bluuebunny/crossref_metadata_2025_split huggingface dataset:
Prevalence of Diabetes in India: A Review of IDF Diabetes Atlas 10th
Edition
Authors: Kumar Arvind , Gangwar Ruby , Ahmad Zargar Abrar , Kumar Ranjeet , Sharma Amit 
Published: April 2023

Abstract:
Diabetes is a severe chronic disease that arises when insulin generation is insufficient, or
the generated insulin cannot be used in the body, resulting a long-term metabolic disorder. Diabetes
affects an estimated 537 million adults worldwide between the age of 20 to 79 (10.5% of all
adults in this age range). By 2030, 643 million people will have diabetes globally, increasing to
783 million by 2045. According to the IDF 10th edition, the incidence of diabetes has been rising
in South-East Asia (SEA) nations for at least 20 years, and current estimates have outperformed all
previous forecasts. This review aims to provide updated estimates and future projections of diabetes
prevalence at the national and global levels by using data from the 10th edition of the IDF Diabetes
Atlas 2021. For this review, we studied more than 60 previously published related articles
from various sources, such as PubMed and Google Scholar, and we extracted 35 studies out of 60.
however, we used only 34 studies directly related to diabetes and its prevalence at the global, SEA,
and Indian levels. This review article concludes that in 2021 more than 1 in 10 adults worldwide
developed diabetes. The estimated prevalence of diabetes in adults (20 to 79 years) has more than
tripled since the first edition in 2000, rising from an estimated 151 million (4.6% of the world’s
population at the time) to 537.5 million (10.5%) of the world’s population today. The prevalence
rate will be higher than 12.8% by 2045. In addition, this study indicates that the incidence of diabetes
in the world, Southeast Asia, and India was 10.5%, 8.8%, and 9.6%, respectively, throughout
2021 and will rise to 12.5%, 11.5%, and 10.9%, respectively by 2045.
Two Eggs A Day Can Increase Choline Intake and Size of Mid Upper Arm Circumference (MUAC) in Pregnant Women in Indonesia
Authors: Isdiany Nitta , Rahmat Mamat , Pramintarto Eko Mulyo Gurid , Judiono  
Published: April 2023

Background:
Good nutritional intake is very important for pregnant women to prevent
stunting in children. However, the problem of CED in pregnant women in Indonesia remains high.
Higher choline intake in pregnant women is associated with better memory in a child by the time
the child turns 7 years old. Choline functions in the process of methylation and cholinergic transmission
during the process of brain development in children. Modification of the high choline diet
in daily menu is needed by pregnant women to increase choline intake and size of MUAC.

Objective:
This study aims to examine the effectiveness of high choline diet modification on changes
in choline intake and size of MUAC in pregnant women.

Methods:
A total of 14 pregnant women in the treatment group received 2 eggs every day, while 13
pregnant women in the control group received education on balanced nutrition during the study
period. Changes in choline intake and size of MUAC were stastiscally compared between the two
groups.

Results:
There was a significant change in the average intake of choline before and after the
intervention in pregnant women between the treatment and control group (p < 0.05). The results
stated that there was a significant difference in the size of MUAC in pregnant women between the
treatment and control groups (p < 0.05). Energy intake was not a confounder of the intervention
outcome.

Conclusion:
Modification of low choline level diet by giving 2 eggs a day for 1 month as an additional
food in the diet of pregnant women can increase choline intake and size of MUAC.
Atypical Cytotoxic Lesion and Hemorrhagic Involvement of the Corpus
Callosum in Severe COVID-19 Infection
Authors: Guarnizo-Capera Angela , Tapias Manuela Gallo , Ortegén José David Cardona , Valencia Valentina Ferrer 
Published: April 2023

Introduction/Background:
The COVID-19 pandemic has resulted in a large number of deaths and has caused a significant increase in population morbidity. This viral
infection has been associated with different neurological symptoms and complications that do not have a clear pathophysiological mechanism and
exact implications for these patients.

Case Presentation:
A 40-year-old man with COVID-19 and co-infection with Klebsiella pneumoniae KPC presented extensive pulmonary involvement and required
comprehensive management in the intensive care unit (ICU). During his hospitalization, he developed neurological symptoms with evidence of
involvement of the corpus callosum, which was attributed to the cytotoxic lesion of the corpus callosum (CLOCC). After several months of
interdisciplinary management in the ICU, there was a progressive improvement in his general condition, with discharge from the hospital without
significant sequelae, with follow-up images showing complete involvement of the corpus callosum due to what was considered an atypical
cytotoxic lesion of the corpus callosum.

