bluuebunny/crossref_metadata_2025 huggingface dataset:
Involvement of A5/a7 Noradrenergic Neurons and B2 Serotonergic Neurons in Nociceptive Processing: A Fiber Photometry Study
Authors: Moriya Shunpei , Yamashita Akira , Masukawa Daiki , Sakaguchi Junichi , Setoyama Honami , Ikoma Yoko , Yamanaka Akihiro , Kuwaki Tomoyuki
Published: June 2020

In nociceptive processing, the descending antinociceptive system (DAS) is well known to include a number of descending pathways.As the main pathway of DAS, the locus coeruleus (A6) – spinal horn circuit including the noradrenergic (NAergic) system andthe periaqueductal gray-rostral ventromedial medulla (B3) – spinal horn circuit including the serotonergic (5-HTergic) system are well known.OtherNAergic or 5-HTegic systems, however,are less well known. Some studies have reported that A5/A7 noradrenaline (NA) neurons or B2 serotonin (5-HT, 5-hydroxytryptamine) neurons partially participate in DAS.In this study, we recorded G-CaMP6 green fluorescence signal intensities in theA5/A7/B2 sites of awake mice in response to acute tail pinch stimuli, acute heat stimuli, and in the context of a noninvasive control test, using fiber photometry with acalcium imaging system.We first introduced G-CaMP6 in the A5/A7 NA neuronal soma or B2 5-HT neuronal soma, using transgenic mice carrying tetracycline-controlled transactivator transgene (tTA) under the control of either a dopamine β-hydroxylase promoter or a tryptophan hydroxylase-2 and by the site-specific injection of adeno-associated virus (AAV-TetO(3G)-G-CaMP6).The specific expression patterns of G-CaMP6 were clearly confirmed in the A5/A7 areasand B2 area.After confirming the specific expression patterns of G-CaMP6, we recorded G-CaMP6 green fluorescence signals in these sites fromawake mice in response to acute nociceptive stimuli.G-CaMP6 fluorescence intensity in the A5, A7, and B2 groups wasrapidly increased by acute nociceptive stimuli,soon returning to baseline fluorescence intensity.This was not observed in the context of the noninvasive control test.Weused mCherry red fluorescent protein as a control indicator. mCherry fluorescence intensity was not significantly changed by acute nociceptive stimuli or in the noninvasive control test in any of the groups. These results clearly indicate that acute nociceptive stimuli rapidly increase the activities of A5/A7 NA neurons or B2 5-HT neurons, suggesting that A5/A7 NA neurons or B2 5-HT neurons play important roles in nociceptive processing in the central nervous system.
Long noncoding RNA TSLNC8 Enhances Pancreatic Cancer Aggressiveness by Regulating CTNNB1 Expression via Association with HuR
Authors: Chai Wei , Liu Ruhai , Li Fengshan , Zhang Zhiquan , Lei Bao
Published: June 2020

Background Pancreatic cancer (PC) is one of the most lethal malignancies worldwide. Tumor suppressor long noncoding RNA on chromosome 8p12 (TSLNC8) is a newly identified long noncoding RNA (lncRNA) and play an important role in human cancers. However, the function and molecular mechanism of TSLNC8 in PC progression remains to be elucidated. Methods qRT-PCR was performed to examine the expression pattern of TSLNC8 in PC tissues and cell lines. Overexpression and knockdown experiments were conducted to detect the function of TSLNC8 in PC. The interaction between TSLNC8 and HuR was tested by RNA immunoprecipitation assay. Results Our results showed a significant increase of TSLNC8 expression in PC tissues and cell lines. Upregulation of TSLNC8 expression in PC tissues was closely correlated with TNM stage, distant and lymph node metastasis, and poor prognosis of PC patients. Functional experiments demonstrated that TSLNC8 promoted PC cells proliferation and invasion in vitro, and enhanced PC growth and metastasis in vivo. Mechanistically, TSLNC8 associated with HuR, promoted the binding of HuR with CTNNB1 mRNA and increased the stability of CTNNB1 mRNA, thus activating WNT/β-catenin signaling pathway. Conclusion Our present study revealed that oncogenic lncRNA TSLNC8 positively regulate PC growth and metastasis via HuR-mediated mRNA stability of CTNNB1, extending the understanding of PC pathogenesis regulated by lncRNAs.
A systematic review of interventions to increase attendance at health and fitness venues: identifying key behaviour change techniques
Authors: Rand Matthew , Norman Paul , Goyder Elizabeth
Published: June 2020

Background

Members’ attendance at health and fitness venues typically declines over the course of their membership, with a likely negative impact on physical activity and health outcomes. This systematic review sought to examine the effectiveness of interventions to increase attendance at health and fitness venues and identify the behaviour change techniques (BCTs) included in effective interventions.

Methods

A systematic search of seven databases was conducted. The Behaviour Change Technique Taxonomy was used to code the interventions. Cohen’s d was used to assess the effectiveness of the interventions.

