bluuebunny/crossref_metadata_2025_split huggingface dataset:
Synthesis, and In-silico Studies of Indole-chalcone Derivatives Targeting
Estrogen Receptor Alpha (ER-α) for Breast Cancer
Authors: Choudhari Rahul Charudatta , Kaur Kamalpreet , Das Agnidipta , Jaitak Vikas 
Published: October 2023

Background:
Breast cancer is the prominent reason of death in women worldwide,
and the cases are increasing day by day. There are many FDA-approved drugs for treating breast
cancer. Due to drug resistance, and problems in selectivity, there is a need to develop more effective
agents with few side effects. Indole derivatives have demonstrated significant pharmacological
potential as anti-breast cancer agents. Further, chalcone derivatives incorporating heterocyclic
scaffolds play a significant role in medicine. Indole-chalcone-based compounds offer the
potential for improved biological activity and enhanced drug-like properties. It prompted us to
explore the synthesis of Indole-Chalcone derivatives targeting estrogen receptor alpha (ER-α) to
discover potent anti-breast cancer agents.

Objectives:
To synthesize indole-chalcone derivatives and study their binding interactions for
ER-α protein by molecular docking for breast cancer treatment.

Methods:
In this study, indole-chalcone derivatives have been synthesized using conventional
heating. With the help of Schrodinger software, molecular interaction as well as ADME (Adsorption,
Distribution, Metabolism, and Excretion) studies of the compounds were conducted.

Results:
Among all the synthesized compounds, four compounds (1, 2, 3, and 4) showed better
docking scores (-10.24 kcal/mol, -10.15 kcal/mol, -9.40 kcal/mol, -9.29 kcal/mol, respectively)
than the standard tamoxifen (-8.43 kcal/mol).

Conclusion:
From In-silico studies, we can conclude that four compounds from the synthesized
series fit into the active site of ER-α. ADME properties of synthesized derivatives were found in
the acceptable range. In the future, these compounds can be further explored for biological activity.
DMR_Kmeans: Identifying Differentially Methylated Regions Based on
k-means Clustering and Read Methylation Haplotype Filtering
Authors: Peng Xiaoqing , Cui Wanxin , Kong Xiangyan , Huang Yuannan , Li Ji 
Published: October 2023

Introduction::
Differentially methylated regions (DMRs), including tissue-specific DMRs
and disease-specific DMRs, can be used in revealing the mechanisms of gene regulation and screening diseases. Up until now, many methods have been proposed to detect DMRs from bisulfite sequencing data. In these methods, differentially methylated CpG sites and DMRs are usually identified based on statistical tests or distribution models, which neglect the joint methylation statuses
provided in each read and result in inaccurate boundaries of DMRs.

Methods::
In this paper, a method, named DMR_Kmeans, is proposed to detect DMRs based on kmeans clustering and read methylation haplotype filtering. In DMR_Kmeans, for each CpG site, the
k-means algorithm is used to cluster the methylation levels from two groups, and the methylation
difference of the CpG is measured based on the different distributions in clusters. Methylation haplotypes of reads are employed to extract the methylation patterns in a candidate region. Finally, DMRs
are identified based on the methylation differences and the methylation patterns in candidate regions.

Result::
Comparing the performance of DMR_Kmeans and eight DMR detection methods on the
whole genome bisulfite sequencing data of six pairs of tissues, the results show that DMR_Kmeans
achieves higher Qn and Ql, and more overlapped promoters than other methods when given a certain
threshold of methylation difference greater than 0.4, which indicates that the DMRs predicted by
DMR_Kmeans with accurate boundaries contain less CpGs with small methylation differences than
those by other methods.

Conclusion::
Furthermore, it suggests that DMR_Kmeans can provide a DMR set with high quality
for downstream analysis since the total length of DMRs predicted by DMR_Kmeans is longer and
the total number of CpG sites in the DMRs is greater than those of other methods.
A Deep Neural Network Model with Attribute Network Representation for
lncRNA-Protein Interaction Prediction
Authors: Wei Meng-Meng , Yu Chang-Qing , Li Li-Ping , You Zhu-Hong , Lei-Wang  
Published: October 2023

Background:
LncRNA is not only involved in the regulation of the biological functions of
protein-coding genes, but its dysfunction is also associated with the occurrence and progression of
various diseases. Various studies have shown that an in-depth understanding of the mechanism of
action of lncRNA is of great significance for disease treatment. However, traditional wet testing is
time-consuming, laborious, expensive, and has many subjective factors which may affect the accuracy
of the experiment.