Conclusion:
Imaging features of CLOCCs are known to be temporary, but in the setting of COVID-19, it has not yet been determined if this is true and further
studies are needed. Nonetheless, the one-year follow-up of our patient makes us believe that this atypical involvement of the corpus callosum
described in severe SARS-CoV-2 infections is not transitory, even if there are no neurologic sequelae.
MLP-Res-Unet: MLPs and Residual Blocks-based U-shaped Network
Intervertebral Disc Segmentation of Multi-modal MR Spine Images
Authors: Liu Hanqiang , Lu Sipei , Zhao Feng 
Published: April 2023

Background:
Intervertebral disc degeneration (IVD) is now the most prevalent disease in the world; thus, precise intervertebral disc segmentation is essential for the assessment and diagnosis of spinal diseases. Multi-modal magnetic resonance (MR) imaging is more multi-dimensional and thorough than unimodal imaging. However, manual segmentation of multi-modal MRI not only imposes a huge burden on physicians but also has a high error rate.

Objective:
In this study, we propose a new method that can efficiently and accurately segment intervertebral discs from multi-modal MR spine images, providing a reproducible usage scheme for the diagnosis of spinal disorders.

Methods:
We suggest a network structure called MLP-Res-Unet that reduces the amount of computational load and the number of parameters while maintaining performance. Our contribution is two-fold. First, a medical image segmentation network that fuses residual blocks and a multilayer perceptron (MLP) is proposed. Secondly, we design a new deep supervised method and pass the features extracted from the encoder to the decoder through the residual path to achieve a new full-scale residual connection.

Results:
We evaluate the network on the MICCAI-2018 IVD dataset and obtain Dice similarity coefficient equal to 94.77 (%) and Jaccard coefficient equal to 84.74 (%), while we reduce the amount of parameters by a factor of 3.9 and computation by a factor of 2.4 compared to the IVD-Net.

Conclusion:
Experiments show that MLP-Res-Unet improves segmentation performance and creates a simpler model structure while reducing the number of parameters and computation.
Non-functional Adrenocortical Carcinoma in the Wall of the Small Bowel
Authors: Lin Shu-Juan , Gao Yan , Sun Chun-Juan 
Published: April 2023

Background:
Extra-adrenal non-functional adrenocortical carcinoma (ACC)is an extremely rare tumor with only eight cases having been reported at different
localizations.

Case Presentation:
A 60-year-old woman was presented to our hospital with abdominal pain. Magnetic resonance imaging revealed a solitary mass abutting the wall
of the small bowel. She underwent resection of the mass, and the results of histopathology and immunohistochemistry were consistent with ACC.

Conclusion:
We report the first occurrence of non-functional adrenocortical carcinoma in the wall of the small bowelin the literature. Magnetic resonance
examination is sensitive enough to indicate the accurate location of the tumor and is of great help to clinical operation.
Analysis of COVID-19 CT Chest Image Classification using Dl4jMlp Classifier
and Multilayer Perceptron in WEKA Environment
Authors: S. Sreejith , Ajayan J. , Reddy N.V.Uma , Devasenapati S. Babu , Rebelli Shashank 
Published: April 2023

Introduction:
In recent years, various deep learning algorithms have exhibited remarkable performance in various data-rich applications, like health care, medical imaging, as well as in computer vision. Covid-19, which is a rapidly spreading virus, has affected people of all ages both socially and economically. Early detection of this virus is therefore important in order to prevent its further spread.

Methods:
Covid-19 crisis has also galvanized researchers to adopt various machine learning as well as deep learning techniques in order to combat the pandemic. Lung images can be used in the diagnosis of Covid-19.

Results:
In this paper, we have analysed the Covid-19 chest CT image classification efficiency using multilayer perceptron with different imaging filters, like edge histogram filter, colour histogram equalization filter, color-layout filter, and Garbo filter in the WEKA environment.