Results

Fourteen papers reporting 20 interventions were included in the review. Most interventions were found to have negligible or small effects on attendance, although one had a medium effect ( d = 0.60) and three had a large effect ( d s = 1.00, 1.37, 1.45). The interventions used a limited range of BCTs, with “Prompts/Cues” being the most frequently used. Of the interventions with large effect sizes, two used “Problem solving” and “Pros and cons” and one used “Goal setting (behaviour)” and “Review behaviour goals”.

Conclusions

Only a small number of studies have tested interventions to increase attendance at health and fitness venues, with predominantly small effects. With the possible exception of problem solving alongside decisional balance and goal setting alongside review behaviour goals, there is little evidence for the effectiveness of specific BCTs. Further research is required to identify the key components of effective interventions to increase attendance at health and fitness venues.
Comparison of inequity in health-related quality of life among unemployed and employed in China
Authors: Zhao Ya-xin , Zhou Zhongliang , Fan Xiao-jing , Nawaz Rashed , Zhao Dan-tong , Xu Tian-ge , Su Min , Cao Dan , Shen Chi , Lai Sha
Published: June 2020

Background

In China, achieving the health equity has been regarded as a key issue of health reforms and development in the current stage. It is well known that unemployment have a negative effect on health. However, few studies have addressed the association between unemployment and the inequity of health-related quality of life (HRQOL). The study aims to compare the inequality and inequity in HRQOL among the unemployed and employed in China.

Methods

The material regarding this study has been illustrated from the Chinese National Health Services Survey (NHSS) of Shaanxi Province for 2013. We have controlled the confounding factors by the utilization of coarsened exact matching method (CEM). Finally, 7,524 employed individuals and 283 unemployed individuals were aged 15 to 64 in urban area has been incorporated for this study. We use HRQOL as the outcome variable, which was evaluated by the Chinese version of EQ-5D-3L. Health concentration index, decomposition analysis based on the Tobit model and the horizontal inequity index were employed to compute the income-related equity and the contribution of factors among the unemployed and employed.

Results

After matching, unemployed people tended to express poorer EQ-5D utility than employed people. The horizontal inequity indices among employed and unemployed people were 0.0020 and 0.0077 respectively, demonstrating that the pro-rich health inequity of unemployed people was a great deal superior to employed people. Economic status, age, education, smoking and health insurances are the main impact factors that affect the inequality in HRQOL among employed and unemployed. Education status and basic health insurances reduce the pro-rich inequity in HRQOL for the unemployed.

Conclusion

It is suggested that unemployment intensifies the inequality and inequity in HRQOL. In view of the policy makers, the basic health insurances are still a critical health policy for improving health equity of the unemployed. Re-employment programs, the socialization of medical health insurances, initiatives to improve educational equity and the psychological counseling for the unemployed should be considered by government to attain health equity.
Evidence of Protective Role of Ultraviolet-B (UVB) Radiation in Reducing COVID-19 Deaths
Authors: Moozhipurath Rahul Kalippurayil , Kraft Lennart , Skiera Bernd
Published: June 2020

Background. Prior studies indicate the protective role of Ultraviolet-B (UVB) radiation in human health, mediated by vitamin D synthesis. In this observational study, we empirically outline a negative association of UVB radiation as measured by ultraviolet index (UVI) with the number of COVID-19 deaths.Methods. We apply a fixed-effect log-linear regression model to a panel dataset of 152 countries over 108 days (n=6524). We use the cumulative number of COVID-19 deaths and case-fatality rate (CFR) as the main dependent variables and isolate UVI effect from potential confounding factors.Findings. After controlling for time-constant and time-varying factors, we find that a permanent unit increase in UVI is associated with a 1.2 percentage points decline in daily growth rates of cumulative COVID-19 deaths [p < 0.01] and a 1.0 percentage points decline in the CFR daily growth rate [p < 0.05]. These results represent a significant percentage reduction in terms of daily growth rates of cumulative COVID-19 deaths (-11.88%) and CFR (-38.46%).Interpretation. We find a significant negative association between UVI and COVID-19 deaths, indicating evidence of the protective role of UVB in mitigating COVID-19 deaths. If confirmed via clinical studies, then the possibility of mitigating COVID-19 deaths via sensible sunlight exposure or vitamin D intervention will be very attractive.
Effect of End-of-production High-energy Radiation on Nutritional Quality of Indoor-grown Red-leaf Lettuce
Authors: Gómez Celina , Jiménez Juan
Published: June 2020

