bluuebunny/crossref_metadata_2025_split huggingface dataset:
Applying systems approaches to stakeholder and community engagement and knowledge mobilisation in youth mental health system modelling
Authors: Freebairn Louise , Song Yun Ju Christine , Occhipinti Jo-An , Huntley Samantha , Dudgeon Pat , Robotham Julie , Lee Grace Yeeun , Hockey Samuel , Gallop Geoff , Hickie Ian B. 
Published: April 2022

Abstract
Background
There is a significant push to change the trajectory of youth mental ill-health and suicide globally. Ensuring that young people have access to services that meet their individual needs and are easily accessible is a priority. Genuine stakeholder engagement in mental health system design is critical to ensure that system strengthening is likely to be successful within these complex environments. There is limited literature describing engagement processes undertaken by research teams in mental health program implementation and planning. This protocol describes the methods that will be used to engage local communities using systems science methods to mobilize knowledge and action to strengthen youth mental health services.

Methods
Using participatory action research principles, the research team will actively engage with local communities to ensure genuine user-led participatory systems modelling processes and enhance knowledge mobilisation within research sites. Ensuring that culturally diverse and Aboriginal and Torres Strait Islander community voices are included will support this process. A rigorous site selection process will be undertaken to ensure that the community is committed and has capacity to actively engage in the research activities. Stakeholder engagement commences from the site selection process with the aim to build trust between researchers and key stakeholders. The research team will establish a variety of engagement resources and make opportunities available to each site depending on their local context, needs and audiences they wish to target during the process.

Discussion
This protocol describes the inclusive community engagement and knowledge mobilization process for the Right care, first time, where you live research Program. This Program will use an iterative and adaptive approach that considers the social, economic, and political context of each community and attempts to maximise research engagement. A theoretical framework for applying systems approaches to knowledge mobilization that is flexible will enable the implementation of a participatory action research approach. This protocol commits to a rigorous and genuine stakeholder engagement process that can be applied in mental health research implementation.
Management of depression during the perinatal period: state of the evidence
Authors: Falek Idan , Acri Mary , Dominguez Joanna , Havens Jennifer , McCord Mary , Sisco Sarah , Wilcox Wendy , Hoagwood Kimberly 
Published: April 2022

Abstract
Background
Perinatal depression (PND) is a prevalent ailment that affects both the woman and her family. Addressing PND in primary health care, such as pediatrics and obstetric care settings, has been proposed as an effective way to identify and treat women.

Objective
The purpose of this study is to examine best practices for management of PND in obstetric and pediatric settings, as well as investigate the evidence that supports the guidelines.

Methods
Guidelines were identified through a literature search and discussion with experts in the field of perinatal depression, while evidence was examined through a literature search of reviews and thereafter experimental studies.

Results
Twenty-five guidelines, across 17 organizations were retained for analysis. Findings suggest that there is little or varied guidance on the management of PND, as well as a lack of specificity. Treatment was the topic most frequently reported, followed by screening. However best practices vary greatly and often contradict one another. Across all areas, there is inadequate or contrasting evidence to support these guidelines.

Conclusions
Although there was consensus on the key steps in the pathway to care, the review revealed lack of consensus across guidelines on specific issues relating to identification and management of depression during the perinatal period. Clinicians may use these recommendations to guide their practice, but they should be aware of the limitations of the evidence supporting these guidelines and remain alert to new evidence. There is a clear need for researchers and policymakers to prioritize this area in order to develop evidence-based guidelines for managing perinatal depression.
Identification of RNA-splicing factor Lsm12 as a novel tumor-associated gene and a potent biomarker in Oral Squamous Cell Carcinoma (OSCC)
Authors: Dong Yan , Xue Liyan , Zhang Yan , Liu Caiyun , Zhang Yanguang , Jiang Na , Ma Xiaoyan , Chen Fangyu , Li Lingxia , Yu Liyuan , Liu Xuefeng , Shao Shujuan , Guan Shufang , Zhang Jian , Xiao Qingchun , Li Hui , Dong Ailing , Huang Lijie , Shi Chenyang , Wang Yan , Fu Ming , Lv Ning , Zhan Qimin 
Published: April 2022

Abstract
Background
Oral squamous cell carcinoma (OSCC) is one of the common cancers worldwide. The lack of specific biomarkers and therapeutic targets leads to delayed diagnosis and hence the poor prognosis of OSCC patients. Thus, it is urgent to identify effective biomarkers and therapeutic targets for OSCC.

