bluuebunny/crossref_metadata_2025 huggingface dataset:
A Deep Learning-based Approach for Predictive Evaluation of Microservice Maintainability
Authors: YILMAZ Rahime , KÖSE Abdullah Huzeyfe , BUZLUCA Feza
Published: April 2024

Microservice Architecture (MSA) has emerged as a prominent paradigm in software system design, emphasizing decomposing monolithic applications into independent and modular functional services. This architectural approach provides a number of benefits; however, realizing these benefits requires a robust evaluation strategy focused on assessing the quality of the software system. This study proposes an innovative learning-based approach to evaluate the microservices’ quality, particularly maintainability. It is based on a deep learning technique that predicts the maintainability levels of microservices into three categories: low, medium, and high, with the low category indicating the need for refactoring. The prediction technique asses maintainability by feeding source-code metric values from different open-source microservice projects as inputs and obtaining results directly through transfer learning. The proposed method employed transfer learning and achieved % a 91.83 F1 score on the validated dataset obtained from open-source projects for predicting the need for refactoring services. Additionally, it reached %82 overall accuracy in the three class categorizations, showing notable performance. Considering these findings, it can be stated that the proposed learning-based evaluation is an effective method to assess microservice quality. As a result, this proposed method offers valuable insights for informed decision-making in software development and maintenance processes.
Polyacrylamide gel synthesis of CuO/CuFe2O4 nanoparticles for H2S gas sensing
Authors: Tabrizi S.A. Hassanzadeh
Published: April 2024

In the present work, CuO/CuFe2O4 nanoparticles were synthesized via a polyacrylamide gel. The produced nanocomposites were utilized as a gas sensor for the detection of H2S gas. The nanoparticles were characterized via XRD, FTIR, SEM and TEM techniques. XRD results revealed that the as-prepared product was amorphous and CuO and CuFe2O4 phases were formed after calcination at 800°C. Microstructural studies showed that the nanoparticles have a particle size distribution ranging from 60 to 120 nm. Most of the particles had a spherical morphology. The polyacrylamide network acted as a template for the formation of the nanoparticles. The H2S gas sensing characteristics of the products were studied at different concentrations and operating temperatures. In addition, the effect of humidity on the gas-sensing response was investigated. The prepared CuO/CuFe2O4 sensors can respond up to 25 when exposed to 10 ppm H2S which is higher than the pure CuO or CuFe2O4 sensors. The sensors reached a detection limit of 0.1 ppm and demonstrated clear sensitivity and quick response and recovery behavior toward H2S gas. The CuO/CuFe2O4 heterogeneous nanostructures also showed proper H2S gas response and selectivity in response to interfering gases like NH3, NO2, HCHO and CO. The gas sensing mechanism of the composites was also discussed.
Research on enterprise carbon reduction technology selection strategy under low-carbon city and smart city
Authors: Wan Anwei , Huang Yongchun , Cui Wei
Published: April 2024

Low-carbon cities and smart cities are important policy tools for achieving China's "dual-carbon" goal. It is of great practical significance to explore the choice of carbon emission reduction technologies for enterprises under different pilot policies, in order to save production costs and enhance the effectiveness of enterprise emission reduction. Based on this, the study takes profit maximization as the goal, and includes only cleaner production technologies and end-of-pipe technologies in carbon emission reduction technologies, constructs a production function based on Hicks' neutral technology, and analyses the carbon reduction technology selection strategies of enterprises under the three types of pilot policies. Further, the Hansen threshold panel model is applied to verify the scientific validity of this technology selection mechanism. It is found that the selection of cleaner production technologies and end-of-pipe technologies in different pilot policies is based on the ratio of end-of-pipe technology inputs to outputs. Specifically: (1) If this ratio is at (0, 0.5), in low carbon cities, enterprises choose lower cost end-of-pipe technologies; in smart cities, enterprises lack the willingness to invest in carbon emission reduction technologies; and in dual-pilot cities, enterprises use both end-of-pipe technologies and cleaner production technologies to reduce carbon emissions. (2) If this ratio is at (0.5, 1), enterprises in all three types of pilot cities choose lower-cost source management technologies to reduce carbon. (3) The results of the heterogeneity analysis show that under the constraint of production cost, non-state-owned enterprises, old enterprises and enterprises in high-carbon industries lack the incentive to increase their investment in carbon reduction technologies. Therefore, governments at all levels should guide these three types of enterprises to enter the carbon trading market, and stimulate the initiative of low-carbon technological innovation of these three types of enterprises through policy subsidies, high-tech enterprise incubation, and the promotion of carbon emission reduction source-governance technologies, so as to ultimately achieve the decline of the total amount of carbon emissions at the smallest cost of carbon emission reduction.
Use of Prompt-Based Learning for Code-Mixed and Code-Switched Text Classification
Authors: Udawatta Pasindu , Udayangana Indunil , Gamage Chathulanka , Shekhar Ravi , Ranathunga Surangika
Published: April 2024

