Psychological health problems, especially emotional disorders, are common among adolescents. The epidemiology of emotional disorders is greatly influenced by stressful events. This study sought to ...assess the prevalence rate and socio-demographic correlates of depressive and anxiety symptoms among Chinese adolescents affected by the outbreak of COVID-19. We conducted a cross-sectional study among Chinese students aged 12–18 years during the COVID-19 epidemic period. An online survey was used to conduct rapid assessment. A total of 8079 participants were involved in the study. An online survey was used to collect demographic data, assess students’ awareness of COVID-19, and assess depressive and anxiety symptoms with the Patient Health Questionnaire (PHQ-9) and the Generalized Anxiety Disorder (GAD-7) questionnaire, respectively. The prevalence of depressive symptoms, anxiety symptoms, and a combination of depressive and anxiety symptoms was 43.7%, 37.4%, and 31.3%, respectively, among Chinese high school students during the COVID-19 outbreak. Multivariable logistic regression analysis revealed that female gender was the higher risk factor for depressive and anxiety symptoms. In terms of grades, senior high school was a risk factor for depressive and anxiety symptoms; the higher the grade, the greater the prevalence of depressive and anxiety symptoms. Our findings show there is a high prevalence of psychological health problems among adolescents, which are negatively associated with the level of awareness of COVID-19. These findings suggest that the government needs to pay more attention to psychological health among adolescents while combating COVID-19.
Conspectus Expansion of the genetic code allows unnatural amino acids (Uaas) to be site-specifically incorporated into proteins in live biological systems, thus enabling novel properties selectively ...introduced into target proteins in vivo for basic biological studies and for engineering of novel biological functions. Orthogonal components including tRNA and aminoacyl-tRNA synthetase (aaRS) are expressed in live cells to decode a unique codon (often the amber stop codon UAG) as the desired Uaa. Initially developed in E. coli, this methodology has now been expanded in multiple eukaryotic cells and animals. In this Account, we focus on addressing various biological challenges for rewriting the genetic code, describing impacts of code expansion on cell physiology and discussing implications for fundamental studies of code evolution. Specifically, a general method using the type-3 polymerase III promoter was developed to efficiently express prokaryotic tRNAs as orthogonal tRNAs and a transfer strategy was devised to generate Uaa-specific aaRS for use in eukaryotic cells and animals. The aaRSs have been found to be highly amenable for engineering substrate specificity toward Uaas that are structurally far deviating from the native amino acid, dramatically increasing the stereochemical diversity of Uaas accessible. Preparation of the Uaa in ester or dipeptide format markedly increases the bioavailability of Uaas to cells and animals. Nonsense-mediated mRNA decay (NMD), an mRNA surveillance mechanism of eukaryotic cells, degrades mRNA containing a premature stop codon. Inhibition of NMD increases Uaa incorporation efficiency in yeast and Caenorhabditis elegans. In bacteria, release factor one (RF1) competes with the orthogonal tRNA for the amber stop codon to terminate protein translation, leading to low Uaa incorporation efficiency. Contradictory to the paradigm that RF1 is essential, it is discovered that RF1 is actually nonessential in E. coli. Knockout of RF1 dramatically increases Uaa incorporation efficiency and enables Uaa incorporation at multiple sites, making it feasible to use Uaa for directed evolution. Using these strategies, the genetic code has been effectively expanded in yeast, mammalian cells, stem cells, worms, fruit flies, zebrafish, and mice. It is also intriguing to find out that the legitimate UAG codons terminating endogenous genes are not efficiently suppressed by the orthogonal tRNA/aaRS in E. coli. Moreover, E. coli responds to amber suppression pressure promptly using transposon insertion to inactivate the introduced orthogonal aaRS. Persistent amber suppression evading transposon inactivation leads to global proteomic changes with a notable up-regulation of a previously uncharacterized protein YdiI, for which an unexpected function of expelling plasmids is discovered. Genome integration of the orthogonal tRNA/aaRS in mice results in minor changes in RNA transcripts but no significant physiological impairment. Lastly, the RF1 knockout E. coli strains afford a previously unavailable model organism for studying otherwise intractable questions on code evolution in real time in the laboratory. We expect that genetically encoding Uaas in live systems will continue to unfold new questions and directions for studying biology in vivo, investigating the code itself, and reprograming genomes for synthetic biology.
