bluuebunny/crossref_metadata_2025_split huggingface dataset:
Identification and Quantification of Phenolic Compounds in Grains of Biofortified Cowpea Cultivars, Before and After Cooking
Authors: Anjos Barros Nara Vanessa dos , Abreu Bruna Barbosa de , Sampaio da Silva Débora Thaís , Soares Ana Karine de Oliveira , Rocha Maurisrael de Moura , Reis Moreira-Araújo Regilda Saraiva dos 
Published: September 2019

Objective:This study aimed to identify and quantify phenolic compounds in the grains of biofortified cowpea (Vigna unguiculata) cultivars before and after cooking.Methods:We analyzed two cultivars of genetically improved cowpeas, namely BRS Aracê and BRS Tumucumaque. Raw and cooked samples of the cultivars were analyzed (in triplicate). The concentrations of phenolics, flavonoids, anthocyanins, and flavanols, as well as the antioxidant activity, were determined. Phenolic compounds were identified and quantified using high-performance liquid chromatography.Results:Grains of cultivar BRS Tumucumaque had higher concentrations of total phenolic compounds before (297.23 ± 4.24 (mean ± standard deviation) mg/100 g) and after (147.15 ± 6.94 mg/100 g) cooking, and higher concentrations of total flavonoids before (49.36 ± 2.02 mg/100 g) and after (23.97± 0.67 mg/100 g) cooking. Anthocyanins were not measured in the grains of either cultivars. There was a statistically significant reduction in the concentration of total flavanols after cooking, with the greater retention in BRS Aracê. Similarly, the antioxidant activity was significantly reduced after cooking, with greater reductions in BRS Tumucumaque than in BRS Aracê. Five phenolic acids were identified and quantified, including gallic, caffeic, and ferulic acids.Conclusion:We conclude that cooking affected the concentrations of phenolic compounds in the cultivars, as well as the antioxidant activity exhibited by these cultivars. The cultivars contained beneficial compounds that can contribute to disease prevention and health maintenance.
Imaging Features of Carcinosarcoma Arising from Adenofibroma of the Uterus: A Case Report
Authors: Oh Jiyun , Park Sung Bin , Han Byoung Hee , Kim Hye-Sun , Lee Eun Sun , Park Hyun Jeong 
Published: September 2019

Background:Adenofibroma is a benign tumor composed histologically of epithelial elements and mesenchymal stroma. Carcinosarcoma is a malignant neoplasm that contains elements of carcinoma and sarcoma. Carcinosarcoma arising from adenofibroma of the uterus has never been reported in the literature in English language.Case Presentaion:We report a case of a 56-year-old woman who complained vaginal spotting persisting for several months. We described here for the first time a case of malignant transformation of uterine endometrial adenofibroma into carcinosarcoma that was depicted as a multilocular cystic lesion with enhancing solid portions and stalk-like structure between the myometrium and endometrial mass.
NasalIn-situGel: An Approach to Enhance Therapeutic Benefits of the Drug
Authors: Khatri Kapil , Jain Shikha , Shilpi Satish 
Published: September 2019

Objective::Drug delivery through the nasal route is emerging as a promising approach due to its capability to transport the drug to the systemic circulation and the central nervous system for therapeutic benefits.Methods:In-situ gelling formulations comprising polymeric substances are emerging as preferential nasal drug delivery systems. When exposed to biological stimuli, they have the ability to undergo a solgel conversion.Result:Such mucoadhesive in-situ gel formulations designed and developed for the nasal administration have the ability to prolong the residence time of formulation in the nasal cavity, thereby serving better for complete uptake of the drug across the nasal mucosa.Conclusion:Thus, this review focuses on temperature-responsive, pH-responsive and ion responsive polymers utilized in the nasal in-situ gels together with their physicochemical characterization, evaluation and pharmaceutical applications.
Significant Association of miR-605 rs2043556 with Susceptibility to Breast Cancer
Authors: Kazemi Arezu , Vallian Sadeq 
Published: September 2019

Background:
MicroRNAs (miRNAs) are noncoding RNA molecules, which directly
regulate gene expression. It has been documented that single nucleotide polymorphisms in miRNA
genes could alter the regulation of miRNA expression and function.

