bluuebunny/crossref_metadata_2025_split huggingface dataset:
Concurrent müllerianosis of the urinary bladder and the umbilicus presenting with umbilical bleeding: a rare case report and review of the literature
Authors: Jhang Syu , Chen Marcelo , Chen Li-Chen 
Published: April 2020

Abstract
Background
Müllerianosis is a very rare neoplasm composed of two or three Müllerian derived tissues (endosalpinx, endometrium and endocervix). We report the first case of concurrent müllerianosis of the urinary bladder and the umbilicus presenting with umbilical bleeding.

Case presentation
A 43-year-old Asian premesopausal female, gravida 1, para 1, presented with intermittent umbilical bleeding. An umbilical nodule and a bladder tumor on the posterior wall of the urinary bladder were identified. She underwent transurethral resection of the bladder tumor and excision of the umbilical nodule successively. Diagnosis of müllerianosis was confirmed by the histological and immunological features. No tumor recurrence was noted at 6 months of follow-up.

Conclusions
Müllerianosis is extremely rare and mainly reported in the urinary bladder, and generally affects women of reproductive age. Despite the common presentations of müllerianosis of the urinary bladder including irritative voiding symptoms, abdominal/pelvic pain and gross hematuria, our rare case had no symptom except umbilical bleeding. The possibility of concurrent bladder müllerianosis should be considered when müllerianosis is found at other location. We suggest a surgical intervention to establish the correct pathological diagnosis because it is essential to exclude malignant neoplasms of the urinary bladder. The majority of patients have a favorable prognosis.
Evaluating users’ experiences of electronic prescribing systems in relation to patient safety: a mixed methods study
Authors: Aufegger Lisa , Serou Naresh , Chen Shiping , Franklin Bryony Dean 
Published: April 2020

Abstract
Background
User interface (UI) design features such as screen layout, density of information, and use of colour may affect the usability of electronic prescribing (EP) systems, with usability problems previously associated with medication errors. To identify how to improve existing systems, our aim was to explore prescribers’ perspectives of UI features of a commercially available EP system, and how these may affect patient safety.

Methods
Two studies were conducted, each including ten participants prescribing a penicillin for a test patient with a penicillin allergy. In study 1, eye-gaze tracking was used as a means to explore visual attention and behaviour during prescribing, followed by a self-reported EP system usability scale. In study 2, a think-aloud method and semi-structured interview were applied to explore participants’ thoughts and views on prescribing, with a focus on UI design and patient safety.

Results
Study 1 showed high visual attention toward information on allergies and patient information, allergy pop-up alerts, and medication order review and confirmation, with less visual attention on adding medication. The system’s usability was rated ‘below average’. In study 2, participants highlighted EP design features and workflow, including screen layout and information overload as being important for patient safety, benefits of EP systems such as keeping a record of relevant information, and suggestions for improvement in relation to system design (colour, fonts, customization) and patient interaction.

Conclusions
Specific UI design factors were identified that may improve the usability and/or safety of EP systems. It is suggested that eye-gaze tracking and think-aloud methods are used in future experimental research in this area. Limitations include the small sample size; further work should include similar studies on other EP systems.
Understanding the association between caregiver sex and HIV infection among orphans and vulnerable children in Tanzania: learning from the USAID Kizazi Kipya project
Authors: Exavery Amon , Charles John , Kuhlik Erica , Barankena Asheri , Koler Alison , Kikoyo Levina , Jere Elizabeth 
Published: April 2020

Abstract
Background
Tanzania has met only 50.1% of the 90% target for diagnosing HIV in children. The country’s pediatric case finding strategy uses global best practices of index testing, provider-initiated counselling and testing, and targeted community testing of at-risk populations to find about 50,000 children living with HIV (CLHIV) who are undiagnosed. However, context-specific strategies are necessary to find the hidden children to meet the full 90% target. This study assesses whether sex of the caregiver is associated with HIV status of orphans and vulnerable children (OVC) as a valuable strategy for enhanced pediatric case findings.

Methods
Data originate from the community-based, United States Agency for International Development (USAID)-funded Kizazi Kipya Project, which works towards increasing OVC’s and their caregivers’ uptake of HIV/AIDS and other health and social services in Tanzania. Included in this study are 39,578 OVC ages 0–19 years who the project enrolled during January through March 2017 in 18 regions of Tanzania and who voluntarily reported their HIV status. Data analysis involved multi-level logistic regression, with OVC HIV status as the outcome of interest and caregiver’s sex as the main independent variable.

