bluuebunny/crossref_metadata_2025_split huggingface dataset:
Cost-effectiveness of abemaciclib plus endocrine therapy in high-risk HR+/HER2–early breast cancer in China
Authors: Wei Qiran , Xu YuTing , Liu Wei , Guan Xin 
Published: November 2023

Abstract
Objective
The aim of this article is to evaluate the cost-effectiveness of abemaciclib plus endocrine therapy (ABE + ET) vs. ET as adjuvant treatment for high-risk hormone receptor-positive and human epidermal growth factor receptor 2-negative (HR+/HER2–) early breast cancer in China.

Methods
From the perspective of the Chinese health care system, a 5-state Markov model was developed with a lifetime horizon. Data of the monarchE phase III clinical trial were used to model the invasive disease-free survival (iDFS) and standard parameters models were used for data extrapolation. Costs were obtained from national data sources, expert opinions and published literature using 2023 US dollars and discounted by 5%. The results were evaluated in terms of life-years (LYs) and quality-adjusted life-years (QALYs). Sensitivity analyses and scenario analyses were performed to test the robustness of the basic results.

Results
In the base-case analysis result, the model projected improved outcomes (by 0.65 LYs and 0.72 QALYs) and increased costs (by $16,057.72) for incremental cost-effectiveness ratios (ICERs) of $24,841/LY and $22,385/QALY for ABE + ET vs. ET patients. The results in scenario analysis estimated the ICERs of ABE + ET treatment to be $16,959/LY and $15,264/QALY in a mixture cure model, and $13,560/LY and $12,191/QALY in a non-mixture cure model. The model was sensitive to outcome discount rate and utility of iDFS.

Conclusion
ABE + ET might not have an economic advantage over ET at a willingness-to-pay (WTP) threshold of one time the per capita GDP in China, but was expected to be more cost-effective at a WTP threshold of three times the per capita GDP. Further analysis will be conducted once data from longer-term studies become available.
A Bayesian spatio-temporal study of the association between meteorological factors and the spread of COVID-19
Authors: Mullineaux Jamie D. , Leurent Baptiste , Jendoubi Takoua 
Published: November 2023

Abstract
Background
The spread of COVID-19 has brought challenges to health, social and economic systems around the world. With little to no prior immunity in the global population, transmission has been driven primarily by human interaction. However, as with common respiratory illnesses such as influenza some authors have suggested COVID-19 may become seasonal as immunity grows. Despite this, the effects of meteorological conditions on the spread of COVID-19 are poorly understood. Previous studies have produced contrasting results, due in part to limited and inconsistent study designs.

Methods
This study investigates the effects of meteorological conditions on COVID-19 infections in England using a Bayesian conditional auto-regressive spatio-temporal model. Our data consists of daily case counts from local authorities in England during the first lockdown from March–May 2020. During this period, legal restrictions limiting human interaction remained consistent, minimising the impact of changes in human interaction. We introduce a lag from weather conditions to daily cases to accommodate an incubation period and delays in obtaining test results. By modelling spatio-temporal random effects we account for the nature of a human transmissible virus, allowing the model to isolate meteorological effects.

Results
Our analysis considers cases across England’s 312 local authorities for a 55-day period. We find relative humidity is negatively associated with COVID-19 cases, with a 1% increase in relative humidity corresponding to a reduction in relative risk of 0.2% [95% highest posterior density (HPD): 0.1–0.3%]. However, we find no evidence for temperature, wind speed, precipitation or solar radiation being associated with COVID-19 spread. The inclusion of weekdays highlights systematic under reporting of cases on weekends with between 27.2–43.7% fewer cases reported on Saturdays and 26.3–44.8% fewer cases on Sundays respectively (based on 95% HPDs).