Numerous studies have evaluated the effect of high-energy radiation as means to increase nutritional quality of lettuce (Lactuca sativa). However, most research has focused on providing constant radiation quality or quantity throughout the production cycle, which typically results in yield reductions or increases in production costs. End-of-production (EOP) radiation is a cost-effective, preharvest practice that can allow growers to manipulate product quality and thus increase market value of lettuce without negatively affecting plant growth. The objective of this study was to quantify and compare growth and accumulation of secondary metabolites from ‘Rouxaï RZ’ and ‘Codex RZ’ red-leaf lettuce grown indoors and exposed to different strategies of EOP high-energy radiation. Plants were grown for 24 days under an average daily light integral (DLI) of 15.8 mol·m‒2·d‒1 (220 µmol·m‒2·s‒1 for 20 h·d−1) using red:blue light-emitting diode (LED) lamps. Four days before harvest (36 days after sowing), plants were exposed to one of three EOP treatments added to red:blue LEDs: 1) ultraviolet-A (EOP-ultraviolet); 2) high blue (EOP-B); or 3) high-intensity (EOP-H) radiation. A fourth treatment was included as a control, with no EOP. Except for EOP-H, all treatments provided a DLI of 15.8 mol·m‒2·d‒1; EOP-H provided a DLI of 31.7 mol·m‒2·d‒1. No treatment differences were measured for shoot fresh weight (FW) of ‘Rouxaï RZ’ but shoot FW of ‘Codex RZ’ was negatively affected by EOP radiation, indicating potential changes in lettuce yield from applying EOP high-energy radiation during active plant growth. In general, EOP treatments did not affect total phenolic content and total carotenoid concentration of plants, but anthocyanin content and antioxidant capacity were positively influenced by EOP-B and EOP-H, whereas EOP-ultraviolet resulted in similar nutritional quality to control. Findings from this study indicate that EOP high-energy radiation, especially EOP-B, has significant potential to improve the nutritional quality of red-leaf lettuce grown in controlled environments.
Mind Skills Training Model through Experiential Learning as Guide Teacher and Islamic Counselors
Authors: Supa'at Supa'at , Azmi Khilman Rofi
Published: June 2020

This article is aimed to create mind skills training manual books for guidance teachers and counselors to increase counseling skills theoretically and practically. Mind skill used by counselors and guides teachers in MTs 1 Kudus, MTs TBS, and Muhammadiyah Kudus, Central Java to manage and think about what they think and do. It will implicate how they react and act, communicate, and respond to their counselee or client. This article used a development approach that modified from Borg and Gall model through three phases included (1) preparation, (2) implementation, and (3) trial. The mind skills training book was developed by referring to the needs of research subjects based on the results of interviews and literature studies. The result shows that the mind skills manual book for guide teacher counselor is accepted and fulfillment with an average value of 87% in the "very good" category for small group tests by corresponding of correctness, usefulness, and conformity aspect.AbstrakArtikel ini bertujuan untuk membuat buku panduan pelatihan keterampilan pikiran untuk guru bimbingan dan konselor dalam rangka meningkatkan keterampilan konseling secara teoritis dan praktis. Keterampilan pikiran digunakan oleh konselor dan membimbing guru di MTs 1 Kudus, MTs TBS, dan Muhammadiyah Kudus, Jawa Tengah untuk mengelola dan berpikir tentang apa yang mereka pikirkan dan lakukan. Ini akan melibatkan bagaimana mereka bereaksi dan bertindak, berkomunikasi, dan menanggapi konseli atau klien mereka. Artikel ini menggunakan pendekatan pengembangan yang dimodifikasi dari model Borg dan Gall melalui tiga fase termasuk (1) persiapan, (2) implementasi, dan (3) percobaan. Buku pelatihan keterampilan pikiran dikembangkan dengan merujuk pada kebutuhan subyek penelitian berdasarkan hasil wawancara dan studi literatur. Hasil penelitian menunjukkan bahwa buku panduan keterampilan pikiran untuk guru BK membimbing diterima dan dipenuhi dengan nilai rata-rata 87% dalam kategori "sangat baik" untuk tes kelompok kecil dengan aspek ketepatan, kegunaan, dan kesesuaian.
Some Possibilities of Energy Supply of Autonomous Consumers due to Non-Traditional and Renewable Sources
Authors: Babayan Robert Suren , Asrian Ruzanna Artashes , Grigoryan Susanna Abel
Published: June 2020

The paper provides solutions for energy supply to agricultural consumers remote from energy sources due to non-traditional types of energy, based on patents of the Russian Federation. A scheme of a thermodynamic installation operating according to the Rankine cycle on a low boiling liquid is considered. The circuit uses a capacitor that increases the temperature of the condensate, leading to an increase in the efficiency of the thermodynamic installation. A series of graphs is given, confirming the required amount of heat received for the operation of the installation and a graph of the dependence of the efficiency of the installation on temperature conditions. A graph of solar energy is shown, which feeds per unit of horizontal surface and its integral value for one day. Options for improving the installation using concentrating receivers of solar energy are given. Test schedules for the solar collector module are provided.
Analysis of the Used Car Market in Moscow
Authors: Ugurchieva Izabella Magometovna , Kulakova Aleksandra Vitalevna
Published: June 2020

The used car market currently remains at a high level in Russia, since not everyone can afford to buy a new car. The situation is similar in the capital of our country, Moscow. Except that there is more demand for foreign-made cars than for domestic ones, unlike the other regions of the country. The authors have analyzed the used car market in Moscow and determined which brands and models are the most popular in the city.
Approaches to Implementation of the Requirements of Educational Standards and Key Employers
Authors: Kolesova Tatiana Kimovna
Published: June 2020

The article considers the specifics of designing educational programs in higher education. When planning the educational results, it is important to develop all components of the educational program of each undergraduate and graduate course. The structure, content and the conditions for implementation of the educational program should guarantee the expected quality of graduate training according to the requirements of the Federal Educational Standards of Higher Education and the employers’ demands, as well as consider the starting opportunities of freshman students.
Analysis of the Current State of Abortion and Reproductive Health
Authors: Khrebtova Kira Andreevna
Published: June 2020

