Direct observation of translational activation by a ribonucleoprotein granule.

Biomolecular condensates organize biochemical processes at the subcellular level and can provide spatiotemporal regulation within a cell. Among these, ribonucleoprotein (RNP) granules are storage hubs for translationally repressed mRNA. Whether RNP granules can also activate translation and how this could be achieved remains unclear. Here, using single-molecule imaging, we demonstrate that the germ cell-determining RNP granules in Drosophila embryos are sites for active translation of nanos mRNA. Nanos translation occurs preferentially at the germ granule surface with the 3' UTR buried within the granule. Smaug, a cytosolic RNA-binding protein, represses nanos translation, which is relieved when Smaug is sequestered to the germ granule by the scaffold protein Oskar. Together, our findings uncover a molecular process by which RNP granules achieve localized protein synthesis through the compartmentalized loss of translational repression.

Mechanistic Insight into the Synthesis and Morphological Evolution of Superhydrophobic Silica Nanotubes.

Silica nanotubes have significant applications in various fields, including thermal insulation, self-cleaning, and catalysis. Currently, the synthesis methods of silica nanotubes are mostly limited to the template method. In this work, a template-free strategy and vapor-phase approach were used to prepare silica nanotubes. Poly(methylhydrosiloxane) (PMHS) was hydrolyzed and condensed in a high-temperature closed reactor by using ammonia as a catalyst. The resulting product was then subjected to template-free self-assembly to synthesize silica nanotubes incorporating methyl groups. The silica nanotubes were synthesized under varying conditions, resulting in lengths ranging from 50 nm to several micrometers, exterior diameters between 40 and 120 nm, and wall thicknesses varying from 7 to 30 nm. The synthesized products underwent morphology analysis using TEM and FESEM for morphology analysis, elemental composition analysis using XPS, and chemical structure identification using FTIR, and the possible formation mechanism of silica nanotubes formation was also speculated. Furthermore, the coatings formed by silica nanotubes exhibited remarkable superhydrophobic self-cleaning properties with a water contact angle of 162° and a rolling angle of less than 1°.

Comprehensive assessment of ocular parameters for identifying diagnostic indicators of diabetic peripheral neuropathy.

PURPOSE: To explore variations in systemic and ocular parameters among patients with diabetes, both with and without diabetic peripheral neuropathy (DPN) and to identify sensitive indicators for DPN diagnosis. METHODS: Ninty-five patients with type 2 diabetes mellitus (T2DM) were involved in this cross-sectional study, including 49 without DPN and 46 with DPN. Ocular parameters were obtained using optical coherence tomography angiography (OCTA) and corneal confocal microscopy (CCM). RESULT: Patients with DPN presented with significantly higher HbA1c (p < 0.05) and glycated albumin (GA, p < 0.01) levels, increased prevalence of diabetic retinopathy (DR, p < 0.05), and lower serum albumin (ALB, p < 0.01) and red blood cell (RBC, p < 0.05) levels. Ocular assessments revealed reduced corneal nerve fiber length (CNFL, p < 0.001) and enlarged foveal avascular zone (FAZ) area (p < 0.05) in DPN group. Logistic regression analysis indicated a significant association of presence of DR, RBC, GA, ALB, CNFL and DPN (p < 0.05, respectively). In the binary logistic regression for DPN risk, all three models including the presence of DR and CNFL exhibited the area under the curve (AUC) exceeding 0.8. CONCLUSION: The study establishes a strong correlation between ocular parameters and DPN, highlighting CCM's role in early diagnosis. Combining systemic and ocular indicators improves DPN risk assessment and early management.

Targeting DNMT3A-mediated oxidative phosphorylation to overcome ibrutinib resistance in mantle cell lymphoma.

