bluuebunny/crossref_metadata_2025_split huggingface dataset:
MicroRNA-877-5p promotes osteoblast differentiation by targeting EIF4G2 expression
Authors: Shen YingChao , Zhang Yang , Wang Qiang , Jiang Bo , Jiang XiaoWei , Luo Bin 
Published: February 2024

AbstractStimulating bone formation potentially suggests therapeutics for orthopedic diseases including osteoporosis and osteoarthritis. Osteoblasts are key to bone remodeling because they act as the only bone-forming cells. miR-877-5p has a chondrocyte-improving function in osteoarthritis, but its effect on osteoblast differentiation is unknown. Here, miR-877-5p-mediated osteoblast differentiation was studied. Real-time reverse transcriptase-polymerase chain reaction was performed to measure miR-877-5p expression during the osteogenic differentiation of MC3T3-E1 cells. Osteoblast markers, including alkaline phosphatase (ALP), collagen type I a1 chain, and osteopontin, were measured and detected by alizarin red staining and ALP staining. Potential targets of miR-877-5p were predicted from three different algorithms: starBase (http://starbase.sysu.edu.cn/), PITA (http://genie.weizmann.ac.il/pubs/mir07/mir07_data.html), and miRanda (http://www.microrna.org/microrna/home.do). It was further verified by dual luciferase reporter gene assay. The experimental results found that miR-877-5p was upregulated during the osteogenic differentiation of MC3T3-E1 cells. Overexpression of miR-877-5p promoted osteogenic differentiation, which was characterized by increased cell mineralization, ALP activity, and osteogenesis-related gene expression. Knockdown of miR-877-5p produced the opposite result. Dual luciferase reporter gene assay showed that miR-877-5p directly targeted eukaryotic translation initiation factor 4γ2 (EIF4G2). Overexpression of EIF4G2 inhibited osteogenic differentiation and reversed the promoting effect of overexpression of miR-135-5p on osteogenic differentiation. These results indicate that miR-877-5p might have a therapeutic application related to its promotion of bone formation through targeting EIF4G2.
Defining usual care comparators when designing pragmatic trials of complex health interventions: a methodology review
Authors: Turner Katrina M. , Huntley Alyson , Yardley Tom , Dawson Sarah , Dawson Shoba 
Published: February 2024

Abstract
Background
Pragmatic trials evaluating complex health interventions often compare them to usual care. This comparator should resemble care as provided in everyday practice. However, usual care can differ for the same condition, between patients and practitioners, across clinical sites and over time. Heterogeneity within a usual care arm can raise methodological and ethical issues. To address these it may be necessary to standardise what usual care entails, although doing so may compromise a trial’s external validity. Currently, there is no guidance detailing how researchers should decide the content of their usual care comparators. We conducted a methodology review to summarise current thinking about what should inform this decision.

Methods
MEDLINE, Embase, CINAHL and PsycINFO were searched from inception to January 2022. Articles and book chapters that discussed how to identify or develop usual care comparators were included. Experts in the field were also contacted. Reference lists and forward citation searches of included articles were screened. Data were analysed using a narrative synthesis approach.

Results
One thousand nine hundred thirty records were identified, 1611 titles and abstracts screened, 112 full texts screened, and 16 articles included in the review. Results indicated that the content of a usual care comparator should be informed by the aims of the trial, existing care practices, clinical guidelines, and characteristics of the target population. Its content should also be driven by the trial’s requirements to protect participants, inform practice, and be methodologically robust, efficient, feasible and acceptable to stakeholders. When deciding the content of usual care, researchers will need to gather information about these drivers, balance tensions that might occur when responding to different trial objectives, and decide how usual care will be described and monitored in the trial.

Discussion
When deciding the content of a usual care arm, researchers need to understand the context in which a trial will be implemented and what the trial needs to achieve to address its aim and remain ethical. This is a complex decision-making process and trade-offs might need to be made. It also requires research and engagement with stakeholders, and therefore time and funding during the trial’s design phase.