Objective:
In this study, the allele and genotype frequency of miR-605 rs2043556 and its association
with breast cancer were investigated in the Iranian population.

Methods:
Genotyping was performed in 162 females affected with breast cancer and 180 healthy individuals.
Genotyping was performed using Restriction Fragment Length Polymorphism (RFLP) followed
by Sanger sequencing.

Results:
The data showed the presence of Hardy Weinberg equilibrium (HWE) for this marker in the
Iranian population. Allelic frequency for A and G allele was 0.75 and 0.25, respectively. Odd ratios
for the association between miR-605 rs2043556 AG/GG genotypes was 3.86 with p-value= 0.

Conclusion:
The results indicated an increased risk for breast cancer susceptibility for miR-605
rs2043556 in the Iranian population.
Developing Machine Learning Algorithms for the Prediction of Early Death in Elderly Cancer Patients: Usability Study
Authors: Sena Gabrielle Ribeiro , Lima Tiago Pessoa Ferreira , Mello Maria Julia Gonçalves , Thuler Luiz Claudio Santos , Lima Jurema Telles Oliveira 
Published: September 2019

Background
The importance of classifying cancer patients into high- or low-risk groups has led many research teams, from the biomedical and bioinformatics fields, to study the application of machine learning (ML) algorithms. The International Society of Geriatric Oncology recommends the use of the comprehensive geriatric assessment (CGA), a multidisciplinary tool to evaluate health domains, for the follow-up of elderly cancer patients. However, no applications of ML have been proposed using CGA to classify elderly cancer patients.

Objective
The aim of this study was to propose and develop predictive models, using ML and CGA, to estimate the risk of early death in elderly cancer patients.

Methods
The ability of ML algorithms to predict early mortality in a cohort involving 608 elderly cancer patients was evaluated. The CGA was conducted during admission by a multidisciplinary team and included the following questionnaires: mini-mental state examination (MMSE), geriatric depression scale-short form, international physical activity questionnaire-short form, timed up and go, Katz index of independence in activities of daily living, Charlson comorbidity index, Karnofsky performance scale (KPS), polypharmacy, and mini nutritional assessment-short form (MNA-SF). The 10-fold cross-validation algorithm was used to evaluate all possible combinations of these questionnaires to estimate the risk of early death, considered when occurring within 6 months of diagnosis, in a variety of ML classifiers, including Naive Bayes (NB), decision tree algorithm J48 (J48), and multilayer perceptron (MLP). On each fold of evaluation, tiebreaking is handled by choosing the smallest set of questionnaires.

Results
It was possible to select CGA questionnaire subsets with high predictive capacity for early death, which were either statistically similar (NB) or higher (J48 and MLP) when compared with the use of all questionnaires investigated. These results show that CGA questionnaire selection can improve accuracy rates and decrease the time spent to evaluate elderly cancer patients.

Conclusions
A simplified predictive model aiming to estimate the risk of early death in elderly cancer patients is proposed herein, minimally composed by the MNA-SF and KPS. We strongly recommend that these questionnaires be incorporated into regular geriatric assessment of older patients with cancer.
Evaluation of Privacy Risks of Patients’ Data in China: Case Study
Authors: Gong Mengchun , Wang Shuang , Wang Lezi , Liu Chao , Wang Jianyang , Guo Qiang , Zheng Hao , Xie Kang , Wang Chenghong , Hui Zhouguang 
Published: September 2019

Background
Patient privacy is a ubiquitous problem around the world. Many existing studies have demonstrated the potential privacy risks associated with sharing of biomedical data. Owing to the increasing need for data sharing and analysis, health care data privacy is drawing more attention. However, to better protect biomedical data privacy, it is essential to assess the privacy risk in the first place.

