Since its emergence in December 2019, severe acute respiratory syndrome coronavirus 2 (SARS‐CoV‐2) has developed into a global pandemic within a matter of months. While subunit vaccines are one of ...the prominent options for combating coronavirus disease 2019 (COVID‐19), the immunogenicity of spike protein‐based antigens remains unknown. When immunized in mice, the S1 domain induced much higher IgG and IgA antibody levels than the receptor‐binding domain (RBD) and more efficiently neutralized SARS‐CoV‐2 when adjuvanted with alum. It is inferred that a large proportion of these neutralization epitopes are located in the S1 domain but outside the RBD and that some of these are spatial epitopes. This finding indicates that expression systems with posttranslational modification abilities are important to maintain the natural configurations of recombinant spike protein antigens and are critical for effective COVID‐19 vaccines. Further, adjuvants prone to a Th1 response should be considered for S1‐based subunit COVID‐19 vaccines to reduce the potential risk of antibody‐dependent enhancement of infection.
Highlights
Antibodies induced by the S1 domain neutralized SARS‐Cov‐2 more efficiently than those induced by the receptor‐binding domain (RBD). Antibodies induced by the S1 domain produced from HEK293K cells neutralized SARS‐Cov‐2 more efficiently than those induced by the S1 domain produced from E. coli. Both the S1 domain and the RBD induced a highly Th2 response when adjuvanted with alum.
A
bstract
In holographic duality, boundary states that have semiclassical bulk duals must obey inequalities, which bound their subsystems’ von Neumann entropies. Hitherto known inequalities constrain ...entropies of reduced states on up to
N
= 5 disjoint subsystems. Here we report one new such inequality, which involves
N
= 7 disjoint regions. Our work supports a recent conjecture on the structure of holographic inequalities, which predicted the existence and schematic form of the new inequality. We explain the logic and educated guesses by which we arrived at the inequality, and comment on the feasibility of employing similar tactics in a more exhaustive search.
To reveal the inherent relation between energy change and confining pressure during the process of sandstone damage, and its characteristics of energy storage and energy dissipation in different ...deformation stage. Obtaining the mechanical parameters by testing the Sandstone of two1 coal seam roof under uniaxial compression in Zhaogu coalmine, using Particle Flow Code (PFC) and fish program to get the meso-mechanical parameters, studying Sandstone energy evolution mechanism under different confining pressures, and deducing energy strength criterion based on energy principle of rock failure, some main researching results are reached as follows: with the increasing of confining pressure, the Sandstone yield stage and ductility increases, but brittleness decreases; Under higher confining pressure, the elastic strain energy of Sandstone before peak approximately keeps constant in a certain strain range, and rock absorbs all the energy which converts into surface energy required for internal damage development; Under lower confining pressure, Sandstone no longer absorbs energy with increasing strain after peak under lower confining pressure, while it sequentially absorbs energy under higher confining pressure; Under lower confining pressure, the energy Sandstone before peak absorbed mainly converts into elastic strain energy, while under higher confining pressure, dissipation energy significantly increases before peak, which indicates that the degree rock strength loss is higher under higher confining pressure; with the increasing of confining pressure, the limit of elastic strain energy increases and there exists a favourable linear variation relationship; At the peak point, the ratio of elastic strain energy to total energy of Sandstone nonlinearly decreases, while the ratio of dissipation energy to total energy nonlinearly increases with the increasing of confining pressure; According to energy evolution mechanism of rock failure, an energy strength criterion is derived. The criterion equation includes lithology constants and three principal stresses, and its physical meaning is clear. This criterion has an evident advantage than Hoek-Brown and Drucker-Prager criterion in calculation accuracy and can commendably describe rock failure characteristics.
•According to energy evolution mechanism of rock failure, an energy strength criterion is derived.•The criterion equation includes lithology constants and three principal stresses, and its physical meaning is clear.•This criterion has an evident advantage than Hoek-Brown and Drucker-Prager criterion in calculation accuracy and can commendably describe rock failure characteristics.