Methodology review registration
PROSPERO CRD42022307324.
Novel quinazolines bearing 1,3,4-thiadiazole-aryl urea derivative as anticancer agents: design, synthesis, molecular docking, DFT and bioactivity evaluations
Authors: Masoudinia Sara , Samadizadeh Marjaneh , Safavi Maliheh , Bijanzadeh Hamid Reza , Foroumadi Alireza 
Published: February 2024

AbstractA novel series of 1-(5-((6-nitroquinazoline-4-yl)thio)-1,3,4-thiadiazol-2-yl)-3-phenylurea derivatives 8 were designed and synthesized to evaluate their cytotoxic potencies. The structures of these obtained compounds were thoroughly characterized by IR, 1H, and 13C NMR, MASS spectroscopy and elemental analysis methods. Additionally, their in vitro anticancer activities were investigated using the MTT assay against A549 (human lung cancer), MDA-MB231 (human triple-negative breast cancer), and MCF7 (human hormone-dependent breast cancer). Etoposide was used as a reference marketed drug for comparison. Among the compounds tested, compounds 8b and 8c demonstrated acceptable antiproliferative activity, particularly against MCF7 cells. Considering the potential VEGFR-2 inhibitor potency of these compounds, a molecular docking study was performed for the most potent compound, 8c, to determine its probable interactions. Furthermore, computational investigations, including molecular dynamics, frontier molecular orbital analysis, Fukui reactivity descriptor, electrostatic potential surface, and in silico ADME evaluation for all compounds were performed to illustrate the structure–activity relationship (SAR).
Evaluating the safety profile of calcineurin inhibitors: cancer risk in patients with systemic lupus erythematosus from the LUNA registry—a historical cohort study
Authors: Ichinose Kunihiro , Sato Shuntaro , Igawa Takashi , Okamoto Momoko , Takatani Ayuko , Endo Yushiro , Tsuji Sosuke , Shimizu Toshimasa , Sumiyoshi Remi , Koga Tomohiro , Kawashiri Shin-ya , Iwamoto Naoki , Tamai Mami , Nakamura Hideki , Origuchi Tomoki , Yajima Nobuyuki , Sada Ken-Ei , Miyawaki Yoshia , Yoshimi Ryusuke , Shimojima Yasuhiro , Ohno Shigeru , Kajiyama Hiroshi , Sato Shuzo , Fujiwara Michio , Kawakami Atsushi 
Published: February 2024

Abstract
Background
Previous studies have shown conflicting evidence regarding the incidence of cancer in patients with systemic lupus erythematosus (SLE) compared with that in healthy individuals. Calcineurin inhibitors (CNIs) such as cyclosporine and tacrolimus have been widely used to treat SLE; however, their effects on cancer risk remain unclear. We aimed to investigate the incidence of cancer in patients with SLE and determine the potential association between CNI use and cancer risk.

Methods
The standardized incidence ratio (SIR) of cancer among patients with lupus in the Lupus Registry of Nationwide Institutions (LUNA) was calculated based on the age-standardized incidence rate of cancer reported by Japan’s Ministry of Health, Labour and Welfare. We also examined the association between CNI exposure and cancer risk, while considering potential confounding factors. The analysis accounted for confounding variables such as age, sex, smoking history, maximum glucocorticoid dose, treatment history with cyclophosphamide, ongoing hydroxychloroquine, Systemic Lupus International Collaboration Clinics/American College of Rheumatology Damage Index (SDI) value (excluding cancer occurrence), comorbidity of diabetes mellitus, and smoking history.

Results
The study included 704 patients with SLE (625 females; 88.8%) with a median age of 44 years [interquartile range (IQR) = 34–55] years. The median past maximum glucocorticoid dose was 40 mg/day [IQR = 30–60 mg/day], and the SDI at registration was 1 [IQR = 0–2]. Among the patients, 246 (35.1%) had smoking histories, and 38 (5.4%) experienced cancer complications. Gynecological malignancies accounted for 63.2% of all cancers. The SIR of cancer in the LUNA cohort was 1.08 (95% confidence interval [CI] = 0.74–1.43). No statistically significant risks of cancer were found in relation to CNI treatment history; the odds ratio using multiple logistic regression was 1.12 (95% CI = 0.42–3.00), the risk ratio using standardization was 1.18 (95% CI = 0.47–2.16), and the risk ratio using inverse probability weighting was 1.8 (95% CI = 0.41–4.66).

