bluuebunny/crossref_metadata_2025_split huggingface dataset:
Advancing data science in drug development through an innovative computational framework for data sharing and statistical analysis
Authors: Mallon Ann-Marie , Häring Dieter A. , Dahlke Frank , Aarden Piet , Afyouni Soroosh , Delbarre Daniel , El Emam Khaled , Ganjgahi Habib , Gardiner Stephen , Kwok Chun Hei , West Dominique M. , Straiton Ewan , Haemmerle Sibylle , Huffman Adam , Hofmann Tom , Kelly Luke J. , Krusche Peter , Laramee Marie-Claude , Lheritier Karine , Ligozio Greg , Readie Aimee , Santos Luis , Nichols Thomas E. , Branson Janice , Holmes Chris 
Published: November 2021

Abstract
Background
Novartis and the University of Oxford’s Big Data Institute (BDI) have established a research alliance with the aim to improve health care and drug development by making it more efficient and targeted. Using a combination of the latest statistical machine learning technology with an innovative IT platform developed to manage large volumes of anonymised data from numerous data sources and types we plan to identify novel patterns with clinical relevance which cannot be detected by humans alone to identify phenotypes and early predictors of patient disease activity and progression.

Method
The collaboration focuses on highly complex autoimmune diseases and develops a computational framework to assemble a research-ready dataset across numerous modalities. For the Multiple Sclerosis (MS) project, the collaboration has anonymised and integrated phase II to phase IV clinical and imaging trial data from ≈35,000 patients across all clinical phenotypes and collected in more than 2200 centres worldwide. For the “IL-17” project, the collaboration has anonymised and integrated clinical and imaging data from over 30 phase II and III Cosentyx clinical trials including more than 15,000 patients, suffering from four autoimmune disorders (Psoriasis, Axial Spondyloarthritis, Psoriatic arthritis (PsA) and Rheumatoid arthritis (RA)).

Results
A fundamental component of successful data analysis and the collaborative development of novel machine learning methods on these rich data sets has been the construction of a research informatics framework that can capture the data at regular intervals where images could be anonymised and integrated with the de-identified clinical data, quality controlled and compiled into a research-ready relational database which would then be available to multi-disciplinary analysts. The collaborative development from a group of software developers, data wranglers, statisticians, clinicians, and domain scientists across both organisations has been key. This framework is innovative, as it facilitates collaborative data management and makes a complicated clinical trial data set from a pharmaceutical company available to academic researchers who become associated with the project.

Conclusions
An informatics framework has been developed to capture clinical trial data into a pipeline of anonymisation, quality control, data exploration, and subsequent integration into a database. Establishing this framework has been integral to the development of analytical tools.
Association between multiple sclerosis and dietary patterns based on the traditional concept of food nature: a case-control study in Iran
Authors: Sharifi Mohammad Hossein , Keshani Parisa , Salehi Alireza , Jaladat Amir Mohammad , Mirzaei Zahra , Nikseresht Alireza 
Published: November 2021

AbstractIntroductionIt remains a matter of debate whether traditional concepts regarding the nature of food affect the development and progression of multiple sclerosis (MS).To date, there are limited studies that have investigated the association between MS and dietary patterns based on the categories of food nature (hot, cold, or balanced) defined in traditional medicine.MethodThis case-control study was conducted from October 2019 to February 2020. In total, 60 patients diagnosed with MS within the preceding 6 months and referred to our neurology outpatient clinic were included in our case group. The control group included 180 patients who were referred to the same center for general or orthopedic surgery. Dietary intake was assessed in both groups through a reliable and valid semi-quantitative food frequency questionnaire. Data were assessed using principal component analysis.ResultsThe mean age of the participants was 44.9 ± 17.33 years. The analysis showed that four food patterns were distinguished (eigenvalue > 1), namely “additives and cold-natured foods”, “hot and balanced foods and nuts”, “dairy and legumes”, and “hot and balanced starches”. These food patterns explained 57.8% of the total variance.After adjusting all confounding factors, individuals in the highest quartile and medium quartile of “additives and cold-natured foods” had an elevated MS risk compared with the lowest quartile (OR = 7.21, 95%CI = 2.01–12.38 and OR = 3.37, 95%CI = 1.02–11.35, respectively). Furthermore, individuals in the highest quartile of the “hot and balanced foods and nuts” group were protected against MS compared with its lowest quartile (OR = 0.28, 95%CI = 0.08–0.90). Moreover, a protective effect against MS was seen in the highest quartile of the “hot and balanced starches” group relative to its lowest quartile (OR = 0.34, 95%CI = 0.12–0.98). No significant association was found between “dairy and legumes” and the risk of MS.ConclusionThis study revealed that dietary patterns based on the traditional concept of food nature might be associated with the risk of developing MS. This represents the first work in this area, so further research is recommended.
Lymphatic leakage after pelvic lymphadenectomy for cervical cancer: a retrospective case-control study
Authors: Chen Li , Lin Liang , Li Ling , Xie Zuolian , He Haixin , Lin Cuibo , Chen Jian , Lin An 
Published: November 2021

