bluuebunny/crossref_metadata_2025_split huggingface dataset:
3D Gait Analysis in Children Using Wearable Sensors: Feasibility of Predicting Joint Kinematics and Kinetics with Personalized Machine Learning Models and Inertial Measurement Units
Authors: Moghadam Shima Mohammadi , Auriol Pablo Ortega , Yeung Ted , Choisne Julie 
Published: January 2024

Abstract

Children's walking patterns evolve with age, exhibiting less repetitiveness at a young age and more variability than adults. Three-dimensional gait analysis (3DGA) is crucial for understanding and treating lower limb movement disorders in children, traditionally performed using Optical Motion Capture (OMC). Inertial Measurement Units (IMUs) offer a cost-effective alternative to OMC, although challenges like drift errors persist. Machine learning (ML) models can mitigate these issues in adults, prompting an investigation into their applicability to a heterogeneous paediatric population. This study aimed at identifying an optimal ML model tailored for children's gait, enabling accurate predictions from IMUs. Seventeen typically developed (TD) children, aged 6 to 15, participated in data collection involving OMC, force plates, and IMU sensors. Joint kinematics and kinetics were computed from OMC and force plates' data using OpenSim. Tsfresh, a Python package, extracted features from raw IMU data. Each target's ten most important features were input in the development of personalized and generalized random forest (RF) and convolutional neural networks (CNN) models. Findings suggested that the RF and CNN models demonstrated comparable performance. RF predicted joint kinematics with a 9.5% and 19.9% NRMSE for personalized and generalized models, respectively, and joint kinetics with an NRMSE of 10.7% for personalized and 15.2% for generalized models in TD children. Personalized models provided accurate estimations from IMU data in children, while generalized models lacked accuracy due to the limited dataset. This study proposed a promising approach for gait time series prediction in children, involving an RF model and two IMUs on the feet.
Graph Neural Networks with Rule-based Embeddings for Enhanced Recommender System
Authors: Williams Samuel , Smith Benjamin , Carter Daniel 
Published: January 2024

Abstract
We are now entering the era of big data, transitioning from a previous era of information scarcity to one where we face significant information overload. In this context, the challenge of filtering out valuable information for individuals from the vast sea of internet data has become increasingly important. A graph is a crucial information organization structure consisting of nodes and edges. Content-based recommendation systems require extensive background knowledge about items and users. This knowledge can often be organized in the form of a knowledge graph. With the development of the internet, a considerable amount of knowledge has been structured into graphs, such as Wikipedia or knowledge trees and classification tree structures like e-commerce directories. This paper conducts research on recommender systems based on graph neural network (GNN) technology. Utilizing graph convolutional neural networks, a graph information extractor is constructed to merge information from the user-item bipartite graph's node neighbors and generate dense vector representations for the nodes. The model employs a multi-task learning approach by introducing the reconstruction tasks of auxiliary information graphs for users and items into the traditional collaborative filtering recommendation task through graph neural networks.
Time Course of Biochemical and Metabolic Parameters During and
After COVID-19
Authors: Ghoreshi Zohreh-al-sadat , Abbasi-jorjandi Mojtaba , Asadikaram Gholamreza , Sharif-zak Mohsen , Haddad Mohammad Khaksari , Afgar Ali , Arefinia Nasir , Dabiri Shahriar , Rosen Clifford 
Published: January 2024

Background:
Long COVID is characterized by the persistence of symptoms among individuals who are infected with the SARS-CoV-2 virus. The enduring impact of these long-term
effects on the health and well-being of those affected cannot be denied.

Method:
About 470 patients with SARS-CoV-2 were consecutively recruited in this longitudinal
study. The participants were entered into moderate, severe, and critical groups. 235 out of 470 participants were female. The levels of fasting blood sugar (FBS), alanine transaminase (SGPT), aspartate aminotransferase (SGOT), alkaline phosphatase (ALP), creatinine (Cr), urea, uric acid
(UA), and total protein (TP) were measured during hospitalization and again at one and three
months after infection. The levels of Zn and hemoglobin A1c (HbA1c) were also measured only
during hospitalization.

Result:
COVID-19 severity was associated with high levels of glucose, urea, Cr, ALT, AST,
ALP, and HbA1c, and low levels of Zn, UA, and TP. There were significant sex differences for these markers at all three-time points. Glucose, urea, Cr, ALT, AST, and ALP all decreased three
months after infection, whereas the levels of UA and TP returned towards normal.

