Tag: nevin manimala

PLoS Comput Biol. 2021 Dec 8;17(12):e1009623. doi: 10.1371/journal.pcbi.1009623. Online ahead of print.

ABSTRACT

Stochastic models of biomolecular reaction networks are commonly employed in systems and synthetic biology to study the effects of stochastic fluctuations emanating from reactions involving species with low copy-numbers. For such models, the Kolmogorov’s forward equation is called the chemical master equation (CME), and it is a fundamental system of linear ordinary differential equations (ODEs) that describes the evolution of the probability distribution of the random state-vector representing the copy-numbers of all the reacting species. The size of this system is given by the number of states that are accessible by the chemical system, and for most examples of interest this number is either very large or infinite. Moreover, approximations that reduce the size of the system by retaining only a finite number of important chemical states (e.g. those with non-negligible probability) result in high-dimensional ODE systems, even when the number of reacting species is small. Consequently, accurate numerical solution of the CME is very challenging, despite the linear nature of the underlying ODEs. One often resorts to estimating the solutions via computationally intensive stochastic simulations. The goal of the present paper is to develop a novel deep-learning approach for computing solution statistics of high-dimensional CMEs by reformulating the stochastic dynamics using Kolmogorov’s backward equation. The proposed method leverages superior approximation properties of Deep Neural Networks (DNNs) to reliably estimate expectations under the CME solution for several user-defined functions of the state-vector. This method is algorithmically based on reinforcement learning and it only requires a moderate number of stochastic simulations (in comparison to typical simulation-based approaches) to train the “policy function”. This allows not just the numerical approximation of various expectations for the CME solution but also of its sensitivities with respect to all the reaction network parameters (e.g. rate constants). We provide four examples to illustrate our methodology and provide several directions for future research.

PMID:34879062 | DOI:10.1371/journal.pcbi.1009623

J Craniofac Surg. 2021 Dec 7. doi: 10.1097/SCS.0000000000008404. Online ahead of print.

ABSTRACT

BACKGROUND: Baseball is 1 of the most played sports among adolescents in the United States. Yet, youth baseball players experience the greatest number of oral and facial injuries, compared to other athletes involved in other sports.

METHODS: The National Electronic Injury Surveillance System was analyzed for all hospital admissions for youth baseball athletes (5-19-year-old) experiencing a baseball-related craniofacial injury. These included concussions, head contusions, head lacerations, facial contusions, facial fractures, facial hematomas, face lacerations, eye contusions, mouth lacerations, dental injuries, and neck contusions. Descriptive statistics were performed, and injury incidence was described by sport, injury type, and age group.

RESULTS: Nearly half of the injuries (45.0%) occurred among 10- to 14-year-old patients, followed by 5- to 9-year-olds and 15- to 19-year-olds. Of all age groups, the most common type of injury was facial contusions, compromising one fourth of the injuries. Other frequent injuries included facial lacerations (19.9%), facial fractures (19.7%), and concussions (13.4%).

CONCLUSIONS: Overall, this analysis underscores the need for increased implementation of protective equipment, such as faceguards and safety balls. Although facial fractures are less common amongst the pediatric population, physicians and coaches need to be better educated about the most frequent injury patterns and management. Further prospective studies are warranted to better characterize these findings and to prevent injuries.

PMID:34879017 | DOI:10.1097/SCS.0000000000008404

JMIR Public Health Surveill. 2021 Dec 7;7(12):e33296. doi: 10.2196/33296.

ABSTRACT

BACKGROUND: Many factors contribute to the spreading of hospital-acquired infections (HAIs).

OBJECTIVE: This study aimed to standardize the HAI rate using prediction models in Iran based on the National Healthcare Safety Network (NHSN) method.

METHODS: In this study, the Iranian nosocomial infections surveillance system (INIS) was used to gather data on patients with HAIs (126,314 infections). In addition, the hospital statistics and information system (AVAB) was used to collect data on hospital characteristics. First, well-performing hospitals, including 357 hospitals from all over the country, were selected. Data were randomly split into training (70%) and testing (30%) sets. Finally, the standardized infection ratio (SIR) and the corrected SIR were calculated for the HAIs.

