bluuebunny/crossref_metadata_2025_split huggingface dataset:
Simultaneous Determination of Glycerol and Carbohydrates in Sweat by
Capillary Electrophoresis with Amperometric Detection
Authors: Jiang Zhe , Zhao Jinlei , Wang Xing , Lu Jianzhong , Chen Gang 
Published: July 2024

Background:
Glycerol, sucrose, lactose, glucose, and fructose are important biomarkers
in human sweat because their contents can reflect physiological status and health conditions. It is of
high importance to determine them in sweat for health monitoring, disease diagnosis, physical training, etc.

Aim:
The aim of this work is to develop a method based on capillary electrophoresis and amperometric detection for the simultaneous determination of glycerol and carbohydrates in sweat.

Objective:
A capillary electrophoretic method based on pipette-tip-based detection electrodes and
micro-injectors was developed for the simultaneous determination of glycerol, sucrose, lactose, glucose, and fructose in sweat samples

Method:
Sweat samples diluted in the background electrolyte of 75 mM NaOH aqueous solution
were electrokinetically introduced into a piece of separation capillary via pipette tip-based microinjectors. Glycerol, sucrose, lactose, glucose, and fructose were determined by capillary electrophoresis in combination with a pipette-tip-based copper electrode.

Results:
At a DC voltage of 12 kV, the capillary electrophoretic separation of the five analytes could
be achieved in less than 11 min in a piece of 40 cm long fused silica capillary containing 75 mM
NaOH aqueous solution. Linearity was observed between the currents and concentrations, with the
limits of detection ranging from 0.21 to 0.72 µM at a detection potential of 0.65 V. Glycerol, sucrose, lactose, glucose, and fructose in sweat samples were positively identified and accurately
measured.

Conclusion:
The method was successfully applied in the simultaneous determination of glycerol and
carbohydrates in sweat samples with satisfactory assay results. It will find a wide range of applications in clinical diagnosis, health monitoring, and drug and food analysis.
Effect of PCBs on Production Characteristics and Fucoxanthin / Fatty Acid Content of Cylindrotheca closterium (Ehrenberg) Reimann et Lewin
Diatom Enrichment Culture
Authors: Ludmila Malakhova , Ruslan Gevorgiz , Zheleznova Svetlana 
Published: July 2024

Background:
Since the mid-20th century, polychlorinated biphenyls (PCBs) have
emerged as one of the foremost anthropogenic organic pollutants in aquatic environments. Microphytobenthic
algae of the genus Cylindrotheca have been recurrently employed in laboratory experiments
to assess sediment toxicity. Recently, a novel strain of benthic diatoms belonging to the genus
Cylindrotheca has been identified and characterized from PCB-contaminated sediments in the
coastal region of Sevastopol Bay (Black Sea). This species of algae has high biomass productivity,
the ability to synthesize fucoxanthin, and a variety of fatty acids. Cylindrotheca closterium is capable
of metabolizing organic pollutants in bottom sediments.

Objective:
The objective of the study was to investigate the effects of PCBs on the growth patterns
and physiological responses of C. closterium through a 9-day experiment, subjecting the microalgae
to varying concentrations of PCBs ranging from 0.0003 to 100 mg/L.

Results:
The experiments revealed that C. closterium could grow in environments containing concentrations
of PCBs ranging from 0.0003 to 10 mg/L, indicating its resilience to moderate levels of
PCB exposure. Additionally, adaptive biochemical processes were observed in C. closterium under
PCB exposure. Notably, on the sixth day of the experiment, the culture transitioned into a stationary
growth phase, accompanied by significant increases in total lipid content by 1.6 times and fucoxanthin
by 4.6 times compared to the control. However, a pronounced decrease in culture growth was
observed at a PCB concentration of 100 mg/L, coinciding with reductions in total lipid and fucoxanthin
content, suggesting a tolerance threshold of C. closterium between 10 and 100 mg/L PCB concentrations.
Furthermore, alterations in the fatty acid profile of C. closterium were noted, characterized
by a decrease in polyene content and an increase in monoene fatty acids, under PCB exposure.