Objective:
Most of the methods for predicting lncRNA-protein interaction (LPI) rely on a single
feature, or there is noise in the feature. To solve this problem, we proposed a computational model,
CSALPI based on a deep neural network.

Methods:
Firstly, this model utilizes cosine similarity to extract similarity features for lncRNAlncRNA
and protein-protein, denoising similar features using the Sparse Autoencoder. Second, a
neighbor enhancement autoencoder is employed to enforce neighboring nodes to be represented
similarly by reconstructing the denoised features. Finally, a Light Gradient Boosting Machine classifier
is used to predict potential LPIs.

Results:
To demonstrate the reliability of CSALPI, multiple evaluation metrics were used under a 5-
fold cross-validation experiment, and excellent results were achieved. In the case study, the model
successfully predicted 7 out of 10 disease-associated lncRNA and protein pairs.

Conclusion:
The CSALPI can be an effective complementary method for predicting potential LPIs
from biological experiments.
Arsenic Trioxide inhibits Activation of Hedgehog Pathway in Human Neuroblastoma
Cell Line SK-N-BE(2) Independent of Itraconazole
Authors: Liu Xiaoshan , Wang Zhixuan , Xiong Xilin , Li Chunmou , Wu Yu , Su Mingwei , Yang Shu , Zeng Meilin , Weng Wenjun , Huang Ke , Zhou Dunhua , Fang Jianpei , Xu Lvhong , Li Peng , Zhu Yafeng , Qiu Kunyin , Ma Yuhan , Lei Jiaying , Li Yang 
Published: October 2023

Background:
Neuroblastoma (NB) remains associated with a low overall survival rate over the long term.
Abnormal activation of the Hedgehog (HH) signaling pathway can activate the transcription of various downstream
target genes that promote NB. Both arsenic trioxide (ATO) and itraconazole (ITRA) can inhibit tumor growth.

Objective:
To determine whether ATO combined with ITRA can be used to treat NB with HH pathway activation,
we examined the effects of ATO and ITRA monotherapy or combined inhibition of the HH pathway in NB.

Methods:
Analysis of CCK8 and flow cytometry showed cell inhibition and cell cycle, respectively. Real-time
PCR analysis was conducted to assess the mRNA expression of HH pathway.

Results:
We revealed that as concentrations of ATO and ITRA increased, the killing effects of both agents on
SK-N-BE(2) cells became more apparent. During G2/M, the cell cycle was largely arrested by ATO alone and
combined with ITRA, and in the G0/G1 phase by ITRA alone. In the HH pathway, ATO inhibited the transcription
of the SHH, PTCH1, SMO and GLI2 genes, however, ITRA did not. Instead of showing synergistic effects in
a combined mode, ITRA decreased ATO inhibitory effects.

Conclusion:
We showed that ATO is an important inhibitor of HH pathway but ITRA can weaken the inhibitory
effect of ATO. This study provides an experimental evidence for the clinical use of ATO and ITRA in the treatment
of NB with HH pathway activation in cytology.
The Landscape of Randomized Clinical Trial Meta-analyses on Statins for
Aneurysmal Subarachnoid Hemorrhage: A Scoping Review
Authors: Skouras Panagiotis , Kalamatianos Theodosis , Markouli Mariam , Karagiannis Angelos , Stavrinou Lampis C. 
Published: October 2023

Introduction:
Aneurysmal subarachnoid hemorrhage (aSAH) is a type of non-traumatic
SAH that can have detrimental effects on the central nervous system, resulting in severe disability or
death.

Methods:
Early nimodipine is currently the only strongly recommended pharmacological treatment
that has shown efficacy in improving neurological/functional outcomes in aSAH patients. Whether
statin treatment is of benefit to aSAH patients is an issue that has generated considerable interest and
debate. In the present scoping review, we mapped and analyzed the available literature on metaanalyses
of randomized clinical trials (RCTs) examining the effect of statins on aSAH. Seventeen
meta-analyses of RCTs, published between 2008 and 2023, were identified.