The use of Bruton tyrosine kinase (BTK) inhibitors such as ibrutinib achieves a remarkable clinical response in mantle cell lymphoma (MCL). Acquired drug resistance, however, is significant and affects long-term survival of MCL patients. Here, we demonstrate that DNA methyltransferase 3A (DNMT3A) is involved in ibrutinib resistance. We find that DNMT3A expression is upregulated upon ibrutinib treatment in ibrutinib-resistant MCL cells. Genetic and pharmacological analyses reveal that DNMT3A mediates ibrutinib resistance independent of its DNA-methylation function. Mechanistically, DNMT3A induces the expression of MYC target genes through interaction with the transcription factors MEF2B and MYC, thus mediating metabolic reprogramming to oxidative phosphorylation (OXPHOS). Targeting DNMT3A with low-dose decitabine inhibits the growth of ibrutinib-resistant lymphoma cells both in vitro and in a patient-derived xenograft mouse model. These findings suggest that targeting DNMT3A-mediated metabolic reprogramming to OXPHOS with decitabine provides a potential therapeutic strategy to overcome ibrutinib resistance in relapsed/refractory MCL.

Fusion dsRNA designs incorporating multiple target sequences can enhance the aphid control capacity of an RNAi-based strategy.

BACKGROUND: RNA interference (RNAi) is the sequence-dependent suppression of gene expression by double-stranded RNA (dsRNA). This is a promising strategy for the control of insect pests because dsRNA can be rationally designed to maximize efficacy and biosafety, the latter by using sequences that are found in target pests but are safe for non-target insects. However, this has yet to be optimized in aphids, destructive sap-sucking pests that also transmit plant viruses. We used the green peach aphid (Myzus persicae) as a case study to optimize the efficiency of RNAi by applying a novel fusion dsRNA design. RESULTS: Comparative transcriptomics revealed a number of genes that are induced in feeding aphids, and eight candidate genes were chosen as RNAi targets. To improve RNAi efficiency, our fusion dsRNA design approach combined optimal gene fragments (highly conserved in several aphid species but with less homology in beneficial insects such as the predator ladybeetle Propylea japonica) from three candidate genes. We compared this RNAi-based biological control approach with conventional chemical control using imidacloprid. We found that the fusion dsRNA strategy inhibited the aphid population to a significantly greater extent than single-target RNAi and did not affect ladybeetle fitness, allowing an additive effect between RNAi and natural predation, whereas imidacloprid was harmful to aphids and ladybeetles. CONCLUSION: Our fusion dsRNA design approach enhances the ability of RNAi to control aphids without harming natural predators. © 2024 Society of Chemical Industry.

Translating color fundus photography to indocyanine green angiography using deep-learning for age-related macular degeneration screening.

Age-related macular degeneration (AMD) is the leading cause of central vision impairment among the elderly. Effective and accurate AMD screening tools are urgently needed. Indocyanine green angiography (ICGA) is a well-established technique for detecting chorioretinal diseases, but its invasive nature and potential risks impede its routine clinical application. Here, we innovatively developed a deep-learning model capable of generating realistic ICGA images from color fundus photography (CF) using generative adversarial networks (GANs) and evaluated its performance in AMD classification. The model was developed with 99,002 CF-ICGA pairs from a tertiary center. The quality of the generated ICGA images underwent objective evaluation using mean absolute error (MAE), peak signal-to-noise ratio (PSNR), structural similarity measures (SSIM), etc., and subjective evaluation by two experienced ophthalmologists. The model generated realistic early, mid and late-phase ICGA images, with SSIM spanned from 0.57 to 0.65. The subjective quality scores ranged from 1.46 to 2.74 on the five-point scale (1 refers to the real ICGA image quality, Kappa 0.79-0.84). Moreover, we assessed the application of translated ICGA images in AMD screening on an external dataset (n = 13887) by calculating area under the ROC curve (AUC) in classifying AMD. Combining generated ICGA with real CF images improved the accuracy of AMD classification with AUC increased from 0.93 to 0.97 (P < 0.001). These results suggested that CF-to-ICGA translation can serve as a cross-modal data augmentation method to address the data hunger often encountered in deep-learning research, and as a promising add-on for population-based AMD screening. Real-world validation is warranted before clinical usage.

