Fluid biomarkers in cerebral amyloid angiopathy.

Cerebral amyloid angiopathy (CAA) is a type of cerebrovascular disorder characterised by the accumulation of amyloid within the leptomeninges and small/medium-sized cerebral blood vessels. Typically, cerebral haemorrhages are one of the first clinical manifestations of CAA, posing a considerable challenge to the timely diagnosis of CAA as the bleedings only occur during the later disease stages. Fluid biomarkers may change prior to imaging biomarkers, and therefore, they could be the future of CAA diagnosis. Additionally, they can be used as primary outcome markers in prospective clinical trials. Among fluid biomarkers, blood-based biomarkers offer a distinct advantage over cerebrospinal fluid biomarkers as they do not require a procedure as invasive as a lumbar puncture. This article aimed to provide an overview of the present clinical data concerning fluid biomarkers associated with CAA and point out the direction of future studies. Among all the biomarkers discussed, amyloid ß, neurofilament light chain, matrix metalloproteinases, complement 3, uric acid, and lactadherin demonstrated the most promising evidence. However, the field of fluid biomarkers for CAA is an under-researched area, and in most cases, there are only one or two studies on each of the biomarkers mentioned in this review. Additionally, a small sample size is a common limitation of the discussed studies. Hence, it is hard to reach a solid conclusion on the clinical significance of each biomarker at different stages of the disease or in various subpopulations of CAA. In order to overcome this issue, larger longitudinal and multicentered studies are needed.

Color and physiochemical attributes of pointed gourd (Trichosanthes dioica Roxb.) influenced by modified atmosphere packaging and postharvest treatment during storage.

The efficiency of modified atmosphere packaging (MAP) in combination with postharvest treatment on the shelf-life, physiochemical attributes, color, and nutrition of pointed gourd was studied after storing in refrigerated (low temperature, LT) and ambient (room temperature, RT) conditions. Fresh pointed gourd fruits were dipped in NaOCl solution (0.01% w/v) and potassium metabisulphite (KMS) (0.05% w/v), blanched (100°C for 4 min), and then packed in perforated and non-perforated polythene and polypropylene packets of each type and brown paper bags as MAP before storing at LT and RT. Physiochemical attributes, color, and nutrition were measured until the marketable level of acceptance (up to shelf-life) after storage and compared with the untreated and unpacked samples (control). The results showed profound differences among the treatment variables in all the studied dependent parameters regarding the LT and RT storage conditions. Among the treatments, perforated and non-perforated polyethylene (NPE) and polypropylene (NPP) packaging performed well to retain a considerable amount of ascorbic acid, ß-carotene, and greenish color (lower L*, high h*) in pointed gourd treated with NaOCl (0.01%) and KMS (0.05%) after storing at LT and RT. Furthermore, the principal component analysis suggested that five major quality attributes (L*, C*, h*, shelf-life, and ascorbic acid) were influenced remarkably in terms of non-perforated polyethylene packaging in combination with KMS treatment both in LT and RT storage conditions. However, perforated polythene and polypropylene in combination with NaOCl responded well in RT but only for the shortest storage life. Thus, a non-perforated polythene package with KMS treatment would be the best solution for retaining market quality acceptance with green color up to the extended shelf-life of 23 and 10 days, respectively, in the refrigerator (LT) and in ambient (RT) storage conditions.

Evaluation of spatial Bayesian Empirical Likelihood models in analysis of small area data.

Bayesian empirical likelihood (BEL) models are becoming increasingly popular as an attractive alternative to fully parametric models. However, they have only recently been applied to spatial data analysis for small area estimation. This study considers the development of spatial BEL models using two popular conditional autoregressive (CAR) priors, namely BYM and Leroux priors. The performance of the proposed models is compared with their parametric counterparts and with existing spatial BEL models using independent Gaussian priors and generalised Moran basis priors. The models are applied to two benchmark spatial datasets, simulation study and COVID-19 data. The results indicate promising opportunities for these models to capture new insights into spatial data. Specifically, the spatial BEL models outperform the parametric spatial models when the underlying distributional assumptions of data appear to be violated.

Correction to 'Augmenting disease maps: a Bayesian meta-analysis approach'.

[This corrects the article DOI: 10.1098/rsos.192151.][This corrects the article DOI: 10.1098/rsos.192151.].

Multivariate Bayesian meta-analysis: joint modelling of multiple cancer types using summary statistics.