Conclusions
The incidence of cancer in patients with SLE in the LUNA cohort did not significantly differ from that in the general population. These findings suggest that CNI treatment in this cohort did not pose a risk factor for cancer development.
Detection of gene mutation in the prognosis of a patient with arrhythmogenic right ventricular cardiomyopathy: a case report
Authors: Phan Dinh Phong , Tran Tuan Viet , Le Vo Kien , Nguyen Tuan Viet 
Published: February 2024

Abstract
Background
Arrhythmogenic right ventricular cardiomyopathy (ARVC), or more recently known as arrhythmogenic cardiomyopathy (ACM), is an heritable disorder of the myocardium characterized by progressive fibrofatty replacement the heart muscle and risk of ventricular arrhythmias and sudden cardiac death (SCD). We report a case study to demonstrate the role of gene mutation detection in risk stratification for primary prevention of SCD in a young patient diagnosed with ARVC.

Case presentation
A 15-year-old Asian (Vietnamese) male patient with no history of documented tachyarrhythmia or syncope and a family history of potential SCD was admitted due to palpitations. Clinical findings and work-up including cardiac magnetic resonance imaging (MRI) were highly suggestive of ARVC. Gene sequencing was performed for SCD risk stratification, during which PKP2 gene mutation was found. Based on the individualized risk stratification, an ICD was implanted for primary prevention of SCD. At 6 months post ICD implantation, the device detected and successfully delivered an appropriate shock to terminate an episode of potentially fatal ventricular arrhythmia. ICD implantation was therefore proven to be appropriate in this patient.

Conclusions
While gene mutations are known to be an important factor in the diagnosis of ARVC according to the 2010 Task Force Criteria and recent clinical guidelines, their role in risk stratification of SCD remains controversial. Our case demonstrated that when used with other clinical factors and family history, this information could be helpful in identifying appropriate indication for ICD implantation.
A systematic review and meta-analysis of balance training in patients with chronic ankle instability
Authors: Guo Yiwei , Cheng Tianyue , Yang Zihao , Huang Yonglei , Li Ming , Wang Taoli 
Published: February 2024

Abstract
Background
Chronic ankle instability (CAI) is a common yet serious problem for elder patients. This meta-analysis aimed to evaluate the effects of balance training for CAI, to provide evidence for the clinical treatment, and care of CAI patients.

Methods
Two investigators searched PubMed, EMBASE, Science Direct, Web of Science, Cochrane Library, China National Knowledge Infrastructure, Wanfang, and Weipu Databases up to May 20, 2023, for randomized controlled trials (RCTs) on the effects of balance training for CAI. The mean difference (MD) with 95% confidence intervals (95%CIs) was calculated for each outcome with a fixed or random effect model. Review Manager 5.3 software was used for meta-analysis.

Results
Nine RCTs involving 341 patients were included. Meta-analysis results showed that compared with blank controls, balanced training treatment of CAI could significantly improve the score of CAI [MD = 3.95, 95% CI (3.26, 4.64), P < 0.00001], SEBT-PM [MD = 4.94, 95% CI (1.88, 8.00), P = 0.002], SEBT-PL [MD = 5.19, 95% CI (1.57, 8.81), P = 0.005], and FAAM Sports [MD = 17.74, 95% CI (14.36, 21.11), P < 0.00001]. Compared with strength training, balance training treatment of CAI improved the score of CAIT [MD = 2.36, 95% CI (0.29, 4.44), P = 0.03], FAAM-ADL [MD = 4.06, 95% CI (1.30, 6.83), P = 0.004].

Conclusion
The analysis outcomes indicate that balance training enhances daily activity capability, motor function, and dynamic balance to different extents. Additionally, when comparing the results of balance training and strength training, no significant difference was observed between the two methods in improving the dynamic stability of CAI patients. However, it is noteworthy that balance training exhibits a more pronounced impact on enhancing functional scale scores.
Decreased TLR7 expression was associated with airway eosinophilic inflammation and lung function in asthma: evidence from machine learning approaches and experimental validation
Authors: Yan Kemin , Liang Yuxia 
Published: February 2024

