NADPH composite index analysis quantifies the relationship between compartmentalized NADPH dynamics and growth rates in cancer cells.

NADPH, a highly compartmentalized electron donor in mammalian cells, plays essential roles in cell metabolism. However, little is known about how cytosolic and mitochondrial NADPH dynamics relate to cancer cell growth rates in response to varying nutrient conditions. To address this issue, we present NADPH composite index analysis, which quantifies the relationship between compartmentalized NADPH dynamics and growth rates using genetically encoded NADPH sensors, automated image analysis pipeline, and correlation analysis. Through this analysis, we demonstrated that compartmentalized NADPH dynamics patterns were cancer cell-type dependent. Specifically, cytosolic and mitochondrial NADPH dynamics of MDA-MB-231 decreased in response to serine deprivation, while those of HCT-116 increased in response to serine or glutamine deprivation. Furthermore, by introducing a fractional contribution parameter, we correlated cytosolic and mitochondrial NADPH dynamics to growth rates. Using this parameter, we identified cancer cell lines whose growth rates were selectively inhibited by targeting cytosolic or mitochondrial NADPH metabolism. Mechanistically, we identified citrate transporter as a key mitochondrial transporter that maintains compartmentalized NADPH dynamics and growth rates. Altogether, our results present a significant advance in quantifying the relationship between compartmentalized NADPH dynamics and cancer cell growth rates, highlighting a potential of targeting compartmentalized NADPH metabolism for selective cancer cell growth inhibitions.

Route planning of mobile robot based on improved RRT star and TEB algorithm.

This paper presents a fusion algorithm based on the enhanced RRT* TEB algorithm. The enhanced RRT* algorithm is utilized for generating an optimal global path. Firstly, proposing an adaptive sampling function and extending node bias to accelerate global path generation and mitigate local optimality. Secondly, eliminating path redundancy to minimize path length. Thirdly, imposing constraints on the turning angle of the path to enhance path smoothness. Conducting kinematic modeling of the mobile robot and optimizing the TEB algorithm to align the trajectory with the mobile robot's kinematics. The integration of these two algorithms culminates in the development of a fusion algorithm. Simulation and experimental results demonstrate that, in contrast to the traditional RRT* algorithm, the enhanced RRT* algorithm achieves a 5.8% reduction in path length and a 62.5% decrease in the number of turning points. Utilizing the fusion algorithm for path planning, the mobile robot generates a superior, seamlessly smooth global path, adept at circumventing obstacles. Furthermore, the local trajectory meticulously conforms to the kinematic constraints of the mobile robot.

Cystatin C Attenuates Perihematomal Secondary Brain Injury by Inhibiting the Cathepsin B/NLRP3 Signaling Pathway in a Rat Model of Intracerebral Hemorrhage.

Secondary brain injury (SBI) is a noticeable contributor to the high mortality and morbidity rates associated with intracerebral hemorrhage (ICH), and effective treatment options remain limited. Cystatin C (CysC) emerges as a novel candidate for SBI intervention. The therapeutic effects and underlying mechanisms of CysC in mitigating SBI following ICH were explored in the current research. An in vivo ICH rat model was established by injecting autologous blood into the right caudate nucleus. Western blotting (WB) was utilized to assess the levels of CysC, cathepsin B (CTSB), and the NLRP3 inflammasome. Subsequently, the ICH rat model was treated with exogenous CysC supplementation or CysC knockdown plasmids. Various parameters, including Evans blue (EB) extravasation, brain water content, and neurological function in rats, were examined. RT-qPCR and WB were employed to determine the expression levels of CTSB and the NLRP3 inflammasome. The co-expression of CTSB, CysC, and NLRP3 inflammasome with GFAP, NeuN, and Iba1 was assessed through double-labeled immunofluorescence. The interaction between CysC and CTSB was investigated using double-labeled immunofluorescence and co-immunoprecipitation. The findings revealed an elevation of CysC expression level, particularly at 24 h after ICH. Exogenous CysC supplementation alleviated severe brain edema, neurological deficit scores, and EB extravasation induced by ICH. Conversely, CysC knockdown produced opposite effects. The expression levels of CTSB and the NLRP3 inflammasome were significantly risen following ICH, and exogenous CysC supplement attenuated their expression levels. Double-labeled immunofluorescence illustrated that CysC, CTSB, and the NLRP3 inflammasome were predominantly expressed in microglial cells, and the interaction between CysC and CTSB was evidenced. CysC exhibited potential in ameliorating SBI following ICH via effectively suppressing the activation of the NLRP3 inflammasome mediated by CTSB specifically in microglial cells. These findings underscore the prospective therapeutic efficacy of CysC in the treatment of ICH-induced complications.