In the course of an analysis of scientific literature and legal documents, indications for induced termination of pregnancy have been reviewed, as well as problems associated with the protection of reproductive health and the availability of safe abortions in different countries of the world.
Protein Secondary Structure Prediction Using Character Bi-gram Embedding and Bi-LSTM
Authors: Sharma Ashish Kumar , Srivastava Rajeev
Published: June 2020

Background:

Protein secondary structure is vital to predicting the tertiary structure,
which is essential in deciding protein function and drug designing. Therefore, there is a high
requirement of computational methods to predict secondary structure from their primary sequence.
Protein primary sequences represented as a linear combination of twenty amino acid characters and
contain the contextual information for secondary structure prediction.

Objective and Methods:

Protein secondary structure predicted from their primary sequences using a
deep recurrent neural network. Protein secondary structure depends on local and long-range residues
in primary sequences. In the proposed work, the local contextual information of amino acid residues
captures with character n-gram. A dense embedding vector represents this local contextual
information. Furthermore, the bidirectional long short-term memory (Bi-LSTM) model is used to
capture the long-range contexts by extracting the past and future residues information in primary
sequences.

Results:

The proposed deep recurrent architecture is evaluated for its efficacy for datasets, namely
ss.txt, RS126, and CASP9. The model shows the Q3 accuracies of 88.45%, 83.48%, and 86.69% for
ss.txt, RS126, and CASP9, respectively. The performance of the proposed model is also compared
with other state-of-the-art methods available in the literature.

Conclusion:

After a comparative analysis, it was observed that the proposed model is performing
better in comparison to state-of-art methods.
Phenolic profile and antioxidant activity from wild and in vitro cultivated Rhynchostele rossii (Orchidaceae)
Authors: Martínez Cruz Nieves del Socorro , Monribot Villanueva Juan Luis , Cocotle Ronzón Yolanda , Gutiérrez Sánchez Rosa Angélica , Guerrero Analco José Antonio
Published: June 2020

Background and Aims: Rhynchostele rossii is an orchid native to Mexico known as gallinitas (little chickens) that is threatened due to overexploitation for ornamental purposes, as a consequence of which it is necessary to realize efforts for its conservation. To date there are no reports of phytochemical studies of this orchid, although it is well known that species of the Orchidaceae family are a good source of bioactive and nutraceutical compounds (e. g. vanillin). Therefore, the main objective of this research was to establish a R. rossii in vitro germination protocol for propagation and determination of phenolic compounds that contribute to its phytochemical knowledge.Methods: A specimen of a wild plant and some seedlings obtained by in vitro culture were dried, milled and their components extracted with MeOH; anti-free radical activity (DPPH), total phenols and flavonoids were determined by spectrophotometric methods, and individual phenolic compounds were identified and quantified by liquid chromatography coupled to mass spectrometry (LC-MS).Key results: The root of the wild plant showed the highest content of total phenols and flavonoids with 121.60 mg GAE g-1 and 108.73 mg CE g-1, respectively, and the best anti-free radical activity with an IC50 53.63 μg ml-1. Extracts from seedlings obtained by in vitro culture also produced phenolic compounds, showing a total phenolic and flavonoid content of 37.35 mg GAE g-1 and 0.16 mg CE g-1, respectively. One coumarin (scopoletin) , three cinnamic acids (4-coumaric acid, ferulic acid and trans-cinnamic acid), three benzoic acids (vanillic acid, vanillin and 4-hydroxybenzoic acid) and three flavonoids (quercetin-3-D-galactoside, quercetin-3-glucoside and kaempferide) were identified and quantified by LC-MS.Conclusions: This study demonstrates that R. rossii is a potential source of antioxidant metabolites that can be obtained by in vitro culture, without harming the wild specimens.
Project Kris: Knowledge Reinforcement and Intervention for Student Performance: An Action Research
Authors: Iii Jimmy P. Manigbas , Rubi Kristine P. , Bersola Luzviminda I.
Published: June 2020

This study aims to assess the significant improvement of the academic performance of Grade 12 learners in Cookery subject. This study utilized a one shot case study. The teacher-researchers introduced the interventions that are implemented inside the classroom; a. Care Tech Project; b. One Hand Project; c. Play Magic Box Project; d. Friendly Helping Project; e. Lend a Gift Project; f. Celebrity of the Weeks Project. Atotal of 25 Grade 12 TVLlearners of Tabgon High School, Goa, Camarines Sur, Philippines who were enrolled in the class of teacher-researchers for the school year 2018-2019. The statistical tools used were Frequency and Percentage Distribution, Weighted Mean, and Mean for Dependent Samples to determine the significant improvement between 2nd semester midterm and final grade mean rating academic performance of the students.The baseline data of this study obtained from midterm grades of the learners. As reflected in the results the midterm mean rating of the male learners is 84.80% which increased to 88% which has significant difference of 3.20 or High and for female learners' midterm rating is 88.85% which increased to 92.10% which 3.25 or High is the significant difference. That immense increased in their mean rating was made after the implementation of interventions. Based on the level of acceptability of the interventions implemented, all of the various interventions garnered Highly Acceptable with grand weighted mean rating of 4.83. It implies that Project KRIS interventions provided a big impact to the learners. Thus, that Project KRIS helped the learners that improved and enhanced their performances with its various interventions.
Business Prospects For Entrepreneurs In Skill Based Online Education
Authors: Rathore G S , Singh Bhagwan , Kumar Sachin , Rai Rita , Kumar Kamlesh
Published: June 2020