Novel NASICON-Type Na-V-Mn-Ni-Containing Cathodes for High-Rate and Long-Life SIBs.

Partial substitution of V by other transition metals in Na3 V2 (PO4 )3 (NVP) can improve the electrochemical performance of NVP as a cathode for sodium-ion batteries (SIBs). Herein, phosphate Na-V-Mn-Ni-containing composites based on NASICON (Natrium Super Ionic Conductor)-type structure have been fabricated by sol-gel method. The synchrotron-based X-ray study, X-ray diffraction (XRD), and X-ray photoelectron spectroscopy (XPS) studies show that manganese/nickel combinations successfully substitute the vanadium in its site within certain limits. Among the received samples, composite based on Na3.83 V1.17 Mn0.58 Ni0.25 (PO4 )3 (VMN-0.5, 108.1 mAh g-1 at 0.2 C) shows the highest electrochemical ability. The cyclic voltammetry, galvanostatic intermittent titration technique, in situ XRD, ex situ XPS, and bond valence site energy calculations exhibit the kinetic properties and the sodium storage mechanism of VMN-0.5. Moreover, VMN-0.5 electrode also exhibits excellent electrochemical performance in quasi-solid-state sodium metal batteries with PVDF-HFP quasi-solid electrolyte membranes. The presented work analyzes the advantages of VMN-0.5 and the nature of the substituted metal in relation to the electrochemical properties of the NASICON-type structure, which will facilitate further commercialization of SIBs.

RNA interference in insects: the link between antiviral defense and pest control.

RNA interference (RNAi) is a form of gene silencing triggered by double-stranded RNA (dsRNA) that operates in all eukaryotic cells. RNAi has been widely investigated in insects to determine the underlying molecular mechanism, to investigate its role in systemic antiviral defense, and to develop strategies for pest control. When insect cells are infected by viruses, viral dsRNA signatures trigger a local RNAi response to block viral replication and generate virus-derived DNA that confers systemic immunity. RNAi-based insect pest control involves the application of exogenous dsRNA targeting genes essential for insect development or survival, but the efficacy of this approach has limited potency in many pests through a combination of rapid dsRNA degradation, inefficient dsRNA uptake/processing, and ineffective RNAi machinery. This could be addressed by dsRNA screening and evaluation, focusing on dsRNA design and off-target management, as well as dsRNA production and delivery. This review summarizes recent progress to determine the role of RNAi in antiviral defense and as a pest control strategy in insects, addressing gaps between our fundamental understanding of the RNAi mechanism and the exploitation of RNAi-based pest control strategies.

A Non-Flammable and Flexible Aluminum Derived Lithium-Ion Storage Device with a Wide Temperature Range of Operation.

With the rapid development and increasing popularity of electric vehicles and wearables, battery safety has become a leading focus in the field of energy storage research. Specifically, aluminum-ion batteries are gaining increasing attention as low-cost energy-storage systems with high safety levels and theoretical energy density. However, the dense alumina passivation layer on the aluminum anode surface and slow kinetic performance of commonly used ionic liquid electrolytes still render poor performance. This report presents a new type of aluminum-derived lithium-ion battery (ALIB) that maintains a certain discharge performance under damaging conditions, including continuous bending, high- and low-temperature environments, and shearing. This new ALIB effectively meets the current demand for flexible and wearable batteries. The prepared ALIB achieves a stable cycle of 130 mAh g-1 specific capacity and ≈260 Wh kg-1 theoretical energy density at a wide voltage platform of 2 V and a test temperature of 25 °C without undergoing combustion. Additionally, the study analyzes the reaction mechanism of this ALIB based on density functional theory and conducts ex situ XRD and XPS analyses to elucidate the underlying storage mechanism.