Conclusion:
The study underscores the resilience of C. closterium to moderate PCB concentrations
and highlights the complex physiological responses and adaptive mechanisms initiated in response to
PCB exposure. The findings contribute to understanding the toxic effects of PCBs on C. closterium
and provide insights into potential mechanisms underlying these effects.
Progresses and Developments in Chitosan-based Materials and its Derivatives for Biomedical and Biosensing Applications
Authors: Vosoughi Pegah , Naghib Seyed Morteza , Mozafari M. R. 
Published: July 2024

Abstract:
This extensive review highlights the different techniques used to extract chitosan, its antibacterial
characteristics, and its wide range of applications across various industries. Thanks to its
exceptional solubility and notable chemical and biological properties, it has been used in several
applications. It is biodegradable, and biocompatible, and has numerous reactive amino side groups
that enable chemical modification and the development of various practical derivatives. Several academic
publications have extensively covered many characteristics of chitosan and its applications in
different industries, such as medicine. Chitosan can impart different functions in multiple fields, such
as antibacterial, antiviral, and other biological features. Chitosan has various applications across
various industries. Due to its exceptional solubility and significant chemical and biological properties,
it has been utilized in numerous applications. Chitosan is biodegradable and biocompatible, and
its multiple reactive amino side groups enable chemical modification and the development of various
practical derivatives. Chitosan can provide different functions in numerous fields, such as antibacterial,
antiviral, and other biological features. This review primarily focuses on chitosan's sources and
extraction methods, providing an up-to-date overview of its properties. Additionally, the review
highlights the diverse applications of chitosan, whether in its original state or modified and incorporated
into nanocomposites, in various fields, making it a highly versatile and commonly used material
in the biomedical industry.
Examining the Synergic Effect of Exosomes Derived from Mouse Mesenchymal Stem Cells and Low-frequency Electromagnetic Field on Chondrogenic Differentiation
Authors: Lotfi Maryam , Baharara Javad , Nejad Shahrokhabadi Khadije , Khorshid Pejman 
Published: July 2024

Background:
Cartilage has intrinsically limited healing power, and regeneration of cartilage
damages has remained a challenge. Secreted products of mesenchymal stem cells have
shown a new therapeutic strategies for cartilage injuries. Also it has been observed that low frequency
electromagnetic field plays a key role in biological processes.

Objective:
This research was performed to investigate the synergic effect of mesenchymal stem
cell-derived exosomes and low frequency electromagnetic field on chondrogenic differentiation.

Methods:
In this in vitro study, mesenchymal stem cell-derived exosomes were identified using
AFM, SEM, TEM microscopy, and DLS method. Cells were treated in chondrogenic medium by
exosomes, low frequency electromagnetic field, and the synergy of both. The cell survival was examined
using MTT and Annexin methods, and cartilage differentiation was confirmed by Alcian
blue staining. The expression of Sox-9, Acan, Col 2a1 and Col 10a1 genes was examined via Real-
Time PCR technique on day 14 post-treatment.

Results:
The results confirmed the presence of exosomes with an approximate size of less than
100 nm. The results of Alcian blue revealed greater expression of glycosaminoglycans in the synergic
treatment group compared to the other groups. Real-time PCR showed a significant increase
in the expression of Sox-9, Acan, and Col 2a1 genes, as well as a significant reduction of Col
10a1 gene expression in the synergic treatment group compared to other groups.

Conclusion:
This study indicated that the synergic effect of exosome and low-frequency electromagnetic
fields would lead to enhanced chondrogenic differentiation, which can be further explored
in future clinical studies
MFTP-Tool: A Wide & Deep Learning Framework for Multi-Functional Therapeutic Peptides Prediction
Authors: Lv Yang , Liu Ting , Ma Yuchen , Lyu Hongqiang , Liu Ze 
Published: July 2024

Background:
The identification and functional prediction of Multifunctional Therapeutic
Peptides (MFTP) play a pivotal role in drug discovery, particularly for conditions such as inflammation
and hyperglycemia. Current computational methods exhibit limitations in their ability to accurately
predict the multifunctionality of these peptides.

Methods:
We propose a novel Wide and Deep Learning Framework that integrates both deep learning
and machine learning approaches. The deep learning segment processes word vectors using a
neural network model, while the wide segment utilizes the physicochemical properties of peptides in
a random forest-based model. This hybrid approach aims to enhance the accuracy of MFTP function
prediction.