The present time is for Knowledge-Based Economy (KBE) because people can access any required information via internet browsers or mobile phone applications. The mobile applications have created a high demand for online education, as it is convenient to use, it has lower cost, higher reach etc. This is conceptual paper highlighting the future business opportunities that are available for young entrepreneurs in the field of online education. The young people who are aspiring to be entrepreneurs can help our country grow to a knowledge-based economy by shaping the students' skills in a required way. It can create ample of business opportunities to the aspiring entrepreneurs and job opportunities to the job seekers.The content analysis approach is used to study the different websites of government and no-government institutes. The study is an attempt to highlight few of the online education platforms for Indian i.e. Bhartiyastudents and job seekers. The study concludes that online education system is rising as it generates the student's satisfaction level. Moreover, anyone on job can continue (h)is/er studies. Many IITs, IIMs, NPTEL, NPTEL(SWAYAM) and CEC are providing freer and online courses to the students. For young aspiring entrepreneurs Government of India is providing freer online courses under startup India program. The study identified 20 online courses under start up India initiative of Government of India (GoI) and many freer and paid online education platforms in India. The findings reveal that there is rising demand for online courses in India after launch of Digital India Programme. New entrepreneurs can avail this opportunity and start their own online presence in online education.
Skilling and Growth Nexus - Measurement, Policy and challenges in the context of India
Authors: Mishra Sumit  Kumar
Published: June 2020

If we have to promote the development of our country then our mission has to be skill development and skilled India”.Prime Minister Narendra ModiSkill is the capability to do something nicely, create something new and innovations leading from existing talent, training, or practice. It is also the ability to provide solutions to the different kind of problems and situations. Developments of these skills are very important for the economic prosperity of the country. Skilling is considered to be one of the most important factor as it certainly leads to economic growth by building capability and making economy self-sustainable. Skill and the right set of knowledge are also regarded as the key factors for the growth and social upliftment of any country. It is noticed that the countries having skilled labor force find it easier to adjust in the competitiveness nature of world of work. Skilled labors are not prone to changing work environment of world.India is on the verge of becoming a knowledge economy. It is therefore indispensable to identify the right set of skills required to be imparted to labor force and lead them towards capability development.To accomplish the very objective of the economic growth, the Gross Domestic Product (GDP) of India has to grow at a rapid pace of 8% to 9% consistently. This will require some major changes and significant improvement in infrastructure sector, agricultural sector, manufacturing sector and also need skilled labor force to fasten the process of goods and services delivery.Major challenge India withholds is not only to impart skill leading to economic prosperity but to soak in the excess supply of labor coming from rural sector. India is a labor intensive country and there is labor availability in abundance. With the limited training infrastructure, it is indeed a challenging task to train this vast number of laborers in India and turn them into productive skilled workforce. Even the lack of awareness among labor force to go through training program is other issue. As per the National Skill Development Mission (NSDM) Document, there is a shortage of the trained laborers in India. Only 2.3 percent of the workers in India went through formal training. If we look at the statistics of labor force attending training for some other country, it was like sixty-seven percent in United Kingdom, seventy-five percent in Germany, eighty percent in Japan and so on. All these countries are already a developed nation. This fact reveals an interesting finding that the pool of Indian workforce mostly lacked requisite skills and was mostly unemployable.High percentage of labor receiving training makes them skilled and capable. It also shows a pattern of a linear correlation among developed nation workforce and skill.
Enhanced Enrollment in the National Diabetes Prevention Program to Increase Engagement and Weight Loss for the Underserved: Protocol for a Randomized Controlled Trial (Preprint)
Authors: Ritchie Natalie D , Holtrop Jodi Summers , Gritz R Mark , Sauder Katherine Ann , Durfee Michael Josh , Dickinson L Miriam , Kaufmann Peter G
Published: June 2020

BACKGROUND

Type 2 diabetes affects 9.4% of US adults with higher rates among racial and ethnic minorities and individuals of low socioeconomic status. The National Diabetes Prevention Program (NDPP) is an evidence-based and widely disseminated behavioral intervention to reduce diabetes incidence through modest weight loss. However, retention in the yearlong NDPP is problematic and leads to suboptimal weight loss, especially among diverse, underserved populations. Strategies to improve NDPP engagement and weight loss are needed urgently. Pilot results of the pre-NDPP, a novel enhancement to enrollment in the NDPP based on the Health Belief Model, were highly successful in a nonrandomized cohort study among 1140 racially diverse, predominately low-income participants. A total of 75 presession participants had doubled attendance and weight loss as compared with earlier participants who did not receive presessions. On the basis of these promising results, we are conducting a randomized controlled trial (RCT) to determine whether pre-NDPP reliably improves NDPP outcomes, as reported on ClinicalTrials.gov.