Code-mixing and code-switching (CMCS) are prevalent phenomena observed in social media conversations and various other modes of communication. When developing Natural Language Processing (NLP) systems such as sentiment analysers and hate-speech detectors that operate on this social media data, CMCS text poses challenges. Recent studies have demonstrated that prompt-based learning of pre-trained language models (PLMs) outperforms full fine-tuning of PLMs across various NLP tasks. Despite the growing interest in CMCS text classification, the effectiveness of prompt-based learning for the task remains unexplored. Our study endeavours to bridge this gap by examining the impact of prompt-based learning on CMCS text classification. We discern that the performance in CMCS text classification is significantly influenced by the inclusion of multiple scripts and the intensity of code-mixing. In response, we introduce a novel method, Dynamic+AdapterPrompt, which employs distinct models for each script, integrated with adapters. While DynamicPrompt captures the script-specific representation of CMCS text, AdapterPrompt emphasizes capturing the task-oriented functionality. Our experiments span across Sinhala-English, Kannada-English, and Hindi-English datasets, encompassing sentiment classification, hate-speech detection, and humour detection tasks. The outcomes indicate that our proposed method outperforms strong fine-tuning baselines and basic prompting strategies.
Impact of TMZ treatment on the nucleolar features of live glioblastoma cells
Authors: Torgo Daphne , Mattos Camilla B. , Pereira Luiza C. , Lenz Guido , Lenz Luana S.
Published: April 2024

Nucleoli are essential for maintaining cell homeostasis as they regulate the formation of ribosomal subunits, fundamental for protein synthesis. Failure of proper ribosomal biogenesis under favorable conditions or cell stress can create an environment that may favor cancer development. The number and size of nucleoli are commonly altered in almost all cancers and can be considered a prognostic factor due to their influence on cell growth. Despite their recognized morphological significance in tumor progression, the involvement of the nucleolus in the acute tolerance to chemotherapy and the incidence of nucleolar changes after treatment remains unclear. Here, we characterized the nucleolar response of glioblastoma cells to acute temozolomide (TMZ) treatment. The stress induced by TMZ led to notable changes in nucleolar morphology, including increased nucleolar area and number, accompanied by a reduction in circularity. Furthermore, the signals of Ki67 and fibrillarin, proteins associated with cell proliferation and nucleolar activity, were boosted in response to treatment. These responses differed from typical nucleolar stress, here induced by actinomycin-D, suggesting that TMZ triggers an alternative nucleolar response to the stress caused by chemotherapy. These findings highlight a connection between nucleoli and chemotherapy response, offering new insights into the potential mechanisms of tolerance that underlay cancer dynamics.
Improved Reinforcement Learning for Preventing Consumer Food Waste in Volatile Food Markets
Authors: Turgut Ozgu
Published: April 2024

Lack of proper planning is pointed out as one of the main culprits behind the significant consumer-end food waste. This observation can be used to build effective solutions, especially in digitalized societies. This paper proposes a reinforcement learning (RL) based decision support unit (DSU) in order to prevent food waste specifically for household and restaurant kitchens. The proposed RL model is improved with the help of mathematical modeling. The DSU assumes a generic kitchen environment for improving three important aspects of food management: the total shopping budget, the unused amount of ingredients, and the nutrition level offered by the selected menu. The RL-based algorithm is built to generate menu recommendations in a volatile market. All the practical contributions of the proposed planning tool to “monitor”, “prevent” and “reuse” levers of sustainable food strategy are summarized in a generic kitchen example. Results indicate that the proposed DSU can save around 30% from monthly shopping costs concurrently improving unused ingredients and nutritional intake. More insights about industrial processes such as package sizing and integration with “food sharing” services are also highlighted. Offering only one extra package size option for each ingredient in a market with volatile prices can help to diminish unused amounts completely and cut total shopping costs by 68% in a planned kitchen. Furthermore, the contribution of integrating mathematical optimization results into basic reinforcement learning implementation is observed as a 40% more reduction in the unused ingredients amount especially when the volatility of the market increases due to any disruption.
Therapiefreie Remission bei Patienten mit chronisch myeloischer Leukämie : Umsetzung in onkologischen Praxen
Authors:   , Nesswetter Sophie
Published: April 2024

Die chronische myeloische Leukämie (CML) ist eine klonale myeloproliferative Neoplasie und hat ihren Ursprung in transformierten pluripotenten Stammzellen im Knochenmark. Der Krankheitsentstehung liegt eine reziproke chromosomale Translokation zugrunde, in deren Folge ein neues Fusionsgen, das sogenannte Philadelphia-Chromosom, entsteht. Das hiervon codierte Genprodukt ist eine Tyrosinkinase mit konstitutiver Aktivität mit resultierender unkontrollierter Signaltransduktion. Gegen diese Tyrosinkinase existiert eine molekular zielgerichtete Therapie, die Tyrosinkinase-Inhibitoren (TKI). Den Therapiestandard stellt die Behandlung mit einem TKI dar. Seit einigen Jahren existiert jedoch das Therapieziel der therapiefreien Remission (TFR), bei dem CML-Patienten mit einem guten molekularen Ansprechen den TKI nach einiger Zeit absetzen und unter engmaschigen Kontrollen therapiefrei bleiben. Ungefähr die Hälfte dieser Patienten erleidet kein molekulares Rezidiv und bleibt langfristig in TFR. Zu der Thematik der TFR existieren zahlreiche klinische Studien, die die Umsetzbarkeit und die Sicherheit eines Absetzversuchs belegen und Kriterien definiert haben, die für einen Absetzversuch erfüllt sein sollten. In dieser Dissertation wird die Umsetzung der TFR im klinischen Alltag onkologischer Praxen untersucht. Es wird untersucht, ob die Studienergebnisse mit den TFR-Raten und den identifizierten Einflussfaktoren auf den Praxisalltag übertragbar sind und ob das Therapieziel TFR in den klinischen Alltag integrierbar ist. Hierfür werden die Daten von 61 CML-Patienten mit einem Absetzversuch aus fünf onkologischen Praxen retrospektiv ausgewertet. Erhoben werden Parameter der Routineversorgung und die Ergebnisse der Kontrolluntersuchungen während der TFR werden dokumentiert und ausgewertet. Die TFR-Raten von ca. 50%, die in den Absetz-Studien beobachtet wurden, finden sich im hier untersuchten Patientenkollektiv wieder. Mithilfe der binären logistischen Regression wird getestet, ob bestimmte Faktoren, wie die Therapiedauer und das verwendete Medikament vor dem Absetzen, einen signifikanten Einfluss auf den Verlauf der TFR haben. Hier kann kein signifikanter Einflussfaktor identifiziert werden. Es lässt sich eine signifikant längere therapiefreie Überlebensdauer bei den Patienten zeigen, die mit einem TKI der zweiten Generation vor dem Absetzen behandelt wurden. Zusammenfassend lässt sich sagen, dass die TFR bei geeigneten CML-Patienten in der Praxis umsetzbar und sicher ist und fest im klinischen Alltag onkologischer Praxen verankert sein sollte.
In Silico Analysis of Mutations Along the Amyloidogenic Pathway in Alzheimer’s Disease
Authors: Zhao Wenqi
Published: April 2024