Methods
We established the golden hamster carcinogenic model of OSCC induced by 7,12-dimethylbenz(a) anthrancene (DMBA) and used mRNA microarrays to detect the differentially expressed genes (DEGs). DEGs were validated in OSCC clinical tissue microarrays using immunohistochemistry method. Whole transcriptome sequencing was performed to obtain an overview of biological functions of Lsm12. PCR assay and sequencing were employed to investigate the alternative splicing of genes regulated by Lsm12. Cell proliferation, colony formation, Transwell migration and invasion assay and in vivo tumor formation assay were performed to investigate the roles of Lsm12 and two transcript variants of USO1 in OSCC cells.

Results
Lsm12 was identified to be significantly up-regulated in the animal model of OSCC tumorigenesis, which was validated in the clinical OSCC samples. In the paired normal tissues, Lsm12 staining was negative (91%, 92/101) or weak, while in OSCC tissues, positive rate is 100% and strong staining spread over the whole tissues in 93 (93/101, 92%) cases. Lsm12 overexpression significantly promoted OSCC cell growth, colony formation, migration and invasion abilities, while Lsm12 knockdown showed the opposite trends on these phenotypes and obviously inhibited the tumor formation in vivo. Furthermore, Lsm12 overexpression caused the inclusion of USO1 exon 15 and Lsm12 knockdown induced exon 15 skipping. Exon 15-retained USO1 significantly promoted the malignant phenotypes of OSCC cells when compared with the exon 15-deleted USO1.

Conclusions
We identified Lsm12, a novel tumorigenesis-related gene, as an important regulator involved in OSCC tumorigenesis. Lsm12 is a novel RNA-splicing related gene and can regulate the alternative splicing of USO1 exon 15 which was associated closely with OSCC carcinogenesis. Our findings thus provide that Lsm12 might be a potent biomarker and potential therapeutic target for OSCC.
CDK16 promotes the progression and metastasis of triple-negative breast cancer by phosphorylating PRC1
Authors: Li Xiao , Li Jinpeng , Xu Liming , Wei Wei , Cheng Anyi , Zhang Lingxian , Zhang Mengna , Wu Gaosong , Cai Cheguo 
Published: April 2022

Abstract
Background
Cyclin-dependent kinase 16 (CDK16) is an atypical PCTAIRE kinase, and its activity is dependent on the Cyclin Y (CCNY) family. Ccnys have been reported to regulate mammary stem cell activity and mammary gland development, and CCNY has been recognized as an oncoprotein in various cancers, including breast cancer. However, it remains unclear whether CDK16 has a role in breast cancer and whether it can be used as a therapeutic target for breast cancer.

Methods
Publicly available breast cancer datasets analyses and Kaplan-Meier survival analyses were performed to reveal the expression and clinical relevance of atypical CDKs in breast cancer. CDK16 protein expression was further examined by immunohistochemical and immunoblot analyses of clinical samples. Cell proliferation was measured by colony formation and MTT analyses. Cell cycle and apoptosis were examined by fluorescence-activated cell sorting (FACS) analysis. Wound-healing and trans-well invasion assays were conducted to test cell migration ability. The functions of CDK16 on tumorigenesis and metastasis were evaluated by cell line-derived xenograft, patient-derived organoid/xenograft, lung metastasis and systemic metastasis mouse models. Transcriptomic analysis was performed to reveal the potential molecular mechanisms involved in the function of CDK16. Pharmacological inhibition of CDK16 was achieved by the small molecular inhibitor rebastinib to further assess the anti-tumor utility of targeting CDK16.

