PLoS One. 2021 Aug 9;16(8):e0256189. doi: 10.1371/journal.pone.0256189. eCollection 2021.
ABSTRACT
[This corrects the article DOI: 10.1371/journal.pone.0251107.].
PMID:34370793 | DOI:10.1371/journal.pone.0256189
PLoS One. 2021 Aug 9;16(8):e0255857. doi: 10.1371/journal.pone.0255857. eCollection 2021.
ABSTRACT
In the current study, based on the national fire statistics from 2003 to 2017, we analyzed the 24-hour occurrence regularity of fire in China to study the occurrence regularity and influencing factors of fire and provide a reference for scientific and effective fire prevention. The results show that the frequency of fire is low from 0 to 6 at night, accounting for about 13.48%, but the death toll due to fire is relatively high, accounting for about 39.90%. Considering the strong seasonal characteristics of the time series of monthly fire frequency, the SARIMA model predicts the fire frequency. According to the characteristics of time series data and prediction results, an optimized Seasonal Autoregressive Integrated Moving Average Model (SARIMA) model based on Quantile outlier detection method and similar mean interpolation method is proposed, and finally, the optimal model is constructed as SARIMA (1,1,1) (1,1,1) 12 for prediction. The results show that: according to the optimized SARIMA model to predict the number of fires in 2018 and 2019, the root mean square error of the fitting results is 2826.93, which is less than that of the SARIMA model, indicating that the improved SARIMA model has a better fitting effect. The accuracy of the results is increased by 11.5%. These findings verified that the optimized SARIMA model is an effective improvement for the series with quantile outliers, and it is more suitable for the data prediction with seasonal characteristics. The research results can better mine the law of fire aggregation and provide theoretical support for fire prevention and control work of the fire department.
PMID:34370785 | DOI:10.1371/journal.pone.0255857
PLoS One. 2021 Aug 9;16(8):e0255718. doi: 10.1371/journal.pone.0255718. eCollection 2021.
ABSTRACT
Regardless of all efforts on community discovery algorithms, it is still an open and challenging subject in network science. Recognizing communities in a multilayer network, where there are several layers (types) of connections, is even more complicated. Here, we concentrated on a specific type of communities called seed-centric local communities in the multilayer environment and developed a novel method based on the information cascade concept, called PLCDM. Our simulations on three datasets (real and artificial) signify that the suggested method outstrips two known earlier seed-centric local methods. Additionally, we compared it with other global multilayer and single-layer methods. Eventually, we applied our method on a biological two-layer network of Colon Adenocarcinoma (COAD), reconstructed from transcriptomic and post-transcriptomic datasets, and assessed the output modules. The functional enrichment consequences infer that the modules of interest hold biomolecules involved in the pathways associated with the carcinogenesis.
PMID:34370784 | DOI:10.1371/journal.pone.0255718
PLoS One. 2021 Aug 9;16(8):e0255293. doi: 10.1371/journal.pone.0255293. eCollection 2021.
ABSTRACT
Uveal melanoma (UVM), the most common primary intraocular malignancy, has a high mortality because of a high propensity to metastasize. Our study analyzed prognostic value and immune-related characteristics of CARD11 in UVM, hoping to provide a potential management and research direction. The RNA-sequence data of 80 UVM patients were downloaded from The Cancer Genome Atlas database and divided them into high- and low-expression groups. We analyzed the differentially expressed genes, enrichment analyses and the infiltration of immune cells using the R package and Gene-Set Enrichment Analysis. A clinical prediction nomogram and protein-protein interaction network were constructed and the first 8 genes were considered as the hub-genes. Finally, we constructed a competing endogenous RNA (ceRNA) network by Cytoscape and analyzed the statistical data via the R software. Here we found that CARD11 expression had notable correlation with UVM clinicopathological features, which was also an independent predictor for overall survival (OS). Intriguingly, CARD11 had a positively correlation to autophagy, cellular senescence and apoptosis. Infiltration of monocytes was significantly higher in low CARD11 expression group, and infiltration of T cells regulatory was lower in the same group. Functional enrichment analyses revealed that CARD11 was positively related to T cell activation pathways and cell adhesion molecules. The expressions of hub-genes were all increased in the high CARD11 expression group and the ceRNA network showed the interaction among mRNA, miRNA and lncRNA. These findings show that high CARD11 expression in UVM is associated with poor OS, indicating that CARD11 may serve as a potential biomarker for the diagnosis and prognosis of the UVM.
PMID:34370778 | DOI:10.1371/journal.pone.0255293
PLoS One. 2021 Aug 9;16(8):e0255675. doi: 10.1371/journal.pone.0255675. eCollection 2021.
