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SynopsisA deep-learning-based macular extrafoveal avascular area (EAA) on a 6×6 mm optical coherence tomography (OCT) angiogram is less dependent on the signal strength and shadow artefacts, providing better diagnostic accuracy for diabetic retinopathy (DR) severity than the commercial software measured extrafoveal vessel density (EVD).AimsTo compare a deep-learning-based EAA to commercial output EVD in the diagnostic accuracy of determining DR severity levels from 6×6 mm OCT angiography (OCTA) scans.MethodsThe 6×6 mm macular OCTA scans were acquired on one eye of each participant with a spectral-domain OCTA system. After excluding the central 1 mm diameter circle, the EAA on superficial vascular complex was measured with a deep-learning-based algorithm, and the EVD was obtained with commercial software.ResultsThe study included 34 healthy controls and 118 diabetic patients. EAA and EVD were highly correlated with DR severity (ρ=0.812 and −0.577, respectively, both pConclusionMacular EAA on 6×6 mm OCTA measured with a deep learning-based algorithm is less dependent on the signal strength and shadow artefacts, and provides better diagnostic accuracy for DR severity than EVD measured with the instrument-embedded software.

ObjectiveWe investigated the clinical efficiency and complications of treatment of retinal sub-inner limiting membrane (sub-ILM) hemorrhage by 577-nm semiconductive laser membranotomy.MethodsThe clinical features, ocular fundus photography, and SD-OCT image of patients who received 577-nm laser membranotomy for sub-ILM hemorrhage were assessed from January 2017 to April 2022 in this retrospective case-series study.ResultsA total of 19 patients (19 eyes) were treated for sub-ILM hemorrhage of the macula, in which eight were women and 11 were men. The age was 15–83 years (with an average age of 49.05 ± 19.41 years old). The right eye was affected in 12 patients, the left eye in seven patients. The follow-up period after laser treatment was from 0.5 to 9 months (with an average follow-up time of 3.25 ± 2.45 months). Treatment was not successful in one patient, and 577-nm laser membranotomy was successful in 18 patients (equaling a success rate of 94.74%). The best corrected visual acuity (BCVA) before laser treatment was from figure count to 40/200, and the BCVA after laser treatment was from 20/2000 to 20/20. Complications after laser treatment comprised macular hole (one patient), macular epi-membrane (one patient), vitreous hemorrhage without absorption (two patients), and sub-ILM cavity (12 patients).ConclusionsThe 577-nm laser is effective in treating sub-ILM hemorrhage and has a high success rate. Posttreatment complications should be monitored, and vitrectomy was needed with long-lasting vitreous hemorrhage and macular hole.

The applications of the most promising Fe-N-C catalysts are prohibited by their limited intrinsic activities. Manipulating the Fe energy level through anchoring electron-withdrawing ligands is found effective in boosting the catalytic performance. However, such regulation remains elusive as the ligands are only uncontrollably introduced oweing to their energetically unstable nature. Herein, we report a rational manipulation strategy for introducing axial bonded O to the Fe sites, attained through hexa-coordinating Fe with oxygen functional groups in the precursor. Moreover, the O modifier is stabilized by forming the Fe-O-Fe bridge bond, with the approximation of two FeN4 sites. The energy level modulation thus created confers the sites with an intrinsic activity that is over 10 times higher than that of the normal FeN4 site. Our finding opens a novel strategy to manage coordination environments at an atomic level for high activity ORR catalysts.

Well-dispersed palladium nanoparticles (NPs) anchored on a porous N-doped carbon is prepared by wet chemical method, using metal organic frameworks (ZIF-8) as a precursor to derive the porous N-doped carbon support. Benefitting from the N-doping and the porous structure of the carbon materials, the final Pd NPs are in high dispersion and exhibit reduced particle sizes, with electronic structure and chemical status tuned to favor the formic acid decomposition (FAD). The prepared Pd/CZIF-8-950 catalysts show enhanced catalytic performance and selectivity for FAD, the turnover of frequency (TOF) and the mass activity up to 1166 h−1 and 11.01 mol H2 g−1 pd h−1 were obtained at 30 °C. This work provides an effective and easy way for synthesis the Pd-based catalyst, which has enormous application prospects for the next generation hydrogen energy preparation and storage.

