bluuebunny/crossref_metadata_2025_split huggingface dataset:
Using administrative healthcare data to evaluate drug repurposing opportunities for cancer: the possibility of using beta-blockers to treat breast cancer
Authors: Tan George S. Q. , Botteri Edoardo , Wood Stephen , Sloan Erica K. , Ilomäki Jenni 
Published: August 2023

Introduction: Cancer registries and hospital electronic medical records are commonly used to investigate drug repurposing candidates for cancer. However, administrative data are often more accessible than data from cancer registries and medical records. Therefore, we evaluated if administrative data could be used to evaluate drug repurposing for cancer by conducting an example study on the association between beta-blocker use and breast cancer mortality.Methods: A retrospective cohort study of women aged ≥50 years with incident breast cancer was conducted using a linked dataset with statewide hospital admission data and nationwide medication claims data. Women receiving beta blockers and first-line anti-hypertensives prior to and at diagnosis were compared. Breast cancer molecular subtypes and metastasis status were inferred by algorithms from commonly prescribed breast cancer antineoplastics and hospitalization diagnosis codes, respectively. Subdistribution hazard ratios (sHR) and corresponding 95% confidence intervals (CIs) for breast cancer mortality were estimated using Fine and Gray’s competing risk models adjusted for age, Charlson comorbidity index, congestive heart failure, myocardial infraction, molecular subtype, presence of metastasis at diagnosis, and breast cancer surgery.Results: 2,758 women were hospitalized for incident breast cancer. 604 received beta-blockers and 1,387 received first-line antihypertensives. In total, 154 breast cancer deaths were identified over a median follow-up time of 2.7 years. We found no significant association between use of any beta-blocker and breast-cancer mortality (sHR 0.86, 95%CI 0.58–1.28), or when stratified by beta-blocker type (non-selective, sHR 0.42, 95%CI 0.14–1.25; selective, sHR 0.95, 95%CI 0.63–1.43). Results were not significant when stratified by molecular subtypes (e.g., triple negative breast cancer (TNBC), any beta blocker, sHR 0.16, 95%CI 0.02–1.51).Discussion: It is possible to use administrative data to explore drug repurposing opportunities. Although non-significant, an indication of an association was found for the TNBC subtype, which aligns with previous studies using registry data. Future studies with larger sample size, longer follow-up are required to confirm the association, and linkage to clinical data sources are required to validate our methodologies.
Establishment and interpretation of the gamma pass rate prediction model based on radiomics for different intensity-modulated radiotherapy techniques in the pelvis
Authors: Ni Qianxi , Zhu Jun , Chen Luqiao , Tan Jianfeng , Pang Jinmeng , Sun Xiangshang , Yang Xiaohua 
Published: August 2023

Backgroundand objectives: Implementation of patient-specific quality assurance (PSQA) is a crucial aspect of precise radiotherapy. Various machine learning-based models have showed potential as virtual quality assurance tools, being capable of accurately predicting the dose verification results of fixed-beam intensity-modulated radiation therapy (IMRT) or volumetric modulated arc therapy (VMAT) plans, thereby ensuring safe and efficient treatment for patients. However, there has been no research yet that simultaneously integrates different IMRT techniques to predict the gamma pass rate (GPR) and explain the model.Methods: Retrospective analysis of the 3D dosimetric verification results based on measurements with gamma pass rate criteria of 3%/2 mm and 10% dose threshold of 409 pelvic IMRT and VMAT plans was carried out. Radiomics features were extracted from the dose files, from which the XGBoost algorithm based on SHapley Additive exPlanations (SHAP) values was used to select the optimal feature subset as the input for the prediction model. The study employed four different machine learning algorithms, namely, random forest (RF), adaptive boosting (AdaBoost), extreme gradient boosting (XGBoost), and light gradient boosting machine (LightGBM), to construct predictive models. Sensitivity, specificity, F1 score, and AUC value were calculated to evaluate the classification performance of these models. The SHAP values were utilized to perform a related interpretive analysis on the best performing model.Results: The sensitivities and specificities of the RF, AdaBoost, XGBoost, and LightGBM models were 0.96, 0.82, 0.93, and 0.89, and 0.38, 0.54, 0.62, and 0.62, respectively. The F1 scores and area under the curve (AUC) values were 0.86, 0.81, 0.88, and 0.86, and 0.81, 0.77, 0.85, and 0.83, respectively. The explanation of the model output based on SHAP values can provide a reference basis for medical physicists when adjusting the plan, thereby improving the efficiency and quality of treatment plans.Conclusion: It is feasible to use a machine learning method based on radiomics to establish a gamma pass rate classification prediction model for IMRT and VMAT plans in the pelvis. The XGBoost model performs better in classification than the other three tree-based ensemble models, and global explanations and single-sample explanations of the model output through SHAP values may offer reference for medical physicists to provide high-quality plans, promoting the clinical application and implementation of GPR prediction models, and providing safe and efficient personalized QA management for patients.
Post-feeding transcriptomics reveals essential genes expressed in the midgut of the desert locust
Authors: Van Lommel Joachim , Holtof Michiel , Tilleman Laurentijn , Cools Dorien , Vansteenkiste Seppe , Polgun Daria , Verdonck Rik , Van Nieuwerburgh Filip , Vanden Broeck Jozef 
Published: August 2023

