bluuebunny/crossref_metadata_2025_split huggingface dataset:
Pubertal gynecomastia incidence among 530,000 boys: a cross sectional population based study
Authors: Berger Ori , Hornik-Lurie Tzipi , Talisman Ran 
Published: March 2024

BackgroundAdolescent gynecomastia, a benign proliferation of male breast tissue, can lead to psychological issues during adolescence. The prevalence varies widely (4%−69%). The incidence peaks are during neonatal, pubertal, and senescent periods. Its affect on emotional well-being necessitates understanding and occasional intervention. This study aimed to determine the incidence of gynecomastia among male adolescents aged 12–15 years.MethodsA retrospective cross-sectional study utilized the Clalit Health Care Services database (2008–2021) with a population of approximately 4.5 million. Participants aged 12–15 years were included if diagnosed with gynecomastia (International classification of diseases-9 code 611.1) and having a body mass index (BMI) measurement and no obesity diagnosis (ICD9 code 278.0). Data analysis included incidence rates and associations with ethnicity, age, BMI, and socioeconomic status.Results531,686 participants included with an incidence of 1.08%. Of all participants, 478,140 had a BMI ≤ 25 with an incidence of 0.7%, and 0.25%–0.35% yearly, and 70% of gynecomastia patients were aged 13–14 years. The prevalence of gynecomastia differed between Jews (1.28%) and Arabs (0.67%), but the disparity diminished when socioeconomic status was considered.ConclusionsThis unprecedented Population study establishes a definitive rate of true pubertal gynecomastia, revealing a lower yearly incidence as compared to previous reports. The higher observed prevalence among Jewish adolescents, may be caused due to complex interactions between different influencing factors. Understanding these dynamics can aid in formulating more targeted interventions and policy strategies to address gynecomastia's affect on adolescent well-being.
Machine learning-based prediction of sertraline concentration in patients with depression through therapeutic drug monitoring
Authors: Fu Ran , Hao Xin , Yu Jing , Wang Donghan , Zhang Jinyuan , Yu Ze , Gao Fei , Zhou Chunhua 
Published: March 2024

Background: Sertraline is a commonly employed antidepressant in clinical practice. In order to control the plasma concentration of sertraline within the therapeutic window to achieve the best effect and avoid adverse reactions, a personalized model to predict sertraline concentration is necessary.Aims: This study aimed to establish a personalized medication model for patients with depression receiving sertraline based on machine learning to provide a reference for clinicians to formulate drug regimens.Methods: A total of 415 patients with 496 samples of sertraline concentration from December 2019 to July 2022 at the First Hospital of Hebei Medical University were collected as the dataset. Nine different algorithms, namely, XGBoost, LightGBM, CatBoost, random forest, GBDT, SVM, lasso regression, ANN, and TabNet, were used for modeling to compare the model abilities to predict sertraline concentration.Results: XGBoost was chosen to establish the personalized medication model with the best performance (R2 = 0.63). Five important variables, namely, sertraline dose, alanine transaminase, aspartate transaminase, uric acid, and sex, were shown to be correlated with sertraline concentration. The model prediction accuracy of sertraline concentration in the therapeutic window was 62.5%.Conclusion: In conclusion, the personalized medication model of sertraline for patients with depression based on XGBoost had good predictive ability, which provides guidance for clinicians in proposing an optimal medication regimen.
Epigenetic small-molecule screen for inhibition and reversal of acinar ductal metaplasia in mouse pancreatic organoids
Authors: Atanasova Kalina R. , Perkins Corey M. , Ratnayake Ranjala , Jiang Jinmai , Chen Qi-Yin , Schmittgen Thomas D. , Luesch Hendrik 
Published: March 2024

Background: Acinar ductal metaplasia (ADM) is among the earliest initiating events in pancreatic ductal adenocarcinoma (PDAC) development.Methods: We developed a novel morphology-based screen using organoids from wildtype and p48Cre/+ (Cre) mice to discover epigenetic modulators that inhibit or reverse pancreatic ADM more effectively than the broad-spectrum HDAC inhibitor trichostatin A (TSA).Results: Of the 144 compounds screened, nine hits and two additional natural product HDAC inhibitors were validated by dose-response analysis. The class I HDAC inhibitors apicidin and FK228, and the histone methyltransferase inhibitor chaetocin demonstrated pronounced ADM inhibition and reversal without inducing significant cytotoxicity at 1 µM. Thioester prodrug class I HDAC inhibitor largazole attenuated ADM while its disulfide homodimer was effective in both ADM inhibition and reversal. Prioritized compounds were validated for ADM reversal in p48Cre/+; LSL-KrasG12D/+ (KC) mouse organoids using both morphological and molecular endpoints. Molecular index analysis of ADM reversal in KC mouse organoids demonstrated improved activity compared to TSA. Improved prodrug stability translated into a stronger phenotypic and molecular response. RNA-sequencing indicated that angiotensinogen was the top inhibited pathway during ADM reversal.Conclusion: Our findings demonstrate a unique epigenetic mechanism and suggest that the phenotypic screen developed here may be applied to discover potential treatments for PDAC.
Bioinformatics identifies key genes and potential drugs for energy metabolism disorders in heart failure with dilated cardiomyopathy
Authors: Wang Haixia , Cai Peifeng , Yu Xiaohan , Li Shiqi , Zhu Wei , Liu Yuntao , Wang Dawei 
Published: March 2024

