bluuebunny/crossref_metadata_2025_split huggingface dataset:
Expression of microRNA-133a and microRNA-208b in acute myocardial infarction; A randomized clinical trial
Authors: Ibrahim Sally , Osama Dina , Hegazy Ahmed , Hashmi Hafiz , Abou-Aisha Khaled , Gad Mohammed.Z 
Published: June 2023

Abstract
Background: Myocardial microRNAs (Myo-miR) like MiR-1, miR-133 and miR-208 are specific to cardiac muscles development and function. Diagnostic potential of MiR-1, miR-133 and miR-208 in acute episodes of myocardial infarction is unknown.
Methods: Patient of newly onset of acute myocardial infarction with elevated ST-segment admitted to Ain-Shams university hospital Cairo from May 2013 to December 2022 were enrolled. Written consent was obtained. Circulating MiRNAs were measured at 04, 08, 12, 24, 48 hours from onset of angina by RT-PCR and compare with conventional creatin-kinases for diagnostic potential. Results were analyzed by student t-test, ROC curve calculations and ANOVA were performed using GraphPad-Prism-9Version.
Results: 746 patients admitted with STEMI and 10(1.34%) cases were presented with new-onset episodes of STEMI with mean±SD age 54.2±8.49 year. miR-133a peaks at 8 hours, miR-208b peaks at 12 hours from onset of AMI compared to cTnI and CK-MB peak at 12hrs(P<0.001). ROC-curve for miR-133a AUC was 0.583,0.8,1,0.78 and 0.58 at 4,8,12,24 & 48 hours respectively. AUC for miR-208b was 0.87,0.888,0.888,0.627 compared to AUC of cTnI concentrations 0.59,1,1,0.75,0 and (ROC) curve for CK-MB was 0.59,1,1,0.8&0.73 respectively. Positive correlation was present between miR-133a and cTnI (R=0.926-R2= 0.858 P=0.47), miR-208b and cTnI (R=0.8-R2=0.64 P=0.1) , miR-208b and CK-MB was (R=0.888-R2=0.789 P=0.044) and CK-MB-cTnI (R=0.72) respectively.
Conclusion: We showed miR-133a and miR-208b diagnostic specificity superior over conventional blood biomarkers for acute onset of STEMI. (NCT05692752)
Venetoclax with Decitabine or Azacitidine in Relapsed or Refractory Acute Myeloid Leukemia
Authors: Bouligny Ian Michael , Murray Graeme , Ho Thuy , Doyel Michael , Patel Tilak , Boron Josh , Tran Valerie , Gor Juhi , Hang Yiwei , Alnimer Yanal , Zacholski Kyle , Venn Chad , Wages Nolan A. , Grant Steven , Maher Keri R. 
Published: June 2023

Abstract
Relapsed or refractory acute myeloid leukemia (AML) is associated with poor outcomes and resistance to therapy. The addition of venetoclax, a BCL-2 antagonist, to lower-intensity therapies results in improved survival in the first-line setting compared to monotherapy with a hypomethylating agent or low-dose cytarabine. Despite this, much remains unknown about the performance of venetoclax with a hypomethylating agent following the first-line setting. Additionally, while the ELN 2022 guidelines appear to improve the prognostication of AML, clarification is needed to determine how the revision applies to lower-intensity strategies. To investigate this, we retrospectively analyzed the performance of venetoclax with decitabine or azacitidine in relapsed or refractory AML under the ELN 2022 guidelines. We demonstrated that the ELN 2022 revision is not optimized for lower-intensity venetoclax-based strategies. To refine the prognostication schema, we showed significantly improved response and survival benefits for patients with mutated NPM1 and IDH. Relatively, patients with mutated NRAS, KRAS, and FLT3-ITD were associated with inferior response and survival. Furthermore, there is an unmet clinical need for tools to improve the selection of lower-intensity therapy candidates with borderline functional status. Using an incremental survival computation method, we discovered that a CCI score threshold of 5 distinguishes patients at an elevated risk of death. Together, these novel findings highlight areas of refinement to improve survival in relapsed or refractory AML.
An Energy-Efficient and Dynamic Clustering Approach for Wireless Sensor Networks
Authors: Abdolrazzagh-Nezhad Majid , Kherad Mehdi 
Published: June 2023