A self-amplifying loop of TP53INP1 and P53 drives oxidative stress-induced apoptosis of bone marrow mesenchymal stem cells.

Bone marrow mesenchymal stem cell (BMSC) transplantation is a promising regenerative therapy; however, the survival rate of BMSCs after transplantation is low. Oxidative stress is one of the main reasons for the high apoptosis rate of BMSCs after transplantation, so there is an urgent need to explore the mechanism of oxidative stress-induced apoptosis of BMSCs. Our previous transcriptome sequencing results suggested that the expression of P53-induced nuclear protein 1 (TP53INP1) and the tumor suppressor P53 (P53) was significantly upregulated during the process of oxidative stress-induced apoptosis of BMSCs. The present study further revealed the role and mechanism of TP53INP1 and P53 in oxidative stress-induced apoptosis in BMSCs. Overexpression of TP53INP1 induced apoptosis of BMSCs, knockdown of TP53INP1 alleviated oxidative stress apoptosis of BMSCs. Under oxidative stress conditions, P53 is regulated by TP53INP1, while P53 can positively regulate the expression of TP53INP1, so the two form a positive feedback loop. To clarify the mechanism of feedback loop formation. We found that TP53INP1 inhibited the ubiquitination and degradation of P53 by increasing the phosphorylation level of P53, leading to the accumulation of P53 protein. P53 can act on the promoter of the TP53INP1 gene and increase the expression of TP53INP1 through transcriptional activation. This is the first report on a positive feedback loop formed by TP53INP1 and P53 under oxidative stress. The present study clarified the formation mechanism of the positive feedback loop. The TP53INP1-P53 positive feedback loop may serve as a potential target for inhibiting oxidative stress-induced apoptosis in BMSCs.

APOE4/4 is linked to damaging lipid droplets in Alzheimer's disease microglia.

Several genetic risk factors for Alzheimer's disease implicate genes involved in lipid metabolism and many of these lipid genes are highly expressed in glial cells1. However, the relationship between lipid metabolism in glia and Alzheimer's disease pathology remains poorly understood. Through single-nucleus RNA sequencing of brain tissue in Alzheimer's disease, we have identified a microglial state defined by the expression of the lipid droplet-associated enzyme ACSL1 with ACSL1-positive microglia being most abundant in patients with Alzheimer's disease having the APOE4/4 genotype. In human induced pluripotent stem cell-derived microglia, fibrillar Aß induces ACSL1 expression, triglyceride synthesis and lipid droplet accumulation in an APOE-dependent manner. Additionally, conditioned media from lipid droplet-containing microglia lead to Tau phosphorylation and neurotoxicity in an APOE-dependent manner. Our findings suggest a link between genetic risk factors for Alzheimer's disease with microglial lipid droplet accumulation and neurotoxic microglia-derived factors, potentially providing therapeutic strategies for Alzheimer's disease.

Glycerophosphodiesters inhibit lysosomal phospholipid catabolism in Batten disease.

