Pernicious anemia is a common cause of cobalamin deficiency-caused megaloblastic anemia in Hainan, China.

BACKGROUND: Pernicious anemia (PA) is believed to be highly prevalent in Western countries but has rarely been reported in China. The study explores whether PA, an autoimmune disease, is an uncommon cause of cobalamin (vitamin B12) deficiency anemia in China. METHODS: Clinical and hematological data were collected from 90 cobalamin deficiency-caused megaloblastic anemia (MA) patients between July 2014 and December 2021. Through anti-intrinsic factor antibody (IFA) and anti-parietal cell antibody (PCA) testing, PA was distinguished from other causes of cobalamin deficiency leading to MA. Meanwhile, 30 healthy controls (HCs) were included to estimate the positive rates of IFA and PCA. RESULTS: Of the 30 HCs, only one tested positive for IFA, and all 30 tested negative for PCA. Among the 90 patients with cobalamin deficiency-caused MA, 76.7% were positive for IFA, and 47.8% were positive for PCA; a total of 76 patients (84.4%) were diagnosed with PA. The mean follow-up time was 41.0 ± 16.3 months. During the follow-up period, no case relapsed among the continuous cobalamin-supply treatment patients, while 24.4% of patients relapsed due to the interruption of maintenance cobalamin-supplement therapy (the median recurrence time was 54.0 ± 17.7 months). CONCLUSIONS: The proportion of PA in cobalamin deficiency-caused MA patients in Hainan province was higher than 80%, which was more common than expected. Therefore, screening for IFA, PCA, endoscopic biopsy, and thyroid-related parameters are recommended for all cobalamin deficiency-caused MA patients. Furthermore, maintenance cobalamin-supplement therapy is important for PA patients.

This research examines pernicious anemia (PA), a type of anemia caused by vitamin B12 deficiency, which has been widely reported in Western countries but is less known in China. The study focuses on determining if PA is also a significant cause of this deficiency in Hainan, China. Researchers gathered data from patients with megaloblastic anemia (a blood disorder) due to lack of vitamin B12, comparing them with healthy individuals to see how common PA is. The findings reveal that a very high percentage of the patients studied have PA, much higher than expected. This suggests that PA is not as rare in this region of China as previously thought. The study also highlights the importance of continuous treatment with vitamin B12 to prevent the recurrence of the anemia. Based on these results, the researchers recommend that all patients with vitamin B12 deficiency should be tested for PA and continuously receive vitamin B12 supplements to maintain their health once diagnosed with PA. This strategic insight is of paramount importance to medical practitioners in China, potentially paving the way for enhanced clinical management protocols for individuals afflicted by this ailment.

Wavelet-based selection-and-recalibration network for Parkinson's disease screening in OCT images.

BACKGROUND AND OBJECTIVE: Parkinson's disease (PD) is one of the most prevalent neurodegenerative brain diseases worldwide. Therefore, accurate PD screening is crucial for early clinical intervention and treatment. Recent clinical research indicates that changes in pathology, such as the texture and thickness of the retinal layers, can serve as biomarkers for clinical PD diagnosis based on optical coherence tomography (OCT) images. However, the pathological manifestations of PD in the retinal layers are subtle compared to the more salient lesions associated with retinal diseases. METHODS: Inspired by textural edge feature extraction in frequency domain learning, we aim to explore a potential approach to enhance the distinction between the feature distributions in retinal layers of PD cases and healthy controls. In this paper, we introduce a simple yet novel wavelet-based selection and recalibration module to effectively enhance the feature representations of the deep neural network by aggregating the unique clinical properties, such as the retinal layers in each frequency band. We combine this module with the residual block to form a deep network named Wavelet-based Selection and Recalibration Network (WaveSRNet) for automatic PD screening. RESULTS: The extensive experiments on a clinical PD-OCT dataset and two publicly available datasets demonstrate that our approach outperforms state-of-the-art methods. Visualization analysis and ablation studies are conducted to enhance the explainability of WaveSRNet in the decision-making process. CONCLUSIONS: Our results suggest the potential role of the retina as an assessment tool for PD. Visual analysis shows that PD-related elements include not only certain retinal layers but also the location of the fovea in OCT images.

