Non-Ischemic, Non-Hypoxic Myocardial Injury, and Long-Term Mortality in Patients with Coronavirus Disease 2019: A Retrospective Cohort Study.

Cardiac damage is commonly reported in patients with coronavirus disease 2019 (COVID-19) but its prevalence and impact on the long-term survival of patients remain uncertain. This study aimed to explore the prevalence of myocardial injury and assess its prognostic value in patients with COVID-19. A single-center, retrospective cohort study was performed at the Affiliated Hospital of Jianghan University. Data from 766 patients with confirmed COVID-19 who were hospitalized from December 27, 2019 to April 25, 2020 were collected. Demographic, clinical, laboratory, electrocardiogram, treatment data and all-cause mortality during follow-up were collected and analyzed. Of the 766 patients with moderate to critically ill COVID-19, 86 (11.2%) died after a mean follow-up of 72.8 days. Myocardial injury occurred in 94 (12.3%) patients. The mortality rate was 64.9% (61/94) and 3.7% (25/672) in patients with and without myocardial injury, respectively. Cox regression showed that myocardial injury was an independent risk factor for mortality (hazard ratio: 8.76, 95% confidence interval: 4.76-16.11,    0.001). Of the 90 patients with myocardial injury with electrocardiogram results, sinus tachycardia was present in 29, bundle branch block in 26, low voltage in 10, and abnormal T-wave in 53. COVID-19 not only involves pneumonia but also cardiac damage. Myocardial injury is a common complication and an independent risk factor for mortality in COVID-19 patients

Vaccination against coronavirus disease 2019 in patients with pulmonary hypertension: a national prospective cohort study

Background: Coronavirus disease 2019 (COVID-19) has potential risks for both clinically worsening pulmonary hypertension (PH) and increasing mortality. However, the data regarding the protective role of vaccination in this population are still lacking. This study aimed to assess the safety of approved vaccination for patients with PH. Methods: In this national prospective cohort study, patients diagnosed with PH (World Health Organization [WHO] groups 1 and 4) were enrolled from October 2021 to April 2022. The primary outcome was the composite of PH-related major adverse events. We used an inverse probability weighting (IPW) approach to control for possible confounding factors in the baseline characteristics of patients. Results: In total, 706 patients with PH participated in this study (mean age, 40.3 years; mean duration after diagnosis of PH, 8.2 years). All patients received standardized treatment for PH in accordance with guidelines for the diagnosis and treatment of PH in China. Among them, 278 patients did not receive vaccination, whereas 428 patients completed the vaccination series. None of the participants were infected with COVID-19 during our study period. Overall, 398 patients received inactivated severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) vaccine, whereas 30 received recombinant protein subunit vaccine. After adjusting for baseline covariates using the IPW approach, the odds of any adverse events due to PH in the vaccinated group did not statistically significantly increase (27/428 [6.3%] vs. 24/278 [8.6%], odds ratio = 0.72, P = 0.302). Approximately half of the vaccinated patients reported at least one post-vaccination side effects, most of which were mild, including pain at the injection site (159/428, 37.1%), fever (11/428, 2.6%), and fatigue (26/428, 6.1%). Conclusions: COVID-19 vaccination did not significantly augment the PH-related major adverse events for patients with WHO groups 1 and 4 PH, although there were some tolerable side effects. A large-scale randomized controlled trial is warranted to confirm this finding. The final approval of the COVID-19 vaccination for patients with PH as a public health strategy is promising

Energy Conservation for Indoor Attractions Based on NRBO-LightGBM

In the context of COVID-19, energy conservation is becoming increasingly crucial to the overwhelmed tourism industry, and the heating, ventilation, and air conditioning system (HVAC) is the most energy-consuming factor in the indoor area of scenic spots. As tourist flows are not constant, the intelligent control of an HVAC system is the key to tourist satisfaction and energy consumption management. This paper proposes a noise-reduced and Bayesian-optimized (NRBO) light-gradient-boosting machine (LightGBM) to predict the probability of tourists entering the next scenic spot, hence adopting the feedforward dynamic adaptive adjustment of the ventilation and air conditioning system. The customized model is more robust and effective, and the experimental results in Luoyang City Hall indicate that the proposed system outperforms the baseline LightGBM model and a random-search based method concerning prediction loss by 5.39% and 4.42%, respectively, and saves energy by 23.51%. The study illustrates a promising step in the advancement of tourism energy consumption management and sustainable tourism in the experimental area by improving tourist experiences and conserving energy efficiently, and the software-based system can also be smoothly applied to other indoor scenic spots