Abstract
Background
The study aims to evaluate the clinical features and management of postoperative lymphatic leakage (PLL) in patients with cervical cancer who received pelvic lymphadenectomy.

Methods
This retrospective study screened consecutive patients with cervical cancer (stage Ia2-IIb).

Results
Among 3427 cases screened, 63 patients (1.8%) were diagnosed with PLL, which manifested as persistent abdominal drainage (42/63, 66.7%), chylous ascites (12/63, 19.0%) or vaginal drainage (9/63, 14.3%). Median time from surgery to onset of PLL was 6 days (range, 4–21 days). All cases resolved in a median 10 days (range, 3–56 days) after conservative treatment; although one case experienced recurrence of vaginal drainage after 26 days, this also resolved after conservative therapy. Multivariate analysis showed that two cycles of neoadjuvant chemotherapy (odds ratio [OR], 3.283; 95% confidence interval [95%CI], 1.289–8.360; P = 0.013), a decrease in hemoglobin level of ≥20 and < 30 g/L (OR, 6.175; 95%CI, 1.033–10.919; P = 0.046) or ≥ 30 g/L (OR, 8.467; 95%CI, 1.248–17.426; P = 0.029), and postoperative albumin level ≥ 30 and < 35 g/L (OR, 2.552; 95%CI, 1.112–5.857; P = 0.027) or < 30 g/L (OR, 5.517; 95%CI, 2.047–18.148; P = 0.012) were associated with PLL.

Conclusion
Neoadjuvant chemotherapy, postoperative anemia and postoperative hypoproteinemia are risk factors for PLL.
A novel rat model of interbody fusion based on anterior lumbar corpectomy and fusion (ALCF)
Authors: Kang Yu , Liu Chao , Wang Ming , Wang Cheng , Yan Yi-Guo , Wang Wen-Jun 
Published: November 2021

Abstract
Background
Rats have been widely used as experimental animals when performing fundamental research because they are economical, rapidly reproducing, and heal quickly. While the rat interbody fusion model has been applied in basic studies, existing rat models generally have shortcomings, such as insufficiently simulating clinical surgery. The purpose of this study was to develop a novel rat model of interbody fusion which more closely represents clinical surgery.

Methods
The internal fixation was designed based on physical measurements of the rats’ lumbar spine. Then, ten rats divided into two groups (A and B) underwent anterior lumbar corpectomy and fusion of the L5 vertebrae. Groups A and B were sacrificed four and 8 weeks post-surgery, respectively. Micro-CT and histological examination were used to evaluate the model. Fusion rate, bone volume fraction (BV/TV), trabecular bone number (Tb.N), trabecular bone thickness (Tb.Th), and the area ratio of newly formed bone (NB) were calculated for quantitative analysis.

Results
Based on the L5 body dimensions of individual rats, 3D-printed titanium cage of the appropriate size were printed. The operations were successfully completed in all ten rats, and X-ray confirmed that internal fixation was good without migration. Micro-CT suggested that fusion rates in group B (100%) were greater than group A (40%, P < 0.05). The BV/TV (B: 42.20 ± 10.50 vs. A: 29.02 ± 3.25, P < 0.05) and Tb.N (B: 4.66 ± 1.23 vs. A: 1.97 ± 0.40, P < 0.05) were greater in group B than A, and the Tb.Th in group B was lower than group A (B: 0.10 ± 0.04 vs. A: 0.15 ± 0.02, P < 0.05). Histomorphometry results demonstrated that the area ratio of NB in group B were greater than group A (B: 35.72 ± 12.80 vs. A: 12.36 ± 16.93, P < 0.05).

