bluuebunny/crossref_metadata_2025_split huggingface dataset:
Correlation of microbiota and antibiotic resistance genes in the swine manure-soil interface in Chongming Island
Authors: Qian Jing , Wu Zheyuan , Zhu Yongzhang , Zhang Yan , Zhou Xiaonong , Guo Xiaokui , Liu Chang 
Published: April 2023

Abstract
Background: Swine farming is a widespread agricultural practice that produces a substantial amount of antibiotics and genes associated with antibiotic resistance in swine manure. The presence of these antibiotic resistance genes (ARGs) poses a potential threat to the environment and human health. In order to investigate the microbiota and ARG profiles of swine manure and soil, samples from five swine farms on Chongming Island were collected and high-throughput sequencing and bioinformatics analysis were conducted. The sequencing data and MetaCompare allowed us to estimate the risk of ARG transmission to human pathogens in the sampled environments and prioritize the potential for antibiotic resistance.Results: Significant differences in microbial communities and antibiotic resistance gene (ARG) profiles were revealed both in swine manure and soil samples from five farms. Bacteroidetes was the dominant phylum in swine manure, while Proteobacteria was dominant in soil. The abundance of different drug classes varied from manure to soil. Multidrug, tetracycline, glycopeptide, peptide, fluoroquinolone, beta-lactam, rifamycin, macrolide, and aminoglycoside were the main drug classes of ARGs identified in both samples, with a large proportion of macrolide-lincosamide-streptogramin (MLS) and carbapenem resistance genes. Samples from the same farm showed a strong correlation in microbiota abundance and resistance gene diversity, indicating the effect of swine manure application and composting on the soil. However, microbial communities and ARGs varied among samples collected from different farms, influenced by factors including but not limited to feed composition, feeding density, husbandry practices, and sanitation. Beneficial bacteria in swine manure, including Bacillus spp., Eubacterium spp., Lactobacillus spp., Blautia, Dorea, and Methanobrevibacter, had symbiotic relationships with one another at the pig manure-soil interface. These genera were able to inhibit the growth of opportunistic pathogenic bacteria, such as Escherichia spp. However, some beneficial bacteria, represented by the NmcR gene, may promote the spread of antimicrobial resistance. We also observed numerous symbiotic relationships between different species of drug resistance genes, including cdeA, Bbif_ileS_MUP, macB, patB, vanSD, and tetQ, among others. Microbiota were found to determine the composition of drug resistance gene profiles. Quantifying the health risks associated with antibiotic resistance can help us identify and mitigate the risk. The mean risk value of ARGs for swine manure and soil samples from the five farms was 23.42 and 22.23 respectively, with higher values indicating greater risk.Conclusion Our study sheds light on the complex relationships between microbiota and ARG profiles in swine manure and soil, and highlights the potential impact of swine farming practices on the environment and public health.
On the Usefulness of the Vector Field Singular Points Shapes for Classification
Authors: Igbasanmi Oluwaseyi , Sirakov Nikolay M. 
Published: April 2023

Abstract
The objects’ features play significant role in the machine learning (ML) classification. The present paper proofs and validates that the shapes of vector field (VF) singular points (SPs) embedded into image objects may improve classification accuracy. For this purpose the present paper develops two VFs vû and v ˆ ϕ with real and complex SPs. The VFs are developed on the solution û(x, y) of a particular form of the Poisson equation. Further, we define the mappings between the SPs of ∇û(x, y), vû and v ˆ ϕ. Next, we develop the local Polya’s model of a VF and prove that the shapes of the SPs are invariant according to scaling, translation and weak rotations. This property implies that embedding the shapes of the SPs into the image objects extends the set of objects features, which leads to the advantage of increasing the classification statistics. We validate the invariance and the advantage with sets of experiments classifying the public image datasets ISIC2020 and COIL100. For the purpose of classification, we designed a new convolution neural network optimized to classify SP shapes and image objects features. The paper ends with conclusions on the contributions, advantages and the bottlenecks of this study.
WITHDRAWN: An Improved High Step-Up DC-DC Converter for Electrical Machines and Hybrid Electric Vehicles
Authors: Zarei Mehdi , Peng Huei 
Published: April 2023

