bluuebunny/crossref_metadata_2025_split huggingface dataset:
Bacterial DNA Diversity among Clear and Cloudy Sakes, and Sake-kasu
Authors: Terasaki Momoka , Nishida Hiromi 
Published: August 2020

Background:
The traditional Japanese alcoholic drink, sake, is classified into two types: those that contain sediment produced during the production process (cloudy sakes) and those that do not contain such sediment (clear sakes). Leftover pressed sediment from the sake production process, sake-kasu (sake cake or sake lees), is commercially available and is highly nutritious for humans.

Objective:
The purpose of this study was to determine the difference among component bacterial DNA sequences of clear and cloudy sakes, and sake-kasu.

Methods:
We compared the 16S rDNA sequences from 44 samples of clear sake, 3 samples of cloudy sake, and 11 samples of sake-kasu.

Results:
The DNA sequences were divided into three major clusters; however, sequences in sake-kasu were located in just one cluster forming two lineages. The microbial diversity in sake-kasu was lower than that in clear and cloudy sakes, which may be because some of the contaminating bacterial cells do not lyse during the production process and remain intact, along with yeast cells, in sake-kasu.

Conclusion:
Bacterial DNA frequently detected in sake samples was from environmental bacterial contamination that occurs early in the sake production process. Contaminating bacteria are usually killed by the ethanol produced as the sake yeast grows; after which, if bacteria lyse, the bacterial DNA is released into the sake solution. However, if the bacterial cells do not lyse, they will precipitate toward the sediment. Thus, there is bacterial DNA diversity in clear and cloudy sake, but less diversity in sake-kasu.
Development and validation of an RP-HPLC method for the simultaneous determination of total withanolide glycosides and Withaferin A in Withania somnifera (Ashwagandha)
Authors: Antony Benny , Benny Merina , Kuruvilla Binu T. , Sebastian Anu , Aravindakshan Pillai Anu Aravind , Joseph Biji , Edappattu Chandran Sheeja 
Published: August 2020

Background:
Withanolide glycosides in Ashwagandha (Withania somnifera), are important
metabolites attributed with widely acclaimed therapeutic potential for which validated methods
for quantitative determination are limited.

Objective:
The primary objective was to develop and validate a Reversed-Phase High Performance
Liquid Chromatography (RP-HPLC) method for simultaneous quantification of total withanolide
glycosides (WG), withanoside IV and withaferin A present in ashwagandha extract.The study also
aimed to identify various other constituents present in the extract.

Materials and Methods:
Aqueous methanol extract (AME) of Ashwagandha was prepared and fractionated
into two viz. flavonoid rich fraction (FF) and withanolide rich fraction (WF). RP-HPLC
method was developed and validated for the estimation of total WG in ashwagandha extract according
to ICH guidelines. Preparative HPLC based purification of major compounds from WF fraction
was carried out and constituents were identified using spectroscopic techniques. HPLC chemical
profiling of WF before and after acid hydrolysis under controlled conditions was carried out to further
confirm the glycosidic compounds.

Results and Discussion:
The RP-HPLC method gave a precise differentiation of flavonoids, withanolides
and WG present in ashwagandha extract. The method demonstrated good reliability and
sensitivity, and can be conveniently used for the quantification of total WG, withanoside IV and
withaferin A present in ashwagandha extracts. According to this method, a purified fraction (WF)
prepared from roots and leaves of Ashwagandha comprise 35% of total WG, 3.27% of withanoside
IV and 2.40% of Withaferin A. The method was also applied to different products prepared from
Ashwagandha with total withanolide glycosides ranged from 1.5% to 60%, and the results were
found to be reproducible. Identification of the individual chemical constituents as well as the acid
hydrolytic pattern of the extract further supported the reliability of the developed method for the
quantitative determination of total WG. This study also reported a new withanolide glycoside
named, cilistol V-6’-O-glucoside (Aswanoside) along with some other known withanolide glycosides.