RESULTS: The mean age of the 100,110 patients with an HAI was 40.02 (SD 23.56) years. The corrected SIRs based on the observed and predicted infections for respiratory tract infections (RTIs), urinary tract infections (UTIs), surgical site infections (SSIs), and bloodstream infections (BSIs) were 0.03 (95% CI 0-0.09), 1.02 (95% CI 0.95-1.09), 0.93 (95% CI 0.85-1.007), and 0.91 (95% CI 0.54-1.28), respectively. Moreover, the corrected SIRs for RTIs in the infectious disease, burn, obstetrics and gynecology, and internal medicine wards; UTIs in the burn, infectious disease, internal medicine, and intensive care unit wards; SSIs in the burn and infectious disease wards; and BSIs in most wards were >1, indicating that more HAIs were observed than expected.

CONCLUSIONS: The results of this study can help to promote preventive measures based on scientific evidence. They can also lead to the continuous improvement of the monitoring system by collecting and systematically analyzing data on HAIs and encourage the hospitals to better control their infection rates by establishing a benchmarking system.

PMID:34879002 | DOI:10.2196/33296

J Acquir Immune Defic Syndr. 2021 Dec 7. doi: 10.1097/QAI.0000000000002880. Online ahead of print.

ABSTRACT

BACKGROUND: People with HIV (PWH) smoke tobacco at much higher rates than the general population. Prior research has shown that PWH have faster nicotine metabolism than HIV-uninfected individuals which may underlie this disparity, but the cause is unknown. We investigated whether higher nicotine metabolite ratio (NMR; 3-hydroxycotinine:cotinine), a validated biomarker of nicotine metabolism via CYP2A6, was associated with antiretroviral use among HIV-infected smokers.

METHODS: We conducted a retrospective cohort study of HIV-positive smokers in the University of Pennsylvania Center for AIDS Research cohort. We compared the NMR before viral suppression (>10,000 copies/ml) and after viral suppression on ART (<200 copies/ml). We used mixed effects linear regression to analyze the change in NMR after viral suppression and assessed for effect modification by efavirenz use.

RESULTS: Eighty-nine individuals were included in the study. We observed effect modification by efavirenz use (interaction term for efavirenz use, P<0.001). Among those on non-efavirenz regimens, the mean NMR increased by 0.14 (95% CI 0.05-0.23, P=0.002). Among those on efavirenz-containing regimens, the mean NMR increased by 0.53 (95% CI 0.39-0.66, P<0.001).

CONCLUSION: We observed a clinically and statistically significant increase in NMR after viral suppression among smokers with HIV, which more than doubled among those on efavirenz-based regimens. Higher NMR among HIV-positive smokers on ART may help explain the higher rates of tobacco use and lower quit rates among PWH in care. These findings suggest that regimen choice and other modifiable factors may be targets for future attempts to increase success rates for tobacco cessation among PWH.

PMID:34879005 | DOI:10.1097/QAI.0000000000002880

JMIR Mhealth Uhealth. 2021 Dec 7;9(12):e26185. doi: 10.2196/26185.

ABSTRACT

BACKGROUND: The successful management of heart failure (HF) involves guideline-based medical therapy as well as self-management behavior. As a result, the management of HF is moving toward a proactive real-time technological model of assisting patients with monitoring and self-management.

OBJECTIVE: The aim of this paper was to evaluate the efficacy of enhanced self-management via a mobile app intervention on health-related quality of life, self-management, and HF readmissions.

METHODS: A single-center randomized controlled trial was performed. Participants older than 45 years and admitted for acute decompensated HF or recently discharged in the past 4 weeks were included. The intervention group (“app group”) used a mobile app, and the intervention prompted daily self-monitoring and promoted self-management. The control group (“no-app group”) received usual care. The primary outcome was the change in Minnesota Living with Heart Failure Questionnaire (MLHFQ) score from baseline to 6 and 12 weeks. Secondary outcomes were the Self-Care Heart Failure Index (SCHFI) questionnaire score and recurrent HF admissions.

RESULTS: A total of 83 participants were enrolled and completed all baseline assessments. Baseline characteristics were similar between the groups except for the prevalence of ischemic HF. The app group had a reduced MLHFQ at 6 weeks (mean 37.5, SD 3.5 vs mean 48.2, SD 3.7; P=.04) but not at 12 weeks (mean 44.2, SD 4 vs mean 45.9, SD 4; P=.78), compared to the no-app group. There was no effect of the app on the SCHFI at 6 or 12 weeks. The time to first HF readmission was not statistically different between the app group and the no-app group (app group 11/42, 26% vs no-app group 12/41, 29%; hazard ratio 0.89, 95% CI 0.39-2.02; P=.78) over 12 weeks.

CONCLUSIONS: The adaptive mobile app intervention, which focused on promoting self-monitoring and self-management, improved the MLHFQ at 6 weeks but did not sustain its effects at 12 weeks. No effect was seen on HF self-management measured by self-report. Further research is needed to enhance engagement in the app for a longer period and to determine if the app can reduce HF readmissions in a larger study.