Results
CDK16 is highly expressed in breast cancer, particularly in triple-negative breast cancer (TNBC). The elevated CDK16 expression is correlated with poor outcomes in breast cancer patients. CDK16 can improve the proliferation and migration ability of TNBC cells in vitro, and promote tumor growth and metastasis of TNBC in vivo. Both genetic knockdown and pharmacological inhibition of CDK16 significantly suppress the tumor progression of TNBC. Mechanistically, CDK16 exerts its function by phosphorylating protein regulator of cytokinesis 1 (PRC1) to regulate spindle formation during mitosis.

Conclusion
CDK16 plays a critical role in TNBC and is a novel promising therapeutic target for TNBC.
Publication of clinical trials on medicinal products: follow-up on trials authorized in Hungary
Authors: Sándor-Bajusz Kinga Amália , Kraut Andrea , Baasan Odgerel , Márovics Gergely , Berényi Károly , Lohner Szimonetta 
Published: April 2022

Abstract
Background
Clinical research should provide reliable evidence to clinicians, health policy makers, and researchers. The reliability of evidence will be assured once study planning, conducting, and reporting of results are transparent. The present research investigates publication rates, time until publication, and characteristics of clinical trials on medicinal products associated with timely publication of results, measures of scientific impact, authorship, and open access publication.

Methods
Clinical trials authorized in Hungary in 2012 were followed until publication and/or June 2020. Corresponding scientific publications were searched via clinical trial registries, PubMed (MEDLINE), and Google.

Results
Overall, 330 clinical trials were authorized in 2012 of which 232 trials were completed for more than 1 year in June 2020. The proportion of industry initiation was high (97%).
Time to publication was 21 (22) months [median (IQR)]. Time to publication was significantly shorter when trials involved both European and non-European countries (26 vs 69 months [median]; hazard ratio = 0.38, 95% CI 0.22–0.66, p< 0.001), and were registered in both EU CTR and clinicaltrials.gov (27 vs 88 months; hazard ratio = 0.24, 95% CI 0.11–0.54; p< 0.001) based on survival analyses.
A significant amount (24.1%) of unpublished clinical trial results were accessible in a trial register. The majority of available publications were published “open access” (70.93%). A minority of identified publications had a Hungarian author (21.5%).

Conclusions
We encourage academic researchers to plan, register and conduct trials on medicinal products. Registries should be considered as an important source of information of clinical trial results. Publications with domestic co-authors contribute to the research output of a country. Measurable domestic scientific impact of trials on medicinal products needs further improvement.
Records and altitudinal assessment of Amblyomma aureolatum and Amblyomma ovale (Acari: Ixodidae) in the State of Rio de Janeiro, southeast Brazil
Authors: Faccini João L. H. , Santos Hélio F. , Costa-Junior Lívio M. , Costa-Neto Socrates F. , Tassinari Wagner S. , Luz Hermes R. 
Published: April 2022

AbstractInformation on the altitudinal distribution of the hard ticks Amblyomma aureolatum and Amblyomma ovale in Brazil is scarce and mainly limited to occasional records. In this study we report our evaluation of records on the altitudinal distribution of A. aureolatum and A. ovale collected from dogs and humans and directly from the environment (host-questing ticks), based on active or passive procedures. The collections were conducted in rural areas of municipalities in the state of Rio de Janeiro, Brazil between 2013 and 2017. Active procedures consisted of dragging or flagging, visual examination of vegetation and removal of ticks present on the authors’ clothing or on infested dogs. Overall, 222 ticks were collected. The altitudes at the collection sites ranged from 98 to 1220 m a.s.l. We noted a significant difference in the altitudinal distribution of A. aureolatum and A. ovale (Mann–Whitney U-test, U = 518.5, P < 0.001). The overlap of these two species occurred at altitudes of between 650 and 900 m a.s.l. The results indicated that the higher the altitude, the greater the probability for the occurrence of A. aureolatum and, conversely, the lower the likelihood for the occurrence of A. ovale. The findings of this study improve currrent knowledge on the bioecology of these tick species and have implications for studies on the epidemiology of spotted fever in Brazil.
Graphical Abstract
Ancylostoma in dogs in the Caribbean: a review and study from St. Kitts, West Indies
Authors: Kim Jenny , Lucio-Forster Araceli , Ketzis Jennifer K. 
Published: April 2022

Abstract
Background
Little is known about the prevalence of Ancylostoma in dogs in the Caribbean. In view of the number of owned free-roaming and feral dogs within the islands and the ideal subtropical climate for parasite development and environmental survival, Ancylostoma could pose a threat to the health of the dogs as well as a zoonotic risk to people.