Abstract

Wireless sensor networks (WSNs) consist of multiple sensor nodes that are often randomly distributed in the environment and operate independently without human intervention. However, the limited power supply of these nodes presents a significant challenge for WSNs, making the development of energy-saving algorithms critical to increase network lifespan. Node clustering is a commonly used solution to reduce data transfer nodes and achieve data aggregation. Furthermore, the mobility of nodes in the network is often overlooked but can impact energy consumption. This study proposes a Dynamic Dual Head Clustering algorithm for WSNs (DDHCWSN) to reduce energy consumption. Instead of re-clustering in each round, the DDHCWSN updates existing clusters based on energy and position, allowing normal nodes to send data to the closest cluster head node. The algorithm considers two cluster heads, one for data aggregation and the other for sending data to the base station, which can have a better effect on network power consumption. The proposed algorithm was compared with six different algorithms in six different scenarios, and it performed well.
A novel subspace outlier detection method by entropy-based clustering algorithm
Authors: Zuo Zheng , Li Ziqiang , Cheng Pengsen , Zhao Jian 
Published: June 2023

Abstract

Subspace outlier detection has emerged as a practical approach for outlier detection. Classical full space outlier detection methods become ineffective in high dimensional data due to the “curse of dimensionality”. Subspace outlier detection methods have great potential to overcome the problem. However, the challenge becomes how to determine which subspaces to be used for outlier detection among a huge number of all subspaces. In this paper, firstly, we propose an intuitive definition of outliers in subspaces. We study the desirable properties of subspaces for outlier detection and investigate the metrics for those properties.Then, a novel subspace outlier detection algorithm with a statistical foundation is proposed. Our method adopts an entropy-based clustering algorithm to yield interesting subspace for outlier detection.Outliers are then detected by comparing outlierness of its neighbors, and the method only makes use of a small number of most interesting subspaces for outlier detection. We show by experiments that outliers discovered in a very small number of most interesting subspaces achieves remarkable higher accuracy than in the full space, and that the proposed method outperforms competing subspace outlier detection approaches on real world data sets.
Hypothyroidism Among Children and Adolescents With Nephrotic Syndrome in Mulago National Referral Hospital, Kampala, Uganda; a Cross-sectional Study
Authors: Tumwesige Maureen , Rujumba Joseph , Piloya Thereza , Aujo Carol 
Published: June 2023

Abstract
Background
Nephrotic syndrome (NS) is the commonest glomerular disease among children. It is characterized by heavy proteinuria and is a risk factor for hypothyroidism in the affected children. Hypothyroidism is of concern because it affects the physical and intellectual development of children and adolescents. This study sought to establish the prevalence and factors associated with hypothyroidism among children and adolescents with NS.
Methods
A cross-sectional design was used to study 70 children and adolescents aged 1–19 years diagnosed with nephrotic syndrome and being followed up in the kidney clinic in Mulago National Referral Hospital. Questionnaires were used to collect patients’ socio-demographics and clinical information. A blood sample was taken for analysis for thyroid stimulating hormone (TSH) and free thyroxine (FT4), renal function tests and serum albumin. Hypothyroidism included both overt and subclinical forms. Overt hypothyroidism was defined as TSH level > 10 mU/L and FT4 < 10pmol/L, or FT4 < 10pmol/l with normal TSH, or TSH < 0.5mU/l. Sub-clinical hypothyroidism was defined as TSH ranging between 5 and10 mU/L with normal age appropriate FT4 levels. Urine samples were collected and taken for a dipstick examination. The data was analyzed using STATA version 14 and a p-value < 0.05 was considered as significant.
Results
The mean age (standard deviation) of participants was 9 years (3.8). There were more males; 36 of 70 (51.4%). The prevalence of hypothyroidism was 23% (16/70 participants). Of the 16 children with hypothyroidism, 3 (18.7%) had overt hypothyroidism while 13 had subclinical hypothyroidism. Only low serum albumin, aOR 35.80 (confidence interval 5.97-214.69 and a p value of < 0.001) was associated with hypothyroidism.
Conclusion
The prevalence of hypothyroidism among children and adolescent with nephrotic syndrome attending Mulago Hospital paediatric kidney clinic was 23%. Hypolbuminemia was found to be associated with hypothyroidism. Therefore, children and adolescents that have severely low levels of serum albumin should be screened for hypothyroidism and linked to endocrinologists for care.
A Mixed Methods Exploration of Values and Attitudes of Healthcare Students towards Interprofessional Education involving an Inpatient in an Acute Hospital Setting
Authors: McCarthy Nora , Slattery Amy , Daly Jennifer , Hynes Helen 
Published: June 2023