Through in silico simulation of mutations and their effect on protein structure, we conclusively examine the impact of mutations along the amyloidogenic pathway in three steps: as factors which undermine the suppression of A? production from BACE-1; the inhibition of amyloid breakdown by neprilysin; and the aggregation of A? monomers through oligomeric and fibril stages. We verified the significance of mutations in miRNA that particularly complement with BACE1. We discovered novel mutations that impede most significantly on neprilysin function. And we examined the importance of mutations on the propensity of A? to aggregate. The results are significant: the framework and algorithm of the paper can be employed to make accurate predictions for patients from simple and widely accessible genetic data. Beyond that, given the ubiquity of proteins within our body, the functions for modelling miRNA suppression, predicting protein function and calculating protein aggregation also have widespread uses in all areas of human biology and medicine.
Возможности использования платформ ProgressMe и Notion в преподавании иностранных языков
Authors: Пьяных А.И. , Климентьев Д.Д.
Published: April 2024

В статье авторы предлагают подробный обзор образовательных платформ ProgressMe и Notion для преподавания иностранных языков, в частности, основные преимущества и недостатки их использования в учебном процессе. Исследование представляет практические рекомендации по интеграции этих платформ в учебный процесс с целью повышения мотивации студентов и качества обучения.
Включение лиц с инвалидностью в добровольческую деятельность как механизм сопровождения в процессе профессионального самоопределения на примере КГМУ
Authors: Алюшина Д.С. , Заднепровский А.С.
Published: April 2024

В данной статье представлен обзор отечественных исследований опыта развития добровольчества в инклюзивной сфере. Авторами рассмотрены вопросы сопровождения лиц с инвалидностью в процессе профессионального самоопределения посредством включения в добровольческую деятельность. В статье приведен опыт работы с инвалидами в условиях медицинского университета в сфере профессионально ориентированной добровольческой деятельности.
Study on temporal and spatial variations of excessive dissolved phosphorus in the Fuquan section of the Chong-an River
Authors: Lu Xiaobin
Published: April 2024

There were many phosphorus chemical enterprises and phosphogypsum slag fields in the Fuquan section of the Chong-an River in the Guizhou Province of China; therefore, the dissolved phosphorus in the Fengshanqiaobian water quality monitoring section of the area has exceeded 0.2 mg/L for a long time. This study analyzed the monitoring data of dissolved phosphorus, fluoride, nitrate–nitrogen, and chemical oxygen demand in the main stream and key tributaries of the Fuquan section of the Chong-an River from 2015 to 2021, in which the main exceeding factor was dissolved phosphorus of more than 0.2 mg/L; determined the variation law of phosphorus pollution in the water body of the Fuquan section of the Chong-an River, in which the exceedance of phosphorus was mainly concentrated in May of flood season and in January and March of the drought season; evaluated the sources of phosphorus pollution, in which the main pollution sources were from phosphogypsum slag field leakage, phosphorus chemical industry plant leakage, agricultural nonpoint source pollution; and presented measures to reduce phosphorus pollutants in rivers, such as strengthening phosphogypsum slag field and phosphorus chemical enterprise seepage prevention measures, and reducing the amount of phosphate fertilizer application.
Effects of carbonization temperature and time on the characteristics of carbonized sludge
Authors: Wan Junjie , Feng Xin , Li Biqing , Wang Mingsheng , Tang Xia , Chen Jun , Rong Jianyun , Ma ShanShan , Jiang Yiwen , Zhang Zemin
Published: April 2024

To investigate the influence of carbonization process parameters on the characteristics of municipal sludge carbonization products, this study selected carbonization temperatures of 300–700 °C and carbonization times of 0.5–1.5 h to carbonize municipal sludge. The results showed that with an increase in temperature and carbonization time, the sludge was carbonized more completely, and the structure and performance characteristics of the sludge changed significantly. Organic matter was continuously cracked, the amorphous nature of the material was reduced, its morphology was transformed into an increasing number of regular crystalline structures, and the content of carbon continued to decrease, from the initial 52.85 to 38.77%, while the content of inorganic species consisting continued to increase. The conductivity was reduced by 87.8%, and the degree of conversion of salt ions into their residual and insoluble states was significant. Natural water absorption in the sludge decreased from 8.13 to 1.29%, and hydrophobicity increased. The dry-basis higher calorific value decreased from 8,703 to 3,574 kJ/kg. Heavy metals were concentrated by a factor of 2–3, but the content of the available state was very low. The results of this study provide important technological support for the selection of suitable carbonization process conditions and for resource utilization.
Protective Effects and Mechanisms of Luteolin against Acute Respiratory
Distress Syndrome: Network Pharmacology and In vivo and In vitro Studies
Authors: Li Quan , Chen Juan , Ren Yi , Yang Zhizhou , Wang Mengmeng , Zhang Wei , Cao Liping , Sun Haijun , Nie Shinan , Sun Zhaorui
Published: April 2024

Background:

Acute Respiratory Distress Syndrome (ARDS) is an acute life-threatening disease,
and luteolin has the potential to become a therapeutic agent for ARDS. However, its mechanism of action has
not yet been clarified.