Methods
To determine whether generalities about Ancylostoma in dogs in the Caribbean could be made and to obtain a better understanding of the prevalence, published (Scielo, Scopus, and PubMed databases) and gray (e.g., student theses, conference presentations) literature was reviewed. Retrieved manuscripts were screened, and relevant data (year, location, dog population, method of diagnosis, positivity rate) were extracted. Data from two dog populations on St. Kitts also were included: a 2014 field study involving dogs with limited veterinary care and data from the Ross University School of Veterinary Medicine’s Veterinary Clinic records for 2018–2019.

Results
Fourteen manuscripts from the 1950s to 2019, representing ten of the Caribbean islands/countries and the Bahamas, were identified. Methods of diagnosing infection status ranged from simple qualitative or quantitative flotation methods to centrifugation with Sheather’s sugar flotation solution or necropsy. Dog populations sampled included stray, owned free-roaming, and owned confined. Reported rates of Ancylostoma infection ranged from 10 to 91%. Studies from the last 10 years indicate positivity rates of 21 to 73%. Ancylostoma positivity rates in the St. Kitts’ populations were 61% and 10% for the 2014 and 2018–2019 populations, respectively.

Conclusions
There was no indication that hookworm prevalence has changed over time in the Caribbean, and there were no obvious differences between owned and unowned dogs or free-roaming and confined dogs. The data from St. Kitts were on par with positivity rates from the other islands within the last 10 years and reflective of the impact that veterinary care, including anthelmintic treatment, is expected to have on parasites in pets. There is a clear need to expand the available data for the region and improve control programs for Ancylostoma infections to protect both canine and human health.

Graphical Abstract
An evaluation of information online on artificial intelligence in medical imaging
Authors: Mulryan Philip , Ni Chleirigh Naomi , O’Mahony Alexander T. , Crowley Claire , Ryan David , McLaughlin Patrick , McEntee Mark , Maher Michael , O’Connor Owen J. 
Published: April 2022

Abstract
Background
Opinions seem somewhat divided when considering the effect of artificial intelligence (AI) on medical imaging. The aim of this study was to characterise viewpoints presented online relating to the impact of AI on the field of radiology and to assess who is engaging in this discourse.

Methods
Two search methods were used to identify online information relating to AI and radiology. Firstly, 34 terms were searched using Google and the first two pages of results for each term were evaluated. Secondly, a Rich Search Site (RSS) feed evaluated incidental information over 3 weeks. Webpages were evaluated and categorized as having a positive, negative, balanced, or neutral viewpoint based on study criteria.

Results
Of the 680 webpages identified using the Google search engine, 248 were deemed relevant and accessible. 43.2% had a positive viewpoint, 38.3% a balanced viewpoint, 15.3% a neutral viewpoint, and 3.2% a negative viewpoint. Peer-reviewed journals represented the most common webpage source (48%), followed by media (29%), commercial sources (12%), and educational sources (8%). Commercial webpages had the highest proportion of positive viewpoints (66%). Radiologists were identified as the most common author group (38.9%). The RSS feed identified 177 posts of which were relevant and accessible. 86% of posts were of media origin expressing positive viewpoints (64%).