Abstract

In this paper, an improved topology for a non-isolated high step-up DC-DC converter is proposed. The suggested converter has a straightforward structure, high voltage gains in comparison to the most non-isolated high gain structures shown in the literature, the low voltage stress on capacitors, low voltage stress on one of the switches and diodes, continuous input current, common ground, and low ripple in the output voltage and current. The continuous conduction mode (CCM) of the proposed converters, voltage stress on semiconductor devices, and component design are all fully considered in the mathematical analysis. The comparison results are addressed after the suggested converter has been compared to various converters offered in other references. The simulation findings of the proposed converter using PSCAD-EMTDC software are demonstrated to support the theoretical arguments.
Usability of the Premature Newborn Clinical Assessment Scale (PNCAS) during pretransport preparation of newborns
Authors: Kovtun O. P. , Davydova N. S. , Mukhametshin R. F. , Kurganski A. A. 
Published: April 2023

Purpose. To study the patient’s characteristics and hospital outcomes in subgroups depending on the PNCAS scale score.Material and methods. The cohort study included data from 604 trips of the transport team to newborns hospitalized in medical organizations of the Sverdlovsk region from August 1, 2017, to December 31, 2018. Median birth weight [IQR] 2515 [1600; 3275] grams, median gestational age [IQR] 36 [32; 38] weeks. The total sample was divided into subgroups depending on the assessment of the score, followed by a comparison of characteristics and outcomes in these subgroups.Results. There are significant differences in the structure of birth weight and gestational age, as the PNCAS score increases, there is a significant increase in the proportion of patients weighing less than 1000 grams and a decrease in the proportion of patients weighing 2500–3499 grams. The largest proportion of extremely premature newborns was observed in 6–8 points and 9–14 points subgroups, 30.16% and 24.00%, respectively. Assessment of the intensive care showed an increase in the proportion of patients requiring HFOV, dopamine and epinephrine infusion while increasing PNCAS score. Analysis of the outcomes showed a significant increase of mortality while increasing PNCAS score, 0.76% [0.02; 4.18] in the 0–2 points subgroup and 42.86% [21.82; 65.98] in the 9–14 points subgroup. There is also an increase in the proportion of patients who have formed severe IVH, 0.00% [0.00; 2.78] in the 0–2 points subgroup and 19.05% [5.45; 41.91] in the 9–14 points subgroup. A similar pattern is observed in the frequency of late onset sepsis.Conclusion. The PNCAS scale we studied demonstrates a reliable division of patients by severity and predicts the outcomes of the hospital stage of treatment.
Carbon Nanocomposites-based Electrochemical Sensors and
Biosensors for Biomedical Diagnostics
Authors: Kannan Palanisamy , Maduraiveeran Govindhan 
Published: April 2023

Abstract:
Detection of emergent biomolecules or biomarkers remains crucial for early diagnosis
in advancing healthcare monitoring and biomedicine. The possibility for rapid detection,
real-time monitoring, high sensitivity, low detection limit, good selectivity, and
low cost is central, among other significant issues for advancing point-of-care diagnosis.
Carbon-based nanocomposites have been employed as sensing materials for various biomarkers
due to their high surface-to-volume ratio, high electrical conductivity, chemical
stability, and biocompatibility. The carbon nanomaterials, such as carbon nanotubes (CNTs),
graphene (GR), carbon quantum dots (CQDs), carbon fibres (CFs), and their nanocomposites
have broadly integrated with numerous sensing electrode materials for the detection
of biomarkers under various experimental settings. The present review includes
the recent advances in the development of carbon nanomaterials-based electrochemical
sensors and biosensors for biomedical applications. The preparation, electrode preparation,
effective utilization of carbon-derived nanomaterials, and their sensing performances
towards numerous biomarkers have been highlighted. The state-of-the-merit,
challenges, and prospects for designing carbon nanocomposites-based electrochemical
sensor/biosensor platforms for biomedical diagnostics have also been described.
Anthracycline in Medicinal Chemistry: Mechanism of Cardiotoxicity, Preventive and
Treatment Strategies
Authors: Hussen Narmin Hamaamin , Hasan Aso Hameed , Muhammed Gashbeen Osman , Yassin Akar Yousif , Salih Roza Rafiq , Esmail Parwa Ahmed , Alanazi Mohammed M. , Jamalis Joazaizulfazli 
Published: April 2023