OBJECTIVE

This study aims to (1) conduct an RCT comparing NDPP attendance and weight loss outcomes between participants who receive pre-NDPP versus direct enrollment into the NDPP (usual care), (2) examine potential effect mediators (perceived risk for developing diabetes and self-efficacy and readiness for weight control) and moderators (race and ethnicity; income level), and (3) evaluate implementation factors, including cost and projected return on investment.

METHODS

This two-arm RCT will compare outcomes among diverse, predominately low-income participants who receive pre-NDPP versus direct enrollment into the NDPP (usual care). This is a type 1 hybrid effectiveness-implementation design to determine clinical effectiveness through an RCT, while assessing factors that may impact future pre-NDPP dissemination and implementation, including cost. Our primary research question is whether pre-NDPP improves NDPP attendance and weight loss compared with standard NDPP delivery.

RESULTS

This project was funded in April 2019. Recruitment is underway as of July 2019. Initial participants began the intervention in October 2019. Data analysis and results reporting are expected to be completed in 2024.

CONCLUSIONS

This RCT of pre-NDPP may lead to future dissemination of a scalable, evidence-based strategy to improve success of the NDPP, reduce disparities in NDPP effectiveness, and help prevent type 2 diabetes across the country.

CLINICALTRIAL

ClinicalTrials.gov NCT04022499; https://clinicaltrials.gov/ct2/show/NCT04022499.

INTERNATIONAL REGISTERED REPORT

PRR1-10.2196/15499
The Ubiquitous Cognitive Assessment Tool for Smartwatches: Design, Implementation, and Evaluation Study (Preprint)
Authors: Hafiz Pegah , Bardram Jakob Eyvind
Published: June 2020

BACKGROUND

Cognitive functioning plays a significant role in individuals’ mental health, since fluctuations in memory, attention, and executive functions influence their daily task performance. Existing digital cognitive assessment tools cannot be administered in the wild and their test sets are not brief enough to capture frequent fluctuations throughout the day. The ubiquitous availability of mobile and wearable devices may allow their incorporation into a suitable platform for real-world cognitive assessment.

OBJECTIVE

The aims of this study were threefold: (1) to evaluate a smartwatch-based tool for the assessment of cognitive performance, (2) to investigate the usability of this tool, and (3) to understand participants’ perceptions regarding the application of a smartwatch in cognitive assessment.

METHODS

We built the Ubiquitous Cognitive Assessment Tool (UbiCAT) on a smartwatch-based platform. UbiCAT implements three cognitive tests—an Arrow test, a Letter test, and a Color test—adapted from the two-choice reaction-time, N-back, and Stroop tests, respectively. These tests were designed together with domain experts. We evaluated the UbiCAT test measures against standard computer-based tests with 21 healthy adults by applying statistical analyses significant at the 95% level. Usability testing for each UbiCAT app was performed using the Mobile App Rating Scale (MARS) questionnaire. The NASA-TLX (Task Load Index) questionnaire was used to measure cognitive workload during the N-back test. Participants rated perceived discomfort of wearing a smartwatch during the tests using a 7-point Likert scale. Upon finishing the experiment, an interview was conducted with each participant. The interviews were transcribed and semantic analysis was performed to group the findings.

RESULTS

Pearson correlation analysis between the total correct responses obtained from the UbiCAT and the computer-based tests revealed a significant strong correlation (r=.78, P<.001). One-way analysis of variance (ANOVA) showed a significant effect of the N-back difficulty level on the participants' performance measures. The study also demonstrated usability ratings above 4 out of 5 in terms of aesthetics, functionality, and information. Low discomfort (<3 out of 7) was reported by our participants after using the UbiCAT. Seven themes were extracted from the transcripts of the interviews conducted with our participants.

CONCLUSIONS

UbiCAT is a smartwatch-based tool that assesses three key cognitive domains. Usability ratings showed that participants were engaged with the UbiCAT tests and did not feel any discomfort. The majority of the participants were interested in using the UbiCAT, although some preferred computer-based tests, which might be due to the widespread use of personal computers. The UbiCAT can be administered in the wild with mentally ill patients to assess their attention, working memory, and executive function.
Physiological State and Learning Ability of Students in Normal and Virtual Reality Conditions: Complexity-Based Analysis (Preprint)
Authors: Babini Mohammad H , Kulish Vladimir V , Namazi Hamidreza
Published: June 2020

BACKGROUND

Education and learning are the most important goals of all universities. For this purpose, lecturers use various tools to grab the attention of students and improve their learning ability. Virtual reality refers to the subjective sensory experience of being immersed in a computer-mediated world, and has recently been implemented in learning environments.

OBJECTIVE

The aim of this study was to analyze the effect of a virtual reality condition on students’ learning ability and physiological state.

METHODS

Students were shown 6 sets of videos (3 videos in a two-dimensional condition and 3 videos in a three-dimensional condition), and their learning ability was analyzed based on a subsequent questionnaire. In addition, we analyzed the reaction of the brain and facial muscles of the students during both the two-dimensional and three-dimensional viewing conditions and used fractal theory to investigate their attention to the videos.