Background: Dysfunction in myocardial energy metabolism plays a vital role in the pathological process of Dilated Cardiomyopathy (DCM). However, the precise mechanisms remain unclear. This study aims to investigate the key molecular mechanisms of energy metabolism and potential therapeutic agents in the progression of dilated cardiomyopathy with heart failure.Methods: Gene expression profiles and clinical data for patients with dilated cardiomyopathy complicated by heart failure, as well as healthy controls, were sourced from the Gene Expression Omnibus (GEO) database. Gene sets associated with energy metabolism were downloaded from the Molecular Signatures Database (MSigDB) for subsequent analysis. Weighted Gene Co-expression Network Analysis (WGCNA) and differential expression analysis were employed to identify key modules and genes related to heart failure. Potential biological mechanisms were investigated through Gene Set Enrichment Analysis (GSEA), Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), and the construction of a competing endogenous RNA (ceRNA) network. Molecular docking simulations were then conducted to explore the binding affinity and conformation of potential therapeutic drugs with hub genes.Results: Analysis of the left ventricular tissue expression profiles revealed that, compared to healthy controls, patients with dilated cardiomyopathy exhibited 234 differentially expressed genes and 2 genes related to myocardial energy metabolism. Additionally, Benzoylaconine may serve as a potential therapeutic agent for the treatment of dilated cardiomyopathy.Conclusion: The study findings highlight the crucial role of myocardial energy metabolism in the progression of Dilated Cardiomyopathy. Notably, Benzoylaconine emerges as a potential candidate for treating Dilated Cardiomyopathy, potentially exerting its therapeutic effects by targeted modulation of myocardial energy metabolism through NRK and NT5.
Quantum image encryption algorithm based on four-dimensional chaos
Authors: Liu Xiao-Dong , Chen Qian-Hua , Zhao Run-Sheng , Liu Guang-Zhe , Guan Shuai , Wu Liang-Long , Fan Xing-Kui 
Published: March 2024

Background: Quantum image processing is rapidly developing in the field of quantum computing, and it can be successfully implemented on the Noisy Intermediate-Scale Quantum (NISQ) device. Quantum image encryption holds a pivotal position in this domain. However, the encryption process often encounters security vulnerabilities and entails complex computational complexities, thereby consuming substantial quantum resources. To address this, the present study proposes a quantum image encryption algorithm based on four-dimensional chaos.Methods: The classical image is first encoded into quantum information using the Generalized Quantum Image Representation (GQIR) method. Subsequently, the trajectory of the four-dimensional chaotic system is randomized, and multi-dimensional chaotic keys are generated to initially encrypt the pixel values of the image. Then, the Arnold transformation is applied to randomly encrypt the pixel positions, resulting in the encrypted image. During the decryption process, the inverse process of encryption is employed to restore the original image.Results: We simulated this process in the Python environment, and the information entropy analysis experiment showed that the information entropy of the three encrypted images reached above 7.999, so the system has good encryption. At the same time, the correlation of the pixel distribution after the encryption algorithm is weak, which proves that the control parameters of the chaotic system can effectively reduce the correlation between pixels in the image. In the final key space analysis, the key space issued by our encryption can reach $10140\gg 2128$.Conclusion: Our method is resistant to destructive attacks and can produce scrambled images with higher encryption and usability. This algorithm solves the problems of general encryption algorithms such as periodicity, small key space, and vulnerability to statistical analysis, and proposes a reliable and effective encryption scheme. By making full use of the characteristics of Arnold transformation permutation, ergodicity and the randomness of the four-dimensional chaotic system, the encryption algorithm uses the larger key space provided by the four-dimensional Lorenz system.
Quantifying cognitive and affective impacts of Quizlet on learning outcomes: a systematic review and comprehensive meta-analysis
Authors: Özdemir Osman , Seçkin Hümset 
Published: March 2024