The digestive tract constitutes an important interface between an animal’s internal and external environment. In insects, available gut transcriptome studies are mostly exploratory or look at changes upon infection or upon exposure to xenobiotics, mainly performed in species belonging to holometabolan orders, such as Diptera, Lepidoptera or Coleoptera. By contrast, studies focusing on gene expression changes after food uptake and during digestion are underrepresented. We have therefore compared the gene expression profiles in the midgut of the desert locust, Schistocerca gregaria, between three different time points after feeding, i.e., 24 h (no active digestion), 10 min (the initial stage of feeding), and 2 h (active food digestion). The observed gene expression profiles were consistent with the polyphagous herbivorous lifestyle of this hemimetabolan (orthopteran) species. Our study reveals the upregulation of 576 genes 2 h post-feeding. These are mostly predicted to be associated with digestive physiology, such as genes encoding putative digestive enzymes or nutrient transporters, as well as genes putatively involved in immunity or in xenobiotic metabolism. The 10 min time point represented an intermediate condition, suggesting that the S. gregaria midgut can react rapidly at the transcriptional level to the presence of food. Additionally, our study demonstrated the critical importance of two transcripts that exhibited a significant upregulation 2 h post-feeding: the vacuolar-type H(+)-ATPase and the sterol transporter Niemann-Pick 1b protein, which upon RNAi-induced knockdown resulted in a marked increase in mortality. Their vital role and accessibility via the midgut lumen may make the encoded proteins promising insecticidal target candidates, considering that the desert locust is infamous for its huge migrating swarms that can devastate the agricultural production in large areas of Northern Africa, the Middle East, and South Asia. In conclusion, the transcriptome datasets presented here will provide a useful and promising resource for studying the midgut physiology of S. gregaria, a socio-economically important pest species.
Dispositional mindfulness and BIS/BAS up-close: can the self-regulation of people be seen in the eyes?
Authors: Valachová Michaela , Lisá Elena 
Published: August 2023

IntroductionPigmentation in animal models is related to behavioral regulation and development, suggesting that both may belong to the same biological system. However, such models are poorly documented in humans. The current study explored personality and group differences in self-regulation among healthy subjects and their specific eye structures (contraction furrows and pigment spots). Three objectives were proposed: to analyze statistical differences in dispositional mindfulness (DM), behavioral inhibition system (BIS), and behavioral approach system (BAS) among subjects with a specific iris type of contraction furrows and pigment spots.MethodsThe study sample consisted of 194 university students. One month after taking photographs of their eyes, the students completed the online scales of DM, BIS, and BAS.ResultsDM was negatively related to pigment spots (rs = −0.193; p &lt; 0.01). Cluster analysis of the iris structures converged at a four-cluster solution. The cluster types 2 (absence of pigment spots and contraction furrows extending 8/10 of iris circle or more) and 3 (one or more pigment spots and contraction furrows extending 8/10 of iris circle or more) significantly differed in DM with a small effect size (F = 3.37; p = 0.021; η2 = 0.051). Participants with contraction furrows (8/10 or more circle extent) and without pigment spots had a significantly higher DM than those with pigment spots. No significant differences existed among the iris types in BIS/BAS.DiscussionFuture research directions are suggested.
COVID-19 symptoms, internet information seeking, and stigma influence post-lockdown health anxiety
Authors: Li Qian , Yang Xue , Wang Xin , Zhang Han , Ding Ningning , Zhao Wenqian , Tian Wenwen , He Jiankang , Du Mingxuan , Hu Haiyan , Zhang Guohua 
Published: August 2023

