bluuebunny/crossref_metadata_2025_split huggingface dataset:
Diet, Physical Activity, and Emotional Health: What Works, What Doesn’t, and Why We Need Integrated Solutions for Total Worker Health
Authors: Syed Iffath Unissa 
Published: August 2019

Abstract
Objectives: Current research advocates lifestyle factors to manage workers’ health issues, such as obesity, metabolic syndrome, and type II diabetes mellitus, among other things (World Health Organization (WHO), 2000; WHO, 2016), though little is known about employees’ lifestyle factors in high-stress, high turnover environments, such as in the long term care (“LTC”) sector. Methods: Drawing on qualitative single-case study in Ontario, Canada, this paper investigates an under-researched area consisting of the health practices of health care workers from high-stress, high turnover environments. In particular, it identifies LTC worker’s mechanisms for maintaining physical, emotional, and social wellbeing. Results: The findings suggest that while particular mechanisms were prevalent, such as through diet and exercise, they were often conducted in group settings or tied to emotional health, suggesting important social and mental health contexts to these behaviors. Furthermore, there were financial barriers that prevented workers from participating in these activities and achieving health benefits. Conclusion: Accordingly, this study advocates integrated, total worker health (TWH) initiatives that consider social determinants of health approaches, recognizing the wider socio-economic impacts of workers’ health and wellbeing.
The effect of early antenatal booking on adherence to Iron/folic acid supplementation among antenatal care attendees in Libo kemkem district, Ethiopia
Authors: liyeh Tewachew Muche , Goshu Yitayal Ayalew , Ayele Amare Simegn , Abebe Yibeltal 
Published: August 2019

Abstract
Background

Iron and folic acid supplementation is the feasible and cost effective strategy to control and prevent anemia in pregnancy. Pregnant women are vulnerable for iron deficiency anemia due to increased nutrient requirement during pregnancy. In Ethiopia, the national data suggests that from all pregnant women supplemented with these tablets, only 5.1% consumed more than 90 tablets during their pregnancy time. The factors for this low adherence are not clearly known.
Objective: To assess factors associated with adherence to iron-folic acid supplementation among pregnant women attending antenatal care service in Libo Kemkem district, Ethiopia 2017.

Method: Hospital based cross sectional study was conducted using quantitative methods on 406 pregnant women attending antenatal care at Libo Kemkem district public health institutions. Systematic random sampling method was used. An interview with pre tested semi structured questionnaire was carried out. The collected data was entered in Epi data 4.1 and analyzed with SPSS version 20. Bivariate and multivariable logistic regression model were used. Odds ratio with 95% interval was computed and P- value <0.05% considered as level of significance.

Result: About 406 respondents were included in the study. The adherence rate of iron-folic acid supplementation was 49.3% (95% CI= 44.3%-54.2%). Factors significantly associated with adherence to iron-folic acid utilization were urban residence (AOR =4.8, 95% CI=1.82-12.79), women aged 21-30 (AOR = 4.3, 95% CI=1.60-11.42) ,women aged 31-40 (AOR =4.2, 95% CI=1.33-13.41),early ANC booking (AOR =4.1, 95% CI=1.80-9.30) and getting medical advice (AOR = 2.5, 95% CI = 1.04 – 6.16). Fear of side effects, forgetfulness and too many pills were the major reasons for missing the doses of tablets.

Conclusion: adherence rate of iron and folic acid supplementation was low. Residence, maternal age, early ANC booking and getting medical advice were significantly associated with adherence to iron and folic acid.

Key Words: Iron-folic acid, pregnant women and adherence
Prevalence and predictors of self-medication among University students in Ethiopia: A systematic review and Meta-analysis
Authors: Fetensa Getahun , Tolossa Tadesse , Ebi Werku Etafa 
Published: August 2019

Abstract
Background

Self-medication is the global issue especially on those having access and education about medication irrespective of its side effect. It has a significant impact on resistance and medication-related complication. There are limited and inconsistent studies regarding self-medication practice in Ethiopia. The aim of this systematic review and meta-analysis was to estimates the pooled prevalence of self-medication and its predictors among Ethiopian university students.