Conclusion
By applying a Bayesian conditional auto-regressive model to COVID-19 case data we capture the underlying spatio-temporal trends present in the data. This enables us to isolate the main meteorological effects and make robust claims about the association of weather variables to COVID-19 incidence. Overall, we find no strong association between meteorological factors and COVID-19 transmission.
Neuropharmacological potential of honokiol and its derivatives from Chinese herb Magnolia species: understandings from therapeutic viewpoint
Authors: Faysal Md. , Khan Jishan , Zehravi Mehrukh , Nath Nikhil , Singh Laliteshwar Pratap , Kakkar Saloni , Perusomula Rajashekar , Khan Pathan Amanulla , Nainu Firzan , Asiri Mohammed , Khan Sharuk L. , Das Rajib , Emran Talha Bin , Wilairatana Polrat 
Published: November 2023

AbstractHonokiol is a neolignan biphenol found in aerial parts of the Magnolia plant species. The Magnolia plant species traditionally belong to China and have been used for centuries to treat many pathological conditions. Honokiol mitigates the severity of several pathological conditions and has the potential to work as an anti-inflammatory, anti-angiogenic, anticancer, antioxidant, and neurotherapeutic agent. It has a long history of being employed in the healthcare practices of Southeast Asia, but in recent years, a greater scope of research has been conducted on it. Plenty of experimental evidence suggests it could be beneficial as a neuroprotective bioactive molecule. Honokiol has several pharmacological effects, leading to its exploration as a potential therapy for neurological diseases (NDs), including Alzheimer's disease (AD), Parkinson’s disease (PD), cerebral ischemia, anxiety, depression, spinal cord injury, and so on. So, based on the previous experimentation reports, our goal is to discuss the neuroprotective properties of honokiol. Besides, honokiol derivatives have been highlighted recently as possible therapeutic options for NDs. So, this review focuses on honokiol's neurotherapeutic actions and toxicological profile to determine their safety and potential use in neurotherapeutics.
Prone versus lateral position in acute hypoxemic respiratory failure patients with HFNO therapy: study protocol for a multicentre randomised controlled open-label trial
Authors: Zhou Xixin , Luo Xiaoqing , Li Qin , Chen Guihua , Tong Jin , Deng Wang 
Published: November 2023

Abstract
Background
High-flow nasal oxygen (HFNO) therapy is a leading treatment technique for acute hypoxemic respiratory failure (AHRF), but its treatment failure rate remains high. The awake prone position (APP) has been proven to increase oxygenation and reduce the endotracheal intubation rate in patients with COVID-19-induced AHRF. However, the APP is poorly tolerated in patients, and its performance in improving prognoses is controversial. The lateral position has a similar mechanism and effect to the prone position, but it is more tolerable than the prone position. Therefore, it is worth exploring whether the lateral position is better for awake patients with AHRF.

Methods
This is a protocol for a three-arm parallel-group multicentre randomised controlled open-label exploratory trial. A total of 583 patients from two hospitals in Chongqing, China, will be randomised to take the semi-recumbent position, lateral position, or prone position at a ratio of 1:1:1. Patients are all diagnosed with AHRF secondary to non-COVID-19 pneumonia or lung infection and receiving HFNO therapy. The primary outcome is ventilator-free days in 28 days. The secondary outcomes are the 28-day intubation rate, 28-day all-cause mortality, total position change time, the incidence of adverse events, number of hours using HFNO therapy, length of hospital and intensive care unit (ICU) stay, and others. We will conduct subgroup analyses on the arterial partial pressure of oxygen to the fraction of inspiration oxygen (PaO2/FiO2) ratio (> 200 mmHg or ≤ 200 mmHg), time from admission to intervention implementation (< 24 h or ≥ 24 h), position changing time, and different diagnoses.

Discussion
This trial will explore the prognostic effects of the APP with that of the lateral position in awake patients with non-COVID-19AHRF and compare the differences between them. To provide evidence for clinical decision-making and further research on position management.

Trial registration
This trial was registered in the Chinese Clinical Trial Registry. The registration number is ChiCTR2200055822. Registered on January 20, 2022.
An innovative combination of Box-Behnken design and ecofriendly approaches for the simultaneous determination of aspirin, clopidogrel, atorvastatin and rosuvastatin in their fixed-dose combination tablets
Authors: Mostafa Eman A. , El‐Ashrey Mohamed K. , Mahmoud Sally Tarek 
Published: November 2023