TRIAL REGISTRATION: ClinicalTrials.gov NCT03149510; https://clinicaltrials.gov/ct2/show/NCT03149510.

PMID:34878990 | DOI:10.2196/26185

JMIR Form Res. 2021 Dec 7;5(12):e33123. doi: 10.2196/33123.

ABSTRACT

BACKGROUND: Individuals with autism spectrum disorder (ASD) often exhibit difficulties in social and communication skills. For more than 30 years, specialists, parents, and caregivers have used techniques, such as applied behavioral analysis, augmentative and alternative communication, and the picture exchange communication system to support the social and communication skills of people with ASD. Even though there are many techniques devised to enhance communication, these techniques are not considered in existing social media apps for people with ASD.

OBJECTIVE: This study aimed to investigate the effect of adding accessibility features, such as text-to-speech (TTS), speech-to-text (STT), and communication symbols (CS), to a messaging app (MAAN). We hypothesized that these accessibility features can enhance the social and communication skills of adults with ASD. We also hypothesized that usage of this app can reduce social loneliness in adults with ASD.

METHODS: Semistructured interviews were conducted with 5 experts working in fields related to ASD to help design the app. Seven adults with ASD participated in the study for a period of 10 to 16 weeks. Data logs of participants’ interactions with the app were collected. Additionally, 6 participants’ parents and 1 caregiver were asked to complete a short version of the Social and Emotional Loneliness Scale for Adults (SELSA-S) questionnaire to compare pre-post study results. The Mobile Application Rating Scale: user version questionnaire was also used to evaluate the app’s usability. Following the study, interviews were conducted with participants to discuss their experiences with the app.

RESULTS: The SELSA-S questionnaire results showed no change in the family subscale; however, the social loneliness subscale showed a difference between prestudy and poststudy. The Wilcoxon signed-rank test indicated that poststudy SELSA-S results were statistically significantly higher than prestudy results (z=-2.047; P=.04). Point-biserial correlation indicated that the SELSA-S rate of change was strongly related to usage of the TTS feature (r=0.708; P=.04) and CS feature (r=-0.917; P=.002), and moderately related to usage of the STT feature (r=0.428; P=.17). Lastly, we adopted grounded theory to analyze the interview data, and the following 5 categories emerged: app support, feature relevance, user interface design, overall feedback, and recommendations.

CONCLUSIONS: This study discusses the potential for improving the communication skills of adults with ASD through special features in mobile messaging apps. The developed app aims to support the inclusion and independent life of adults with ASD. The study results showed the importance of using TTS, STT, and CS features to enhance social and communication skills, as well as reduce social loneliness in adults with ASD.

PMID:34878998 | DOI:10.2196/33123

J Med Internet Res. 2021 Dec 7;23(12):e21681. doi: 10.2196/21681.

ABSTRACT

BACKGROUND: Massive open online course (MOOC) research is an emerging field; to date, most research in this area has focused on participant engagement.

OBJECTIVE: The aim of this study is to evaluate both participant engagement and measures of satisfaction, appropriateness, and burden for a MOOC entitled Understanding Multiple Sclerosis (MS) among a cohort of 3518 international course participants.

METHODS: We assessed the association of key outcomes with participant education level, MS status, caregiver status, sex, and age using summary statistics, and 2-tailed t tests, and chi-square tests.

RESULTS: Of the 3518 study participants, 928 (26.37%) were people living with MS. Among the 2590 participants not living with MS, 862 (33.28%) identified as formal or informal caregivers. Our key findings were as follows: the course completion rate among study participants was 67.17% (2363/3518); the course was well received, with 96.97% (1502/1549) of participants satisfied, with an appropriate pitch and low burden (a mean of 2.2 hours engagement per week); people living with MS were less likely than those not living with MS to complete the course; and people with a recent diagnosis of MS, caregivers, and participants without a university education were more likely to apply the material by course completion.

CONCLUSIONS: The Understanding MS MOOC is fit for purpose; it presents information in a way that is readily understood by course participants and is applicable in their lives.

PMID:34878985 | DOI:10.2196/21681

J Med Internet Res. 2021 Dec 7;23(12):e28021. doi: 10.2196/28021.

ABSTRACT

BACKGROUND: Researchers face challenges in patient recruitment, especially for rare, fatal diseases such as amyotrophic lateral sclerosis (ALS). These challenges include obtaining sufficient statistical power as well as meeting eligibility requirements such as age, sex, and study proximity. Similarly, persons with ALS (PALS) face difficulty finding and enrolling in research studies for which they are eligible.