Batten disease, the most prevalent form of neurodegeneration in children, is caused by mutations in the CLN3 gene, which encodes a lysosomal transmembrane protein. CLN3 loss leads to significant accumulation of glycerophosphodiesters (GPDs), the end products of glycerophospholipid catabolism in the lysosome. Despite GPD storage being robustly observed upon CLN3 loss, the role of GPDs in neuropathology remains unclear. Here, we demonstrate that GPDs act as potent inhibitors of glycerophospholipid catabolism in the lysosome using human cell lines and mouse models. Mechanistically, GPDs bind and competitively inhibit the lysosomal phospholipases PLA2G15 and PLBD2, which we establish to possess phospholipase B activity. GPDs effectively inhibit the rate-limiting lysophospholipase activity of these phospholipases. Consistently, lysosomes of CLN3-deficient cells and tissues accumulate toxic lysophospholipids. Our work establishes that the storage material in Batten disease directly disrupts lysosomal lipid homeostasis, suggesting GPD clearance as a potential therapeutic approach to this fatal disease.

High-accuracy 3D segmentation of wet age-related macular degeneration via multi-scale and cross-channel feature extraction and channel attention.

Wet age-related macular degeneration (AMD) is the leading cause of visual impairment and vision loss in the elderly, and optical coherence tomography (OCT) enables revolving biotissue three-dimensional micro-structure widely used to diagnose and monitor wet AMD lesions. Many wet AMD segmentation methods based on deep learning have achieved good results, but these segmentation results are two-dimensional, and cannot take full advantage of OCT's three-dimensional (3D) imaging characteristics. Here we propose a novel deep-learning network characterizing multi-scale and cross-channel feature extraction and channel attention to obtain high-accuracy 3D segmentation results of wet AMD lesions and show the 3D specific morphology, a task unattainable with traditional two-dimensional segmentation. This probably helps to understand the ophthalmologic disease and provides great convenience for the clinical diagnosis and treatment of wet AMD.

Association of NLRPs with pathogenesis of dry age-related macular degeneration.

BACKGROUND: Age-related macular degeneration (AMD) is the leading cause of blindness in the elderly population, and Dry AMD is the most common clinical subtype. However, effective measures for the early diagnosis and treatment of dry AMD have not been proposed. In recent years, NOD-like receptors (NLRs) have received attention in the study of AMD as an important class of pattern recognition receptors. We attempted to elucidate the pathogenesis of NLRs in dry AMD from the perspective of chronic inflammation. METHODS: This study involved 13 patients with dry AMD, 10 age- and sex-matched normal population without any history of disease and 8 patients with wet AMD as controls. Using RT-qPCR, the mRNA expression levels of NLRs in peripheral blood peripheral blood mononuclear cells (PBMCs) were compared to analyze the statistical differences in the expression contents among the three populations. RESULTS: The relative RNA expression of nucleotide-binding oligomerization-like receptor protein 12 (NLRP12) with negative regulation of inflammation was significantly lower in dry AMD patients than in normal people and wet AMD patients. And NLRX1, which also has an anti-inflammatory effect, was lower in dry AMD patients than in wet AMD patients. However, NLRP3 with proinflammatory effect was significantly expressed in wet AMD. CONCLUSION: The significant decrease in NLRP12 in dry AMD may become a breakthrough in the study of dry AMD and systemic chronic inflammatory response. However, NLRP3 may have a more important role in wet AMD.

Stable Isotope-Assisted Untargeted Metabolomics Identifies ALDH1A1-Driven Erythronate Accumulation in Lung Cancer Cells.

Using an untargeted stable isotope-assisted metabolomics approach, we identify erythronate as a metabolite that accumulates in several human cancer cell lines. Erythronate has been reported to be a detoxification product derived from off-target glycolytic metabolism. We use chemical inhibitors and genetic silencing to define the pentose phosphate pathway intermediate erythrose 4-phosphate (E4P) as the starting substrate for erythronate production. However, following enzyme assay-coupled protein fractionation and subsequent proteomics analysis, we identify aldehyde dehydrogenase 1A1 (ALDH1A1) as the predominant contributor to erythrose oxidation to erythronate in cell extracts. Through modulating ALDH1A1 expression in cancer cell lines, we provide additional support. We hence describe a possible alternative route to erythronate production involving the dephosphorylation of E4P to form erythrose, followed by its oxidation by ALDH1A1. Finally, we measure increased erythronate concentrations in tumors relative to adjacent normal tissues from lung cancer patients. These findings suggest the accumulation of erythronate to be an example of metabolic reprogramming in cancer cells, raising the possibility that elevated levels of erythronate may serve as a biomarker of certain types of cancer.