AbstractThree-levels Box-Behnken design was used in the experimental design approach for the optimization of chromatographic parameters to achieve the optimum resolution and sharp peak shape within a reasonable run time. A method that is sensitive, reliable, and selective was constructed and validated for the simultaneous measurement of a combination therapy that contains blood-thinning and cholesterol-lowering compounds. The four cited drugs namely, aspirin (ASP), clopidogrel (CLP), atorvastatin (ATV) and rosuvastatin (ROS) were estimated in bulk and in pharmaceutical dosage forms in line with International Council for Harmonization guidelines. The separation was done utilizing Kinetex 2.6 C18 column (100 mm, 4.6 mm, 5 m) and RP-HPLC with diode array detector. The separation of the cited drugs and the degradation product of ASP was achieved with mobile phase composed of acetonitrile: KH2PO4 buffer in a gradient mode with pH 3.2 at room temperature. The four drugs were linear over the concentration range (0.05–50 µg/mL). The technique is feasible to be used in quality control laboratories. To picture the green profile of the developed method, four greenness assessment tools were applied. National environmental methods index (NEMI), analytical eco-scale assessment (ESA), green analytical procedure index (GAPI) and analytical greenness metric (AGREE) are the most widely used metrics. They were employed to evaluate the greenness profile of the proposed method and to perform a detailed greenness comparison between the developed method and some of the reported methods for the determination of the investigated drugs. The developed method was found to be relatively green with 0.54 AGREE score.
Efficacy and safety of basal-bolus insulin at 1:1.5 ratio compared to 1:1 ratio using a weight-based initiation and titration (WIT2) algorithm in hospitalized patients with type 2 Diabetes: a multicenter, randomized, clinical study
Authors: Zhang Xiaodan , Yan Dewen , Du Tao , Zhao Yunjuan , Zhang Jiangong , Zhang Tong , Lin Mingrun , Li Yanli , Li Wangen 
Published: November 2023

Abstract
Background
Most studies initiated basal-bolus insulin in a ratio of 1:1 and titrated based on glucose. This study aimed to investigate the effectiveness and safety of a weight-based and ratio of 1:1.5 basal-bolus insulin using an algorithm for both initiation and titration in hospitalized patients with type 2 diabetes (T2D).

Methods
Hospitalized patients with T2D were randomly assigned to two groups in equal numbers to receive 1:1.5 and 1:1 ratios of basal-bolus insulin using a weight-based algorithm for both initiation and titration. The primary outcome was the time taken to reach the fasting blood glucose (FBG) target and 2-h postprandial blood glucose (2hBG) targets after three meals. The secondary outcome included insulin dosage to achieve glycemic control and the incidence of hypoglycemia during hospitalization.

Results
250 patients were screened between October 2021 and June 2022, 220 were randomly grouped, and 182 completed the trial (89 in the 1:1.5 and 93 in the 1:1 groups). The time taken to reach FBG targets was comparable between the two groups (3.4 ± 1.7 vs. 3.0 ± 1.3 days, p = 0.137) within about 3 days. The 2hBG after three meals was shorter in the 1:1.5 group than in the 1:1group (2.9 ± 1.5 vs. 3.4 ± 1.4 days, p = 0.015 for breakfast, 3.0 ± 1.6 vs. 3.6 ± 1.4 days, p = 0.005 for lunch, and 3.1 ± 2.1 vs. 4.0 ± 1.5 days, p = 0.002 for dinner). No significant difference in insulin dosages was found between the two groups at the end of the study. The incidence of hypoglycemia was similar in both groups.

Conclusions
We demonstrated that fixed dose-ratio basal-bolus insulin at 1:1.5 calculated using a weight-based initiation and titration algorithm was simple, as effective, and safe as ratio at 1:1 in managing T2D in hospitalized patients.
Trial Registration ChiCTR 2,100,050,963. Date of registration: September 8, 2021.
Predicting MYCN amplification in paediatric neuroblastoma: development and validation of a 18F-FDG PET/CT-based radiomics signature
Authors: Qian Luo-Dan , Zhang Shu-Xin , Li Si-Qi , Feng Li-Juan , Zhou Zi-Ang , Liu Jun , Zhang Ming-Yu , Yang Ji-Gang 
Published: November 2023

Abstract
Objectives
To develop and validate an 18F-FDG PET/CT-based clinical-radiological-radiomics nomogram and evaluate its value in the diagnosis of MYCN amplification (MNA) in paediatric neuroblastoma (NB) patients.

Methods
A total of 104 patients with NB were retrospectively included. We constructed a nomogram to predict MNA based on radiomics signatures, clinical and radiological features. The multivariable logistic regression and the least absolute shrinkage and selection operator (LASSO) were used for feature selection. Radiomics models are constructed using decision trees (DT), logistic regression (LR) and support vector machine (SVM) classifiers. A clinical-radiological (C-R) model was developed using clinical and radiological features. A clinical-radiological-radiomics (C-R-R) model was developed using the C-R model of the best radiomics model. The prediction performance was verified by receiver operating characteristic (ROC) curve analysis, calibration curve analysis and decision curve analysis (DCA) in the training and validation cohorts.

