Advancing treatment of retinal disease through in silico trials

Abstract Treating retinal diseases to prevent sight loss is an increasingly important challenge. Thanks to the configuration of the eye, the retina can be examined relatively easily in situ. Owing to recent technological development in scanning devices, much progress has been made in understanding the structure of the retina and characterising retinal biomarkers. However, treatment options remain limited and are often of low efficiency and efficacy.&amp;#xD;&amp;#xD;In recent years, the concept of in silico clinical trials has been adopted by many pharmaceutical companies to optimise and accelerate the development of therapeutics. In silico clinical trials rely on the use of mathematical models based on the physical and biochemical mechanisms underpinning a biological system. With appropriate simplifications and assumptions, one can generate computer simulations of various treatment regimens, new therapeutic molecules, delivery strategies and so forth, rapidly and at a fraction of the cost required for the equivalent experiments. Such simulations have the potential not only to hasten the development of therapies and strategies but also to&amp;#xD;optimise the use of existing therapeutics.&amp;#xD;&amp;#xD;In this paper, we review the state-of-the-art in in silico models of the retina for mathematicians, biomedical scientists and clinicians, highlighting the challenges to developing in silico clinical trials. Throughout this paper, we highlight key findings from in silico models about the physiology of the retina in health and disease. We describe the main building blocks of in silico clinical trials and identify challenges to developing in silico clinical trials of retinal diseases.</jats:p

Advancing treatment of retinal disease through in silico trials

Treating retinal diseases to prevent sight loss is an increasingly important challenge. Thanks to the configuration of the eye, the retina can be examined relatively easily in situ. Owing to recent technological development in scanning devices, much progress has been made in understanding the structure of the retina and characterising retinal biomarkers. However, treatment options remain limited and are often of low efficiency and efficacy. In recent years, the concept of in silico clinical trials (ISCTs) has been adopted by many pharmaceutical companies to optimise and accelerate the development of therapeutics. ISCTs rely on the use of mathematical models based on the physical and biochemical mechanisms underpinning a biological system. With appropriate simplifications and assumptions, one can generate computer simulations of various treatment regimens, new therapeutic molecules, delivery strategies and so forth, rapidly and at a fraction of the cost required for the equivalent experiments. Such simulations have the potential not only to hasten the development of therapies and strategies but also to optimise the use of existing therapeutics. In this paper, we review the state-of-the-art in in silico models of the retina for mathematicians, biomedical scientists and clinicians, highlighting the challenges to developing ISCTs. Throughout this paper, we highlight key findings from in silico models about the physiology of the retina in health and disease. We describe the main building blocks of ISCTs and identify challenges to developing ISCTs of retinal diseases

Quantifying the contribution of intracranial pressure and arterial blood pressure to spontaneous tympanic membrane displacement

Objective: Although previous studies have shown associations between patient symptoms/outcomes and the spontaneous tympanic membrane displacement (spTMD) pulse amplitude, the contribution of the underlying intracranial pressure (ICP) signal to the spTMD pulse remains largely unknown. We have assessed the relative contributions of ICP and arterial blood pressure (ABP) on spTMD at different frequencies in order to determine whether spTMD contains information about the ICP above and beyond that contained in the ABP. Approach: Eleven patients, who all had invasive ICP and ABP measurements in situ, were recruited from our intensive care unit. Their spTMD was recorded and the power spectral densities of the three signals, as well as coherences between the signals, were calculated in the range 0.1–5 Hz. Simple and multiple coherences, coupled with statistical tests using surrogate data, were carried out to quantify the relative contributions of ABP and ICP to spTMD. Main results: Most power of the signals was found to predominate at respiration rate, heart rate, and their harmonics, with little outside of these frequencies. Analysis of the simple coherences found a slight preference for ICP transmission, beyond that from ABP, to the spTMD at lower frequencies (7/11 patients at respiration, 7/10 patients at respiration 1st harmonic) which is reversed at the higher frequencies (2/11 patients at heart rate and its 1st harmonic). Both ICP and ABP were found to independently contribute to the spTMD. The multiple coherence reinforced that ICP is preferentially being transmitted at respiration and respiration 1st harmonic. Significance: Both ABP and ICP contribute independently to the spTMD signal, with most power occurring at clear physiological frequencies—respiration and harmonics and heart rate and harmonics. There is information shared between the ICP and spTMD that is not present in ABP. This analysis has indicated that lower frequencies appear to favour ICP as the driver for spTMD