Choroidal vascular changes in early-stage myopic maculopathy from deep learning choroidal analysis: a hospital-based SS-OCT study.

BACKGROUND: The objective of this study is to illustrate the changes in the choroidal vasculature in individuals with diffuse chorioretinal atrophy (DCA, early-stage myopic maculopathy) and investigate the association between them. METHODS: This study included 1418 highly myopic eyes from 720 participants aged 18 - 60 years from the Wenzhou High Myopia Cohort Study. These participants underwent comprehensive ophthalmic assessments. Myopic maculopathy classification followed the Meta-PM system, with pathological myopia defined as myopic maculopathy of DCA or severer. Eyes with myopic maculopathy categorized as no macular lesions (C0), tessellated fundus (C1), and DCA (C2) were enrolled in the analysis. Choroidal images were obtained from swept-source optical coherence tomography (SS-OCT), and the images were processed with a deep learning-based automatic segmentation algorithm and the Niblack auto-local threshold algorithm. RESULTS: DCA was detected in 247 eyes (17.4%). In comparison to eyes with C0, those with C2 exhibited significant reductions in choroidal thickness (ChT), luminal area (LA), and stromal area (SA) across all evaluated regions (all P < 0.001). An increase in choroidal vascular index (CVI) was observed in all regions, except for the nasal perifoveal (N2) and inferior perifoveal (I2) regions (all P < 0.01). Multivariable logistic regression analysis revealed a negative association between the presence of DCA and increases in choroidal LA and SA (odds ratio ≤ 0.099, P < 0.001). Multivariable linear regression analysis showed that the mean deviation of the visual field test was positively associated with LA and SA at the vertical meridian (B = 1.512, P < 0.001 for LA; B = 1.956, P < 0.001 for SA). Furthermore, the receiver operating characteristic curve analyses showed the optimal ChT to diagnose pathological myopia was 82.4 µm in the N2 region, the LA was 0.076 mm2 and the SA was 0.049 mm2, with area under the curves of 0.916, 0.908, and 0.895, respectively. CONCLUSIONS: The results of this study indicated that both the presence of DCA and visual function impairment were associated with reductions in choroidal perfusion and stromal components. Moreover, we established threshold values for choroidal parameters in diagnosing pathological myopia, offering valuable references for clinical diagnosis and management.

ScLNet: A cornea with scleral lens OCT layers segmentation dataset and new multi-task model.

Objective: To develop deep learning methods with high accuracy for segmenting irregular corneas and detecting the tear fluid reservoir (TFR) boundary under the scleral lens. Additionally, this study aims to provide a publicly available cornea with scleral lens OCT dataset, including manually labeled layer masks for training and validation of segmentation algorithms. This study introduces ScLNet, a dataset comprising cornea with Scleral Lens (ScL) optical coherence tomography (OCT) images with layer annotations, and a multi-task network designed to achieve rapid, accurate, automated segmentation of scleral lens with regular and irregular corneas. Methods: We created a dataset comprising 31,360 OCT images with scleral lens annotations. The network architecture includes an encoder with multi-scale input and a context coding layer, along with two decoders for specific tasks. The primary task focuses on predicting ScL, TFR, and cornea regions, while the auxiliary task, aimed at predicting the boundaries of ScL, TFR, and cornea, enhances feature extraction for the main task. Segmentation results were compared with state-of-the-art methods and evaluated using Dice similarity coefficient (DSC), intersection over union (IoU), Matthews correlation coefficient (MCC), Precision, and Hausdorff distance (HD). Results: ScLNet achieves 98.22 % DSC, 96.50 % IoU, 98.13 % MCC, 98.35 % Precision, and 3.6840 HD (in pixels) in segmenting ScL; 97.78 % DSC, 95.66 % IoU, 97.71 % MCC, 97.70 % Precision, and 3.7838 HD (in pixels) in segmenting TFR; and 99.22 % DSC, 98.45 % IoU, 99.15 % MCC, 99.14 % Precision, and 3.5355 HD (in pixels) in segmenting cornea. The layer interfaces recognized by ScLNet closely align with expert annotations, as evidenced by high IoU scores. Boundary metrics further confirm its effectiveness. Conclusion: We constructed a dataset of corneal OCT images with ScL wearing, which includes regular and irregular cornea patients. The proposed ScLNet achieves high accuracy in extracting ScL, TFR, and corneal layer masks and boundaries from OCT images of the dataset.