Conclusion:
COVID-19 infection affects the levels of multiple biochemical factors in a gender-dependent manner. The biochemical changes become more tangible with increasing disease severity,
and several of these predict mortality. Levels begin to return to normal after the acute phase of the
disease, but in some individuals, at three months, several markers were still not within the normal
range. Whether the trajectory of these changes can predict long COVID requires further testing.
Statin Therapy and Lipid Indices in Chronic Kidney Disease: A Systematic
Review and Meta-analysis of Randomized Control Trials
Authors: Karami Jafar , Razi Bahman , Imani Danyal , Aslani Saeed , Pakjoo Mahdi , Fasihi Mahdieh , Mohammadi Keyhan , Sahebkar Amirhossein 
Published: January 2024

Background:
Several studies have demonstrated the improvement in serum lipoproteins by statins
in patients with Chronic Kidney Diseases (CKDs), including End-Stage Renal Disease (ESRD). However, the
results of these studies are inconclusive.

Aims:
We aimed to systematically investigate the effect of statins on lipid profiles of patients with CKD by performing
a meta-analysis of Randomized Controlled Trials (RCTs).

Methods:
Major electronic databases (Scopus, MEDLINE/PubMed, and ISI Web of Science) were searched
from inception to August, 2023, to find randomized controlled trials (RCTs) evaluating the effect of different
statins on serum lipoproteins in CKD patients. Weighted Mean Difference (WMD) with 95% Confidence Intervals
(CI) was used to estimate the effect size. Trial Sequential Analysis (TSA) was performed to confirm the
robustness of the evidence.

Results:
A total of 18 publications were identified. It was found that statins reduced serum levels of Low-Density
Lipoprotein (LDL)-C (WMD = -27.81 mg/dl, 95% CI = -34.47 to -21.15, P < 0.001) and total cholesterol
(WMD = -25.44 mg/dl, 95% CI = -34.71 to -16.18, P < 0.001) in patients with CKD compared to the control
group. Nonetheless, the effect of statins on High-Density Lipoprotein (HDL)-C (WMD = 0.57 mg/dl, 95% CI
= -0.71 to 1.85, P = 0.38) and Triglyceride (TG) (WMD = -9.08 mg/dl, 95% CI = -22.22 to 2.06, P = 0.11)
was not statistically significant. The results of TSA confirmed the robustness of the evidence and were consistent
with the pooled effect size. The findings of subgroup analysis and time response analysis were also significant.

Conclusion:
It was found that statin therapy reduced the levels of LDL-C and total cholesterol in patients with
CKD.
The Role of Zuo Jin Wan in Modulating the Tumor Microenvironment of Colorectal Cancer
Authors: Wang Jiajia , Hua Dongming , Li Mengyao , Liu Ningning , Zhang Yingru , Zhao Yiyang , Jiang Shasha , Hu Xueqing , Wang Yan , Zhu Huirong 
Published: January 2024

Introduction:
Traditional Chinese medicine (TCM) can modulate the immune function
of tumor patients in various ways. Zuojin Wan (ZJW, a 6:1 ratio of Huang Lian and Wu Zhu
Yu) can modulate the microenvironment of ulcerative colitis, but its role in regulating the colorectal
cancer (CRC) microenvironment remains unclear. Exploring the role of ZJW in CRC immunomodulation
may improve the antitumor effect of existing immunotherapeutic strategies.

Material and Methods:
The active compounds of each herb in ZJW were obtained from the HIT2.0
database with literature evidence. Single-cell RNA sequencing data of CRC were obtained from
published studies (PMID: 32451460, 32103181, and 32561858). Pathway enrichment was analyzed
using the reactome database, and intergenic correlation analysis was performed using the corrplot R
software package. ZJW-regulated gene expression was verified by RT-qPCR.

Results:
Huang Lian and Wu Zhu Yu contain 19 and 4 compounds, respectively. Huang Lian
targets 146 proteins, and Wu Zhu Yu targets 28 proteins based on evidence from the literature.
ZJW regulates a range of biological processes associated with immune function, including cytokine
signaling and Toll-Like Receptor 4 (TLR4) cascade. ZJW regulates malignant CRC cells, immune
cells (including T-cells, B-cells, mast cells, NK/NKT cells, and myeloid cells), and other nonimmune
cells (including endothelial cells, enteric glial cells, and pericytes). We confirmed that ZJW
significantly downregulated the expression of TIMP1 and MTDHin CRC cell lines.

