bluuebunny/crossref_metadata_2025 huggingface dataset:
L-lysine Increases the Anticancer Effect of Doxorubicin in Breast Cancer by Inducing ROS-dependent Autophagy
Authors: Jahani Mozhgan , Yarani Reza , Rezazadeh Davood , Tahmasebi Hadis , Hoseinkhani Zohreh , Kiani Sara , Mansouri Kamran
Published: April 2024

Background:

Doxorubicin (DOX) is a chemotherapy drug that is widely used in cancer
therapy, especially in Triple-Negative Breast Cancer (TNBC) patients. Nevertheless, cytoprotective
autophagy induction by DOX limits its cytotoxic effect and drug resistance induction in patients.
Therefore, finding a new way is essential for increasing the effectiveness of this drug for
cancer treatment.

Objective:

This study aimed to investigate the effect of L-lysine on DOX cytotoxicity, probably
through autophagy modulation in TNBC cell lines.

Methods:

We used two TNBC cell lines, MDA-MB-231 and MDA-MB-468, with various levels
of autophagy activity. Cell viability after treatment with L-lysine alone and in combination therapy
was evaluated by MTT assay. Reactive Oxygen Species (ROS), nitric oxide (NO) concentration,
and arginase activity were assessed using flow cytometric analysis, Griess reaction, and arginase
activity assay kit, respectively. Real-time PCR and western blot analysis were used to evaluate
the L-lysine effect on the autophagy-related genes and protein expression. Cell cycle profile
and apoptotic assay were performed using flow cytometric analysis.

Results:

The obtained data indicated that L-lysine in both concentrations of 24 and 32 mM increased
the autophagy flux and enhanced the DOX cytotoxicity, especially in MDA-MB-231,
which demonstrated higher autophagy activity than MDA-MB-468, by inducing ROS and NO production.
Furthermore, L-lysine induced G2/M arrest autophagy cell death, while significant apoptotic
changes were not observed.

Conclusion:

These findings suggest that L-lysine can increase DOX cytotoxicity through autophagy
modulation. Thus, L-lysine, in combination with DOX, may facilitate the development of novel
adjunct therapy for cancer.
Noncoding RNAs in Alzheimer’s Disease: Overview of Functional and
Therapeutic Significance
Authors: Adiga Divya , Eswaran Sangavi , Srinath Sriharikrishnaa , Khan Nadeem G. , Kumar Dileep , Kabekkodu Shama P.
Published: April 2024

:

Alzheimer’s disease (AD) is a multifactorial disorder resulting from the complex interaction
between genetic, epigenetic, and environmental factors. It represents an impending epidemic
and lacks effective pharmacological interventions. The emergence of high throughput sequencing
techniques and comprehensive genome evaluation has uncovered a diverse spectrum of noncoding
RNA (ncRNA) families. ncRNAs are the critical modulators of an eclectic array of biological
processes and are now transpiring as imperative players in diagnosing and treating various diseases,
including neurodegenerative disorders. Several ncRNAs are explicitly augmented in the
brain, wherein they potentially regulate cognitive abilities and other functions of the central nervous
system. Growing evidence suggests the substantial role of ncRNAs as modulators of tau
phosphorylation, Aβ production, neuroinflammation, and neuronal survival. It indicates their therapeutic
relevance as a biomarker and druggable targets against AD. The current review summarizes
the existing literature on the functional significance of ncRNAs in AD pathogenesis and its imminent
implications in clinics.
Insight into the Novel Synthesis Approaches and Biological Activity of 1,3,4 Oxadiazole: A Review
Authors: Jain Ayush , Majee Chandana , Mazumder Rupa , Padhi Swrupanjali , Mazumder Avijit , Das Saumya , Kumar Arvind , Chaitanya Mvnl
Published: April 2024

Oxadiazole is an organic compound featuring a heterocyclic ring housing carbon, oxygen,
and nitrogen atoms. Due to their heightened stability in biological environments, oxadiazole rings
exhibit significant biological activities, effectively addressing health challenges like infectious diseases
and chronic conditions in medicinal chemistry. The main objective of this review is to discuss
various synthetic approaches related to 1,3,4-oxadiazole and its derivatives. The diverse reactivity
positions oxadiazole as a valuable building block in organic synthesis, with derivatives exhibiting
promising pharmacological activities. It involves a systematic literature review, critical analysis, and
synthesis of existing research. This review comprises the ever-expanding chemical knowledge and
has significant implications for drug development. Synthetic approaches to synthesizing oxadiazole
through different schemes and methods have been discussed thoroughly. This review also concisely
associated the pharmacological activities of oxadiazole and its derivatives. This review highlights the
importance of continued research into the structure-activity relationships of oxadiazole derivatives,
paving the way for developing novel and more potent therapeutic agents.
COVID-19 Beyond the Lungs: Neuropsychiatric Symptoms and EEG Correlations
Authors: Attardi Anna Gaia , Ceraolo Graziana , Galletta Federica , Maimone Maria Grazia , Amore Greta
Published: April 2024

:

COVID-19, previously considered a mere respiratory illness affecting predominantly
the adult age, is today acknowledged as the cause of a wide spectrum of multisystemic signs and
symptoms, ranging from mild to severe degrees, including neurological manifestations. Even if
less frequently than adults, pediatric patients may also develop severe COVID-19 and present
with peculiar clinical pictures, including multi-system inflammatory syndrome (MIS-C) and neuropsychiatric
manifestations. Mounting evidence is available on the potential pathogenic mechanisms
underpinning the nervous system involvement and on the Post-COVID19 sequelae. However,
little is known about EEG changes that may come along with them, particularly in the pediatric
age. Herein, we briefly overview the neuropsychiatric COVID-19-related features in pediatric
patients and the reported potential EEG correlates. Further research may help unravel new insights
and provide new biomarkers regarding diagnosis, prognosis, and treatment options for post--
COVID-19 neuro-cognitive disorders.
Gait Analysis of Knee Joint Walking Based on Image Processing
Authors: Wang Shuai , Zhou Jihe
Published: April 2024

Background::

With the in-depth development of assistive treatment devices, the application of artificial knee joints in the rehabilitation of amputees is becoming
increasingly mature. The length of residual limbs and muscle strength of patients have individual differences, and the current artificial knee joint
lacks certain adaptability in the personalized rehabilitation of patients.

Purpose::

In order to deeply analyze the impact of different types of artificial knee joints on the walking function of unilateral thigh amputees, improve the
performance of artificial knee joints, and enhance the rehabilitation effect of patients, this article combines image processing technology to conduct
in-depth research on the walking gait analysis of different artificial knee joints of unilateral thigh amputees.

Methods::

This article divides patients into two groups: the experimental group consists of patients with single leg amputation, and the control group consists
of patients with different prostheses. An image processing system is constructed using universal video and computer hardware, and relevant
technologies are used to recognize and track landmarks; Furthermore, image processing technology was used to analyze the gait of different groups
of patients. Finally, by analyzing the different psychological reactions of amputees, corresponding treatment plans were developed.

Results::

Different prostheses worn by amputees have brought varying degrees of convenience to life to a certain extent. The walking stability of wearing
hydraulic single axis prosthetic joints is only 79%, and the gait elegance is relatively low. The walking stability of wearing intelligent artificial
joints is as high as 96%. Elegant gait is basically in good condition.

Conclusion::

Image processing technology helps doctors and rehabilitation practitioners better understand the gait characteristics and rehabilitation progress of
patients wearing different artificial knee joints, providing objective basis for personalized rehabilitation of patients
Improving Breast Cancer Detection with Convolutional Neural Networks and
Modified ResNet Architecture
Authors: Nouri Pour Javad , Pourmina Mohammad Ali , Moghaddasi Mohammad Naser
Published: April 2024

Background::

The pathogenesis of breast cancer is characterized by dysregulated cell proliferation, leading to the formation of a neoplastic mass. Conventional
methodologies for analyzing carcinomatous distal areas within whole-slide images (WSIs) tissue regions may lack comprehensive insights.

Purpose::

This study aims to introduce an innovative methodology based on convolutional neural networks (CNN), specifically employing a CNN Modified
ResNet architecture for breast cancer detection. The research seeks to address the limitations of existing approaches and provide a robust solution
for the comprehensive analysis of tissue regions.

Methods::

The dataset utilized in this study comprises approximately 275,000 RGB image patches, each standardized at 50x50 pixels. The CNN Modified
ResNet architecture is implemented, and a comparative evaluation against diverse architectures is conducted. Rigorous validation tests employing
established performance metrics are carried out to assess the proposed methodology.

Results::

The proposed architecture achieves a notable 89% accuracy in breast cancer detection, surpassing alternative methods by 2%. The results signify
the efficacy and superiority of the CNN Modified ResNet model in analyzing carcinomatous distal areas within WSIs tissue regions.

Conclusion::

In conclusion, this study demonstrates the potential of the CNN Modified ResNet architecture as an effective tool for breast cancer detection. The
enhanced accuracy and comprehensive analysis capabilities make it a promising approach for advancing the understanding of neoplastic masses in
WSIs tissue regions. Further research and validation could solidify its role in clinical applications and diagnostic procedures.
Antimicrobial Potential of Polyphenols: An Update on Alternative for
Combating Antimicrobial Resistance
Authors: Sharma Alok , Anurag  , Kaur Jasleen , Kesharwani Anuradha , Parihar Vipan Kumar
Published: April 2024

