Search

Many e-Health strategies rely on the secure integration of datasets that have previously resided in isolated locations, but can now in principle be accessed over the Internet. Of paramount importance in the health domain is the need for the security and privacy of data that is transmitted across these networks. One such collaboration, which spans several specialist centres across France, Germany, Italy and the UK, is ENSAT – the European Network for the Study of Adrenal Tumors. The rarity of the tumors under study means the value of accessing, aggregating and comparing data from many centres is great indeed. However this is especially challenging given that ENSAT require clinical and genomic data to be seamlessly linked, but in such a way that the information governance, ethics and privacy concerns of the patients and associated stakeholders involved are visibly satisfied. Key to this is the clear separation of clinical and genomic data sets and support for rigorous patient-identity protecting access control. This is especially challenging when such data sets exist across different organisational boundaries. In this paper we describe a prototype solution offering a security-oriented tailored portal supported by a layered encryption-driven linkage technology (VANGUARD) that offers precisely such patient-privacy protecting capabilities. We describe the architecture, implementation and use to date of this facility to support the ENSAT adrenal cancer research network. [ABSTRACT FROM AUTHOR]

The simulation of biochemical networks provides insight and understanding about the underlying biochemical processes and pathways used by cells and organisms. BioNessie is a biochemical network simulator which has been developed at the University of Glasgow. This paper describes the simulator and focuses in particular on how it has been extended to benefit from a wide variety of high performance compute resources across the UK through Grid technologies to support larger scale simulations. [ABSTRACT FROM AUTHOR]

Microarray experiments are one of the key ways in which gene activity can be identified and measured thereby shedding light and understanding for example on biological processes. The BBSRC funded Grid enabled Microarray Expression Profile Search (GEMEPS) project has developed an infrastructure which allows post-genomic life science researchers to ask and answer the following questions: who has undertaken microarray experiments that are in some way similar or relevant to mine; and how similar were these relevant experiments? Given that microarray experiments are expensive to undertake and may possess crucial information for future exploitation (both academically and commercially), scientists are wary of allowing unrestricted access to their data by the wider community until fully exploited locally. A key requirement is thus to have fine grained security that is easy to establish and simple (or ideally transparent) to use across inter-institutional virtual organisations. In this paper we present an enhanced security-oriented data Grid infrastructure that supports the definition of these kinds of queries and the analysis and comparison of microarray experiment results. [ABSTRACT FROM AUTHOR]

Objective: To investigate the clinical value of miR-216a-5p and miR-34a in early screening for cervical cancer (CC)., Methods: 99 patients were selected and classified into a cervical cancer group, a precancerous lesion group, and a chronic cervicitis group, with 33 patients in each group. The miR-216a-5p and miR-34a levels in the morning urine samples of patients in the three groups were detected. Additionally, the urine samples of CC patients were analyzed and their cervical tissues examined to confirm the presence of Human Papilloma Virus (HPV) infection. The differences in the levels of miR-216a-5p and miR-34a in CC patients exhibiting varying clinical features and the clinical values of the two biomarkers in identifying CC were analyzed. Patients in the cervical cancer group were divided into a recurrence group and a non-recurrence group, after which their levels of miR-216a-5p and miR-34a were analyzed. These patients were subsequently divided into a high-expression group and a low-expression group with the aforementioned biomarker levels in the non-recurrence group as cutoff values. The progression-free survival was compared between the low- and high-expression groups., Results: Sensitivity and specificity of the urine sample test for HPV infection were 85.19% and 93.33%, respectively. Compared to chronic cervicitis group and precancerous lesion groups, or the non-recurrence group, the levels of miR-216a-5p and miR-34a in both the cervical cancer group and recurrence group were significantly lower (P < 0.05). CC patients with moderately to poorly differentiated tumor cells, an infiltration depth of the muscle layer > 1/2, lymph node metastasis, parametrial infiltration, or vascular invasion had significantly lower levels of miR-216a-5p and miR-34a than those without these risk factors (P < 0.05). The AUC for the application of the two biomarkers in diagnosing CC individually or in combination, or in forecasting recurrence, was greater than 0.8. Additionally, the cumulative progression-free survival was shorter in the low-expression group compared to the high-expression group., Conclusion: Use of morning urine samples for testing HPV infection shows high sensitivity and specificity. Moreover, the miR-216a-5p and miR-34a levels were closely associated with the progression and recurrence of CC., Competing Interests: None., (AJTR Copyright © 2025.)

Many e-Health strategies rely on the secure integration of datasets that have previously resided in isolated locations, but can now in principle be accessed over the Internet. Of paramount importance in the health domain is the need for the security and privacy of data that is transmitted across these networks. One such collaboration, which spans several specialist centres across France, Germany, Italy and the UK, is ENSAT - the European Network for the Study of Adrenal Tumors. The rarity of the tumors under study means the value of accessing, aggregating and comparing data from many centres is great indeed. However this is especially challenging given that ENSAT require clinical and genomic data to be seamlessly linked, but in such a way that the information governance, ethics and privacy concerns of the patients and associated stakeholders involved are visibly satisfied. Key to this is the clear separation of clinical and genomic data sets and support for rigorous patient-identity protecting access control. This is especially challenging when such data sets exist across different organisational boundaries. In this paper we describe a prototype solution offering a security-oriented tailored portal supported by a layered encryption-driven linkage technology (VANGUARD) that offers precisely such patient-privacy protecting capabilities. We describe the architecture, implementation and use to date of this facility to support the ENSAT adrenal cancer research network.

The simulation of biochemical networks provides insight and understanding about the underlying biochemical processes and pathways used by cells and organisms. BioNessie is a biochemical network simulator which has been developed at the University of Glasgow. This paper describes the simulator and focuses in particular on how it has been extended to benefit from a wide variety of high performance compute resources across the UK through Grid technologies to support larger scale simulations.

Microarray experiments are one of the key ways in which gene activity can be identified and measured thereby shedding light and understanding for example on biological processes. The BBSRC funded Grid enabled Microarray Expression Profile Search (GEMEPS) project has developed an infrastructure which allows post-genomic life science researchers to ask and answer the following questions: who has undertaken microarray experiments that are in some way similar or relevant to mine; and how similar were these relevant experiments? Given that microarray experiments are expensive to undertake and may possess crucial information for future exploitation (both academically and commercially), scientists are wary of allowing unrestricted access to their data by the wider community until fully exploited locally. A key requirement is thus to have fine grained security that is easy to establish and simple (or ideally transparent) to use across inter-institutional virtual organisations. In this paper we present an enhanced security-oriented data Grid infrastructure that supports the definition of these kinds of queries and the analysis and comparison of microarray experiment results.