Fusion dsRNA in targeting salivary protein genes enhance the RNAi-based aphid control.

RNA interference (RNAi) is a promising tool for pest control and relies on sequence-specific gene silencing. Salivary proteins are cooperatively secreted into plants to guarantee the feeding of aphids; thus they have potential to develop as selective targets for RNAi-based pest control strategy. For this purpose, we firstly analyzed 18 salivary proteomes of various aphid species, and these salivary proteins can be mainly categorized into seven functional groups. Secondly, we created a work-flow for fusion dsRNA design that can target multiple genes but were selectively safe to beneficial insects. Based on this approach, seven fusion dsRNAs were designed to feed the green peach aphid, which induced a significant reduction in aphid fitness. Among them, ingestion of dsperoxidase induced the highest mortality in aphids, which was also significantly higher than that of traditional dsRNAs in targeting three peroxidases separately. In addition, dsperoxidase-fed green peach aphids triggered the highest H2O2 content of host plants as well as the attraction to natural enemies (ladybeetle and parasitic wasp) but repellent to other control aphids. Our results indicate that the fusion dsRNA design approach can improve aphid control capacity, and the fusion dsRNA targeting salivary protein-encoding genes can enhance the direct and indirect defenses of host plants, thus providing a new strategy for RNAi-based aphid control.

EGR1-mediated metabolic reprogramming to oxidative phosphorylation contributes to ibrutinib resistance in B-cell lymphoma.

The use of Bruton tyrosine kinase inhibitors, such as ibrutinib, to block B-cell receptor signaling has achieved a remarkable clinical response in several B-cell malignancies, including mantle cell lymphoma (MCL) and diffuse large B-cell lymphoma (DLBCL). Acquired drug resistance, however, is significant and affects the long-term survival of these patients. Here, we demonstrate that the transcription factor early growth response gene 1 (EGR1) is involved in ibrutinib resistance. We found that EGR1 expression is elevated in ibrutinib-resistant activated B-cell-like subtype DLBCL and MCL cells and can be further upregulated upon ibrutinib treatment. Genetic and pharmacological analyses revealed that overexpressed EGR1 mediates ibrutinib resistance. Mechanistically, TCF4 and EGR1 self-regulation induce EGR1 overexpression that mediates metabolic reprogramming to oxidative phosphorylation (OXPHOS) through the transcriptional activation of PDP1, a phosphatase that dephosphorylates and activates the E1 component of the large pyruvate dehydrogenase complex. Therefore, EGR1-mediated PDP1 activation increases intracellular adenosine triphosphate production, leading to sufficient energy to enhance the proliferation and survival of ibrutinib-resistant lymphoma cells. Finally, we demonstrate that targeting OXPHOS with metformin or IM156, a newly developed OXPHOS inhibitor, inhibits the growth of ibrutinib-resistant lymphoma cells both in vitro and in a patient-derived xenograft mouse model. These findings suggest that targeting EGR1-mediated metabolic reprogramming to OXPHOS with metformin or IM156 provides a potential therapeutic strategy to overcome ibrutinib resistance in relapsed/refractory DLBCL or MCL.

Self-supervised deep clustering of single-cell RNA-seq data to hierarchically detect rare cell populations.