Conclusion:
A Reversed-Phase High Performance Liquid Chromatography (RP-HPLC) method
was developed and validated for the quantitative determination of total WG, withanoside IV and
withaferin A present in ashwagandha extract according to ICH guidelines. This study also reported
a new withanolide glycoside named, cilistol V-6’-O-glucoside (Aswanoside) along with some
other known WG.
COVID-19: A Review on Epidemiology, Clinical Features and Possible Potential Drugs Based on Available Case Studies
Authors: Badgujar Kirtikumar C. , Patil Dipak V. , Dhangar Dipak V. , Patil Vikrant P. , Badgujar Ashish B. 
Published: August 2020

:The emerging novel coronavirus disease 2019 has caused a global outbreak and significant public health concern. The World Health Organization (WHO) has announced a coronavirus disease outbreak a pandemic with a global public health emergency of international concern. As of now, 12th April 2020 almost 18,37,404 cases have been confirmed globally (in 209 countries) with almost 1,13,274 fatalities. This increasing number has created anxiety throughout the world, which has severely affected the whole world's culture, societies, behavioral patterns, peace and economics. At present, research on novel coronavirus is in the preliminary stage. There is no vaccine or specific antiviral to treat coronavirus disease. Also, very few case studies are available; hence it has become difficult to treat and to control this pandemic situation. In view of this, the present systematic review is done to highlight clinical epidemiology features, radiographic characteristics, and potential drugs based on available clinical case reports. Biomarkers for early diagnosis and impact of age, sex, pre-existing comorbidity on COVID-19 is also discussed. Further, this paper also outlines various possible antiviral chemical drug agents that can be potential and promising to treat this coronavirus disease in 2019. This review may be helpful for the medical practitioner, public health workers and government authorities to manage and deal with novel coronavirus disease 2019.
XML Data and Knowledge-Encoding Structure for a Web-Based and Mobile Antenatal Clinical Decision Support System: Development Study
Authors: Torres Silva Ever Augusto , Uribe Sebastian , Smith Jack , Luna Gomez Ivan Felipe , Florez-Arango Jose Fernando 
Published: August 2020

Background
Displeasure with the functionality of clinical decision support systems (CDSSs) is considered the primary challenge in CDSS development. A major difficulty in CDSS design is matching the functionality to the desired and actual clinical workflow. Computer-interpretable guidelines (CIGs) are used to formalize medical knowledge in clinical practice guidelines (CPGs) in a computable language. However, existing CIG frameworks require a specific interpreter for each CIG language, hindering the ease of implementation and interoperability.

Objective
This paper aims to describe a different approach to the representation of clinical knowledge and data. We intended to change the clinician’s perception of a CDSS with sufficient expressivity of the representation while maintaining a small communication and software footprint for both a web application and a mobile app. This approach was originally intended to create a readable and minimal syntax for a web CDSS and future mobile app for antenatal care guidelines with improved human-computer interaction and enhanced usability by aligning the system behavior with clinical workflow.

Methods
We designed and implemented an architecture design for our CDSS, which uses the model-view-controller (MVC) architecture and a knowledge engine in the MVC architecture based on XML. The knowledge engine design also integrated the requirement of matching clinical care workflow that was desired in the CDSS. For this component of the design task, we used a work ontology analysis of the CPGs for antenatal care in our particular target clinical settings.

Results
In comparison to other common CIGs used for CDSSs, our XML approach can be used to take advantage of the flexible format of XML to facilitate the electronic sharing of structured data. More importantly, we can take advantage of its flexibility to standardize CIG structure design in a low-level specification language that is ubiquitous, universal, computationally efficient, integrable with web technologies, and human readable.

Conclusions
Our knowledge representation framework incorporates fundamental elements of other CIGs used in CDSSs in medicine and proved adequate to encode a number of antenatal health care CPGs and their associated clinical workflows. The framework appears general enough to be used with other CPGs in medicine. XML proved to be a language expressive enough to describe planning problems in a computable form and restrictive and expressive enough to implement in a clinical system. It can also be effective for mobile apps, where intermittent communication requires a small footprint and an autonomous app. This approach can be used to incorporate overlapping capabilities of more specialized CIGs in medicine.
A Systematic Framework for Analyzing Observation Data in Patient-Centered Registries: Case Study for Patients With Depression
Authors: Zolnoori Maryam , Williams Mark D , Leasure William B , Angstman Kurt B , Ngufor Che 
Published: August 2020

Background
Patient-centered registries are essential in population-based clinical care for patient identification and monitoring of outcomes. Although registry data may be used in real time for patient care, the same data may further be used for secondary analysis to assess disease burden, evaluation of disease management and health care services, and research. The design of a registry has major implications for the ability to effectively use these clinical data in research.

