The twenty-first century is bearing witness to a drastic change in population demographics and diseases of old age, such as dementia, are placing an unprecedented burden on the global healthcare system. Normal pressure hydrocephalus may be the only curable form of dementia, yet its pathophysiology is paradoxical and a consistent treatment currently remains elusive. A novel application of multiple-network poroelastic theory (MPET) is proposed to investigate water transport in the cerebral environment. Specifically, MPET is modified to allow a detailed investigation of spatio-temporal transport of fluid between the cerebral blood, cerebrospinal fluid (CSF) and brain parenchyma across scales. This framework thus allows an exploration of hypotheses defining the initiation and progression of both acute and chronic hydrocephalus. Results show that a breakdown in the transport mechanisms between the arterial vascular network and interstitial space within the parenchyma may be a cause of accumulation of CSF in the ventricles. Specifically, there must be an increase in the compliance of the arteriole/capillary network, which may combine with a breakdown in the blood–CSF barrier to allow an increased flow from the arteriole/capillary blood to the CSF. The results of this study should prove useful to guide experimental exploration in areas that warrant further investigation and validation.

Reproducible research is the bedrock of experimental science. To enable the deployment of large-scale proteomics, we assess the reproducibility of mass spectrometry (MS) over time and across instruments and develop computational methods for improving quantitative accuracy. We perform 1560 data independent acquisition (DIA)-MS runs of eight samples containing known proportions of ovarian and prostate cancer tissue and yeast, or control HEK293T cells. Replicates are run on six mass spectrometers operating continuously with varying maintenance schedules over four months, interspersed with~5000 other runs. We utilise negative controls and replicates to remove unwanted variation and enhance biological signal, outperforming existing methods. We also design a method for reducing missing values. Integrating these computational modules into a pipeline (ProNorM), we mitigate variation among instruments over time and accurately predict tissue proportions. We demonstrate how to improve the quantitative analysis of large-scale DIA-MS data, providing a pathway toward clinical proteomics.

There is emerging evidence suggesting that Alzheimer's disease is a vascular disorder, caused by impaired cerebral perfusion, which may be promoted by cardiovascular risk factors that are strongly influenced by lifestyle. In order to develop an understanding of the exact nature of such a hypothesis, a biomechanical understanding of the influence of lifestyle factors is pursued. An extended poroelastic model of perfused parenchymal tissue coupled with separate workflows concerning subject-specific meshes, permeability tensor maps and cerebral blood flow variability is used. The subject-specific datasets used in the modelling of this paper were collected as part of prospective data collection. Two cases were simulated involving male, non-smokers (control and mild cognitive impairment (MCI) case) during two states of activity (high and low). Results showed a marginally reduced clearance of cerebrospinal fluid (CSF)/interstitial fluid (ISF), elevated parenchymal tissue displacement and CSF/ISF accumulation and drainage in the MCI case. The peak perfusion remained at 8 mm s −1 between the two cases.