BackgroundWith the lifting of Zero-COVID policies in China, rapid transmission of the virus has led to new challenges for patients’ health anxiety. This study aimed to evaluate the relationship between COVID-19 symptoms and health anxiety, as well as the mediation paths between them in individuals infected with COVID-19.MethodA cross-sectional study was conducted in December 2022, following the relaxation of anti-COVID measures in China. A validated online questionnaire was used to collect data from COVID-19 patients on the number and severity of symptoms, health anxiety, internet health information-seeking behavior (IHISB), and perceived stigma. Structural equation modeling was used to examine the mediation model in which COVID-19 symptoms would affect health anxiety via IHISB and perceived stigma.ResultsOverall, 1,132 participants (women, 67.6%) were included, with a mean (SD) age of 28.12 (10.07) years. Participants had an average of seven COVID-19 symptoms, with cough (91.3%), nasal congestion (89.1%) and fatigue (87.8%) being the most common. The number and severity of COVID-19 symptoms, IHISB, perceived stigma, and health anxiety were positively correlated with each other after adjusting for covariates (r ranging from 0.10 to 0.81, all p &lt; 0.05). IHISB (effect = 0.14, p &lt; 0.001) and perceived stigma (effect = 0.04, p &lt; 0.001) fully mediated the relationship between COVID-19 symptoms and health anxiety.ConclusionInterventions for health anxiety reduction during and after pandemics should target improving the quality of online health information, enhancing individuals’ online healthy literacy, and reducing stigma.
Construction and evaluation of hourly average indoor PM2.5 concentration prediction models based on multiple types of places
Authors: Shi Yewen , Du Zhiyuan , Zhang Jianghua , Han Fengchan , Chen Feier , Wang Duo , Liu Mengshuang , Zhang Hao , Dong Chunyang , Sui Shaofeng 
Published: August 2023

BackgroundPeople usually spend most of their time indoors, so indoor fine particulate matter (PM2.5) concentrations are crucial for refining individual PM2.5 exposure evaluation. The development of indoor PM2.5 concentration prediction models is essential for the health risk assessment of PM2.5 in epidemiological studies involving large populations.MethodsIn this study, based on the monitoring data of multiple types of places, the classical multiple linear regression (MLR) method and random forest regression (RFR) algorithm of machine learning were used to develop hourly average indoor PM2.5 concentration prediction models. Indoor PM2.5 concentration data, which included 11,712 records from five types of places, were obtained by on-site monitoring. Moreover, the potential predictor variable data were derived from outdoor monitoring stations and meteorological databases. A ten-fold cross-validation was conducted to examine the performance of all proposed models.ResultsThe final predictor variables incorporated in the MLR model were outdoor PM2.5 concentration, type of place, season, wind direction, surface wind speed, hour, precipitation, air pressure, and relative humidity. The ten-fold cross-validation results indicated that both models constructed had good predictive performance, with the determination coefficients (R2) of RFR and MLR were 72.20 and 60.35%, respectively. Generally, the RFR model had better predictive performance than the MLR model (RFR model developed using the same predictor variables as the MLR model, R2 = 71.86%). In terms of predictors, the importance results of predictor variables for both types of models suggested that outdoor PM2.5 concentration, type of place, season, hour, wind direction, and surface wind speed were the most important predictor variables.ConclusionIn this research, hourly average indoor PM2.5 concentration prediction models based on multiple types of places were developed for the first time. Both the MLR and RFR models based on easily accessible indicators displayed promising predictive performance, in which the machine learning domain RFR model outperformed the classical MLR model, and this result suggests the potential application of RFR algorithms for indoor air pollutant concentration prediction.
A New Leaf Essential Oil from Endemic Gynoxys laurifolia (Kunth) Cass. of Southern Ecuador: Chemical and Enantioselective Analyses
Authors: Gilardoni Gianluca , Lara Luis Rubén , Cumbicus Nixon , Malagón Omar 
Published: August 2023