Abstract

Background
Interprofessional education (IPE) occurs when students from two or more professions learn about, from, and with each other. Involving an inpatient in IPE in an acute hospital setting with patient-centred education may encourage movement between individual communities of practice, improving navigation of the broader clinical landscape of practice.
Methods
Four pilot workshops involving inpatients in an acute hospital occurred. Nine students from later years of their programmes were selected for each workshop by purposive sampling, three each from medicine, nursing and physiotherapy. Each workshop involved three subgroups of mixed disciplines with final full group discussion resulting in documentation of an overall picture of the patient, their clinical care to date and future clinical plan. One subgroup interacted directly with the patient. The other groups accessed relevant hospital documentation about the patient and their admission. A concurrent mixed methods research approach was taken. Semi-structured focus groups occurred with each discipline after each workshop, with subsequent analysis using Braun & Clarke’s reflexive thematic analysis process. Students completed the validated ‘Interprofessional Socialisation and Valuing Scale’ (ISPV) pre and post intervention. Inferential statistics compared overall scale and subscale scores pre- and post- intervention.
Results
Three major themes were identified: How are we currently relevant to one another? Who are we in our future professional context and in relation to one another? How do we align our activities and collaborate to develop into practice-ready healthcare professionals? These themes mirror landscapes of practice’s modes of identification of engagement, imagination and alignment, highlighting growth in knowledgeability of the students of the clinical landscape of practice. There was a statistically significant increase in overall interprofessional socialisation levels post-intervention, p < 0.001, with a statistically significant increase in all 3 subscales of the ISPV: Value - p < 0.001; Comfort - p < 0.001; and Ability - p < 0.001.
Conclusions
Through mixed methods research, the values and attitudes of healthcare students towards IPE involving an inpatient in an acute hospital setting were explored. A statistically significant increase in interprofessional socialisation and valuing was demonstrated. Furthermore, students grew in knowledgeability of the clinical landscape of practice, with inpatient involvement central to this growth.
An Inpatient Fall Risk Assessment Tool: Application of Machine Learning Models on Intrinsic and Extrinsic Risk Factors
Authors: Jahangiri Sonia , Abdollahi Masoud , Patil Rasika , Rashedi Ehsan , Azadeh-Fard Nasibeh 
Published: June 2023

Abstract
Purpose
This study aimed to identify the most impactful set of intrinsic and extrinsic fall risk factors and develop a data-driven inpatient fall risk assessment tool (FRAT).
Methods
The dataset used for the study comprised in-hospital fall records from 2012 to 2017. Two machine learning (ML) algorithms, Support Vector Machine (SVM) and Random Forest (RF) were utilized to predict the inpatient fall risk level. To enhance the performance of the prediction models, two approaches were implemented, including (1) feature selection to identify the optimal feature set and (2) the development of three distinct shift-wise models. Furthermore, the optimal feature sets in the shift-wise models were extracted.
Results
According to the results, RF outperformed SVM by reaching an accuracy, sensitivity, specificity, and AUC of 0.66, 0.74, 0.59, and 0.73, respectively, considering the full set of features. The performance of the models was further improved (by 3%-5%) by conducting a feature selection process for both RF and SVM models. Specifically, the RF model achieved an accuracy of 0.69 while considering the optimal set of predictors. Moreover, the shift-wise RF models demonstrated higher accuracies (by 4%-10%) compared to the same model using a full feature set.
Conclusion
This study's outcome confirms ML models' compelling capability in developing an inpatient FRAT while considering intrinsic and extrinsic factors. The insight from such models could form a foundation to (1) monitor the inpatients’ fall risk, (2) identify the major factors involved in inpatient falls, and (3) create subject-specific self-care plans.
Plasma GDF15 levels are not modified in response to weight loss induced by liraglutide in patients with type 2 diabetes mellitus
Authors: Straat Maaike , Bizino Maurice , Eyk Huub van , Lamb Hildo J , Smit Johannes , Jazet Ingrid , de Jager Saskia , Boon Mariëtte , Martinez-Tellez Borja , Hoekx Carlijn 
Published: June 2023