Objective:

The present study explored the potential effects and mechanisms of luteolin in the treatment of
ARDS through network pharmacology analysis and verified them through biological experiments.

Methods:

The potential targets of luteolin and ARDS were obtained from online databases. Functional enrichment
and protein-protein interaction (PPI) analyses were performed to explore the underlying molecular mechanisms
and to identify hub targets. Molecular docking was used to verify the relationship between luteolin and
target proteins. Finally, the effects of luteolin on key signaling pathways and biological processes were verified
by in vitro and in vivo experiments.

Results:

A total of 146 luteolin- and 496 ARDS-related targets were extracted from public databases. The network
pharmacological analysis suggested that luteolin could inhibit ARDS through the following potential
therapeutic targets: AKT1, RELA, and NFKBIA. Inflammatory and oxidative stress responses were the main
biological processes involved, with the AKT/NF-κB signaling pathway being the key signaling pathway targeted
by luteolin for the treatment of ARDS. Molecular docking analysis indicated that luteolin had a good binding
affinity to AKT1, RELA, and NFKBIA. The in vitro and in vivo experiments revealed that luteolin could
regulate the inflammatory response and oxidative stress in the treatment of ARDS by inhibiting the AKT/NF-
κB signaling pathway.

Conclusion:

Luteolin could reduce the production of reactive oxygen species and inflammatory factors by inhibiting
the AKT/NF-κB signaling pathway, thus reducing apoptosis and attenuating ARDS.
Identification of Molecular Correlations of GSDMD with Pyroptosis in
Alzheimer's Disease
Authors: Song Tangtang , Chen Yan , Li Chen , Yao Yinhui , Ma Shuai , Shang Yazhen , Cheng Jianjun
Published: April 2024

Aim:

An analysis of bioinformatics and cell experiments was performed to verify the relationship
between gasdermin D (GSDMD), an executive protein of pyroptosis, and Alzheimer's disease (AD).

Methods:

The training set GSE33000 was utilized to identify differentially expressed genes (DEGs) in
both the AD group and control group, as well as in the GSDMD protein high/low expression group.
Subsequently, the weighted gene co-expression network analysis (WGCNA) and the least absolute
shrinkage and selection operator (LASSO) regression analysis were conducted, followed by the selection
of the key genes for the subsequent Gene Ontology (GO) and Kyoto Encyclopedia of Genes and
Genomes (KEGG) analyses. The association between GSDMD and AD was assessed and confirmed in
the training set GSE33000, as well as in the validation sets GSE5281 and GSE48350. Immunofluorescence
(IF) was employed to detect the myelin basic protein (MBP), a distinctive protein found in the
rat oligodendrocytes (OLN-93 cells). A range of concentrations (1-15 μmol/L) of β-amyloid 1-42
(Aβ1-42) were exposed to the cells, and the subsequent observations were made regarding cell morphology.
Additionally, the assessments were conducted to evaluate the cell viability, the lactate dehydrogenase
(LDH) release, the cell membrane permeability, and the GSDMD protein expression.

Results:

A total of 7,492 DEGs were screened using GSE33000. Subsequently, WGCNA analysis identified
19 genes that exhibited the strongest correlation with clinical traits in AD. Additionally, LASSO regression
analysis identified 13 key genes, including GSDMD, AFF1, and ATOH8. Furthermore, the investigation
revealed that the key genes were associated with cellular inflammation based on GO and
KEGG analyses. Moreover, the area under the curve (AUC) values for the key genes in the training and
validation sets were determined to be 0.95 and 0.70, respectively. Significantly, GSDMD demonstrated
elevated levels of expression in AD across both datasets. The positivity of MBP expression in cells exceeded
95%. As the concentration of Aβ1-42 action gradually escalated, the detrimental effects on cells
progressively intensified, resulting in a gradual decline in cell survival rate, accompanied by an increase
in lactate dehydrogenase release, cell membrane permeability, and GSDMD protein expression.

Conclusion:

The association between GSDMD and AD has been observed, and it has been found that Aβ1-42
can induce a significant upregulation of GSDMD in OLN-93 cells. This suggests that Aβ1-42 has the potential
to induce cellular pyroptosis and can serve as a valuable cellular pyroptosis model for the study of AD.
Vernodalin Triggers ROS-Mediated Apoptosis in TPC-1 Human Papillary
Thyroid Cancer Cells via Suppression of the MAPKs Signaling Pathway
Authors: Yang Xijia , Wei Meng , An Yuan , Liang Qinlong , Nan Jing , Vijayalakshmi Annamalai , Wang Zizhang
Published: April 2024

Background:

Thyroid Cancer (TC) is an endocrine organ malignancy that has become
more common in recent decades. Vernodalin (VN), a cytotoxic sesquiterpene, has been reported
to exhibit anticancer properties against human breast and liver cancer cells. However, no study
has explored the efficacy of VN with respect to its antiproliferative and apoptotic action on human
Papillary Thyroid Cancer cells (PTC).