Results
The present study showed that four radiomics signatures were significantly correlated with MNA. The SVM classifier was the best model of radiomics signature. The C-R-R model has the best discriminant ability to predict MNA, with AUCs of 0.860 (95% CI, 0.757–0.963) and 0.824 (95% CI, 0.657–0.992) in the training and validation cohorts, respectively. The calibration curve indicated that the C-R-R model has the goodness of fit and DCA confirms its clinical utility.

Conclusion
Our research provides a non-invasive C-R-R model, which combines the radiomics signatures and clinical and radiological features based on 18F-FDGPET/CT images, shows excellent diagnostic performance in predicting MNA, and can provide useful biological information with stratified therapy.

Critical relevance statement
Radiomic signatures of 18F-FDG-based PET/CT can predict MYCN amplification in neuroblastoma.

Key points
• Radiomic signatures of 18F-FDG-based PET/CT can predict MYCN amplification in neuroblastoma.
• SF, LDH, necrosis and TLG are the independent risk factors of MYCN amplification.
• Clinical-radiological-radiomics model improved the predictive performance of MYCN amplification.

Graphical Abstract
A multi-model based on radiogenomics and deep learning techniques associated with histological grade and survival in clear cell renal cell carcinoma
Authors: Wang Shihui , Zhu Chao , Jin Yidong , Yu Hongqing , Wu Lili , Zhang Aijuan , Wang Beibei , Zhai Jian 
Published: November 2023

Abstract
Objectives
This study aims to evaluate the efficacy of multi-model incorporated by radiomics, deep learning, and transcriptomics features for predicting pathological grade and survival in patients with clear cell renal cell carcinoma (ccRCC).

Methods
In this study, data were collected from 177 ccRCC patients, including radiomics features, deep learning (DL) features, and RNA sequencing data. Diagnostic models were then created using these data through least absolute shrinkage and selection operator (LASSO) analysis. Additionally, a multi-model was developed by combining radiomics, DL, and transcriptomics features. The prognostic performance of the multi-model was evaluated based on progression-free survival (PFS) and overall survival (OS) outcomes, assessed using Harrell’s concordance index (C-index). Furthermore, we conducted an analysis to investigate the relationship between the multi-model and immune cell infiltration.

Results
The multi-model demonstrated favorable performance in discriminating pathological grade, with area under the ROC curve (AUC) values of 0.946 (95% CI: 0.912–0.980) and 0.864 (95% CI: 0.734–0.994) in the training and testing cohorts, respectively. Additionally, it exhibited statistically significant prognostic performance for predicting PFS and OS. Furthermore, the high-grade group displayed a higher abundance of immune cells compared to the low-grade group.

Conclusions
The multi-model incorporated radiomics, DL, and transcriptomics features demonstrated promising performance in predicting pathological grade and prognosis in patients with ccRCC.

Critical relevance statement
We developed a multi-model to predict the grade and survival in clear cell renal cell carcinoma and explored the molecular biological significance of the multi-model of different histological grades.

Key points
1. The multi-model achieved an AUC of 0.864 for assessing pathological grade.
2. The multi-model exhibited an association with survival in ccRCC patients.
3. The high-grade group demonstrated a greater abundance of immune cells.

Graphical Abstract
Correlation analysis of MR elastography and Ki-67 expression in intrahepatic cholangiocarcinoma
Authors: Gao Shanshan , Sun Wei , Zhang Yunfei , Wang Feihang , Jin Kaipu , Qian Xianling , Han Jing , Wang Xiaolin , Dai Yongming , Sheng Ruofan , Zeng Mengsu 
Published: November 2023

Abstract
Background
Intrahepatic cholangiocarcinoma (iCCA) is an aggressive primary liver cancer with dismal outcome, high Ki-67 expression is associated with active progression and poor prognosis of iCCA, the application of MRE in the prediction of iCCA Ki-67 expression has not yet been investigated until now. We aimed to evaluate the value of magnetic resonance elastography (MRE) in assessing Ki-67 expression for iCCA.

