Tag: statistics

Sci Rep. 2023 Feb 10;13(1):2423. doi: 10.1038/s41598-023-29585-x.

ABSTRACT

Competing endogenous RNAs (ceRNAs) have gained attention in cancer research owing to their involvement in microRNA-mediated gene regulation. Previous studies have identified ceRNA networks of individual cancers. Nevertheless, none of these studies has investigated different cancer stages. We identify stage-specific ceRNAs in breast cancer using the cancer genome atlas data. Moreover, we investigate the molecular functions and prognostic ability of ceRNAs involved in stage I-IV networks. We identified differentially expressed candidate ceRNAs using edgeR and limma R packages. A three-step analysis was used to identify statistically significant ceRNAs of each stage. Survival analysis and functional enrichment analysis were conducted to identify molecular functions and prognostic ability. We found five genes and one long non-coding RNA unique to the stage IV ceRNA network. These genes have been described in previous breast cancer studies. Genes acted as ceRNAs are enriched in cancer-associated pathways. Two, three, and three microRNAs from stages I, II, and III were prognostic from the Kaplan-Meier survival analysis. Our results reveal a set of unique ceRNAs in metastatic breast cancer. Further experimental work is required to evaluate their role in metastasis. Moreover, identifying stage-specific ceRNAs will improve the understanding of personalised therapeutics in breast cancer.

PMID:36765262 | DOI:10.1038/s41598-023-29585-x

Sci Rep. 2023 Feb 10;13(1):2434. doi: 10.1038/s41598-023-29625-6.

ABSTRACT

Bazhong City is located on stratum dominated by red-bed conditions. This type of weak geological condition with sand and mudstone interbedding is very easily affected by climatic conditions to produce rainfall-type landslides. On the basis of landslide data statistics collected in Bazhong City from 2011 to 2019, this paper uses ERA5-Land rainfall data to statistically analyze the correlation between rainfall and landslide events in Bazhong City. The landslide events in Bazhong City are greatly affected by rainfall events lasting for 10 days. Considering the influence of rainfall seepage and other processes, an effective cumulative rainfall-duration threshold curve for Bazhong City is obtained via median nonlinear fitting. Then, on the basis of the prediction interval, the rainfall threshold formula under different landslide occurrence probabilities is obtained and the critical threshold curve with a non-exceeding probability of 1% in Bazhong City is calculated and verified. Subsequently, a continuous probability distribution fitting function of landslide occurrence is established and a continuous probability distribution surface with a good fitting effect in Bazhong City is obtained. This allows a definite probability of whether future rainfall events will induce landslides to be obtained, providing an important basis for engineering disaster prevention and mitigation.

PMID:36765198 | DOI:10.1038/s41598-023-29625-6

Sci Rep. 2023 Feb 10;13(1):2414. doi: 10.1038/s41598-023-29635-4.

ABSTRACT

Clinical gait analysis is an important biomechanics field that is often influenced by subjectivity in time-varying analysis leading to type I and II errors. Statistical Parametric Mapping can operate on all time-varying joint dynamics simultaneously, thereby overcoming subjectivity errors. We present MovementRx, the first gait analysis modelling application that correctly models the deviations of joints kinematics and kinetics both in 3 and 1 degrees of freedom; presented with easy-to-understand color maps for clinicians with limited statistical training. MovementRx is a python-based versatile GUI-enabled movement analysis decision support system, that provides a holistic view of all lower limb joints fundamental to the kinematic/kinetic chain related to functional gait. The user can cascade the view from single 3D multivariate result down to specific single joint individual 1D scalar movement component in a simple, coherent, objective, and visually intuitive manner. We highlight MovementRx benefit by presenting a case-study of a right knee osteoarthritis (OA) patient with otherwise undetected postintervention contralateral OA predisposition. MovementRx detected elevated frontal plane moments of the patient’s unaffected knee. The patient also revealed a surprising adverse compensation to the contralateral limb.

PMID:36765193 | DOI:10.1038/s41598-023-29635-4

Sci Rep. 2023 Feb 10;13(1):2398. doi: 10.1038/s41598-023-29523-x.

