Publications

PURPOSE: The purpose of this study was to assess the reflectivity of the outer retinal layers (ORLs) in patients with central serous chorioretinopathy (CSCR) and to examine the relationship between the dimensions of the subretinal fluid (SRF) and ORL.

METHODS: This retrospective, cross-sectional study included 33 eyes of 33 patients with CSCR and 33 age- and gender-matched controls. Unnormalized and relative reflectivities for the retinal pigment epithelium (RPE), the external limiting membrane (ELM), and the ellipsoid zone (EZ), as well as SRF height, base width, and area, were measured on optical coherence tomography images. Reflectivity measurements for each retinal layer were performed at three anatomic locations (foveal center, nasal, and temporal regions, 1 mm apart), and the average of these three values was used to calculate average reflectivity (RPEav, EZav, ELMav).

RESULTS: RPEav, EZav, and ELMav were lower in patients with CSCR (P < 0.001). In the pigment epithelium detachment (PED) group, EZn and EZav were significantly lower than in the non-PED group (P = 0.012 and P = 0.013, respectively). A negative correlation was observed between SRF base width and EZav (P = 0.018) and ELMav (P = 0.021). SRF area was negatively correlated with both EZav (P = 0.049) and ELMav (P = 0.025). RPEc was negatively correlated with SRF elevation (P = 0.016).

CONCLUSIONS: This study reveals novel associations between SRF dimensions, PED presence, and outer retinal layer damage in CSCR. Monitoring ORL reflectivity changes may provide insights into disease pathogenesis and help evaluate treatment efficacy.

The growing impact of climate change has highlighted the importance of effective disaster housing recovery (DHR) measures, particularly in resource-constrained places prone to flooding. As these communities confront displacement and financial instability, allocating resources for post-DHR is crucial. This study presents an innovative strategy for improving DHR planning and execution that uses genetic algorithms (GAs), with a focus on Long-Term Recovery Groups (LTRGs) and community engagement for long-term results. By utilizing adaptive capabilities of GAs, the model efficiently navigates the complexity of resource allocation, balancing several criteria, such as cost-effectiveness, housing coverage, and stakeholder needs. This study evaluates the efficacy of GAs in DHR planning by developing and evaluating hypotheses on optimization, LTRG preparedness, and community autonomy. The results show that GA-driven planning considerably improves resource allocation decisions, promoting resilience and long-term recovery. The findings highlight the ability of GAs to solve complex difficulties in DHR, providing insights for policymakers, urban planners, and disaster response teams looking to improve recovery processes and community -resilience.