Evaluation of retinal and choroidal thickness changes in overweight and obese adults without ocular symptoms by swept-source optical coherence tomography.

AIM: To evaluate the relationship of overweight and obesity with retinal and choroidal thickness in adults without ocular symptoms by swept-source optical coherence tomography (SS-OCT). METHODS: According to the body mass index (BMI) results, the adults enrolled in the cross-sectional study were divided into the normal group (18.50≤BMI<25.00 kg/m2), the overweight group (25.00≤BMI<30.00 kg/m2), and the obesity group (BMI≥30.00 kg/m2). The one-way ANOVA and the Chi-square test were used for comparisons. Pearson's correlation analysis was used to evaluate the relationships between the measured variables. RESULTS: This research covered the left eyes of 3 groups of 434 age- and sex-matched subjects each: normal, overweight, and obesity. The mean BMI was 22.20±1.67, 26.82±1.38, and 32.21±2.35 kg/m2 in normal, overweight and obesity groups, respectively. The choroid was significantly thinner in both the overweight and obesity groups compared to the normal group (P<0.05 for all), while the retinal thickness of the three groups did not differ significantly. Pearson's correlation analysis showed that BMI was significantly negatively correlated with choroidal thickness, but no significant correlation was observed between BMI and retinal thickness. CONCLUSION: Choroidal thickness is decreased in people with overweight or obesity. Research on changes in choroidal thickness contributes to the understanding of the mechanisms of certain ocular disorders in overweight and obese adults.

Prediction Model of Ocular Metastases in Gastric Adenocarcinoma: Machine Learning-Based Development and Interpretation Study.

Background: Although gastric adenocarcinoma (GA) related ocular metastasis (OM) is rare, its occurrence indicates a more severe disease. We aimed to utilize machine learning (ML) to analyze the risk factors of GA-related OM and predict its risks. Methods: This is a retrospective cohort study. The clinical data of 3532 GA patients were collected and randomly classified into training and validation sets in a ratio of 7:3. Those with or without OM were classified into OM and non-OM (NOM) groups. Univariate and multivariate logistic regression analyses and least absolute shrinkage and selection operator were conducted. We integrated the variables identified through feature importance ranking and further refined the selection process using forward sequential feature selection based on random forest (RF) algorithm before incorporating them into the ML model. We applied six ML algorithms to construct the predictive GA model. The area under the receiver operating characteristic (ROC) curve indicated the model's predictive ability. Also, we established a network risk calculator based on the best performance model. We used Shapley additive interpretation (SHAP) to identify risk factors and to confirm the interpretability of the black box model. We have de-identified all patient details. Results: The ML model, consisting of 13 variables, achieved an optimal predictive performance using the gradient boosting machine (GBM) model, with an impressive area under the curve (AUC) of 0.997 in the test set. Utilizing the SHAP method, we identified crucial factors for OM in GA patients, including LDL, CA724, CEA, AFP, CA125, Hb, CA153, and Ca2+. Additionally, we validated the model's reliability through an analysis of two patient cases and developed a functional online web prediction calculator based on the GBM model. Conclusion: We used the ML method to establish a risk prediction model for GA-related OM and showed that GBM performed best among the six ML models. The model may identify patients with GA-related OM to provide early and timely treatment.

Retinal thickness and fundus blood flow density changes in chest pain subjects with dyslipidemia.

AIM: To assess the retinal thickness and fundus blood flow density changes in chest pain patients with dyslipidemia using optical coherence tomography angiography (OCTA). METHODS: All subjects with chest pain as the main symptom accepted a comprehensive ophthalmological examination. According to the serum lipid levels, the participants were divided into the control group and the dyslipidemia group. The retina thickness and fundus blood flow density were determined using OCTA. RESULTS: The study enrolled 87 left eyes from 87 adults with dyslipidemia and 87 left eyes from age- and sex-matched participants without dyslipidemia. The retina of dyslipidemia subjects was significantly thinner than that of the controls in the inferior (P=0.004 and P=0.014, respectively) and temporal (P=0.015 and P=0.019, respectively) regions, both inner and outer layers. In terms of blood flow density in the macula or optic disk, there was a decreasing trend in the dyslipidemia group compared with the control group, especially in the inferior and temporal regions. CONCLUSION: Dyslipidemia may contribute to the decrease in retinal thickness and fundus blood flow density. Further validation of the association between abnormal lipid metabolism and fundus microcirculation alterations needs to be carried out in chest pain patients.

Prediction model of ocular metastasis from primary liver cancer: Machine learning-based development and interpretation study.