Conclusion:
The performance of CT image classification has also been compared comprehensively with the deep learning classifier Dl4jMlp. It was observed that the multilayer perceptron with edge histogram filter outperformed other classifiers compared in this paper with 89.6% of correctly classified instances.
An In silico Investigation to Identify Promising Inhibitors for SARS-CoV-2 Mpro Target
Authors: Alagarsamy V. , Sundar P. Shyam , Narendhar B. , Sulthana M. T. , Kulkarni Vishaka S. , Aishwarya A. Dharshini , Solomon V. Raja , Murugesan S. , Jubie S. , Rohitha K. , Dhanwar Sangeeta 
Published: April 2023

Background:A limited number of small molecules against SARS-CoV-2 has been discovered since the epidemic commenced in November 2019. The conventional medicinal chemistry approach demands more than a decade of the year of laborious research and development and a substantial financial commitment, which is not achievable in the face of the current epidemic.Objective:This study aims to discover and recognize the most effective and promising small molecules by interacting SARS-CoV-2 Mpro target through computational screening of 39 phytochemicals from five different Ayurvedic medicinal plants.Methods:The phytochemicals were downloaded from Research Collaboratory for Structural Bioinformatics (RCSB) Protein Data Bank (PDB) PubChem, and the SARS-CoV-2 protein (PDB ID: 6LU7; Mpro) was taken from the PDB. The molecular interactions, binding energy, and ADMET properties were analyzed.Results:The binding affinities were studied using a structure-based drug design of molecular docking, divulging 21 molecules possessing greater to equal affinity towards the target than the reference standard. Molecular docking analysis identified 13 phytochemicals, sennoside-B (-9.5 kcal/mol), isotrilobine (-9.4 kcal/mol), trilobine (-9.0 kcal/mol), serratagenic acid (-8.1 kcal/mol), fistulin (-8.0 kcal/mol), friedelin (-7.9 kcal/mol), oleanolic acid (-7.9 kcal/mol), uncinatone (-7.8 kcal/mol), 3,4-di- O-caffeoylquinic acid (-7.4 kcal/mol), clemaphenol A (-7.3 kcal/mol), pectolinarigenin (-7.2 kcal/mol), leucocyanidin (-7.2 kcal/mol), and 28-acetyl botulin (-7.2 kcal/mol) from ayurvedic medicinal plants phytochemicals possess greater affinity than the reference standard Molnupiravir (-7.0 kcal/mol) against SARS-CoV-2-Mpro.Conclusion:Two molecules, namely sennoside-B, and isotrilobine with low binding energies, were predicted as most promising. Furthermore, we carried out molecular dynamics simulations for the sennoside-B protein complexes based on the docking score. ADMET properties prediction confirmed that the selected docked phytochemicals were optimal. These compounds can be investigated further and utilized as a parent core molecule to create novel lead molecules for preventing COVID-19.
ADME Prediction, Structure-activity Relationship of Boswellic Acid Scaffold for the
Aspect of Anticancer & Anti-inflammatory Potency
Authors: Kumar Akhalesh , Sharma Saurabh , Mishra Sudhanshu , Ojha Smriti , Upadhyay Pawan 
Published: April 2023

Abstract:
Nature is the chief source of various remedies which are used to cure various diseases. Boswellic acid (BA)
is a secondary metabolite from the pentacyclic terpenoid compound groups that are derived from the plant genus Boswellia. The oleo gum resins of these plants are primarily composed of polysaccharides, with the remaining amounts of
resin (30-60%) and essential oils (5-10%) soluble in organic solvents. BA and its analogs are also reported to exhibit
various in vivo and biological responses for example anti-inflammatory, anti-tumor, free radical scavenging activity,
etc. Among all analogs, 11-keto-β-boswellic acid (KBA) and 3-O-acetyl-11-keto-β-boswellic acid (AKBA) has been
demonstrated to be the most effective at reducing cytokine production and inhibiting the inflammatory responsecausing enzymes. In this review, we summarized the computational ADME prediction via the SwissADME computational tool and the structure-activity relationship of the Boswellic acid scaffold for the aspect of anticancer and antiinflammatory potency. In addition to these research findings which are associated with the therapy of acute inflammation and some cancers, the potential of boswellic acids against other disorders was also discussed.
New Approach Methodologies in Immunotoxicology: Challenges and
Opportunities
Authors: Maddalon Ambra , Iulini Martina , Melzi Gloria , Corsini Emanuela , Galbiati Valentina 
Published: April 2023

Abstract:
To maintain the integrity of an organism, a well-functioning immune system is essential.
Immunity is dynamic, with constant surveillance needed to determine whether to initiate an immune
response or to not respond. Both inappropriate immunostimulation and decreased immune
response can be harmful to the host. A reduced immune response can lead to high susceptibility to
cancer or infections, whereas an increased immune response can be related to autoimmunity or
hypersensitivity reactions. Animal testing has been the gold standard for hazard assessment in immunotoxicity
but a lot of efforts are ongoing to develop non-animal-based test systems, and important
successes have been achieved. The term “new approach methodologies” (NAMs) refer to
the approaches which are not based on animal models. They are applied in hazard and risk assessment
of chemicals and include approaches such as defined approaches for data interpretation and
integrated approaches to testing and assessment.