Abstract
Objectives
Glucagon-like peptide-1 receptor (GLP-1R) agonists induce weight loss in patients with type 2 diabetes mellitus (T2DM), but the underlying mechanism is unclear. Recently, the mechanism by which metformin induces weight loss could be explained by an increase in the growth differentiation factor 15 (GDF15), that suppresses appetite. Therefore, we aimed to investigate whether the GLP-1R agonist liraglutide modifies plasma GDF15 levels in patients with T2DM.
Methods
GDF15 levels were measured in plasma samples obtained from Dutch Europids and Dutch South Asians with T2DM before and after 26 weeks of treatment with liraglutide (n = 44) or placebo (n = 50).
Results
Treatment with liraglutide, compared to placebo, decreased body weight, but did not modify plasma GDF15 levels in all patients, or when data were split by ethnicity. Also, the change in plasma GDF15 levels after treatment with liraglutide did not correlate with changes in body weight or HbA1c levels. In addition, the dose of metformin used did not correlate with baseline plasma GDF15 levels.
Conclusion
Compared to placebo, liraglutide treatment for 26 weeks does not modify plasma GDF15 levels in Dutch Europid or South Asian patients with T2DM. Thus, the weight loss induced by liraglutide is likely explained by other mechanisms beyond the GDF15 pathway.
Proteomic landscape of astrocytes and pericytes infected with HIV/SARS-CoV-2 mono/co-infection, impacting on neurological complications
Authors: Acharya Arpan , Ambikan Anoop T , Thurman Michellie , Malik Mohid Reza , Dyavar Shetty Ravi , Végvári Ákos , Neogi Ujjwal , Byrareddy Siddappa N 
Published: June 2023

Abstract
Background
Although most individuals recover from coronavirus disease 2019 (COVID-19) within a few weeks, some people continue to experience a wide range of symptoms known as post-acute sequelae of SARS-CoV-2 (PASC) or long COVID. Majority of patients with PASC develop neurological disorders like brain fog, fatigue, mood swings, sleep disorders, loss of smell and test among others collectively called neuro-PASC. While the people living with HIV (PWH) do not have a higher risk of developing severe disease and mortality/morbidity due to COVID-19. As a large section of PWH suffered from HIV-associated neurocognitive disorders (HAND), it is essential to understand the impact of neuro-PASC on people with HAND. In pursuit of this, we infected HIV/SARS-CoV-2 alone or together in primary human astrocytes and pericytes and performed proteomics to understand the impact of co-infection in the central nervous system.
Methods
Primary human astrocytes and pericytes were infected with SARS-CoV-2 or HIV or HIV + SARS-CoV-2. The concentration of HIV and SARS-CoV-2 genomic RNA in the culture supernatant was quantified using reverse transcriptase quantitative real time polymerase chain reaction (RT-qPCR). This was followed by a quantitative proteomics analysis of mock, HIV, SARS-CoV-2, and HIV + SARS-CoV-2 infected astrocytes and pericytes to understand the impact of the virus in CNS cell types.
Results
Both healthy and HIV-infected astrocytes and pericytes support abortive/low level of SARS-CoV-2 replication. In both mono-infected and co-infected cells, we observe a modest increase in the expression of SARS-CoV-2 host cell entry factors (ACE2, TMPRSS2, NRP1, and TRIM28) and inflammatory mediators (IL-6, TNF-α, IL-1β and IL-18). Quantitative proteomic analysis has identified uniquely regulated pathways in mock vs SARS-CoV-2, mock vs HIV + SARS-CoV-2, and HIV vs HIV + SARS-CoV-2 infected astrocytes and pericytes. The gene set enrichment analysis revealed that the top ten enriched pathways are linked to several neurodegenerative disorders, including Alzheimer's disease, Parkinson's disease, Huntington's disease, and amyotrophic lateral sclerosis.
Conclusions
Our study emphasizes the significance of long-term monitoring of patients co-infected with HIV and SARS-CoV-2 to detect and understand the development of neurological abnormalities. By unraveling the molecular mechanisms involved, we can identify potential targets for future therapeutic interventions.
Synthesis and Preparation of Nanocomposites of Polyacrylamide Nanofluids in Enhanced Oil Recovery
Authors: Shahbazpanahi Hamid 
Published: June 2023

