bluuebunny/crossref_metadata_2025_split huggingface dataset:
Longitudinal Study on the Impact of Three Major Regulations on the Korean Pharmaceutical Industry in the Last 30 Years
Authors: Um Seung In , Sohn Uy Dong , Jung Sun-Young , You Seung-Hun , Kim Changone , Lee Sora , Lee Heesang 
Published: April 2021

Abstract
Background: The pharmaceutical industry is heavily regulated. Partly for this reason, new drugs generally take over ten years to reach market entry from the product development stage. Although regulations affect the pharmaceutical industry over a long time, extant studies have usually focused on the short period before and after implementing a new regulatory policy to determine the impact of that policy. The purpose of this study is to examine whether and how significant regulatory policies affect long-term innovation in the pharmaceutical industry in Korea.Methods: This study focused on three significant regulatory policies: the product patent system, changes in the Good Manufacturing Practice (GMP) system, and the Drug Expenditure Rationalization Plan (DERP). This study used Interrupted Time Series (ITS) analysis to investigate the policies' long-term impacts before and after their implementation.Results: Our results show that the introduction of the product patent system in 1987 significantly increased the number of Korean patent applications. The revised GMP policies' effect was also statistically significant, both before and after implementation and between preemptive companies and non-preemptive ones. The DERP, however, did not significantly delay new drug registration in Korea due to companies' negotiations with the regulatory authorities or the system that links drug approval and price evaluation.Conclusion: This study showed that the policies of the product patent system, GMP policies, and DERP regulations have significantly altered the course of the pharmaceutical industry in Korea. This study suggests that it is necessary for companies to preemptively respond to systemic changes in development and production strategies to deal with regulatory changes and achieve sustainable growth. Also, this study implies that the governmental authorities need to develop a regulatory policy that links innovation and competitiveness in domestic pharmaceutical companies.
Effect of paclitaxel-coated balloon angioplasty on side branch lesion and cardiovascular outcomes in patients with de novo true coronary bifurcation lesions undergoing percutaneous coronary intervention
Authors: Li Youmei , Mao Qi , Liu Huanyun , Zhou Denglu , Zhao Jianhua 
Published: April 2021

Abstract
Purpose
To compare the effects of paclitaxal-coated balloon (PCB) versus conventional balloon (CB) on side branch (SB) lesion and cardiovascular outcomes in patients with de novo true bifurcation lesions.
Methods
In total, 219 patients with de novo true bifurcation lesions were enrolled and divided into PCB group (102 cases) and CB group (117 cases) according to angioplasty strategy in SB. Drug-eluting stent (DES) was implanted in main vessel (MV) for each subject. All subjects underwent a 12-month follow-up for late lumen loss (LLL), restenosis and major adverse cardiovascular events (MACE) after percutaneous coronary intervention (PCI). MACEs included cardiac death, nonfatal myocardial infarction and angina pectoris.
Results
There were no differences in diameter, minimum lumen diameter (MLD) and stenosis for bifurcation lesions between the two groups before and immediately after PCI (P > 0.05). After 12-month follow-up, no differences occurred in MV-MLD and MV-LLL between the two groups (P > 0.05); SB-MLD in PCB group was higher than that in CB group (1.97 ± 0.36 mm vs. 1.80 ± 0.43 mm, P = 0.007); SB-LLL in PCB group was lower than that in CB group (0.11 ± 0.18 mm vs. 0.19 ± 0.25 mm, P = 0.024). Multivariate COX analyses indicated that PCB group had lower MACE risk than CB group (HR = 0.480, 95%CI 0.244–0.941, P = 0.033).
Conclusion
PCB could decrease SB-LLL and MACE risk in patients with de novo true coronary bifurcation lesion 12 months after single-DES intervention.
Use of an electronic medication management support system in patients with polypharmacy in general practice: study protocol of a quantitative process evaluation of the AdAM trial
Authors: Brünn Robin , Lemke Dorothea , Chapidi Kiran , Köberlein-Neu Juliane , Piotrowski Alexandra , Söling Sara , Greiner Wolfgang , Kellermann-Mühlhoff Petra , Timmesfeld Nina , Akker Marjan van den , Muth Christiane 
Published: April 2021