BACKGROUND: Ocular metastasis (OM) is a rare metastatic site of primary liver cancer (PLC). The purpose of this study was to establish a clinical predictive model of OM in PLC patients based on machine learning (ML). METHODS: We retrospectively collected the clinical data of 1540 PLC patients and divided it into a training set and an internal test set in a 7:3 proportion. PLC patients were divided into OM and non-ocular metastasis (NOM) groups, and univariate logistic regression analysis was performed between the two groups. The variables with univariate logistic analysis p < 0.05 were selected for the ML model. We constructed six ML models, which were internally verified by 10-fold cross-validation. The prediction performance of each ML model was evaluated by receiver operating characteristic curves (ROCs). We also constructed a web calculator based on the optimal performance ML model to personalize the risk probability for OM. RESULTS: Six variables were selected for the ML model. The extreme gradient boost (XGB) ML model achieved the optimal differential diagnosis ability, with an area under the curve (AUC) = 0.993, accuracy = 0.992, sensitivity = 0.998, and specificity = 0.984. Based on these results, an online web calculator was constructed by using the XGB ML model to help clinicians diagnose and treat the risk probability of OM in PLC patients. Finally, the Shapley additive explanations (SHAP) library was used to obtain the six most important risk factors for OM in PLC patients: CA125, ALP, AFP, TG, CA199, and CEA. CONCLUSION: We used the XGB model to establish a risk prediction model of OM in PLC patients. The predictive model can help identify PLC patients with a high risk of OM, provide early and personalized diagnosis and treatment, reduce the poor prognosis of OM patients, and improve the quality of life of PLC patients.

Retinal alterations in evaluation of rheumatoid arthritis with chloroquine treatment: A new approach.

OBJECTIVE: To evaluate the effect of hydroxychloroquine on conjunctival and retinal microvascular density in rheumatoid arthritis (RA) patients. METHODS: Ten healthy controls, 10 RA patients who had not been treated with hydroxychloroquine, and 10 RA patients who had been treated with chloroquine for more than 5 years were recruited. Optical coherence tomography (OCTA) was used to examine the conjunctival and superficial and deep retinal microvascular density and compared the differences in microvascular density between the three groups. RESULTS: The vascular density in RA group in superficial microvascular was significantly lower than that in control group (p < 0.001). Compared with RA group, the chloroquine group showed statistically significantly lower microvascular (p < 0.001) and deep microvascular (p = 0.018). Superficial microvascular was positively correlated with conjunctival vessel density in RA patients (r = 0.868, p = 0.0048). CONCLUSIONS: The use of chloroquine could further reduce the vascular density in the absence of statistical difference in the course of the disease.

Dynamic analysis of wild and sterile mosquito release model with Poincaré map.

In recent years, the application of impulsive semi-dynamic system in state-dependent feed-back control has attracted extensive attention, but most models only discuss their special cases without delving into their complex dynamics. Therefore, we establish the wild and sterile mosquito system with integrated mosquito control, and use the Poincaré map method to conduct a comprehensive analysis of the model dynamics. First, the main properties of Poincaré map such as monotonicity, continuous differentiability, extremum and fixed point are discussed. Second, we prove the existence and stability of boundary periodic solution and study the influence of its parameters on the system. Then the ex-istence and global stability of the order-1 periodic solution and the existence condition of the order-k (k > 1) periodic solution are analyzed. Finally, our conclusion is verified by numerical analysis. The results show that the population density of wild mosquitoes can be controlled below the threshold by integrated mosquito control.

The Use of Apatinib in Treating Nonsmall-Cell Lung Cancer: Case Report and Review of Literature.

Apatinib is a novel tyrosine kinase inhibitor targeting vascular endothelial growth factor receptor-2, which has been proved to be effective and safe in treating heavily pretreated patients with gastric cancer.The aim of the study was to explore the use of apatinib in treatment of nonsmall cell lung cancer and its side effects.We report 2 patients presented with advanced nonsmall-cell lung cancer, who received apatinib after failure in the first- or third-line chemotherapy. They are treated with apatinib in daily dose of 850 mg, 28 days per cycle.Favorable oncologic outcomes were achieved in the 2 cases after the treatment of apatinib. Patient I's progression-free-survival has increased to 4.6 months after palliative therapy of apatinib, whereas Patient II nearly 6 months. The common side effects of apatinib were hypertension and hand-foot syndrome; however, the toxicity of apatinib was controllable and tolerable.Apatinib may be an option for advanced nonsmall cell lung cancer after failure of chemotherapy or other targeted therapy. But that still warrants further investigation in the prospective study.