The last decade has encountered an increasing demand for plant-based natural antibiotics.
This demand has led to more research-based investigations for natural sources of antimicrobial
agents and published reports demonstrating that plant extracts are widely applied in modern medicine,
reporting potential activity that may be due to polyphenol compounds. Interestingly, the effects
of polyphenols on the sensitivity of bacteria to antibiotics have not been well-studied. Hence,
the current review encompasses the prospective application of plant-based phenolic extracts from
plants of Indian origin. The emergence of resistance to antimicrobial agents has increased the inefficacy
of many antimicrobial drugs. Several strategies have been developed in recent times to overcome
this issue. A combination of antimicrobial agents is employed for the failing antibiotics,
which restores the desirable effect but may have toxicity-related issues. Phytochemicals such as
some polyphenols have demonstrated their potent activity as antimicrobial agents of natural origin
to work against resistance issues. These agents alone or in combination with certain antibiotics have
been shown to enhance the antimicrobial activity against a spectrum of microbes. However, the
information regarding the mechanisms and structure-activity relationships remains elusive. The
present review also focuses on the possible mechanisms of natural compounds based on their structure-
activity relationships for incorporating polyphenolic compounds in the drug-development processes.
Besides this work, polyphenols could reduce drug dosage and may diminish the unhidden or
hidden side effects of antibiotics. Pre-clinical findings have provided strong evidence that polyphenolic
compounds, individually and in combination with already approved antibiotics, work well
against the development of resistance. However, more studies must focus on in vivo results, and
clinical research needs to specify the importance of polyphenol-based antibacterials in clinical trials.
UV-Visible Spectroscopy: A Review on its Pharmaceutical and Bio-allied
Sciences Applications
Authors: Singhal Abhinav , Saini Urvashi , Chopra Bhawna , Dhingra Ashwani K. , Jain Akash , Chaudhary Jasmine
Published: April 2024

Ultraviolet-Visible (UV-Vis) spectroscopy has emerged as a powerful analytical tool
with diverse applications in pharmaceutical and bio-allied sciences. This article provides a comprehensive
overview of the extensive utility of UV-Vis spectroscopy, emphasizing its pivotal role in
characterizing and analyzing various compounds critical for drug development and bio-allied research.
In the pharmaceutical sector, UV-Vis spectroscopy is a fundamental technique for quantifying
the concentrations of active pharmaceutical ingredients (APIs) in formulations. Its non-destructive
nature and high sensitivity make it an indispensable tool for quality control, ensuring the
consistency and potency of pharmaceutical products. Furthermore, this technique has been employed
in the study of drug-receptor interactions to elucidate the molecular mechanisms underlying
therapeutic effects. In bio-allied applications, UV-Vis spectroscopy is used to analyze biomolecules
like proteins, nucleic acids, and enzymes. This technique allows for the study of protein
conformational changes, DNA structure, and enzymatic activity, offering crucial insights into fundamental
biological processes. Additionally, UV-Vis spectroscopy aids in determining biomarker
concentrations, assisting in the early diagnosis and monitoring of various diseases. This article also
explores recent advancements in UV-Vis spectroscopy, including the integration of nanomaterials
and computational approaches to enhance sensitivity and selectivity. Moreover, it discusses
the potential of UV-Vis spectroscopy in emerging areas such as personalized medicine and point-
of-care diagnostics. As technology continues to evolve, UV-Visible spectroscopy is poised to significantly
contribute to the ever-expanding landscape of pharmaceutical and bio-related research.
An Effective Method to Identify Cooperation Driver Gene Sets
Authors: Zhang Wei , Zeng Yifu , Zhao Bihai , Xiong Jie , Zhu Tuanfei , Wang Jingjing , Li Guiji , Wang Lei
Published: April 2024

Background:

In cancer genomics research, identifying driver genes is a challenging
task. Detecting cancer-driver genes can further our understanding of cancer risk factors and promote
the development of personalized treatments. Gene mutations show mutual exclusivity and cooccur,
and most of the existing methods focus on identifying driver pathways or driver gene sets
through the study of mutual exclusivity, that is functionally redundant gene sets. Moreover, less research
on cooperation genes with co-occurring mutations has been conducted.

Objective:

We propose an effective method that combines the two characteristics of genes, cooccurring
mutations and the coordinated regulation of proliferation genes, to explore cooperation
driver genes.

Methods:

This study is divided into three stages: (1) constructing a binary gene mutation matrix;
(2) combining mutation co-occurrence characteristics to identify the candidate cooperation gene
sets; and (3) constructing a gene regulation network to screen the cooperation gene sets that perform
synergistically regulating proliferation.

Results:

The method performance is evaluated on three TCGA cancer datasets, and the experiments
showed that it can detect effective cooperation driver gene sets. In further investigations, it
was determined that the discovered set of co-driver genes could be used to generate prognostic
classifications, which could be biologically significant and provide complementary information to
the cancer genome.

Conclusion:

Our approach is effective in identifying sets of cancer cooperation driver genes, and
the results can be used as clinical markers to stratify patients.
Gastrodin Attenuates Colitis and Prevents Tumorigenesis in Mice by Interrupting
TLR4/MD2/NF-κB Signaling Transduction
Authors: Yu Zhilun , Yue Bei , Gao Ruiyang , Zhang Beibei , Geng Xiaolong , Lv Cheng , Wang Hao , Wang Ziyi , Wang Zhengtao , Dou Wei
Published: April 2024

Introduction::

Chronic inflammation is one of the causative factors for tumorigenesis. Gastrodin is a
main active ingredient isolated from Gastrodia elata Blume, a famous medicinal herb with a long edible history.

Aim::

This study aimed to explore the effects of gastrodin on colitis-associated carcinogenesis (CRC) in mice and
to elucidate its potential molecular mechanisms.