Method

A systematic review and meta-analysis were conducted to assess the prevalence and predictors of self-medication among university students in Ethiopia. We searched literature from the databases of Medline, Hinari, Scopes, PubMed CINAHL, PopLine, MedNar, Embase, Cochrane library, the JBI Library, the Web of Science, Google Scholar and manual search. A total of nine studies reporting the prevalence of self-medication among university students were included. Data were extracted using a standardized data extraction format prepared in Microsoft Excel and the analysis was done using STATA 14 statistical software. To assess heterogeneity, I2 test was used since the included studies exhibit high heterogeneity, a random effect meta-analysis model was computed to estimate the pooled prevalence of self-medication. In another way, the association between predictor variables, and self-medication practice were examined.

Result

A total of 3513 study respondents from nine studies in Ethiopia published between 2010-2017 were included in the study. The result of our study reveals that a pooled prevalence of self-medication among university students was 45.61% (95%CI: 30.66, 60.57). Included studies have a sample size ranged from 250 to 548 with lowest prevalence (19.81%) of self-medication from University of Gondar, whereas the highest prevalence (77.01%) recorded in a study conducted at Arsi University.

Conclusion

Prevalence of Ethiopian university students was 45.61%, which is very high with the current global health problem with Anti-microbial resistance increment and other toxicity. In addition to this in this study, the association between self-medication and year of study was insignificant and statistically significant with the sex of participants and income level.

Systemic review registration

PROSPERO International prospective register of systematic reviews: CRD42018099975
Metabolic alterations provide insights into Stylosanthes roots responding to phosphorus deficiency
Authors: Luo Jiajia , Liu Yunxi , Zhang Huikai , Wang Jinpeng , Chen Zhijian , Luo Lijuan , Liu Guodao , Liu Pandao 
Published: August 2019

Abstract
Background

Low phosphorus (P) availability is a major constraint on the growth of plants, especially in acid soils. Stylosanthes (stylo) is a pioneer tropical legume with several adaptive strategies to cope with P deficiency, but its metabolic reprogramming during P limitation remain poorly understood.

Results

To shed light on the acclimation of stylo roots to low P stress, morphophysiological and metabolic response were investigated in this study. After 15 days of low P treatment, shoot dry weight and total P concentration were markedly hampered, whereas root growth, root APase activity, root antioxidant activity were markedly enhanced. Corresponding investigation of metabolic profiling showed that a total of 256 metabolites with differential accumulation in response to P deficiency were identified in stylo roots, mainly including sugars, organic acids, amino acids, nucleotides, phenylpropanoids and their derivatives. P deficiency leads to significant reduction in the levels of phosphorylated sugars and nucleotides, indicates that the known strategies of P scavenging from P-containing metabolites are observed. The metabolisms of organic acids and amino acids were also remodeled by P limitation, which suggests that P-deficient stylo roots redistribute their carbohydrates in responding P deprivation, by releasing organic acids into the rhizosphere to mobilize phosphate from P complexes and employing amino acids as alternative carbon resource for energy metabolism. In phenylpropanoid metabolism pathway, the increased accumulation flavonoids, as well as up-regulated expression of involved genes SgF3H, SgF3’H, SgFLS, might contribute to enhance the antioxidant activity of stylo roots, especially kaempferol, quercetin, dihydromyricetin. The enhanced accumulation isoflavonoids with differential expression of related genes (SgHID and SgUGT) supported the opinion of isoflavonoids secreted to function with rhizosphere microbes in responding to P deficiency condition, especially daidzein and rotenone.

Conclusions

This study provides valuable insights generated from stylo roots into the various adaptation responses to Pi-starvation, identified candidate genes and metabolites will make some contributions to detect potential target region for future developing Pi-efficiency breeding research.
Assessing Anticoagulation Management and Shared Decision-Making Documentation from Providers Participating in the SUPPORT-AF Study
Authors: Hoque Laboni , Amroze Azraa , Gilvaz Vinit , Abraham Sonu , Lal Amos , Mishra Ajay , Crawford Sybil , Mazor Kathleen , McManus David , Kapoor Alok 
Published: August 2019