ABSTRACT

Individuals of many animal populations exhibit idiosyncratic behaviors. One measure of idiosyncratic behavior is a behavior syndrome, defined as the stability of one or more behavior traits in an individual across different situations. While behavior syndromes have been described in various animal systems, their properties and the circuit mechanisms that generate them are poorly understood. We thus have an incomplete understanding of how circuit properties influence animal behavior. Here, we characterize olfactory behavior syndromes in the Drosophila larva. We show that larvae exhibit idiosyncrasies in their olfactory behavior over short time scales. They are influenced by the larva’s satiety state and odor environment. Additionally, we identified a group of antennal lobe local neurons that influence the larva’s idiosyncratic behavior. These findings reveal previously unsuspected influences on idiosyncratic behavior. They further affirm the idea that idiosyncrasies are not simply statistical phenomena but manifestations of neural mechanisms. In light of these findings, we discuss more broadly the importance of idiosyncrasies to animal survival and how they might be studied.

PMID:36765192 | DOI:10.1038/s41598-023-29523-x

Commun Med (Lond). 2023 Feb 10;3(1):21. doi: 10.1038/s43856-023-00250-8.

ABSTRACT

BACKGROUND: Patients with Type 2 diabetes mellitus (T2D) are at risk for micro- and macrovascular complications. Implementable risk scores are needed to improve targeted prevention for patients that are particularly susceptible to complications. The epigenetic clock estimates an individual’s biological age using DNA methylation profiles.

METHODS: In this study, we examined older adults of the Berlin Aging Study II that were reexamined on average 7.4 years after baseline assessment as part of the GendAge study. DNA methylation age (DNAmA) and its deviation from chronological age DNAmA acceleration (DNAmAA) were calculated with the 7-CpG clock (available at both timepoints, n = 1,071), Horvath’s clock, Hannum’s clock, PhenoAge and GrimAge (available at follow-up only, n = 1,067). T2D associated complications were assessed with the Diabetes Complications Severity Index (DCSI).

RESULTS: We report on a statistically significant association between oral glucose tolerance test results and Hannum and PhenoAge DNAmAA. PhenoAge was also associated with fasting glucose. In contrast, we found no cross-sectional association after covariate adjustment between DNAmAA and a diagnosis of T2D. However, longitudinal analyses showed that every additional year of 7-CpG DNAmAA at baseline increased the odds for developing one or more additional complications or worsening of an already existing complication during the follow-up period by 11% in male participants with T2D. This association persisted after covariate adjustment (OR = 1.11, p = 0.045, n = 56).

CONCLUSION: Although our results remain to be independently validated, this study shows promising evidence of utility of the 7-CpG clock in identifying patients with diabetes who are at high risk for developing complications.

PMID:36765171 | DOI:10.1038/s43856-023-00250-8

Nat Methods. 2023 Feb;20(2):259-267. doi: 10.1038/s41592-022-01750-6. Epub 2023 Feb 10.

ABSTRACT

Single-molecule localization microscopy (SMLM) generates data in the form of coordinates of localized fluorophores. Cluster analysis is an attractive route for extracting biologically meaningful information from such data and has been widely applied. Despite a range of cluster analysis algorithms, there exists no consensus framework for the evaluation of their performance. Here, we use a systematic approach based on two metrics to score the success of clustering algorithms in simulated conditions mimicking experimental data. We demonstrate the framework using seven diverse analysis algorithms: DBSCAN, ToMATo, KDE, FOCAL, CAML, ClusterViSu and SR-Tesseler. Given that the best performer depended on the underlying distribution of localizations, we demonstrate an analysis pipeline based on statistical similarity measures that enables the selection of the most appropriate algorithm, and the optimized analysis parameters for real SMLM data. We propose that these standard simulated conditions, metrics and analysis pipeline become the basis for future analysis algorithm development and evaluation.

PMID:36765136 | DOI:10.1038/s41592-022-01750-6

Sci Rep. 2023 Feb 10;13(1):2435. doi: 10.1038/s41598-023-28752-4.

ABSTRACT

One clear aspect of behaviour in the COVID-19 pandemic has been people’s focus on, and response to, reported or observed infection numbers in their community. We describe a simple model of infectious disease spread in a pandemic situation where people’s behaviour is influenced by the current risk of infection and where this behavioural response acts homeostatically to return infection risk to a certain preferred level. This homeostatic response is active until approximate herd immunity is reached: in this domain the model predicts that the reproduction rate R will be centred around a median of 1, that proportional change in infection numbers will follow the standard Cauchy distribution with location and scale parameters 0 and 1, and that high infection numbers will follow a power-law frequency distribution with exponent 2. To test these predictions we used worldwide COVID-19 data from 1st February 2020 to 30th June 2022 to calculate [Formula: see text] confidence interval estimates across countries for these R, location, scale and exponent parameters. The resulting median R estimate was [Formula: see text] (predicted value 1) the proportional change location estimate was [Formula: see text] (predicted value 0), the proportional change scale estimate was [Formula: see text] (predicted value 1), and the frequency distribution exponent estimate was [Formula: see text] (predicted value 2); in each case the observed estimate agreed with model predictions.

