CRISPR/Cas9‐mediated somatic correction of a novel coagulator factor IX gene mutation ameliorates hemophilia in mouse

The X‐linked genetic bleeding disorder caused by deficiency of coagulator factor IX, hemophilia B, is a disease ideally suited for gene therapy with genome editing technology. Here, we identify a family with hemophilia B carrying a novel mutation, Y371D, in the human F9 gene. The CRISPR/Cas9 system was used to generate distinct genetically modified mouse models and confirmed that the novel Y371D mutation resulted in a more severe hemophilia B phenotype than the previously identified Y371S mutation. To develop therapeutic strategies targeting this mutation, we subsequently compared naked DNA constructs versus adenoviral vectors to deliver Cas9 components targeting the F9 Y371D mutation in adult mice. After treatment, hemophilia B mice receiving naked DNA constructs exhibited correction of over 0.56% of F9 alleles in hepatocytes, which was sufficient to restore hemostasis. In contrast, the adenoviral delivery system resulted in a higher corrective efficiency but no therapeutic effects due to severe hepatic toxicity. Our studies suggest that CRISPR/Cas‐mediated in situ genome editing could be a feasible therapeutic strategy for human hereditary diseases, although an efficient and clinically relevant delivery system is required for further clinical studies

Generation of obese rat model by transcription activator-like effector nucleases targeting the leptin receptor gene

Abstract The laboratory rat is a valuable mammalian model organism for basic research and drug discovery. Here we demonstrate an efficient methodology by applying transcription activator-like effector nucleases (TALENs) technology to generate Leptin receptor (Lepr) knockout rats on the Sprague Dawley (SD) genetic background. Through direct injection of in vitro transcribed mRNA of TALEN pairs into SD rat zygotes, somatic mutations were induced in two of three resulting pups. One of the founders carrying bi-allelic mutation exhibited early onset of obesity and infertility. The other founder carried a chimeric mutation which was efficiently transmitted to the progenies. Through phenotyping of the resulting three lines of rats bearing distinct mutations in the Lepr locus, we found that the strains with a frame-shifted or premature stop codon mutation led to obesity and metabolic disorders. However, no obvious defect was observed in a strain with an in-frame 57 bp deletion in the extracellular domain of Lepr. This suggests the deleted amino acids do not significantly affect Lepr structure and function. This is the first report of generating the Lepr mutant obese rat model in SD strain through a reverse genetic approach. This suggests that TALEN is an efficient and powerful gene editing technology for the generation of disease models.</jats:p

Investigation of altered retinal microvasculature in female patients with rheumatoid arthritis: optical coherence tomography angiography detection

Background: Rheumatoid arthritis (RA) is a chronic, systemic autoimmune disorder that primarily causes symmetrical polyarthritis and bone deformity. In RA patients, sight-threatening inflammatory eye complications would be expected. Objective: The objective of the study is to ascertain the macular retinal vessel density changes in RA patients and controls using optical coherence tomography angiography (OCTA), and to investigate the association between disease and microvascular density alterations. Methods: A total of 12 RA patients (24 eyes) and 12 age- and gender-matched control participants (24 eyes) were recruited to the study. We used the Early Treatment Diabetic Retinopathy Study partitioning, hemispheric quadrants and annular partitioning to segment each image into different subregions. The vascular density of superficial retina layer, deep retina layer and conjunctival capillary plexus was quantitatively measured by OCTA and compared with the control group. Correlation analysis was used to explore the relationship between STMI and conjunctival capillaries densities. Results: In the superficial retinal layer, the vascular density of S, I, L, SL, SR, IL and C1-C5 were significantly decreased in the RA group compared with the control group (P<0.05). For the deep retinal layer, the vascular density of S, SL, SR, IL, C1, C2 and C4 also decreased in RA group. A significant positive correlation was indicated between conjunctival vascular and STMI densities (r = 0.713, P<0.05). Conclusion: OCTA results suggest that RA patients present with a reduced macular retinal vascular density. These subtle alterations of ocular microcirculation may precede severe eye involvements and may be a potential biomarker for early distinguishing abnormal eyes from healthy eyes