Results
Three-quarters (74.3%) of the OVC included in the study had female caregivers, and their overall HIV prevalence was 7.1%. The prevalence was significantly higher (p < 0.001) among OVC with male caregivers (7.8%) than among OVC with female caregivers (6.8%), and indeed, multivariate analysis showed that OVC with male caregivers were significantly 40% more likely to be HIV-positive than those with female caregivers (OR = 1.40, 95% CI 1.08–1.83). This effect was the strongest among 0–4 year-olds (OR = 4.02, 95% CI 1.61–10.03), declined to 1.72 among 5–9 year-olds (OR = 1.72, 95% CI 1.02–2.93), and lost significance for children over age 9 years. Other significant factors included OVC age and nutritional status; caregiver HIV status and marital status; household health insurance status, and family size; and rural versus urban residence.

Conclusions
OVC in Tanzania with male caregivers have a 40% higher likelihood of being HIV-positive than those with female caregivers. HIV risk assessment activities should target OVC with male caregivers, as well as OVC who have malnutrition, HIV-positive caregivers, or caregivers who do not disclose their HIV status to community volunteers. Further, younger HIV-positive OVC are more likely to live in rural areas, while older HIV-positive OVC are more likely to live in urban areas. These factors should be integrated in HIV risk assessment algorithms to enhance HIV testing yields and pediatric case-finding in the OVC population in Tanzania.
Practice, perceived barriers and motivating factors to medical-incident reporting: a cross-section survey of health care providers at Mbarara regional referral hospital, southwestern Uganda
Authors: Naome Turyahabwe , James Mwesigwa , Christine Atuhairwe , Mugisha Taremwa Ivan 
Published: April 2020

AbstractBackgroundMedical-incident reporting (MIR) ensures patient safety and delivery of quality of care by minimizing unintentional harm among health care providers. We explored medical-incident reporting practices, perceived barriers and motivating factors among health care providers at Mbarara Regional Referral Hospital (MRRH).MethodsWe conducted a cross-sectional descriptive study on 158 health provider at Mbarara Regional Referral Hospital (MRRH), Western Uganda. Data was gathered using a structured questionnaire and analyzed with SPSS. The chi-square was used to determine factors associated with MIR at MRRH.ResultsThe results showed that there was no formal incident reporting structure. However the medical-incidences identified were: medication errors (89.9%), diagnostic errors (71.5%), surgical errors (52.5%) and preventive error (47.7%). The motivating factors of MIR were: establishment of a good communication system, instituting corrective action on the reported incidents and reinforcing health workers knowledge on MIR (p-value 0.004); presence of effective organizational systems like: written guidelines, practices of open door policy, no blame approach, and team work were significantly associated with MIR (p-value 0.000). On the other hand, perceived barriers to MIR were: lack of knowledge on incidents and their reporting, non-existence of an incident reporting team and fear of being punished (p- value 0.669).ConclusionMedical Incident Reporting at MRRH was sub-optimal. Therefore setting up an incident management team and conducting routine training MIR among health care workers will increase patient safety.
Trends in anticoagulant prescribing: a review of local policies in English primary care
Authors: Ho Katherine H. , van Hove Maria , Leng Gillian 
Published: April 2020

Abstract
Background
Oral anticoagulants are prescribed for stroke prophylaxis in patients with atrial fibrillation, which is the most common heart arrhythmia worldwide. The vitamin K antagonist (VKA) warfarin is a long-established anticoagulant. However, newer direct oral anticoagulants (DOACs) have been recently introduced as an alternative. Given the prevalence of atrial fibrillation, anticoagulant choice has substantial clinical and financial implications for healthcare systems. In this study, we explore trends and geographic variation in anticoagulant prescribing in English primary care. Because national guidelines in England do not specify a first-line anticoagulant, we investigate the association between local policies and prescribing data.

Methods
Primary care prescribing data of anticoagulants for all NHS practices from 2014 to 2019 in England was obtained from the ePACT2 database. Public formularies were accessed online to obtain local anticoagulation prescribing policies for 89.5% of clinical commissioning groups (CCGs). These were categorized according to their recommendations: no local policies, warfarin as first-line, or identification of a preferred DOAC (but not a preferred anticoagulant). Local policies were cross-tabulated with pooled prescribing data to measure the strength of association with Cramér’s V.

Results
Nationally, prescribing of DOACs increased from 9% of all anticoagulants in 2014 to 74% in 2019, while that of warfarin declined accordingly. Still, there was significant local variation. Across geographical regions, DOACs ranged from 53 to 99% of all anticoagulants. Most CCGs (73%) did not specify a first-line choice, and 16% recommended warfarin first line. Only 11% designated a preferred DOAC. Policies with a preferred DOAC indeed correlated with increased prescribing of that DOAC (Cramér’s V = 0.25, 0.27, 0.38 for rivaroxaban, apixaban, edoxaban respectively). However, local policies showed a negligible relationship with the classes of anticoagulants prescribed—DOAC or VKA (Cramér’s V = 0.01).