AbstractBackgroundAsthma is a global public health concern. The underlying pathogenetic mechanisms of asthma were poorly understood. This study aims to explore potential biomarkers associated with asthma and analyze the pathological role of immune cell infiltration in the disease.MethodsThe gene expression profiles of induced sputum were obtained from Gene Expression Omnibus datasets (GSE76262 and GSE137268) and were combined for analysis. Toll-like receptor 7 (TLR7) was identified as the core gene by the intersection of two different machine learning algorithms, namely, least absolute shrinkage and selector operation (LASSO) regression and support vector machine-recursive feature elimination (SVM-RFE), and the top 10 core networks based on Cytohubba. CIBERSORT algorithm was used to analyze the difference of immune cell infiltration between asthma and healthy control groups. Finally, the expression level of TLR7 was validated in induced sputum samples of patients with asthma.ResultsA total of 320 differential expression genes between the asthma and healthy control groups were screened, including 184 upregulated genes and 136 downregulated genes. TLR7 was identified as the core gene after combining the results of LASSO regression, SVM-RFE algorithm, and top 10 hub genes. Significant differences were observed in the distribution of 13 out of 22 infiltrating immune cells in asthma. TLR7 was found to be closely related to the level of several infiltrating immune cells. TLR7 mRNA levels were downregulated in asthmatic patients compared with healthy controls (p = 0.0049). The area under the curve of TLR7 for the diagnosis of asthma was 0.7674 (95% CI 0.631–0.904,p = 0.006). Moreover, TLR7 mRNA levels were negatively correlated with exhaled nitric oxide fraction (r = − 0.3268,p = 0.0347) and the percentage of peripheral blood eosinophils (%) (r = − 0.3472,p = 0.041), and positively correlated with forced expiratory volume in the first second (FEV1) (% predicted) (r = 0.3960,p = 0.0071) and FEV1/forced vital capacity (r = 0.3213,p = 0.0314) in asthmatic patients.ConclusionsDecreased TLR7 in the induced sputum of eosinophilic asthmatic patients was involved in immune cell infiltration and airway inflammation, which may serve as a new biomarker for the diagnosis of eosinophilic asthma.
Characterization of T-Cell receptor repertoire in immunoglobulin a nephropathy
Authors: Ho Szu-Ying , Kao Chih-Chin , Chang Che-Mai , Chou Yi-Chien , Luo Wei-Tzu , Chou Wan-Hsuan , Tsai I-Lin , Wu Mai-Szu , Chang Wei-Chiao 
Published: February 2024

AbstractImmunoglobulin A nephropathy (IgAN) is an autoimmune disease characterized by abnormal IgA deposition in glomerulus. Current diagnosis of IgAN still depends on renal biopsy, an invasive method that might increase the risk of clinical outcomes. Therefore, we aimed to explore the characteristics of T cell repertoire in IgAN from peripheral blood samples for identifying innovative diagnostic biomarkers. Herein, we included 8 IgAN patients, 25 non-IgAN patients, and 10 healthy controls in the study. A high-throughput immune repertoire sequencing was conducted to investigate the T-cell receptor beta-chain (TCRβ) repertoire of peripheral blood. Characteristics of TCRβ repertoire were assessed for these three distinct groups. A reduced TCRβ repertoire diversity was observed in IgAN patients compared to non-IgAN and healthy individuals. A skewed distribution toward shorter TCRβ complementarity determining region (CDR3) length was found in non-IgAN relative to IgAN patients. In addition, the differences in usages of five TRBV genes (TRBV5-4, TRBV6-4, TRBV12-1, TRBV16, and TRBV21-1) were identified between IgAN, non-IgAN, and healthy subjects. Of note, the TRBV6-4 gene, which is associated with mucosal-associated invariant T (MAIT) cells, exhibited higher usage in IgAN patients, suggesting potential importance of MAIT cells in IgAN. In short, our findings supported TCR repertoire characteristics as potential biomarkers for IgAN diagnosis.
Characteristics of departments with high-use of active learning in introductory STEM courses: implications for departmental transformation
Authors: Lau Alexandra C. , Henderson Charles , Stains Marilyne , Dancy Melissa , Merino Christian , Apkarian Naneh , Raker Jeffrey R. , Johnson Estrella 
Published: February 2024