Rational regulation on pore structure and active site density plays critical roles in enhancing the performance of Fe-N-C catalysts. As the microporous structure of the carbon substrate is generally regarded as the active site hosts, its hostility to electron/mass transfer could lead to the incomplete fulfillment of the catalytic activity. Besides, the formation of inactive metallic Fe particles during the conventional catalyst synthesis could also decrease the active site density and complicate the identification of real active site. Herein, we developed a facial hydrogen etching methodology to yield single site Fe-N-C catalysts featured with micro/mesoporous hierarchical structure. The hydrogen concentration in pyrolysis process was designated to effectively regulate the pore structure and active site density of the resulted catalysts. The optimized sample achieves excellent ORR catalytic performance with an ultralow H2O2 yield (1%) and superb stability over 10,000 cycles. Our finding provides new thoughts for the rational design of hierarchically porous carbon-based materials and highly promising non-precious metal ORR catalysts.

Objective: Optical coherence tomography (OCT) and its angiography (OCTA) have several advantages for the early detection and diagnosis of diabetic retinopathy (DR). However, automated, complete DR classification frameworks based on both OCT and OCTA data have not been proposed. In this study, a convolutional neural network (CNN) based method is proposed to fulfill a DR classification framework using en face OCT and OCTA. Methods: A densely and continuously connected neural network with adaptive rate dropout ( DcardNet ) is designed for the DR classification. In addition, adaptive label smoothing was proposed and used to suppress overfitting. Three separate classification levels are generated for each case based on the International Clinical Diabetic Retinopathy scale. At the highest level the network classifies scans as referable or non-referable for DR. The second level classifies the eye as non-DR, non-proliferative DR (NPDR), or proliferative DR (PDR). The last level classifies the case as no DR, mild and moderate NPDR, severe NPDR, and PDR. Results: We used 10-fold cross-validation with 10% of the data to assess the network's performance. The overall classification accuracies of the three levels were 95.7%, 85.0%, and 71.0% respectively. Conclusion/Significance: A reliable, sensitive and specific automated classification framework for referral to an ophthalmologist can be a key technology for reducing vision loss related to DR.

ObjectiveTo detect the plexus-specific retinal capillary avascular area in exudative age-related macular degeneration (EAMD) with projection-resolved optical coherence tomography angiography (PR-OCTA).Methods and analysisIn this prospective cross-sectional single centre study, eyes with treatment-naïve EAMD underwent macular 3×3 mm OCTA with AngioVue system. OCTA scans were analysed and processed including three-dimensional projection artefact removal, retinal layer semi-automated segmentation and en face angiogram generation. Automated quantification of extrafoveal (excluding the central 1 mm circle) avascular area (EAA) were calculated on projection-resolved superficial vascular complex (SVC), intermediate capillary plexus (ICP) and deep capillary plexus (DCP), respectively.ResultsNineteen eyes with EAMD and 19 age-matched healthy control eyes were included. There was no significant difference between the EAMD and control eyes in terms of age, sex, axial length and mean ocular perfusion pressure (all p>0.05). Compared with control eyes, EAMD eyes had significantly larger EAA in SVC (median 0.125 vs 0.059 mm2, p=0.006), ICP (0.016 vs 0.000 mm2, p=0.004) and DCP (0.033 vs 0.000 mm2, p＜0.001).ConclusionPR-OCTA showed that EAMD is associated with focal avascular area in all the three retinal vascular plexuses.

Detecting and quantifying choroidal neovascularization (CNV) is essential for the diagnosis of neovascular age-related macular degeneration (AMD). Projection-resolved OCT angiography (PR-OCTA) has enabled both en face and volumetric visualization of CNV. However, previously described CNV detection methods only quantify CNV that was already diagnosed, and were unable to identify CNV form unknown inputs . Previous methods were also limited by artifacts. A fully automated CNV diagnosis and quantification algorithm using convolutional neural networks (CNNs) was developed. It was able to diagnose CNV and output CNV membrane and vessel area from retinal structural and angiographic images.