Objective
This study aims to develop a systematic framework to address the data and methodological issues involved in analyzing data in clinically designed patient-centered registries.

Methods
The systematic framework was composed of 3 major components: visualizing the multifaceted and heterogeneous patient-centered registries using a data flow diagram, assessing and managing data quality issues, and identifying patient cohorts for addressing specific research questions.

Results
Using a clinical registry designed as a part of a collaborative care program for adults with depression at Mayo Clinic, we were able to demonstrate the impact of the proposed framework on data integrity. By following the data cleaning and refining procedures of the framework, we were able to generate high-quality data that were available for research questions about the coordination and management of depression in a primary care setting. We describe the steps involved in converting clinically collected data into a viable research data set using registry cohorts of depressed adults to assess the impact on high-cost service use.

Conclusions
The systematic framework discussed in this study sheds light on the existing inconsistency and data quality issues in patient-centered registries. This study provided a step-by-step procedure for addressing these challenges and for generating high-quality data for both quality improvement and research that may enhance care and outcomes for patients.

International Registered Report Identifier (IRRID)
DERR1-10.2196/18366
Patient Portal Barriers and Group Differences: Cross-Sectional National Survey Study
Authors: Turner Kea , Clary Alecia , Hong Young-Rock , Alishahi Tabriz Amir , Shea Christopher M 
Published: August 2020

Background
Past studies examining barriers to patient portal adoption have been conducted with a small number of patients and health care settings, limiting generalizability.

Objective
This study had the following two objectives: (1) to assess the prevalence of barriers to patient portal adoption among nonadopters and (2) to examine the association between nonadopter characteristics and reported barriers in a nationally representative sample.

Methods
Data from this study were obtained from the 2019 Health Information National Trends Survey. We calculated descriptive statistics to determine the most prevalent barriers and conducted multiple variable logistic regression analysis to examine which characteristics were associated with the reported barriers.

Results
The sample included 4815 individuals. Among these, 2828 individuals (58.73%) had not adopted a patient portal. Among the nonadopters (n=2828), the most prevalent barriers were patient preference for in-person communication (1810/2828, 64.00%), no perceived need for the patient portal (1385/2828, 48.97%), and lack of comfort and experience with computers (735/2828, 25.99%). Less commonly, individuals reported having no patient portal (650/2828, 22.98%), no internet access (650/2828, 22.98%), privacy concerns (594/2828, 21.00%), difficulty logging on (537/2828, 18.99%), and multiple patient portals (255/2828, 9.02%) as barriers. Men had significantly lower odds of indicating a preference for speaking directly to a provider compared with women (odds ratio [OR] 0.75, 95% CI 0.60-0.94; P=.01). Older age (OR 1.01, 95% CI 1.00-1.02; P<.001), having a chronic condition (OR 1.83, 95% CI 1.44-2.33; P<.001), and having an income lower than US $20,000 (OR 1.61, 95% CI 1.11-2.34; P=.01) were positively associated with indicating a preference for speaking directly to a provider. Hispanic individuals had significantly higher odds of indicating that they had no need for a patient portal (OR 1.59, 95% CI 1.24-2.05; P<.001) compared with non-Hispanic individuals. Older individuals (OR 1.05, 95% CI 1.04-1.06; P<.001), individuals with less than a high school diploma (OR 3.15, 95% CI 1.79-5.53; P<.001), and individuals with a household income of less than US $20,000 (OR 2.78, 95% CI 1.88-4.11; P<.001) had significantly higher odds of indicating that they were uncomfortable with a computer.