Objective
In China, there is no clear regulation for health systems to deidentify data. It is also not known whether a mechanism such as the Health Insurance Portability and Accountability Act (HIPAA) safe harbor policy will achieve sufficient protection. This study aimed to conduct a pilot study using patient data from Chinese hospitals to understand and quantify the privacy risks of Chinese patients.

Methods
We used g-distinct analysis to evaluate the reidentification risks with regard to the HIPAA safe harbor approach when applied to Chinese patients’ data. More specifically, we estimated the risks based on the HIPAA safe harbor and limited dataset policies by assuming an attacker has background knowledge of the patient from the public domain.

Results
The experiments were conducted on 0.83 million patients (with data field of date of birth, gender, and surrogate ZIP codes generated based on home address) across 33 provincial-level administrative divisions in China. Under the Limited Dataset policy, 19.58% (163,262/833,235) of the population could be uniquely identifiable under the g-distinct metric (ie, 1-distinct). In contrast, the Safe Harbor policy is able to significantly reduce privacy risk, where only 0.072% (601/833,235) of individuals are uniquely identifiable, and the majority of the population is 3000 indistinguishable (ie the population is expected to share common attributes with 3000 or less people).

Conclusions
Through the experiments based on real-world patient data, this work illustrates that the results of g-distinct analysis about Chinese patient privacy risk are similar to those from a previous US study, in which data from different organizations/regions might be vulnerable to different reidentification risks under different policies. This work provides reference to Chinese health care entities for estimating patients’ privacy risk during data sharing, which laid the foundation of privacy risk study about Chinese patients’ data in the future.
Measuring Regional Quality of Health Care Using Unsolicited Online Data: Text Analysis Study
Authors: Hendrikx Roy Johannus Petrus , Drewes Hanneke Wil-Trees , Spreeuwenberg Marieke , Ruwaard Dirk , Baan Caroline 
Published: September 2019

Background
Regional population management (PM) health initiatives require insight into experienced quality of care at the regional level. Unsolicited online provider ratings have shown potential for this use. This study explored the addition of comments accompanying unsolicited online ratings to regional analyses.

Objective
The goal was to create additional insight for each PM initiative as well as overall comparisons between these initiatives by attempting to determine the reasoning and rationale behind a rating.

Methods
The Dutch Zorgkaart database provided the unsolicited ratings from 2008 to 2017 for the analyses. All ratings included both quantitative ratings as well as qualitative text comments. Nine PM regions were used to aggregate ratings geographically. Sentiment analyses were performed by categorizing ratings into negative, neutral, and positive ratings. Per category, as well as per PM initiative, word frequencies (ie, unigrams and bigrams) were explored. Machine learning—naïve Bayes and random forest models—was applied to identify the most important predictors for rating overall sentiment and for identifying PM initiatives.

Results
A total of 449,263 unsolicited ratings were available in the Zorgkaart database: 303,930 positive ratings, 97,739 neutral ratings, and 47,592 negative ratings. Bigrams illustrated that feeling like not being “taken seriously” was the dominant bigram in negative ratings, while bigrams in positive ratings were mostly related to listening, explaining, and perceived knowledge. Comparing bigrams between PM initiatives showed a lot of overlap but several differences were identified. Machine learning was able to predict sentiments of comments but was unable to distinguish between specific PM initiatives.

Conclusions
Adding information from text comments that accompany online ratings to regional evaluations provides insight for PM initiatives into the underlying reasons for ratings. Text comments provide useful overarching information for health care policy makers but due to a lot of overlap, they add little region-specific information. Specific outliers for some PM initiatives are insightful.
Digital Competencies and Attitudes Toward Digital Adherence Solutions Among Elderly Patients Treated With Novel Anticoagulants: Qualitative Study
Authors: Herrmann Maximilian , Boehme Philip , Hansen Arne , Jansson Katharina , Rebacz Patrick , Ehlers Jan P , Mondritzki Thomas , Truebel Hubert 
Published: September 2019

Background
Nonadherence to medication is a driver of morbidity and mortality, and complex medication regimens in patients with chronic diseases foster the problem. Digital technology might help, but despite numerous solutions being developed, none are currently widely used, and acceptance rates remain low, especially among the elderly.