RESULTS

The learning ability of students was increased in the three-dimensional condition compared to that in the two-dimensional condition. In addition, analysis of physiological signals showed that students paid more attention to the three-dimensional videos.

CONCLUSIONS

A virtual reality condition has a greater effect on enhancing the learning ability of students. The analytical approach of this study can be further extended to evaluate other physiological signals of subjects in a virtual reality condition.
Using a Mobile App-Based International Classification of Functioning, Disability, and Health Set to Assess the Functioning of Spinal Cord Injury Patients: Rasch Analysis (Preprint)
Authors: Jia Mengmeng , Tang Jie , Xie Sumei , He Xiaokuo , Wang Yingmin , Liu Ting , Yan Tiebin , Li Kun
Published: June 2020

BACKGROUND

The International Classification of Functioning, Disability, and Health (ICF) is a unified system of functioning terminology that has been used to develop electronic health records and assessment instruments. Its application has been limited, however, by its complex terminology, numerous categories, uncertain operationalization, and the training required to use it well. Together is a mobile health app designed to extend medical support to the families of spinal cord injury (SCI) patients in China. The app’s core framework is a set of only 31 ICF categories. The app also provides rating guidelines and automatically transforms routine assessment results to the terms of the ICF qualifiers.

OBJECTIVE

The goal of the research is to examine the suitability of the ICF set used in the app Together for use as an instrument for assessing the functioning of SCI patients.

METHODS

A cross-sectional study was conducted including 112 SCI patients recruited before discharge from four rehabilitation centers in China between May 2018 and October 2019. Nurses used the app to assess patient functioning in face-to-face interviews. The resulting data were then subjected to Rasch analysis.

RESULTS

After deleting two categories (family relationships and socializing) and one personal factor (knowledge about spinal cord injury) that did not fit the Rasch model, the body functions and body structures, activities and participation, and contextual factors components of the ICF exhibited adequate fit to the Rasch model. All three demonstrated acceptable person separation indices. The 28 categories retained in the set were free of differential item functioning by gender, age, education level, or etiology.

CONCLUSIONS

Together overcomes some of the obstacles to practical application of the ICF. The app is a reliable assessment tool for assessing functioning after spinal cord injury.
Using Artificial Neural Network Condensation to Facilitate Adaptation of Machine Learning in Medical Settings by Reducing Computational Burden: Model Design and Evaluation Study (Preprint)
Authors: Liu Dianbo , Zheng Ming , Sepulveda Nestor Andres
Published: June 2020

BACKGROUND

Machine learning applications in the health care domain can have a great impact on people’s lives. At the same time, medical data is usually big, requiring a significant number of computational resources. Although this might not be a problem for the wide adoption of machine learning tools in high-income countries, the availability of computational resources can be limited in low-income countries and on mobile devices. This can limit many people from benefiting from the advancement in machine learning applications in the field of health care.

OBJECTIVE

In this study, we explore three methods to increase the computational efficiency and reduce model sizes of either recurrent neural networks (RNNs) or feedforward deep neural networks (DNNs) without compromising their accuracy.

METHODS

We used inpatient mortality prediction as our case analysis upon review of an intensive care unit dataset. We reduced the size of RNN and DNN by applying pruning of “unused” neurons. Additionally, we modified the RNN structure by adding a hidden layer to the RNN cell but reducing the total number of recurrent layers to accomplish a reduction of the total parameters used in the network. Finally, we implemented quantization on DNN by forcing the weights to be 8 bits instead of 32 bits.

RESULTS

We found that all methods increased implementation efficiency, including training speed, memory size, and inference speed, without reducing the accuracy of mortality prediction.

CONCLUSIONS

Our findings suggest that neural network condensation allows for the implementation of sophisticated neural network algorithms on devices with lower computational resources.
COVID-19 ARIMA Model Forecast: Confirmed, Mortality & Recovered Cases in 13 Caribbean Countries (Preprint)
Authors: Talukdar Debjyoti , Tripathi Dr. Vrijesh
Published: June 2020

BACKGROUND

Rapid spread of SARS nCoV-2 virus in Caribbean region has prompted heightened surveillance with more than 350,000 COVID-19 confirmed cases in 13 Caribbean countries namely Antigua and Barbados, Bahamas, Barbados, Cuba, Dominica, Dominican Republic, Grenada, Haiti, Jamaica, Saint Kitts and Nevis, Saint Lucia, Saint Vincent and the Grenadines, Trinidad and Tobago.

OBJECTIVE

The aim of our study is to analyze the impact of coronavirus (SARS nCoV-2) in 13 Caribbean countries in terms of confirmed cases, number of deaths and recovered cases. Current and projected forecasts using advanced autoregressive integrated moving average (ARIMA) models will enable local health organisations to plan future courses of action in terms of lockdown and managing essential public services.

METHODS

The study uses the auto regressive integrated moving average (ARIMA) model based upon time series pattern as per data retrieved from John Hopkins University, freely accessible on public domain and used for research and academic purposes. The data was analyzed using STATA 14 SE software between the time period - Jan 22, 2020 till May 27, 2020 using ARIMA time series analysis. It involves generalizing an autoregressive moving average model to better understand the data and predict future points in the time series until June 15, 2020.