In this letter, a reduced-dimension multiple signal classification (MUSIC) algorithm for near-field source localization ( i.e ., elevation angle and range) with uniform linear arrays is proposed. By ...splitting the directional matrix in terms of angle and range, the reduced-dimension spectrum function can be constructed, where the 2-D spectral search can be avoided and only the spectral search over angle domain is involved. Moreover, in contrast to a rank-reduced (RARE) algorithm with several times of 1-D spectral searches, the proposed algorithm can obtain the angle estimates by only one 1-D search, and then, the paired range estimates can be directly computed, which remarkably decreases the computational complexity. Furthermore, the proposed algorithm can achieve similar estimation accuracy with the 2-D-MUSIC and RARE algorithms. Simulation results are provided to verify the effectiveness and superiority of the reduced-dimension MUSIC algorithm.
Complex diseases, such as cancer, are often associated with aberrant gene expression at both the transcriptional and post-transcriptional level. Over the past several years, competing endogenous RNAs ...(ceRNAs) have emerged as an important class of post-transcriptional regulators that alter gene expression through a miRNA-mediated mechanism. Recent studies in both solid tumors and hematopoietic malignancies showed that ceRNAs have significant roles in cancer pathogenesis by altering the expression of key tumorigenic or tumor-suppressive genes. Characterizing the identity, function, and mechanism of the ceRNAs will not only further our fundamental understanding of RNA-mediated cancer pathogenesis, but may also shed light on the development of new RNA-based therapeutic strategies for treating cancer.
In this letter, the issue of direction of arrival (DOA) estimation for narrowband signals with two parallel linear arrays is discussed, and an extended DOA-Matrix method is derived. Specifically, the ...proposed method makes full use of the auto-correlation and cross-correlation information by constructing an extended DOA matrix. Subsequently, the auto-paired DOA estimates can be calculated by the eigenvalues and eigenvectors of the extended DOA matrix. Moreover, the proposed method outperforms the traditional DOA-Matrix method which partially neglects the auto-correlation and cross-correlation information. Simulation results are provided to validate the superiority of the proposed method.
This meta-analysis and systematic review aimed to evaluate the global prevalence and risk factors of mental problems (i.e., depression, anxiety, stress, sleep disorder, posttraumatic stress disorder ...(PTSD), burnout, psychological distress, and suicidal ideation) among medical students during the COVID-19 pandemic.
We searched PubMed, Embase, Web of Science, psycARTICLES, PsycINFO, CNKI, and Wan Fang for studies on the prevalence of mental problems among medical students from January 1, 2020, to April 1, 2022. The pooled prevalence was calculated by random-effect models. We performed a narrative review to identify the risk factors.
The meta-analysis included 201 studies (N = 198,000). The prevalence of depression (41 %, 95 % CI, 37–45 %,), anxiety (38 %,95 % CI, 34 %–42 %), stress (34 %, 95 % CI, 27 %–42 %), sleep disorder (52 %, 95 % CI, 44 %–60 %), psychological distress (58 %, 95 % CI, 51 %–65 %), PTSD (34 %, 95 % CI, 22 %–46 %), suicidal ideation (15 %, 95 % CI, 11 %–18 %) and burnout (38 %, 95 % CI, 25 %–50 %) was high. The major risk factors were being female, being junior or preclinical students, exposure to COVID-19, academic stress, psychiatric or physical disorders history, economic trouble, fear of education impairment, online learning trouble, fear of infection, loneliness, low physical activity, low social support, problematic internet or smartphone use, and young age.
Most studies were cross-sectional. Few studies provided a reasonable response rate, suggesting potential selection bias.
The study demonstrated a high prevalence and risk factors for mental problems during COVID-19, calling for mental health services. Our findings are valuable for college and health authorities to identify high-risk students and provide targeted intervention.
