Temporal variations in meibomian gland structure—A pilot study

Purpose: To investigate whether there is a measurable change in meibomian gland morphological characteristics over the course of a day (12h) and over a month.Methods: The study enrolled 15 participants who attended a total of 11 study visits spanning a 5-week period. To assess diurnal changes in meibomian glands, seven visits were conducted on a single day, each 2h apart. For monthly assessment, participants attended an additional visit at the same time of the day every week for three consecutive weeks. Meibography using the LipiView® II system was performed at each visit, and meibomian gland morphological parameters were calculated using custom semi-automated software. Specifically, six central glands were analysed for gland length ratio, gland width, gland area, gland intensity and gland tortuosity.Results: The average meibomian gland morphological metrics did not exhibit significant changes during the course of a day or over a month. Nonetheless, certain individual gland metrics demonstrated notable variation over time, both diurnally and monthly. Specifically, meibomian gland length ratio, area, width and tortuosity exhibited significant changes both diurnally and monthly when assessed on a gland-by-gland basis.Conclusions: Meibomian glands demonstrated measurable structural change over short periods of time (hours and days). These results have implications for innovation in gland imaging and for developing precision monitoring of gland structure to assess meibomian gland  health more accurately

Antimalarial Activity and Mechanisms of Action of Two Novel 4-Aminoquinolines against Chloroquine-Resistant Parasites

Chloroquine (CQ) is a cost effective antimalarial drug with a relatively good safety profile (or therapeutic index). However, CQ is no longer used alone to treat patients with Plasmodium falciparum due to the emergence and spread of CQ-resistant strains, also reported for P. vivax. Despite CQ resistance, novel drug candidates based on the structure of CQ continue to be considered, as in the present work. One CQ analog was synthesized as monoquinoline (MAQ) and compared with a previously synthesized bisquinoline (BAQ), both tested against P. falciparum in vitro and against P. berghei in mice, then evaluated in vitro for their cytotoxicity and ability to inhibit hemozoin formation. Their interactions with residues present in the NADH binding site of P falciparum lactate dehydrogenase were evaluated using docking analysis software. Both compounds were active in the nanomolar range evaluated through the HRPII and hypoxanthine tests. MAQ and BAQ derivatives were not toxic, and both compounds significantly inhibited hemozoin formation, in a dose-dependent manner. MAQ had a higher selectivity index than BAQ and both compounds were weak PfLDH inhibitors, a result previously reported also for CQ. Taken together, the two CQ analogues represent promising molecules which seem to act in a crucial point for the parasite, inhibiting hemozoin formation

Meibomian gland function cannot be predicted by Meibography in patients symptomatic for dry eye

Purpose: The purpose of this study was to determine if meibography could predict meibomian gland (MG) function with regard to number of functional MGs and/or estimation of functional MG volume in patients symptomatic for dry eye. Methods: Patients (n=23) symptomatic for dry eye who met the inclusion criteria for the study were fully consented and enrolled. Inclusion criteria: willingness to participate in the study, over the age of 18, no lid abnormalities, no current ocular inflammation/disease, no ocular surgery within the last 6 months, no history of lid surgery. Symptoms were scored using the SPEED questionnaire. MG function and estimation of functional MG volume were performed with the Korb meibomian gland evaluator. Meibography was performed using the Modi Topographer and analyzed using the Phoenix software provided. Lower lids were examined in three equal sections: nasal (N), central (C) and temporal (T) for the number of functional MGs and their functional volume (volume was as 1 for minimal, 2 for moderate and 3 for copious), and for MG dropout. MG dropout was categorized according to the Pult Meiboscale. Results: Only data for right eyes are presented. The mean age and symptom score of the patients was 48.0±12.1 years (5 males; 18 females) and 8.9±5.0 respectively. The average number of functional glands per lid section was: N=2.7±1.7, C=2.2±2.0, T=0.2±0.5. The estimated functional gland volume per lid section was: N=5.0±3.9, C=3.2±3.2, T=0.3±1.1. The N and C lid sections had significantly more functional MGs and higher functional gland volume relative to the T section (p < 0.005). Conversely the amount of gland loss as determined by gland atrophy was significantly highest in the nasal section of the lid (p<0.0001) and drop out showed no apparent correlation with MG function or functional volume. Conclusions: There appears to be no relationship between the level of apparent drop out and the number of functional MGs and/or functional MG volume. These counterintuitive results strongly indicate that standard noncontact infrared meibography cannot be used to predict MG function in terms of number of functional glands and/or functional gland volume except in the case of total gland dropout, when the glands are completely absent

