DeepGrading: Deep Learning Grading of Corneal Nerve Tortuosity

Accurate estimation and quantification of the corneal nerve fiber tortuosity in corneal confocal microscopy (CCM) is of great importance for disease understanding and clinical decision-making. However, the grading of corneal nerve tortuosity remains a great challenge due to the lack of agreements on the definition and quantification of tortuosity. In this paper, we propose a fully automated deep learning method that performs image-level tortuosity grading of corneal nerves, which is based on CCM images and segmented corneal nerves to further improve the grading accuracy with interpretability principles. The proposed method consists of two stages: 1) A pre-trained feature extraction backbone over ImageNet is fine-tuned with a proposed novel bilinear attention (BA) module for the prediction of the regions of interest (ROIs) and coarse grading of the image. The BA module enhances the ability of the network to model long-range dependencies and global contexts of nerve fibers by capturing second-order statistics of high-level features. 2) An auxiliary tortuosity grading network (AuxNet) is proposed to obtain an auxiliary grading over the identified ROIs, enabling the coarse and additional gradings to be finally fused together for more accurate final results. The experimental results show that our method surpasses existing methods in tortuosity grading, and achieves an overall accuracy of 85.64% in four-level classification. We also validate it over a clinical dataset, and the statistical analysis demonstrates a significant difference of tortuosity levels between healthy control and diabetes group. We have released a dataset with 1500 CCM images and their manual annotations of four tortuosity levels for public access. The code is available at: https://github.com/iMED-Lab/TortuosityGrading

Mg3(Bi,Sb)2 single crystals towards high thermoelectric performance

The rapid growth of the thermoelectric cooler market makes the development of novel room temperature thermoelectric materials of great importance. Ternary n-type Mg3(Bi,Sb)2 alloys are promising alternatives to the state-of-the-art Bi2(Te,Se)3 alloys but grain boundary resistance is the most important limitation. n-type Mg3(Bi,Sb)2 single crystals with negligible grain boundaries are expected to have particularly high zT but have rarely been realized due to the demanding Mg-rich growth conditions required. Here, we report, for the first time, the thermoelectric properties of n-type Mg3(Bi,Sb)2 alloyed single crystals grown by a one-step Mg-flux method using sealed tantalum tubes. High weighted mobility ∼140 cm2 V−1 s−1 and a high zT of 0.82 at 315 K are achieved in Y-doped Mg3Bi1.25Sb0.75 single crystals. Through both experimental angle-resolved photoemission spectroscopy and theoretical calculations, we denote the origin of the high thermoelectric performance from a point of view of band widening effect and electronegativity, as well as the necessity to form high Bi/Sb ratio ternary Mg3(Bi,Sb)2 alloys. The present work paves the way for further development of Mg3(Bi,Sb)2 for near room temperature thermoelectric applications

Tulp1 deficiency causes early-onset retinal degeneration through affecting ciliogenesis and activating ferroptosis in zebrafish

Mutations in TUB-like protein 1 (TULP1) are associated with severe early-onset retinal degeneration in humans. However, the pathogenesis remains largely unknown. There are two homologous genes of TULP1 in zebrafish, namely tulp1a and tulp1b. Here, we generated the single knockout (tulp1a(−/−) and tulp1b(−/−)) and double knockout (tulp1-dKO) models in zebrafish. Knockout of tulp1a resulted in the mislocalization of UV cone opsins and the degeneration of UV cones specifically, while knockout of tulp1b resulted in mislocalization of rod opsins and rod-cone degeneration. In the tulp1-dKO zebrafish, mislocalization of opsins was present in all types of photoreceptors, and severe degeneration was observed at a very early age, mimicking the clinical manifestations of TULP1 patients. Photoreceptor cilium length was significantly reduced in the tulp1-dKO retinas. RNA-seq analysis showed that the expression of tektin2 (tekt2), a ciliary and flagellar microtubule structural component, was downregulated in the tulp1-dKO zebrafish. Dual-luciferase reporter assay suggested that Tulp1a and Tulp1b transcriptionally activate the promoter of tekt2. In addition, ferroptosis might be activated in the tulp1-dKO zebrafish, as suggested by the up-regulation of genes related to the ferroptosis pathway, the shrinkage of mitochondria, reduction or disappearance of mitochondria cristae, and the iron and lipid droplet deposition in the retina of tulp1-dKO zebrafish. In conclusion, our study establishes an appropriate zebrafish model for TULP1-associated retinal degeneration and proposes that loss of TULP1 causes defects in cilia structure and opsin trafficking through the downregulation of tekt2, which further increases the death of photoreceptors via ferroptosis. These findings offer insight into the pathogenesis and clinical treatment of early-onset retinal degeneration

The splicing factor DHX38 enables retinal development through safeguarding genome integrity

