bluuebunny/crossref_metadata_2025_split huggingface dataset:
QSPR analysis of drugs for anti-hypertension using degree based topological indices through M-polynomial and NM-polynomial
Authors: A Pradeepa , P Arathi 
Published: November 2023

Abstract
There are several uses for chemical graph theory in experimental science, medicine, drug development, and clinical studies. The statistical characteristics of medications have been developed and determined by topological descriptors. To extract a quantitative structural property/activity relationship (QSPR/QSAR), these indices can be employed alone or in conjunction with other numeric descriptors. Scientists are interested in investigating the chemical network's topology through QSPR investigations, employing specific mathematical constants and parameters derived from the molecular structures of networks. This paper focuses on using the M-polynomials and NM-polynomials of nine anti-hypertensive drugs to compute several degree-based topological indices. It is further shown that these topological descriptors have an excellent correlation with the physicochemical properties of considered anti-hypertensive drugs. Different statistical parameters are analyzed based on the collected results and conclusions are made for each parameter. Researchers exploring drug science in the pharmaceutical sector can utilize the findings to acquire a better understanding of the physical characteristics of newly discovered drugs that are used to treat various diseases.
Mathematics Subject classification (2020): 92E10; 05C09; 05C31; 05C90; 05C92
Towards an intelligent and adapted small scale landslides Monitoring system in East Africa: Shyira Landslide Monitoring Using Sentinel - 1 SAR data On Google Earth Engine Cloud Computing
Authors: Hakizimana Bernard , CHUKWU Kingsley 
Published: November 2023

Abstract
Rainfall-induced landslides pose significant threats in the North-Western provinces of Rwanda, contributing to major disasters. This paper addresses technological challenges in disaster response, specifically focusing on soil displacement quantification. The study concentrates on the local scale around Mukungwa River, employing remote sensing techniques and community science. The methodology involves using INSAR polarization and phase measurements, with a focus on Shyira Landslide Monitoring using Google Earth Engine Cloud Computing.
A citizen science approach was integrated into the study's framework. The methodology for landslide detection included the careful selection of an Area of Interest (AOI) and distinct time periods Before Event (BEvent) and After Event (AEvent) corresponding to the landslide occurrence.
For a comprehensive representation of ground surface properties before and after the landslide event, SAR image stacks were generated. These stacks, calculated as temporal medians of SAR data, were constructed for ascending data, descending data, and a combination of both. Landslide detection involved assessing changes in the backscatter coefficient using the standard SAR intensity log ratio approach.
The classification process categorized changes into three classes: stable, subsidence/decrease, and increase/uplift. To gain deeper insights, a CSV file was generated for statistical analysis, providing a quantitative examination of the landslide event dynamics. The study conducted comprehensive statistical analysis and derived meaningful recommendations.
This research contributes to the understanding of landslide monitoring through a robust methodology that combines remote sensing technologies, community engagement, and statistical analysis. In a sample of data containing 885,632 points generated from imagery within the study area, using Python script code. This dataset was utilized to create a pair plot, effectively visualizing the before-event and after-event data and these have presented a strong correlation.
In a sample of the 5,000 households in the study area, 96 were completely destroyed and 231 heavily damaged .The findings and recommendations have implications for disaster response strategies and underscore the importance of technological advancements in addressing the challenges posed by landslides.
Anti-Gene IGF-I Vaccines in Cancer Gene Therapy: A Review of a
Case of Glioblastoma
Authors: Trojan Annabelle , Lone Yu-Chun , Briceno Ignacio , Trojan Jerzy 
Published: November 2023

Objective:
Vaccines for the deadliest brain tumor - glioblastoma (GBM) - are
generally based on targeting growth factors or their receptors, often using antibodies.
The vaccines described in the review were prepared to suppress the principal cancer
growth factor - IGF-I, using anti-gene approaches either of antisense (AS) or of triple helix
(TH) type. Our objective was to increase the median survival of patients treated with
AS and TH cell vaccines.

Methodology:
The cells were transfected in vitro by both constructed IGF-I AS and
IGF-I TH expression episomal vectors; part of these cells was co-cultured with plant
phytochemicals, modulating IGF-I expression. Both AS and TH approaches completely
suppressed IGF-I expression and induced MHC-1 / B7 immunogenicity related to the
IGF-I receptor signal.