Abstract
Background We previously tested an intervention featuring educational outreach with modified academic detailing (AD) to increase anticoagulation (AC) use in patients with atrial fibrillation (AF). Currently, we compare providers receiving and not receiving AD in terms of inclusion of our AD educational topics and shared decision-making elements in documentation. Methods Physicians reviewed themes discussed with providers during AD and evaluated charts for evidence of shared decision-making. We then compared frequency of documentation of individual items for providers receiving AD compared with non-AD providers. To understand baseline documentation practices of AD providers, we also randomly selected encounters of AD providers before their AD participation. Results There were 113 eligible encounters in the four months after AD - 36 from AD providers and 77 from non-AD providers. We also identified 35 encounters from AD providers before participating in the intervention. Providers infrequently documented many reviewed items (% documenting): AC mentioned (44%), multiple options for AC (5%), CHA2DS2-VASc score (11%), bleeding risk factors (2%). Compared with non-AD providers, AD providers had statistically significant higher percentages for the following items: mention of AC (64% versus 35%), stroke risk (11% versus 0%), AC benefits (8% versus 0%), patient involvement (70% versus 0%). There was no improvement, however, for AD providers compared with baseline documentation percentages. Conclusions Providers infrequently documented important items in AC management and shared decision-making. AD participation did not improve documentation. Improving adoption of AD educational items may require more prolonged interaction with providers. Improving shared decision-making may require an intervention more focused on it and its documentation. Trial Registration The trial was registered as NCT03583008 on Clinicaltrials.gov on July 11, 2018.
Diffusion-weighted imaging in normal pancreas: Apparent diffusion coefficient test-retest repeatability
Authors: Chen Shiyue , Liu Ri , Ma Chao , Bian Yun , Li Jing , Yang Panpan , Wang Minjie , Lu Jianping 
Published: August 2019

Abstract
Background

The assessment of apparent diffusion coefficient (ADC) repeatability is important to body diffusion weighted imaging (DWI). However, data onto evaluating the repeatability of ADC values for normal pancreas are limited. The aim of this study was to evaluate the ADC test-retest repeatability of the normal pancreas.Methods

Twenty-six healthy volunteers (mean 47.6 years; 13 men) were included and scanned twice with reposition using a DWI sequence at 3.0-T. ADCs of the pancreatic head, body and tail for two DWIs were measured by two readers. The mean ADCs of the pancreatic head, body and tail were calculated as the global pancreatic ADC. Test-retest repeatability and agreement of ADC measurement were evaluated by the Bland-Altman analysis, intra-class correlation coefficient (ICC) and coefficient of variation (CV).Results

The global pancreatic ADC showed the best test-retest repeatability (mean difference ± limits of agreement were 0.05 ± 0.25×10 -3 mm 2 /s; ICC, 0.79; CV, 6%). Test-retest repeatabilities for ADC of pancreatic head, body or tail were scattered, with mean difference ± limits of agreement between two tests were 0.03 ± 0.47, 0.05 ± 0.42 and 0.06 ± 0.31 (×10 -3 mm 2 /s), respectively (ICCs, 0.81, 0.52 and 0.68; CVs, 9%, 8% and 8%). Both intra-observer repeatability and inter-observer reproducibility were acceptable for whole pancreas between ADC measurements of the two DWIs.Conclusions

ADC values of the pancreas are technically challenging and repeatability is variable. Cautions should be taken when interpreting longitudinal clinical changes in ADC values of the normal pancreas because the measurements do have an inherent variability by locations.
Clinical efficacy of locoregional therapy prior to living donor liver transplantation for hepatocellular carcinoma based on UCSF criteria
Authors: Wu Tsung-Han , Cheng Chih-Hsien , Lee Chen-Fang , Wu Ting-Jung , Chou Hong-Shiue , Chan Kun-Ming , Lee Wei-Chen 
Published: August 2019