Abstract:
Anthracyclines are one of the most effective cancer treatments ever created, but
these compounds are somewhat cardiotoxic to some patients, causing heart failure. The likelihood
of such adverse effects restricts the overall prescribed dose of anthracyclines for patients.
Based on the pathophysiology of anthracycline-induced cardiotoxicity, the cardiotoxicity
plausibly originates from a reduction reaction of a single electron in its structure to form
surplus reactive oxygen species (ROS) or two electrons reducing and converting into C-13
alcohol metabolites. While excess ROS is the probable cause for acute cardiotoxicity brought
on by anthracyclines, it is not all characteristic of progressive cardiomyopathy. The formed
secondary alcohol metabolites could also profoundly accelerate cardiotoxicity, which then
develops into cardiomyopathy and eventually congestive heart failure. This review offers an
overview of the molecular pathways of anthracycline-induced cardiotoxicity, emphasizing the roles of secondary
alcohol metabolites of anthracyclines and/or their morbific role as ROS. The most effective ways to minimize or
terminate anthracycline-induced cardiotoxicity are also covered.
Proteins in Complement, Immune, and Clotting Cascades and their Role in
Preterm Births
Authors: Thakur Shubham , Jain Subheet Kumar 
Published: April 2023

Abstract:
Preterm birth (PTB) (< 37 completed weeks gestation) is a pathological outcome of pregnancy
and its associated complications are the leading global cause of death in children younger than
5 years of age. Babies born prematurely have an elevated risk for short- and long-term adverse effects
of medical and neurodevelopmental sequelae. Substantial evidence suggests that multiple sets
of symptoms are allied with PTB etiology, and the exact mechanism cannot be recognized. Notably,
various proteins, especially (i) complement cascade; (ii) immune system; and (iii) clotting cascade,
have become attractive research targets that are associated with PTB. Further, a small imbalance of
these proteins in maternal or foetal circulation could serve as a marker/precursor in a series of events
that lead to PTBs. Thus, the present review lightens the basic description of the circulating proteins,
their role in PTB, and current concepts for future development. Further, deepening the research on
these proteins will lead to a better understanding of PTB etiology and alleviate scientists' confidence
in the early identification of PTB mechanisms and biological markers.
Structural and Pharmacological Network Focused on MiRNAs
Involved in Rheumatoid Arthritis: A Systematic Review
Authors: Barrera-Vázquez Oscar Salvador , Hernández-González Olivia 
Published: April 2023

Background:
Rheumatoid Arthritis (RA) is a chronic autoimmune disease
that has a prevalence of over one percent of the world population, causing substantial
pain, joint deformity, and functional disability in patients. The identification and
measurement of miRNAs are relatively easy to perform. Future studies will corroborate if
miRNAs can fulfill their roles as biomarkers with either predictive or diagnostic evaluation
of treatment potential and provide actual clinical utility.

Methods:
In the last decade, various advances have been made regarding the
identification of the origin and exact functions of miRNAs, allowing us to have a potential
use both in the research and clinical fields.

Objective:
This systematic review aimed to collect, analyze, and improve the current
understanding of RA-related miRNAs and their applicability in therapeutics. A
bibliographic search of the miRNAs involved in RA was carried out, and through the use
of databases, their target genes and small molecules that had some relationship with
their expression were searched. The analysis of these data was done through structural
network analysis.

Results:
During the network analysis, miR-30a, miR-30c, let-7a, miR-144, miR-17-5p,
miR-124, miR -23b, miR-23, miR-15a, miR-16 were the most connected, which could be
used as possible biomarkers or be candidates for further analysis due to their interaction
with other miRNAs and genes.

Conclusion:
Additionally, this is the first systematic review, in which we proposed that
small compounds like toxicants and drugs could have a potential role within RA because
they regulate the expression of miRNAs involved in this pathology. Some of these
compounds are commonly found as environmental contaminants, and others as drugs.
These ideas open a new panorama of understanding RA, proposing possible causes or
treatments against this pathology. Therefore, these small molecules would give us some
indication of a relationship with RA, thereby helping in seeking causes, treatment, or
prevention of this disease. Conclusion: This is the first time it is intended to use
structural network analysis to determine possible biomarkers of AR for diagnosis and
prognosis through the expression of these miRNAs and their relationship with
compounds of daily life.
A Lightweight AMResNet Architecture with an Attention Mechanism for
Diagnosing COVID-19
Authors: Zhou Qi , Hammad Kowah Jamal Alzobair , Li Huijun , Yuan Mingqing , Jiang Lihe , Liu Xu 
Published: April 2023

Aims:
COVID-19 has become a worldwide epidemic disease and a new challenge for all mankind. The potential advantages of chest X-ray images on COVID-19 were discovered. We proposed a lightweight and effective Convolution Neural Network framework based on chest X-ray images for the diagnosis of COVID-19, named AMResNet.