AbstractBackgroundIt is well established in the literature that active learning instruction in introductory STEM courses results in many desired student outcomes. Yet, regular use of high-quality active learning is not the norm in many STEM departments. Using results of a national survey, we identified 16 departments where multiple instructors reported using high levels of active learning in their introductory chemistry, mathematics, or physics courses. We conducted interviews with 27 instructors in these 16 departments to better understand the characteristics of such departments.ResultsUsing grounded theory methodology, we developed a model that highlights relevant characteristics of departments with high use of active learning instruction in their introductory courses. According to this model, there are four main, interconnected characteristics of such departments: motivated people, knowledge about active learning, opportunities, and cultures and structures that support active learning. These departments have one or more people who are motivated to promote the use of active learning. These motivated people have knowledge about active learning as well as access to opportunities to promote the use of active learning. Finally, these departments have cultures and structures that support the use of active learning. In these departments, there is a positive feedback loop that works iteratively over time, where motivated people shape cultures/structures and these cultures/structures in turn increase the number and level of commitment of the motivated people. A second positive feedback loop was found between the positive outcome of using active learning instruction and the strengthening of cultures/structures supportive of active learning.ConclusionsAccording to the model, there are two main take-away messages for those interested in promoting the use of active learning. The first is that all four components of the model are important. A weak or missing component may limit the desired outcome. The second is that desired outcomes are obtained and strengthened over time through two positive feedback loops. Thus, there is a temporal aspect to change. In all of the departments that were part of our study, the changes took at minimum several years to enact. While our model was developed using only high-use of active learning departments and future work is needed to develop the model into a full change theory, our results do suggest that change efforts may be made more effective by increasing the robustness of the four components and the connections between them.
Landslide susceptibility assessment of South Korea using stacking ensemble machine learning
Authors: Lee Seung-Min , Lee Seung-Jae 
Published: February 2024

Abstract
Background
Landslide susceptibility assessment (LSA) is a crucial indicator of landslide hazards, and its accuracy is improving with the development of artificial intelligence (AI) technology. However, the AI algorithms are inconsistent across regions and strongly dependent on input variables. Additionally, LSA must include historical data, which often restricts the assessment to the local scale and single landslide events.

Methods
In this study, we performed an LSA for the entirety of South Korea. A total of 30 input variables were constructed, consisting of 9 variables from past climate model data MK-PRISM, 12 topographical factors, and 9 environmental factors. Sixteen machine learning algorithms were used as basic classifiers, and a stacking ensemble was used on the four algorithms with the highest area under the curve (AUC). Additionally, a separate assessment model was established for areas with a risk of landslides affecting areas larger than 1 ha.

Results
The highest-performing classifier was CatBoost, with an AUC of ~ 0.89 for both assessments. Among the input variables, distance of road, daily maximum precipitation, digital elevation model, and soil depth were the most influential. In all landslide events, CatBoost, lightGBM, XGBoost, and Random Forest had the highest AUC in descending order; in large landslide events, the order was CatBoost, XGBoost, Extra Tree, and lightGBM. The stacking ensemble enabled the construction of two landslide susceptibility maps.

Conclusions
Our findings provide a statistical method for constructing a high-resolution (30 m) landslide susceptibility map on a country scale using diverse natural factors, including past climate data.
Classification of geogrid reinforcement in aggregate using machine learning techniques
Authors: Aregbesola Samuel Olamide , Byun Yong-Hoon 
Published: February 2024

AbstractThe present study proposes a novel ML methodology for differentiating between unstabilized aggregate specimens and those stabilized with triangular and rectangular aperture geogrids. This study utilizes the compiled experimental results obtained from stabilized and unstabilized specimens under repeated loading into a balanced, moderate-sized database. The efficacy of five ML models, including tree-ensemble and single-learning algorithms, in accurately identifying each specimen class was explored. Shapley’s additive explanation was used to understand the intricacies of the models and determine global feature importance ranking of the input variables. All the models could identify the unstabilized specimen with an accuracy of at least 0.9. The tree-ensemble models outperformed the single-learning models when all three classes (unstabilized specimens and specimens stabilized by triangular and rectangular aperture geogrids) were considered, with the light gradient boosting machine showing the best performance—an accuracy of 0.94 and an area under the curve score of 0.98. According to Shapley’s additive explanation, the resilient modulus and confining pressure were identified as the most important features across all models. Therefore, the proposed ML methodology may be effectively used to determine the type and presence of geogrid reinforcement in aggregates, based on a few aggregate material properties and performance under repeated loading.