Category: Nevin Manimala

Optom Vis Sci. 2023 Oct 30. doi: 10.1097/OPX.0000000000002078. Online ahead of print.

ABSTRACT

SIGNIFICANCE: This study provides information about the repeatability of Myopia Master and its agreement with Lenstar LS900, which might be useful for the practitioners involved in myopia management.

PURPOSE: Myopia Master is a new optical biometer that measures ocular biometry and refractive error. The purpose of this study is to assess its repeatability (intra-session and short-term inter-session) and its agreement with Lenstar LS900 for the measurement of axial length and corneal curvature.

METHODS: A total of 304 participants including 254 children (Mean age: 13.7 ± 1.6 years) and 50 adults (24 ± 2.9 years) underwent measurements on Myopia Master and Lenstar LS900 to obtain axial length (AL), flat K (K1), and steep K (K2). On a subset of 30 participants, measurements were obtained with Myopia Master in two sessions that were spread over 10 minutes to assess the short-term inter-session repeatability.

RESULTS: The mean standard deviation of Myopia Master in the measurement of axial length in the total sample was 0.01 mm for intra-session, when the best three measurements were considered. The short-term inter-session mean standard deviation for AL, K1, and K2 was 0.06 mm, 0.15 D, and 0.21 D respectively. There were statistically significant differences in mean values of AL (-0.04 ± 0.06 mm), K1 (-0.07 ± 0.15 D), and K2 (-0.24 ± 0.29 D) between Lenstar LS900 and Myopia Master with the Lenstar providing slightly longer axial length and steeper K values. Adults showed better repeatability with Myopia Master and better agreement between the biometers for AL measurement than children. Neither axial length nor refractive error influenced the repeatability or agreement.

CONCLUSIONS: Myopia Master is repeatable for the measurement of axial length and corneal curvature. Considering the differences in axial length between the Myopia Master and Lenstar LS900, caution must be applied when these biometers are used interchangeably.

PMID:37889981 | DOI:10.1097/OPX.0000000000002078

Sci Adv. 2023 Oct 27;9(43):eadg6194. doi: 10.1126/sciadv.adg6194. Epub 2023 Oct 27.

ABSTRACT

An extensive evaluation of disease occurrence after statin use based on a “hypothesis-free” approach remains scarce. To examine the effect of statin use on the potential risk of developing diseases, a propensity score-matched cohort study was executed using data from the National Sample Cohort in South Korea. A total of 7847 statin users and 39,235 nonstatin users were included in the final analysis. The period of statin use was defined as our main time-dependent exposure and was divided into three periods: current, recent, and past. The main outcomes were defined as new-onset diseases with ≥100 events based on the International Statistical Classification of Diseases, 10th Revision. We calculated the adjusted hazard ratios and 95% confidence intervals (CIs) using Cox regression. We found that statin use significantly increased the risk of developing iron deficiency anemia up to 5.04 times (95% CI, 2.11 to 12.03). Therefore, the iron levels of patients using statins should be monitored carefully.

PMID:37889968 | DOI:10.1126/sciadv.adg6194

Chaos. 2023 Oct 1;33(10):103139. doi: 10.1063/5.0165484.

ABSTRACT

Fisher information is a lower bound on the uncertainty in the statistical estimation of classical and quantum mechanical parameters. While some deterministic dynamical systems are not subject to random fluctuations, they do still have a form of uncertainty. Infinitesimal perturbations to the initial conditions can grow exponentially in time, a signature of deterministic chaos. As a measure of this uncertainty, we introduce another classical information, specifically for the deterministic dynamics of isolated, closed, or open classical systems not subject to noise. This classical measure of information is defined with Lyapunov vectors in tangent space, making it less akin to the classical Fisher information and more akin to the quantum Fisher information defined with wavevectors in Hilbert space. Our analysis of the local state space structure and linear stability leads to upper and lower bounds on this information, giving it an interpretation as the net stretching action of the flow. Numerical calculations of this information for illustrative mechanical examples show that it depends directly on the phase space curvature and speed of the flow.

PMID:37889952 | DOI:10.1063/5.0165484

Sex Transm Dis. 2023 Oct 23. doi: 10.1097/OLQ.0000000000001882. Online ahead of print.

ABSTRACT

BACKGROUND: During the 2022 mpox outbreak, most cases were associated with sexual contact and many people with mpox sought care from sexual health clinics and programs. The National Network of STD Clinical Prevention Training Centers (NNPTC), in partnership with Centers for Disease Control and Prevention, conducted a survey of United States sexual health clinics and programs to assess knowledge, practices, and experiences around mpox to inform a future public health response.

METHODS: Between August 31-September 13, 2022, the NNPTC facilitated a web-based survey. Descriptive statistics were generated in R.