Abstract
Background: Much research is currently devoted to polypharmacy, but interventional studies often fail to significantly improve patient-relevant outcomes or just measure surrogate parameters. Interventions and their settings are often complex, and a wide range of factors affect results. The aim of the AdAM study is to reduce hospitalization and death by requiring general practitioners (GPs) to use a computerized decision-support system (CDSS). The study will undergo a process evaluation to identify relevant factors for successful implementation and to assess whether the intervention was implemented as intended.Research questions: We will assess implementation (reach, fidelity, dose, tailoring) by asking the following questions: (1) Who took part in the intervention, i.e., the proportion of GPs that used the CDSS, and the proportion of patients that were enrolled by them? Information on the characteristics of GPs and patients will also be collected. (2) How many and what type of medication alerts were handled by the GPs? (3) Was the intervention implemented as intended? (4) On what days did GPs use the intervention tool? We will conduct subgroup analyses to all questions, including time effects to account for software improvements over time.Methods: The process evaluation is part of a stepped wedge cluster-randomized controlled trial. Characteristics of practices, GPs and patients using the CDSS will be compared with the non-participating population. CDSS log data will be analyzed to evaluate how the number of medication alerts changed between baseline and two months later and identify the kind of medication alerts that are given highest priority. The comparison of enrolled patients on weekdays vs weekends will shed light on whether GPs use the CDSS in the absence or presence of patients. All outcomes will be presented using descriptive statistics, and significance tests will be used to identify any associations between them.Discussion: This study protocol is the basis for conducting the analyses of the log data-based process evaluation. By providing insight into the way GPs conduct medication reviews, the evaluation will provide a context to the trial results and support their interpretation. The evaluation relies on the proper documentation of what the CDSS was used for, which may limit its explanatory power.Trial registration: ClinicalTrials.gov, NCT03430336. Registered on February 6, 2018. https://clinicaltrials.gov/ct2/show/NCT03430336
Inhibition of β-catenin Protects Mouse Hearts From Ventricular Arrhythmias After Myocardial Infarction Independent of Ion Channel Gene Changes
Authors: Wang Jerry , Xia Ying , Lu Aizhu , Wang Hongwei , Davis Darryl R. , Liu Peter , Beanlands Rob S. , Liang Wenbin 
Published: April 2021

Abstract
The Wnt/β-catenin signaling regulates ion channel gene expressions in cardiomyocytes. Because Wnt/β-catenin signaling is activated in myocardial infarction (MI), this study aims to investigate if β-catenin inhibition affects post-MI ion channel gene alterations and ventricular tachycardias (VT). MI was induced by permanent ligation of left anterior descending artery in wild-type (WT) and cardiomyocyte-specific β-catenin knockout (KO) mice. KO mice showed reduced susceptibility to VT (18% vs. 77% in WT) at week-8 after MI, associated with attenuated structural remodeling (reduced scar size and attenuated left ventricle dilation) as compared to WT. However, at the subacute phase (week-1) and chronic phase (week-8) after MI, Wnt/β-catenin signaling activation was found in non-cardiomyocytes, but not in cardiomyocytes. Downregulations of Scn5a (encoding Nav1.5) and Gja1 (encoding Cx43) were found at week-1 but not at week-8, while downregulations of K+ channel genes were present at both week-1 and -8. Consistent with no activation of Wnt/β-catenin pathway in cardiomyocytes at week-1 and -8, these alterations in ion channel/transporter genes were not different between KO and WT mice. This study demonstrated that mice with cardiomyocyte-specific β-catenin deletion have reduced VT susceptibility after MI which is caused by attenuated structural remodeling, instead of alterations in ion channel gene expressions.
Manganese distribution in the Mn-hyperaccumulator Grevillea meisneri from New Caledonia
Authors: Bihanic Camille , Petit Eddy , Perrot Roseline , Cases Lucie , Garcia Armelle , Pelissier Franck , Poullain Cyril , Rivard Camille , Hossaert Martine , Grison Claude 
Published: April 2021