Results
In the whole cohort, 97 patients (57 high Ki-67 and 40 low Ki-67; 58 males, 39 females; mean age, 58.89 years, ranges 36–70 years) were included. At the multivariate analysis, tumor stiffness (odds ratio (OR) = 1.669 [95% CI: 1.307–2.131], p < 0.001) and tumor apparent diffusion coefficient (ADC) (OR = 0.030 [95% CI: 0.002, 0.476], p = 0.013) were independent significant variables associated with Ki-67. Areas under the curve of tumor stiffness for the identification of high Ki-67 were 0.796 (95% CI 0.702, 0.871). Tumor stiffness was moderately correlated with Ki-67 level (r = 0.593, p < 0.001). When both predictive variables of tumor stiffness and ADC were integrated, the best performance was achieved with area under the curve values of 0.864 (95% CI 0.780–0.926).

Conclusion
MRE-based tumor stiffness correlated with Ki-67 in iCCA and could be investigated as a potential prognostic biomarker. The combined model incorporating both tumor stiffness and ADC increased the predictive performance.

Critical relevance statement
MRE-based tumor stiffness might be a surrogate imaging biomarker to predict Ki-67 expression in intrahepatic cholangiocarcinoma patients, reflecting tumor cellular proliferation. The combined model incorporating both tumor stiffness and apparent diffusion coefficient increased the predictive performance.

Key points
• MRE-based tumor stiffness shows a significant correlation with Ki-67.
• The combined model incorporating tumor stiffness and apparent diffusion coefficient demonstrated an optimized predictive performance for Ki-67 expression.
• MRE-based tumor stiffness could be investigated as a potential prognostic biomarker for intrahepatic cholangiocarcinoma.

Graphical Abstract
Crack modeling via minimum-weight surfaces in 3d Voronoi diagrams
Authors: Jung Christian , Redenbach Claudia 
Published: November 2023

AbstractAs the number one building material, concrete is of fundamental importance in civil engineering. Understanding its failure mechanisms is essential for designing sustainable buildings and infrastructure. Micro-computed tomography (μCT) is a well-established tool for virtually assessing crack initiation and propagation in concrete. The reconstructed 3d images can be examined via techniques from the fields of classical image processing and machine learning. Ground truths are a prerequisite for an objective evaluation of crack segmentation methods. Furthermore, they are necessary for training machine learning models. However, manual annotation of large 3d concrete images is not feasible. To tackle the problem of data scarcity, the image pairs of cracked concrete and corresponding ground truth can be synthesized. In this work we propose a novel approach to stochastically model crack structures via Voronoi diagrams. The method is based on minimum-weight surfaces, an extension of shortest paths to 3d. Within a dedicated image processing pipeline, the surfaces are then discretized and embedded into real μCT images of concrete. The method is flexible and fast, such that a variety of different crack structures can be generated in a short amount of time.
Do public healthcare programs make societies more equal? Cross-country evidence on subjective wellbeing
Authors: Dizon Ryan Joseph R. 
Published: November 2023

Abstract
Background
Universal health coverage (UHC) aims to provide quality healthcare services and safeguard the population from the financial burden of catastrophic health expenditure. Its primary objectives are to improve longevity and enhance overall quality of life. This study investigates the relationship between UHC and the inequality in subjective wellbeing (SWB) and explores whether public health programs can reduce social inequality. By employing SWB inequality as a measure, we go beyond the conventional income-centric approach to assess social inequality.

Methods
The SWB data used in this study are derived from the repeated cross-sectional survey obtained from the European Values Study (EVS) and the World Values Survey (WVS). We adopt an observational study design and employ statistical techniques, such as ordinary least squares, Oaxaca–Blinder decomposition, and the recentered influence function (RIF). The RIF, in particular, allows us to characterise the entire distribution of SWB, rather than focusing on a single point.

Results
UHC programs are negatively associated with SWB inequality (-0.070, significant at 5%). The negative association is observed at the 5th, 50th, and 75th percentiles of the SWB distribution, whilst the association becomes positive at the 95th percentile. UHC programs do not contribute to the SWB inequality gap.

Conclusions
UHC programs exhibit an inequality-reduction property when the inequality is not severe or when countries are more equal. However, their effectiveness diminishes in the presence of extreme inequality. Health programs do not contribute to the existing SWB inequality gap between developed and developing countries. Strengthening the two dimensions of the UHC program (i.e., service coverage and financial protection) will ensure better health and wellbeing for all, and potentially foster a more equal and inclusive society.