Changes in bulbar conjunctival microcirculation and microvasculature during short-term scleral lens wearing and their associated factors.

OBJECTIVE: To explore the changes in microcirculation and microvasculature of the bulbar conjunctiva during the short-term wearing of the scleral lenses (ScCL). And investigate the factors affecting the microcirculation and microvasculature of the bulbar conjunctiva. METHODS: In this prospective cross-sectional study, functional slit lamp biomicroscopy (FSLB) was used to image the ocular surface microcirculation and microvascular images at two different sites (under the area of ScCL and outside of the area of ScCL) before (baseline) and during the wearing of ScCL at 0 h, 1 h, 2 h and 3 h. Anterior segment optical coherence tomography (AS-OCT) (RTVue, Optovue Inc, USA) was also used to image central post-lens tear film (PoLTF) and the morphology changes of the conjunctiva under the landing zone at the same time period. The semi-automatic quantification of microcirculation and microvasculature including vessel density (Dbox), vessel diameter (D), axial blood flow velocity (Va) and blood flow volume (Q). And the morphological changes of conjunctiva and PoLTF fogging grading were evaluated manually. The changes in the microcirculation and microvasculature of the ocular surface, PoLTF fogging grade and conjunctival morphology were compared before and during the ScCL wearing at different time periods, and the relationship between them was analyzed. RESULTS: Nineteen eyes (11 right eyes, 8 left eyes) were analyzed in this study. Outside of the area of ScCL, the Dbox before wearing lenses was less than that at 0 h (P = 0.041). The Q at baseline was greater than that after 1 h ScCL wearing (P = 0.026). Under the area of the ScCL, the Q at 1 h was less than that at baseline and 3 h. During the ScCL wearing, statistically significant conjunctival morphology changes were found among different time stages (baseline (0 µm), 0 h (113.18 µm), 2 h (138.97 µm), 3 h (143.83 µm) (all P ＜0.05). Outside the area of the ScCL, the morphology changes of the conjunctiva were negatively correlated with the changes of Va (P＜0.001,r = -0.471) and Q (P = 0.003,r = -0.348),but positively correlated with the Dbox (P = 0.001,r = 0.386). Under the area of ScCL, the morphology changes of the conjunctiva were negatively correlated with the Q (P = 0.012, r = -0.291). The fogging grade was positively correlated with the Q under the area of the ScCL (P = 0.005, r = 0.331). CONCLUSIONS: The microcirculation and microvasculature of the ocular surface and conjunctival morphology were changed after wearing ScCL in wearers, which indicated that the microvascular responses happened in the ScCL wearers and the severity of microvascular responses of the ocular surface related to the morphology changes of the conjunctiva. The quantification methods and findings in this study provide clues for the safety of ScCL wearing and may supervise the health of the wearer's ocular surface.

Outer retina and choroid as potential imaging markers for evaluation of neural impairment in early type 2 diabetic patients.

PURPOSE: To quantify the presence of early structural alterations in the outer retinal layer and choroid among healthy subjects and diabetic patients with no or mild diabetic retinopathy, and to establish the correlation between the measured structural parameters and retinal sensitivity. METHODS: In total, 31 eyes from subjects with type 2 diabetes and 29 eyes from healthy subjects were enrolled. Optical coherence tomography was used to measure outer retina layers and choroid, while microperimetry was used to characterize the changes of visual function in a 6-mm diameter area at macula. Quantitative analysis of structural and functional changes was performed between groups and the structure-function correlations were determined. RESULTS: The thickness of myoid and ellipsoid zone, choroid and the mean retinal sensitivity were significantly smaller in diabetic group than that in controls (all P values < 0.05). Besides, thinner choroid and outer retina was associated with the decreased retinal sensitivity，especially in diabetic patients (r = 0.377, P = 0.048; r = 0.401, P = 0.034; respectively). Final multiple regression models showed the outer retinal thickness (ORT) (P = 0.033), choroidal thickness (P = 0.003) and the interaction between ORT and choroidal thickness (P = 0.001) were significant predictors to retinal sensitivity. CONCLUSIONS: Thinning of choroid and outer retina were significantly correlated with reduced retinal sensitivity, which indicate outer retina and choroid might be potential imaging markers for evaluation of visual function related to neural impairment in type 2 diabetic patients without or in the early stage of diabetic retinopathy.