Conclusions
Nationally, the use of DOACs to treat atrial fibrillation has increased rapidly. Despite this, significant geographical variation in uptake remains. This study provides insights on how local policies relate to this variation. Our findings suggest that, in the absence of a nationally recommended first-line anticoagulant, local prescribing policies may aid in deciding between individual DOACs, but not in adjudicating between DOACs and vitamin K antagonists (i.e. warfarin) as general classes.
Comparative evaluation of network features for the prediction of breast cancer metastasis
Authors: Adnan Nahim , Liu Zhijie , Huang Tim H.M. , Ruan Jianhua 
Published: April 2020

AbstractBackgroundDiscovering a highly accurate and robust gene signature for the prediction of breast cancer metastasis from gene expression profiling of primary tumors is one of the most challenging tasks to reduce the number of deaths in women. Due to the limited success of gene-based features in achieving satisfactory prediction accuracy, many methodologies have been proposed in recent years to develop network-based features by integrating network information with gene expression. However, evaluation results are inconsistent to confirm the effectiveness of network-based features, because of many confounding factors involved in classification model learning process, such as data normalization, dimension reduction, and feature selection. An unbiased comparative evaluation is essential for uncovering the strength of network-based features.MethodsIn this study, we compared several types of network-based features obtained using different mathematical operators (Mean, Maximum, Minimum, Median, Variance) on geneset (i.e., a gene and its’ neighbors in the network) in protein-protein interaction network and gene co-expression network for their ability in predicting breast cancer metastasis using gene expression data from more than 10 patient cohorts.ResultsWhile network-based features are usually statistically more significant than gene-based feature, a consistent improvement of prediction performance using network-based features requires a substantial number of patients in the dataset. In contrary to many previous reports, no evidence was found to support the robustness of network-based features and we argue some of the robustness may be due to the inherent bias associated with node degree in the network. In addition, different types of network features seem to cover different pathways and are complementary to each other. Consequently, an ensemble classifier combining different network features was proposed and was found to significantly outperform classifiers based on gene-based feature or any single type of network-based features.ConclusionsNetwork-based features and their combination show promise for improving the prediction of breast cancer metastasis but may require a large amount of training data. Robustness claim of network-based features needs to be re-examined with network node degree and other confounding factors in consideration.
A pan-cancer study of class-3 semaphorins as therapeutic targets in cancer
Authors: Zhang Xiaoli , Klamer Brett , Li Jin , Fernandez Soledad , Li Lang 
Published: April 2020

Abstract
Background
Initially characterized as axon guidance factors, semaphorins also have been implicated to have critical roles in multiple physiological and developmental functions, including the regulation of immune responses, angiogenesis, organ formation, and the etiology of multiple forms of cancer. Moreover, their contribution in immunity and the regulation of tumour microenvironment is becoming increasingly recognized. Here, we provide a comprehensive analysis of class-3 semaphorins, the only secreted family of genes among veterbrate semaphorins, in terms of their expression profiles and their association with patient survival. We also relate their role with immune subtypes, tumour microenvironment, and drug sensitivity using a pan-cancer study.

Results
Expression profiles of class-3 semaphorins (SEMA3s) and their association with patient survival and tumour microenvironment were studied in 31 cancer types using the TCGA pan-cancer data. The expression of SEMA3 family varies in different cancer types with striking inter- and intra- cancer heterogeneity. In general, our results show that SEMA3A, SEMA3C, and SEMA3F are primarily upregulated in cancer cells, while the rest of SEMA3s are mainly down-regulated in the tested tumours. The expression of SEMA3 family members was frequently associated with patient overall survival. However, the direction of the association varied with regards to the particular SEMA3 isoform queried and the specific cancer type tested. More specifically, SEMA3A and SEMA3E primarily associate with a poor prognosis of survival, while SEMA3G typically associates with survival advantage. The rest of SEMA3s show either survival advantage or disadvantage dependent on cancer type. In addition, all SEMA3 genes show significant association with immune infiltrate subtypes, and they also correlate with level of stromal cell infiltration and tumour cell stemness with various degrees. Finally, our study revealed that SEMA3 genes, especially SEMA3C and SEMA3F may contribute to drug induced cancer cell resistance.

Conclusions
Our systematic analysis of class-3 semaphorin gene expression and their association with immune infiltrates, tumour microenvironment and cancer patient outcomes highlights the need to study each SEMA3 member as a separate entity within each specific cancer type. Also our study validated the identification of class-3 semaphorin signals as promising therapeutic targets in cancer although further laboratory validation still needed.
ProGeo-neo: a customized proteogenomic workflow for neoantigen prediction and selection
Authors: Li Yuyu , Wang Guangzhi , Tan Xiaoxiu , Ouyang Jian , Zhang Menghuan , Song Xiaofeng , Liu Qi , Leng Qibin , Chen Lanming , Xie Lu 
Published: April 2020