Results:
Treatments in included meta-analyses were based on various regimens of simvastatin,
pravastatin, pitavastatin or atorvastatin for up to 21 days. Eleven of the included reports indicated
some beneficial effect of statin treatment, reducing rates of at least one of the following: cerebral
vasospasm, delayed cerebral ischemia/delayed ischemic neurologic deficit, mortality or functional/
neurological outcome. In contrast, six meta-analyses, showed no such effects.

Conclusion:
The limitations reported by several meta-analyses, included low patient numbers or disproportionate
representation of patients from certain RCTs, differences in drug treatment, patient diagnostic
criteria and outcome evaluation between RCTs, as well as poor data quality or lack of RCTs
data. Knowledge of the reported limitations may aid the design of future clinical trials and/or their
meta-analyses.
Why Pharmacovigilance of Non-steroidal Anti-inflammatory Drugs is Important in India?
Authors: Dash Subhransu , Singh Preet Amol , Bajwa Neha , Choudhury Abinash , Bisht Preeti , Sharma Rajiv 
Published: October 2023

Background:Non-steroidal Anti-Inflammatory Drugs (NSAIDs) are among the drugs that are most regularly administered to manage inflammation and pain. Over-the-Counter (OTC) NSAIDs are widely accessible, particularly in developing countries like India. This casual approach to using NSAIDs may operate as a magnet for NSAID-related adverse drug reactions (ADRs) among patients.Objectives:As patients in India are less informed about the appropriate use of NSAIDs and consumption patttern, adverse drug reactions, and the importance of reporting ADRs, the current study's objective is to promote patient safety by using pharmacovigilance as a tool to educate patients.Methods:A targeted literature methodology was utilized to gather the data pertaining to NSAIDs, their ADRs and their pharmacovigilance. Different scientific databases, such as Science Direct, PubMed, Wiley Online Library, Springer, and Google Scholar, along with authentic textbooks, were explored as reference literature.Results:In general, NSAIDs consumption pattern depends upon the different age groups. Around 1.6 billion tablets of NSAIDs are consumed in India for ailments, such as headaches, arthritis, menstrual cramps, osteoarthritis, back pain, rheumatoid arthritis, gout, osteoporosis, tendinitis, cancer pain and chronic pain. Common ADRs of NSAIDs include nausea, vomiting, headache, gastritis, abdominal pain, and diarrhoea. Also, they can cause renal damage and cardiovascular problems if not consumed in a dose-dependent manner. However, Diclofenac and Ibuprofen have both been linked to depression and dementia. There have been reports of aplastic anaemia, agranulocytosis linked to phenylbutazone, Stevens-Johnson, and Lyell's syndrome linked to isoxicam and piroxicam, as well as the vulnerability of new-borns to Reye's syndrome after aspirin use. Lack of awareness, time constraints and unpredictability, poor training in ADRs identification, etc., are some of the reasons for the under-reporting of ADR of NSAIDs in India.Conclusion:In order to rationally prescribe NSAIDs, it is essential to be aware of probable ADR’s and establish prescription guidelines. Prescribers' behaviour can be changed toward excellent prescribing practices by conducting routine prescription assessments dealing with NSAIDs and providing feedback. In the near future, it will be critical to strengthen ADR data management and expand the reach of pharmacovigilance programs, ADR monitoring centers, and healthcare professionals' especially pharmacists’ training in rural locations.
The New Kernel-based Multiple Instances Learning Algorithm for Object Tracking
Authors: Zhang Hua , Wang Lijia 
Published: October 2023

Background:
Visual tracking is a crucial component of computer vision systems.

Objective:
To deal with the problems of occlusion, pose variation, and illumination in long-time
tracking, we propose a new kernel-based multiple instances learning tracker.

Method:
The tracker captures five positive bags, including the occlusion bag, pose bag, illumination
bag, scale bag, and object bag, to deal with the appearance changes of an object in a complex
environment. A Gaussian kernel function is used to compute the inner product for selecting the
powerful weak classifiers, which further improves the efficiency of the tracker. Moreover, the
tracking situation is determined by using these five classifiers, and the correlating classifiers are
updated.

Results:
The experimental results show that the proposed algorithm is robust in terms of occlusion
and various appearance changes.