Multi-omics deep learning for radiation pneumonitis prediction in lung cancer patients underwent volumetric modulated arc therapy.

BACKGROUND AND OBJECTIVE: To evaluate the feasibility and accuracy of radiomics, dosiomics, and deep learning (DL) in predicting Radiation Pneumonitis (RP) in lung cancer patients underwent volumetric modulated arc therapy (VMAT) to improve radiotherapy safety and management. METHODS: Total of 318 and 31 lung cancer patients underwent VMAT from First Affiliated Hospital of Wenzhou Medical University (WMU) and Quzhou Affiliated Hospital of WMU were enrolled for training and external validation, respectively. Models based on radiomics (R), dosiomics (D), and combined radiomics and dosiomics features (R+D) were constructed and validated using three machine learning (ML) methods. DL models trained with CT (DLR), dose distribution (DLD), and combined CT and dose distribution (DL(R+D)) images were constructed. DL features were then extracted from the fully connected layers of the best-performing DL model to combine with features of the ML model with the best performance to construct models of R+DLR, D+DLD, R+D+DL(R+D)) for RP prediction. RESULTS: The R+D model achieved a best area under curve (AUC) of 0.84, 0.73, and 0.73 in the internal validation cohorts with Support Vector Machine (SVM), XGBoost, and Logistic Regression (LR), respectively. The DL(R+D) model achieved a best AUC of 0.89 and 0.86 using ResNet-34 in training and internal validation cohorts, respectively. The R+D+DL(R+D) model achieved a best performance in the external validation cohorts with an AUC, accuracy, sensitivity, and specificity of 0.81(0.62-0.99), 0.81, 0.84, and 0.67, respectively. CONCLUSIONS: The integration of radiomics, dosiomics, and DL features is feasible and accurate for the RP prediction to improve the management of lung cancer patients underwent VMAT.

Spatial mapping of corneal biomechanical properties using wave-based optical coherence elastography.

Quantifying the mechanical properties of the cornea can provide valuable insights into the occurrence and progression of keratoconus, as well as the effectiveness of corneal crosslinking surgery. This study presents a non-contact and non-invasive wave-based optical coherence elastography system that utilizes air-pulse stimulation to create a two-dimensional map of corneal elasticity. Homogeneous and dual concentration phantoms were measured with the sampling of 25 × 25 points over a 6.6 × 6.6 mm2 area, to verify the measurement capability for elastic mapping and the spatial resolution (0.91 mm). The velocity of elastic waves distribution of porcine corneas before and after corneal crosslinking surgery were further mapped, showing a significant change in biomechanics in crosslinked region. This system features non-invasiveness and high resolution, holding great potential for application in ophthalmic clinics.

The outcome and the risk factors of mucormycosis among patients with hematological diseases: a systematic and meta-analysis.

Objectives: Mucorale has come into a significant pathogen over recent decades. Nonetheless, mucormycosis-related mortality rates among patients with hematological disorders remain unascertained. Thus, we conducted a meta-analysis to determine mortality rates of mucormycosis in patients with hematology-related conditions. Methods: We scoured PubMed, Embase, and Web of Science for original papers exploring the intersection of Mucormycosis and Hematological Diseases (from 2000 to 2022). We scrutinized the overall mortality across three distinct periods, as well as differentiating between high-income and middle-income nations. We further evaluated the pooled mortality and the risk differential (RD) across several subgroups. Results: The overall mortality rate for hematology patients with mucormycosis was 61%, within a 95% confidence interval (CI) of 0.54-0.68. A significant observation was that mortality rates were somewhat lower in high-income countries compared to middle-income countries (0.60 versus 0.64, p = 0.45). Importantly, we discovered that a combination of surgical and medical treatment significantly improved survival rates compared to medical treatment alone [mortality 0.49 versus 0.67, RD -0.19 (95%CI -0.38-0.00, I2 63.7%)]. As might be expected, disseminated mucormycosis posed a significantly higher risk of death compared to isolated mucormycosis [0.60 versus 0.57, RD death 0.16 (95%CI 0.03-0.28)]. Additionally, our analysis showed no discernible differences in survival rates between genders, between patients with and without breakthrough infection, between those who received mucor-active or mucor-inactive drugs prior to mucor infection, or between those on a multi-drug regimen and those on a single drug treatment. Conclusion: Despite the high mortality rates associated with mucormycosis in patients with hematological disorders, those receiving both medical and surgical interventions, as well as those with isolated infection sites, exhibited improved survival outcomes. Conversely, factors such as gender, the presence of breakthrough infection, the use of mucor-active drugs before mucor infection, and multi-drug administration did not significantly influence patient outcomes.