Results:
This immunogenicity proved to be stronger in IGF-I TH than in IGF-I AS-prepared
cell vaccines, especially in TH / phytochemical cells. The AS and TH vaccines
generated an important TCD8+ and TCD8+CD11b- immune response in treated GBM patients
and increased the median survival of patients up to 17-18 months, particularly using
TH vaccines; in some cases, 2- and 3-year survival was reported. These clinical results
were compared with those obtained in therapies targeting other growth factors.

Conclusion:
The anti-gene IGF-I vaccines continue to be applied in current GBM personalized
medicine. Technical improvements in the preparation of AS and TH vaccines to
increase MHC-1 and B7 immunogenicity have, in parallel, allowed to increase in the median
survival of patients.
Prediction of Human Microbe-Drug Association based on Layer
Attention Graph Convolutional Network
Authors: Qu Jia , Ni Jie , Ni Tong-Guang , Bian Ze-Kang , Liang Jiu-Zhen 
Published: November 2023

:
Human microbes are closely associated with a variety of complex diseases and
have emerged as drug targets. Identification of microbe-related drugs is becoming a key
issue in drug development and precision medicine. It can also provide guidance for solving
the increasingly serious problem of drug resistance enhancement in viruses.

Methods:
In this paper, we have proposed a novel model of layer attention graph convolutional
network for microbe-drug association prediction. First, multiple biological data
have been integrated into a heterogeneous network. Then, the heterogeneous network has
been incorporated into a graph convolutional network to determine the embedded microbe
and drug. Finally, the microbe-drug association scores have been obtained by decoding
the embedding of microbe and drug based on the layer attention mechanism.

Results:
To evaluate the performance of our proposed model, leave-one-out crossvalidation
(LOOCV) and 5-fold cross-validation have been implemented on the two datasets
of aBiofilm and MDAD. As a result, based on the aBiofilm dataset, our proposed
model has attained areas under the curve (AUC) of 0.9178 and 0.9022 on global LOOCV
and local LOOCV, respectively. Based on aBiofilm dataset, the proposed model has attained
an AUC value of 0.9018 and 0.8902 on global LOOCV and local LOOCV, respectively.
In addition, the average AUC and standard deviation of the proposed model for 5-
fold cross-validation on the aBiofilm and MDAD datasets were 0.9141±6.8556e-04 and
0.8982±7.5868e-04, respectively. Also, two kinds of case studies have been further conducted
to evaluate the proposed models.

Conclusion:
Traditional methods for microbe-drug association prediction are timeconsuming
and laborious. Therefore, the computational model proposed was used to predict
new microbe-drug associations. Several evaluation results have shown the proposed
model to achieve satisfactory results and that it can play a role in drug development and
precision medicine.
Periodontitis Continuum: Antecedents, Triggers, Mediators, and Treatment Strategies
Authors: Gasmi Benahmed Asma , Tippairote Torsak , Gasmi Amin , Noor Sadaf , Avdeev Oleksandr , Shanaida Yurii , Mojgani Naheed , Emadali Alireza , Dadar Maryam , Bjørklund Geir 
Published: November 2023

:
Periodontitis (PD) is a chronic inflammatory disease of the periodontium characterized
by the formation of gingival pockets and gingival recession. The local inflammatory
environment can lead to the destruction of the extracellular matrix and subsequent
bone loss. The pathophysiology of PD involves interactions between genetic predisposition,
lifestyle, environmental factors, the oral microbiota condition, systemic
health disorders, innate and adaptive immune responses, and various host defenses. The
review highlighted the importance of the oral cavity condition in systemic health. Thus,
a correlation between harmful oral microbiota and cardiovascular disease (CVD)/diabetes/
arthritis, etc, progressions through inflammation and bacterial translocation was
highlighted. Antecedents increase an individual's risk of developing PD, trigger initiate
microbe-host immunologic responses, and mediators sustain inflammatory interactions.
Generally, this review explores the antecedents, triggers, and mediators along the pathophysiological
continuum of PD. An analysis of modern approaches to treating periodontitis,
including antibiotics for systemic and local use, was carried out. The potential role
of natural ingredients such as herbal extracts, phytoconstituents, propolis, and probiotics
in preventing and treating PD was highlighted.
Identification of an Exosome-relevant SNHG6-hsa-miR-429-
CHRDL1/CCNA2 Axis for Lung Adenocarcinoma Prognosis
Evaluation
Authors: Yuan Yuan , Li Qian , Chen Feifei , Zhao Yujie , Ma Jiyong , Fang Surong 
Published: November 2023

Aims:
To explore an exosome-relevant molecular classification in lung adenocarcinoma (LUAD).