Abstract
• Grevillea meisneri, an endemic New Caledonian Mn-hyperaccumulator, is used in rehabilitation of degraded mining sites on the island. Large-scale programs require transplanting nursery-grown seedlings, but effects of the nursery environment on Mn tolerance of transplants and their capacity to hyper-accumulate Mn are unknown, slowing rehabilitation efforts.• We studied tissue-level distribution of Mn and other elements in different tissues of G. meisneri using micro-X-Ray Fluorescence spectroscopy (μXRF), comparing nursery-grown plants transplanted into the site and sampled seven years later, and similar-sized plants that had grown spontaneously in the site. • Mirroring patterns in other Mn-hyperaccumulators, Mn was preferentially accumulated in leaves but was also present in roots. Concentrations were highest in leaf epidermal tissues, in cortex and vascular tissues of stems and primary roots, and in phloem and pericycle-endodermis of parent cluster roots. Although abundant in soil, Ni was absent from all tissues of G. meisneri. Ca was always co-localised with Mn. Preferential uptake of Mn vs Ni in roots implies as-yet-uncharacterized specific Mn-transporters, while Ca and Mn co-localisation suggests shared transport pathways. • No differences were observed in concentration and distribution of Mn in transplanted and spontaneously-growing plants. Nursery-grown transplants should be highly suitable for large-scale, high-throughput rehabilitation programs.
Handwork Vs Machine; A Comparison of Rheumatoid Arthritis Patient Populations as Identified From Ehr Free-text by Diagnosis Extraction Through Machine-learning or Traditional Criteria-based Chart Review
Authors: Maarseveen Tjardo , Maurits Marc , Niemantsverdriet Ellis , Mil Annette van der Helm - van , Huizinga Thomas W.J. , Knevel Rachel 
Published: April 2021

Abstract
BackgroundElectronic Health Records (EHRs) offer a wealth of observational data. Machine-Learning (ML) methods are efficient at data extraction, capable of processing the information-rich free-text physician notes in EHRs. The clinical diagnosis contained therein represents physician expert opinion and is more consistently recorded than classification criteria components.ObjectivesTo investigate the overlap and differences between Rheumatoid Arthritis patients as identified either from EHR free-text through extraction of the rheumatologist diagnosis using machine-learning (ML) or through manual chart-review applying the 1987 and 2010 RA classification criteria.MethodsSince EHR initiation, 17,662 patients visited the Leiden outpatient clinic. For ML, we used a Support Vector Machine (SVM) model to identify those who were diagnosed with RA by their rheumatologist. We trained & validated the model on a random selection of 2,000 patients, balancing PPV and Sensitivity to define a cutoff, and assessed performance on a separate 1,000 patients. We then deployed the model on our entire patient selection (including the 3,000). Of those, 1,212 patients had both a 1987 and 2010 EULAR/ACR criteria status at one year after inclusion into the local prospective arthritis cohort. In these 1,212 patients we compared the patient characteristics of RA cases identified with ML and those fulfilling the classification criteria. ResultsThe ML model performed very well in the independent test set (sensitivity=0.85, specificity=0.99, PPV=0.86, NPV=0.99). In our selection of patients with both EHR and classification information, 406 were recognized as RA by ML and 386 and 457 fulfilled the 1987 or 2010 criteria respectively. Eighty percent of the ML-identified cases fulfilled at least one of the criteria sets. Both demographic and clinical parameters did not differ between the ML extracted cases and those identified with EULAR/ACR classification criteria. ConclusionsWith ML methods we enable fast patient extraction from the huge EHR resource. Our ML algorithm accurately identifies patients diagnosed with RA by their rheumatologist. This resulting group of RA patients had a strong overlap with patients identified using the 1987 or 2010 classification criteria and the baseline (disease) characteristics were comparable. ML assisted case labelling enables high-throughput creation of inclusive patient selections for research purposes.
Efficacy of Lenvatinib for Unresectable Hepatocellular Carcinoma Based on Background Liver Disease Etiology: Multi-center Retrospective Study
Authors: Hiraoka Atsushi , Kumada Takashi , Tada Toshifumi , Tani Joji , Kariyama Kazuya , Fukunishi Shinya , Atsukawa Masanori , Hirooka Masashi , Tsuji Kunihiko , Ishikawa Toru , Takaguchi Koichi , Itobayashi Ei , Tajiri Kazuto , Shimada Noritomo , Shibata Hiroshi , Ochi Hironori , Kawata Kazuhito , Yasuda Satoshi , Toyoda Hidenori , Aoki Tomoko , Tanaka Takaaki , Ohama Hideko , Nouso Kazuhiro , Tsutsui Akemi , Nagano Takuya , Itokawa Norio , Arai Taeang , Okubo Tomomi , Imai Michitaka , Koizumi Yohei , Nakamura Shinichiro , Joko Koji , Hiasa Yoichi , Kudo Masatoshi 
Published: April 2021