Conclusion
The overall opinion of the impact of AI on radiology presented online is a positive one. Consistency across a range of sources and author groups exists. Radiologists were significant contributors to this online discussion and the results may impact future recruitment.
Radiology–pathology correlation of endometrial carcinoma assessment on magnetic resonance imaging
Authors: Dokter Eveline , Anderson Lyndal , Cho Soo-Min , Cohen-Hallaleh Violette , Lam Kim May , Saidi Samir A. , Kitzing Yu Xuan 
Published: April 2022

AbstractEndometrial carcinoma is the most common gynaecological cancer in developed countries. Most cases are low-volume/low-grade tumour at presentation; however, high-grade subtypes may present with locally advanced disease with higher propensity for spread outside of the pelvis. MRI has a role in local staging of the tumour and helping the clinicians in treatment decision making. This pictorial essay gives examples of endometrial carcinoma at different stages with histological correlation. It also explores the potential limitations and pitfalls of imaging in this context.
Applying the FAIR principles to data in a hospital: challenges and opportunities in a pandemic
Authors: Queralt-Rosinach Núria , Kaliyaperumal Rajaram , Bernabé César H. , Long Qinqin , Joosten Simone A. , van der Wijk Henk Jan , Flikkenschild Erik L.A. , Burger Kees , Jacobsen Annika , Mons Barend , Roos Marco ,   BEAT-COVID Group,   COVID-19 LUMC Group
Published: April 2022

Abstract
Background
The COVID-19 pandemic has challenged healthcare systems and research worldwide. Data is collected all over the world and needs to be integrated and made available to other researchers quickly. However, the various heterogeneous information systems that are used in hospitals can result in fragmentation of health data over multiple data ‘silos’ that are not interoperable for analysis. Consequently, clinical observations in hospitalised patients are not prepared to be reused efficiently and timely. There is a need to adapt the research data management in hospitals to make COVID-19 observational patient data machine actionable, i.e. more Findable, Accessible, Interoperable and Reusable (FAIR) for humans and machines. We therefore applied the FAIR principles in the hospital to make patient data more FAIR.

Results
In this paper, we present our FAIR approach to transform COVID-19 observational patient data collected in the hospital into machine actionable digital objects to answer medical doctors’ research questions. With this objective, we conducted a coordinated FAIRification among stakeholders based on ontological models for data and metadata, and a FAIR based architecture that complements the existing data management. We applied FAIR Data Points for metadata exposure, turning investigational parameters into a FAIR dataset. We demonstrated that this dataset is machine actionable by means of three different computational activities: federated query of patient data along open existing knowledge sources across the world through the Semantic Web, implementing Web APIs for data query interoperability, and building applications on top of these FAIR patient data for FAIR data analytics in the hospital.

Conclusions
Our work demonstrates that a FAIR research data management plan based on ontological models for data and metadata, open Science, Semantic Web technologies, and FAIR Data Points is providing data infrastructure in the hospital for machine actionable FAIR Digital Objects. This FAIR data is prepared to be reused for federated analysis, linkable to other FAIR data such as Linked Open Data, and reusable to develop software applications on top of them for hypothesis generation and knowledge discovery.
MFVT: an anomaly traffic detection method merging feature fusion network and vision transformer architecture
Authors: Li Ming , Han Dezhi , Li Dun , Liu Han , Chang Chin-Chen 
Published: April 2022

AbstractNetwork intrusion detection, which takes the extraction and analysis of network traffic features as the main method, plays a vital role in network security protection. The current network traffic feature extraction and analysis for network intrusion detection mostly uses deep learning algorithms. Currently, deep learning requires a lot of training resources and has weak processing capabilities for imbalanced datasets. In this paper, a deep learning model (MFVT) based on feature fusion network and vision transformer architecture is proposed, which improves the processing ability of imbalanced datasets and reduces the sample data resources needed for training. Besides, to improve the traditional raw traffic features extraction methods, a new raw traffic features extraction method (CRP) is proposed, and the CPR uses PCA algorithm to reduce all the processed digital traffic features to the specified dimension. On the IDS 2017 dataset and the IDS 2012 dataset, the ablation experiments show that the performance of the proposed MFVT model is significantly better than other network intrusion detection models, and the detection accuracy can reach the state-of-the-art level. And, when MFVT model is combined with CRP algorithm, the detection accuracy is further improved to 99.99%.