Methods::

Balb/c mice were induced with azoxymethane (AOM) and dextran sulfate sodium (DSS) for 12 weeks.
Gastrodin (50 mg/kg) was administered via oral gavage three times per week until the end of the experiment.
Disease indexes, including body weight, bloody diarrhea, colon length, histopathological score, and tumor size,
were measured. Tumor cell proliferation was evaluated by BrdU incorporation assay and tumor cell cytotoxicity
was assessed by cell counting kit (CCK-8). The expression levels of toll-like receptor 4 (TLR4)/nuclear factor
kappa-B (NF-κB) signaling molecules, NF-κB luciferase, and pro-inflammatory cytokines were determined by
real-time fluorescence quantitative polymerase chain reaction (RT-qPCR), immunoblotting, immunohistochemistry
(IHC), enzyme-linked immunosorbent assay (ELISA), or reporter gene assays. The binding affinity between
gastrodin and myeloid differentiation protein-2 (MD2) was analyzed by molecular docking and cellular thermal
shift assay (CETSA).

Results::

Gastrodin administration was demonstrated to mitigate various CRC-related symptoms in mice, including
weight loss, diarrhea, and tissue abnormalities. Notably, gastrodin suppressed tumor cell growth during colitis-
associated tumorigenesis, resulting in fewer and smaller adenomas in the colon. Unlike irinotecan, a broadspectrum
antitumor drug, gastrodin did not exhibit apparent cytotoxicity in various colorectal adenocarcinoma
cell lines. Additionally, gastrodin downregulated TLR4/NF-κB signaling molecules and pro-inflammatory mediators
in mice and macrophages. Molecular docking and CETSA experiments suggested that gastrodin binds to the
MD2 protein, potentially interfering with the recognition of lipopolysaccharide (LPS) by TLR4, leading to NF-κB
pathway inhibition.

Conclusion::

This study provides evidence for the first time that gastrodin attenuated colitis and prevented colitisrelated
carcinogenesis in mice, at least partially, by diminishing tumor-promoting cytokines through the interruption
of TLR4/MD2/NF-κB signaling transduction.
Effects of Dietary Restriction on PGC-1α Regulation in the Development
of Age-associated Diseases
Authors: Widjaja Shefilyn , Antarianto Radiana Dhewayani , Hardiany Novi Silvia
Published: April 2024

:

Ageing is the most significant risk factor for a number of non-communicable diseases,
manifesting as cognitive, metabolic, and cardiovascular diseases. Although multifactorial, mitochondrial
dysfunction and oxidative stress have been proposed to be the driving forces of ageing.
Peroxisome proliferator-activated receptor γ coactivator α (PGC-1α) is a transcriptional coactivator
central to various metabolic functions, of which mitochondrial biogenesis is the most prominent
function. Inducible by various stimuli, including nutrient limitations, PGC-1α is a molecule
of interest in the maintenance of mitochondrial function and, therefore, the prevention of degenerative
diseases. This review involves a literature search for articles retrieved from PubMed using
PGC-1α, ageing, and dietary restriction as keywords. Dietary restriction has been shown to promote
tissue-specific PGC-1α expression. Both dietary restriction and PGC-1α upregulation have
been shown to prolong the lifespans of both lower and higher-level organisms; the incidence of
non-communicable diseases also decreased in fasting mammals. In conclusion, dietary interventions
may delay ageing by regulating healthy mitochondria in various organs, presenting the possibility
of a new primary prevention for many age-related diseases.
Green Synthesis of Au-Ni Bimetallic Nanoparticles using Aqueous Extract of Coccinia grandis (L.) Voigt and their Catalytic Activity in Oxidation of Alcohols
Authors: Hazarika Munmi , Das Pankaj , Puzari Amlan
Published: April 2024

Background:

In recent years, bimetallic nanoparticles have gained remarkable attention due to their excellent physical and chemical properties. Especially, bimetallic nanoparticles are found to be highly efficient as catalysts in many important organic transformations.

Objective:

The objective of the present work involves green synthesis of Au-Ni bimetallic nano-particles using plant extract as the bio-reductant and to evaluate their catalytic efficiency in oxidation of alcohols.

Methods:

The experiment involves a simple and eco-friendly protocol for synthesis of Au-Ni bi-metallic as well as their corresponding monometallic nanoparticles that involves the use of aqueous fruit seed extract of Coccinia grandis(L.) Voigt as the bio-reductant and tannic acid as the bio-stabilizer. The synthesized nanoparticles were characterized by using XRD, TEM, FTIR, TGA etc., and their catalytic activity was evaluated for oxidation of alcohols.

Results:

The synthesized bimetallic nanoparticles have shown excellent catalytic activity towards aqueous phase oxidation of alcohols to aldehydes under ambient reaction conditions. Further-more, the results have revealed better effective performance of the bimetallic nanoparticles over the corresponding monometallic nanoparticles of gold and nickel, establishing the synergic influence of the two metals. Another attractive feature of this work is that the Au-Ni bimetallic nano-particles could be recycled and reused up to four catalytic cycles without any significant decline in product yield.

Conclusion:

The green synthesized bimetallic Au-Ni nanoparticles have shown excellent catalyt-ic activity toward the oxidation of alcohols in aqueous media under ambient reaction conditions. In addition, the nanoparticles are found to be successfully recyclable upto four catalytic cycles.
Optimal Design and Simulation Analysis of Phase Change Material Composite Self-Insulating Block in a Typical Cold Region City of China in Summer
Authors: Dong Xue
Published: April 2024

Background::

Incorporating PCMs (Phase Change Materials) into the building envelope
can achieve the purpose of regulating heat transfer and enhancing indoor comfort. In recent years,
lots of patents for new phase change concretes have been proposed and applied to the envelope.