Single-nucleus transcriptomes reveal spatiotemporal symbiotic perception and early response in Medicago.

Establishing legume-rhizobial symbiosis requires precise coordination of complex responses in a time- and cell type-specific manner. Encountering Rhizobium, rapid changes of gene expression levels in host plants occur in the first few hours, which prepare the plants to turn off defence and form a symbiotic relationship with the microbes. Here, we applied single-nucleus RNA sequencing to characterize the roots of Medicago truncatula at 30 min, 6 h and 24 h after nod factor treatment. We found drastic global gene expression reprogramming at 30 min in the epidermis and cortex and most of these changes were restored at 6 h. Moreover, plant defence response genes are activated at 30 min and subsequently suppressed at 6 h in non-meristem cells. Only in the cortical cells but not in other cell types, we found the flavonoid synthase genes required to recruit rhizobia are highly expressed 30 min after inoculation with nod factors. A gene module enriched for symbiotic nitrogen fixation genes showed that MtFER (MtFERONIA) and LYK3 (LysM domain receptor-like kinase 3) share similar responses to symbiotic signals. We further found that MtFER can be phosphorylated by LYK3 and it participates in rhizobial symbiosis. Our results expand our understanding of dynamic spatiotemporal symbiotic responses at the single-cell level.

The Batten disease gene product CLN5 is the lysosomal bis(monoacylglycero)phosphate synthase.

Lysosomes critically rely on bis(monoacylglycero)phosphate (BMP) to stimulate lipid catabolism, cholesterol homeostasis, and lysosomal function. Alterations in BMP levels in monogenic and complex neurodegeneration suggest an essential function in human health. However, the site and mechanism responsible for BMP synthesis have been subject to debate for decades. Here, we report that the Batten disease gene product CLN5 is the elusive BMP synthase (BMPS). BMPS-deficient cells exhibited a massive accumulation of the BMP synthesis precursor lysophosphatidylglycerol (LPG), depletion of BMP species, and dysfunctional lipid metabolism. Mechanistically, we found that BMPS mediated synthesis through an energy-independent base exchange reaction between two LPG molecules with increased activity on BMP-laden vesicles. Our study elucidates BMP biosynthesis and reveals an anabolic function of late endosomes/lysosomes.

Development and validation of a contrast-enhanced CT-based radiomics nomogram for differentiating mass-like thymic hyperplasia and low-risk thymoma.

PURPOSE: To explore the efficiency of a contrast-enhanced CT-based radiomics nomogram integrated with radiomics signature and clinically independent predictors to distinguish mass-like thymic hyperplasia (ml-TH) from low-risk thymoma (LRT) preoperatively. METHODS: 135 Patients with histopathology confirmed ml-TH (n = 65) and LRT (n = 70) were randomly divided into training set (n = 94) and validation set (n = 41) at a ratio of 7:3. The least absolute shrinkage and selection operator (LASSO) algorithm was used to obtain the optimal features. Based on the selected features, four machine learning models, support vector machine (SVM), logistic regression (LR), extreme gradient boosting (XGBOOST), and random forest (RF) were constructed. Multivariate logistic regression was used to establish a radiomics nomogram containing clinically independent predictors and radiomics signature. Receiver operating characteristic (ROC), DeLong test, and calibration curves were used to detect the performance of the radiomics nomogram in training set and validation set. RESULTS: In the validation set, the area under the curve (AUC) value of LR (0.857; 95% CI: 0.741, 0.973) was the highest of the four machine learning models. Radiomics nomogram containing radiomics signature and clinically independent predictors (including age, shape, and net enhancement degree) had better calibration and identification in the training set (AUC: 0.959; 95% CI: 0.922, 0.996) and validation set (AUC: 0.895; 95% CI: 0.795, 0.996). CONCLUSION: We constructed a contrast-enhanced CT-based radiomics nomogram containing clinically independent predictors and radiomics signature as a noninvasive preoperative prediction method to distinguish ml-TH from LRT. The radiomics nomogram we constructed has potential for preoperative clinical decision making.