Background:
Exosome genes or relevant non-coding RNAs are regulators of cancer
treatment and prognosis, but their function in LUAD has not yet been determined.

Objective:
Unraveling a molecular classification applying exosome-related RNA networks for LUAD prognosis evaluation.

Methods:
MicroRNA sequencing data (miRNAs-seq) and RNA sequencing data (RNA-
seq) were derived from The Cancer Genome Atlas (TCGA). The ConsensusCluster-
Plus package was used for molecular typing in LUAD based on 121 Exosome-related
genes. Then, a limma package was conducted to explore differentially expressed mRNAs
(DEmRNAs), differentially expressed miRNAs (DEmiRNAs) and differentially expressed
lncRNAs (DElncRNAs) in molecular typing for constructing an Exosome-driven
competing endogenous RNA network (ceRNA). Dominant miRNAs, as well as target
mRNAs, were identified by COX modeling and Kaplan-Meier survival analysis.

Results:
Two Exosome-associated molecular clusters classified in LUAD. The C2 cluster
favored high clinicopathology and showed a trend toward poor prognosis. 29 lncRNA-
miRNA and 12 miRNA-mRNA interaction pairs were identified. The hsa-miR-429
was the pivotal miRNA in the network that affected the prognosis of LUAD. According
to the interaction relationship and LUAD prognostic role, SNHG6-hsa-
miR-429-CHRDL1/CCNA2 was identified. SNHG6-hsa-miR-429-CHRDL1 exerts
oncogenic effects, and SNHG6-hsa-miR-429- CCNA2 exerts pro-oncogenic effects.

Conclusion:
Overall, our study identified an Exosome-driven ceRNA network in LUAD,
and the SNHG6-hsa-miR-429-CHRDL1/CCNA2 axis could be a new therapeutic
target for LUAD and our study provides new insights into the molecular mechanisms of
LUAD.
Design, Molecular Modeling, MD Simulations, Essential Dynamics, ADMET, DFT,
Synthesis, Anti-proliferative, and Apoptotic Evaluations of a New Anti-VEGFR-2
Nicotinamide Analogue
Authors: Eissa Ibrahim H. , Elkaeed Eslam B. , Elkady Hazem , Yousef Reda G. , Alsfouk Bshra A. , Elzahabi Heba S.A. , Ibrahim Ibrahim M. , Metwaly Ahmed M. , Husein Dalal Z. 
Published: November 2023

Objectives:
This study aims to design and evaluate (in silico and in vitro) a new nicotinamide derivative
as an inhibitor of VEGFR-2, a major mediator of angiogenesis.

Methods:
The following in silico studies were performed; DFT calculations, molecular modelling, MD simulations,
MM-GBSA, PLIP, and PCAT studies. The compound's in silico (ADMET) analysis was also
conducted. Subsequently, the compound ((E)-N-(4-(1-(2-(4-(4-Chlorobenzamido)benzoyl)hydrazono)ethyl)
phenyl)nicotinamide) was successfully synthesized and designated as compound X. In vitro, VEGFR-2 inhibition
and cytotoxicity of compound X against HCT-116 and A549 cancer cell lines and normal Vero cell lines
were conducted. Apoptosis induction and migration assay of HCT-116 cell lines after treatment with compound
X were also evaluated.

Results:
DFT calculations assigned stability and reactivity of compound X. Molecular docking and MD simulations
indicated its excellent binding against VEGFR-2. Furthermore, MM-GBSA analysis, PLIP experiments,
and PCAT studies confirmed compound X’s correct binding with optimal dynamics and energy. ADMET
analysis expressed its general likeness and safety. The in vitro assays demonstrated that compound X
effectively inhibited VEGFR-2, with an IC50 value of 0.319 ± 0.013 μM and displayed cytotoxicity against
HCT-116 and A549 cancer cell lines, with IC50 values of 57.93 and 78.82 μM, respectively. Importantly,
compound X exhibited minimal toxicity towards the non-cancerous Vero cell lines, (IC50 = 164.12 μM). Additionally,
compound X significantly induced apoptosis of HCT-116 cell lines and inhibited their potential to
migrate and heal.