Evaluation of Meibomian gland structure and appearance after therapeutic Meibomian gland expression

Clinical Relevance: Evaluating how Meibomian glands can change in appearance has the potential to advance the understanding of Meibomian gland health and may lead to enhanced diagnosis and therapy.Background: This work aimed to investigate Meibomian gland appearance after therapeutic Meibomian gland expression.Methods: Fifteen subjects attended three study visits over a two-week period. Meibography was performed before and after therapeutic Meibomian gland expression, the following day, and 2 weeks after expression. Six central glands were used to calculate Meibomian gland morphological parameters such as gland length ratio, gland width, gland area, gland tortuosity, and gland contrast. A custom semi-automated image analysis software was used to calculate Meibomian gland metrics. Furthermore, a high-resolution imaging system was developed to capture clear images of the Meibomian glands, free of any artefacts, which were used for precise calculations of Meibomian gland contrast.Results: The expression procedure had a significant impact on Meibomian gland contrast and length ratio immediately afterwards. The least square mean difference (95% CI) from baseline for Michelson contrast was −0.006 (−0.010, −0.001) and −1.048 (−2.063, −0.033) for simple contrast.  The least square mean ratio of the gland length ratio immediately after the expression to baseline was 0.758 (0.618, 0.931).Conclusions: Following therapeutic expression, Meibomian glands exhibit reduced brightness and length. However, within 24 h, they appear to recover and return to their baseline state, indicating a relatively short recovery time. This sheds light on whether meibography is solely focused on capturing gland structure or if it also captures acinar activity. The hyperreflective properties of lipids suggest that the decrease in contrast observed after expression could be attributed to a reduction in the visualisation of acini activity. A decrease in Meibomian gland length ratio implies that the loss of gland structure following treatment may be indicative of a temporary structural alteration

A Deep Learning Approach for Meibomian Gland Appearance Evaluation

Purpose: To develop and evaluate a deep learning algorithm for Meibomian gland characteristics calculation. Design: Evaluation of diagnostic technology. Subjects: A total of 1616 meibography images of both the upper (697) and lower (919) eyelids from a total of 282 individuals. Methods: Images were collected using the LipiView II device. All the provided data were split into 3 sets: the training, validation, and test sets. Data partitions used proportions of 70/10/20% and included data from 2 optometry settings. Each set was separately partitioned with these proportions, resulting in a balanced distribution of data from both settings. The images were divided based on patient identifiers, such that all images collected for one participant could end up only in one set. The labeled images were used to train a deep learning model, which was subsequently used for Meibomian gland segmentation. The model was then applied to calculate individual Meibomian gland metrics. Interreader agreement and agreement between manual and automated methods for Meibomian gland segmentation were also carried out to assess the accuracy of the automated approach. Main Outcome Measures: Meibomian gland metrics, including length ratio, area, tortuosity, intensity, and width, were measured. Additionally, the performance of the automated algorithms was evaluated using the aggregated Jaccard index. Results: The proposed semantic segmentation–based approach achieved average aggregated Jaccard index of mean 0.4718 (95% confidence interval [CI], 0.4680–0.4771) for the ‘gland’ class and a mean of 0.8470 (95% CI, 0.8432–0.8508) for the ‘eyelid’ class. The result for object detection–based approach was a mean of 0.4476 (95% CI, 0.4426–0.4533). Both artificial intelligence–based algorithms underestimated area, length ratio, tortuosity, widthmean, widthmedian, width10th, and width90th. Meibomian gland intensity was overestimated by both algorithms compared with the manual approach. The object detection–based algorithm seems to be as reliable as the manual approach only for Meibomian gland width10th calculation. Conclusions: The proposed approach can successfully segment Meibomian glands; however, to overcome problems with gland overlap and lack of image sharpness, the proposed method requires further development. The study presents another approach to utilizing automated, artificial intelligence–based methods in Meibomian gland health assessment that may assist clinicians in the diagnosis, treatment, and management of Meibomian gland dysfunction. Financial Disclosure(s): The authors have no proprietary or commercial interest in any materials discussed in this article