Biology subjects

Clifton, D.

Publications and source records attributed to Clifton, D..

5 recordsLinked to original sources

bioRxiv2024

AI-assisted In-silico Trial for the Optimization of Osmotherapy following Ischaemic Stroke

Over the past few decades, osmotherapy has commonly been employed to reduce intracranial pressure in post-stroke oedema. However, evaluating the effectiveness of osmotherapy has been challenging due to the difficulties in clinical intracranial pressure measurement. As a result, there are no established guidelines regarding the selection of administration protocol parameters. Considering that the infusion of osmotic agents can also give rise to various side effects, the effectiveness of osmotherapy has remained a subject of debate. In previous studies, we proposed the first mathematical model for the investigation of osmotherapy and validated the model with clinical intracranial pressure data. The physiological parameters vary among patients and such variations can result in the failure of osmotherapy. Here, we propose an AI-assisted in-silico trial for further investigation of the optimisation of administration protocols. The proposed deep neural network predicts intracranial pressure evolution over osmotherapy episodes. The effects of the parameters and the choice of dose of osmotic agents are investigated using the model. In addition, clinical stratifications of patients are related to a brain model for the first time for the optimisation of treatment of different patient groups. This provides an alternative approach to tackle clinical challenges with in-silico trials supported by both mathematical/physical laws and patient-specific biomedical information.

bioengineering↗

bioRxiv2023

Early-adulthood intermittent fasting and reduced insulin/IGF-1 signalling additively increase lifespan and slow down reproductive ageing

The developmental theory of ageing proposes that age-specific decline in the force of natural selection results in suboptimal levels of gene expression in adulthood, leading to functional senescence. This theory explicitly predicts that optimising gene expression in adulthood can ameliorate functional senescence and improve fitness. Reduced insulin/IGF-1 signalling (rIIS) extends the reproductive lifespan of Caenorhabditis elegans at the cost of reduced reproduction. Here, we show that adulthood-only rIIS improves late-life reproduction without any detrimental effects on other life-history traits in both benign and stressful conditions. Remarkably, we show that rIIS additively extends late-life reproduction and lifespan when animals are exposed to a fluctuating food environment - intermittent fasting (IF) - resulting in reduced food intake in early adulthood. Full factorial genome-wide RNA-Seq across the life course demonstrated that IF and rIIS modulate the age-specific expression of pro-longevity genes. IF, rIIS and combined IF + rIIS treatment downregulated genes involved in peptide metabolism in early life and differentially regulated immunity genes in later life. Importantly, combined IF + rIIS treatment uniquely regulated a large cluster of genes in mid-life that are associated with immune response. These results suggest that optimising gene expression in adulthood can decelerate reproductive ageing and increase fitness.

molecular biology↗

bioRxiv2022

Patient Clustering and Classification for Vital Organ Failure Using ICD Code with Graph Attention

ObjectiveHeart failure, respiratory failure and kidney failure are three severe organ failures (OF) that have high mortalities and are most prevalent in intensive care units. The objective of this work is to offer insights on OF clustering from the aspects of graph neural network and diagnosis history. MethodsThis paper proposes a neural network-based pipeline to cluster three types of organ failure patients by incorporating embedding pre-train using an ontology graph of International Classification of Diseases (ICD) codes. We employ an autoencoder-based deep clustering architecture jointly trained with a K-means loss, and a non-linear dimension reduction is performed to obtain patient clusters on the MIMIC-III dataset. ResultsThe clustering pipeline shows superior performance on a public-domain image dataset. For MIMIC-III, the model gives two distinct clusters that are related to the severity of the diseases. The learnt ICD embeddings present strong power in identifying the OF type in supervised learning. ConclusionOur proposed pipeline gives stable clusters, however, they do not correspond to the type of OF which indicates these OF share significant hidden characteristics in diagnosis. These clusters can be used to signal possible complications and severity of illness. SignificanceWe are the first to apply an unsupervised approach to offer insights from a biomedical engineering perspective on these three types of organ failure, and publish the pre-trained embeddings for future transfer learning.

bioengineering↗

bioRxiv2021

BashTheBug: a crowd of volunteers reproducibly and accurately measure the minimum inhibitory concentrations of 13 antitubercular drugs from photographs of 96-well broth microdilution plates.

Tuberculosis is a respiratory disease that is treatable with antibiotics. An increasing prevalence of resistance means that to ensure a good treatment outcome it is desirable to test the susceptibility of each infection to different antibiotics. Conventionally this is done by culturing a clinical sample and then exposing aliquots to a panel of antibiotics, thereby determining the minimum inhibitory concentration (MIC) of each drug. Using 96-well broth micro dilution plates with each well containing a lyophilised pre-determined amount of an antibiotic is a convenient and cost-effective way to measure the MICs of several drugs at once for a clinical sample. Although accurate, this is an expensive and slow process that requires highly-skilled and experienced laboratory scientists. Here we show that, through the BashTheBug project hosted on the Zooniverse citizen science platform, a crowd of volunteers can reproducibly and accurately determine the MICs for 13 drugs and that simply taking the median or mode of 11-17 independent classifications is sufficient. There is therefore a potential role for crowds to support (but not supplant) the role of experts in antibiotic susceptibility testing.

microbiology↗

bioRxiv2019

Heart rate variability as an indicator of autonomic nervous system disturbance in tetanus

Autonomic nervous system dysfunction (ANSD) is a significant cause of mortality in tetanus. Currently diagnosis relies on non-specific clinical signs. Heart rate variability (HRV) may indicate underlying autonomic nervous system activity and represents a potentially valuable non-invasive tool for ANSD diagnosis in tetanus. HRV was measured from 3 5-minute ECG recordings during a 24-hour period in a cohort patients with severe tetanus, all receiving mechanical ventilation. HRV measurements from all subjects - 5 with ANSD (Ablett Grade 4) and 4 patients without ANSD (Ablett Grade 3) - showed HRV was lower than reported ranges for healthy individuals. Comparing different severities of tetanus, raw data for both time and frequency measurements of HRV were reduced in those with ANSD compared to those without. Differences were statistically significant in all except root mean square standard deviation RMSSD (p=0.07) indicating HRV may be a valuable tool in ANSD diagnosis.

pathology↗