Objective:

The study intended to examine the antitumor and antiproliferative effects of VN and
the apoptosis mechanisms underlying its action on TPC-1 human PTC cells.

Methods:

In this study, we examined the VN cell viability by MTT assay; performed ROS
measurement by DCFH staining method, MMP identification by Rh-123 staining method, and
apoptotic morphological assay by employing AO/EB and DAPI stain method, and further, p38
MAPK/ERK/JNK cell proliferation markers were determined by western blotting technique.

Results:

The findings showed that VN could inhibit the growth of PTC cells by increasing intracellular
ROS, damaging MMP, and stimulating apoptosis in a concentration-dependent manner.
The study demonstrated how VN inhibited TPC-1 cell viability by causing ROS-induced cell
death via the MAPK signaling pathway.

Conclusion:

VN may serve as an agonist to impact apoptosis in PTC cells. In human PTC, VN
could play an effective role in chemotherapy. More studies pertaining to animal tumor models
are needed to prove its anti-cancer effectiveness in vivo.
Knockdown of Ubiquitin-Conjugating Enzyme E2 T Abolishes the
Progression of Head and Neck Squamous Cell Carcinoma by Inhibiting
NF-Κb Signaling and inducing Ferroptosis
Authors: Cai Feng , Xu Hongbo , Song Shilong , Wang Gengming , Zhang Yajun , Qian Jing , Xu Lu
Published: April 2024

Background:

Ubiquitin-conjugating enzyme 2T (UBE2T) has been reported to be associated
with uncontrolled cell growth and tumorigenesis in multiple cancer types. However, the understanding
of its regulatory role in the carcinogenesis of Head And Neck Squamous Cell Carcinoma
(HNSC) is limited.

Methods:

UBE2T expression in HNSC patient samples and the correlation between its expression
and patients’ survival rates were evaluated using The Cancer Genome Atlas (TCGA) database.
Cell survival and proliferation were investigated in UM-SCC1 and UM-SCC15 cells infected with
control and shUBE2T lentivirus. The xenograft mouse model was established using UM-SCC15
cells to examine HNSC tumorigenesis with or without UBE2T. Western blot, qRT-PCR, and ferroptosis
assays were carried out to disclose the interaction between UBE2T and NF-κB signaling
and ferroptosis.

Results:

The increased expression of UBE2T was noted in tumor tissues of patients with HNSC,
correlating with a significantly reduced overall survival time in this patient cohort. Knockdown of
UBE2T inhibited HNSC tumorigenesis and tumor growth. Mechanistically, inhibition of UBE2T
suppressed NF-κB signaling and induced ferroptosis in HNSC.

Conclusion:

Our study underscores the multifaceted role of UBE2T in HNSC, illuminating its potential
as a biomarker and therapeutic target.
The Value of Computer Vision in Identifying the Bone of Dialysis Patients
Authors: Zhang Wei , Sun Dong , Zhang Xiaoli , Wu Gang
Published: April 2024

Background::

In the end stage of kidney disease, abnormal levels of blood calcium, phosphorus, and parathyroid hormone lead to bone metabolism disorders,
manifesting as osteoporosis or fibrocystic osteoarthritis. X-ray, CT, and MR are useful for detecting bone lesions in dialysis patients, but currently,
computer vision has not yet been used for this purpose.

Methods::

ResNet is a powerful deep CNN model, which has not yet been used to distinguish between the bones of dialysis patients and healthy people.
Therefore, this study aimed to investigate the ability of the Resnet50 model to identify the bone of dialysis patients from normal bone.

Results::

CT images of 200 cases (100 dialysis patients and 100 healthy people aged 31-72 years with male:female ratio of 51:49) were randomly divided
into the training and testing groups at the ratio of 8:2. The module of ‘torch’ was used to train the model of Resnet50 for the current task of image
classification. In the test cohort, the accuracy, sensitivity, and specificity with hyper-parameter=0 were 60%, 65%, and 55%, respectively. When
the hyper-parameter was 0.6 or 0.7 versus 0, the accuracy was significantly higher (P<0.05). When the hyper-parameter was another number, the
accuracy was not significantly different from that with no hyper-parameter (P>0.05).

Conclusion::

This study has indicated computer vision to be suitable for identifying bone changes caused by dialysis; a hyper-parameter has been found
necessary for improving model accuracy. The ResNet50 model with hyper-parameter = 0.7 has exhibited 90% sensitivity in identifying the bone of
dialysis patients.
Antioxidant Properties of Brassica Rapa L. Seeds and Immunostimulant Effect on Immunity Broilers Cells (Gallus Gallus Domesticus)
Authors: Laaraj Soukaina , Ouahidi Ibtissam , Al Moudani Nada , Boukir Abdellatif , Jaouhar Samira , Er Raouan Safae , Aarab Lotfi
Published: April 2024

Background:

In the past few decades, researchers have focused on finding the benefits
of natural substances derived from plants.

Objective:

This study aimed to evaluate the use of Brassica rapa seeds in poultry feed as an antioxidant
and immunostimulant of host defenses.

Methods:

We prepared three extracts using ethanol, Ethyl Acetate, and water. Spectrophotometric
methods determined the total phenolic and flavonoid content in the three extracts. Antioxidant
activity was assessed using 1,1-diphenyl-2-picrylhydrazyl (DPPH), ferric reducing/antioxidant
power (FRAP), 2,2'-azinobis(3-ethylbenzothiazoline-6-sulfonic acid) diammonium salt (ABTS)
radicals and β-Carotene bleaching methods. An assessment of their immunostimulant activities in
vitro was performed on chicken immunity cell proliferation (splenocytes, thymocytes, and Bursa
cells) and IgY production.

