lay the groundwork for future research on organic bismuth halide‐based memristor synapses usable for a neuromorphic computing system.