ABSTRACT
Dealing with a system of first-order reactions is a recurrent issue in chemometrics, especially in the analysis of data obtained by spectroscopic methods applied on complex biological systems. We argue that global multiexponential fitting, the still common way to solve such problems, has serious weaknesses compared to contemporary methods of sparse modeling. Combining the advantages of group lasso and elastic net-the statistical methods proven to be very powerful in other areas-we created an optimization problem tunable from very sparse to very dense distribution over a large pre-defined grid of time constants, fitting both simulated and experimental multiwavelength spectroscopic data with high computational efficiency. We found that the optimal values of the tuning hyperparameters can be selected by a machine-learning algorithm based on a Bayesian optimization procedure, utilizing widely used or novel versions of cross-validation. The derived algorithm accurately recovered the true sparse kinetic parameters of an extremely complex simulated model of the bacteriorhodopsin photocycle, as well as the wide peak of hypothetical distributed kinetics in the presence of different noise levels. It also performed well in the analysis of the ultrafast experimental fluorescence kinetics data detected on the coenzyme FAD in a very wide logarithmic time window. We conclude that the primary application of the presented algorithms-implemented in available software-covers a wide area of studies on light-induced physical, chemical, and biological processes carried out with different spectroscopic methods. The demand for this kind of analysis is expected to soar due to the emerging ultrafast multidimensional infrared and electronic spectroscopic techniques that provide very large and complex datasets. In addition, simulations based on our methods could help in designing the technical parameters of future experiments for the verification of particular hypothetical models.
PMID:34370771 | DOI:10.1371/journal.pone.0255675
PLoS One. 2021 Aug 9;16(8):e0255912. doi: 10.1371/journal.pone.0255912. eCollection 2021.
ABSTRACT
BACKGROUND: In Ethiopia, nearly one-third of people living with human immunodeficiency viruses do not adhere to antiretroviral therapy. Moreover, information regarding non-adherence and its associated factors among adults on first-line antiretroviral therapy in Northeast Ethiopia is limited. Therefore, this study aimed to assess the level of non-adherence and its associated factors among adults on first-line antiretroviral therapy in North Shewa Zone, Amhara Regional State, Ethiopia.
METHODS: A facility-based cross-sectional study was conducted on 326 participants selected by systematic random sampling technique from the five randomly selected public health facilities. Data were collected using the questionnaire adapted from the studies conducted previously and the collected data were entered into Epi data version 3.1 and exported to Stata version 14 for further analysis. Multivariable logistic regression analysis was done and an adjusted odds ratio with its corresponding 95% confidence interval was used to declare a statistical significance.
RESULTS: The overall prevalence of non-adherence was 17.4% [95% CI: (12.8%, 21.2%)]. Patients with no formal education [AOR (95% CI) = 5.57 (1.97, 15.88)], those who did not use memory aids to take their medications [AOR (95% CI) = 3.01 (1.27, 7.11)], travel more than 10 kilometers to visit the nearby antiretroviral therapy clinics [AOR (95% CI) = 2.42 (1.22, 25.86)], those who used substance [AOR (95% CI) = 3.57 (1.86, 28.69)], and patients whose medication time interfered with their daily routine activities [AOR (95% CI) = 15.46 (4.41, 54.28) had higher odds of having non-adherence to first-line antiretroviral therapy compared to their counter groups.
CONCLUSION: The level of non-adherence to first-line antiretroviral therapy was 17.4%, higher compared to WHO’s recommendation. Hence, patients counseling focused on avoiding substance use, use memory aids, and adjusting working time with medication schedule are very crucial. Furthermore, the ministry of health and the regional health bureau with other stakeholders should expand antiretroviral therapy service delivery at health facilities that are close to the community to address distance barriers.
PMID:34370762 | DOI:10.1371/journal.pone.0255912
PLoS One. 2021 Aug 9;16(8):e0255279. doi: 10.1371/journal.pone.0255279. eCollection 2021.
ABSTRACT
BACKGROUND: The purpose of this study is to investigate and analyze the prevalence and influencing factors of stroke in hypertensive patients aged 60 and above in Jiading District, Shanghai.
METHODS: The population-based study included 18,724 screened people with hypertension (age ≥ 60 years, 48.7% women). From 2016 to 2019, data on demographics, potential influencing factors and health status were collected through face-to-face interviews, physical examinations, and laboratory tests. Logistic multivariate logistic regression model was used to analyze the influencing factors associated with stroke.
RESULTS: Among the object of study from 2016 to 2019, 2,025 patients were screened for stroke, with the overall prevalence rate of 10.82% (10.41%-11.23%). Multivariate adjusted model analysis showed that dyslipidemia (OR:1.31,95%CI:1.19-1.45), lack of exercise (OR:1.91,95%CI:1.32-2.76), atrial fibrillation [OR:1.49,95%CI:1.35-1.65), family history of stroke (OR:2.18,95%CI:1.6-2.88) were the significant independent influencing factors of stroke in hypertensive patients over 60 years old. When these four factors were combined, compared with participants without any of these factors, the multi-adjusted odds ratios (95% confidence interval) of risk of stroke for persons concurrently having one, two and three or more of these factors were 1.89 (1.67-2.13), 2.15 (1.86-2.47) and 6.84 (4.90-9.55), respectively (linear trend P < 0.001); after multivariate adjustment, the family history of stroke had additive interaction with lack of exercise [RERI = 1.08(0.22-1.94), AP = 0.19(0.04-0.35), S = 1.31(1.02-1.69)], dyslipidemia [RERI = 0.87(0.41-1.33), AP = 0.23(0.08-0.38), S = 1.46(1.04-2.05)].