Causal relationships between type 2 diabetes, glycemic traits and keratoconus.

Purpose: The relationship between diabetes mellitus and keratoconus remains controversial. This study aimed to assess the potential causal relationships among type 2 diabetes, glycemic traits, and the risk of keratoconus. Methods: We used a two-sample Mendelian randomization (MR) design based on genome-wide association summary statistics. Fasting glucose, proinsulin levels, adiponectin, hemoglobin A1c (HbA1c) and type 2 diabetes with and without body mass index (BMI) adjustment were used as exposures and keratoconus was used as the outcome. MR analysis was performed using the inverse-variance weighted method, MR-Egger regression method, weighted-mode method, weighted median method and the MR-pleiotropy residual sum and outlier test (PRESSO). Results: Results showed that genetically predicted lower fasting glucose were significantly associated with a higher risk of keratoconus [IVW: odds ratio (OR) = 0.382; 95% confidence interval (CI) = 0.261-0.560; p = 8.162 × 10-7]. Genetically predicted lower proinsulin levels were potentially linked to a higher risk of keratoconus (IVW: OR = 0.739; 95% CI = 0.568-0.963; p = 0.025). In addition, genetically predicted type 2 diabetes negatively correlated with keratoconus (IVW: BMI-unadjusted: OR = 0.869; 95% CI = 0.775-0.974, p = 0.016; BMI-adjusted: OR = 0.880, 95% CI = 0.789-0.982, p = 0.022). These associations were further corroborated by the evidence from all sensitivity analyses. Conclusion: These findings provide genetic evidence that higher fasting glucose levels are associated with a lower risk of keratoconus. However, further studies are required to confirmed this hypothesis and to understand the mechanisms underlying this putative causative relationship.

Characteristics of the Peripapillary Structure and Vasculature in Patients With Myopic Anisometropia.

Purpose: To evaluate the interocular differences of the peripapillary structural and vascular parameters and that of association with axial length (AL) in participants with myopic anisometropia using swept-source optical coherence tomography. Methods: This prospective cross-sectional study included 90 eyes of 45 participants. Each participant's eyes were divided into the more and less myopic eye respectively according to spherical equivalent. The ß- and γ-parapapillary atrophy (PPA) areas, Bruch's membrane opening distance, border length, and border tissue angle were measured manually. Peripapillary choroidal vascularity index and choroidal thickness (CT) values in superior, nasal, inferior, and temporal were calculated using a custom-built algorithm based on MATLAB. Results: The interocular difference in AL and spherical equivalent was 0.62 ± 0.26 mm and -1.50 (-2.13, -1.25) diopters (D), respectively. The interocular difference in spherical equivalent was highly correlated with that of the AL. The ß- and γ-PPA areas were significantly greater in more myopic eyes. The mean and inferior peripapillary choroidal vascularity index and all regions of peripapillary CT were significantly lower in the more myopic eyes. The interocular difference in AL was significantly positively correlated with the interocular differences in γ-PPA area and border length and negatively correlated with the interocular differences in temporal choroidal vascularity index and mean, inferior, and temporal peripapillary CT. There was an independent correlation between the interocular differences in AL and the interocular differences in γ-PPA area, inferior, and temporal peripapillary CT. Conclusions: Significant differences between both groups were detected in most peripapillary parameters, especially in peripapillary CT. The γ-PPA area, border length, and peripapillary CT were significantly correlated with the elongation of AL. Translational Relevance: The current study characterized and analyzed the peripapillary parameters in myopic anisometropia, which helped to monitor myopic progression.