AbstractBackgroundNeoantigens can be differentially recognized by T cell receptor (TCR) as these sequences are derived from mutant proteins and are unique to the tumor. The discovery of neoantigens is the first key step for tumor-specific antigen (TSA) based immunotherapy. Based on high-throughput tumor genomic analysis, each missense mutation can potentially give rise to multiple neopeptides, resulting in a vast total number, but only a small percentage of these peptides may achieve immune-dominant status with a given major histocompatibility complex (MHC) class I allele. Specific identification of immunogenic candidate neoantigens is consequently a major challenge.Currently almost all neoantigen prediction tools are based on genomics data.ResultsHere we report the construction of proteogenomics prediction of neoantigen (ProGeo-neo) pipeline, which incorporates the following modules: mining tumor specific antigens from next-generation sequencing genomic and mRNA expression data, predicting the binding mutant peptides to class I MHC molecules by latest netMHCpan (v.4.0), verifying MHC-peptides by MaxQuant with mass spectrometry proteomics data searched against customized protein database, and checking potential immunogenicity of T-cell-recognization by additional screening methods. ProGeo-neo pipeline achieves proteogenomics strategy and the neopeptides identified were of much higher quality as compared to those identified using genomic data only.ConclusionsThe pipeline was constructed based on the genomics and proteomics data of Jurkat leukemia cell line but is generally applicable to other solid cancer research. With massively parallel sequencing and proteomics profiling increasing, this proteogenomics workflow should be useful for neoantigen oriented research and immunotherapy.
Somatic synonymous mutations in regulatory elements contribute to the genetic aetiology of melanoma
Authors: Zhang Di , Xia Junfeng 
Published: April 2020

Abstract
Background
Non-synonymous mutations altering tumor suppressor genes and oncogenes are widely studied. However, synonymous mutations, which do not alter the protein sequence, are rarely investigated in melanoma genome studies.

Methods
We explored the role of somatic synonymous mutations in melanoma samples from TCGA (The Cancer Genome Atlas). The pathogenic synonymous mutation and neutral synonymous mutation data were used to assess the significance of pathogenic synonymous mutations in melanoma likely to affect genetic regulatory elements using Fisher’s exact test. Poisson distribution probabilities of each gene were used to mine the genes with multiple potential functional synonymous mutations affecting regulatory elements.

Results
Concentrating on five types of genetic regulatory functions, we found that the mutational patterns of pathogenic synonymous mutations are mostly involved in exonic splicing regulators in near-splicing sites or inside DNase I hypersensitivity sites or non-optimal codon. Moreover, the sites of miRNA binding alteration exhibit a significantly lower rate of evolution than other sites. Finally, 12 genes were hit by recurrent potentially functional synonymous mutations, which showed statistical significance in the pathogenic mutations. Among them, nine genes (DNAH5, ADCY8, GRIN2A, KSR2, TECTA, RIMS2, XKR6, MYH1, SCN10A) have been reported to be mutated in melanoma, and other three genes (SLC9A2, CASR, SLC8A3) have a great potential to impact melanoma.

Conclusion
These findings confirm the functional consequences of somatic synonymous mutations in melanoma, emphasizing the significance of research in future studies.
Deep learning-based cancer survival prognosis from RNA-seq data: approaches and evaluations
Authors: Huang Zhi , Johnson Travis S. , Han Zhi , Helm Bryan , Cao Sha , Zhang Chi , Salama Paul , Rizkalla Maher , Yu Christina Y. , Cheng Jun , Xiang Shunian , Zhan Xiaohui , Zhang Jie , Huang Kun 
Published: April 2020

AbstractBackgroundRecent advances in kernel-based Deep Learning models have introduced a new era in medical research. Originally designed for pattern recognition and image processing, Deep Learning models are now applied to survival prognosis of cancer patients. Specifically, Deep Learning versions of the Cox proportional hazards models are trained with transcriptomic data to predict survival outcomes in cancer patients.MethodsIn this study, a broad analysis was performed on TCGA cancers using a variety of Deep Learning-based models, including Cox-nnet, DeepSurv, and a method proposed by our group named AECOX (AutoEncoder with Cox regression network). Concordance index andp-value of the log-rank test are used to evaluate the model performances.ResultsAll models show competitive results across 12 cancer types. The last hidden layers of the Deep Learning approaches are lower dimensional representations of the input data that can be used for feature reduction and visualization. Furthermore, the prognosis performances reveal a negative correlation between model accuracy, overall survival time statistics, and tumor mutation burden (TMB), suggesting an association among overall survival time, TMB, and prognosis prediction accuracy.ConclusionsDeep Learning based algorithms demonstrate superior performances than traditional machine learning based models. The cancer prognosis results measured in concordance index are indistinguishable across models while are highly variable across cancers. These findings shedding some light into the relationships between patient characteristics and survival learnability on a pan-cancer level.