Objective::

This study aimed to explore the optimum phase change temperature and installation position
of PCM by optimizing different concrete blocks to improve the thermal behavior of concrete
compound self-insulating blocks.

Methods::

Firstly, based on the existing patents, five new types of phase change self-insulating
blocks were proposed. The thermal insulation performance of different blocks was tested using
ANSYS simulation. Then, the feasibility of using EnergyPlus to simulate the thermal environment
of the room was verified by taking a summer south-facing room in Hohhot City as a research object.
Finally, 13 phase-change block types containing 4 phase-change temperatures and 3 PCM installation
locations were designed for further testing.

Results::

A three-row staggered perforated block was selected, and the heat transmission coefficient
of the masonry wall was 0.437 W/(m2·K). The optimal phase change temperatures of outdoor, medium-
temperature, high-temperature, and low-temperature periods in summer, were 24.0oC, 30.0oC,
and 28.0oC, respectively. The optimal phase change temperature in the whole summer was 26.0~
28.0oC, and the best phase transition layer location was the inner hole of the block.

Conclusion::

The PCM mounting position has a greater effect on room temperature than the PCM
phase change temperature. The study results are of great significance for stabilizing room temperature
and building energy conservation.
Solvent-Free Synthesis of Bioactive Heterocycles
Authors: Bajpai Sangeeta , Kamboj Monika , Singh Surabhi , Yadav Monika , Banik Bimal Krishna
Published: April 2024

:

The main emphasis of green chemistry is to reduce environmental pollution. Its main goal is to adopt a cost-effective and harmless strategy for human health and the environment. The green synthetic routes have succeeded in adopting solvent-free conditions as an effective tool for sustainability. Heterocycles are organic compounds that are widely distributed by nature. Many of them possess medicinal and pharmacological properties, as this heterocyclic moiety is found in many drugs. The solvent-free strategies for the Synthesis of bioactive heterocycles are, now-adays, regarded as an important objective. Solvent-free reactions are eco-friendly, cost-effective, and an environmentally benign route in organic transformation methods because of their effi-ciency, reduced reaction time, and high yields, thereby saving energy. This mini-review focuses on the environmentally benign solvent-free Synthesis of heterocycles and their potential pharma-cological applications.
Development and Optimization of Polymeric Nanoparticles and their
In vitro Deposition Studies Using Modified TSI
Authors: Rane Bhushan R. , Waghchaure Pranit S. , Amkar Akash J. , Jain Ashish R.
Published: April 2024

Background:

To deliver the drug through the pulmonary route, polymers like oleoylcarboxymethyl
chitosan (O-CMC), chitosan, and HPMC (hydroxypropyl methylcellulose) K4M are
well known for their effective mucoadhesive properties. Drug-loaded polymeric nanoparticles have
the potential for a therapeutic response for the targeted site is a beneficial approach.

Objective:

The present study is to develop polymeric nanoparticles (PNPs) utilizing mucoadhesive
polymers with varying concentrations as well as to develop the PNPs for pulmonary delivery.

Methods:

Polymeric nanoparticles are developed by homogenization and solvent evaporation methods
and characterized by modified twin-stage impinger to study in vitro deposition.

Results:

The characterization of pirfenidone-loaded polymeric nanoparticles (PFD-PNPs) reveals
that the mean particle size of O-CMC-PNPs is 140.8 nm ± 20, found to be less than CS-PNPs and
HPMC-PNPs. The polydispersibility index reveals that the particles of all prepared formulations are
homogenous. At the same time, the zeta potential of O-CMC-PNPs is 40.8 mV ± 5.64, and the entrapment
efficiency is 91% ± 1.2, which is better as compared to Chitosan and HPMC K4M PNPs
and makes them efficient for pulmonary delivery. Findings from the in vitro deposition study using
modified TSI show that 88.5% of the drug delivered through nebulization from both the stage of
right and left sides of the TSI suggests effective deposition in the lungs of O-CMC PNPs, and it may
move to the deeper regions because of the lowest diameter of the particles. Sustaining release of the
drug was found in the O-CMC PNPs for 8 hours, compared with 5 and 7 hours for HPMC PNPs and
Chitosan PNPs, respectively.

Conclusions:

Overall, the results of the O-CMC-PNPs highlight that the prepared nanoparticles with
O-CMC would be effective for pulmonary delivery instead of chitosan and HPMC K4M.
Rebaudioside B Attenuates Lung Ischemia-reperfusion Injury Associated Apoptosis and Inflammation
Authors: Wu Xiangyang , Qiao Tao , Huang Jian , Li Jian , Wei Shilin , Yang Jianbao , Zhang Yanchun , Li Yongnan
Published: April 2024

Objective:

At present, no proven effective treatment is available for Lung Ischemiareperfusion
Injury (LIRI). Natural compounds offer promising prospects for developing new
drugs to address various diseases. This study sought to explore the potential of Rebaudioside B
(Reb B) as a treatment compound for LIRI, both in vivo and in vitro.

