Blockchain is the core technology used to create the cryptocurrencies, like bitcoin. As part of the fourth industrial revolution since the invention of steam engine, electricity, and information technology, blockchain technology has been applied in many areas such as finance, judiciary, and commerce. The current paper focused on its potential educational applications and explored how blockchain technology can be used to solve some education problems. This article first introduced the features and advantages of blockchain technology following by exploring some of the current blockchain applications for education. Some innovative applications of using blockchain technology were proposed, and the benefits and challenges of using blockchain technology for education were also discussed.

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The indica and japonica rice (Oryza sativa) subspecies differ in nitrate (NO3−) assimilation capacity and nitrogen (N) use efficiency (NUE). Here, we show that a major component of this difference is conferred by allelic variation at OsNR2, a gene encoding a NADH/NADPH-dependent NO3− reductase (NR). Selection-driven allelic divergence has resulted in variant indica and japonica OsNR2 alleles encoding structurally distinct OsNR2 proteins, with indica OsNR2 exhibiting greater NR activity. Indica OsNR2 also promotes NO3− uptake via feed-forward interaction with OsNRT1.1B, a gene encoding a NO3− uptake transporter. These properties enable indica OsNR2 to confer increased effective tiller number, grain yield and NUE on japonica rice, effects enhanced by interaction with an additionally introgressed indica OsNRT1.1B allele. In consequence, indica OsNR2 provides an important breeding resource for the sustainable increases in japonica rice yields necessary for future global food security.

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Summary To formulate a machine learning (ML) model to establish the polymer's structure-property correlation for glass transition temperature , we collect a diverse set of nearly 13,000 real homopolymers from the largest polymer database, PoLyInfo. We train the deep neural network (DNN) model with 6,923 experimental values using Morgan fingerprint representations of chemical structures for these polymers. Interestingly, the trained DNN model can reasonably predict the unknown values of polymers with distinct molecular structures, in comparison with molecular dynamics simulations and experimental results. With the validated transferability and generalization ability, the ML model is utilized for high-throughput screening of nearly one million hypothetical polymers. We identify more than 65,000 promising candidates with > 200°C, which is 30 times more than existing known high-temperature polymers (∼2,000 from PoLyInfo). The discovery of this large number of promising candidates will be of significant interest in the development and design of high-temperature polymers.

Background Follow-up study of Coronavirus disease 2019 (COVID-19) survivors has rarely been reported. We aimed to investigate longitudinal changes in the characteristics of COVID-19 survivors after discharge. Methods and findings A total of 594 COVID-19 survivors discharged from Tongji Hospital in Wuhan from February 10 to April 30, 2020 were included and followed up until May 17, 2021. Laboratory and radiological findings, pulmonary function tests, electrocardiogram, symptoms and signs were analyzed. 257 (51.2%) patients had at least one symptom at 3 months post-discharge, which decreased to 169 (40.0%) and 138 (28.4%) at 6-month and 12-month visit respectively. During follow-up period, insomnia, chest tightness, and fatigue were the most prevalent symptoms. Most laboratory parameters returned to normal, whereas increased incidence of abnormal liver and renal function and cardiovascular injury was evidenced after discharge. Fibrous stripes (213; 42.4%), pleural thickening and adhesions (188; 37.5%) and enlarged lymph nodes (120; 23.9%) were the most common radiographical findings at 3 months post-discharge. The abnormalities of pulmonary function included obstructive, restrictive, and mixed, which were 5.5%, 4.0%, 0.9% at 6 months post, and 1.9%, 4.7%, 0.2% at 12 months. Electrocardiogram abnormalities occurred in 256 (51.0%) patients at 3 months post-discharge, including arrhythmia, ST-T change and conduction block, which increased to 258 (61.1%) cases at 6-month visit and were maintained at high frequency (242;49.8%) at 12-month visit. Conclusions Physiological, laboratory, radiological or electrocardiogram abnormalities, particularly those related to renal, cardiovascular, liver functions are common in patients who recovered from COVID-19 up to 12months post-discharge.

Background Coronavirus disease 2019 (COVID-19) has rapidly become a major international public health concern. This study was designed to evaluate the clinical characteristics and risk factors of COVID-19-associated liver injury. Methods A fraction of 657 COVID-19 patients were retrospectively analyzed. Clinical and laboratory data were derived from electronic medical records and compared between patients with or without liver injury. Multivariate logistic regression method was used to analyze the risk factors for liver injury. Results Among 657 patients, 303 (46.1%) patients had liver injury with higher rate in severe/critically ill patients [148/257 (57.6%)] than those in moderate cases [155/400 (38.8%)]. The incidence of liver injury was much higher in male [192/303 (63.4%)] than female [111/303 (36.6%)], and in severe/critical patients [148/303 (48.8%)] with percutaneous oxygen saturation ≤ 93% [89/279 (31.9%)] or peak body temperature ≥ 38.5 °C [185/301 (61.5%)] on admission. Liver injury-related inflammations included increased white blood cells, neutrophils and decreased lymphocytes. More patients with liver injury than without had increased serum IL-2R, TNFα, ferritin, hsCRP, PCT, ESR, γ-GT, and LDH. Multivariate regression analysis revealed that increasing odds of liver injury were related to male, higher serum hsCRP (≥ 10 mg/L), and neutrophil-to-lymphocyte ratio (NLR) (≥ 5). Moreover, more deceased patients (14/82 (17%)) had significantly elevated serum TBIL than discharged patients [25/532 (4.7%)]. Conclusion Liver injury is a common complication in COVID-19 patients. The potential risk factors of liver injury include male, hsCRP and NLR score. A close monitor of liver function should be warned in COVID-19 patients, especially in severe/critical individuals.

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