Abstract
Background/Aim: Hepatocellular carcinoma patients (HCC) related with non-alcoholic steatohepatitis (NASH) has been recently reported to be not responsive to immune-checkpoint inhibitor treatment (ICI). This study aimed to evaluate therapeutic efficacy in non-alcoholic fatty liver disease (NAFLD)/NASH-related unresectable-HCC (u-HCC) treated with lenvatinib.Material/Methods: Five-hundred-thirty u-HCC with Child-Pugh A were enrolled, and divided into the NAFLD/NASH (n=103) and Viral/Alcohol (n=427) groups. Clinical features were compared in a retrospective manner.Results: Progression-free survival (PFS) was better in the NAFLD/NASH than the Viral/Alcohol group (median 9.3 vs. 7.5 months, P=0.012), while there was no significant difference in overall survival (OS) (20.5 vs. 16.9 months, P=0.057). In Cox-hazard analysis of prognostic factors for PFS, elevated AFP (≥400ng/mL) (HR1.294, P=0.014), elevated ALT (≥30 U/L) (HR1.247, P=0.029), modified ALBI grade 2b (HR1.236, P=0.047), and NAFLD/NASH etiology (HR0.763, P=0.036) were significant prognostic factors. NAFLD/NASH etiology was not a significant prognostic factor in Cox-hazard analysis for OS (HR0.750, P=0.076), whereas AFP (≥400ng/mL) (HR1.402, P=0.009), later line use (HR0.737, P=0.0137), BCLC C stage (HR1.297, P=0.035), and modified ALBI grade 2b (HR1.875, P<0.001) were significant.Conclusion: ICI is reportedly not effective for NAFLD/NASH-related HCC, while lenvatinib can improve the prognosis of u-HCC irrespective of HCC etiology or its line of treatment.
Prediction Models for Energy Consumption and Surface Quality in Stainless Steel Milling
Authors: Yu Shuo , Zhao Guoyong , Li Chunxiao , Xu Shuang , Zheng Zhifu 
Published: April 2021

Abstract
Stainless steel is a kind of difficult-to-machine material, and the work hardening in milling easily leads to high energy consumption and poor surface quality. Thus, the influence of machined surface hardness on energy consumption and surface quality cannot be ignored. To solve this problem, the prediction models for machine tool specific energy consumption and surface roughness are developed with tool wear and machined surface hardness considered firstly. Then, the validity of the models is verified through AISI 304 stainless steel milling experiments. The results show that the prediction accuracy of the machine tool specific energy consumption model can reach 98.7%, and the roughness model can reach 96.8%. Later, according to the developed prediction models, the influence of milling parameters, surface hardness, and tool wear on the machine specific energy consumption and surface roughness is studied. Results show that in stainless steel milling, the most significant parameters for surface roughness is the machined surface hardness, while that for energy consumption is the feed per tooth. The machine specific energy consumption increases linearly with the increase of the tool wear and the machined surface hardness gradually. The proposed models are helpful to optimize the process parameters for high efficiency and high quality machining of stainless steel.
Deep Learning for Early Dental Caries Detection in Bitewing Radiographs
Authors: Lee Shinae , Oh Sang-il , Jo Junik , Kang Sumi , Shin Yooseok , Park Jeong-won 
Published: April 2021

Abstract
The early detection of incipient dental caries enables preventive treatment, and bitewing radiography is a good diagnostic tool for posterior incipient caries. In the field of medical imaging, the utilization of deep learning with convolutional neural networks (CNNs) to process various types of images has been actively researched and has shown promising performance. In this study, we developed a CNN model using a U-shaped deep CNN (U-Net) for dental caries detection on bitewing radiographs and investigated whether this model can improve clinicians’ performance. In total, 304 bitewing radiographs were used to train the deep learning model and 50 radiographs were used for performance evaluation. The diagnostic performance of the CNN model on the total test dataset was as follows: precision, 63.29%; recall, 65.02%; and F1-score, 64.14%, showing quite accurate performance. When three dentists detected dental caries using the results of the CNN model as reference data, the overall diagnostic performance of all three clinicians significantly improved, as shown by an increased recall ratio (D1, 85.34%; D1', 92.15%; D2, 85.86%; D2', 93.72%; D3, 69.11%; D3', 79.06%). These increases were especially significant in the incipient and moderate caries subgroups. The deep learning model may help clinicians to diagnose dental caries more accurately.
An Improved Calibration and Uncertainty Analysis Approach Using a Multicriteria Sequential Algorithm for Hydrological Modeling
Authors: Wu Hongjing , Chen Bing , Ye Xudong , Guo Huaicheng , Meng Xianyong , Zhang Baiyu 
Published: April 2021