Background:
COVID-19 has become a worldwide epidemic disease and a new challenge for all mankind. The potential advantages of chest X-ray images on COVID-19 were discovered.

Objective:
A lightweight and effective Convolution Neural Network framework based on chest X-ray images for the diagnosis of COVID-19.

Methods:
By introducing the channel attention mechanism and image spatial information attention mechanism, a better level can be achieved without increasing the number of model parameters.

Results:
In the collected data sets, we achieved an average accuracy rate of more than 92%, and the sensitivity and specificity of specific disease categories were also above 90%.

Conclusion:
The convolution neural network framework can be used as a novel method for artificial intelligence to diagnose COVID-19 or other diseases based on medical images.
The Comparison of Low and High-dose Scintigraphy findings in Patients with
Primary Parathyroid Lesions in which Intraoperative Gamma-probe was
Applied
Authors: Sule Ceylan , Necati Yilmaz 
Published: April 2023

Objective:
We aimed to evaluate the effectiveness of high-dose and low-dose use of radioactive material in intraoperative gamma probe application methods in patients diagnosed with primary hyperparathyroidism and planned for surgery.

Methods:
47 patients with primary hyperparathyroidism underwent minimally-invasive parathyroid surgery (MIS) after preoperative imaging studies
consisting of ultrasonography (USG) and sestamibi parathyroid scintigraphy (SPS) showed a possible primary parathyroid lesion (PPL). All
patients received Tc-99 sestamibi on day-of-surgery imaging (DOSI) to help with the localization of a primary parathyroid lesion (PPL) via both
DOSI and intraoperative gamma probe (IGP). Patients in Group I were administered 20-25 mCi Tc-99m sestamibi (methoxy isobutyl isonitrile)
and images were obtained at the 20th and 120th minutes. Patients in Group II were administered 8-10 mCi doses and images were obtained at the
20th and 40th minutes. Two nuclear medicine specialists independently evaluated the images. Lesions in the localizations determined by DOSI and
IGP were compared with the histopathological results of these lesions.

Results:
47 patients, 35 females, and 12 males were included in the study. The mean age of 28 patients in the first group given the high dose was 54 (41-60), and the mean age was 48 (42-57) in the second group given the low dose (p=0.011). In the group given low-dose radioactive material during intraoperative gamma probe application, the observer's sensitivity, specificity, positive, and negative predictive values for finding pathology were 61.1, 100, 100, and 12.5, respectively. In the group given high-dose radioactive material, the same values were 90.9, 33.3, 50, and 83.3, respectively. While the success of MIS increases with the use of DOSI and IGP in large lesions, the success decreases with the prolongation of the accumulation time of the given dose.

Conclusions:
In the intraoperative gamma probe technique used in primary hyperparathyroidism patients, the method used with low-dose radioactive material has lower sensitivity but higher specificity in estimating the post-operative pathology compared to the high-dose technique.
Application of Cell Penetrating Peptides for Intracellular Delivery of
Endostatin: A Computational Approach
Authors: Zamani Mozhdeh , Nezafat Navid , Mokarram Pooneh , Kadkhodaei Behnam 
Published: April 2023

Background:
Endostatin is an antiangiogenic compound with anticancer activity. The
poor stability and low half-life of endostatin are the main barriers to the clinical use of this protein.
Cell-penetrating peptides (CPPs) are extensively applied as carrier in the delivery of drugs and
different therapeutic agents. Therefore, they can be proper candidates to improve endostatin delivery
to the target cells.

Objective:
In this study, we aim to computationally predict appropriate CPPs for the delivery of
endostatin.

Methods:
Potential appropriate CPPs for protein delivery were selected based on the literature.
The main parameters for detection of best CPP-endostatin fusions, including stability, hydrophobicity,
antigenicity, and subcellular localization, were predicted using ProtParam, VaxiJen, and
DeepLoc-1.0 servers, respectively. The 3D structures of the best CPP-Endostatin fusions were
modeled by the I-TASSER server. The predicted models were validated using PROCHECK, ERRAT,
Verify3D and ProSA-Web servers. The best models were visualized by the PyMol molecular
graphics system.