CONCLUSION: The prevalence of stroke was high in hypertensive patients aged 60 and above in Jiading District, Shanghai. Dyslipidemia, lack of exercise, atrial fibrillation and family history of stroke were significantly associated with stroke in hypertensive population. Stroke risk can be increased especially when multiple factors coexisting, and family history of stroke combined with a lack of exercise or dyslipidemia.
PMID:34370757 | DOI:10.1371/journal.pone.0255279
J Long Term Eff Med Implants. 2021;31(3):83-89. doi: 10.1615/JLongTermEffMedImplants.2021038612.
ABSTRACT
Our goal was to evaluate the association between gingival biotype and flap design consideration at the time of stage two uncovery. A retrospective study was done in which 528 implants were placed from June 1, 2019, to March 1, 2020, were included. Data was reviewed from patient records, and the data of 86,000 patients that were documented in a private institution between June 2019 and March 2020 was analyzed. Statistical analysis was performed to assess the association between gingival biotype and flap design consideration at the time of stage two uncovery. We found that gingival biotype had no significant difference when compared between males and females and among different age groups. Flap design consideration had no significant difference when compared between males and females, but the difference was statistically significant when different age groups were compared. There was a statistically significant association between gingival biotype and flap design consideration at the time of stage two uncovery (p < 0.05). We conclude that there is significant association between gingival biotype and flap design consideration at the time of stage two uncovery. Therefore, it should be one of the factors considered during planning of implant placement in a particular case for successful implant treatment.
PMID:34369727 | DOI:10.1615/JLongTermEffMedImplants.2021038612
J Long Term Eff Med Implants. 2021;31(3):51-56. doi: 10.1615/JLongTermEffMedImplants.2021038608.
ABSTRACT
Implant systems today have come a long way to provide comfort and long-term success rate in patients requiring implant supported prosthesis as part of their oral rehabilitation. It is currently overtaking the other prosthetic treatment especially in the case of replacing anterior teeth. The aim of this study was to evaluate the association of age, gender, bone density and implant brands with respect to implants placed in the maxillary anterior region in a private hospital setup. It is a retrospective university setting study performed by evaluating the case histories of patients placed with implants in the anterior region. The data was extracted and subjected to statistical analyses using SPSS software. In this study, D2 bone was most commonly seen in the anterior region followed by D3 and D1. D1 and D3 bone were prevalent in patients in the age group of 41 to 60 years and D2 bone was prevalent in the group of 26-40 years. Males showed greater bone density than females. Implant brand Straumann Roxolid SLActive was mostly used in the anterior region and most of the implants are placed equicrestal in position. As a practitioner, one should have clear knowledge on implant brand, bone densities, crestal relation and age association in order to exert a successful treatment response in the future.
PMID:34369722 | DOI:10.1615/JLongTermEffMedImplants.2021038608
J Long Term Eff Med Implants. 2021;31(3):27-32. doi: 10.1615/JLongTermEffMedImplants.2021036412.
ABSTRACT
AIM: The aim of the current study is to assess and evaluate the effectiveness of concentrated growth factors on wound healing after implant placement procedures.
METHODOLOGY: Twenty-four patients who underwent implant placement were included in the study and were divided into two groups (group 1 = non-CGF group; group 2 = CGF group). Conventional implant placement was done in both the groups followed by placement of CGF membrane and closure using 3-0 silk in the CGF group and only closure using 3-0 silk sutures in the control group. The patients were asked to report on the 3rd and 7th day respectively and the wound healing was assessed using an early wound healing index given by Lorenzo Marini.
STATISTICAL ANALYSIS: Shapiro-Wilk test was used to test the normality of the test, which was found to deviate from normal distribution and hence Mann-Whitney U test was employed to evaluate the statistical significance of the two independent samples.
RESULTS: The mean ± SD was found to be 6.17 ± 2.04 for the control (group 1) and 5.67 ± 0.51 for CGF group (group 2) on the 3rd day. The mean and SD of control group and test group on the 7th day was 7 ± 1.55 and 9.33 ± 1.63, respectively. The difference between the groups on the 7th day was found to be statistically significant (P value < 0.05).
CONCLUSION: Concentrated growth factor application had positive effects on surgical wound healing after implant placement.
PMID:34369719 | DOI:10.1615/JLongTermEffMedImplants.2021036412