Single-cell RNA sequencing (scRNA-seq) is a widely used technique for characterizing individual cells and studying gene expression at the single-cell level. Clustering plays a vital role in grouping similar cells together for various downstream analyses. However, the high sparsity and dimensionality of large scRNA-seq data pose challenges to clustering performance. Although several deep learning-based clustering algorithms have been proposed, most existing clustering methods have limitations in capturing the precise distribution types of the data or fully utilizing the relationships between cells, leaving a considerable scope for improving the clustering performance, particularly in detecting rare cell populations from large scRNA-seq data. We introduce DeepScena, a novel single-cell hierarchical clustering tool that fully incorporates nonlinear dimension reduction, negative binomial-based convolutional autoencoder for data fitting, and a self-supervision model for cell similarity enhancement. In comprehensive evaluation using multiple large-scale scRNA-seq datasets, DeepScena consistently outperformed seven popular clustering tools in terms of accuracy. Notably, DeepScena exhibits high proficiency in identifying rare cell populations within large datasets that contain large numbers of clusters. When applied to scRNA-seq data of multiple myeloma cells, DeepScena successfully identified not only previously labeled large cell types but also subpopulations in CD14 monocytes, T cells and natural killer cells, respectively.

Polyphosphate as an antithrombotic target and hemostatic agent.

Polyphosphate (PolyP) is a polymer comprised of linear phosphate units connected by phosphate anhydride bonds. PolyP exists in a diverse range of eukaryotes and prokaryotes with varied chain lengths ranging from six to thousands of phosphate units. Upon activation, human platelets and neutrophils release short-chain PolyP, along with other components, to initiate the coagulation pathway. Long-chain PolyP derived from cellular or bacterial organelles exhibits higher proinflammatory and procoagulant effects compared to short-chain PolyP. Notably, PolyP has been identified as a low-hemorrhagic antithrombotic target since neutralizing plasma PolyP suppresses the thrombotic process without impairing the hemostatic functions. As an inorganic polymer without uniform steric configuration, PolyP is typically targeted by cationic polymers or recombinant polyphosphatases rather than conventional antibodies, small-molecule compounds, or peptides. Additionally, because of its procoagulant property, PolyP has been incorporated in wound-dressing materials to facilitate blood hemostasis. This review summarizes current studies on PolyP as a low-hemorrhagic antithrombotic target and the development of hemostatic materials based on PolyP.

High resolution micro-confocal Raman spectrometer-based photo-affinity microarray technology for the investigation of active ingredients - Target protein recognition strategy.

Natural products has been used for the prevention and treatment of diseases for a long history. Research on the bioactive components from natural products and their interaction with target proteins are essential for drug discovery. However, studying the binding ability of natural products' active ingredients to target proteins is usually time-consuming and laborious due to their complex and diverse chemical structures. In this study, we have developed a high resolution micro-confocal Raman spectrometer-based photo-affinity microarray (HRMR-PM) technology for the investigation of active ingredients-target protein recognition strategy. The novel photo-affinity microarray was constructed by photo-cross-linking the small molecule with the photo-affinity group (4-[3-(Trifluoromethyl)-3H-diazirin-3-yl]benzoic acid, TAD) on the photo-affinity linker coated (PALC) slides under 365 nm ultraviolet irradiation. The small molecules on the microarrays with specific binding ability might immobilize target protein, which were characterized by high resolution micro-confocal Raman spectrometer. Using this method, more than a dozen components of Shenqi Jiangtang granules (SJG) were made into small molecule probe (SMP) microarrays. As a result, 8 of them had been identified to have α-glucosidase binding ability according to characteristic Raman shift at about 3060 cm-1. These compounds were further verified by different small molecule-protein interaction analysis methods, including contact angle D-value, surface plasmon resonance (SPR) and molecular docking. The results showed that Ginsenosides Mb, Formononetin and Gomisin D exhibited the strongest binding ability. In conclusion, the HRMR-PM strategy for investigating the interaction between target proteins and small molecules has the advantages such as high throughput, low sample consumption and fast qualitative characterization. This strategy is universal which can be applied in the study of in vitro binding activity of various types of small molecules to target proteins.

Deep-learning-based 3D blood flow reconstruction in transmissive laser speckle imaging.