BackgroundThis study synthesizes research on the impact of Quizlet on learners’ vocabulary learning achievement, retention, and attitude. Quizlet’s implementation in language education is posited to enhance the learning experience by facilitating the efficient and engaging assimilation of new linguistic concepts. The study aims to determine the extent to which Quizlet influences vocabulary learning achievement, retention, and attitude.MethodsEmploying a meta-analysis approach, this study investigates the primary research question: “Does Quizlet affect students’ vocabulary learning achievement, learning retention, and attitude?” Data were collected from various databases, identifying 94 studies, of which 23 met the inclusion criteria. The coding reliability was established at 98%, indicating a high degree of agreement among experts. A combination of random and fixed effects models was used to analyze the effect size of Quizlet on each outcome variable.ResultsQuizlet was found to have a statistically significant impact on learners’ vocabulary learning achievement, retention, and attitude. Specifically, it showed moderate effects on vocabulary learning achievement (g = 0.62) and retention (g = 0.74), and a small effect on student attitude (g = 0.37). The adoption of the fixed effects model for attitude was due to homogeneous distribution, while the random effects model was used for achievement and retention because of heterogeneous distribution.ConclusionQuizlet enhances vocabulary learning achievement, retention, and has small positive effect on learner attitude. Its integration into language education curricula is recommended to leverage these benefits. Further research is encouraged to explore the optimization of Quizlet and similar platforms for educational success.
Process and outcome of outpatient psychotherapies under clinically representative conditions in Austria: protocol and feasibility of an ongoing study
Authors: Schaffler Yvonne , Jesser Andrea , Humer Elke , Haider Katja , Pieh Christoph , Probst Thomas , Schigl Brigitte 
Published: March 2024

BackgroundWhile most studies assessing psychotherapy efficacy are randomized-controlled trials conducted in research institutions or short clinical treatments, the understanding of psychotherapy effectiveness under regular, clinically representative conditions, particularly in outpatient practice, remains limited. Representative data examining the effectiveness of psychotherapy under real-world conditions in Austria is lacking.Aims and MethodsThis paper introduces a naturalistic observational combined process- and outcome study, implementing a dual-perspective approach through standardised pre- and post-treatment questionnaires and evaluating changes in the therapeutic alliance after each session. Further, semi-structured qualitative interviews aim to illuminate the personal experiences of patients and therapists. The primary objective of the presented study is to discern whether symptoms markedly decrease following therapy. A significant secondary goal is to trace the therapeutic alliance’s evolution from both patient and therapist viewpoints, emphasising the alliance-outcome association and gender dynamics within the pairs. This paper discusses the project’s feasibility after three years and shares key insights.DiscussionRecruitment for this study has posed substantial challenges due to psychotherapists’ concerns regarding data protection, extensive documentation, and philosophical reservations about the study design. Consequently, we recruited fewer participants than initially planned. Despite these hurdles, qualitative data collection has shown notable success. Given psychotherapists’ busy schedules and reluctance to participate, more potent external incentives or a legal obligation may be necessary to encourage participation in future studies.
Evidence-based long term interventions targeting acute mental health presentations for children and adolescents: systematic review
Authors: Gerstl Brigitte , Ahinkorah Bright Opoku , Nguyen Thomas P. , John James Rufus , Hawker Patrick , Winata Teresa , Brice Febe , Bowden Michael , Eapen Valsamma 
Published: March 2024

BackgroundLong term intervention services have proven to be effective in improving mental health (MH) outcomes and the quality of life for children and young people (CYP).AimTo synthesize evidence on the effectiveness of long-term interventions in improving MH outcomes for CYP, 0-17 years, presenting with MH conditions.MethodsA systematic search was carried out and the methodological quality of included long term MH intervention studies were assessed. Six databases were searched for peer-reviewed articles between January 2000 and September 2022.ResultsWe found 30 studies that reported on the effectiveness of a range of long-term MH interventions in the form of (i) group therapy, (ii) multisystemic behavior therapy, (iii) general services, (iv) integrated services, (v) psychotherapy, (vi) intensive intervention services, (vii) comprehensive collaborative care, (viii) parent training, and (ix) home outreach service. Among the included studies, seven were rated as high level of evidence based on the National Health and Medical Research Council (NHMRC) levels of evidence hierarchy scale and seven were of moderate quality evidence. Others were rated as lower-quality evidence. Among the studies providing high quality evidence, most were reported for group therapy, general services, and psychotherapy studies demonstrating beneficial effects.ConclusionThis systematic review provides evidence to demonstrate the benefits of a range of long-term interventions, in a range of settings, can be effective in improving MH outcomes for CYP and their families.Systematic review registrationhttps://www.crd.york.ac.uk/prospero/, identifier CRD42022323324.
Association of altitude and frailty in Chinese older adults: using a cumulative frailty index model
Authors: Dong Yongfei , Ma Hongmei , Sun Hao , Li Yuemei , Li Xiaofang , Pan Shiqin , Li Caixia , Liu Songbai , Tang Zaixiang , Li Lirong 
Published: March 2024