APOE4/4 is linked to damaging lipid droplets in Alzheimer's microglia.

Several genetic risk factors for Alzheimer's Disease (AD) implicate genes involved in lipid metabolism and many of these lipid genes are highly expressed in glial cells. However, the relationship between lipid metabolism in glia and AD pathology remains poorly understood. Through single-nucleus RNA-sequencing of AD brain tissue, we have identified a microglial state defined by the expression of the lipid droplet (LD) associated enzyme ACSL1 with ACSL1-positive microglia most abundant in AD patients with the APOE4/4 genotype. In human iPSC-derived microglia (iMG) fibrillar Aß (fAß) induces ACSL1 expression, triglyceride synthesis, and LD accumulation in an APOE-dependent manner. Additionally, conditioned media from LD-containing microglia leads to Tau phosphorylation and neurotoxicity in an APOE-dependent manner. Our findings suggest a link between genetic risk factors for AD with microglial LD accumulation and neurotoxic microglial-derived factors, potentially providing novel therapeutic strategies for AD.

Drug screening in human physiologic medium identifies uric acid as an inhibitor of rigosertib efficacy.

The non-physiological nutrient levels found in traditional culture media have been shown to affect numerous aspects of cancer cell physiology, including how cells respond to certain therapeutic agents. Here, we comprehensively evaluated how physiological nutrient levels impact therapeutic response by performing drug screening in human plasma-like medium (HPLM). We observed dramatic nutrient-dependent changes in sensitivity to a variety of FDA-approved and clinically trialed compounds, including rigosertib, an experimental cancer therapeutic that has recently failed in phase 3 clinical trials. Mechanistically, we found that the ability of rigosertib to destabilize microtubules is strongly inhibited by the purine metabolism waste product uric acid, which is uniquely abundant in humans relative to traditional in vitro and in vivo cancer models. Structural modelling studies suggest that uric acid interacts with the tubulin-rigosertib complex and may act as an uncompetitive inhibitor of rigosertib. These results offer a possible explanation for the failure of rigosertib in clinical trials and demonstrate the utility of physiological media to achieve in vitro results that better represent human therapeutic responses.

Value of the application of computed tomography-based radiomics for preoperative prediction of unfavorable pathology in initial bladder cancer.