Classification can often benefit from efficient feature selection. However, the presence of linearly nonseparable data, quick response requirement, small sample problem and noisy features makes the ...feature selection quite challenging. In this work, a class separability criterion is developed in a high-dimensional kernel space, and feature selection is performed by the maximization of this criterion. To make this feature selection approach work, the issues of automatic kernel parameter tuning, the numerical stability, and the regularization for multi-parameter optimization are addressed. Theoretical analysis uncovers the relationship of this criterion to the radius-margin bound of the SVMs, the KFDA, and the kernel alignment criterion, providing more insight on using this criterion for feature selection. This criterion is applied to a variety of selection modes with different search strategies. Extensive experimental study demonstrates its efficiency in delivering fast and robust feature selection.
A
bstract
Combining the Higgs searches at the LHC, we study the Higgs inflation in the type-I and type-II two-Higgs-doublet models with non-minimally couplings to gravity. After imposing relevant ...theoretical and experimental constraints, we find that the Higgs inflation imposes stringent constraints on the mass splitting between
A
,
H
±
, and
H
, and they tend to be nearly degenerate in mass with increasing of their masses. The direct searches for Higgs at the LHC can exclude many points achieving Higgs inflation in the region of
m
H
(
m
A
)
<
450 GeV in the type-I model, and impose a lower bound on tan
β
for the type-II model. The Higgs inflation disfavors the wrong sign Yukawa coupling region of type-II model. In the parameter space achieving the Higgs inflation, the type-I and type-II models can produce a first order electroweak phase transition, but
v
c
/
T
c
is much smaller than 1.0.
Acidity is a hallmark of malignant tumor, representing a very efficient mechanism of chemoresistance. Proton pump inhibitors (PPI) at high dosage have been shown to sensitize chemoresistant human ...tumor cells and tumors to cytotoxic molecules. The aim of this pilot study was to investigate the efficacy of PPI in improving the clinical outcome of docetaxel + cisplatin regimen in patients with metastatic breast cancer (MBC).
Patients enrolled were randomly assigned to three arms: Arm A, docetaxel 75 mg/m(2) followed by cisplatin 75 mg/m(2) on d4, repeated every 21 days with a maximum of 6 cycles; Arm B, the same chemotherapy preceded by three days esomeprazole (ESOM) 80 mg p.o. bid, beginning on d1 repeated weekly. Weekly intermittent administration of ESOM (3 days on 4 days off) was maintained up to maximum 66 weeks; Arm C, the same as Arm B with the only difference being dose of ESOM at 100 mg p.o. bid. The primary endpoint was response rate.
Ninety-four patients were randomly assigned and underwent at least one injection of chemotherapy. Response rates for arm A, B and C were 46.9, 71.0, and 64.5 %, respectively. Median TTP for arm A (n = 32), B (n = 31), C (n = 31) were 8.7, 9.4, and 9.7 months, respectively. A significant difference was observed between patients who had taken PPI and who not with ORR (67.7 % vs. 46.9 %, p = 0.049) and median TTP (9.7 months vs. 8.7 months, p = 0.045) corrected. Exploratory analysis showed that among 15 patients with triple negative breast cancer (TNBC), this difference was bigger with median TTP of 10.7 and 5.8 months, respectively (p = 0.011). PPI combination showed a marked effect on OS as well, while with a borderline significance (29.9 vs. 19.2 months, p = 0.090). No additional toxicity was observed with PPI.
The results of this pilot clinical trial showed that intermittent high dose PPI enhance the antitumor effects of chemotherapy in MBC patients without evidence of additional toxicity, which requires urgent validation in a multicenter, randomized, phase III trial.
Clinicaltrials.gov identifier: NCT01069081 .
Electrochemical reduction of carbon dioxide (CO2) is substantially researched due to its potential for storing intermittent renewable electricity and simultaneously helping mitigating the pressing ...CO2 emission concerns. The major challenge of electrochemical CO2 reduction lies on having good controls of this reaction due to its complicated reaction networks and its unusual sensitivity to the dynamic changes of the catalyst structure (chemical states, compositions, facets and morphology, etc.), and to the non‐catalyst components at the electrode/electrolyte interface, in another word the reaction environments. To date, a comprehensive analysis on the interplays between the above catalyst‐dynamic‐changes/reaction environments and the CO2 reduction performance is rare, if not none. In this review, the catalyst dynamic changes observed during the catalysis are discussed based on the recent reports of electrochemical CO2 reduction. Then, the above dynamic changes are correlated to their effects on the catalytic performance. The influences of the reaction environments on the performance of CO2 reduction are also discussed. Finally, some perspectives on future investigations are offered with the aim of understanding the origins of the effects from the catalyst dynamic changes and the reaction environments, which will allow one to better control the CO2 reduction toward the desired products.