Conclusion:
In summary, the presented study has identified compound X as a promising candidate for the development
of a novel apoptotic lead anticancer drug.
Withaferin A Inhibits Liver Cancer Tumorigenesis by Suppressing
Aerobic Glycolysis through the p53/IDH1/HIF-1α Signaling Axis
Authors: Zhou Xiangyang , Wu Di , Zhu Linmiao , Li Ruohan , Yu Haitao , Li Wenjuan 
Published: November 2023

Background:
The energy supply of certain cancer cells depends on aerobic glycolysis
rather than oxidative phosphorylation. Our previous studies have shown that withaferin A (WA), a
lactone compound derived from Withania somnifera, suppresses skin carcinogenesis at least partially
by stabilizing IDH1 and promoting oxidative phosphorylation. Here, we have extended our
studies to evaluate the anti-tumor effect of WA in liver cancer.

Methods:
Differential expression of glycolysis-related genes between liver cancer tissues and normal
tissues and prognosis were verified using an online database. Glycolysis-related protein expression
was detected using western blot after overexpression and knockdown of IDH1 and mitochondrial
membrane potential assay based on JC-1, and mitochondrial complex I activity was also
detected. The inhibitory effect of WA on the biological functions of HepG2 cells was detected
along with cell viability using MTT assay, scratch assay, clone formation assay, glucose consumption
and lactate production assay. Western blot and qRT-PCR were used to detect the expression
of proteins and genes related to IDH1, p53 and HIF1α signaling pathways.

Results:
We first identified that IDH1 expression was downregulated in human liver cancer cells
compared to normal liver cells. Next, we found that treatment of HepG2 cells with WA resulted in
significantly increased protein levels of IDH1, accompanied by decreased levels of several glycolytic
enzymes. Furthermore, we found that WA stabilized IDH1 proteins by inhibiting the degradation
by the proteasome. The tumor suppressor p53 was also upregulated by WA treatment, which
played a critical role in the upregulation of IDH1 and downregulation of the glycolysis-related
genes. Under hypoxic conditions, glycolysis-related genes were induced, which was suppressed
by WA treatment, and IDH1 expression was still maintained at higher levels under hypoxia.

Conclusion:
Taken together, our results indicated that WA suppresses liver cancer tumorigenesis
by p53-mediated IDH1 upregulation, which promotes mitochondrial respiration, thereby inhibiting
the HIF-1α pathway and blocking aerobic glycolysis.
An Updated Review on Molecular Biomarkers in Diagnosis and Therapy
of Colorectal Cancer
Authors: Ravichandran Shruthi Nagainallur , Kumar Makalakshmi Murali , Das Alakesh , Banerjee Antara , Veronica Suhanya , Sun-Zhang Alexander , Zhang Hong , Anbalagan Muralidharan , Sun Xiao-Feng , Pathak Surajit 
Published: November 2023

Abstract:
Colorectal cancer is one of the most common cancer types worldwide. Since colorectal
cancer takes time to develop, its incidence and mortality can be treated effectively if it is detected
in its early stages. As a result, non-invasive or invasive biomarkers play an essential role in the early diagnosis of colorectal cancer. Many experimental studies have been carried out to assess genetic, epigenetic, or protein markers in feces, serum, and tissue. It may be possible to find biomarkers
that will help with the diagnosis of colorectal cancer by identifying the genes, RNAs, and/or proteins indicative of cancer growth. Recent advancements in the molecular subtypes of colorectal
cancer, DNA methylation, microRNAs, long noncoding RNAs, exosomes, and their involvement
in colorectal cancer have led to the discovery of numerous new colorectal cancer biomarkers. In
small-scale investigations, most biomarkers appear promising. However, large-scale clinical trials
are required to validate their effectiveness before routine clinical implementation. Hence, this review focuses on small-scale investigations and results of big data analysis that may provide an
overview of the biomarkers for the diagnosis, therapy, and prognosis of colorectal cancer.
Interaction of C-terminal Truncated Beta-amyloid Peptides with Human Serum Albumin
Authors: Firozabadi Diba Aslani , Bozorgmehr Mohammad Reza , Beyramabadi Safar Ali , Mohseni Sharareh 
Published: November 2023