Conclusion
A rat interbody fusion model based on anterior lumbar corpectomy and fusion has successfully been constructed and verified. It could provide a new choice for fundamental research using animal models of spinal fusion.
State of the practice of health information systems: a survey study amongst health care professionals in intellectual disability care
Authors: Tummers Joep , Tobi Hilde , Schalk Bianca , Tekinerdogan Bedir , Leusink Geraline 
Published: November 2021

Abstract
Background
Care for people with an Intellectual Disability (ID) is complex: multiple health care professionals are involved and use different Health Information Systems (HISs) to store medical and daily care information on the same individuals. The objective of this study is to identify the HISs needs of professionals in ID care by addressing the obstacles and challenges they meet in their current HISs.

Methods
We distributed an online questionnaire amongst Dutch ID care professionals via different professional associations and care providers. 328 respondents answered questions on their HISs. An inventory was made of HIS usage purposes, problems, satisfaction and desired features, with and without stratification on type of HIS and care professional.

Results
Typical in ID care, two types of HISs are being used that differ with respect to their features and users: Electronic Client Dossiers (ECDs) and Electronic Patient Dossiers (EPDs). In total, the respondents mentioned 52 unique HISs. Groups of care professionals differed in their satisfaction with ECDs only. Both HIS types present users with difficulties related to the specifics of care for people with an ID. Particularly the much needed communication between the many unique HISs was reported a major issue which implies major issues with inter-operability. Other problems seem design-related as well.

Conclusion
This study can be used to improve current HISs and design new HISs that take ID care professionals requirements into account.
Pilot study of dogs with suppurative and non-suppurative Malassezia otitis: A case series
Authors: Nunes Rodrigues Tania C. , Vandenabeele Sophie I. 
Published: November 2021

AbstractBackgroundRarely,Malasseziaotitis presents as a painful, erosive otitis with an otic discharge containingMalasseziaand neutrophils on cytology. There are no published reports of this type of suppurativeMalasseziaotitis (SMO). The role ofMalasseziahypersensitivity in otitis is still unknown, and no association has been demonstrated with SMO. We comparedMalasseziaIgE levels, intradermal test and histology changes in SMO dogs with the more conventionalMalasseziaotitis (MO) presentation.ResultsThree dogs (case 1, case 2 and case 3) were diagnosed with SMO, one dog (case 4) was diagnosed with unilateral MO and unilateral SMO, and one dog (case 5) was diagnosed with MO. Only one case (case 4) with SMO/MO had a positive Intradermal Allergy Test (IDAT) and elevated IgE levels forMalassezia. Histopathology findings from SMO revealed: interface dermatitis (case 1 and 3), lymphocytic dermatitis (case 2) and chronic hyperplastic eosinophilic and lymphoplasmacytic dermatitis (case 4). Histopathology findings from MO showed perivascular dermatitis (case 4 and 5). All the cases were treated successfully.ConclusionsSMO presents with a distinct clinical phenotype in comparison with conventional MO. No consistent aetiology could be isolated. In these clinical cases it is possible that previous treatments could have influenced the results. More research is needed to understand the possible aetiologies and the pathogenesis of SMO.
Development and validation of an expanded targeted sequencing panel for non-invasive prenatal diagnosis of sporadic skeletal dysplasia
Authors: Wang Ching-Yuan , Tang Yen-An , Lee I-Wen , Chang Fong-Ming , Chien Chun-Wei , Pan Hsien-An , Sun H. Sunny 
Published: November 2021

Abstract
Background
Skeletal dysplasia (SD) is one of the most common inherited neonatal disorders worldwide, where the recurrent pathogenic mutations in the FGFR2, FGFR3, COL1A1, COL1A2 and COL2A1 genes are frequently reported in both non-lethal and lethal SD. The traditional prenatal diagnosis of SD using ultrasonography suffers from lower accuracy and performed at latter gestational stage. Therefore, it remains in desperate need of precise and accurate prenatal diagnosis of SD in early pregnancy. With the advancements of next-generation sequencing (NGS) technology and bioinformatics analysis, it is feasible to develop a NGS-based assay to detect genetic defects in association with SD in the early pregnancy.