Pulsatile tympanic membrane displacement is associated with cognitive score in healthy subjects

To test the hypothesis that pulsing of intracranial pressure has an association with cognition, we measured cognitive score and pulsing of the tympanic membrane in 290 healthy subjects. This hypothesis was formed on the assumptions that large intracranial pressure pulses impair cognitive performance and tympanic membrane pulses reflect intracranial pressure pulses. 290 healthy subjects, aged 20–80 years, completed the Montreal Cognitive Assessment Test. Spontaneous tympanic membrane displacement during a heart cycle was measured from both ears in the sitting and supine position. We applied multiple linear regression, correcting for age, heart rate, and height, to test for an association between cognitive score and spontaneous tympanic membrane displacement. Significance was set at P < 0.0125 (Bonferroni correction.) A significant association was seen in the left supine position (p = 0.0076.) The association was not significant in the right ear supine (p = 0.28) or in either ear while sitting. Sub-domains of the cognitive assessment revealed that executive function, language and memory have been primarily responsible for this association. In conclusion, we have found that spontaneous pulses of the tympanic membrane are associated with cognitive performance and believe this reflects an association between cognitive performance and intracranial pressure pulses

Systematic Review and Meta-Analysis of Prehospital Machine Learning Scores as Screening Tools for Early Detection of Large Vessel Occlusion in Patients With Suspected Stroke.

BackgroundEnhanced detection of large vessel occlusion (LVO) through machine learning (ML) for acute ischemic stroke appears promising. This systematic review explored the capabilities of ML models compared with prehospital stroke scales for LVO prediction.Methods and resultsSix bibliographic databases were searched from inception until October 10, 2023. Meta-analyses pooled the model performance using area under the curve (AUC), sensitivity, specificity, and summary receiver operating characteristic curve. Of 1544 studies screened, 8 retrospective studies were eligible, including 32 prehospital stroke scales and 21 ML models. Of the 9 prehospital scales meta-analyzed, the Rapid Arterial Occlusion Evaluation had the highest pooled AUC (0.82 [95% CI, 0.79-0.84]). Support Vector Machine achieved the highest AUC of 9 ML models included (pooled AUC, 0.89 [95% CI, 0.88-0.89]). Six prehospital stroke scales and 10 ML models were eligible for summary receiver operating characteristic analysis. Pooled sensitivity and specificity for any prehospital stroke scale were 0.72 (95% CI, 0.68-0.75) and 0.77 (95% CI, 0.72-0.81), respectively; summary receiver operating characteristic curve AUC was 0.80 (95% CI, 0.76-0.83). Pooled sensitivity for any ML model for LVO was 0.73 (95% CI, 0.64-0.79), specificity was 0.85 (95% CI, 0.80-0.89), and summary receiver operating characteristic curve AUC was 0.87 (95% CI, 0.83-0.89).ConclusionsBoth prehospital stroke scales and ML models demonstrated varying accuracies in predicting LVO. Despite ML potential for improved LVO detection in the prehospital setting, application remains limited by the absence of prospective external validation, limited sample sizes, and lack of real-world performance data in a prehospital setting

Multicenter evaluation of the vitek MS matrix-assisted laser desorption ionization-time of flight mass spectrometry system for identification of gram-positive aerobic bacteria