Results:

The total phenolic contents ranged from 462.5 to 794.8 mg /g of extract, the order of
TPC was as follows: EtOAc > EtOH >Water. Flavonoid contents were, 63.7 mg in EtOH extract,
81.2 mg in EtOAc extract, and 108.7 mg/g Extract in aqueous extract. By DPPH, the IC50s of
EtOH, EtOAc, and water, were 1.8μg/ml, 2.4μg/ml, and 1.5μg/ml, respectively. Using the Ferric-
Reducing Antioxidant Power (FRAP), we remarked that the EtOH and EtOAc extracts have important
antioxidant powers. The ABTS assay indicated that EtOH and water had the highest activities
with IC50s of 0.19 and 0.07, respectively. Finally, by the β-carotene bleaching test, we observed
that the IC50 of the EtOH, EtOAc, and water were 62.1 μg/mL; 72.7 μg/mL, and 45.8
μg/mL, respectively. The results obtained indicate that Brassica aqueous extract stimulates humoral
immunity by stimulating splenocyte (B and T-lymphocytes) and Bursa cell (B-lymphocyte)
proliferation by more than 200% of response vs control. In addition, the aqueous extract highly
stimulated the function of bursa cells by 208% of the reaction. In the same conditions, we recorded
a stimulation of cellular immunity mediated by thymocytes by an increase in cell proliferation
(352.7% of response) implicated in virus protection. These extracts also possessed an antimicrobial
effect against diverse microorganisms such as coliforms and Staphylococcus. The FT-IR
spectrum indicated that the hydroxyl group (phenol), hydroxybenzoic acid family, carbohydrate
molecules such as glucopyranose, a carbonyl ester group, hydrocarbon chains (alkyls groups))
were present.

Conclusion:

This result could have interesting applications in the poultry feed industry to enhance
the performance of animal development.
GB5mCPred: Cross-species 5mc Site Predictor Based on Bootstrap-based Stochastic Gradient Boosting Method for Poaceae
Authors: Sinha Dipro , Dasmandal Tanwy , Yeasin Md , Mishra Dwijesh Chandra , Rai Anil , Archak Sunil
Published: April 2024

Background:

One of the most prevalent epigenetic alterations in all three kingdoms of
life is 5mC, which plays a part in a wide range of biological functions. Although in-vitro techniques
are more effective in detecting epigenetic alterations, they are time and cost-intensive. Artificial intelligence-
based in silico approaches have been used to overcome these obstacles.

Aim:

This study aimed to develop a ML-based predictor for the detection of 5mC sites in Poaceae.

Objective:

The objective of this study was the evaluation of machine learning and deep learning
models for the prediction of 5mC sites in rice.

Methods:

In this study, the vectorization of DNA sequences has been performed using three distinct
feature sets- Oligo Nucleotide Frequencies (k = 2), Mono-nucleotide Binary Encoding, and Chemical
Properties of Nucleotides. Two deep learning models, long short-term memory (LSTM) and Bidirectional
LSTM (Bi-LSTM), as well as nine machine learning models, including random forest,
gradient boosting, naïve bayes, regression tree, k-Nearest neighbour, support vector machine, adaboost,
multiple logistic regression, and artificial neural network, were investigated. Also, bootstrap
resampling was used to build more efficient models along with a hybrid feature selection module for
dimensional reduction and removal of irrelevant features of the vector space.

Result:

Random Forest gains the maximum accuracy, specificity and MCC, i.e., 92.6%, 86.41%
and 0.84. Gradient Boosting obtained the maximum sensitivity, i.e., 96.85%. The Technique for Order
of Preference by Similarity to Ideal Solution (TOPSIS) technique showed that the best three
models were Random Forest, Gradient Boosting, and Support Vector Machine in terms of accurate
prediction of 5mC sites in rice. We developed an R-package, ‘GB5mCPred,’ and it is available in
CRAN (https://cran.r-project.org/web/packages/GB5mcPred/index.html). Also, a user-friendly prediction
server was made based on this algorithm (http://cabgrid.res.in:5474/).

Conclusion:

With nearly equal TOPSIS scores, Random Forest, Gradient Boosting, and Support
Vector Machine ended up being the best three models. The major rationale may be found in their architectural
design since they are gradual learning models that can capture the 5mC sites more correctly
than other learning models.
Mavacamten: A Review of a Novel Therapeutic Approach for
Hypertrophic Cardiomyopathy
Authors: Abdul Qadir Memon Ayesha , Shamim Areeba , Mirza Sanoober , Osama Muhammad , Naeem Muhammad Iyad , R. Wei Calvin
Published: April 2024

Hypertrophic Cardiomyopathy (HCM) is a heart disease that can cause left ventricular
hypertrophy, arrhythmias, heart failure, and sudden cardiac death. Currently, pharmacological
treatment is limited and ineffective. Mavacamten (CamzyosTM) is a cardiac myosin inhibitor developed
as a therapeutic option to reduce myocardial contractility and restoration of myocardial
function. The Food and Drug Administration (FDA) approved the use of Mavacamten in 2022
for HCM symptoms. Clinical studies have proven that Mavacamten can reduce Left Ventricular
Outflow Tract (LVOT) involvement, cardiac hypercontraction, and hypertrophy. This review
provides an overview of HCM, its pathophysiology, current treatments, synthesis of Mavacamten,
and the clinical trials of Mavacamten.
Transethosomal Carrier of Curcumin for Improved Topical Delivery:
Optimization, In-vitro and Stability Assessment
Authors: Rathod Raju , Pawar Pravin
Published: April 2024

Objective:

Currently, there is a clear lack of effective topical treatments for psoriasis. In
light of this unaddressed requirement, the work intends to develop, enhance, and assess the effectiveness
of a curcumin transethosomal gel for managing psoriasis. This work signifies the delivery
of a potential solution to fill the gap in topical psoriasis treatment.