Abstract
Background
The study analyzed the loco-regional therapy outcomes prior to living donor liver transplantation (LDLT), to provide additional information for decision-making regarding therapeutic strategy for hepatocellular carcinoma (HCC) patients.
Methods
A total of 308 consecutive patients undergoing LDLTs for HCC between August 2004 and December 2018 were retrospectively analyzed. Patients subjected to loco-regional therapy prior to LT were grouped and the outcomes were compared.
Results
Overall, HCC recurrence after LDLT were detected in 38 patients (12.3%) during the follow-up period. By the end of the study, 205 patients, 6 of whom with recurrent HCC, were alive. Patients who had radiological imaging beyond the University of California at San Francisco (UCSF) criteria had significant inferior outcomes for both recurrence-free survival (RFS, p = 0.0005) and overall survival (OS, p = 0.0462) despite receiving loco-regional therapy as down-staging intention. Moreover, patients with profound tumor necrosis (TN) had a superior RFS at 3 and 5 years (97.4% and 93.8%, respectively), compared with others.
Conclusion
LDLT gains a satisfactory result based on the expanded UCSF criteria for HCC. However, the loco-regional therapy prior to LDLT does not seem to provide benefit unless a profound TN is noted.
iSulfoTyr-PseAAC: Identify Tyrosine Sulfation Sites by Incorporating Statistical Moments via Chou’s 5-steps Rule and Pseudo Components
Authors: Barukab Omar , Khan Yaser Daanial , Khan Sher Afzal , Chou Kuo-Chen 
Published: August 2019

Background:The amino acid residues, in protein, undergo post-translation modification (PTM) during protein synthesis, a process of chemical and physical change in an amino acid that in turn alters behavioral properties of proteins. Tyrosine sulfation is a ubiquitous posttranslational modification which is known to be associated with regulation of various biological functions and pathological processes. Thus its identification is necessary to understand its mechanism. Experimental determination through site-directed mutagenesis and high throughput mass spectrometry is a costly and time taking process, thus, the reliable computational model is required for identification of sulfotyrosine sites.Methodology:In this paper, we present a computational model for the prediction of the sulfotyrosine sites named iSulfoTyr-PseAAC in which feature vectors are constructed using statistical moments of protein amino acid sequences and various position/composition relative features. These features are incorporated into PseAAC. The model is validated by jackknife, cross-validation, self-consistency and independent testing.Results:Accuracy determined through validation was 93.93% for jackknife test, 95.16% for crossvalidation, 94.3% for self-consistency and 94.3% for independent testing.Conclusion:The proposed model has better performance as compared to the existing predictors, however, the accuracy can be improved further, in future, due to increasing number of sulfotyrosine sites in proteins.
Scientific Papers and Patents on Substances with Unproven Effects. Part 2
Authors: Jargin Sergei V. 
Published: August 2019

:Several examples are discussed in this review, where substances without proven effects were proposed for practical use within the scope of evidence-based medicines. The following is discussed here: generalizations of the hormesis concept and its use in support of homeopathy; phytoestrogens and soy products potentially having feminizing effects; glycosaminoglycans for the treatment of osteoarthritis and possibilities of their replacement by diet modifications; flavonoids recommended for the treatment of chronic venous insufficiency and varicose veins; acetylcysteine as a mucolytic agent and its questionable efficiency especially by an oral intake; stem cells and cell therapies. In conclusion, placebo therapies can be beneficial and ethically justifiable but it is not a sufficient reason to publish biased information. Importantly, placebo must be devoid of adverse effects, otherwise, it is named pseudo-placebo. Therapeutic methods with unproven effects should be tested in high-quality research shielded from the funding bias. Some issues discussed in this review are not entirely clear, and the arguments provided here can initiate a constructive discussion.
An Un-Supervised Approach for Backorder Prediction Using Deep Autoencoder
Authors: Saraogi Gunjan , Gupta Deepa , Sharma Lavanya , Rana Ajay 
Published: August 2019

Background:
Backorders are an accepted abnormality affecting accumulation alternation
and logistics, sales, chump service, and manufacturing, which generally leads to low sales and low
chump satisfaction. A predictive archetypal can analyze which articles are best acceptable to acquaintance
backorders giving the alignment advice and time to adjust, thereby demography accomplishes
to aerate their profit.

Objective:
To address the issue of predicting backorders, this paper has proposed an un-supervised
approach to backorder prediction using Deep Autoencoder.