Methods:

This study involved utilizing the human pulmonary alveolar cell line A549, consisting
of epithelial type II cells, subjected to Oxygen-glucose Deprivation/recovery (OGD/R) for highthroughput
in vitro cell viability screening. The aim was to identify the most promising candidate
compounds. Additionally, an in vivo rat model of lung ischemia-reperfusion was employed
to evaluate the potential protective effects of Reb B.

Results:

Through high-throughput screening, Reb B emerged as the most promising natural
compound among those tested. In the A549 OGD/R models, Reb B exhibited a capacity to enhance
cell viability by mitigating apoptosis. In the in vivo LIRI model, pre-treatment with Reb B
notably decreased apoptotic cells, perivascular edema, and neutrophil infiltration within lung
tissues. Furthermore, Reb B demonstrated its ability to attenuate lung inflammation associated
with LIRI primarily by elevating IL-10 levels while reducing levels of IL-6, IL-8, and TNF-α.

Conclusion:

The comprehensive outcomes strongly suggest Reb B's potential as a protective
agent against LIRI. This effect is attributed to its inhibition of the mitochondrial apoptotic
pathway and its ability to mitigate the inflammatory response.
Analytical Modeling of Breast Elastography
Authors: Kravchuk D. А. , Chernov N. N. , Michralieva A. I.
Published: April 2024

The purpose of the research is to develop a method for assessing the level of nonspecific protection of the body. Тhe purpose of the research. Тo develop an analytical method based on micromechanics to determine the location, size and modulus of elasticity of a tumor mass embedded in symmetrical double-dimensional breast tissue and obtain a closed solution for deformation elastograms.Methods. Changes in tissue elasticity usually correlate with pathological phenomena. Many cancers, such as scirrhous carcinoma of the breast, appear as extremely hard nodules that result from increased stromal density. Other diseases include deposits that increase or decrease tissue elasticity. Complex fluid-filled cysts may not be visible on standard ultrasound, but may be much softer than the embedded tissue. Тhe elastic moduli of tumors change during their pathological evolution. Еlastographic imaging has the potential to detect and characterize cancers by mapping tissue stiffness distribution. Тhe work developed a model of the mammary gland in the form of a two-dimensional layer of unit thickness with a round tumor, taking into account boundary conditions. Local elastic responses were obtained when an acoustic field was applied.Results. Тo evaluate the possibilities of determining the quantitative values of the elastic modules of the medium, we proposed a model of the process of deformation of heterogeneity under the conditions of ultrasonic static elastography and investigated the influence of elastic moduli and deformation of heterogeneity in the direction of applied pressure. Conclusion. Тhe developed technique made it possible to obtain an analytical solution for the field of deformations and stresses of two-dimensional models of mammary glands containing inhomogeneities. Тhe model makes it possible to use the developed methodology for constructing medical elastographic devices and conducting research in the field of elastography.
Analysis of the Effectiveness of Using Two-Stage Neural Network Models for Early Detection of Forest Fires
Authors: Kiselyov A. V. , Brusencev N. S. , Kuleshova E. A.
Published: April 2024

The purpose of the research – analysis of the effectiveness of two-stage neural network models for solving the problem of detecting forest fires in images obtained from unmanned aerial vehicles.Methods. А training dataset was synthesized for training neural network models for the purpose of detection and semantic segmentation of forest fires in images. Тwo-stage neural network models (“Faster R-CNN”, “Mask RCNN” and “Retina-Net”) were used for training. Тhe neural network models were trained according to the same parameters set for all models in order to ensure consistency and a common basis for experiments. Optimization of model parameters during the training process was carried out to minimize the classification loss function. Тo synthesize the test sample, we used a video sequence covering the events of forest fires in the /rkutsk region, which was filmed by an unmanned aerial vehicle. Using a specially developed script in the Рython programming language, the process of dividing this video sequence into separate frames was carried out, which were used as a test data set when assessing the quality of classification of trained neural network models.Results. Based on the analysis of the obtained values of the quality criterion, as well as visual analysis on the test data set produced as part of testing neural network models, the effectiveness of the studied models for detecting forest fires in images was assessed. Тo assess the quality of binary classification of neural network models, the quality criterion “Accuracy” (classification accuracy) was used.Conclusion. Еxperimental studies on a test data set showed that the Retina-Net model demonstrates the lowest, but acceptable, performance compared to other studied neural network models. Тhe two-stage neural network models “Faster R-CNN” and “Mask R-CNN” demonstrate similar classification accuracy values (0.9492 and 0.9521, respectively), which allows us to recommend them for use in early detection systems for forest fires.
Accounting and Monitoring System of Electricity Expenditures Based on Geospatient Data Consumers Location
Authors: Lapina T. I. , Malykhina V. S. , Krupchatnikov R. A.
Published: April 2024