•201 studies (N=198,000) from six databases were included.•COVID-19 increased prevalence of depression, anxiety, stress, distress, and suicidal ideation.•The pooled prevalence: depression (41%), anxiety (38%), stress (34%), sleep disorder (52%), psychological distress (58%), PTSD (34%), suicidal ideation (15%) and burnout (38%).•A range of risk factors at multiple levels were identified, most of which were reversible.•The results will help colleges and policymakers to provide targeted mental intervention.
•A CNN-LSTM network was proposed to recognize the basic behaviors of a single cow.•Accurate recognition of single cow’s basic behavior could be got in complex scenes.•It is helpful for building ...intelligent behavior monitor system of dairy cows.
The basic behaviors of dairy cows (drinking, ruminating, walking, standing and lying) are closely related to their physiological health status. Consequently, intelligent behavior recognition is of significance for the automatic diagnosis and precision farming of dairy cows. Realizing the accurate behaviors classification in complex environments involving low quality surveillance videos, complex illumination and weather changes is a key problem in dairy farming that must be solved. In this study, CNN-LSTM (fusion of convolutional neural network and long short-term memory) an algorithm for recognizing the basic behaviors of a single cow, was proposed. First, the VGG16 trained on ImageNet was used as the network skeleton to extract the feature vector sequence corresponding to each video, so as to avoid the shortcomings of traditional feature engineering which were time-consuming and laborious. Then, these features were input Bi-LSTM (bidirectional long short-term memory) classification model, which could extract semantic information of time series data in two directions, so as to realize accurate recognition of dairy cow’s basic behaviors. To verify the effectiveness of the VGG16 feature extraction network used in this research, 1370 segments of approximately 18 h of videos collected from dairy farm monitoring cameras were tested and compared with those of five different feature extraction networks based on VGG19, ResNet18, ResNet101, MobileNet V2 and DenseNet201. Moreover, the effects of changes in illumination, weather, and wind velocity on behaviors recognition were tested and discussed. The test results indicated that the precision of the proposed algorithm for the recognition of the five behaviors ranged from 0.958 to 0.995, the recall ranged from 0.950 to 0.985, and the specificity ranged from 0.974 to 0.991, while the average precision, recall and specificity were 0.971, 0.965 and 0.983, respectively. The average recognition accuracy of the proposed method was 0.976, which was higher than the methods based on VGG19, ResNet18, ResNet101, MobileNet V2 and DenseNe201 by 0.08 × 10−2, 1.97 × 10−2, 2.19 × 10−2, 2.85 × 10−2 and 2.34 × 10−2, respectively. Furthermore, the influences of illumination, weather and wind speed on the algorithm were discussed. The results showed that the difference of behavior recognition accuracy of this method under the above interference was less than 0.02, indicating that the method is good in stability. The research results showed that it was feasible to use the proposed algorithm to recognize behaviors of a single target dairy cow. This study could not only provide valuable references for the behaviors identification and understanding of multiple target dairy cows based on computer vision in complex environments such as low-quality surveillance video, complex illumination and weather variations, but also contribute to their physiological health assessment and remote diagnosis. The study may be valuable for the dairy cows’ prevention and treatment of health and reproduction problems using the “medical-engineering interdisciplinary” approach.
The interfacial recombination at the perovskite/hole conductor interface generally results in significant energy losses in inverted perovskite solar cells (PSCs) with a p–i–n device architecture. ...Herein, a chemical bridge is built at the interface of poly(triarylamine) (PTAA)/perovskites by using 3-(1-pyridinio)-1-propanesulfonate (PPS) molecules to minimize interfacial recombination of charge carriers. Extensively theoretical calculations and experimental studies reveal that the pyridine of PPS molecule and the phenyl group of PTAA could be chemically coupled through π–π stacking, and the sulfonate at the other end of PPS molecule could anchor perovskites through a strong SO···Pb coordination bond. The chemical bridge structure significantly suppresses charge carrier recombination at the interface of PTAA/perovskites. Meanwhile, after incorporation of PPS molecules as an additive in the perovskites to effectively passivate surface defects of perovskites, an efficiency of up to 21.7% with negligible hysteresis is achieved for inverted PSCs.
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