:
This review aims to summarize the available NAMs for immunotoxicity assessment, taking into
consideration both inappropriate immunostimulation and immunosuppression, including implication
for cancer development.
Nanocrystal Materials for Resistive Memory and Artificial Synapses:
Progress and Prospects
Authors: Chen Yingchun , Chen Dunkui , Zhang Chi , Zhang Xian 
Published: April 2023

Background:
Resistive random-access memory (RRAM) is considered to be the most promising
next-generation non-volatile memory because of its low cost, low energy consumption, and excellent
data storage characteristics. However, the on/off (SET/RESET) voltages of RRAM are too random
to replace the traditional memory. Nanocrystals (NCs) offer an appealing option for these applications
since they combine excellent electronic/optical properties and structural stability and can address the requirements
of low-cost, large-area, and solution-processed technologies. Therefore, the doping NCs in
the function layer of RRAM are proposed to localize the electric field and guide conductance filaments
(CFs) growth.

Objective:
The purpose of this article is to focus on a comprehensive and systematical survey of the NC
materials, which are used to improve the performance of resistive memory (RM) and optoelectronic
synaptic devices and review recent experimental advances in NC-based neuromorphic devices from artificial
synapses to light-sensory synaptic platforms.

Methods:
Extensive information related to NCs for RRAM and artificial synapses and their associated
patents were collected. This review aimed to highlight the unique electrical and optical features of metal
and semiconductor NCs for designing future RRAM and artificial synapses.

Results:
It was demonstrated that doping NCs in the function layer of RRAM could not only improve
the homogeneity of SET/RESET voltage but also reduce the threshold voltage. At the same time, it
could still increase the retention time and provide the probability of mimicking the bio-synapse.

Conclusion:
NC doping can significantly enhance the overall performance of RM devices, but there are
still many problems to be solved. This review highlights the relevance of NCs for RM and artificial synapses
and also provides a perspective on the opportunities, challenges, and potential future directions.
Silver Ion Release from Polymethylmethacrylate Reinforced with
Silvernanoparticles-An In vitro Study
Authors: Shenava Aashritha 
Published: April 2023

Background:
Despite the awareness among patients with complete dentures, the risk factor for developing denture related candidiasis is when it is not removed during sleep and cleaned regularly. The routine treatment is an antifungal application, but frequent infection is seen after treatment. Nanotechnology has led the medical field to a cutting edge in most of the treatment aspects of various conditions. Moreover, the assimilation of silver nanoparticles into the polymer can be useful as an antifungal agent. To assess the antifungal efficacy of AgNP’s/ PMMA (silver nanoparticles /polymethlmethacrylate) against Candida albicansstrain and to evaluate the continuous release of silver ions which would increase antifungal mechanism.

Methods:
Chemical methods of synthesis of silver nanoparticles using metal precursors, reducing agents, and stabilizing agents were used because of its convenience and simple equipment. MIC (minimum inhibitory concentration) was evaluated along with antifungal efficacy by incorporating PMMA (polymethylmethacrylate) discs with silver nanoparticles. Silver ion release was carried out by immersing the PMMA/Ag discs in deionised water for different immersion periods.

Results:
In the Independent Sample ‘t’ test, the comparison of optical density between the study groups at 6 months at absorbance A230, A260,A280, A320, A420, and A550 was statistically significant(p<0.05).

Conclusion:
Silver Nanoparticles could be prepared which is cost-effective and can serve as an antifungal agent against Candida albicans. Silver ion release was seen with AgNP’s /PMMA (SilverNanoparticle /polymethylmethacrylate) at 6 months and Group A ( .06M) and Group B (.03 M) was confirmed to be used as an antifungal agent.
Plant-mediated Synthesis of Silver Nanoparticles using Mangosteen Pericarp
Extract and their Antimicrobial Potential
Authors: Amargo Mely Mariz S. , Bucoya Ella Angelique M. , Fundador Erwin Oliver V. , Fundador Noreen Grace V. 
Published: April 2023

Introduction:
Silver nanoparticles (AgNPs) were synthesized using mangosteen pericarp ethanolic
extract (MPEE) as a source of bioreductants and their antimicrobial activity against common foodborne
pathogens was evaluated.