Conclusions
The most common barriers to patient portal adoption are preference for in-person communication, not having a need for the patient portal, and feeling uncomfortable with computers, which are barriers that are modifiable and can be intervened upon. Patient characteristics can help predict which patients are most likely to experience certain barriers to patient portal adoption. Further research is needed to tailor implementation approaches based on patients’ needs and preferences.
Evaluation of a Mobile App to Enhance Relational Awareness and Change During Cognitive Analytic Therapy: Mixed Methods Case Series
Authors: Kellett Stephen , Easton Katherine , Cooper Martin , Millings Abigail , Simmonds-Buckley Melanie , Parry Glenys 
Published: August 2020

Background
There has been a lack of technological innovation regarding improving the delivery of integrative psychotherapies. This project sought to evaluate an app designed to replace previous paper-based methods supporting relational awareness and change during cognitive analytic therapy (CAT).

Objective
We aimed to assess patients’ and therapists’ experience of using the technology (ie, the “CAT-App”) and to evaluate the relationship between app usage and clinical outcome.

Methods
The design was a mixed methods case series. Patients completed the Clinical Outcomes in Routine Evaluation-Outcome Measure pre- and post-CAT. Mood data plus the frequency and effectiveness of relational awareness and change were collected via the app. Therapists and patients were interviewed about their experiences using the app.

Results
Ten patients (treated by 3 therapists) were enrolled; seven completed treatment and 4 had a reliable improvement in their mental health. App usage and mood change did not differ according to clinical outcome, but there was a statistically significant difference in app usage between completers and dropouts. The qualitative themes described by the therapists were (1) the challenge of incorporating the technology into their clinical practice and (2) the barriers and benefits of the technology. Clients’ themes were (1) data protection, (2) motivation and engagement, and (3) restrictions versus flexibility.

Conclusions
The CAT-App is capable of supporting relational awareness and change and is an upgrade on older, paper-based formats. Further clinical evaluation is required.
Improving Provision of Preanesthetic Information Through Use of the Digital Conversational Agent “MyAnesth”: Prospective Observational Trial
Authors: Ferré Fabrice , Boeschlin Nicolas , Bastiani Bruno , Castel Adeline , Ferrier Anne , Bosch Laetitia , Muscari Fabrice , Kurrek Matt , Fourcade Olivier , Piau Antoine , Minville Vincent 
Published: August 2020

BackgroundDue to time limitations, the preanesthetic consultation (PAC) is not the best time for patients to integrate information specific to their perioperative care pathway.ObjectiveThe main objectives of this study were to evaluate the effectiveness of a digital companion on patients' knowledge of anesthesia and their satisfaction after real-life implementation.MethodsWe conducted a prospective, monocentric, comparative study using a before-and-after design. In phase 1, a 9-item self-reported anesthesia knowledge test (Delphi method) was administered to patients before and after their PAC (control group: PAC group). In phase 2, the study was repeated immediately after the implementation of a digital conversational agent, MyAnesth (@+PAC group). Patients’ satisfaction and their representations for anesthesia were also assessed using a Likert scale and the Abric method of hierarchized evocation.ResultsA total of 600 tests were distributed; 205 patients and 98 patients were included in the PAC group and @+PAC group, respectively. Demographic characteristics and mean scores on the 9-point preinformation test (PAC group: 4.2 points, 95% CI 3.9-4.4; @+PAC: 4.3 points, 95% CI 4-4.7; P=.37) were similar in the two groups. The mean score after receiving information was better in the @+PAC group than in the PAC group (6.1 points, 95% CI 5.8-6.4 points versus 5.2 points, 95% CI 5.0-5.4 points, respectively; P<.001), with an added value of 0.7 points (95% CI 0.3-1.1; P<.001). Among the respondents in the @+PAC group, 82% found the information to be clear and appropriate, and 74% found it easily accessible. Before receiving information, the central core of patients’ representations for anesthesia was focused on the fear of being put to sleep and thereafter on caregiver skills and comfort.ConclusionsThe implementation of our digital conversational agent in addition to the PAC improved patients' knowledge about their perioperative care pathway. This innovative audiovisual support seemed clear, adapted, easily accessible, and reassuring. Future studies should focus on adapting both the content and delivery of a digital conversational agent for the PAC in order to maximize its benefit to patients.
Prognostic Machine Learning Models for First-Year Mortality in Incident Hemodialysis Patients: Development and Validation Study
Authors: Sheng Kaixiang , Zhang Ping , Yao Xi , Li Jiawei , He Yongchun , Chen Jianghua 
Published: August 2020

Background
The first-year survival rate among patients undergoing hemodialysis remains poor. Current mortality risk scores for patients undergoing hemodialysis employ regression techniques and have limited applicability and robustness.