Conclusions:
ZJW regulates a range of cells in the CRC microenvironment, including malignant
CRC, immune cells, and stromal cells. In CRC cell lines, downregulation of TIMP1 and MTDH
by ZJW may play an important role in the immunomodulation in CRC.
Cancer and Autoimmune Diseases as Two Sides of Chronic Inflammation
and the Method of Therapy
Authors: Rogovskii Vladimir 
Published: January 2024

:
Chronic inflammation is associated with a prolonged increase in various inflammatory
factors. According to clinical data, it can be linked with both cancer and autoimmune diseases in
the same patients. This raises the critical question of how chronic inflammation relates to seemingly
opposing diseases - tumors, in which there is immunosuppression, and autoimmune diseases, in
which there is over-activation of the immune system. In this review, we consider chronic inflammation
as a prerequisite for both immune suppression and an increased likelihood of autoimmune
damage. We also discuss potential disease-modifying therapies targeting chronic inflammation,
which can be helpful for both cancer and autoimmunity. On the one hand, pro-inflammatory factors
persisting in the areas of chronic inflammation stimulate the production of anti-inflammatory
factors due to a negative feedback loop, eliciting immune suppression. On the other hand, chronic
inflammation can bring the baseline immunity closer to the threshold level required for triggering
an autoimmune response using the bystander activation of immune cells. Focusing on the role of
chronic inflammation in cancer and autoimmune diseases may open prospects for more intensive
drug discovery for chronic inflammation.
Cytoplasmic Polyadenylation Element Binding Protein 1 and Atherosclerosis: Prospective Target and New Insights
Authors: Zhou Jing , Tang Chao-Ke 
Published: January 2024

Abstract:The ribonucleic acid (RNA)-binding protein Cytoplasmic Polyadenylation Element Binding Protein 1 (CPEB1), a key member of the CPEB family, is essential in controlling gene expression involved in both healthy physiological and pathological processes. CPEB1 can bind to the 3'- untranslated regions (UTR) of substrate messenger ribonucleic acid (mRNA) and regulate its translation. There is increasing evidence that CPEB1 is closely related to the pathological basis of atherosclerosis. According to recent investigations, many pathological processes, including inflammation, lipid metabolism, endothelial dysfunction, angiogenesis, oxidative stress, cellular senescence, apoptosis, and insulin resistance, are regulated by CPEB1. This review considers the prevention and treatment of atherosclerotic heart disease in relation to the evolution of the physiological function of CPEB1, recent research breakthroughs, and the potential participation of CPEB1 in atherosclerosis.
Nutritional and Health Benefits of Cereals and Grains
Authors: Zaib Sumera , Hayat Aqsa , Khan Imtiaz 
Published: January 2024

:
The consumption of cereals and grains, along with whole grain food, is considered a
healthy food that has various health benefits. Minerals, proteins, carbohydrates, and vitamins are
present in the diet of many people. Phytochemicals play an essential role in combating oxidative
stress and are present in high amounts in grains. These phytochemicals are also known as secondary metabolites that are present in plants. The nutritional components of basil (Ocimum
basilicum), chia (Salvia hispanica), flax (Linum usitatissimmum), Proso millet (Panicum miliaceum), and oat (Avena sativa) are analyzed. Seeds are considered a good source of omega-3 and
omega-6 fatty acids that have a significant impact on human health. The high amount of tocopherol (vitamin E) is due to the high content of polyunsaturated fatty acids (PUFAs). γ-Tocopherol is an antioxidant nutrient that usually blocks the formation of carcinogenic nitrosamines
from nitrites present in food in the stomach. This review provides detailed information on the nutritional and health benefits of these cereals and grains, in which all the major components have
been discussed. Conclusively, the potential use of these cereals and grains alone and by mixing
them with other food products is also discussed which may enhance the nutritional content of the
food product.
The Effect of Sexual Education Program on Sexual Function and Genital Self-image, Sexual Quality of Life among Primiparous Women
Authors: Rasekh Jahromi Athar , Jafari Hanie , Adedi Parvin , Javadnoori Mojgan , Mohammadi Solmaz , Rahmanian Vahid , Jamali Safieh 
Published: January 2024

Background:
Pregnancy, childbirth, and the postpartum period are among the events that
affect sexual behaviors and interactions, which are associated with many physical and emotional
changes.

Objective:
This study aims to examine the effect of sex education on Genital Self-Image (GSI),
Sexual Quality of Life (SQOL), and sexual function among primiparous women.