OBJECTIVES: To construct and validate unfavorable pathology (UFP) prediction models for patients with the first diagnosis of bladder cancer (initial BLCA) and to compare the comprehensive predictive performance of these models. MATERIALS AND METHODS: A total of 105 patients with initial BLCA were included and randomly enrolled into the training and testing cohorts in a 7:3 ratio. The clinical model was constructed using independent UFP-risk factors determined by multivariate logistic regression (LR) analysis in the training cohort. Radiomics features were extracted from manually segmented regions of interest in computed tomography (CT) images. The optimal CT-based radiomics features to predict UFP were determined by the optimal feature filter and the least absolute shrinkage and selection operator algorithm. The radiomics model consist with the optimal features was constructed by the best of the six machine learning filters. The clinic-radiomics model combined the clinical and radiomics models via LR. The area under the curve (AUC), accuracy, sensitivity, specificity, positive and negative predictive value, calibration curve and decision curve analysis were used to evaluate the predictive performance of the models. RESULTS: Patients in the UFP group had a significantly older age (69.61 vs. 63.93 years, p = 0.034), lager tumor size (45.7% vs. 11.1%, p = 0.002) and higher neutrophil to lymphocyte ratio (NLR; 2.76 vs. 2.33, p = 0.017) than favorable pathologic group in the training cohort. Tumor size (OR, 6.02; 95% CI, 1.50-24.10; p = 0.011) and NLR (OR, 1.50; 95% CI, 1.05-2.16; p = 0.026) were identified as independent predictive factors for UFP, and the clinical model was constructed using these factors. The LR classifier with the best AUC (0.817, the testing cohorts) was used to construct the radiomics model based on the optimal radiomics features. Finally, the clinic-radiomics model was developed by combining the clinical and radiomics models using LR. After comparison, the clinic-radiomics model had the best performance in comprehensive predictive efficacy (accuracy = 0.750, AUC = 0.817, the testing cohorts) and clinical net benefit among UFP-prediction models, while the clinical model (accuracy = 0.625, AUC = 0.742, the testing cohorts) was the worst. CONCLUSION: Our study demonstrates that the clinic-radiomics model exhibits the best predictive efficacy and clinical net benefit for predicting UFP in initial BLCA compared with the clinical and radiomics model. The integration of radiomics features significantly improves the comprehensive performance of the clinical model.

Golgi-IP, a tool for multimodal analysis of Golgi molecular content.

The Golgi is a membrane-bound organelle that is essential for protein and lipid biosynthesis. It represents a central trafficking hub that sorts proteins and lipids to various destinations or for secretion from the cell. The Golgi has emerged as a docking platform for cellular signaling pathways including LRRK2 kinase whose deregulation leads to Parkinson disease. Golgi dysfunction is associated with a broad spectrum of diseases including cancer, neurodegeneration, and cardiovascular diseases. To allow the study of the Golgi at high resolution, we report a rapid Golgi immunoprecipitation technique (Golgi-IP) to isolate intact Golgi mini-stacks for subsequent analysis of their content. By fusing the Golgi-resident protein TMEM115 to three tandem HA epitopes (GolgiTAG), we purified the Golgi using Golgi-IP with minimal contamination from other compartments. We then established an analysis pipeline using liquid chromatography coupled with mass spectrometry to characterize the human Golgi proteome, metabolome, and lipidome. Subcellular proteomics confirmed known Golgi proteins and identified proteins not previously associated with the Golgi. Metabolite profiling established the human Golgi metabolome and revealed the enrichment of uridine-diphosphate (UDP) sugars and their derivatives, which is consistent with their roles in protein and lipid glycosylation. Furthermore, targeted metabolomics validated SLC35A2 as the subcellular transporter for UDP-hexose. Finally, lipidomics analysis showed that phospholipids including phosphatidylcholine, phosphatidylinositol, and phosphatidylserine are the most abundant Golgi lipids and that glycosphingolipids are enriched in this compartment. Altogether, our work establishes a comprehensive molecular map of the human Golgi and provides a powerful method to study the Golgi with high precision in health and disease.

PLU1 Promotes the Proliferation and Migration of Glioma Cells and Regulates Metabolism.

OBJECTIVES: PLU1 is upregulated in many cancers, including breast, mammary, colorectal, and hepatocellular carcinoma. However, little is known about the potential metabolic mechanisms of PLU1 in glioma progression. Therefore, we investigated the relationship between PLU1 and glioma development. METHODS: We analyzed the relationship between PLU1 expression and World Health Organization (WHO) grade using clinical databases and verified the role of PLU1 in glioma development using transcriptome sequencing, Western blotting, Cell Counting Kit 8, colony formation, and wound healing assays. The relationship between PLU1 and glioma glucose metabolism was also initially explored by changing the concentration of glucose in the culture medium and was validated by metabolomics and energy metabolism. RESULT: PLU1 expression was closely related to WHO grade and was significantly elevated in tumor tissues compared to nontumor tissues. Knockdown or inhibition of PLU1 inhibits proliferation and migration of glioma cells. In addition, we found that PLU1 expression was closely associated with glioma metabolism by transcriptomic, metabolomic, and energy-related molecular analyses and correlated with glucose metabolism. We also found that glucose concentration affects PLU1 expression, and that PLU1 expression affects intracellular glucose levels. CONCLUSION: PLU1 is a novel regulator of metabolic reprograming and a novel strategy for the treatment of glioma.