Methods:
In this paper, artificial intelligence paradigms are researched in order to introduce a predictive
model for the present unbalanced data issues, where the number of products going on
backorder is rare.

Results:
Un-supervised anomaly detection using deep auto encoders has shown better Area under
the Receiver Operating Characteristic and precision-recall curves than supervised classification
techniques employed with resampling techniques for imbalanced data problems.

Conclusion:
We demonstrated that Un-supervised anomaly detection methods specifically deep auto-
encoders can be used to learn a good representation of the data. The method can be used as a predictive
model for inventory management and help to reduce the bullwhip effect, raise customer satisfaction
as well as improve operational management in the organization. This technology is expected
to create the sentient supply chain of the future - able to feel, perceive and react to situations
at an extraordinarily granular level.
Bayesian Spam Detection Framework on Mobile Device
Authors: Yang Yitao , Sun Guozi , Qiu Chengyan 
Published: August 2019

Background:
The spam message aimed at mobile devices has become a prevalent activity
in recent years. About 76% of mobile users received spam messages of Ads, fraud messages and
phishing links. It has led to a significant financial loss of 91.5 billion Yuan per year and this problem
will be more severe in the coming future. Although the operators are making much effort against
spam message, the number of spams are increasing day by day.

Aim:
Many schemes designed to detect and filter spam have been proposed in the research area. The
Bayesian classification algorithm is one of the most popular schemes. Most of the spam detection
schemes based on Bayesian are designed for communication providers. The scalability of filter policy
is hard to control because the strict policy might filter the normal messages while some spam
messages would not be detected due to the flexibility in the policy.

Methods:
The current mobile device has a robust computational capability so it can execute complex
jobs. A spam detection framework is designed in the present study.

Results:
It can sniffer the coming messages in mobile device by hooking the Android SMS API, and
send them to the filter module, -which is responsible to filter messages into normal or spam based
on Bayesian classification. This is a light-weight framework of consuming low power, which is suitable
for mobile devices. Extra experiments are conducted to prove their accuracy and efficiency.

Conclusion:
The results showed that it could filter the spam among receiving the messages in realtime
and become more accurate by learning the users' feedback.
Building a Semantic Health Data Warehouse in the Context of Clinical Trials: Development and Usability Study
Authors: Lelong Romain , Soualmia Lina F , Grosjean Julien , Taalba Mehdi , Darmoni Stéfan J 
Published: August 2019

Background
The huge amount of clinical, administrative, and demographic data recorded and maintained by hospitals can be consistently aggregated into health data warehouses with a uniform data model. In 2017, Rouen University Hospital (RUH) initiated the design of a semantic health data warehouse enabling both semantic description and retrieval of health information.

Objective
This study aimed to present a proof of concept of this semantic health data warehouse, based on the data of 250,000 patients from RUH, and to assess its ability to assist health professionals in prescreening eligible patients in a clinical trials context.

Methods
The semantic health data warehouse relies on 3 distinct semantic layers: (1) a terminology and ontology portal, (2) a semantic annotator, and (3) a semantic search engine and NoSQL (not only structured query language) layer to enhance data access performances. The system adopts an entity-centered vision that provides generic search capabilities able to express data requirements in terms of the whole set of interconnected conceptual entities that compose health information.

Results
We assessed the ability of the system to assist the search for 95 inclusion and exclusion criteria originating from 5 randomly chosen clinical trials from RUH. The system succeeded in fully automating 39% (29/74) of the criteria and was efficiently used as a prescreening tool for 73% (54/74) of them. Furthermore, the targeted sources of information and the search engine–related or data-related limitations that could explain the results for each criterion were also observed.

Conclusions
The entity-centered vision contrasts with the usual patient-centered vision adopted by existing systems. It enables more genericity in the information retrieval process. It also allows to fully exploit the semantic description of health information. Despite their semantic annotation, searching within clinical narratives remained the major challenge of the system. A finer annotation of the clinical texts and the addition of specific functionalities would significantly improve the results. The semantic aspect of the system combined with its generic entity-centered vision enables the processing of a large range of clinical questions. However, an important part of health information remains in clinical narratives, and we are currently investigating novel approaches (deep learning) to enhance the semantic annotation of those unstructured data.