Methods
An ampliseq-based targeted sequencing panel was designed to cover 87 recurrent hotspots reported in 11 common dominant SD and run on both Ion Proton and NextSeq550 instruments. Thirty-six cell-free and 23 genomic DNAs were used for assay developed. Spike-in DNA prepared from standard sample harboring known mutation and normal sample were also employed to validate the established SD workflow. Overall performances of coverage, uniformity, and on-target rate, and the detecting limitations on percentage of fetal fraction and read depth were evaluated.

Results
The established targeted-seq workflow enables a single-tube multiplex PCR for library construction and shows high amplification efficiency and robust reproducibility on both Ion Proton and NextSeq550 platforms. The workflow reaches 100% coverage and both uniformity and on-target rate are > 96%, indicating a high quality assay. Using spike-in DNA with different percentage of known FGFR3 mutation (c.1138 G > A), the targeted-seq workflow demonstrated the ability to detect low-frequency variant of 2.5% accurately. Finally, we obtained 100% sensitivity and 100% specificity in detecting target mutations using established SD panel.

Conclusions
An expanded panel for rapid and cost-effective genetic detection of SD has been developed. The established targeted-seq workflow shows high accuracy to detect both germline and low-frequency variants. In addition, the workflow is flexible to be conducted in the majority of the NGS instruments and ready for routine clinical application. Taken together, we believe the established panel provides a promising diagnostic or therapeutic strategy for prenatal genetic testing of SD in routine clinical practice.
A school-based nutrition education program involving children and their guardians in Japan: facilitation of guardian-child communication and reduction of nutrition knowledge disparity
Authors: Asakura Keiko , Mori Sachie , Sasaki Satoshi , Nishiwaki Yuji 
Published: November 2021

Abstract
Background
Since the risk of noncommunicable diseases is closely associated with dietary intake, it is important to establish healthy dietary habits in childhood. Although several dietary education programs for children have been attempted, their implementation at school was often difficult due to overcrowded study curricula. We developed a new program which included homework for children and guardians, and evaluated its effect. Determinants of the effect were also investigated.

Methods
The school-based nutrition education program including a 45-min lecture, a series of homework assignments involving children and guardians, and two handouts was implemented in 14 public primary schools in Japan. Seven schools each underwent the intervention in an alternating manner. Nutrition knowledge (percentage (%) of correct answers in the nutrition knowledge questionnaire) and attitude/behavior toward diet was evaluated three times (May (baseline), October, February) as outcomes. These factors and their changes following the intervention were assessed by linear mixed models to adjust for individual factors, with consideration to clustering of the participants and repeated measurements.

Results
In total, 2227 children aged 10–12 years and their guardians participated. All schools completed the program. Children’s nutrition knowledge level was significantly increased (8.7%, 95% confidence interval [7.7–9.7]) following the intervention. Communication between children and their guardians, which was positively related with nutrition knowledge, was facilitated by the intervention. The increase in nutrition knowledge was greater among children with a lower knowledge level at baseline.

Conclusions
This school-based nutrition education program was effective and feasible. Appropriate teaching materials for homework can reduce the burden on schools and facilitate communication between children and guardians. Public schools can be crucial venues for decreasing disparities in nutrition knowledge.

Trial registration
This study was registered as an intervention study in the UMIN Clinical Trials Registry (trial ID: UMIN000029252) on Sep 22, 2017.
Fus2Net: a novel Convolutional Neural Network for classification of benign and malignant breast tumor in ultrasound images
Authors: Ma He , Tian Ronghui , Li Hong , Sun Hang , Lu Guoxiu , Liu Ruibo , Wang Zhiguo 
Published: November 2021