Pyrolyzed Fe-NX/C materials derived from Fe-doped ZIF-8 are recently emerged as promising alternatives to noble metal platinum-based catalysts towards oxygen reduction reaction (ORR) and elucidating the dependacne of Fe source on the active site structure and final ORR performance is highly desirbale for further development of these materials. Here, we designed and synthesized a series of Fe-N-C catalysts using ZIF-8 and various iron salts (Fe(acac)3, FeCl3, Fe(NO3)3) as precusors. We found that the iron precursors, mainly the molecular size, hydrolysis extent, do play a major role in determining the final morphology of Fe, namely forming the Fe-Nx coordination or Fe3C nanoparticles, as well as the site density, therefore, significantly affecting the ORR activity. Among the three iron sources, Fe(acac)3 is most advantageous to the preferential formation of single-atom Fe-Nx active sites and the derived catalyst demonstrated best ORR performance.

Formic acid, as the simplest carboxylic acid which can be obtained as an industrial by-product, is colorless, low toxicity, and easy to transport and storage at room temperature. Recently, Formic acid has aroused wide-spread interest as a promising material for hydrogen storage. Compared to other organic small molecules, the temperature for formic acid decomposition to produce hydrogen is lower, resulting in less CO toxicant species. Lots of catalysts on both homogeneous catalysts and heterogeneous were reported for the decomposition of formic acid to yield hydrogen and carbon dioxide at mild condition. In this paper, the recent development of mechanism and the material study for both homogeneous catalysts and heterogeneous catalysts are reviewed in detail.

Herein, a novel binuclear active site structure, Co2NxCy, is intentionally designed and successfully fabricated to efficiently catalyze the oxygen reduction reaction (ORR), which is achieved by precisely controlling the atomic scale structure of bimetal-organic frameworks before pyrolysis. Through discovering a two-atom site with Co-Co distance at 2.1–2.2 A from aberration-corrected scanning transmission electron microscopy (STEM), as well as a novel shortened Co-Co path (2.12 A) from the X-ray absorption spectroscopy, we for the first time identified the binuclear Co2NX site in the pyrolyzed catalyst. Combined with density functional theory (DFT) calculation, the structure is further confirmed as Co2N5. Excitingly, the Co2N5 site performs approximately 12 times higher activity than the conventional CoN4 site and the corresponding catalyst shows unprecedented catalytic activity in acidic electrolyte with half-wave potential of 0.79 V, approaching the commercial Pt/C catalyst and presenting the best one among the Co-N-C catalysts. Theoretical density functional theory calculations reveal that the novel binuclear site exhibits considerably reduced thermodynamic barrier towards ORR, thus contributing to the much higher intrinsic activity. Our finding opens up a new path to design efficient M-Nx/C catalysts, thus pushing the fuel cell industry field one step ahead.

Early diagnosis of sepsis is critical for successful treatment. The clinical value of DcR3 in early diagnosis of sepsis was determined in a dynamic follow-up study. Alterations in plasma levels of DcR3, PCT, CRP, and IL-6 were measured by ELISA and compared among patients with sepsis (n = 134), SIRS (n = 60) and normal adults (n = 50). Correlations and dynamic patterns among the biomarkers, APACHE II scores, clinical outcomes, and pathogens were also examined. Plasma DcR3 was significantly increased in sepsis compared to SIRS and normal adults (median 3.87 vs. 1.28 and 0.17 ng/ml). The elevated DcR3 could be detected in 97.60% sepsis patients 1–2 days prior to the result of blood culture reported. For diagnosis of sepsis, the sensitivity was 97.69% and specificity 98.04%; and for differential diagnosis of sepsis from SIRS, the sensitivity was 90.77% and specificity 98.40%. DcR3 level was positively correlated with severity of sepsis (rs = 0.82). In 41 patients who died of sepsis, DcR3 elevated as early as 1–2 days before blood culture and peaked on day 3 after blood culture performed. In 90% of sepsis patients, the dynamic alteration pattern of DcR3 was identical to that of PCT, while pattern of 10% patients differed in which clinical data was consistent with DcR3. In 13% sepsis patients, while PCT remained normal, DcR3 levels were at a high level. DcR3 levels had no difference among various pathogens infected. DcR3, a new biomarker, will aid in early diagnosis of sepsis and monitoring its outcome, especially when sepsis patients were PCT negative.