RESULTS: Among 168 responses by clinicians (n = 131, 78%) and program staff (n = 37, 22%), more than half (51%) reported at least somewhat significant mpox-related clinical disruptions including burdensome paperwork requirements for mpox testing (40%) and tecovirimat use (88%). Long clinic visits (51%) added additional burden, the median mpox-related visit lasted one hour. Few clinicians felt comfortable with advanced pain management, and clinicians felt most uninformed about pre-exposure (19%) and post-exposure (24%) prophylaxis. Of 89 respondents involved in vaccination, 61% reported using equity strategies; however, accounts of these strategies revealed a focus on guideline or risk factor-based screenings instead of equity activities.

CONCLUSIONS: These findings highlight the substantial impact of the 2022 mpox outbreak on sexual health care in the United States. Critical gaps and barriers were identified that may inform additional mpox training and technical assistance, including challenges with testing, diagnosis, and management as well as a disconnect between programs’ stated goal of equity and operationalization of strategies to achieve equity.

PMID:37889929 | DOI:10.1097/OLQ.0000000000001882

PLoS One. 2023 Oct 27;18(10):e0293511. doi: 10.1371/journal.pone.0293511. eCollection 2023.

ABSTRACT

OBJECTIVES: The current study aimed at ascertaining the depression levels of medical students and their knowledge levels of depression, and exploring the relationship between the level of knowledge and coping styles of the medical students on depression.

METHODS: An online-based survey was developed in Changzhi Medical College. The questionnaire included demographic and socioeconomic data, questions about depression knowledge and copying styles of depression, and the Zung Self-Rating Depression Scale (SDS). A total of 1931 questionnaires were returned by respondents.

RESULTS: The medical students produced a mean SDS score of 44.29 (SD = 11.67). The prevalence of depression was 29.7%. Sophomore, female, and poor family relationships were parameters associated with a higher SDS score. The total correct rate for knowledge of depression was 64.14%. There were statistical differences between with depression students and non-depression students on the rate of the correct answers in the following questions:”Female has more probability”, “Depression can be adjusted by oneself”, “Associated with one’s character”, “Know cure method of depression”, “Know drug use of depression”, “Know depression influence for health”, and “Know prevention method of depression”. Depression students were more likely to have a lower rate of correct answer for above questions. Asking for help from psychological consultation was the primary coping mechanism among the medical students. The logistic regression analysis results found that depressed students who chose the coping way of no ways of coping were more likely to be females OR = 1.470 (1.078, 2.005), residents in rural area OR = 1.496 (1.038, 2.156), in poor family relationships OR = 2.428 (1.790, 3.293), and have lower cognitive level of depression knowledge OR = 1.920 (1.426, 3.226).

CONCLUSIONS: It is necessary to focus on mental health of medical students, especially in female, residents in rural area, in poor family relationships, and having lower cognitive level of depression knowledge. Medical students were insufficient on depression knowledge and coping styles, and efforts that train students know risk of impaired mental health could also improve diagnosis and treatment.

PMID:37889924 | DOI:10.1371/journal.pone.0293511

PLoS One. 2023 Oct 27;18(10):e0287983. doi: 10.1371/journal.pone.0287983. eCollection 2023.

ABSTRACT

Currently, there is a large deviation between official road freight data and real road freight performance at a subnational level in China. In order to deal with this deviation, the new concept of local freight tonnage and ton-kilometers is presented in this paper based on the territoriality principle, where either the origin or the destination of goods transported is local. Also, the statistic procedures and estimation models of the local freight tonnage and ton-kilometers are proposed based on five accessible basic datasets. Finally, an empirical study in Sichuan province of China is conducted. The statistical results show that there is a large amount of local freight transported by local non-commercial trucks and non-local trucks, which is ignored in the existing road freight statistics. Especially, the higher the level of local economic development, the greater the deviation between the official road freight data and the real road freight performance at a subnational level.

PMID:37889923 | DOI:10.1371/journal.pone.0287983

PLOS Digit Health. 2023 Oct 27;2(10):e0000233. doi: 10.1371/journal.pdig.0000233. eCollection 2023 Oct.

ABSTRACT

During the COVID-19 pandemic, the use of mobile phone data for monitoring human mobility patterns has become increasingly common, both to study the impact of travel restrictions on population movement and epidemiological modeling. Despite the importance of these data, the use of location information to guide public policy can raise issues of privacy and ethical use. Studies have shown that simple aggregation does not protect the privacy of an individual, and there are no universal standards for aggregation that guarantee anonymity. Newer methods, such as differential privacy, can provide statistically verifiable protection against identifiability but have been largely untested as inputs for compartment models used in infectious disease epidemiology. Our study examines the application of differential privacy as an anonymisation tool in epidemiological models, studying the impact of adding quantifiable statistical noise to mobile phone-based location data on the bias of ten common epidemiological metrics. We find that many epidemiological metrics are preserved and remain close to their non-private values when the true noise state is less than 20, in a count transition matrix, which corresponds to a privacy-less parameter ϵ = 0.05 per release. We show that differential privacy offers a robust approach to preserving individual privacy in mobility data while providing useful population-level insights for public health. Importantly, we have built a modular software pipeline to facilitate the replication and expansion of our framework.