Methods:
This study was a randomized controlled trial conducted on 140 primiparous women referred
to the Women's Clinic of Jahrom City from February to October 2020. Participants were assigned
to an intervention group (n = 70) and a control group (n = 70). The intervention group received
sexual education consisting of two sessions a week (90 min each) for eight consecutive
weeks; the control group received none. Female Sexual Function Index (FSFI), Sexual Quality of
life-Female (SQOL-F) questionnaire, and Genital Self-Image were completed before and four
weeks after the end of the intervention in both groups. Questionnaires were used to assess the variables'
dimensions both before and after each intervention. Descriptive statistics, Chi-square test, independent
t-test, paired t-test, analysis of covariance, and regression analysis were used to examine
the collected data in SPSS 21.

Results:
The total score of FSFI in the intervention group significantly increased from 24.14 ± 3.02
to 27.31 ± 2.59 (P< 0.0001) .Besides, there was a significant difference among the mean scores of
the FSFI domains, including desire (4.82 ± 0.84 vs. 3.42 ± 0.98), arousal (4.91 ± 0.67 vs. 3.60 ±
1.12), orgasm (5.14 ± 0.82 vs. 3.53 ± 1.49), lubrication (5.94 ± 0.83 vs. 4.47 ± 0.97), satisfaction
(5.50 ± 0.67 vs. 4.62 ± 1.09), pain (3.53 ± 1.01 vs. 4.26 ± 1.42), total Score FSFI (27.86 ± 3.56 vs.
24.02 ± 4.84), genital self-image (20.44 ± 3.16 vs. 10.41 ± 2.22), and sexual quality of life (52.37 ±
3.61 vs. 30.87 ± 3.47) between the intervention, and control groups after the educational intervention
(p< 0.05). There was no such difference before the intervention.

Conclusion:
Sexual education improves sexual function, GSI, and SQOL in primiparous women.
Therefore, sexual education workshops are suggested to prevent sexual problems in the postpartum
period for all women, especially primiparous women.
The Cytotoxicity Effect of Chitosan-Encapsulated Ricin-Herceptin Immunotoxin Nanoparticles on Breast Cancer Cell Lines
Authors: Golestani Poor Mohammad Hossein , Zare Karizi Shohreh , Mirhosseini Seyed Ali , Motamedi Mohammad Javad , Frootan Fateme , Khani Soghra , Amani Jafar 
Published: January 2024

Background:
The use of targeted therapy has been increasing for cancer treatment.
The aim of this study is to investigate chitosan-based ricin-Herceptin (rh) immunotoxin on breast
cancer cell lines.

Methods:
The gene construct encoding immunotoxin was designed, cloned, and expressed in E.
coli BL21 (DE3). The expressed proteins were isolated by the nickel-nitrilotriacetic acid column
and were analyzed by the Western-blotting. The cytotoxicity of immunotoxin was assayed on
breast cell line MCF-7 and using MTT assay at 24 and 48 h treatment.

Results:
The immunotoxins extrication rate, size, loading percentage, and electric charge of
nanoparticles were reported appropriately as 78%, 151.5 nm, 83.53%, and +11.1 mV, respectively.
The encapsulated immunotoxins led to the death of 70% and 78% of MCF-7 cells at 24
and 48 h treatment, respectively. The noncapsulated counterparts at equal doses killed 53% and
62% of cancer cells at the same time points.

Conclusion:
The chitosan-immunotoxins impose potential cytotoxic effects on cancer cells.
Achievements and Difficulties with Batch and Optimization Investigations of Heavy Metal Adsorptive Removal Utilizing Enhanced Biomass-based Adsorption Materials
Authors: El-Fahaam Mohamed M. , Sanad Mohamed N. , Farouz Mohamed 
Published: January 2024

:
Surface enhancement improves the porousness and surface area (SSA) of biomass
materials, which boosts their adsorption capability. This work investigates recent advances in
surface modification technologies of biomass-based materials for heavy metal adsorption, including
Pb, As, Cr, Fe, Cd, Mn, Cu, Co, Hg, Ni, Zn, and their ions in waters/wastewaters. The
chemical structure and surface properties of biomass were examined in connection with various
surface modification approaches and their effects on the adsorption process. In addition, adsorption
performance we assessed using various operating conditions, isotherms, kinetics, and computational
and artificial intelligence methodologies. This study found that acid-activated Posidonia
oceanica had the highest adsorption effectiveness of 631.13 mg/g to eliminate Pb2+, whereas
H3PO4/furnace-modified oil palm biomass had the lowest (0.1576 mg/g) for removing Cd2+.
Important insights into knowledge gaps for changing these materials for extremely effective
adsorption performance were emphasized to improve the area.
An Expedition on Synthetic Methodology of FDA-approved Anticancer Drugs
(2018-2021)
Authors: Vishakha S. , Navneesh N. , Kurmi Balak Das , Das Gupta Ghanshyam , Verma Sant Kumar , Jain Ankit , Patel Preeti 
Published: January 2024