Material and Methods:

Curcumin-loaded transethosomes were prepared using a mechanical dispersion
method. An initial study was conducted to determine the ideal concentrations of Lipoid
S100 and Isopropyl Myristate (IPM). To refine the ultimate transethosomal formulation, a full factorial
design (32) was employed, incorporating different levels of Lipoid S100 and IPM. Drug release
investigations and pharmacokinetics assessments of curcumin concentrations were performed
using a specialized dissolution apparatus and an animal model, respectively.

Results:

The characterization profile and analytical examinations have affirmed the stability of the
formulation throughout the study duration. Our findings indicate that the drug release mechanism
conforms to a diffusion pattern akin to Fickian transport. Furthermore, In-vivo investigations revealed
that the curcumin concentration in the bloodstream after oral administration was significantly
superior to that of the conventional formulation.

Conclusion:

Using curcumin-loaded transethosomes extends drug contact time and facilitates controlled
drug release, leading to enhanced bioavailability, decreased dosage needs, and heightened
patient safety.
Management of Gingivitis: Contemporary Approaches and Recent Therapeutic Advancements
Authors: Girbane Yuvraj Rameshrao , Wal Pranay , Khare Riya , Sarkar Sanjiban Utpalkumar , Bhise Manish Ramesh , Singh Virendra , Tyagi Lalit Kumar , Wal Ankita
Published: April 2024

Background:

Gingivitis, commonly known as gum disease, refers to several types of inflammatory diseases that impact the connective tissues that surround the teeth. Gingivitis causes swelling, redness, and bleeding of the gums in its early stages.

Objective:

This article aims to describe the standard gingivitis medication. It emphasizes recent advancements in the initial therapy, treatment, and healing mechanisms of gingivitis for achievement in the clinical testing of medicines that promise to enable disease modification in patients. Also, it aims to review recent advancements and emerging therapeutic developments in the management of gingivitis, including gene-based therapies, nanotherapies, anti-cytokine therapies, stem cell-based therapies, and probiotic therapies.

Methods:

The information for the review articles was acquired by using Google Scholar and PubMed as search engines, as well as a number of publishers, including Springer Nature, Ben-tham Science, Taylor & Francis, Elsevier, and Frontier.

Result and Discussion:

Gingivitis is a gum disease and scaling root planning (SRP) is now the most common kind of periodontitis therapy available. It has the potential to deliver significant therapeutic success, but it can also have substantial problems that reduce the quality of life of a patient. Stem cell therapies, gingivitis genetic engineering, nuclear-based medicines, and other advances have given people hope that a wide range of illnesses, especially genetic disorders, can be cured.

Conclusion:

The current gingivitis therapies are successful and continually evolving, with sev-eral drugs currently in clinical trials. These innovative medicines, when combined, may alter gingivitis treatment in the next few years. Finally, gingivitis therapy requires professional dental care and patient education on oral hygiene. Nonetheless, further research and clinical studies are necessary to validate the efficacy, safety, and long-term benefits of these novel treatment modalities.
Clinical Trial to Evaluate Safety and Efficacy of Thinqure20 (A Herbal Composition) in the Treatment and Prophylaxis of Novel Coronavirus and Testing its In vitro- Potential against MS2 Bacteriophagae, Corona Virus, Influenza Virus and Mucor racemosus
Authors: Gharpure Milind , Rangnekar Hrishikesh , Dhawal Pranjali P , Varma Nikhil
Published: April 2024

Background and Objective:

Thinqure20 is a polyherbal, reverse-pharmacology-based
formulation that contains Piper longum, Piper nigrum, Zingiber officinale, and rock salt as active
ingredients. It is designed to work as an effective antiviral agent and also as a preventive measure
against SARS-CoV-2. Clinical and non-clinical studies have established significant safety efficacy
and tolerability of Thinqure20 formulation in the treatment of COVID-19 infection.

Methods:

In vivo human study was conducted on COVID-19 patients for 5 days. A total of 30
Covid-19 patients (n = 30) were enrolled. In vitro, cell line studies were also carried out to evaluate
the potential effectiveness of Thinqure20 polyherbal formulation as an antiviral, antifungal, and Angiotensin-
Converting Enzyme 2 (ACE2) inhibition.

Results:

Human studies have demonstrated a mean percentage of reduction in viral load from baseline
to end of the study visit which was found to be 75.4%. The minimum and maximum reduction in
viral load was found to be 59.3% and 100%, respectively. Viral load testing was carried out by Reverse
Transcriptase-quantitative Polymerase Chain Reaction (RT-qPCR) test. In vitro studies of
Thinqure, 20 extracts showed potential antiviral activity against MS2 bacteriophage, influenza, and
human coronavirus, antifungal activity against Mucor racemosus, and significant ACE2 receptor
inhibition.