AbstractBackgroundThe rapid development of artificial intelligence technology has improved the capability of automatic breast cancer diagnosis, compared to traditional machine learning methods. Convolutional Neural Network (CNN) can automatically select high efficiency features, which helps to improve the level of computer-aided diagnosis (CAD). It can improve the performance of distinguishing benign and malignant breast ultrasound (BUS) tumor images, making rapid breast tumor screening possible.ResultsThe classification model was evaluated with a different dataset of 100 BUS tumor images (50 benign cases and 50 malignant cases), which was not used in network training. Evaluation indicators include accuracy, sensitivity, specificity, and area under curve (AUC) value. The results in the Fus2Net model had an accuracy of 92%, the sensitivity reached 95.65%, the specificity reached 88.89%, and the AUC value reached 0.97 for classifying BUS tumor images.ConclusionsThe experiment compared the existing CNN-categorized architecture, and the Fus2Net architecture we customed has more advantages in a comprehensive performance. The obtained results demonstrated that the Fus2Net classification method we proposed can better assist radiologists in the diagnosis of benign and malignant BUS tumor images.MethodsThe existing public datasets are small and the amount of data suffer from the balance issue. In this paper, we provide a relatively larger dataset with a total of 1052 ultrasound images, including 696 benign images and 356 malignant images, which were collected from a local hospital. We proposed a novel CNN named Fus2Net for the benign and malignant classification of BUS tumor images and it contains two self-designed feature extraction modules. To evaluate how the classifier generalizes on the experimental dataset, we employed the training set (646 benign cases and 306 malignant cases) for tenfold cross-validation. Meanwhile, to solve the balance of the dataset, the training data were augmented before being fed into the Fus2Net. In the experiment, we used hyperparameter fine-tuning and regularization technology to make the Fus2Net convergence.
How different domains of quality of life are associated with latent dimensions of mental health measured by GHQ-12
Authors: Nouri Fatemeh , Feizi Awat , Roohafza Hamidreza , Sadeghi Masoumeh , Sarrafzadegan Nizal 
Published: November 2021

Abstract
Background and objectives
A short form of the General Health Questionnaire (GHQ-12) is a useful screening instrument for assessing mental health. Furthermore, Quality of life (QoL) is a critical treatment outcome in many clinical and health care research settings. This study aimed to reassess the dimensionality of GHQ-12 using Multidimensional Graded Response Model (MGRM) and evaluate how its extracted dimensions are associated with the QoL's domains.

Methods
Isfahan Cohort Study 2 (ICS2) is a population-based, ongoing prospective cohort study among adults aged 35 years and older who were free of cardiovascular diseases (CVDs) at the beginning of the study in 2013. A total of 1316 participants, all living in urban and rural areas of Isfahan and Najafabad, Iran was completed the GHQ-12 and WHO QoL-brief version at baseline. Five competing MGRMs with different latent structures were specified for GHQ-12. Factor scores derived from the best fitted model were used to associate with various domains of QoL. Results: The Three-Dimensional model for GHQ-12 was the best-fitted model explaining the Social Function (SF), Self Confidence (SC), and Anxiety/Depression (A/D) as three correlated yet different latent dimensions of mental health. Our findings in full adjusted multivariate regression models showed that a one-SD increase in dimensions of SC and SF was associated with a 38- to 48%-SD and 27- to 38%-SD increase in the domains scores of QoL, respectively. Moreover, for each one‐SD increase in score of A/D dimension, the domains scores of QoL decreased by 29- to 40%-SD. The highest to the lowest standardized coefficients for all latent dimensions of mental health were respectively related to the psychological, physical health, social relationships, and environmental condition domains of QoL. Furthermore, SC, A/D, and SF dimensions of GHQ-12 showed the highest to the lowest degree of association with all domains of QoL.

Conclusions
Our findings confirm that the GHQ-12 as a multidimensional rather than unitary instrument measures distinct dimensions of mental health. Furthermore, all aspects of QoL changed when the intensity of latent dimensions of mental health increased. Moreover, the psychological domain of QoL is the most affected by all latent dimensions of mental health, followed by physical health, social relationships, and environmental condition domains. It seems that in an attempt to full recovery as assessed by improved QoL outcomes, treatment of clinical symptoms may not be sufficient. Identifying and differentiating the structures of mental health in each community as well as implementing intervention programs aimed at focusing on specific dimensions may help in the prevention of further deterioration of mental health and improved QoL in the community.