BACKGROUND: Cancer atlases often provide estimates of cancer incidence, mortality or survival across small areas of a region or country. A recent example of a cancer atlas is the Australian cancer atlas (ACA), that provides interactive maps to visualise spatially smoothed estimates of cancer incidence and survival for 20 different cancer types over 2148 small areas across Australia. METHODS: The present study proposes a multivariate Bayesian meta-analysis model, which can model multiple cancers jointly using summary measures without requiring access to the unit record data. This new approach is illustrated by modelling the publicly available spatially smoothed standardised incidence ratios for multiple cancers in the ACA divided into three groups: common, rare/less common and smoking-related. The multivariate Bayesian meta-analysis models are fitted to each group in order to explore any possible association between the cancers in three remoteness regions: major cities, regional and remote areas across Australia. The correlation between the pairs of cancers included in each multivariate model for a group was examined by computing the posterior correlation matrix for each cancer group in each region. The posterior correlation matrices in different remoteness regions were compared using Jennrich's test of equality of correlation matrices (Jennrich in J Am Stat Assoc. 1970;65(330):904-12. https://doi.org/10.1080/01621459.1970.10481133 ). RESULTS: Substantive correlation was observed among some cancer types. There was evidence that the magnitude of this correlation varied according to remoteness of a region. For example, there has been significant negative correlation between prostate and lung cancer in major cities, but zero correlation found in regional and remote areas for the same pair of cancer types. High risk areas for specific combinations of cancer types were identified and visualised from the proposed model. CONCLUSIONS: Publicly available spatially smoothed disease estimates can be used to explore additional research questions by modelling multiple cancer types jointly. These proposed multivariate meta-analysis models could be useful when unit record data are unavailable because of privacy and confidentiality requirements.

Augmenting disease maps: a Bayesian meta-analysis approach.

Analysis of spatial patterns of disease is a significant field of research. However, access to unit-level disease data can be difficult for privacy and other reasons. As a consequence, estimates of interest are often published at the small area level as disease maps. This motivates the development of methods for analysis of these ecological estimates directly. Such analyses can widen the scope of research by drawing more insights from published disease maps or atlases. The present study proposes a hierarchical Bayesian meta-analysis model that analyses the point and interval estimates from an online atlas. The proposed model is illustrated by modelling the published cancer incidence estimates available as part of the online Australian Cancer Atlas (ACA). The proposed model aims to reveal patterns of cancer incidence for the 20 cancers included in ACA in major cities, regional and remote areas. The model results are validated using the observed areal data created from unit-level data on cancer incidence in each of 2148 small areas. It is found that the meta-analysis models can generate similar patterns of cancer incidence based on urban/rural status of small areas compared with those already known or revealed by the analysis of observed data. The proposed approach can be generalized to other online disease maps and atlases.

Twenty-four hour intraocular pressure monitoring with the SENSIMED Triggerfish contact lens: effect of body posture during sleep.

PURPOSE: To determine the difference in relative intraocular pressure (IOP) measured by the SENSIMED Triggerfish (TF) contact lens in flat compared with 30° head-up sleeping positions in patients with progressive primary open-angle glaucoma or normotensive glaucoma, based on recent or recurrent disc haemorrhage. DESIGN: Prospective, randomised, cross-over, open-label comparative study. METHODS: IOP was monitored for 24 hours using TF on two separate sessions. Patients were randomly assigned to sleep flat one night and 30° head-up the other. Outputs in arbitrary units were obtained. Sleep and wake periods were defined as 22:00-6:00 and 8:00-22:00, respectively. Mean TF values during sleep and wake periods and wake-sleep and sleep-wake slopes were calculated for each session. TF output signals were compared between positions. RESULTS: Twelve subjects completed the study. Significant mean positive slopes were noted during the sleep period for both positions (p<0.01). No significant differences in the TF mean values were observed between positions (p=0.51). Six (54%) subjects had mean TF values significantly higher during the flat supine session, while four (36%) subjects had higher values during the head-up session. A significant increase in Goldmann IOP (p=0.001) and TF (p=0.02) measurements were observed after 24 hours of TF wear ('drift phenomenon'). CONCLUSIONS: Sleep position affects IOP as measured by TF in some patients with progressive glaucoma. The upward drift in TF output detected in >50% of the subjects requires further investigation to establish whether the increased output values over time are an artefact induced by the TF or a real change in IOP. TRIAL REGISTRATION NUMBER: NCT01351779.