Transmissive laser speckle imaging (LSI) is useful for monitoring large field-of-view (FOV) blood flow in thick tissues. However, after longer transmissions, the contrast of the transmitted speckle images is more likely to be blurred by multiple scattering, resulting in decreased accuracy and spatial resolution of deep vessels. This study proposes a deep-learning-based strategy for high spatiotemporal resolution three-dimensional (3D) reconstruction from a single transilluminated laser speckle contrast image, providing more structural and functional details without multifocus two-dimensional (2D) imaging or 3D optical imaging with point/line scanning. Based on the correlation transfer equation, a large training dataset is generated by convolving vessel masks with depth-dependent point spread functions (PSF). The UNet and ResNet are used for deblurring and depth estimation. The blood flow in the reconstructed 3D vessels is estimated by a depth-dependent contrast model. The proposed method is evaluated with simulated data and phantom experiments, achieving high-fidelity structural reconstruction with a depth-independent estimation of blood flow. This fast 3D blood flow imaging technique is suitable for real-time monitoring of thick tissue and the diagnosis of vascular diseases.

Comparing the Ability of Secretory Signal Peptides for Heterologous Expression of Anti-Lipopolysaccharide Factor 3 in Chlamydomonas reinhardtii.

Anti-lipopolysaccharide factor 3 (ALFPm3) possesses a wide antimicrobial spectrum and high antibacterial and viral activities for broad application prospects in the aquaculture industry. However, the application of ALFPm3 is limited by its low production in nature, as well as its low activity when expressed in Escherichia coli and yeast. Although it has been proven that its secretory expression can be used to produce antimicrobial peptides with strong antimicrobial activity, there is no study on the high-efficiency secretory expression of ALFPm3 in Chlamydomonas reinhardtii. In this study, signal peptides ARS1 and CAH1 were fused with ALFPm3 and inserted into the pESVH vector to construct pH-aALF and pH-cALF plasmids, respectively, that were transformed to C. reinhardtii JUV using the glass bead method. Subsequently, through antibiotic screening, DNA-PCR, and RT-PCR, transformants expressing ALFPm3 were confirmed and named T-JaA and T-JcA, respectively. The peptide ALFPm3 could be detected in algal cells and culture medium by immunoblot, meaning that ALFPm3 was successfully expressed in C. reinhardtii and secreted into the extracellular environment. Moreover, ALFPm3 extracts from the culture media of T-JaA and T-JcA showed significant inhibitory effects on the growth of V. harveyi, V. alginolyticus, V. anguillarum, and V. parahaemolyticus within 24 h. Interestingly, the inhibitory rate of c-ALFPm3 from T-JcA against four Vibrio was 2.77 to 6.23 times greater than that of a-ALFPm3 from T-JaA, indicating that the CAH1 signal peptide was more helpful in enhancing the secreted expression of the ALFPm3 peptide. Our results provided a new strategy for the secretory production of ALFPm3 with high antibacterial activity in C. reinhardtii, which could improve the application potentiality of ALFPm3 in the aquaculture industry.

Secretory Expression and Application of Antilipopolysaccharide Factor 3 in Chlamydomonas reinhardtii.

Anti-lipopolysaccharide factor is a class of antimicrobial peptides with lipopolysaccharide-binding structural domains, which has a broad antimicrobial spectrum, high antimicrobial activities, and broad application prospects in terms of the aquaculture industry. However, the low yield of natural antimicrobial peptides and their poor expression activity in bacteria and yeast have hindered their exploration and utilization. Therefore, in this study, the extracellular expression system of Chlamydomonas reinhardtii, by fusing the target gene with the signal peptide, was used to express anti-lipopolysaccharide factor 3 (ALFPm3) from Penaeus monodon in order to obtain highly active ALFPm3. Transgenic C. reinhardtii T-JiA2, T-JiA3, T-JiA5, and T-JiA6, were verified using DNA-PCR, RT-PCR, and immunoblot. Additionally, the IBP1-ALFPm3 fusion protein could be detected not only within the cells but also in the culture supernatant. Moreover, the extracellular secretion containing ALFPm3 was collected from algal cultures, and then its bacterial inhibitory activity was analyzed. The results showed that the extracts from T-JiA3 had an inhibition rate of 97% against four common aquaculture pathogenic bacteria, including Vibrio harveyi, Vibrio anguillarum, Vibrio alginolyticus, and Vibrio parahaemolyticus. The highest inhibition rate of 116.18% was observed in the test against V. anguillarum. Finally, the minimum inhibition concentration (MIC) of the extracts from T-JiA3 to V. harveyi, V. anguillarum, V. alginolyticus, and V. parahaemolyticus were 0.11 µg/µL, 0.088 µg/µL, 0.11 µg/µL, and 0.011 µg/µL, respectively. This study supports the foundation of the expression of highly active anti-lipopolysaccharide factors using the extracellular expression system in C. reinhardtii, providing new ideas for the expression of highly active antimicrobial peptides.