Thepurposeof the research is considers the development and implementation of a system of accounting and monitoring of electricity costs with visualization of geospatial location data by consumers, which provides technical accounting and analysis of the structure of electricity consumption, estimation of electricity consumption for the tasks of planning production volumes and purchasing electricity from producing companies based on consumer expenditure statistics, prevention of losses associated with unauthorized electricity extraction.Methods. When creating a project and software implementation of a system for monitoring and controlling energy consumption, methods of system analysis, methods of designing software for information systems, a unified object-oriented modeling language Unified Modeling Language (UML), DBMS SQLServer, development environment Microsoft Visual Studio Code (VS Code.) were used.Results. During the project, software for a monitoring and control system for electricity consumption with visualization of geospatial data on the location of consumers was developed and implemented.Тhe project was implemented, tested and introduced into the activities of JSC АtomЕnergoSbyt when planning and accounting for electricity supplies to consumers.Тhe testing results showed that the software system fully satisfies the functional requirements, is ready for use and was demonstrated at the exhibition center.Conclusion. А system for recording energy consumption data with visualization of the territorial location of consumers has been developed in order to control consumption and payments. Тhe developed system will solve the problem of delay in receiving readings from metering devices in the data collection system. Visualization of energy resource con- sumption data by objects and their territorial location with linked personal accounts, meters and consumption volumes will allow you to quickly control the volume of supplies and energy consumers. availability of payment, which will reduce unproductive losses and unauthorized connections.For the company JSC Аtomenergosbyt, operational visualization of consumer data makes it possible to analyze the coverage of consumers by territorial basis and plan new connections.
Efficacy of COMPAs, an App Designed to Support Communication Between Persons Living With Dementia in Long-Term Care Settings and Their Caregivers: Mixed Methods Implementation Study
Authors: Ansaldo Ana Inés , Masson-Trottier Michèle , Delacourt Barbara , Dubuc Jade , Dubé Catherine
Published: April 2024

Background

Persons living with dementia experience autonomy loss and require caregiver support on a daily basis. Dementia involves a gradual decline in communication skills, leading to fewer interactions and isolation for both people living with dementia and their caregivers, negatively impacting the quality of life for both members of the dyad. The resulting stress and burden on caregivers make them particularly susceptible to burnout.

Objective

This study aims to examine the efficacy of Communication Proches Aidants (COMPAs), an app designed following the principles of person-centered and emotional communication, which is intended to improve well-being in persons living with dementia and caregivers and reduce caregiver burden.

Methods

In this implementation study, volunteer caregivers in 2 long-term care facilities (n=17) were trained in using COMPAs and strategies to improve communication with persons living with dementia. Qualitative and quantitative analyses, semistructured interviews, and questionnaires were completed before and after 8 weeks of intervention with COMPAs.

Results

Semistructured interviews revealed that all caregivers perceived a positive impact following COMPAs interventions, namely, improved quality of communication and quality of life among persons living with dementia and caregivers. Improved quality of life was also supported by a statistically significant reduction in the General Health Questionnaire-12 scores (caregivers who improved: 9/17, 53%; z=2.537; P=.01). COMPAs interventions were also associated with a statistically significant increased feeling of personal accomplishment (caregivers improved: 11/17, 65%; t15=2.430; P=.03; d=0.61 [medium effect size]).

Conclusions

COMPAs intervention improved well-being in persons living with dementia and their caregivers by developing person-centered communication within the dyad, increasing empathy, and reducing burden in caregivers although most caregivers were unfamiliar with technology. The results hold promise for COMPAs interventions in long-term care settings. Larger group-controlled studies with different populations, in different contexts, and at different stages of dementia will provide a clearer picture of the benefits of COMPAs interventions.
Rolling the DICE (Design, Interpret, Compute, Estimate): Interactive Learning of Biostatistics With Simulations (Preprint)
Authors: Thiesmeier Robert , Orsini Nicola
Published: April 2024

UNSTRUCTURED

Despite the increasing relevance of statistics in health sciences, teaching styles in higher education are remarkably similar across disciplines: lectures covering the theory and methods, followed by application and computer exercises in given data sets. This often leads to challenges for students in comprehending fundamental statistical concepts essential for medical research. To address these challenges, we propose an engaging learning approach—DICE (design, interpret, compute, estimate)—aimed at enhancing the learning experience of statistics in public health and epidemiology. In introducing DICE, we guide readers through a practical example. Students will work in small groups to plan, generate, analyze, interpret, and communicate their own scientific investigation with simulations. With a focus on fundamental statistical concepts such as sampling variability, error probabilities, and the construction of statistical models, DICE offers a promising approach to learning how to combine substantive medical knowledge and statistical concepts. The materials in this paper, including the computer code, can be readily used as a hands-on tool for both teachers and students.
Prioritizing Trust in Podiatrists’ Preference for AI in Supportive Roles Over Diagnostic Roles in Health Care: Qualitative Interview and Focus Group Study (Preprint)
Authors: Tahtali Mohammed A , Snijders Chris C P , Dirne Corné W G M , Le Blanc Pascale M
Published: April 2024

BACKGROUND

As artificial intelligence (AI) evolves, its roles have expanded from helping out with routine tasks to making complex decisions, once the exclusive domain of human experts. This shift is pronounced in health care, where AI aids in tasks ranging from image recognition in radiology to personalized treatment plans, demonstrating the potential to, at times, surpass human accuracy and efficiency. Despite AI’s accuracy in some critical tasks, the adoption of AI in health care is a challenge, in part because of skepticism about being able to rely on AI decisions.