DEAH-Box Helicase 38 (DHX38) is a pre-mRNA splicing factor and also a disease-causing gene of autosomal recessive retinitis pigmentosa (arRP). The role of DHX38 in the development and maintenance of the retina remains largely unknown. In this study, by using the dhx38 knockout zebrafish model, wedemonstrated that Dhx38 deficiency causes severe differentiation defects and apoptosis of retinal progenitor cells (RPCs) through disrupted mitosis and increased DNA damage. Furthermore, we found a significant accumulation of R-loops in the dhx38-deficient RPCs and human cell lines. Finally, we found that DNA replication stress is the prerequisite for R-loop-induced DNA damage in the DHX38 knockdown cells. Taken together, our study demonstrates a necessary role of DHX38 in the development of retina and reveals a DHX38/R-loop/replication stress/DNA damage regulatory axis that is relatively independent of the known functions of DHX38 in mitosis control

Surface passivation for highly active, selective, stable, and scalable CO2 electroreduction

Electrochemical conversion of CO2 to formic acid using Bismuth catalysts is one the most promising pathways for industrialization. However, it is still difficult to achieve high formic acid production at wide voltage intervals and industrial current densities because the Bi catalysts are often poisoned by oxygenated species. Herein, we report a Bi3S2 nanowire-ascorbic acid hybrid catalyst that simultaneously improves formic acid selectivity, activity, and stability at high applied voltages. Specifically, a more than 95% faraday efficiency was achieved for the formate formation over a wide potential range above 1.0 V and at ampere-level current densities. The observed excellent catalytic performance was attributable to a unique reconstruction mechanism to form more defective sites while the ascorbic acid layer further stabilized the defective sites by trapping the poisoning hydroxyl groups. When used in an all-solid-state reactor system, the newly developed catalyst achieved efficient production of pure formic acid over 120 hours at 50 mA cm–2 (200 mA cell current)

Flexible operation of coal fired power plant integrated with post combustion CO2 capture using model predictive control

The growing demand for CO2 capture from coal-fired power plant (CFPP) has increased the need to improve the dynamic operability of the integrated power generation-CO2 capture plant. Nevertheless, high-level operation of the entire system is difficult to achieve due to the strong interactions between the CFPP and post combustion CO2 capture (PCC) unit. In addition, the control tasks of power generation and CO2 removal are in conflict, since the operation of both processes requires consuming large amount of steam. For these reasons, this paper develops a model for the integrated CFPP-PCC process and analyzes the dynamic relationships for the key variables within the integrated system. Based on the investigation, a centralized model predictive controller is developed to unify the power generation and PCC processes together, involving the key variables of the two systems and the interactions between them. Three operating modes are then studied for the predictive control system with different focuses on the overall system operation; power generation demand tracking and satisfying the CO2 capture requirement. The predictive controller can achieve a flexible operation of the integrated CFPP- PCC system and fully exert its functions in power generation and CO2 reduction

SnO2Nanowire Arrays and Electrical Properties Synthesized by Fast Heating a Mixture of SnO2and CNTs Waste Soot

SnO2nanowire arrays were synthesized by fast heating a mixture of SnO2and the carbon nanotubes waste soot by high-frequency induction heating. The resultant SnO2nanowires possess diameters from 50 to 100 nm and lengths up to tens of mircrometers. The field-effect transistors based on single SnO2nanowire exhibit that as-synthesized nanowires have better transistor performance in terms of transconductance and on/off ratio. This work demonstrates a simple technique to the growth of nanomaterials for application in future nanoelectronic devices

The major causes and risk factors of total and cause-specific mortality during 5.4-year follow-up: the Shanghai Changfeng Study

To investigate the major causes and predictive factors of death in a middle-aged and elderly Chinese population. A total of 6591 residents aged ≥ 45 years from Shanghai Changfeng community were followed up for an average of 5.4 years. The causes of death were coded according to the 10th Revision of International Classification of Diseases. The mortality rate was calculated by person-years of follow up and age-standardized according to the 2010 Chinese census data. Multivariable-adjusted Cox proportional hazards model was performed to investigate the predictors of all-cause and cause-specific mortality. During the total follow-up of 35,739 person-years, 370 deaths were documented (157 from malignant neoplasms, 70 from heart diseases, 68 from cerebrovascular diseases, 75 from other causes). The age-standardized all-cause mortality rate was 798.2 per 100,000 person-years (927.9 among men and 716.7 among women). Results from multivariable analyses showed that aging, diabetes, and osteoporosis at baseline were independent predictors of all-cause mortality, with hazard ratios (HR) of 1.11 (95% CI 1.10–1.13), 1.91 (1.51–2.42), and 1.71 (1.24–2.35), respectively. The population attributable risk percent of diabetes and osteoporosis was 19.7% and 11.7%, respectively. Cigarette smoking was associated with a higher risk of all-cause mortality in men (HR and 95%CI 1.44, 1.01–2.06). In women, diabetes and osteoporosis were related to a higher risk of cardiovascular mortality (3.27, 1.82–5.88 and 1.89, 1.04–3.46, respectively). While in men, osteoporosis was related to a higher risk of malignant neoplasms mortality (2.39, 1.07–5.33). Malignant neoplasms, heart diseases, and cerebrovascular diseases are the leading causes of death. Aging, smoking, underweight, diabetes, and osteoporosis are independent predictors of premature death among middle-aged and elderly Chinese community population. Moreover, there may have been some differences in the causes and predictors of premature death between men and women