This review focus on understanding the origin of the dynamic changes at the catalyst–electrolyte interface, and uncovering the interplays between these changes and the CO2 reduction performance, the obtained insights can guide the design of catalysts and reactors for the efficient electrochemical CO2 reduction.
Macrophage M1/M2 polarization Yunna, Chen; Mengru, Hu; Lei, Wang ...
European journal of pharmacology,
06/2020, Volume:
877
Journal Article
Peer reviewed
Macrophages can be affected by a variety of factors to change their phenotype and thus affect their function. Activated macrophages are usually divided into two categories, M1-like macrophages and ...M2-like macrophages. Both M1 macrophages and M2 macrophages are closely related to inflammatory responses, among which M1 macrophages are mainly involved in pro-inflammatory responses and M2 macrophages are mainly involved in anti-inflammatory responses. Improving the inflammatory environment by modulating the activation state of macrophages is an effective method for the treatment of diseases. In this review, we analyzed the mechanism of macrophage polarization from the tumor microenvironment, nanocarriers, nuclear receptor PPARγ, phagocytosis, NF-κB signaling pathways, and other pathways.
In vivo cell fate conversions have emerged as potential regeneration-based therapeutics for injury and disease. Recent studies reported that ectopic expression or knockdown of certain factors can ...convert resident astrocytes into functional neurons with high efficiency, region specificity, and precise connectivity. However, using stringent lineage tracing in the mouse brain, we show that the presumed astrocyte-converted neurons are actually endogenous neurons. AAV-mediated co-expression of NEUROD1 and a reporter specifically and efficiently induces reporter-labeled neurons. However, these neurons cannot be traced retrospectively to quiescent or reactive astrocytes using lineage-mapping strategies. Instead, through a retrograde labeling approach, our results reveal that endogenous neurons are the source for these viral-reporter-labeled neurons. Similarly, despite efficient knockdown of PTBP1 in vivo, genetically traced resident astrocytes were not converted into neurons. Together, our results highlight the requirement of lineage-tracing strategies, which should be broadly applied to studies of cell fate conversions in vivo.
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•NEUROD1 specifically and efficiently induces viral-reporter-labeled neurons in vivo•Lineage-traced resident astrocytes are not converted into neurons by NEUROD1•NEUROD1-induced, viral-reporter-labeled neurons are actually endogenous neurons•Knockdown of PTBP1 fails to convert brain astrocytes into neurons in vivo
Stringent lineage tracings reveal that the presumed astrocyte-converted neurons are not originated from the resident astrocytes but from the AAV-infected endogenous neurons.
A material with superhydrophobic and anti‐ice/de‐icing properties, which has a micro‐/nanostructured surface, is produced by a straightforward method. This material comprises a poly(dimethylsiloxane) ...(PDMS) microstructure with ZnO nanohairs and shows excellent water and ice repellency even at low temperatures (−20 °C) and relatively high humidity (90%) for over three months. These results are expected to be helpful for designing smart, non‐wetting materials that can be adapted to low‐temperature environments for the development of anti‐icing systems.
•We provide a whole picture about deep learning-based visual place recognition.•The differences and similarities between VPR and image retrieval are included.•We review different kinds of CNN-based ...methods, novel CNN features and datasets for VPR.•New tools such as GANs and multi-modality feature fusion are discussed for VPR.•We discuss challenges, open issues and future directions of visual place recognition.
Visual place recognition has attracted widespread research interest in multiple fields such as computer vision and robotics. Recently, researchers have employed advanced deep learning techniques to tackle this problem. While an increasing number of studies have proposed novel place recognition methods based on deep learning, few of them has provided a whole picture about how and to what extent deep learning has been utilized for this issue. In this paper, by delving into over 200 references, we present a comprehensive survey that covers various aspects of place recognition from deep learning perspective. We first present a brief introduction of deep learning and discuss its opportunities for recognizing places. After that, we focus on existing approaches built upon convolutional neural networks, including off-the-shelf and specifically designed models as well as novel image representations. We also discuss challenging problems in place recognition and present an extensive review of the corresponding datasets. To explore the future directions, we describe open issues and some new tools, for instance, generative adversarial networks, semantic scene understanding and multi-modality feature learning for this research topic. Finally, a conclusion is drawn for this paper.
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