Objective
This study aimed to better understand and operationalize how new digital solutions can be evaluated. Particularly, the goal was to identify factors that help digital approaches targeting adherence to become more widely accepted.

Methods
A qualitative study using a conceptual grounded theory approach was conducted. We included patients aged 65 years and older who routinely took new oral anticoagulants. To generate theses about the digital competencies of the target group with daily medication intake, face-to-face interviews were conducted, recorded, and anonymized. After coding the interviews, categories were generated, discussed, and combined with several theses until saturation of the statements was reached.

Results
The methodological approach led to the finding that after interviews in 20 of 77 potentially available patients, a saturation of statements was reached. The average patient’s age was 75 years, and 50% (10/20) of the subjects were female. The data identified five main coding categories—Diseases and medicine, Technology, Autonomy, Patient narrative, and Attitude toward technologies—each including positive and negative subcategories. Main categories and subcategories were summarized as Adherence Radar, which can be considered as a framework to assess the potential of adherence solutions in the process of prototyping and can be applied to all adherence tools in a holistic manner.

Conclusions
The Adherence Radar can be used to increase the acceptance rate of digital solutions targeting adherence. For a patient-centric design, an app should be adapted to the individual patient’s needs. According to our results, this application should be based on gender and educational background as well as the individual physician-patient relationship. If used in a proper, individualized manner, digital adherence solutions could become a new cornerstone for the treatment of chronically ill individuals.
A Telehealth-Delivered Pulmonary Rehabilitation Intervention in Underserved Hispanic and African American Patients With Chronic Obstructive Pulmonary Disease: A Community-Based Participatory Research Approach
Authors: Pekmezaris Renee , Kozikowski Andrzej , Pascarelli Briana , Wolf-Klein Gisele , Boye-Codjoe Eugenia , Jacome Sonia , Madera Danielle , Tsang Donna , Guerrero Brenda , Medina Richard , Polo Jennifer , Williams Myia , Hajizadeh Negin 
Published: September 2019

Background
Although home telemonitoring (TM) is a promising approach for patients managing their chronic disease, rehabilitation using home TM has not been tested for use with individuals living with chronic obstructive pulmonary disease (COPD) residing in underserved communities.

Objective
This study aimed to analyze qualitative data from focus groups with key stakeholders to ensure the acceptability and usability of the TM COPD intervention.

Methods
We utilized a community-based participatory research (CBPR) approach to adapt a home TM COPD intervention to facilitate acceptability and feasibility in low-income African American and Hispanic patients. The study engaged community stakeholders in the process of modifying the intervention in the context of 2 community advisory board meetings. Discussions were audio recorded and professionally transcribed and lasted approximately 2 hours each. Structural coding was used to mark responses to topical questions in interview guides.

Results
We describe herein the formative process of a CBPR study aimed at optimizing telehealth utilization among African American and Latino patients with COPD from underserved communities. A total of 5 major themes emerged from qualitative analyses of community discussions: equipment changes, recruitment process, study logistics, self-efficacy, and access. The identification of themes was instrumental in understanding the concerns of patients and other stakeholders in adapting the pulmonary rehabilitation (PR) home intervention for acceptability for patients with COPD from underserved communities.

Conclusions
These findings identify important adaptation recommendations from the stakeholder perspective that should be considered when implementing in-home PR via TM for underserved COPD patients.