Methods:
Characterization of MPEE was conducted using phytochemical screening, total phenolic content
analysis, and DPPH (antioxidant) assay. Synthesis AgNPs and optimization studies were monitored
using UV-Vis spectrophotometry. Transmission electron microscopy was used to characterize the AgNPs,
and resazurin microtiter assay was used for antimicrobial testing.

Results:
Alkaloids, flavonoids, saponins, quinones, anthraquinones, and tannins were confirmed present
in the extract. TPC and IC50 of MPEE were 0.192 mg GAE/mg extract and 0.277 mg/mL, respectively. A
surface plasmon resonance (SPR) peak within 450-403 nm confirmed the formation of AgNPs. At pH 7,
the optimum reaction conditions were 45°C and 3 h. Meanwhile, at pH 9, the optimum reaction conditions
were 27°C and 0.5 h. The sizes of nanoparticles synthesized at pH 7 and pH 9 were 13-35 nm and 7-
38 nm, respectively. The minimum inhibitory concentration (MIC90) of AgNPs produced at pH 7 were
1.45, 2.81, and 2.93 ug/mL for S. aureus, E.coli, and B. cereus, respectively. For AgNPs synthesized at
pH 9, the MIC90 were 2.93, 3.02, and 5.24 ug/mL, for the same microorganisms, respectively.

Conclusion:
MPEE was able to successfully synthesize AgNPs. Compared to chloramphenicol, AgNPs
exhibited better antimicrobial activity, which can address the growing concern of drug resistance in certain
pathogenic microorganisms. Furthermore, the use of MPEE provides a green and sustainable alternative
to synthesizing AgNPs.
Guggul: Potency and Mechanistic Insight for Tremendous Therapeutic
Benefit
Authors: Srivastava Shikha 
Published: April 2023

Abstract:
Commiphoramukul being a treasure to phytochemicals, are of great medicinal value. The plant, composed of flavonoids, phytosterols and terpenes, possesses antimicrobial, anti-inflammatory, antioxidant and anticancerous properties with wide therapeutic activities. The active ingredient in plants include ketosteroids, E and Z guggulsterone, ellagic acid, myrrhanols B, myrrhanonesA, myrrhanoes B, guggulsterone-I, guggulsterone-II, guggulsterone-III. Various phytochemicals in plants play a very vital role in treating acute to chronic diseases, such as rheumatoid arthritis, atherosclerosis, inflammatory gastric disorders, hyperlipidemia, cancer, ageing, and for cosmetic purposes too. The present chapter aims to update mankind with the profound phytochemical constituents present in plants and their pharmacological application.
Research on Medium and Long Term Generation Side Deviation Prediction
of New Power Market Based on Multi-Layer LSTM
Authors: Hong Qu , Ze Ye , Liang Weixuan 
Published: April 2023

Background:
With the large-scale grid connection operation of new or renewable energy
and the access of active loads such as electric vehicles and air conditioners, the electric energy
trading business in the power market faces problems such as the rapid expansion of the number of
market settlement subjects, explosive growth, various subjects responsible for deviation assessment,
various electric energy trading methods and so on.

Objective:
This paper focuses on the medium and long-term generation side power trading in the
new power market. Through cause analysis, induction and summary, algorithm design and case
analysis, the problem of generation side deviation prediction is solved and power waste is reduced.

Methods:
This paper puts forward the reasons for the imbalance of medium and long-term power
trading in the new power market dominated by new energy, as well as the deviation prediction
algorithm based on multi-layer LSTM, which brings the total historical deviation, total planned
deviation, total measurement deviation, new energy consumption and other data into the M-LSTM
deep learning network for testing in each provincial power market center.

Results:
We use the neural network prediction algorithm. Compared with a single LSTM, the
multi-layer LSTM can better maintain the characteristics of the sample time series and reduce the
prediction error. Compared with BPNN、M-BPNN and Cooperative game theory, LSTM has a
better memory effect.

Conclusion:
The experiment shows that the more accurate prediction deviation of this method can
better arrange the generation plan, reduce the loss caused by excessive deviation, reduce the "price
trampling" of the power market, and ensure the fair and efficient development of the power market.