Spatiotemporal Analysis of Urban Nighttime Light After China Lifted 3-Year-Old COVID-19 Restrictions

China fully lifted restrictions of the COVID-19 pandemic on December 7, 2022. However, the influence of this policy on urban socioeconomic activities is unclear. Remotely sensed nighttime light (NTL) data have been widely used in evaluating public policies in near real time; therefore, this article attempts to explore the spatiotemporal impact of liberalization on mainland China from the perspective of NTL data. Taking 25 cities with different development levels as representatives, based on daily Black Marble NTL product (VNP46A2), we obtained monthly and weekly averaged NTL images before and after liberalization, and calculated NTL changes in concentric rings to detect the spatiotemporal variations from the urban centers, which can reflect the urban vitality to some degree. Experiment results show that urban NTL radiances within 18 km from urban center are generally on the rise after the lifting of restrictions. The increase of NTL around urban core is the most significant, and the increase intensity decreases exponentially (R2 &gt; 0.7) with the distance from city center or near-center for most cities. Furthermore, NTL radiance generally increases significantly within 1&#x2013;2 weeks after the lifting in megacities, and different levels of cities responded differently. NTL of megacities and large cities generally changed more rapidly than small&#x2013;medium cities. Moreover, although mainland China has experienced 3 years of pandemic control, urban development is still underway. The lifting of COVID-19 travel restrictions has brought back the recovery of urban economic vitality. These findings can provide insightful support to urban construction and policy guidance intervention after the pandemic

Nonenzymatic Lactic Acid Detection Using Cobalt Polyphthalocyanine/Carboxylated Multiwalled Carbon Nanotube Nanocomposites Modified Sensor

In this study, a novel cobalt polyphthalocyanine/carboxylic acid functionalized multiwalled carbon nanotube nanocomposite (CoPPc/MWCNTs-COOH) to detect lactic acid was successfully fabricated. The nanocomposite was systematically characterized by scanning electron microscopy, Fourier transform infrared spectroscopy, ultraviolet&ndash;visible absorption spectroscopy, and X-ray photoelectron spectroscopy. The nanocomposite provided excellent conductivity for effective charge transfer and avoided the agglomeration of MWCNTs-COOH. The electrochemical surface area, diffusion coefficient and electron transfer resistance of the CoPPc/MWCNTs-COOH glassy carbon electrode (CoPPc/MWCNTs-COOH/GCE) were calculated as A = 0.49 cm2, D = 9.22 &times; 10&minus;5 cm2/s, and Rct = 200 &Omega;, respectively. The lactic acid sensing performance of the CoPPc/MWCNTs-COOH was evaluated using cyclic voltammetry in 0.1 M PBS (pH 4). The results demonstrated that the novel electrode exhibited excellent electrochemical performance toward lactic acid reduction over a wide concentration range (10 to 240 &mu;M), with a low detection limit (2 &mu;M (S/N = 3)), and a reasonable selectivity against various interferents (ascorbic acid, uric acid, dopamine, sodium chloride, glucose, and hydrogen peroxide). Additionally, the electrode was also successfully applied to quantify lactic acid in rice wine samples, showing great promise for rapid monitoring applications

Nonenzymatic Lactic Acid Detection Using Cobalt Polyphthalocyanine/Carboxylated Multiwalled Carbon Nanotube Nanocomposites Modified Sensor