OBJECTIVE: The aim of this study was to describe how the federal Agency for Toxic Substances and Disease Registry’s (ATSDR) National ALS Registry is linking PALS to scientists who are conducting research, clinical trials, and epidemiological studies.

METHODS: Through the Registry’s online research notification mechanism (RNM), PALS can elect to be notified about new research opportunities. This mechanism allows researchers to upload a standardized application outlining their study design and objectives, and proof of Institutional Review Board approval. If the application is approved, ATSDR queries the Registry for PALS meeting the study’s specific eligibility criteria, and then distributes the researcher’s study material and contact information to PALS via email. PALS then need to contact the researcher directly to take part in any research. Such an approach allows ATSDR to protect the confidentiality of Registry enrollees.

RESULTS: From 2013 to 2019, a total of 46 institutions around the United States and abroad have leveraged this tool and over 600,000 emails have been sent, resulting in over 2000 patients conservatively recruited for clinical trials and epidemiological studies. Patients between the ages of 60 and 69 had the highest level of participation, whereas those between the ages of 18 and 39 and aged over 80 had the lowest. More males participated (4170/7030, 59.32%) than females (2860/7030, 40.68%).

CONCLUSIONS: The National ALS Registry’s RNM benefits PALS by connecting them to appropriate ALS research. Simultaneously, the system benefits researchers by expediting recruitment, increasing sample size, and efficiently identifying PALS meeting specific eligibility requirements. As more researchers learn about and use this mechanism, both PALS and researchers can hasten research and expand trial options for PALS.

PMID:34878988 | DOI:10.2196/28021

IEEE Trans Ultrason Ferroelectr Freq Control. 2021 Dec 8;PP. doi: 10.1109/TUFFC.2021.3134163. Online ahead of print.

ABSTRACT

We perform experiments exploring the use of White Rabbit PTP for time and frequency dissemination over long-distance optical fiber links. We use unidirectional links, to ensure compatibility with active telecommunication networks, and White Rabbit equipment with modifications for improved performance. Using fiber spools, we realize a 500 km, four-span cascaded White Rabbit link. We show short term fractional frequency stability of 2×10-12, averaging down to 2×10-15 at one day of integration time, with no frequency shift within the statistical uncertainty. We demonstrate the impact of increasing the White Rabbit SoftPLL bandwidth and the PTP message rate. We show evidence of the effect of thermal fluctuations acting on the fiber, and finally discuss the limitations of the achieved performance. We show comparisons with experimental data acquired with commercial good quality GPS receivers and show that the medium- and long- term stability and accuracy are more than one order of magnitude better with a White Rabbit PTP link.

PMID:34878974 | DOI:10.1109/TUFFC.2021.3134163

Curr Med Res Opin. 2021 Dec 8:1-22. doi: 10.1080/03007995.2021.2010437. Online ahead of print.

ABSTRACT

OBJECTIVE: The SPUR (Social, Psychological, Usage and Rational) Adherence Profiling Tool is a recently developed adaptive instrument for measuring key patient-level risk factors for adherence problems. This study describes the SPUR questionnaire’s psychometric refinement and evaluation.

METHODS: Data were collected through an online survey among individuals with type 2 diabetes in the United States. 501 participants completed multiple questionnaires, including SPUR and several validated adherence measures.A Partial Credit Model (PCM) analysis was performed to evaluate the structure of the SPUR tool and verify the assumption of a single underlying latent variable reflecting adherence. Partial least-squares discriminant analyses (PLS-DA) were conducted to identify which hierarchically-defined items within each dimension needed to be answered by a given patient. Lastly, correlations were calculated between the latent trait of SPUR adherence and other patient-reported adherence measures.

RESULTS: Of the 45 candidate SPUR items, 39 proved to fit well to the PCM confirming that SPUR responses reflected one underlying latent trait hypothesized as non-adherence. Correlations between the latent trait of the SPUR tool and other adherence measures were positive, statistically significant and ranged from 0.32 to 0.48 (p-values <0.0001). The person-item map showed that the items reflected well the range of adherence behaviors from perfect adherence to high levels of non-adherence. The PLS-DA results confirmed the relevance of using four meta-items as filters to open or close subsequent items from their corresponding SPUR dimensions.

CONCLUSIONS: The SPUR tool represents a promising new adaptive instrument for measuring adherence accurately and efficiently using digital behavioral diagnostic tool.

PMID:34878967 | DOI:10.1080/03007995.2021.2010437