Using a dual-stream attention neural network to characterize mild cognitive impairment based on retinal images.

Mild cognitive impairment (MCI) is a critical transitional stage between normal cognition and dementia, for which early detection is crucial for timely intervention. Retinal imaging has been shown as a promising potential biomarker for MCI. This study aimed to develop a dual-stream attention neural network to classify individuals with MCI based on multi-modal retinal images. Our approach incorporated a cross-modality fusion technique, a variable scale dense residual model, and a multi-classifier mechanism within the dual-stream network. The model utilized a residual module to extract image features and employed a multi-level feature aggregation method to capture complex context information. Self-attention and cross-attention modules were utilized at each convolutional layer to fuse features from optical coherence tomography (OCT) and fundus modalities, resulting in multiple output losses. The neural network was applied to classify individuals with MCI, Alzheimer's disease, and control participants with normal cognition. Through fine-tuning the pre-trained model, we classified community-dwelling participants into two groups based on cognitive impairment test scores. To identify retinal imaging biomarkers associated with accurate prediction, we used the Gradient-weighted Class Activation Mapping technique. The proposed method achieved high precision rates of 84.96% and 80.90% in classifying MCI and positive test scores for cognitive impairment, respectively. Notably, changes in the optic nerve head on fundus photographs or OCT images among patients with MCI were not used to discriminate patients from the control group. These findings demonstrate the potential of our approach in identifying individuals with MCI and emphasize the significance of retinal imaging for early detection of cognitive impairment.

The novel HLA-B*27:267 allele, identified by Sanger dideoxy nucleotide sequencing in a Chinese individual.

HLA-B*27:267 differs from HLA-B*27:04:01 by one nucleotide in exon 2.

A case report of T-LGL leukemia-associated pure red cell aplasia harboring STAT3, TNFAIP3, and KMT2D mutation.

Background: T-large granular lymphocyte (T-LGL) leukemia is a rare clonal lymphoproliferative disorder, which has a favorable prognosis. There are different complications between Asian and Western patients diagnosed with LGL leukemia. In Asians, pure red cell aplasia (PRCA) is the most common hematological compatible clinical feature of LGL leukemia, whereas in Western patients, rheumatoid arthritis and neutropenia are more commonly seen. Herein, a rare case of T-LGL leukemia associated PRCA was reported. Case Description: A 72-year-old man, presenting with anemia and leukopenia, was admitted to hospital. The bone marrow (BM) smear revealed that erythroid series were suppressed with only 4%, mature lymphocytes constituting up to 23% of the marrow cells. The results of T-cell receptor (TCR) arrangement revealed mutations in the TCR-ß and TCR-γ genes. Further, STAT3 mutation (p. [D661Y; N664T] and p.N647I), TNFAIP3 mutation (p.L48fs), and KMT2D mutation (p.E5291K) were confirmed. The patient was diagnosed with CD8+ TCRαß T-LGL leukemia-associated PRCA, harboring STAT3, TNFAIP3 and KMT2D mutation. The BM smear, immunophenotype, gene rearrangement and karyotype were consistent with those of the first diagnosis. Cyclosporine A (CyA) based regimens were effective, even in a cessation of discontinued treatment. The patient refused BM-related examinations and has remained in hematological complete remission (CR) until the time of writing (at least 3 years). Conclusions: The administration of CyA yielded a CR in this case. However, the standard therapy for T-LGL leukemia-associated PRCA is not clear, and more prospective studies are needed to ascertain the underlying mechanism of pathogenesis.

Deep learning segmentation of the tear fluid reservoir under the sclera lens in optical coherence tomography images.