Results:
Our framework outperformed the existing PrMFTP predictor in terms of precision, coverage,
accuracy, and absolute true values. The evaluation was conducted on both training and independent
testing datasets, demonstrating the robustness and generalizability of our model.

Conclusion:
The proposed Wide & Deep Learning Framework offers a significant advancement in
the computational prediction of MFTP functions. The availability of our model through a userfriendly
web interface at MFTP-Tool.m6aminer.cn provides a valuable tool for researchers in the
field of therapeutic peptide-based drug discovery, potentially accelerating the development of new
treatments.
The Role of the GH Receptor Polymorphisms as a Prognostic Factor of
Vertebral Fractures in Acromegalic Patients Resistant to First-generation
SSAs and Treated with Pegvisomant or Pasireotide LAR
Authors: Costanza Flavia , Chiloiro Sabrina , Giampietro Antonella , Angelini Flavia , Infante Amato , Pontecorvi Alfredo , De Marinis Laura , Bianchi Antonio 
Published: July 2024

Background:
Acromegaly is associated with skeletal fragility and increased prevalence
of vertebral fractures (VF). Two isoforms of GH receptor (GHR) have been described,
which differ in the presence or absence of a transcript of exon 3 of the GHR gene. Both
isoforms produce a functional receptor, but the exon 3-deleted isoforms (d3-GHR) have greater
sensitivity to endogenous and recombinant GH than the full-length isoform (fl-GHR).

Objective:
We conducted a longitudinal, retrospective, observational, single-center study to investigate
the role of GHR polymorphism as a prognostic factor of incidental VF (I-VF) in firstgeneration
somatostatin analogs (fg-SSAs)-resistant acromegalic patients and treated with
Pegvisomant or Pasireotide LAR.

Methods:
Seventy-two patients with active acromegaly were included: 28 patients carried the
d3-GHR isoform, and 44 patients carried the fl-GHR isoform. Forty-six patients were treated
with Pegvisomant in combination with fg-SSAs, and 26 were treated with Pasireotide LAR. At
the last follow-up, 58 patients achieved biochemical control of acromegaly. Eighteen patients
carried prevalent VF (P-VFs), while 14 patients experienced the occurrence of I-VFs.

Results:
From the group treated with Pegvisomant in combination with fg-SSAs, 32 patients
carried the fl-GHR isoform, and 14 carried the d3-GHR isoform. From the group treated with
Pasireotide LAR, 12 patients had the fl-GHR isoform, and 14 patients carried the d3-GHR isoform.
I-VF occurred more frequently in patients with the fl-GHR isoform compared to d3-GHR
(p =0.04); otherwise, I-VF occurred more frequently in patients with the d3-GHR isoform than
fl-GHR (p =0.01).

Conclusion:
The GHR polymorphisms could improve the therapeutic approach in acromegaly,
tailored to the individual patient, in the context of personalized medicine.
Enhancing Classification of Alzheimer’s Disease using Spatial Attention Mechanism
Authors: Krishnan Deepa , Bishnoi Akshat , Bansal Shaivi , Ravi Vinayakumar , Ravi Pradeep 
Published: July 2024

Aim
This study aims to enhance the precision of Alzheimer's disease (AD) detection by integrating Spatial Attention Mechanism into a Convolutional Neural Network (CNN) architecture.

Background
Alzheimer's disease is a progressive neurodegenerative disorder characterized by abnormal protein deposits in the brain, leading to nerve cell loss and posing a significant global health challenge. Early and accurate detection is crucial for disease management and treatment due to the lack of a cure and the disease's severe progression.

Objective
The objective of this research is to improve the accuracy of Alzheimer's disease classification using MRI data by implementing a Spatial Attention Mechanism in a CNN architecture.

Methods
The study utilized T1-weighted MRI data from the OASIS 1 and OASIS 2 datasets. The key innovation is the Spatial Attention layer incorporated within a CNN model, which computes the average of each channel in the input feature map. This layer guides subsequent layers to focus on critical brain regions, enhancing the model's accuracy in differentiating between Alzheimer's disease stages.