The fresh leaves of Gynoxys laurifolia (Kunth) Cass. (Asteraceae), collected in the province of Loja (Ecuador), were submitted to steam distillation, producing an essential oil with a yield of 0.02% by weight. This volatile fraction, described here for the first time, was submitted to qualitative (GC–MS) and quantitative (GC–FID) chemical analyses, on two orthogonal columns (non-polar and polar stationary phase). A total of 90 components, corresponding to 95.9–95.0% by weight on the non-polar and polar stationary phase, respectively, were detected and quantified with at least one column. Major constituents (≥3%) were: germacrene D (18.9–18.0%), (E)-β-caryophyllene (13.2–15.0%), α-pinene (11.0–10.3%), β-pinene (4.5–4.4%), β-phellandrene (4.0–3.0%), bicyclogermacrene (4.0–3.0%), and bakkenolide A (3.2–3.4%). This essential oil was dominated by sesquiterpene hydrocarbons (about 45%), followed by monoterpene hydrocarbons (about 25–30%). This research was complemented with the enantioselective analysis of some common chiral terpenes, carried out through 2,3-diethyl-6-tert-butyldimethylsilyl-β-cyclodextrin and 2,3-diacetyl-6-tert-butyldimethylsilyl-β-cyclodextrin as stationary phase chiral selectors. As a result, (1S,5S)-(−)-β-pinene, (R)-(−)-α-phellandrene, (R)-(−)-β-phellandrene, (S)-(−)-limonene, (S)-(+)-linalyl acetate, and (S)-(−)-germacrene D were observed as enantiomerically pure compounds, whereas α-pinene, linalool, terpinene-4-ol, and α-terpineol were present as scalemic mixtures. Finally, sabinene was practically racemic. Due to plant wildness and the relatively low distillation yield, no industrial applications can be identified, in the first instance for this essential oil. The focus of the present study is therefore academic.
The relationship between Quality and Outcomes Framework scores and socioeconomic deprivation: a longitudinal study
Authors: Mann Oliver , Bracegirdle Tristan , Shantikumar Saran 
Published: August 2023

BackgroundThe Quality Outcomes Framework (QOF) is a pay incentive scheme in England designed to improve and standardise general practice. QOF attainment has been used as a proxy for primary care quality in previous research.AimTo investigate whether there is a relationship between socioeconomic deprivation and QOF attainment in primary care in England.Design & settingRetrospective longitudinal study of primary care providers in England.MethodQOF scores were obtained for individual general practices in England from between 2007–2019 and linked to practice-level Indices of Multiple Deprivation (IMD) scores derived from census data. Beta regression analyses were used to analyse the relationship with either percentage of total QOF attainment or of domain-specific attainment with multivariate analyses, adjusting for additional practice-level demographics. QOF attainment in the most affluent quintile was used as the reference group.ResultsGeneral practices in less deprived areas have consistently outperformed those in more deprived areas in terms of QOF achievement. Initially, the gap between least and most deprived practices decreased, however since 2015 there has been relatively little change in comparative performance. The magnitude of inequality was reduced after adjusting for demographic factors. Of the independent variables analysed, the proportion of patients aged >65 years (‘over 65s’) had the strongest relationship with QOF attainment.ConclusionThere remains an inequality in primary care quality by socioeconomic deprivation in England, even after accounting for demographic differences.
‘Allâme Kâdî Hıdırî ve el-Fetâvâ el-Muhammediyye Adlı Eseri
Authors: EŞİT Yusuf 
Published: August 2023

‘Allâme Kâdî Muhammed Hıdırî, İrân’da yetişen son dönem Sünnî âlimlerden biridir. 1900’lü yılların
başında dünyaya gelen Hıdırî, keskin zeka ve kuvvetli hafızasıyla Doğu medrese geleneğinin devamı olan
medreselerde kısa sürede eğitimini tamamlayıp ilmî faaliyetlere başlamıştır. İlerleyen zamanlarda ilmiyle
şöhret bulan Hıdırî, İran’ın Sünnî bölgesi olan kuzey bölgelerinde resmi olmasa da kadılık vazifesini ifa
etmiştir. Kendisi ilmî faaliyetlerinin yanında kimi zaman siyasi görevler de üstlenmiştir. Değişen yönetim
ve rejimlere tanıklık eden Hıdırî, her dönemde ilmî konumunu ve halkın nezdindeki yerini korumuştur.
Dil, tefsir, hadis ve fıkıh, gibi dinî ilimlerin yanında mantık, hendese ve astronomi ilimleri de tahsil etmiş
çok yönlü bir âlim olup Kürtçe, Arapça ve Farsça dillerinde eserler telif etmiştir. İslamî ilimlerin her alanında
derin bilgiye sahip olması hasebiyle kendisinin fıkıh, tefsir, tasavvuf alanlarında eser ve risaleleri
bulunmaktadır. Târihi meşâhiri cihân İslam, Tefsîrü’l-Kur’ân, Risâlehây-ı müteneva‘ der bâb mesâili şer‘î, Kitab-ı
der bâb-ı talakı selâse eserlerinden bazısıdır. Hıdırî, bulunduğu toplumun sorunlarına kayıtsız kalmamış din
âliminin gerektirdiği nosyonla toplumuna ışık tutmuş ve bulunduğu toplumun eğitim seviyelerinin
yükselmesi başta olmak üzere her türlü sorunlarıyla ilgilenmiştir. Onun modern kaynaklara hâkim ve
taassuptan uzak ama Sünnî mezhep içerisinde muhakkik bir âlim olduğu söylenebilir. el-Fetâvâ el-
Muhammediyye adlı eseri hem kendi ilmî derinliği hem de yaşadığı toplumun genel hatlarıyla sorunları
hakkında bizlere bilgi vermektedir. Eserde yaklaşık olarak beş y üz o n i ki soruya verdiği fetva yer
almaktadır. Fetvalar hayatın her alanına dair çok çeşitlilik gösteren bir dağılım göstermektedir. Eserde Kâdî
Hıdırî’nin başta ibadet olmak üzere günümüzde tartışılan birçok konuya dair görüşleri yer almaktadır.
Çalışmanın amacı Kâdî Hıdırî’nin hayatı ve fetvaları üzerinde genel bir tasvir çizmektir. Aynı zamanda
çalışma, İran’ın Sünnî bölgelerindeki ilmî birikime dikkat çekmesi açısından da önem arz etmektedir.
Savvadumalaiyil Pallavar Kala Nadukal
Authors: Savita K 
Published: August 2023