RESULTS

The results show the predicted trend in terms of COVID-19 confirmed, mortality and recovered cases for 13 Caribbean countries. The projected ARIMA model forecast for the time period - May 25, 2020 to May 31, 2020 show 20278 (95% CI 19433.21 - 21123.08) confirmed cases, 631 (95% CI 615.90 - 646.51) deaths and 11501 (95% CI 10912.45 - 12089) recovered cases related to SARS nCoV-2 virus. The final ARIMA model chosen for confirmed COVID-19 cases, number of deaths and recovered cases are ARIMA (4,2,2), ARIMA (2,1,2) and ARIMA (4,1,2) respectively. All chosen models were compared with other models in terms of various factors like AIC/BIC (Akaike Information Criterion/Bayesian Information Criterion), log likelihood, p-value significance, coefficient < 1 and 5% significance. The autocorrelation function (ACF) and partial autocorrelation function (PACF) graphs were plotted to reduce bias and select the best fitting model.

CONCLUSIONS

As per the results of the forecasted COVID-19 models, there is a steady rise in terms of confirmed, recovered and mortality cases during the time period March 1, 2020 until May 27, 2020. It shows an increasing trend for confirmed and recovered COVID-19 cases and slowing of the number of mortality cases over a period of time. The predicted model will help the local health administration to devise public policies in terms of awareness measures, lockdown and essential health services accordingly.
Natural Language Processing for Surveillance of Cervical and Anal Cancer and Precancer: Algorithm Development and Split-Validation Study (Preprint)
Authors: Oliveira Carlos R , Niccolai Patrick , Ortiz Anette Michelle , Sheth Sangini S , Shapiro Eugene D , Niccolai Linda M , Brandt Cynthia A
Published: June 2020

BACKGROUND

Accurate identification of new diagnoses of human papillomavirus–associated cancers and precancers is an important step toward the development of strategies that optimize the use of human papillomavirus vaccines. The diagnosis of human papillomavirus cancers hinges on a histopathologic report, which is typically stored in electronic medical records as free-form, or unstructured, narrative text. Previous efforts to perform surveillance for human papillomavirus cancers have relied on the manual review of pathology reports to extract diagnostic information, a process that is both labor- and resource-intensive. Natural language processing can be used to automate the structuring and extraction of clinical data from unstructured narrative text in medical records and may provide a practical and effective method for identifying patients with vaccine-preventable human papillomavirus disease for surveillance and research.

OBJECTIVE

This study's objective was to develop and assess the accuracy of a natural language processing algorithm for the identification of individuals with cancer or precancer of the cervix and anus.

METHODS

A pipeline-based natural language processing algorithm was developed, which incorporated machine learning and rule-based methods to extract diagnostic elements from the narrative pathology reports. To test the algorithm’s classification accuracy, we used a split-validation study design. Full-length cervical and anal pathology reports were randomly selected from 4 clinical pathology laboratories. Two study team members, blinded to the classifications produced by the natural language processing algorithm, manually and independently reviewed all reports and classified them at the document level according to 2 domains (diagnosis and human papillomavirus testing results). Using the manual review as the gold standard, the algorithm’s performance was evaluated using standard measurements of accuracy, recall, precision, and F-measure.

RESULTS

The natural language processing algorithm’s performance was validated on 949 pathology reports. The algorithm demonstrated accurate identification of abnormal cytology, histology, and positive human papillomavirus tests with accuracies greater than 0.91. Precision was lowest for anal histology reports (0.87, 95% CI 0.59-0.98) and highest for cervical cytology (0.98, 95% CI 0.95-0.99). The natural language processing algorithm missed 2 out of the 15 abnormal anal histology reports, which led to a relatively low recall (0.68, 95% CI 0.43-0.87).

CONCLUSIONS

This study outlines the development and validation of a freely available and easily implementable natural language processing algorithm that can automate the extraction and classification of clinical data from cervical and anal cytology and histology.
Telemedicine in the United States: An Introduction for Students and Residents (Preprint)
Authors: Hyder Maryam A , Razzak Junaid
Published: June 2020

UNSTRUCTURED

Telemedicine refers to the delivery of medical care and provision of general health services from a distance. Telemedicine has been practiced for decades with increasing evidence proving its potential for enhanced quality of care for patients, reduction in hospital readmissions, and increase in savings for both patients and providers. The COVID-19 pandemic has resulted in a significant increase in the reliance on telemedicine and telehealth for provision of health care services. Developments in telemedicine should be structured as complements to current health care procedures, not with the goal of completely digitizing the entire health care system, but rather to use the power of technology to enhance areas that may not be working at their full potential. At the same time, it is also clear that further research is needed on the effectiveness of telemedicine in terms of both financial and patient benefits. We discuss the current and rapidly increasing knowledge about the use of telemedicine in the United States, and identify the gaps in knowledge and opportunities for further research. Beginning with telemedicine’s origins in the United States to its widespread use during the COVID-19 pandemic, we highlight recent developments in legislation, accessibility, and acceptance of telemedicine.