Eyes as the windows into cardiovascular disease in the era of big data.

Cardiovascular disease (CVD) is a major cause of mortality and morbidity worldwide and imposes significant socioeconomic burdens, especially with late diagnoses. There is growing evidence of strong correlations between ocular images, which are information-dense, and CVD progression. The accelerating development of deep learning algorithms (DLAs) is a promising avenue for research into CVD biomarker discovery, early CVD diagnosis, and CVD prognostication. We review a selection of 17 recent DLAs on the less-explored realm of DL as applied to ocular images to produce CVD outcomes, potential challenges in their clinical deployment, and the path forward. The evidence for CVD manifestations in ocular images is well documented. Most of the reviewed DLAs analyze retinal fundus photographs to predict CV risk factors, in particular hypertension. DLAs can predict age, sex, smoking status, alcohol status, body mass index, mortality, myocardial infarction, stroke, chronic kidney disease, and hematological disease with significant accuracy. While the cardio-oculomics intersection is now burgeoning, very much remain to be explored. The increasing availability of big data, computational power, technological literacy, and acceptance all prime this subfield for rapid growth. We pinpoint the specific areas of improvement toward ubiquitous clinical deployment: increased generalizability, external validation, and universal benchmarking. DLAs capable of predicting CVD outcomes from ocular inputs are of great interest and promise to individualized precision medicine and efficiency in the provision of health care with yet undetermined real-world efficacy with impactful initial results.

Pepsin in saliva for the diagnosis of erosive esophagitis post-sleeve gastrectomy: a prospective observational study.

BACKGROUND: Laparoscopic sleeve gastrectomy (LSG) has become the preferred bariatric procedure in many countries. However, new onset erosive esophagitis (EE) is a major shortcoming. Current recommendation is esophago-gastro-duodenoscopy (EGD) should be performed routinely at 1 year and subsequently every 2-3 years to enable the early detection of Barrett's or esophageal adenocarcinoma. This would put significant strains on resources and costs of bariatric program. Our study assesses the association between and diagnostic value of salivary pepsin concentration and endoscopically proven EE in post-LSG patients as a surrogate for EGD. METHODS: Twenty patients on routine post-LSG endoscopy between June and September 2022 were recruited for this correlational pilot study. Under supervision, fasting and post-prandial saliva sample was collected and analyzed by Peptest lateral flow device. EGD examinations were performed, and patients completed a validated 25-item QoLRAD questionnaire. RESULTS: We found a significant correlation between positive endoscopy findings of EE and salivary pepsin concentrations. The normal group had a lower mean fasting pepsin level (13.13 ng/mL ± 18.97) versus the EE-group (90.55 ng/mL ± 81.28, p = 0.009) and lower mean post-prandial pepsin level (30.50 ng/mL ± 57.72) versus the EE-group (135.09 ng/mL ± 130.17, p = 0.02). The predictive probabilities from the binary regression of fasting and post-prandial pepsin concentrations yield AUC of 0.955 ± 0.044 (95% CI 0.868 to 1.000, p < 0.001). CONCLUSION: Our study distinctively identified salivary pepsin to have excellent sensitivity and negative predictive value in EE, potentially useful to preclude the need for post-LSG EGD in asymptomatic patients with low salivary pepsin.

Highly recurrent CBS epimutations in gastric cancer CpG island methylator phenotypes and inflammation.

BACKGROUND: CIMP (CpG island methylator phenotype) is an epigenetic molecular subtype, observed in multiple malignancies and associated with the epigenetic silencing of tumor suppressors. Currently, for most cancers including gastric cancer (GC), mechanisms underlying CIMP remain poorly understood. We sought to discover molecular contributors to CIMP in GC, by performing global DNA methylation, gene expression, and proteomics profiling across 14 gastric cell lines, followed by similar integrative analysis in 50 GC cell lines and 467 primary GCs. RESULTS: We identify the cystathionine beta-synthase enzyme (CBS) as a highly recurrent target of epigenetic silencing in CIMP GC. Likewise, we show that CBS epimutations are significantly associated with CIMP in various other cancers, occurring even in premalignant gastroesophageal conditions and longitudinally linked to clinical persistence. Of note, CRISPR deletion of CBS in normal gastric epithelial cells induces widespread DNA methylation changes that overlap with primary GC CIMP patterns. Reflecting its metabolic role as a gatekeeper interlinking the methionine and homocysteine cycles, CBS loss in vitro also causes reductions in the anti-inflammatory gasotransmitter hydrogen sulfide (H2S), with concomitant increase in NF-κB activity. In a murine genetic model of CBS deficiency, preliminary data indicate upregulated immune-mediated transcriptional signatures in the stomach. CONCLUSIONS: Our results implicate CBS as a bi-faceted modifier of aberrant DNA methylation and inflammation in GC and highlights H2S donors as a potential new therapy for CBS-silenced lesions.