Conclusion:
The proposed algorithm preforms well in complex situations.
Network Anomaly Detection using Autoencoder on Various Datasets: A
Comprehensive Review
Authors: Singh Richa , Srivastava Nidhi , Kumar Ashwani 
Published: October 2023

Abstract:
The scientific community is currently very concerned about information and communication
technology security because any assault or network anomaly can have a remarkable collision
on a number of areas, including national security, the storage of private data, social welfare,
economic concerns, and more. As a result, many strategies and approaches for this goal have
been developed over time, making the anomaly detection domain a large research subject. The
primary concern of this study is to review the most crucial elements relating to anomaly detection,
including an overview of background analysis and a core study on the most important approaches,
procedures, and systems in the field. To make the structure of this survey easier to understand,
the domain of anomaly detection was examined along with five dimensions: Detection
methods in network traffic, objectives of the paper, various datasets used, accuracy, and open issues/
gaps. The gap which has been identified after the survey can be extended as a future scope
might be helpful for the researcher.
A Review of Research on Upper Extremity Rehabilitation Robots
Authors: Liu Hongbo , Li Wenheng , Yang Xiaodong 
Published: October 2023

Background:
Most of the patients with limb paralysis caused by stroke and traumatic
brain injury are unable to take care of themselves, which not only causes great physical and psychological
stress to the patients but also poses a heavy burden on their families and society. The
global population is entering the aging phase. The number and proportion of older people is increasing
in almost every country in the world. Population aging has the potential to become one of
the most important social trends of the 21st century, and almost all areas of society are affected by
it, including labor and financial markets, demand for goods and services, such as housing, transportation,
and social security, family structures, and intergenerational relationships. Rehabilitation
robotics is a research field that has emerged from this demand.

Objective:
Through the analysis of the current situation and development of upper limb rehabilitation
robots, several types of upper limb rehabilitation robots with the most widely used structures
today are extracted from the representative results, and each robot is analyzed and elaborated in
detail. It provides a reference for readers to choose the appropriate upper limb rehabilitation robots.

Methods:
We have classified the upper limb rehabilitation robots through several patents, briefly
explained and analyzed the robots grouped, summarized the advantages and disadvantages of various
robots, and provided an outlook on future development trends.

Results:
Through the research and analysis of the degree of freedom and control system of the
upper limb rehabilitation robot, it can be seen that certain upper limb rehabilitation robots have
large structures and complex systems, and their application scope is limited; most domestic rehabilitation
robots have fewer degrees of freedom and can only provide rehabilitation training for
single joints or a few degrees of freedom, especially for the shoulder, which has a small spatial
range, too low range of motion and amplitude, and a single mode of motion, and cannot complete
a wide range of motion for certain joints, as well as a compound motion for multiple joints, thus
failing to provide adequate stimulation of the central nerve.

Conclusion:
The analysis shows that the existing upper limb rehabilitation robots are poorly
adaptable and not well-suited for situations, such as for different patients and different recovery
periods of the same patient. The upper limb rehabilitation robot solution needs to be more appropriately
designed to meet all requirements in the rehabilitation movement of patients.
CYP1A2*F Polymorphism Contributes at Least Partially to the Variability
of Plasma Levels of Dehydroaripiprazole, an Active Metabolite of
Aripiprazole, in Schizophrenic Patients
Authors: Suzuki Takeshi , Nagai Goyo , Mihara Kazuo , Tomori Yoko , Kagawa Shoko , Nakamura Akifumi , Nemoto Kenji , Kondo Tsuyoshi 
Published: October 2023

Aim:
The relationship between CYP1A2 polymorphisms and the steady-state plasma levels of aripiprazole and its active metabolite, dehydroaripiprazole, were investigated in Japanese schizophrenic patients.

Background:
It has been implied that cytochrome P450 (CYP) 1A2 may play a role in the metabo-lism of aripiprazole. Genetic variations in the CYP1A2 gene have been reported.

Objective:
The authors investigated the relationship between 2 CYP1A2 polymorphisms, CYP1A2*C (-3860G>A) and CYP1A2*F (-163C>A), and the steady-state plasma levels/dose (C/D) ratios of aripiprazole and dehydroaripiprazole in Japanese schizophrenic patients.