An Approach for Predicting Global Ionospheric TEC Using Machine Learning

Accurate corrections for ionospheric total electron content (TEC) and early warning information are crucial for global navigation satellite system (GNSS) applications under the influence of space weather. In this study, we propose to use a new machine learning model—the Prophet model, to predict the global ionospheric TEC by establishing a short-term ionospheric prediction model. We use 15th-order spherical harmonic coefficients provided by the Center for Orbit Determination in Europe (CODE) as the training data set. Historical spherical harmonic coefficient data from 7 days, 15 days, and 30 days are used as the training set to model and predict 256 spherical harmonic coefficients. We use the predicted coefficients to generate a global ionospheric TEC forecast map based on the spherical harmonic function model and select a year with low solar activity (63.4 < F10.7 < 81.8) and a year with the high solar activity (79.5 < F10.7 < 255.0) to carry out a sliding 2-day forecast experiment. Meanwhile, we verify the model performance by comparing the forecasting results with the CODE forecast product (COPG) and final product (CODG). The results show that we obtain the best predictions by using 15 days of historical data as the training set. Compared with the results of CODE’S 1-Day (C1PG) and CODE’S 2-Day (C2PG). The number of days with RMSE better than COPG on the first and second day of the low-solar-activity year is 151 and 158 days, respectively. This statistic for high-solar-activity year is 183 days and 135 days

Molecular identification and phylogenetic analysis of mitogenome of the Xenocypris davidi from Cao’e River

In this study, the complete mitochondrial genome sequence of a Xenocypris davidi from Cao’e River was sequenced. The complete mitogenome of X. davidi was 16,630 bp in length, it contains the structure of 22 transfer RNA genes, 13 protein coding genes, 2 ribosomal RNA genes, and 1 non-coding region. The gene arrangement and organization in the mitogenome of X. davidi were in accordance with other Cyprinidae fishes. The results of phylogenetic analysis revealed that the mitochondrial genome sequence could provide useful information for the conservation genetics and evolution study of X. davidi

An Ionospheric TEC Forecasting Model Based on a CNN-LSTM-Attention Mechanism Neural Network

Ionospheric forecasts are critical for space-weather anomaly detection. Forecasting ionospheric total electron content (TEC) from the global navigation satellite system (GNSS) is of great significance to near-earth space environment monitoring. In this study, we propose a novel ionospheric TEC forecasting model based on deep learning, which consists of a convolutional neural network (CNN), long-short term memory (LSTM) neural network, and attention mechanism. The attention mechanism is added to the pooling layer and the fully connected layer to assign weights to improve the model. We use observation data from 24 GNSS stations from the Crustal Movement Observation Network of China (CMONOC) to model and forecast ionospheric TEC. We drive the model with six parameters of the TEC time series, Bz, Kp, Dst, and F10.7 indices and hour of day (HD). The new model is compared with the empirical model and the traditional neural network model. Experimental results show the CNN-LSTM-Attention neural network model performs well when compared to NeQuick, LSTM, and CNN-LSTM forecast models with a root mean square error (RMSE) and R2 of 1.87 TECU and 0.90, respectively. The accuracy and correlation of the prediction results remained stable in different months and under different geomagnetic conditions

UVA Enhanced Promotive Effects of Blue Light on the Antioxidant Capacity and Anthocyanin Biosynthesis of Pak Choi