Results
The model achieved a validation accuracy of 99.69% with a sensitivity and specificity of 1.0000, demonstrating its reliability in distinguishing between different stages of Alzheimer's disease. The adaptability of the Spatial Attention layer allows the model to assign higher weights to crucial brain regions, improving its discriminative power.

Conclusion
The integration of the Spatial Attention Mechanism into the CNN architecture significantly contributes to the early detection of Alzheimer's disease, enabling timely interventions. This innovative approach has the potential to revolutionize Alzheimer's diagnosis by enhancing accuracy and offering a robust solution for classification.
Dynamic Flow Algorithm with Intermediate Storage for Emergency Evacuation Allowing Lane Reversal based on Incomplete Intuitionistic Fuzzy Preference Relation
Authors: Gerasimenko Evgeniya 
Published: July 2024

Background
Evacuation in case of disasters is of the greatest importance because of significant occurrences of natural and artificial disasters worldwide, which is why a reliable evacuation plan is always needed. However, evacuation models are difficult to develop due to various uncertain aspects that need to be considered, multiple and often conflicting criteria for evaluation and as lack of expertise regarding a specific preference of alternatives.

Objective

This study aims to transport the maximum number of evacuees in a dynamic network with lane reversal by a safe pattern of transportation, i.e., allowing storage at intermediate nodes. The optimal order of shelters and intermediate nodes for a reliable evacuation plan will be defined by incomplete intuitionistic fuzzy preference relation.

Methods
The illustrated method incorporates multiple and often conflicting criteria into a process of emergency decision-making. When evaluating evacuation alternatives, a decision-maker may hesitate and be unsure which alternative is better or not have sufficient expertise to evaluate a pair of alternatives. To model uncertainty and hesitation, intuitionistic fuzzy values are used to describe alternatives in more detail. This study relies on flow models and graph theory to simulate the movement of evacuees to safe destinations. Furthermore, fuzzy methods and their recent modifications are applied to determine the effective priority order of shelters. A case study which simulates the evacuation of aggrieved to safe destinations is presented.

Results
A method of evaluating the shelters and intermediate nodes for evacuation based on incomplete intuitionistic fuzzy preference relation is proposed. The method allows the missed values of experts’ assessments to be filled in regarding the evacuation alternatives and deals with intuitionistic fuzzy values, which describe experts’ hesitation. The dynamic character of flow distribution enables transit arc capacities and time factors to be processed. The contraflow technique, which is a powerful tool to decrease traffic jams and congestion on roads by reversing the movement along the unused segments, is applied to maximize the number of survivors.

Conclusion
The results of the method were compared to those of existing methods, and their consistency was proved. In the future, we intend to apply interval-valued intuitionistic preference relations and iterative algorithms to improve the consistency of intuitionistic preference relations to the tasks of transporting the maximum possible number of aggrieved to safe locations.
A Review on Environment-friendly Protocol for the Synthesis of Pyrazole Derivative
Authors: Kumar Nitesh , Rajput Sejal , Patel Ridham , Yadav Ashesha , Raj Lakshmi Shanta 
Published: July 2024

:
Pyrazole derivatives are a significant group of heterocyclic compounds that have a diverse
variety of biological activities and are used in several fields, such as medicines, agrochemicals, and
materials research. Conventional methods for synthesizing pyrazole derivatives typically require
severe reaction conditions, hazardous reagents, and environmentally harmful solvents, presenting
considerable obstacles to achieving sustainable chemistry. This analysis specifically examines the
latest progress made in creating environmentally friendly procedures for producing pyrazole derivatives.
The study investigates different strategies in green chemistry, such as reactions without solvents,
techniques including microwave and ultrasonic assistance, and using renewable resources and
environmentally friendly catalysts. An in-depth analysis is conducted to evaluate the efficiency, selectivity,
and environmental impact of these approaches. This review intends to comprehensively
explore the potential for sustainable practices in synthesizing pyrazole derivatives by emphasizing
advancements in green synthetic methods. It seeks to encourage further research and use of green
chemistry concepts in heterocyclic chemistry.
Nanomedicine in Alzheimer’s Therapy: Enhancing Drug Delivery
Strategies
Authors: Singh Archna , Mazumder Avijit , Das Saumya , Mishra Rashmi , Chaitanya MVNL 
Published: July 2024