World monster history can be divided into pre-history and post-history. The Stone Age, Stone Age, and New Stone Age are important landmarks of prehistoric nomadic society. The history of the human race became clear after the civilization of the human race and the beginning of the arts such as agriculture, architecture and medicine. The historical period of India starts from the Indus Valley. Archaeological remains parallel to the Indus Valley are widely found in Tamil Nadu. Buried cities include Keezhadi, Kodumanal and Adichanallur (Muthumakkal Thazhigal). Ancient man left his fellow human beings who lived and died with him naturally without any burial. Then the stoneworkers set up inscriptions, punches and identified the dead. Its developmental stage is the mediators.
In Sangam Sandal Tree
Authors: Kalavathi V 
Published: August 2023

It is a Well know fact that the inner of an ancient Tamil literature was written with ink. Nature, psychology, warfare, and spiritullity can be traced back to the genres of the genre, but the singularity of the use of inanimate objects in literature is admirable. The purpose of this study is to determine the basis of human survival. The purpose if this study is to examine the basis of people’s livelihood. Sangam literature is capable of intergrating the intrinsic quests of life. People are natural, the study also focuses on the fact that has transformed people into adaptable people by adapting to a wide range of ethics in an adaptive environment. More on it is an opportunity to learn about facial expressions. This study also focuses on the fact that it has transformed. It is also an opportunity to learn about the morals of the greats of ancient Tamil compare the natural culture of the sandalwood.
Analysis Of Regional Fixed Assets Management In Buton District Financial And Regional Assets Agency
Authors: Bahari Samsul 
Published: August 2023

This research was conducted at the Regional Finance and Assets Agency (BKAD) of South Buton Regency. This study aims to determine and provide an overview of the Analysis of Regional Fixed Asset Management at the Regional Finance and Agency (BKAD) of South Buton Regency. This type of research is comparative, the type of data used is qualitative data with data sources, namely primary data and secondary data. Data collection methods include field research (fieldnote research) and library research (library research). The data obtained is then analyzed using the comparative method, which is a method or procedure in the form of numbers that compares the budget data with the realization data. The results of the research and discussion show that Permendagri No. 19 of 2016 concerning Technical Guidelines for the Management of Regional Finance and Assets Agency (BKAD) of South Buton Regency.
THE INFLUENCE OF DEMOCRATIC LEADERSHIP STYLE AND MOTIVATION ON THE PERFORMANCE OF SABHARA MEMBERS AT TOMOHON RESORT POLICE
Authors: Frans Vanya Monica Debora , Kindangen Paulus , Wangke Shinta J. C. 
Published: August 2023

This study aims to figure out the influence of democratic leadership style and motivation on performance partially and simultaneously. The population in this research is 42. The sampling technique used is saturated sampling, where all members of the population are used as samples. The analytical method used is multiple linear analysis with the help of SPSS 29.0 program. The results show that partially democratic leadership style does not have a positive and significant influence on the performance of Sabhara Members at Tomohon Police. However, there is a positive and significant influence of motivation on the performance of Sabhara Members at Tomohon Police. Whereas simultaneously democratic leadership style and motivation have a positive and significant influence on the performance of SABHARA members at Tomohon resort police.

Keywords: democratic leadership style, motivation, employee performance