ObjectiveThe population is aging exponentially and the resulting frailty is becoming increasingly evident. We aimed to explore the association between altitude and frailty, and to identify associated factors for frailty.MethodsThis is a community-based cross-sectional survey. 1,298 participants aged ≥60 years from three different altitudes were included in the study. To quantify frailty, we constructed a frailty index (FI) and a frailty score (FS). The FI was divided into non-frailty, prefrailty, and frailty. The Odds Ratios and confidence intervals (ORs, 95%CIs) were used to evaluate the association between altitude and FI and FS in multivariate ordinal logistic regression and linear regression.ResultsThere were 560 (53.1%) participants in the prefrailty and 488 (37.6%) in the frailty group. The FS increased with higher altitude (P for trend &lt;0.001). Multivariate ordinal logistic regression analysis revealed an association between altitude and frailty, OR = 1.91 (95% CI: 1.38–2.64) in mid-high altitude and 2.49 (95% CI:1.40–4.45) in high altitude. The same trend of association was found in the univariate analysis. The FS increased by 1.69 (95% CI: 0.78–2.60) at mid-high altitude and 3.24 (95%CI:1.66–4.81) at high altitude compared to medium altitude.ConclusionThe study indicates that high altitude exposure is an associated factor for frailty in older adults. This association become stronger with higher altitudes. As a result, it is essential to conduct early frailty screening for residents living at high altitudes.
Effects of household vectors on child health and its determinants in southwest, Ethiopia correspondence analysis
Authors: Alemayehu Bezuayehu , Mekonnen Besufekad , Addisu Abebaw , Asres Abyot 
Published: March 2024

BackgroundHousehold vectors transmit pathogens from one child to another. This study aimed to investigate the prevalence and determinants of household vectors on child health.MethodsA community-based cross-sectional study design was conducted, during which a total of 846 household data were collected using a pretested questionnaire and simple random sampling technique. The data was entered into EpiData3.4 and then exported to Stata 14 software for analysis. A multivariable logistic regression analysis was conducted to identify significant factors associated with household vectors that contribute child health problems. The correspondence analysis was used to determine statistically significant effects or associations between household vectors and child health problems, that was explained by the percentage of variance.ResultsThis study revealed that the prevalence of household vector effects among children was 35.5% suchas itching, allergies, nuisances and aesthetically displeasing factors. Households with no formal education were significantly 36% less likely to be affected compared to their counterparts (AOR 0.64, 95% CI 0.41, 0.99). Housewives are significantly 2.21 times more likely to be bexposed to household vectors compared to government workers (AOR 2.21, 95% CI 1.23, 3.70). Caregivers who had limited awareness of household vectors were 98.6% less likely to be affected compared to their counterparts (AOR 0.014; 95% CI 0.01–0.04). Similarly, children from households that consumed less than 20 liters of water per individual were 1.45 times more likely to be at risk compared to children from households that consumed more water (AOR 1.45, 95% CI 1.02, 2.07). The infestations of household vectors were found to be statistically significant and were associated with the occurrence of child health problems. This significant association accounted for 86.8 percent of the explained variance.ConclusionAddressing the high burden of household vectors on child health requires interventions that target informal education, limited access to information, and inadequate access to safe water. Implementing effective vector control measures is crucial to reduce the incidence of vector-borne diseases among children.
Cervical cancer incidence, mortality, and burden in China: a time-trend analysis and comparison with England and India based on the global burden of disease study 2019
Authors: Wu Siyu , Jiao Jun , Yue Xiaoyu , Wang Yaping 
Published: March 2024

BackgroundCervical cancer is the fourth highest incidence of malignancy in the world and a common cause of cancer death in women. We assessed the trends of incidence and mortality and disability-adjusted life year (DALY) in China, England and India from 1990 to 2030.MethodData were obtained from the Global Burden of Disease (GBD) database. We collected the number and rate of incidence, death and DALY from 1990 to 2019 and calculated the estimated annual percentage change (EAPC). Further analysis was carried out by ages and years. We also collected attributable risk factors to cervical cancer. Finally, we utilized the Bayesian Age-Period-Cohort (BAPC) model to forecast trends in the rate of age-standardized incidence (ASIR) and age-standardized death (ASDR) the for the next decade.ResultGlobally, the incidence of cervical cancer cases increased from 335,641.56 in 1990 to 565,540.89 in 2019. In 2019, the ASIR and ASDR of cervical cancer were higher than those of India but lower than those of England. Furthermore, unsafe sex and smoking emerge as prominent risk factors for cervical cancer. Over the next decade, ASIR and ASDR are expected to decline in China and England, while India’s ASIR is still on an upward trend and ASDR is on a downward trend.ConclusionThe epidemiological data of cervical cancer in these three countries reflects the influence of different stages of development and healthcare systems. Trends over the next decade suggest that China and India still face a huge burden of cervical cancer. When England has made significant progress, China and India need to take more measures to improve the prevention and control of cervical cancer.