ABSTRACT
OBJECTIVES: To explore the optimal maintenance dose of caffeine citrate for preterm infants requiring assisted ventilation and caffeine citrate treatment. METHODS: A retrospective analysis was performed on the medical data of 566 preterm infants (gestational age ≤34 weeks) who were treated and required assisted ventilation and caffeine citrate treatment in the neonatal intensive care unit of 30 tertiary hospitals in Jiangsu Province of China between January 1 and December 31, 2019. The 405 preterm infants receiving high-dose (10 mg/kg per day) caffeine citrate after a loading dose of 20 mg/kg within 24 hours after birth were enrolled as the high-dose group. The 161 preterm infants receiving low-dose (5 mg/kg per day) caffeine citrate were enrolled as the low-dose group. RESULTS: Compared with the low-dose group, the high-dose group had significant reductions in the need for high-concentration oxygen during assisted ventilation (P=0.044), the duration of oxygen inhalation after weaning from noninvasive ventilation (P<0.01), total oxygen inhalation time during hospitalization (P<0.01), the proportion of preterm infants requiring noninvasive ventilation again (P<0.01), the rate of use of pulmonary surfactant and budesonide (P<0.05), and the incidence rates of apnea and bronchopulmonary dysplasia (P<0.01), but the high-dose group had a significantly increased incidence rate of feeding intolerance (P=0.032). There were no significant differences between the two groups in the body weight change, the incidence rates of retinopathy of prematurity, intraventricular hemorrhage or necrotizing enterocolitis, the mortality rate, and the duration of caffeine use (P>0.05). CONCLUSIONS: This pilot multicenter study shows that the high maintenance dose (10 mg/kg per day) is generally beneficial to preterm infants in China and does not increase the incidence rate of common adverse reactions. For the risk of feeding intolerance, further research is needed to eliminate the interference of confounding factors as far as possible.
Subject(s)
Caffeine , Respiration, Artificial , Caffeine/therapeutic use , Citrates , Humans , Infant , Infant, Newborn , Infant, Premature , Retrospective StudiesABSTRACT
Currently, COVID-19 caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has been widely spread around the world; nevertheless, so far there exist no specific antiviral drugs for treatment of the disease, which poses great challenge to control and contain the virus. Here, we reported a research finding that SARS-CoV-2 invaded host cells via a novel route of CD147-spike protein (SP). SP bound to CD147, a receptor on the host cells, thereby mediating the viral invasion. Our further research confirmed this finding. First, in vitro antiviral tests indicated Meplazumab, an anti-CD147 humanized antibody, significantly inhibited the viruses from invading host cells, with an EC50 of 24.86 g/mL and IC50 of 15.16 g/mL. Second, we validated the interaction between CD147 and SP, with an affinity constant of 1.85x10-7M. Co-Immunoprecipitation and ELISA also confirmed the binding of the two proteins. Finally, the localization of CD147 and SP was observed in SARS-CoV-2 infected Vero E6 cells by immuno-electron microscope. Therefore, the discovery of the new route CD147-SP for SARS-CoV-2 invading host cells provides a critical target for development of specific antiviral drugs.
ABSTRACT
Robustness is an important property of image hashing. Most of the existing hashing algorithms do not reach good robustness against large-angle rotation. Aiming at this problem, we jointly exploit visual attention model and ring partition to design a novel image hashing, which can make good rotation robustness. In the proposed image hashing, a visual attention model called PFT (Phase spectrum of Fourier Transform) model is used to detect saliency map of preprocessed image. The LL sub-band of saliency map is then divided into concentric circles invariant to rotation by ring partition, and the means and variances of DWT coefficients on concentric circles are taken as image features. Next, these features are encrypted by a chaotic map and the Euclidean distances between normalized encrypted features are finally exploited to generate hash. Similarity between hashes is measured by L 1 norm. Many experimental tests show that our image hashing is robust to digital operations including rotation and reaches good discrimination. Comparisons demonstrate that classification performance of our image hashing outperforms those of some well-known hashing algorithms in terms of receiver operating characteristics curves. Simulation of image copy detection is carried out on an open image database called UCID and the result validates effectiveness of our hashing.