Purpose: To examine the efficacy of a deep learning-based algorithm to quantify the nonperfusion area (NPA) on montaged widefield OCT angiography (OCTA) for assessment of diabetic retinopathy (DR) severity. Design: Cross-sectional study. Participants: One hundred thirty-seven participants with a full range of DR severity and 26 healthy participants. Methods: A deep learning-based algorithm was developed for detecting and quantifying NPA in the superficial vascular complex on widefield OCTA comprising 3 horizontally montaged 6 × 6-mm OCTA scans from the nasal, macular, and temporal regions. We trained the algorithm on 978 volumetric OCTA scans from all participants using 5-fold cross-validation. The algorithm can distinguish NPA from shadow artifacts. The F1 score evaluated segmentation accuracy. The area under the receiver operating characteristic curve and sensitivity with specificity fixed at 95% quantified network performance to distinguish patients with diabetes from healthy control participants, referable DR from nonreferable DR (nonproliferative DR [NPDR] less than moderate severity), and severe DR (severe NPDR, proliferative DR, or DR with edema) from nonsevere DR (mild to moderate NPDR). Main Outcome Measures: Widefield OCTA NPA, visual acuity (VA), and DR severities. Results: Automatically segmented NPA showed high agreement with the manually delineated ground truth, with a mean ± standard deviation F1 score of 0.78 ± 0.05 in nasal, 0.82 ± 0.07 in macular, and 0.78 ± 0.05 in temporal scans. The extrafoveal avascular area (EAA) in the macular scan showed the best sensitivity at 54% for differentiating those with diabetes from healthy control participants, whereas montaged widefield OCTA scan showed significantly higher sensitivity than macular scans (P < 0.0001, McNemar’s test) for detecting eyes with DR at 66%, referable DR at 63%, and severe DR at 62%. Montaged widefield OCTA showed the highest correlation (Spearman ρ = 0.74; P < 0.0001) between EAA and DR severity. The macular scan showed the strongest negative correlation (Pearson ρ = –0.42; P < 0.0001) between EAA and best-corrected VA. Conclusions: A deep learning-based algorithm for montaged widefield OCTA can detect NPA accurately and can improve the detection of clinically important DR.

The aim of the present study was to investigate the early diagnostic values of measuring procalcitonin (PCT), C-reactive protein (CRP), and interleukin-6 (lL-6) levels in patients with bacterial infections and septicopyemia. Ninety-two patients with septicopyemia who were diagnosed and treated in the First Affiliated Hospital of Fujian Medical University between December 2012 and October 2013 were randomly selected. Based on results of hemoculture, the patients were divided into the Gram-negative bacterial infection group (n=47) and the Gram-positive bacterial infection group (n=45). Immune nephelometry was used for measuring serum CRP levels, electrochemiluminescence assay was used to measure serum PCT and IL-6. The levels of serum CRP, PCT, and IL-6 in the Gram-negative bacterial infection group were significantly higher than in the Gram-positive group. Analysis with Spearman's correlation coefficient showed that there were positive correlations between the levels of PCT and CRP, and between PCT and IL-6 (P

Emerging as a new frontier in heterogeneous catalysis, single-atom site catalysts (SSCs) have sparked enormous attention and bring about new opportunities to oxygen reduction electrocatalysis. Despite considerable progress achieved recently, most of the reported SSCs suffer from either insufficient activity or unsatisfactory stability, which severely retards their practical application. Here, we demonstrate a novel Ru-SSC with appropriate adsorption free energy of OH* (Δ