The tear fluid reservoir (TFR) under the sclera lens is a unique characteristic providing optical neutralization of any aberrations from corneal irregularities. Anterior segment optical coherence tomography (AS-OCT) has become an important imaging modality for sclera lens fitting and visual rehabilitation therapy in both optometry and ophthalmology. Herein, we aimed to investigate whether deep learning can be used to segment the TFR from healthy and keratoconus eyes, with irregular corneal surfaces, in OCT images. Using AS-OCT, a dataset of 31850 images from 52 healthy and 46 keratoconus eyes, during sclera lens wear, was obtained and labeled with our previously developed algorithm of semi-automatic segmentation. A custom-improved U-shape network architecture with a full-range multi-scale feature-enhanced module (FMFE-Unet) was designed and trained. A hybrid loss function was designed to focus training on the TFR, to tackle the class imbalance problem. The experiments on our database showed an IoU, precision, specificity, and recall of 0.9426, 0.9678, 0.9965, and 0.9731, respectively. Furthermore, FMFE-Unet was found to outperform the other two state-of-the-art methods and ablation models, suggesting its strength in segmenting the TFR under the sclera lens depicted on OCT images. The application of deep learning for TFR segmentation in OCT images provides a powerful tool to assess changes in the dynamic tear film under the sclera lens, improving the efficiency and accuracy of lens fitting, and thus supporting the promotion of sclera lenses in clinical practice.

Srgap2 suppression ameliorates retinal ganglion cell degeneration in mice.

Slit-Robo GTPase-activating protein 2 (SRGAP2) plays important roles in axon guidance, neuronal migration, synapse formation, and nerve regeneration. However, the role of SRGAP2 in neuroretinal degenerative disease remains unclear. In this study, we found that SRGAP2 protein was first expressed in the retina of normal mice at the embryonic stage and was mainly located in the mature retinal ganglion cell layer and the inner nuclear layer. SRGAP2 protein in the retina and optic nerve increased after optic nerve crush. Then, we established a heterozygous knockout (Srgap2+/-) mouse model of optic nerve crush and found that Srgap2 suppression increased retinal ganglion cell survival, lowered intraocular pressure, inhibited glial cell activation, and partially restored retinal function. In vitro experiments showed that Srgap2 suppression activated the mammalian target of rapamycin signaling pathway. RNA sequencing results showed that the expression of small heat shock protein genes (Cryaa, Cryba4, and Crygs) related to optic nerve injury were upregulated in the retina of Srgap2+/- mice. These results suggest that Srgap2 suppression reduced the robust activation of glial cells, activated the mammalian target of rapamycin signaling pathway related to nerve protein, increased the expression of small heat shock protein genes, inhibited the degeneration of retinal ganglion cells, and partially restored optic nerve function.

CMS-NET: deep learning algorithm to segment and quantify the ciliary muscle in swept-source optical coherence tomography images.

Background: The ciliary muscle plays a role in changing the shape of the crystalline lens to maintain the clear retinal image during near work. Studying the dynamic changes of the ciliary muscle during accommodation is necessary for understanding the mechanism of presbyopia. Optical coherence tomography (OCT) has been frequently used to image the ciliary muscle and its changes during accommodation in vivo. However, the segmentation process is cumbersome and time-consuming due to the large image data sets and the impact of low imaging quality. Objectives: This study aimed to establish a fully automatic method for segmenting and quantifying the ciliary muscle on the basis of optical coherence tomography (OCT) images. Design: A perspective cross-sectional study. Methods: In this study, 3500 signed images were used to develop a deep learning system. A novel deep learning algorithm was created from the widely used U-net and a full-resolution residual network to realize automatic segmentation and quantification of the ciliary muscle. Finally, the algorithm-predicted results and manual annotation were compared. Results: For segmentation performed by the system, the total mean pixel value difference (PVD) was 1.12, and the Dice coefficient, intersection over union (IoU), and sensitivity values were 93.8%, 88.7%, and 93.9%, respectively. The performance of the system was comparable with that of experienced specialists. The system could also successfully segment ciliary muscle images and quantify ciliary muscle thickness changes during accommodation. Conclusion: We developed an automatic segmentation framework for the ciliary muscle that can be used to analyze the morphological parameters of the ciliary muscle and its dynamic changes during accommodation.

Short-term postoperative changes in the choroidal vascularity index in patients with a unilateral epiretinal membrane.