Methods:
All 89 subjects (46 males and 43 females) had been receiving 2 fixed daily doses of ari-piprazole (24 mg; n=56 and 12 mg: n=33) for more than 2 weeks. No other drugs were used except flunitrazepam and biperiden. The plasma drug levels were determined by LC/MS/MS. These CYP1A2 polymorphisms were detected using polymerase chain reaction analysis.

Results:
The mean C/D ratios of dehydroaripiprazole were significantly (P < 0.05) lower in pa-tients with the A/A allele of CYP1A2*F than in those without the allele. No differences were found in the values of aripiprazole and the combination of aripiprazole and dehydroaripiprazole among the CYP1A2*F genotype. There were no differences in the values of aripiprazole, dehydroaripipra-zole, or the combination of the 2 compounds among the CYP1A2*C genotype. The absence of the A allele of CYP1A2*F was correlated with the mean C/D ratios of dehydroaripiprazole (standardized partial correlation coefficient = 0.276, P < 0.01) by multiple regression analysis.

Conclusion:
The findings of this study suggest that the CYP1A2*F polymorphism contributes at least partially to the variability in the steady-state plasma levels of dehydroaripiprazole.
Effect of Capsule Thickness and Material Properties on the Central Optical Power of Natural Human Lens
Authors: Kakavand Reza , Komeili Amin 
Published: October 2023

Background:A thin membrane capsule covers the eye lens and links the lens and the applied forces by the ciliary muscles. The capsule converts the tension of the concentrated zonules to distributed surface tractions over the cortex surface during the lens accommodation. The gradual changes of the capsule geometry and material properties with age and its important role in the design of intraocular lens implants were the motivation of extensive researches on describing the capsule biomechanical behavior.Aim:The present work aimed to study the lens accommodation response to different capsule thicknesses and material properties at different ages.Materials and Methods:A material and geometry parametric study was performed, drawing some guidelines on the choice of lens capsule thickness and biaxial/uniaxial material parameters and exploring the response sensitivity of the finite element model at different age groupsResults:The 16-, 35- and 48-year-old lenses were considered for lens accommodation simulation. The sensitivity of lens accommodation was studied at each age group by considering constant thickness (cnst-t) and variable thickness (var-t) capsules and biaxial (Biax) and uniaxial (Uniax) material characteristics tests. The lens was stretched through zonules, and corresponding absolute changes in central optical power (COP) were measured.Conclusion:After the stretch, the lens anterior and posterior curvatures increased, producing a change in COP. The Biax models underestimated the ΔCOP compared to the Uniax models. The 16-year lens model was more sensitive to material properties than thickness variation, while thickness variation was more relevant to the ΔCOP of the 35-year lens model. The 48-year model had the least sensitivity to capsule thickness and material property variations.
miRNA as an Ultimate and Emerging Diagnostic Approach for the
Detection of Alzheimer’s Disease
Authors: Jain Mukul , Agarwal Shrishti , Rana Aarzu , Tiwari Ankit , Patil Nil 
Published: October 2023

Abstract:
Alzheimer's disease is a prevalent neurodegenerative disorder primarily affecting elderly
individuals, characterized by cognitive decline and dysfunction in the nervous system. The disease is
hallmarked by the presence of neurofibrillary tangles and amyloid-β plaques. Approximately 10.7%
of the global population aged 65 and above suffer from Alzheimer's disease, and this number is projected
to rise significantly in the foreseeable future. By the year 2050, the worldwide prevalence is
estimated to reach 139 million cases, compared to the current 55 million cases. The identification of
reliable biomarkers that can facilitate the diagnosis and prognosis of Alzheimer's disease is crucial.
MicroRNAs (miRNAs) are a class of small, non-coding RNA molecules that play a significant role
in mRNA regulation and protein level maintenance through mRNA degradation. Over the past decade,
researchers have primarily focused on elucidating the functions and expression patterns of miRNAs
in various diseases, including Alzheimer's disease, to uncover their potential as diagnostic biomarkers.
This review emphasizes the potential of miRNAs as diagnostic biomarkers for Alzheimer's
disease and explores their roles and therapeutic possibilities. MiRNAs possess several features that
make them ideal biomarkers, including their ability to be easily detected in body fluids. Moreover,
the extraction process is minimally invasive, as miRNAs can be readily extracted. Advances in technology
have facilitated the integration of miRNAs into micro-assays, enhancing the reliability and
utility of miRNAs as diagnostic biomarkers for Alzheimer's disease.