A comprehensive overview of PPM1B: From biological functions to diseases.

Reversible phosphorylation of proteins is an important mechanism that regulates cellular processes, which are precisely regulated by protein kinases and phosphatases. PPM1B is a metal ion-dependent serine/threonine protein phosphatase, which regulates multiple biological functions by targeting substrate dephosphorylation, such as cell cycle, energy metabolism, inflammatory responses. In this review, we summarized the occurrent understandings of PPM1B focused on its regulation of signaling pathways, related diseases, and small-molecular inhibitors, which may provide new insights for the identification of PPM1B inhibitors and the treatment of PPM1B-related diseases.

Multimodal imaging analysis for the impact of retinal peripheral lesions on central neurovascular structure and retinal function in type 2 diabetes with diabetic retinopathy.

OBJECTIVES: To explore the possible role of peripheral lesions (PLs) detected by ultrawide field (UWF) imaging system on central neurovascular structure and retinal function. METHODS: Ninety-seven diabetic patients were included in this cross-sectional study using UWF pseudocolour colour imaging with Optos Daytona (Optos, PLC). UWF images were graded as with predominantly peripheral lesions (PPLs) and without PPL. Macular neurovascular alterations and retinal function were measured by optical coherence tomography angiography (OCTA) and RETeval device, respectively. Central microcirculation and retinal function were compared between eyes with and without PPL. RESULTS: The study evaluated 186 eyes (97 patients; 43 females (44.3%)), including 92 eyes without PPL and 94 eyes with PPL. Central retinal vessel density was comparable between eyes with and without PPL. Delayed implicit time and decreased pupil area ratio were found in the PPL group compared with eyes without PPL, and this difference remained unchanged after adjusting for systemic factors (all p＜0.01). CONCLUSIONS: Our study suggests that retinal function is worse in diabetic eyes with PPL. These findings challenged the conventional ETDRS protocols which ignored peripheral retina in determining DR severity. Furthermore, combining UWF imaging with RETeval system to detect more retinal abnormalities may be helpful in DR management.

Online estimating weight of white Pekin duck carcass by computer vision.

The increasing consumption of ducks and chickens in China demands characterizing carcasses of domestic birds efficiently. Most existing methods, however, were developed for characterizing carcasses of pigs or cattle. Here, we developed a noncontact and automated weighing method for duck carcasses hanging on a production line. A 2D camera with its facilitating parts recorded the moving duck carcasses on the production line. To estimate the weight of carcasses, the images in the acquired dataset were modeled by a convolution neuron network (CNN). This model was trained and evaluated using 10-fold cross-validation. The model estimated the weight of duck carcasses precisely with a mean abstract deviation (MAD) of 58.8 grams and a mean relative error (MRE) of 2.15% in the testing dataset. Compared with 2 widely used methods, pixel area linear regression and the artificial neural network (ANN) model, our model decreases the estimation error MAD by 64.7 grams (52.4%) and 48.2 grams (45.0%). We release the dataset and code at https://github.com/RuoyuChen10/Image_weighing.