In this study, a novel cobalt polyphthalocyanine/carboxylic acid functionalized multiwalled carbon nanotube nanocomposite (CoPPc/MWCNTs-COOH) to detect lactic acid was successfully fabricated. The nanocomposite was systematically characterized by scanning electron microscopy, Fourier transform infrared spectroscopy, ultraviolet–visible absorption spectroscopy, and X-ray photoelectron spectroscopy. The nanocomposite provided excellent conductivity for effective charge transfer and avoided the agglomeration of MWCNTs-COOH. The electrochemical surface area, diffusion coefficient and electron transfer resistance of the CoPPc/MWCNTs-COOH glassy carbon electrode (CoPPc/MWCNTs-COOH/GCE) were calculated as A = 0.49 cm2, D = 9.22 × 10−5 cm2/s, and Rct = 200 Ω, respectively. The lactic acid sensing performance of the CoPPc/MWCNTs-COOH was evaluated using cyclic voltammetry in 0.1 M PBS (pH 4). The results demonstrated that the novel electrode exhibited excellent electrochemical performance toward lactic acid reduction over a wide concentration range (10 to 240 μM), with a low detection limit (2 μM (S/N = 3)), and a reasonable selectivity against various interferents (ascorbic acid, uric acid, dopamine, sodium chloride, glucose, and hydrogen peroxide). Additionally, the electrode was also successfully applied to quantify lactic acid in rice wine samples, showing great promise for rapid monitoring applications

Kernel Based Data-Adaptive Support Vector Machines for Multi-Class Classification

Imbalanced data exist in many classification problems. The classification of imbalanced data has remarkable challenges in machine learning. The support vector machine (SVM) and its variants are popularly used in machine learning among different classifiers thanks to their flexibility and interpretability. However, the performance of SVMs is impacted when the data are imbalanced, which is a typical data structure in the multi-category classification problem. In this paper, we employ the data-adaptive SVM with scaled kernel functions to classify instances for a multi-class population. We propose a multi-class data-dependent kernel function for the SVM by considering class imbalance and the spatial association among instances so that the classification accuracy is enhanced. Simulation studies demonstrate the superb performance of the proposed method, and a real multi-class prostate cancer image dataset is employed as an illustration. Not only does the proposed method outperform the competitor methods in terms of the commonly used accuracy measures such as the F-score and G-means, but also successfully detects more than 60% of instances from the rare class in the real data, while the competitors can only detect less than 20% of the rare class instances. The proposed method will benefit other scientific research fields, such as multiple region boundary detection

CO2 emissions from China's iron and steel industry

With the increasing concerns on the severity of climate change, CO2 emissions have become a serious problem in China because of the country&#39;s heavy reliance on fossil fuels as an energy source. Therefore, precise quantification of the CO2 emissions that occur in China is of serious concern. Although most studies focus on CO2 emissions from power plant and cement production, the emissions from iron and steel industry is not well researched. The iron and steel industries, the energy consumptions of which are high compared to the rest of the world, are confronted with an increasing demand to reduce CO2 emissions. Data on CO2 emissions derived from iron and steel-making is a basic requirement for a certificate of CO2 reduction. This is the first study to present an analysis of CO2 emissions from China&#39;s iron and steel industry, and we have estimated the direct emissions, including coal fired emission:non fossil fuel combustion emission and indirect emissions. Carbon flows from blast furnace and basic oxygen furnace steel-making systems are analyzed using Material Flow Analysis. The computation method of coal oxidation factors is built and used to estimate the CO2 emissions of China in 2011 based on the production data of twenty typical iron and steel enterprises. The types of coal involved in iron and steel-making systems include coking coal, sintering (pelletizing) coal and spray-blow coal. It was determined that the coal oxidation factors of coking coal, sintering coal and spray-blow coal are 0.9351, 0.9995, and 0.9745, respectively. Based on the consumption and emission factors of different types of coal used in iron and steel-making systems, the total quantity of CO2 emissions of China in 2011 was estimated to be 1336 million tons, which is 7.06% lower than the result calculated with the parameters offered by the Intergovernmental Panel on Climate Change, in which the contribution of coking coal is the largest at 79.2%. (C) 2016 Elsevier Ltd. All rights reserved.</p