Background:
The formation of plaque from protein fibrils is the major source of diseases,
such as Alzheimer's and Prion diseases. Amyloid beta (Aβ) is a peptide with different lengths,
which is one of the main components of the plaque in the brain of people with Alzheimer's. Of the
amyloid beta of various lengths in the brain cells plaque, beta-amyloid with 40 amino acids (Aβ1-
40) is more abundant than the rest. Aβ monomers are in a dynamic equilibrium of various conformations
with beta sheets that aggregate as oligomers or larger structures. The misfolding of betaamyloid
peptide is involved in its accumulation. On the other hand, various species that exist in the
cell environment can affect the structure of beta-amyloid peptides.

Aims:
This study aimed to study the interaction of truncated forms of beta-amyloid peptide with
human albumin serum protein.

Objective:
Interaction of beta-amyloid peptide with other proteins is effective in causing Alzheimer's
disease. These include interactions between beta-amyloid and cell surface proteins, such as
prions and extracellular proteins, such as clusterins and human serum albumin (HSA). As HSA
concentrations are higher than other proteins, more than half of the interaction of beta-amyloid with
proteins is related to interaction with this protein. Interaction of HSA with beta-amyloid reduces the
aggregation of beta-amyloid. However, due to the diversity of beta-amyloid peptides with different
lengths, the mechanism of their interaction with HSA has not been well understood. In this work,
the interaction of C-terminal truncated beta-amyloid peptides with HSA has been investigated.

Method:
The C-terminal truncated forms of beta-amyloid peptides, Aβ1 − 26, Aβ1 − 30, and
Aβ1 − 36 and Aβ1 − 40, were designed in silico. Docking between these truncated peptides was
performed with serum albumin. A molecular dynamics simulation of the interaction of designed
peptides with serum albumin was also performed.

Results and Discussion:
The results showed that Aβ1 − 26 and Aβ1 − 30 peptides interact with the
interfacial region of the chains A and B of HSA and the surface of the HSA. While the interaction of
Aβ1 − 36 and Aβ1 − 40 peptides occurs only with the HSA surface. On the other hand, the interaction
of peptides with chain A of HSA is more favorable than their interaction with chain B of HSA.
Also, as the length of the peptide increases, the number of residues involved in the hydrophobic interaction
increases. The results of molecular dynamics simulation confirm the results obtained from
docking.

Conclusion:
The results of molecular dynamics and docking simulations show that the binding affinity
of peptides to serum albumin decreases with peptide shortening. Also, by changing the structure
of beta-amyloid peptides, serum albumin reduces their tendency to aggregate.
Immunomodulatory Effects of Clozapine: More Than Just a Side Effect in
Schizophrenia
Authors: Amerio Andrea , Magnani Luca , Arduino Gabriele , Fesce Fabio , de Filippis Renato , Parise Alberto , Costanza Alessandra , Nguyen Khoa D. , Saverino Daniele , De Berardis Domenico , Aguglia Andrea , Escelsior Andrea , Serafini Gianluca , De Fazio Pasquale , Amore Mario 
Published: November 2023

Abstract:
Recent evidence suggests a possible relationship between the immune system and schizophrenia
spectrum disorders (SSDs), as neuroinflammation appears to play a role in major psychiatric
conditions. Neuroinflammation is as a broad concept representing a physiological protective response
to infection or injury, but in some cases, especially if chronic, it may represent an expression of maladaptive
processes, potentially driving to clinical dysfunction and neurodegeneration. Several studies
are concurrently highlighting the importance of microglia, the resident immune cells of the central
nervous system, in a huge number of neurodegenerative diseases, including multiple sclerosis, Alzheimer’s
and Parkinson’s diseases, as well as SSDs. A more fundamental phenomenon of maladaptive
coupling of microglia may contribute to the genesis of dysfunctional brain inflammation involved in
SSDs, from the onset of their neurophenomenological evolution. Clozapine and other antipsychotic
drugs seem to express a provable immunomodulant effect and a more specific action on microglia,
while neuroactive steroids and nonsteroidal anti-inflammatory drugs may reduce some SSDs symptoms
in add-on therapy. Given these theoretical premises, this article aims to summarize and interpret
the available scientific evidence about psychotropic and anti-inflammatory drugs that could express an
immunomodulant activity on microglia.