PMID:36765110 | DOI:10.1038/s41598-023-28752-4

Sci Data. 2023 Feb 10;10(1):86. doi: 10.1038/s41597-023-01961-2.

ABSTRACT

Understanding the fine scale and subnational spatial distribution of reproductive, maternal, newborn, child, and adolescent health and development indicators is crucial for targeting and increasing the efficiency of resources for public health and development planning. National governments are committed to improve the lives of their people, lift the population out of poverty and to achieve the Sustainable Development Goals. We created an open access collection of high resolution gridded and district level health and development datasets of India using mainly the 2015-16 National Family Health Survey (NFHS-4) data, and provide estimates at higher granularity than what is available in NFHS-4, to support policies with spatially detailed data. Bayesian methods for the construction of 5 km × 5 km high resolution maps were applied for a set of indicators where the data allowed (36 datasets), while for some other indicators, only district level data were produced. All data were summarised using the India district administrative boundaries. In total, 138 high resolution and district level datasets for 28 indicators were produced and made openly available.

PMID:36765058 | DOI:10.1038/s41597-023-01961-2

Nat Commun. 2023 Feb 10;14(1):761. doi: 10.1038/s41467-022-35712-5.

ABSTRACT

The anticipation of progression of Alzheimer’s disease (AD) is crucial for evaluations of secondary prevention measures thought to modify the disease trajectory. However, it is difficult to forecast the natural progression of AD, notably because several functions decline at different ages and different rates in different patients. We evaluate here AD Course Map, a statistical model predicting the progression of neuropsychological assessments and imaging biomarkers for a patient from current medical and radiological data at early disease stages. We tested the method on more than 96,000 cases, with a pool of more than 4,600 patients from four continents. We measured the accuracy of the method for selecting participants displaying a progression of clinical endpoints during a hypothetical trial. We show that enriching the population with the predicted progressors decreases the required sample size by 38% to 50%, depending on trial duration, outcome, and targeted disease stage, from asymptomatic individuals at risk of AD to subjects with early and mild AD. We show that the method introduces no biases regarding sex or geographic locations and is robust to missing data. It performs best at the earliest stages of disease and is therefore highly suitable for use in prevention trials.

PMID:36765056 | DOI:10.1038/s41467-022-35712-5

BDJ Open. 2023 Feb 10;9(1):5. doi: 10.1038/s41405-023-00131-1.

ABSTRACT

OBJECTIVES: To determine the overall estimated financial impact and related expenses incurred over the duration of the undergraduate Dental Degree in Thailand.

METHODS: A cross-sectional survey was conducted among all 658 dental undergraduates in Mahidol University, Thailand. Data was collected through a self-administered questionnaire, including the following information: (1) “Background and Demographics”: household income, hometown, residence during study and source(s) of any financial aid received; (2) “Living Expenses”: Living costs including food, transportation, rent, utility bills, and recreational expenses; (3) “Education related expenses”: Including textbooks, stationeries, uniforms, and student activities fees. A cost-median was used as a baseline representation for the actual cost of each item. The mean differences of all expenses between groups before estimation was assessed by using the analysis of variance (ANOVA) method. The statistically significant differences were identified at p < 0.001.

RESULTS: The estimated adjusted cost of becoming a dentist in Thailand is THB1,265,027 (36,143.63 USD) for students living at home and THB1,823,027 (52,086.49 USD) for those renting accommodation. Students who rented accommodation incurred significantly higher yearly living expenses than those who were living at home. (p < 0.001). The majority of participants (78.4%) were in households having a middle-to-high socioeconomic status. Ninety-five percentages of the participants’ received 100% financial support from their families with no additional source of income, which reflects no real diversity in the socioeconomic background of Dental Degree students.

CONCLUSION: The cost of a higher education Dental Degree in Thailand can be a significant barrier to entry and financial burden, especially for students from disadvantaged socioeconomic backgrounds. Government and Educational Policy makers need to pay more attention to this issue in order to provide equal opportunities for obtaining a University Dental Degree for all Thai students wishing to pursue this career path.

PMID:36765031 | DOI:10.1038/s41405-023-00131-1