Great enthusiasm in single-atom catalysts (SACs) for the oxygen reduction reaction (ORR) has been aroused by the discovery of M-NX as a promising ORR catalysis center. However, the performance of SACs lags far behind that of state-of-the-art Pt due to the unsatisfactory adsorption-desorption behaviors of the reported catalytic centers. To address this issue, rational manipulation of the active site configuration toward a well-managed energy level and geometric structure is urgently desired, yet still remains a challenge. Herein, we report a novel strategy to accomplish this task through the construction of an Fe-Co dual-atom centered site. A spontaneously absorbed electron-withdrawing OH ligand was proposed to act proactively as an energy level modifier to empower easy intermediate desorption, while the triangular Fe-Co-OH coordination facilitates O-O bond scission. Benefiting from these attributes, the as-constructed FeCoN5-OH site enables an ORR onset potential and half-wave potential of up to 1.02 and 0.86 V (vs RHE), respectively, with an intrinsic activity over 20 times higher than the single-atom FeN4 site. Our finding not only opens up a novel strategy to tailor the electronic structure of an atomic site toward boosted activity but also provides new insights into the fundamental understanding of diatomic sites for ORR electrocatalysis.

Single-atom catalysts (SACs) are attracting widespread interest for the catalytic oxygen reduction reaction (ORR), with Fe-N

Accurate identification and segmentation of choroidal neovascularization (CNV) is essential for the diagnosis and management of exudative age-related macular degeneration (AMD). Projection-resolved optical coherence tomographic angiography (PR-OCTA) enables both cross-sectional and en face visualization of CNV. However, CNV identification and segmentation remains difficult even with PR-OCTA due to the presence of residual artifacts. In this paper, a fully automated CNV diagnosis and segmentation algorithm using convolutional neural networks (CNNs) is described. This study used a clinical dataset, including both scans with and without CNV, and scans of eyes with different pathologies. Furthermore, no scans were excluded due to image quality. In testing, all CNV cases were diagnosed from non-CNV controls with 100% sensitivity and 95% specificity. The mean intersection over union of CNV membrane segmentation was as high as 0.88. By enabling fully automated categorization and segmentation, the proposed algorithm should offer benefits for CNV diagnosis, visualization monitoring.

Ocular cysticercosis is a parasitic infection of the larval form of the pork tapeworm (cysticerci), Taenia solium, migrates into the eye or its adnexal tissues and encysts, leading to severe vitreous opacity and secondary retinal detachment. Acute retinal necrosis (ARN) is a rare infectious viral uveitis syndrome that is caused by members of the herpes family including varicella zoster virus (VZV), herpes simplex virus (HSV), cytomegalovirus (CMV), and less frequently Epstein-Barr virus (EBV). Choroid is most susceptibly involved in ocular infections of mycobacterium tuberculosis. For the solitary choroidal tuberculoma, careful differential diagnosis should be made with choroidal tumors.

Pathologic myopia (PM) is described as myopia accompanied by excessive axial elongation of the globe and characteristic degenerative changes in the posterior segment, with posterior staphyloma as an important hallmark lesion. Myopia is a complex disease and the etiology of myopia is not clearly understood. The pathogenesis of pathologic myopia is possibly related with biomechanics. It is believed that the excessive elongation of the globe and sclera staphyloma are the most important factors in the development of these degenerative changes in pathologic myopia. Rhegmatogenous retinal detachment is a commom complication of pathologic myopia.

Interferons(IFNs) are a large family of cytokines, belonging to glycoproteins. As for the antiviral and antineoplastic activity of IFNs, IFNs were widely studied. Based of recent gene sequence analyses, we found that codon usages were variation in different IFN genes. Codon usage in a sample of 5 genes from the interferon alpha has been analysed using multivariate statistical analysis. Goose and duck IFN-α gene shared the similar patterns, and differ from chicken IFN-α gene codon usage biases pattern. In other words, goose and duck had a much closer relationship than chicken. Asn(L), His(H), Ala(A) and Pro(P) were the preferred amino acids. RSCU values of 25 codons were greater than 1.0, and these codons had a much higher frequency of occurrence. In the accordance with the comparison, E.coli was much suitable for the expression of Tianfu goose IFN-α gene than Yeast and Human system.

The neural transmission delay of DIVA model was studied.Based on the detailed analysis of the speech transmission delay characteristics,the feedforward and feedback control strategy was proposed.It is proved that the delay can be controlled reasonably.Aiming at the network state disturbance caused by parameters changes during the neural network learning process, this paper does related emulation experiments. Experimental results show that this method is effective and gives good robustness.