OBJECTIVE

This study aimed to identify and delve into more effective and acceptable ways of integrating AI into a broader spectrum of health care tasks.

METHODS

We included 2 qualitative phases to explore podiatrists’ views on AI in health care. Initially, we interviewed 9 podiatrists (7 women and 2 men) with a mean age of 41 (SD 12) years and aimed to capture their sentiments regarding the use and role of AI in their work. Subsequently, a focus group with 5 podiatrists (4 women and 1 man) with a mean age of 54 (SD 10) years delved into AI’s supportive and diagnostic roles on the basis of the interviews. All interviews were recorded, transcribed verbatim, and analyzed using Atlas.ti and QDA-Miner, using both thematic analysis for broad patterns and framework analysis for structured insights per established guidelines.

RESULTS

Our research unveiled 9 themes and 3 subthemes, clarifying podiatrists’ nuanced views on AI in health care. Key overlapping insights in the 2 phases included a preference for using AI in supportive roles, such as triage, because of its efficiency and process optimization capabilities. There is a discernible hesitancy toward leveraging AI for diagnostic purposes, driven by concerns regarding its accuracy and the essential nature of human expertise. The need for transparency and explainability in AI systems emerged as a critical factor for fostering trust in both phases.

CONCLUSIONS

The findings highlight a complex view from podiatrists on AI, showing openness to its application in supportive roles while exercising caution with diagnostic use. This result is consistent with a careful introduction of AI into health care in roles, such as triage, in which there is initial trust, as opposed to roles that ask the AI for a complete diagnosis. Such strategic adoption can mitigate initial resistance, gradually building the confidence to explore AI’s capabilities in more nuanced tasks, including diagnostics, where skepticism is currently more pronounced. Adopting AI stepwise could thus enhance trust and acceptance across a broader range of health care tasks, aligning technology integration with professional comfort and patient care standards.
Development and initial evaluation of a digital phenotype collection system for adolescents: proof-of-concept study (Preprint)
Authors: Cho Minseo , Park Doeun , Choo Myounglee , Kim Jinwoo , Han DougHyun
Published: April 2024

BACKGROUND

The growing concern on adolescent mental health calls for proactive early detection and intervention strategies. There is a recognition of the link between digital phenotypes and mental health, drawing attention to their potential utility. However, the process of collecting digital phenotype data presents challenges despite its promising prospects.

OBJECTIVE

The aim of this study was to develop and validate system concepts for collecting adolescent digital phenotypes that effectively manage inherent challenges in the process.

METHODS

In a formative investigation (n=34), we observed adolescent self-recording behaviors and conducted interviews to develop design goals. These goals were then translated into system concepts, which included planner resembling interfaces, simplified data input with tags, visual reports on behaviors and moods, and supportive EMA prompts. A proof-of-concept study was conducted over two weeks (n=16), using tools that simulated the concepts to record daily activities and complete EMA surveys. The effectiveness of the system was evaluated through semi-structured interviews, supplemented by an analysis of the frequency of records and responses.

RESULTS

The interview findings revealed overall satisfaction with the system concepts, emphasizing strong support for self-recording. Participants consistently maintained daily records throughout the study period, with no missing data. They particularly valued the recording procedures that aligned well with their self-recording goal of time management, facilitated by the interface design and simplified recording procedures. Visualizations during recording and subsequent report viewing further enhanced engagement by identifying missing data and encouraging deeper self-reflection. The average EMA compliance reached 72%, attributed to a design that faithfully reflected adolescents' lives, with surveys scheduled at convenient times and supportive messages tailored to their daily routines. The high compliance rates observed and positive feedback from participants underscore the potential of our approach in addressing the challenges of collecting digital phenotypes among adolescents.

CONCLUSIONS

Integrating observations of adolescents' recording behavior into the design process proved to be beneficial for developing an effective and highly compliant digital phenotype collection system.

CLINICALTRIAL

Ethical approval for the study was granted by the Yonsei University Institutional Review Board (7001988-202304-HR-1711-06)
Prácticas profesionales, modelos de intervención y proceso de producción de conocimientos
Authors: Escolar Cora , Travi Bibiana
Published: April 2024

En este artículo se presenta una serie de reflexiones surgidas en el marco del proyecto de investigación "Los Modelos en Trabajo Social y su implicancia en la intervención profesional". Se trata por una parte, de una revisión bibliográfica centrada en el conocimiento de la perspectiva de diversos autores respecto de los modelos en Trabajo Social, y a su vez de un estudio descriptivo de tipo cualitativo, a partir de dos estudios de caso en el conurbano bonaerense. Su objetivo final es realizar una caracterización y análisis de la utilización de modelos en la intervención profesional y sus implicancias teórico-metodológicas y ético-políticas. En esta ocasión, haremos referencia al concepto de modelo y su utilización en las Ciencias Sociales para luego centrarnos en el desarrollo de modelos de intervención en Trabajo Social según el planteo de diversos autores. Luego presentamos algunas reflexiones en relación al complejo escenario en el que se desarrolla la intervención y los desafíos que se dirimen en el hacer profesional de los trabajadores sociales al interior de una institución. A modo de supuesto, dejamos planteado que este hacer es un proceso de toma de decisiones y que es similar en la práctica de investigación y en la práctica profesional.