Trial Registration
ClinicalTrials.gov NCT03007485; https://clinicaltrials.gov/ct2/show/NCT03007485
Adverse Events Due to Insomnia Drugs Reported in a Regulatory Database and Online Patient Reviews: Comparative Study
Authors: Borchert Jill S , Wang Bo , Ramzanali Muzaina , Stein Amy B , Malaiyandi Latha M , Dineley Kirk E 
Published: September 2019

Background
Patient online drug reviews are a resource for other patients seeking information about the practical benefits and drawbacks of drug therapies. Patient reviews may also serve as a source of postmarketing safety data that are more user-friendly than regulatory databases. However, the reliability of online reviews has been questioned, because they do not undergo professional review and lack means of verification.

Objective
We evaluated online reviews of hypnotic medications, because they are commonly used and their therapeutic efficacy is particularly amenable to patient self-evaluation. Our primary objective was to compare the types and frequencies of adverse events reported to the Food and Drug Administration Adverse Event Reporting System (FAERS) with analogous information in patient reviews on the consumer health website Drugs.com. The secondary objectives were to describe patient reports of efficacy and adverse events and assess the influence of medication cost, effectiveness, and adverse events on user ratings of hypnotic medications.

Methods
Patient ratings and narratives were retrieved from 1407 reviews on Drugs.com between February 2007 and March 2018 for eszopiclone, ramelteon, suvorexant, zaleplon, and zolpidem. Reviews were coded to preferred terms in the Medical Dictionary for Regulatory Activities. These reviews were compared to 5916 cases in the FAERS database from January 2015 to September 2017.

Results
Similar adverse events were reported to both Drugs.com and FAERS. Both resources identified a lack of efficacy as a common complaint for all five drugs. Both resources revealed that amnesia commonly occurs with eszopiclone, zaleplon, and zolpidem, while nightmares commonly occur with suvorexant. Compared to FAERS, online reviews of zolpidem reported a much higher frequency of amnesia and partial sleep activities. User ratings were highest for zolpidem and lowest for suvorexant. Statistical analyses showed that patient ratings are influenced by considerations of efficacy and adverse events, while drug cost is unimportant.

Conclusions
For hypnotic medications, online patient reviews and FAERS emphasized similar adverse events. Online reviewers rated drugs based on perception of efficacy and adverse events. We conclude that online patient reviews of hypnotics are a valid source that can supplement traditional adverse event reporting systems.
Four Dissemination Pathways for a Social Media–Based Breastfeeding Campaign: Evaluation of the Impact on Key Performance Indicators
Authors: Harding Kassandra , Pérez-Escamilla Rafael , Carroll Grace , Aryeetey Richmond , Lasisi Opeyemi 
Published: September 2019

Background
Social media utilization is on the rise globally, and the potential of social media for health behavior campaigns is widely recognized. However, as the landscape of social media evolves, so do techniques used to optimize campaign dissemination.

Objective
The primary aim of this study was to evaluate the impact of 4 material dissemination paths for a breastfeeding social media marketing campaign in Ghana on exposure and engagement with campaign material.

Methods
Campaign materials (n=60) were posted to a Facebook and Twitter campaign page over 12 weeks (ie, baseline). The top 40 performing materials were randomized to 1 of 4 redissemination arms (control simply posted on each platform, key influencers, random influencers, and paid advertisements). Key performance indicator data (ie, exposure and engagement) were extracted from both Facebook and Twitter 2 days after the material was posted. A difference-in-difference model was used to examine the impact of the dissemination paths on performance.

Results
At baseline, campaign materials received an average (SD) exposure of 1178 (670) on Facebook and 1071 (905) on Twitter (n=60). On Facebook, materials posted with paid advertisements had significantly higher exposure and engagement compared with the control arm (P<.001), and performance of materials shared by either type of influencer did not differ significantly from the control arm. No differences in Twitter performance were detected across arms.

Conclusions
Paid advertisements are an effective mechanism to increase exposure and engagement of campaign posts on Facebook, which was achieved at a low cost.