Anthocyanins are widely common natural antioxidants and represent an important economic feature in vegetables, but the potential response of UVA–blue co-irradiation on the anthocyanin biosynthesis of pak choi is not clear. Here, we investigated the effects of the supplement of four doses of UVA to blue light on growth, metabolites and the anthocyanin biosynthesis of two cultivars of pak choi. The results revealed that supplementing UVA light to blue light positively affected the growth of the pak choi and elevated the soluble protein content and antioxidant capacity. Especially, when compared with a monochromatic blue light, the anthocyanin synthesis was enhanced with an increase in UVA light strength, which reached a peak value at the strength of 10 μmol·m−2·s−1. Further study revealed that the UVA–blue co-irradiation enhanced the transcription of partial light-induced and anthocyanin structural genes. The intraspecific difference in the expression patterns of MYB1 and PAP1 were observed in these two tested cultivars. MYB1 was significantly up-regulated in red-leaf pak choi, but down-regulated in purple-leaf pak choi. On the contrary, PAP1 was significantly up-regulated in purple-leaf pak choi, but down-regulated in red-leaf pak choi. To sum up, this study established an efficient pre-harvest lighting strategy to elevate the economic value of pak choi

UVA Enhanced Promotive Effects of Blue Light on the Antioxidant Capacity and Anthocyanin Biosynthesis of Pak Choi

Anthocyanins are widely common natural antioxidants and represent an important economic feature in vegetables, but the potential response of UVA&ndash;blue co-irradiation on the anthocyanin biosynthesis of pak choi is not clear. Here, we investigated the effects of the supplement of four doses of UVA to blue light on growth, metabolites and the anthocyanin biosynthesis of two cultivars of pak choi. The results revealed that supplementing UVA light to blue light positively affected the growth of the pak choi and elevated the soluble protein content and antioxidant capacity. Especially, when compared with a monochromatic blue light, the anthocyanin synthesis was enhanced with an increase in UVA light strength, which reached a peak value at the strength of 10 &mu;mol&middot;m&minus;2&middot;s&minus;1. Further study revealed that the UVA&ndash;blue co-irradiation enhanced the transcription of partial light-induced and anthocyanin structural genes. The intraspecific difference in the expression patterns of MYB1 and PAP1 were observed in these two tested cultivars. MYB1 was significantly up-regulated in red-leaf pak choi, but down-regulated in purple-leaf pak choi. On the contrary, PAP1 was significantly up-regulated in purple-leaf pak choi, but down-regulated in red-leaf pak choi. To sum up, this study established an efficient pre-harvest lighting strategy to elevate the economic value of pak choi

Experimental verification of a CFD model for the closed plant factory under artificial lighting

A computational fluid dynamics (CFD) model for the closed plant factory under artificial lighting has been developed in this study, the experimental verification of CFD model with the air velocity value was compared with the measured air temperature value. The results showed that the mean relative error of validation with the air velocity was 15%, and comparable with experimentally observed air temperature profile inside the plant factory with RMSE of 3% which show the utility of CFD to study plant factory microclimatic parameters

Mid-term outcomes of biventricular obstruction and left ventricular outflow tract obstruction after surgery correction in child and adolescent patients with hypertrophic cardiomyopathy - Fig 2

<p>Fig 2a. Preoperative two-dimensional transthoracic echocardiography (tte) parasternal long axis (PLAX) views in a 16-year-old hypertrophic cardiomyopathy patient with BVOTO. (A) PLAX view demonstrating the massive septal hypertrophy and the thickening of the ventricular septum bulging into the LVOT and RVOT resulting in biventricular obstructions (the colour flows). (B) Colour Doppler flow imaging of PLAX view during systole showing high velocity jet flow simultaneously in both LVOT and RVOT. Postoperative PLAX views showing a substantial decrease in the ventricular septum thickness and an increase in the RV and LV cavity sizes during diastole (C) and the LV and RV colour flows showing laminar without evidence of significant residual obstructions during systole (D).RV: right ventricle; RVOT: right ventricular outflow tract; IVS: interventricular septum; LV: left ventricle; LA: left atrium; LVOT: left ventricular outflow tract.AO: aorta. Fig 2b. Preoperational cardiovascular magnetic resonance (CMR) image 3-chamber views during diastole (A) and systole (B) showing remarkable myocardial hypertrophy at the base ventricular level with LVOT and RVOT obstruction. The postoperative CMR images (C, D) showing thinner IVS, wider LVOT and RVOT diameter and larger LV and RV cavity without the projection of septum into RVOT or LVOT after biventricular resection. LA: left atrial; LV: left ventricular.</p