Stochastic Navier-Stokes equations with fractional Brownian motions

The aim of this dissertation is to study stochastic Navier-Stokes equations with a fractional Brownian motion noise. The second chapter will introduce the background results on fractional Brownian motions and some of their properties. The third chapter will focus on the Stokes operator and the semigroup generated by this operator. The Navier-Stokes equations and the evolution equation setup will be described in the next chapter. The main goal is to prove the existence and uniqueness of solutions for the stochastic Navier-Stokes equations with a fractional Brownian motion noise under suitable conditions. The proof is given with full details for two separate cases based on the value of the Hurst parameter H: 1/2 \u3c 1 and 1/8 \u3c 1/2

Modular forms on noncongruence subgroups and Atkin-Swinnerton-Dyer relations

We give new examples of noncongruence subgroups T C SL2(Z) whose space of weight-3 cusp forms S3(Γ) admits a basis satisfying the Atkin-Swinnerton-Dyer congruence relations with respect to a weight-3 newform for a certain congruence subgroup. © A K Peters, Ltd

Spatiotemporal distribution of malaria and the association between its epidemic and climate factors in Hainan, China

<p>Abstract</p> <p>Background</p> <p>Hainan is one of the provinces most severely affected by malaria epidemics in China. The distribution pattern and major determinant climate factors of malaria in this region have remained obscure, making it difficult to target countermeasures for malaria surveillance and control. This study detected the spatiotemporal distribution of malaria and explored the association between malaria epidemics and climate factors in Hainan.</p> <p>Methods</p> <p>The cumulative and annual malaria incidences of each county were calculated and mapped from 1995 to 2008 to show the spatial distribution of malaria in Hainan. The annual and monthly cumulative malaria incidences of the province between 1995 and 2008 were calculated and plotted to observe the annual and seasonal fluctuation. The Cochran-Armitage trend test was employed to explore the temporal trends in the annual malaria incidences. Cross correlation and autocorrelation analyses were performed to detect the lagged effect of climate factors on malaria transmission and the auto correlation of malaria incidence. A multivariate time series analysis was conducted to construct a model of climate factors to explore the association between malaria epidemics and climate factors.</p> <p>Results</p> <p>The highest malaria incidences were mainly distributed in the central-south counties of the province. A fluctuating but distinctly declining temporal trend of annual malaria incidences was identified (Cochran-Armitage trend test <it>Z </it>= -25.14, <it>P </it>< 0.05). The peak incidence period was May to October when nearly 70% of annual malaria cases were reported. The mean temperature of the previous month, of the previous two months and the number of cases during the previous month were included in the model. The model effectively explained the association between malaria epidemics and climate factors (<it>F </it>= 85.06, <it>P </it>< 0.05, adjusted <it>R </it>²= 0.81). The autocorrelations of the fitting residuals were not significant (<it>P </it>> 0.05), indicating that the model extracted information sufficiently. There was no significant difference between the monthly predicted value and the actual value (<it>t </it>= -1.91, <it>P </it>= 0.08). The <it>R </it>²for predicting was 0.70, and the autocorrelations of the predictive residuals were not significant (<it>P </it>> 0.05), indicating that the model had a good predictive ability.</p> <p>Discussion</p> <p>Public health resource allocations should focus on the areas and months with the highest malaria risk in Hainan. Malaria epidemics can be accurately predicted by monitoring the fluctuations of the mean temperature of the previous month and of the previous two months in the area. Therefore, targeted countermeasures can be taken ahead of time, which will make malaria surveillance and control in Hainan more effective and simpler. This model was constructed using relatively long-term data and had a good fit and predictive validity, making the results more reliable than the previous report.</p> <p>Conclusions</p> <p>The spatiotemporal distribution of malaria in Hainan varied in different areas and during different years. The monthly trends in the malaria epidemics in Hainan could be predicted effectively by using the multivariate time series model. This model will make malaria surveillance simpler and the control of malaria more targeted in Hainan.</p

Multiple sclerosis and breast cancer risk: a meta-analysis of observational and Mendelian randomization studies

BackgroundSeveral observational studies have explored the relationships between multiple sclerosis (MS) and breast cancer; however, whether an association exists remains unknown.MethodsWe conducted a meta-analysis of observational studies and Mendelian randomization (MR) based on genetic variants to identify the relationship between MS and breast cancer. The observational studies were searched from PubMed, Embase, Web of Science, and Scopus to assess the relationship between MS and breast cancer from inception to 07 Nov 2022. Moreover, we explored the association between genetically pre-disposed MS and breast cancer risk based on an MR study. The summary analysis for MS from two separate databases [International Multiple Sclerosis Genetics Consortium (IMSGC), FinnGen] and the summary analysis for breast cancer from Breast Cancer Association Consortium.ResultsFifteen cohort studies involving 173,565 female MS patients were included in this meta-analysis. The correlation between MS and breast cancer was not statistically significant [relative ratio (RR) = 1.08, 95% confidence interval (CI) = 0.99–1.17]. In the MR analysis, we did not observe causal associations of genetically determined MS with breast cancer and its subtypes from both the IMSGC and FinnGen datasets.ConclusionThe meta-analysis of observational and MR based on genetic variants does not support the correlation between MS and breast cancer