Matrix-assisted laser desorption ionization–time of flight mass spectrometry (MALDI-TOF) is gaining momentum as a tool for bacterial identification in the clinical microbiology laboratory. Compared with conventional methods, this technology can more readily and conveniently identify a wide range of organisms. Here, we report the findings from a multicenter study to evaluate the Vitek MS v2.0 system (bioMérieux, Inc.) for the identification of aerobic Gram-positive bacteria. A total of 1,146 unique isolates, representing 13 genera and 42 species, were analyzed, and results were compared to those obtained by nucleic acid sequence-based identification as the reference method. For 1,063 of 1,146 isolates (92.8%), the Vitek MS provided a single identification that was accurate to the species level. For an additional 31 isolates (2.7%), multiple possible identifications were provided, all correct at the genus level. Mixed-genus or single-choice incorrect identifications were provided for 18 isolates (1.6%). Although no identification was obtained for 33 isolates (2.9%), there was no specific bacterial species for which the Vitek MS consistently failed to provide identification. In a subset of 463 isolates representing commonly encountered important pathogens, 95% were accurately identified to the species level and there were no misidentifications. Also, in all but one instance, the Vitek MS correctly differentiated Streptococcus pneumoniae from other viridans group streptococci. The findings demonstrate that the Vitek MS system is highly accurate for the identification of Gram-positive aerobic bacteria in the clinical laboratory setting

Contribution of Exogenous Genetic Elements to the Group A Streptococcus Metagenome

Variation in gene content among strains of a bacterial species contributes to biomedically relevant differences in phenotypes such as virulence and antimicrobial resistance. Group A Streptococcus (GAS) causes a diverse array of human infections and sequelae, and exhibits a complex pathogenic behavior. To enhance our understanding of genotype-phenotype relationships in this important pathogen, we determined the complete genome sequences of four GAS strains expressing M protein serotypes (M2, M4, and 2 M12) that commonly cause noninvasive and invasive infections. These sequences were compared with eight previously determined GAS genomes and regions of variably present gene content were assessed. Consistent with the previously determined genomes, each of the new genomes is ∼1.9 Mb in size, with ∼10% of the gene content of each encoded on variably present exogenous genetic elements. Like the other GAS genomes, these four genomes are polylysogenic and prophage encode the majority of the variably present gene content of each. In contrast to most of the previously determined genomes, multiple exogenous integrated conjugative elements (ICEs) with characteristics of conjugative transposons and plasmids are present in these new genomes. Cumulatively, 242 new GAS metagenome genes were identified that were not present in the previously sequenced genomes. Importantly, ICEs accounted for 41% of the new GAS metagenome gene content identified in these four genomes. Two large ICEs, designated 2096-RD.2 (63 kb) and 10750-RD.2 (49 kb), have multiple genes encoding resistance to antimicrobial agents, including tetracycline and erythromycin, respectively. Also resident on these ICEs are three genes encoding inferred extracellular proteins of unknown function, including a predicted cell surface protein that is only present in the genome of the serotype M12 strain cultured from a patient with acute poststreptococcal glomerulonephritis. The data provide new information about the GAS metagenome and will assist studies of pathogenesis, antimicrobial resistance, and population genomics

Nonstandard Errors

In statistics, samples are drawn from a population in a data-generating process (DGP). Standard errors measure the uncertainty in estimates of population parameters. In science, evidence is generated to test hypotheses in an evidence-generating process (EGP). We claim that EGP variation across researchers adds uncertainty-nonstandard errors (NSEs). We study NSEs by letting 164 teams test the same hypotheses on the same data. NSEs turn out to be sizable, but smaller for more reproducible or higher rated research. Adding peer-review stages reduces NSEs. We further find that this type of uncertainty is underestimated by participants

Non-Standard Errors

In statistics, samples are drawn from a population in a data-generating process (DGP). Standard errors measure the uncertainty in estimates of population parameters. In science, evidence is generated to test hypotheses in an evidence-generating process (EGP). We claim that EGP variation across researchers adds uncertainty: Non-standard errors (NSEs). We study NSEs by letting 164 teams test the same hypotheses on the same data. NSEs turn out to be sizable, but smaller for better reproducible or higher rated research. Adding peer-review stages reduces NSEs. We further find that this type of uncertainty is underestimated by participants