Abstract:
Alzheimer's disease (AD), a progressive neurodegenerative disorder, arises from the
buildup of beta-amyloid plaques within the intricate neural networks of the brain. A lasting remedy
for Alzheimer's disease remains elusive, as current pharmaceutical options merely offer the potential
to decelerate its advancement. Nevertheless, nanotechnology has demonstrated its efficacy
in the realm of medical interventions. Nanotechnology holds immense promise for the treatment
of Alzheimer's disease, particularly in the realms of disease detection and providing alternative
therapeutic approaches. With its demonstrated superiority in medical applications, nanotechnology
emerges as a potent tool with significant potential in addressing the complexities of
Alzheimer's disease, offering enhanced diagnostics and novel treatment strategies. This feat is
achieved by augmenting the efficacy of drug administration through the penetration and surmounting
of the BBB.
Nonetheless, it is crucial to thoroughly investigate and explore the limitations at hand, aiming to
minimize undesired side effects and potential toxicity while enhancing medication absorption,
thereby optimizing the overall therapeutic outcome. Cutting-edge breakthroughs in Alzheimer's
disease treatment utilizing nanotechnology encompass a spectrum of remarkable advancements, including
stem cell regeneration, nanomedicine, and neuroprotection. The present investigation
delves into the remarkable strides made in nanotechnology, specifically examining its pivotal role
in detecting and treating neurodegenerative disorders such as Alzheimer's while shedding light on
the challenges ahead.
Comparison of Characteristics and Clinical Symptoms of Inpatients and
Outpatients with COVID-19
Authors: Nargesi Khoramabad Narges , Mohammadi Rasool , Sedighifar Zahra , Siavashi Ali Safdar 
Published: July 2024

Background:
Nowadays, one of the best ways to manage COVID-19 is to understand the
characteristics of patients and the risk factors associated with the disease.

Objective:
This study aimed to investigate and compare the characteristics, symptoms, and prognosis
of inpatients and outpatients with COVID-19 in Poledokhtar city

Methods:
In this descriptive-analytical study, 288 patients who tested positive for COVID-19
through PCR tests at COVID-19 screening centers and Imam Khomeini Hospital in Poledakhtar city
were selected using the census method. They were divided into inpatient and outpatient groups. Data
from patient files were collected and analyzed using SPSS version 25 software.

Results:
The study revealed significant differences in age, comorbidities, prior infection, and aspirin
use between the inpatient and outpatient groups. Cough was the most common symptom among all
patients, with weakness and fatigue being more common in inpatients and cough being more prevalent
in outpatients. The overall mortality rate was 5.2%, with inpatients having a worse prognosis
compared to outpatients.

Conclusion:
In the present study, inpatients were found to be older, have more underlying health
conditions, fewer prior infections, and experience a poorer prognosis than outpatients. Given that
patients may be asymptomatic or have mild symptoms upon admission, evaluating other patient factors
is crucial in assessing disease severity.
Quality Measurement of Consumer Health Questions: Content and Language Perspectives
Authors: Alasmari Ashwag , Zhou Lina 
Published: July 2024

Background
Health information consumers increasingly rely on question-and-answer (Q&A) communities to address their health concerns. However, the quality of questions posted significantly impacts the likelihood and relevance of received answers.

Objective
This study aims to improve our understanding of the quality of health questions within web-based Q&A communities.

Methods
We develop a novel framework for defining and measuring question quality within web-based health communities, incorporating content- and language-based variables. This framework leverages k-means clustering and establishes automated metrics to assess overall question quality. To validate our framework, we analyze questions related to kidney disease from expert-curated and community-based Q&A platforms. Expert evaluations confirm the validity of our quality construct, while regression analysis helps identify key variables.

Results
High-quality questions were more likely to include demographic and medical information than lower-quality questions (P<.001). In contrast, asking questions at the various stages of disease development was less likely to reflect high-quality questions (P<.001). Low-quality questions were generally shorter with lengthier sentences than high-quality questions (P<.01).

Conclusions
Our findings empower consumers to formulate more effective health information questions, ultimately leading to better engagement and more valuable insights within web-based Q&A communities. Furthermore, our findings provide valuable insights for platform developers and moderators seeking to enhance the quality of user interactions and foster a more trustworthy and informative environment for health information exchange.