Abstract:
New drugs being established in the market every year produce specified structures for selective biological
targeting. With medicinal insights into molecular recognition, these begot molecules open new rooms for
designing potential new drug molecules. In this review, we report the compilation and analysis of a total of 56
drugs including 33 organic small molecules (Mobocertinib, Infigratinib, Sotorasib, Trilaciclib, Umbralisib, Tepotinib,
Relugolix, Pralsetinib, Decitabine, Ripretinib, Selpercatinib, Capmatinib, Pemigatinib, Tucatinib, Selumetinib,
Tazemetostat, Avapritinib, Zanubrutinib, Entrectinib, Pexidartinib, Darolutamide, Selinexor, Alpelisib,
Erdafitinib, Gilteritinib, Larotrectinib, Glasdegib, Lorlatinib, Talazoparib, Dacomitinib, Duvelisib, Ivosidenib,
Apalutamide), 6 metal complexes (Edotreotide Gallium Ga-68, fluoroestradiol F-18, Cu 64 dotatate, Gallium 68
PSMA-11, Piflufolastat F-18, 177Lu (lutetium)), 16 macromolecules as monoclonal antibody conjugates (Brentuximabvedotin,
Amivantamab-vmjw, Loncastuximabtesirine, Dostarlimab, Margetuximab, Naxitamab, Belantamabmafodotin,
Tafasitamab, Inebilizumab, SacituzumabGovitecan, Isatuximab, Trastuzumab, Enfortumabvedotin,
Polatuzumab, Cemiplimab, Mogamulizumab) and 1 peptide enzyme (Erwiniachrysanthemi-derived
asparaginase) approved by the U.S. FDA between 2018 to 2021. These drugs act as anticancer agents against
various cancer types, especially non-small cell lung, lymphoma, breast, prostate, multiple myeloma, neuroendocrine
tumor, cervical, bladder, cholangiocarcinoma, myeloid leukemia, gastrointestinal, neuroblastoma, thyroid,
epithelioid and cutaneous squamous cell carcinoma. The review comprises the key structural features, approval
times, target selectivity, mechanisms of action, therapeutic indication, formulations, and possible synthetic approaches
of these approved drugs. These crucial details will benefit the scientific community for futuristic new
developments in this arena.
Lead Identification Through In Silico Studies: Targeting Acetylcholinesterase
Enzyme Against Alzheimer’s Disease
Authors: Agarwal Dhairiya , Kumar Sumit , Ambatwar Ramesh , Bhanwala Neeru , Chandrakar Lokesh , Khatik Gopal L. 
Published: January 2024

Aim:
In this work, we aimed to acquire the best potential small molecule for Alzheimer's
disease (AD) treatment using different models in Biovia Discovery Studio to identify
new potential inhibitors of acetylcholinesterase (AChE) via in silico studies.

Background:
The prevalence of cognitive impairment-related neurodegenerative disorders,
such as AD, has been observed to escalate rapidly. However, we still know little about the underlying
functions, outcome predictors, or intervention targets causing AD.

Objective:
The objective of the study was to optimize and identify the lead compound to target
AChE against Alzheimer’s disease.

Method:
Different in silico studies were employed, including the pharmacophore model, virtual
screening, molecular docking, de novo evolution model, and molecular dynamics.

Result:
The pharmacophoric features of AChE inhibitors were determined by ligand-based
pharmacophore models and 3D QSAR pharmacophore generation. Further validation of the
best pharmacophore model was done using the cost analysis method, Fischer’s randomization
method, and test set. The molecules that harmonized the best pharmacophore model with the
estimated activity < 1 nM and ADMET parameters were filtered, and 12 molecules were subjected
to molecular docking studies to obtain binding energy. 3vsp_EK8_1 secured the highest
binding energy of 65.60 kcal/mol. Further optimization led to a 3v_Evo_4 molecule with a better
binding energy of 70.17 kcal/mol. The molecule 3v_evo_4 was subjected to 100 ns molecular
simulation compared to donepezil, which showed better stability at the binding site.

Conclusion:
A lead compound, 3v_Evo_4 molecule, was identified to inhibit AChE, and it
could be further studied to develop as a drug with better efficacy than the existing available
drugs for treating AD.