Application of DCE-MRI radiomics signature analysis in differentiating molecular subtypes of luminal and non-luminal breast cancer.

Background: The goal of this study was to develop and validate a radiomics signature based on dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) preoperatively differentiating luminal and non-luminal molecular subtypes in patients with invasive breast cancer. Methods: One hundred and thirty-five invasive breast cancer patients with luminal (n = 78) and non-luminal (n = 57) molecular subtypes were divided into training set (n = 95) and testing set (n = 40) in a 7:3 ratio. Demographics and MRI radiological features were used to construct clinical risk factors. Radiomics signature was constructed by extracting radiomics features from the second phase of DCE-MRI images and radiomics score (rad-score) was calculated. Finally, the prediction performance was evaluated in terms of calibration, discrimination, and clinical usefulness. Results: Multivariate logistic regression analysis showed that no clinical risk factors were independent predictors of luminal and non-luminal molecular subtypes in invasive breast cancer patients. Meanwhile, the radiomics signature showed good discrimination in the training set (AUC, 0.86; 95% CI, 0.78-0.93) and the testing set (AUC, 0.80; 95% CI, 0.65-0.95). Conclusion: The DCE-MRI radiomics signature is a promising tool to discrimination luminal and non-luminal molecular subtypes in invasive breast cancer patients preoperatively and noninvasively.

Early changes to retinal structure in patients with diabetic retinopathy as determined by ultrawide swept-source optical coherence tomography-angiography.

Purpose: To investigate retinal vascular changes in patients with diabetic retinopathy (DR) using the newly developed ultrawide rapid scanning swept-source optical coherence tomography angiography (SS-OCTA) device. Methods: This cross-sectional, observational study enrolled 24 patients (47 eyes) with DR, 45 patients (87 eyes) with diabetes mellitus (DM) without DR, and 36 control subjects (71 eyes). All subjects underwent 24 × 20 mm SS-OCTA examination. Vascular density (VD) and the thickness of the central macula (CM; 1 mm diameter) and temporal fan-shaped areas of 1-3 mm (T3), 3-6 mm (T6), 6-11 mm (T11), 11-16 mm (T16), and 16-21 mm (T21) were compared among groups. The VD and the thicknesses of the superficial vascular complex (SVC) and deep vascular complex (DVC) were analyzed separately. The predictive values of VD and thickness changes in DM and DR patients were evaluated by receiver operating characteristic (ROC) curve analysis. Results: The average VDs of the SVC in the CM and the T3, T6, T11, T16, and T21 areas were significantly lower in the DR than in the control group, whereas only the average VD of the SVC in the T21 area was significantly lower in the DM group. The average VD of the DVC in the CM was significantly increased in the DR group, whereas the average VDs of the DVC in the CM and T21 area were significantly decreased in the DM group. Evaluation of the DR group showed significant increases in the thicknesses of SVC-nourishing segments in the CM and T3, T6, and T11 areas and significant increases in the thicknesses of DVC-nourishing segments in the CM and T3 and T6 areas. In contrast, none of these parameters showed significant changes in the DM group. ROC curve analysis showed that the average VD of the SVC in the CM, T3, and T21 had better ability to predict DR, with areas under the ROC curves (AUCs) of 0.8608, 0.8505, and 0.8353, respectively. The average VD of the DVC in the CM was also predictive of DR, with an AUC of 0.8407. Conclusions: The newly developed ultrawide SS-OCTA device was better able to reveal early peripheral retinal vascular changes than traditional devices.