Objective
We aimed to develop a machine learning model utilizing clinical factors to predict first-year mortality in patients undergoing hemodialysis that could assist physicians in classifying high-risk patients.

Methods
Training and testing cohorts consisted of 5351 patients from a single center and 5828 patients from 97 renal centers undergoing hemodialysis (incident only). The outcome was all-cause mortality during the first year of dialysis. Extreme gradient boosting was used for algorithm training and validation. Two models were established based on the data obtained at dialysis initiation (model 1) and data 0-3 months after dialysis initiation (model 2), and 10-fold cross-validation was applied to each model. The area under the curve (AUC), sensitivity (recall), specificity, precision, balanced accuracy, and F1 score were used to assess the predictive ability of the models.

Results
In the training and testing cohorts, 585 (10.93%) and 764 (13.11%) patients, respectively, died during the first-year follow-up. Of 42 candidate features, the 15 most important features were selected. The performance of model 1 (AUC 0.83, 95% CI 0.78-0.84) was similar to that of model 2 (AUC 0.85, 95% CI 0.81-0.86).

Conclusions
We developed and validated 2 machine learning models to predict first-year mortality in patients undergoing hemodialysis. Both models could be used to stratify high-risk patients at the early stages of dialysis.
Formulation and Evaluation of New Dosage Form of Calcium and Vitamin D
Authors: Sharma Satish Kumar , Singh Anand , Bhandari Anil , Singh Sudhir 
Published: August 2020

The aim of the research work was to develop a new dosage form (tablet in tablet) of calcium and vitamin D. In this research work vitamin D3 was used as vitamin D. This type of dosage form is very useful for elder people and children who have a week swallowing reflex. They have difficulty in swallowing tablets with water. In the present research work, pre-formulated and evaluated chewable tablets of calcium and vitamin D3 (from Formulation and Evaluation of Chewable Tablets of Calcium and Vitamin D) were taken and then moulded into a jelly like material under specified conditions of temperature and humidity and a new dosage form was developed which is sweet, flavored and chewable dosage form (tablet in tablet). The new dosage form was subjected to various tests for evaluation of the new dosage form.
In Vitro Assessment of Some Brands of Fluconazole Capsules Marketed in Port Harcourt, Nigeria
Authors: Nkemakolam Nwachukwu , C Ugoeze Kenneth , Oluigbo Kennedy Emeka 
Published: August 2020

Objectives: A routine in vitro pharmacopeial quality assessment of five brands of fluconazole capsules with label claims of 50.0 mg marketed in Port Harcourt, Nigeria was carried out to ascertain their consistencies.
Methods: The brands were procured from various pharmacies in Port Harcourt and coded Fluco-A, Fluco-B, Fluco-C, Fluco-D and Fluco-E. Visual assessments of the samples were carried out besides in vitro quality considerations such as identification of the active pharmaceutical ingredient (API), capsules uniformity of weight, disintegration, an assay of the total content of fluconazole and dissolution studies.
Results: Each brand contained fluconazole with relevant product packet information uncompromisingly conspicuous.The label claims for fluconazole contents were satisfactory. The weight variation of the capsulesacross the brands were between 170.25 mg ± 2.25% -333.14 mg ± 1.50 %. Each brand disintegrated within 10 min. Total drug content was within 88.43 ± 0.12% to 102.96 ± 0.53 %.Above 80.0% of fluconazole was released within 30.0 min in the release studies of the respective brands.
Conclusion: The results obtained for the capsules uniformity of weight, disintegration time, the total content of the API and the drug release profiles were within acceptable limits of the United States Pharmacopoeia (USP).