PMID:37889905 | DOI:10.1371/journal.pdig.0000233

PLoS One. 2023 Oct 27;18(10):e0293628. doi: 10.1371/journal.pone.0293628. eCollection 2023.

ABSTRACT

In social surveys, the randomized response technique can be considered a popular method for collecting reliable information on sensitive variables. Over the past few decades, it has been a common practice that survey researchers develop new randomized response techniques and show their improvement over previous models. In majority of the available research studies, the authors tend to report only those findings which are favorable to their proposed models. They often tend to hide the situations where their proposed randomized response models perform worse than the already available models. This approach results in biased comparisons between models which may influence the decision of practitioners about the choice of a randomized response technique for real-life problems. We conduct a neutral comparative study of four available quantitative randomized response techniques using separate and combined metrics of respondents’ privacy level and model’s efficiency. Our findings show that, depending on the particular situation at hand, some models may be better than the other models for a particular choice of values of parameters and constants. However, they become less efficient when a different set of parameter values are considered. The mathematical conditions for efficiency of different models have also been obtained.

PMID:37889902 | DOI:10.1371/journal.pone.0293628

PLoS Comput Biol. 2023 Oct 27;19(10):e1011583. doi: 10.1371/journal.pcbi.1011583. Online ahead of print.

ABSTRACT

Clot formation is a crucial process that prevents bleeding, but can lead to severe disorders when imbalanced. This process is regulated by the coagulation cascade, a biochemical network that controls the enzyme thrombin, which converts soluble fibrinogen into the fibrin fibers that constitute clots. Coagulation cascade models are typically complex and involve dozens of partial differential equations (PDEs) representing various chemical species’ transport, reaction kinetics, and diffusion. Solving these PDE systems computationally is challenging, due to their large size and multi-scale nature. We propose a multi-fidelity strategy to increase the efficiency of coagulation cascade simulations. Leveraging the slower dynamics of molecular diffusion, we transform the governing PDEs into ordinary differential equations (ODEs) representing the evolution of species concentrations versus blood residence time. We then Taylor-expand the ODE solution around the zero-diffusivity limit to obtain spatiotemporal maps of species concentrations in terms of the statistical moments of residence time, [Formula: see text], and provide the governing PDEs for [Formula: see text]. This strategy replaces a high-fidelity system of N PDEs representing the coagulation cascade of N chemical species by N ODEs and p PDEs governing the residence time statistical moments. The multi-fidelity order(p) allows balancing accuracy and computational cost providing a speedup of over N/p compared to high-fidelity models. Moreover, this cost becomes independent of the number of chemical species in the large computational meshes typical of the arterial and cardiac chamber simulations. Using a coagulation network with N = 9 and an idealized aneurysm geometry with a pulsatile flow as a benchmark, we demonstrate favorable accuracy for low-order models of p = 1 and p = 2. The thrombin concentration in these models departs from the high-fidelity solution by under 20% (p = 1) and 2% (p = 2) after 20 cardiac cycles. These multi-fidelity models could enable new coagulation analyses in complex flow scenarios and extensive reaction networks. Furthermore, it could be generalized to advance our understanding of other reacting systems affected by flow.

PMID:37889899 | DOI:10.1371/journal.pcbi.1011583

PLoS Comput Biol. 2023 Oct 27;19(10):e1011582. doi: 10.1371/journal.pcbi.1011582. Online ahead of print.

ABSTRACT

Cell lineage decisions occur in three-dimensional spatial patterns that are difficult to identify by eye. There is an ongoing effort to replicate such patterns using mathematical modeling. One approach uses long ranging cell-cell communication to replicate common spatial arrangements like checkerboard and engulfing patterns. In this model, the cell-cell communication has been implemented as a signal that disperses throughout the tissue. On the other hand, machine learning models have been developed for pattern recognition and pattern reconstruction tasks. We combined synthetic data generated by the mathematical model with spatial summary statistics and deep learning algorithms to recognize and reconstruct cell fate patterns in organoids of mouse embryonic stem cells. Application of Moran’s index and pair correlation functions for in vitro and synthetic data from the model showed local clustering and radial segregation. To assess the patterns as a whole, a graph neural network was developed and trained on synthetic data from the model. Application to in vitro data predicted a low signal dispersion value. To test this result, we implemented a multilayer perceptron for the prediction of a given cell fate based on the fates of the neighboring cells. The results show a 70% accuracy of cell fate imputation based on the nine nearest neighbors of a cell. Overall, our approach combines deep learning with mathematical modeling to link cell fate patterns with potential underlying mechanisms.

PMID:37889897 | DOI:10.1371/journal.pcbi.1011582