Conclusion:

Thinqure20, a polyherbal formulation, is a potentially effective antiviral agent against
non-enveloped viruses (MS2 bacteriophage), enveloped viruses (influenza and human coronavirus),
and antifungal agent against mucor strains. It is also proven to be effective in the treatment of
COVID-19 and can be attributed to an early recovery by the reduction in viral load.
Derechos de participación y consulta indígena: el análisis de una postura judicial indiferente
Authors: Colombero Paola , Delas Samanta
Published: April 2024

El presente trabajo explora el uso del derecho internacional de los derechos humanos que hace el Tribunal Superior de Justicia de la provincia de Chubut, Argentina en un caso emblemático fácticamente por su resonancia sociopolítica y por los intereses locales y transnacionales puestos en juego y teóricamente porque requería un uso robusto de las normas del didh. En un marco de flexibilización de la legislación protectora ambiental referente al extractivismo minero, se interpone un reclamo sobre derechos de participación y consulta previa, informada y libre de comunidades indígenas. El análisis expone que el stj toma una postura de indiferencia hacia el uso del didh en el caso bajo estudio.
Effectiveness of a Mobile Phone Messaging–Based Message Framing Intervention for Improving Maternal Health Service Uptake and Newborn Care Practice in Rural Jimma Zone, Ethiopia: Protocol for a Cluster Randomized Controlled Trial
Authors: Bulcha Gebeyehu , Abdissa Hordofa Gutema , Noll Josef , Sori Demisew Amenu , Koricha Zewdie Birhanu
Published: April 2024

Background

Ethiopia has high rates of maternal and neonatal mortality. In 2019 and 2020, the maternal and newborn mortality rates were estimated at 412 per 1,000,000 births and 30 per 10,000 births, respectively. While mobile health interventions to improve maternal and neonatal health management have shown promising results, there are still insufficient scientific studies to assess the effectiveness of mobile phone messaging–based message framing for maternal and newborn health.

Objective

This research aims to examine the effectiveness of mobile phone messaging–based message framing for improving the use of maternal and newborn health services in the Jimma Zone, Ethiopia.

Methods

A 3-arm cluster-randomized trial design was used to evaluate the effects of mobile phone–based intervention on maternal and newborn health service usage. The trial arms were (1) gain-framed messages (2) loss-framed messages, and (3) usual care. A total of 21 health posts were randomized, and 588 pregnant women who had a gestational age of 16-20 weeks, irrespective of their antenatal care status, were randomly assigned to the trial arms. The intervention consisted of a series of messages dispatched from the date of enrolment until 6-8 months. The control group received existing care without messages. The primary outcomes were maternal health service usage and newborn care practice, while knowledge, attitude, self-efficacy, iron supplementation, and neonatal and maternal morbidity were secondary outcomes. The outcomes will be analyzed using a generalized linear mixed model and the findings will be reported according to the CONSORT-EHEALTH (Consolidated Standards of Reporting Trials of Electronic and Mobile HEalth Applications and onLine TeleHealth) statement for randomized controlled trials.

Results

Recruitment of participants was conducted and the baseline survey was administered in March 2023. The intervention was rolled out from May 2023 till December 2023. The end-line assessment was conducted in February 2024.

Conclusions

This trial was carried out to understand how mobile phone–based messaging can improve maternal and newborn health service usage. It provides evidence for policy guidelines around mobile health strategies to improve maternal and newborn health.

Trial Registration

Pan African Clinical Trials Registry PACTR202201753436676; https://tinyurl.com/ykhnpc49

International Registered Report Identifier (IRRID)

DERR1-10.2196/52395
Generation of Backward-Looking Complex Reflections for a Motivational Interviewing–Based Smoking Cessation Chatbot Using GPT-4: Algorithm Development and Validation
Authors: Kumar Ash Tanuj , Wang Cindy , Dong Alec , Rose Jonathan
Published: April 2024

Background

Motivational interviewing (MI) is a therapeutic technique that has been successful in helping smokers reduce smoking but has limited accessibility due to the high cost and low availability of clinicians. To address this, the MIBot project has sought to develop a chatbot that emulates an MI session with a client with the specific goal of moving an ambivalent smoker toward the direction of quitting. One key element of an MI conversation is reflective listening, where a therapist expresses their understanding of what the client has said by uttering a reflection that encourages the client to continue their thought process. Complex reflections link the client’s responses to relevant ideas and facts to enhance this contemplation. Backward-looking complex reflections (BLCRs) link the client’s most recent response to a relevant selection of the client’s previous statements. Our current chatbot can generate complex reflections—but not BLCRs—using large language models (LLMs) such as GPT-2, which allows the generation of unique, human-like messages customized to client responses. Recent advancements in these models, such as the introduction of GPT-4, provide a novel way to generate complex text by feeding the models instructions and conversational history directly, making this a promising approach to generate BLCRs.

Objective

This study aims to develop a method to generate BLCRs for an MI-based smoking cessation chatbot and to measure the method’s effectiveness.

Methods

LLMs such as GPT-4 can be stimulated to produce specific types of responses to their inputs by “asking” them with an English-based description of the desired output. These descriptions are called prompts, and the goal of writing a description that causes an LLM to generate the required output is termed prompt engineering. We evolved an instruction to prompt GPT-4 to generate a BLCR, given the portions of the transcript of the conversation up to the point where the reflection was needed. The approach was tested on 50 previously collected MIBot transcripts of conversations with smokers and was used to generate a total of 150 reflections. The quality of the reflections was rated on a 4-point scale by 3 independent raters to determine whether they met specific criteria for acceptability.

Results

Of the 150 generated reflections, 132 (88%) met the level of acceptability. The remaining 18 (12%) had one or more flaws that made them inappropriate as BLCRs. The 3 raters had pairwise agreement on 80% to 88% of these scores.

Conclusions

The method presented to generate BLCRs is good enough to be used as one source of reflections in an MI-style conversation but would need an automatic checker to eliminate the unacceptable ones. This work illustrates the power of the new LLMs to generate therapeutic client-specific responses under the command of a language-based specification.