Results:
Considering the principal parameters in the selection of best CPPs for endostatin delivery,
endostatin fusions with four CPPs, including Cyt c-ss-MAP, TP-biot1, MPGα, and DPV1047,
high stability and hydrophobicity, no antigenicity and extracellular localization were predicted as
the best potential fusions for endostatin delivery. Four CPPs, including Cyt c-ss-MAP, TP-biot1,
MPGα, and DPV1047, were predicted as the best potential candidates to improve endostatin delivery.

Conclusion:
Application of these CPPs may overcome the limitation of endostatin therapeutic
applications, including poor stability and low half-life. Subsequent experimental studies will contribute
to verifying these computational results.
Neuronal Vulnerability to Degeneration in Parkinson’s Disease and
Therapeutic Approaches
Authors: Sharma Tanushree , Kumar Rajnish , Mukherjee Sayali 
Published: April 2023

Abstract:
Parkinson's disease is the second most common neurodegenerative disease affecting millions
of people worldwide. Despite the crucial threat it poses, currently, no specific therapy exists that
can completely reverse or halt the progression of the disease. Parkinson's disease pathology is driven
by neurodegeneration caused by the intraneuronal accumulation of alpha-synuclein (α-syn) aggregates
in Lewy bodies in the substantia nigra region of the brain. Parkinson’s disease is a multiorgan disease
affecting the central nervous system (CNS) as well as the autonomic nervous system. A bidirectional
route of spreading α-syn from the gut to CNS through the vagus nerve and vice versa has also been reported.
Despite our understanding of the molecular and pathophysiological aspects of Parkinson’s disease,
many questions remain unanswered regarding the selective vulnerability of neuronal populations,
the neuromodulatory role of the locus coeruleus, and alpha-synuclein aggregation. This review article
aims to describe the probable factors that contribute to selective neuronal vulnerability in Parkinson’s
disease, such as genetic predisposition, bioenergetics, and the physiology of neurons, as well as the interplay
of environmental and exogenous modulators. This review also highlights various therapeutic
strategies with cell transplants, through viral gene delivery, by targeting α-synuclein and aquaporin
protein or epidermal growth factor receptors for the treatment of Parkinson’s disease. The application
of regenerative medicine and patient-specific personalized approaches have also been explored as
promising strategies in the treatment of Parkinson’s disease.
Perspectives on the Role of P21-Activated Kinase 1 (PAK1) in the Intestinal
Anti-inflammatory and Antitumor Potential of Artepillin C
Authors: da Silva Luisa Mota 
Published: April 2023

Abstract:
The Brazilian biodiversity may bring new perspectives to the therapy of Inflammatory Bowel Diseases (IBD) and intestinal cancer. The
effect of Brazilian Green Propolis in reducing ulcerative colitis in mice has already been described, as well as high amounts of the prenylated
compound Artepellin C (ARC). The search for new pharmacological targets for IBD is also advancing. Among possibilities is the p21-activated
kinase (PAK1), overexpressed and activated in the intestinal mucosa during IBD and colitis-associated colorectal cancer (CAC). PAK 1 contributes
to tissue inflammation by reducing the expression of peroxisome proliferator-activated receptor type γ (PPARγ) and increasing activation of
nuclear factor (NF)-κB. At least in vitro, inhibition of PAK1 has been reported to mitigate NF-κB-mediated inflammation in intestinal cells and
ARC inhibits PAK1 activation. Given this pharmacological potential of ARC and the role of PAK1 in IBD and CAC, this perspective collected
information that encourages future research to test the hypothesis that ARC can maintain intestinal integrity under the inflammatory and neoplastic
stimulus and that inhibition of PAK1/NF-κB signaling and favoring PPAR-γ activity is pivotal in this action. Therefore, future studies employing
in vitro and in vivo steps, using murine and human enterocytes and rodents submitted to ulcerative colitis and CAC models are incentivized by the
data gathered here, favor retirar essas palavras: mostly in vitro studies, before clinical trials. Therefore, the perspective presented here points to an
interesting path in the search for a drug useful in inflammatory and neoplastic intestinal diseases, which may have ARC as a prototype, acting on a
target not yet explored clinically.