BACKGROUND: To investigate short-term choroidal structural and vascular changes after epiretinal membrane (ERM) surgery. METHODS: In this retrospective study, 65 patients with unilateral ERM underwent pars plana vitrectomy combined with cataract surgery and were examined one day before surgery and one week, one month, and three months after surgery. Choroidal thickness (CT) and choroidal vascular index (CVI) were evaluated using horizontal enhanced depth imaging optical coherence tomography (EDI-OCT) scans and were further calculated using semi-automatic algorithms using MATLAB R2017a. RESULTS: Preoperatively, CVI was higher in eyes with ERM (61.70 ± 5.17%) than in fellow eyes (59.99 ± 5.26%). CVI increased significantly at one week after surgery (62.14 ± 5.02%) and decreased at 1 and 3 months after surgery (60.76 ± 4.97% and 60.4 ± 4.83%, respectively). The change was pronounced in the nasal region (p < 0.001) and central region (p < 0.05). CT in the temporal macula increased at 1 week (239.65 ± 72.98 µm) after surgery and decreased at 1 and 3 months after surgery (222.15 ± 71.91 µm and 222.33 ± 65.72 µm, respectively; p < 0.01). CONCLUSIONS: Short-term postoperative variations in the choroid have been demonstrated in eyes with ERM. This may be related to the release of macular traction. CVI assessment using EDI-OCT may be a useful tool for investigating choroidal structural changes accompanying ERM and postoperative period.

Acute hyperglycemia compromises the responses of choroidal vessels using swept-source optical coherence tomography during dark and light adaptations.

Purpose: To clarify the effects of acute hyperglycemia on the responses of choroidal structural components and vascularity index during light modulation in healthy participants using techniques including image binarization and artificial intelligence (AI) segmentation based on swept-source optical coherence tomography (SS-OCT). Methods: Twenty-four eyes of 24 healthy participants were imaged at different stages after ambient light, 40 min of dark adaptation, and 5 min of light adaptation in two imaging sessions: control and after receiving 75 g of oral glucose solution. The choroidal structural parameters, including luminal volume (LV), stromal volume (SV), total choroidal volume (TCV), and choroidal vascularity index (CVI) within a 6 mm area were determined using a custom algorithm based on image binarization and AI segmentation of SS-OCT. These measurements were compared among the conditions after adjusting for axial length, age to identify the differences. Results: In the dark, CVI decreased (-0.36 ± 0.09%) significantly in acute hyperglycemia compared to the control condition. During the transition to ambient light, there was an increasing trend in the choroidal parameters compared with the control experiment. However, only TCV (0.38 ± 0.17 mm3) and LV (0.27 ± 0.10 mm3) showed a significant increase at the time point of 5 min after ambient light. Conclusion: Analysis of choroidal structural parameters and CVI based on SS-OCT images is a potentially powerful method to objectively reflect subtle changes in neurovascular coupling between the choroid and photoreceptor during dark adaptation.

Mucor indicus caused disseminated infection diagnosed by metagenomic next-generation sequencing in an acute myeloid leukemia patient: A case report.

Background: Mucormycosis commonly occurs in immunosuppressed patients with hematological diseases, which can be life-threatening. However, many cases are often misdiagnosed due to lack of specific clinical manifestations. Additionally, the traditional blood culture or serological testing, with a high false-negative rate, is time-consuming. Thus, precise and timely diagnosis of infections is essential for the clinical care of infected patients. Case presentation: We report a 29-year-old Chinese man with acute myeloid leukemia (AML) who developed febrile neutropenia after the first course of induction chemotherapy. He received empirical antibiotics, which did not relieve his symptoms. No pathogen was detected by traditional microbiologic assays, while Mucor indicus was identified by metagenomic next-generation sequencing (mNGS) in the blood specimen. Liposomal amphotericin B (LAmB) was used, resulting in the patient's temperature returning to normal. A few days later, abdominal computed tomography (CT) scan showed multiple liver abscesses; fluorescence staining, histopathology, and mNGS identified the causative agent-M. indicus. Posaconazole was combined with LAmB as long-term antifungal treatment. Finally, the patient received allogeneic hematopoietic stem cell transplantation successfully after controlled infection. During follow-up 1 year after transplantation, the number of liver abscesses was reduced to one and remained stable. Conclusion: This report described the first case of an AML patient diagnosed with culture-negative disseminated infections caused by M. indicus leading to rare hepatic manifestations using mNGS of peripheral blood and liver biopsy. LAmB combined with posaconazole was given in time, resulting in a favorable outcome. mNGS is a new method that assists in detecting the probable pathogen and increases the accuracy of identifying an etiology.