Contralateral upper tract urothelial carcinoma after nephroureterectomy: the predictive role of DNA methylation

Abstract Background Aberrant methylation of genes is one of the most common epigenetic modifications involved in the development of urothelial carcinoma. However, it is unknown the predictive role of methylation to contralateral new upper tract urothelial carcinoma (UTUC) after radical nephroureterectomy (RNU). We retrospectively investigated the predictive role of DNA methylation and other clinicopathological factors in the contralateral upper tract urothelial carcinoma (UTUC) recurrence after radical nephroureterectomy (RNU) in a large single-center cohort of patients. Methods In a retrospective design, methylation of 10 genes was analyzed on tumor specimens belonging to 664 consecutive patients treated by RNU for primary UTUC. Median follow-up was 48 mo (range: 3–144 mo). Gene methylation was accessed by methylation-sensitive polymerase chain reaction, and we calculated the methylation index (MI), a reflection of the extent of methylation. The log-rank test and Cox regression were used to identify the predictor of contralateral UTUC recurrence. Results Thirty (4.5%) patients developed a subsequent contralateral UTUC after a median follow-up time of 27.5 (range: 2–139) months. Promoter methylation for at least one gene promoter locus was present in 88.9% of UTUC. Fewer methylation and lower MI (P = 0.001) were seen in the tumors with contralateral UTUC recurrence than the tumors without contralateral recurrence. High MI (P = 0.007) was significantly correlated with poor cancer-specific survival. Multivariate analysis indicated that unmethylated RASSF1A (P = 0.039), lack of bladder recurrence prior to contralateral UTUC (P = 0.009), history of renal transplantation (P < 0.001), and preoperative renal insufficiency (P = 0.002) are independent risk factors for contralateral UTUC recurrence after RNU. Conclusions Our data suggest a potential role of DNA methylation in predicting contralateral UTUC recurrence after RNU. Such information could help identify patients at high risk of new contralateral UTUC recurrence after RNU who need close surveillance during follow up.http://deepblue.lib.umich.edu/bitstream/2027.42/110306/1/13046_2015_Article_120.pd

Combining Spatial-Temporal and Phylogenetic Analysis Approaches for Improved Understanding on Global H5N1 Transmission

Background Since late 2003, the highly pathogenic influenza A H5N1 had initiated several outbreak waves that swept across the Eurasia and Africa continents. Getting prepared for reassortment or mutation of H5N1 viruses has become a global priority. Although the spreading mechanism of H5N1 has been studied from different perspectives, its main transmission agents and spread route problems remain unsolved. Methodology/Principal Findings Based on a compilation of the time and location of global H5N1 outbreaks from November 2003 to December 2006, we report an interdisciplinary effort that combines the geospatial informatics approach with a bioinformatics approach to form an improved understanding on the transmission mechanisms of H5N1 virus. Through a spherical coordinate based analysis, which is not conventionally done in geographical analyses, we reveal obvious spatial and temporal clusters of global H5N1 cases on different scales, which we consider to be associated with two different transmission modes of H5N1 viruses. Then through an interdisciplinary study of both geographic and phylogenetic analysis, we obtain a H5N1 spreading route map. Our results provide insight on competing hypotheses as to which avian hosts are responsible for the spread of H5N1. Conclusions/Significance We found that although South China and Southeast Asia may be the virus pool of avian flu, East Siberia may be the source of the H5N1 epidemic. The concentration of migratory birds from different places increases the possibility of gene mutation. Special attention should be paid to East Siberia, Middle Siberia and South China for improved surveillance of H5N1 viruses and monitoring of migratory birds

Spatial analysis of malaria in Anhui province, China

<p>Abstract</p> <p>Background</p> <p>Malaria has re-emerged in Anhui Province, China, and this province was the most seriously affected by malaria during 2005–2006. It is necessary to understand the spatial distribution of malaria cases and to identify highly endemic areas for future public health planning and resource allocation in Anhui Province.</p> <p>Methods</p> <p>The annual average incidence at the county level was calculated using malaria cases reported between 2000 and 2006 in Anhui Province. GIS-based spatial analyses were conducted to detect spatial distribution and clustering of malaria incidence at the county level.</p> <p>Results</p> <p>The spatial distribution of malaria cases in Anhui Province from 2000 to 2006 was mapped at the county level to show crude incidence, excess hazard and spatial smoothed incidence. Spatial cluster analysis suggested 10 and 24 counties were at increased risk for malaria (<it>P </it>< 0.001) with the maximum spatial cluster sizes at < 50% and < 25% of the total population, respectively.</p> <p>Conclusion</p> <p>The application of GIS, together with spatial statistical techniques, provide a means to quantify explicit malaria risks and to further identify environmental factors responsible for the re-emerged malaria risks. Future public health planning and resource allocation in Anhui Province should be focused on the maximum spatial cluster region.</p