Abstract
Hydrological models are widely used as simplified, conceptual, mathematical representatives for water resource management. The performance of hydrological modeling is usually challenged by model calibration and uncertainty analysis during modeling exercises. In this study, a multicriteria sequential calibration and uncertainty analysis (MS-CUA) method was proposed to improve hydrological modeling efficiency and performance with high reliability. To evaluate the performance, the proposed MS-CUA method was applied to two case studies comparing two traditional methods: sequential uncertainty fitting algorithm (SUFI-2) and generalized likelihood uncertainty estimation (GLUE). The results indicated that the MS-CUA method can quickly locate the highest posterior density (HPD) regions of parameters to improve computational efficiency. It also provided better-calibrated results and more balanced uncertainty analysis results comparing with other traditional methods.
Signatures based on tumor microenvironment genes can reliably predict the prognosis of laryngeal cancer patients
Authors: Ren Haitang , Luo Zheng , Wang Min , Chen Lei , Zhang Bo 
Published: April 2021

Abstract
Purpose: To develop a tumor microenvironment (TME) related genes based prognostic model for laryngeal cancer patients risk prediction. Methods: A innovative prognosic model was generated based on TME related genes (760 genes). Based on the model, laryngeal cancer patients were categoried into high and low-risk group. The immune status including immune cell infiltration ratio as well as checkpoints have been exploreds. Results: It can be shown here 15 genes demonstrate significant differences, which can better predict laryngeal cancer patient prognosis. The accuracy of the model prediction is evaluated and approved by the AUC value. From the immune cell infiltration ratio analysis, there is a significant difference in the infiltration degree of several types of immune cells and 6 immune checkpoints between high and low-risk laryngeal cancer patients. At the same time, the close related genes as well as TME pathways have been also investigated. Conclusion: This study has explored a potential prognostic biomarker and developed a novel TME-associated prognostic model for laryngeal cancer, which provides a valuable reference for future clinical research.
The extent of honeycombing on computed tomography cannot predict the treatment outcome of patients with acute exacerbations of interstitial lung disease (Retrospective cohort study)
Authors: Nishikawa Yurika , Hara Yu , Tagami Yoichi , Nagasawa Ryo , Murohashi Kota , Aoki Ayako , Tanaka Katsushi , Watanabe Keisuke , Horita Nobuyuki , Kobayashi Nobuaki , Yamamoto Masaki , Kudo Makoto , Kaneko Takeshi 
Published: April 2021

Abstract
Background: The purpose of this retrospective study was to clarify whether the presence of honeycombing on computed tomography (CT) can affect the prognosis of patients with acute exacerbations (AEs) of interstitial lung diseases (ILDs).Methods: Clinical parameters including age, sex, Charlson Comorbidity Index score (CCIS), blood biomarkers, and 3-month mortality were retrospectively compared between the CT honeycombing present and absent groups at the diagnosis of AEs of ILDs.Results: Ninety-five patients who were on corticosteroid pulse therapy were assessed. Though log-rank tests showed that Kaplan-Meier survival curves of the high and low ground-glass opacity (GGO) score groups differed significantly in 3-month mortality in patients with AEs of idiopathic ILDs (P = 0.007) and overall patients (P = 0.045), there was no significant difference between the CT honeycombing present and absent groups in patients with AEs of idiopathic ILDs (P = 0.600) and AEs of secondary ILDs (P = 0.472), as well as of overall patients (P = 0.905). In addition, whereas CCIS (OR, 1.436; 95% CI, 1.119-1.938; P = 0.004) and age (OR, 1.097; 95% CI, 1.119-1.212; P = 0.026) were significant predictors of 3-month mortality in the CT honeycombing absent group, serum lactate dehydrogenase (OR, 1.004; 95% CI, 1.002-1.007; P = 0.001) and sex (OR, 6.381; 95% CI, 0.821-49.602; P = 0.023) were significant predictors in the CT honeycombing present groupConclusions: The clinical features of patients with or without honeycombing may differ due to the difference in prognostic factors, but these groups were found to have similar prognoses 3 months after AE onset, and clinicopathological examinations according to these groups are essential.