Abstract
EOR is a process that helps maximize recoverable oil reserves, extend field life and increase recovery rates, and is an important tool for companies to maintain production and increase return on investment. In this article, the performance of nanoclay on aqueous phase viscosity, wettability, and recycled oil in core fluidization in polyacrylamide nanofluid has been investigated in different experiments and EOR. We have used polymers due to the properties of polymers in increasing rheology and effective mobility and controlling stability and variability to resume growth oil in nanofluids. Adding 5% by weight of salt to polymer-clay nanofluid has also been investigated in samples comparable to pure nano clay without salt. The viscosity of this suspension increases by about 50% by adding a certain amount of salt. If the same amount of salt is added to the polymer diluent, the viscosity decreases drastically. The results of the wettability test also show that clay has a better potential to change the wettability in the tendency to salt. In core fluidization tests, the highest efficiency of 30% was obtained in the third recycling in the combination of clay nanoparticles and sulfone copolymer. The highest efficiency was obtained in the third scenario in core fluidization tests, that is; A combination of resin nanoparticles and sulfone copolymer. Their detailed behavior in the characteristics of wettability, rheology, and core fluidization is analyzed in this article.
Dissecting the mechanisms of intestinal immune homeostasis by analyzing T-cell immune response in Crohn's disease and colorectal cancer
Authors: Jiang Tianming , Zheng Jie , Li Nana , Li Xiaodong , He Jixing , Zhou Junde , Sun Boshi , Chi Qiang 
Published: June 2023

Abstract

Background: Maintenance of intestinal immune homeostasis is intricately linked to various immune cells, signaling pathways, and molecular mechanisms. Once the intestinal immune homeostasis is out of balance, it may lead to the occurrence of intestinal diseases. Here, we performed single-cell transcriptome analysis for autologous samples from primary colorectal tumors and Crohn’s disease to disentangle factors shaping the intestinal immune microenvironment.
Results:By aligning T cells across different tissues, we identified various T cell subtypes that maintained immune system homeostasis and were confirmed in enrichment analyses. Next, the pseudo-time trajectory of T cell subclusters was constructed in both syndromes so as to characterize their differentiation patterns and dig out key driver genes. Additionally, cellular communication and transcription factor regulatory networks are all critical components of the intricate web of mechanisms that regulate intestinal immune homeostasis. The complex cellular interaction suggested potential T-lineage immunotherapeutic targets against epithelial cells with high copy number variation level. Finally, regulon networks identified multiple candidates for promising cell-specific transcriptional factors.
Conclusion:This study focused on the immune molecular mechanism under intestinal diseases and contributed into novel insight of depicting a detailed immune landscape and revealing T-cell responding mechanisms in Crohn’s disease and colorectal cancer.
Validation of the Indonesian version of the WHO Self-Reporting Questionnaire (SRQ) – 20: A Psychometric Analysis
Authors: Hasanah Kartika Ayu Safinatunnajjah , Iskandar Shelly , Istiqamah Arifah Nur , Fatmawaty Intan Annisa , Jaya I Gede Nyoman Mindra 
Published: June 2023

Abstract

Background
Per year, mental disorders in Indonesia are increasing because of a lack of early detection and an insufficient number of mental health professionals to detect them early. It is important to minimize these problems by using a simple and valid screening tool for mental disorders. The self-reporting questionnaire 20 has been used regularly in Indonesia to detect symptoms of mental disorders. However, there is limited research on the factors and construct validity of SRQ-20. Thus, this study aimed to assess the factors and construct validity of SRQ-20 developed by the World Health Organization (WHO).
Methods
SRQ-20 data were obtained at random through the public health office’s primary health care program, which encompasses 41,588 individuals. Internal reliability was tested using Cronbach’s alpha. Exploratory factor analysis was used to discover its initial factors. In order to assess whether the SRQ-20 items were correctly employed, factorial validity was performed by utilizing principal component analysis with varimax rotation. Construct validity was done using Confirmatory factor analysis. Discriminant validity was done using the average variance extracted.
Results
The SRQ-20 had good internal consistency and reliability (α = 0.82). Findings of exploratory factor analysis (EFA) revealed three factors for SRQ-20 which are classified based on types of symptoms and have a total variance of 46.03%. The confirmatory factor analysis (CFA) validates EFA findings which revealed each item of SRQ-20 correlates with one another and is robust across the multi-group classification.
Conclusion
The SRQ-20 can be used to screen for mental disorders. The study result provides validated and reliable items on SRQ-20. Further study should be done using different samples and methods across Indonesia.