DNA hydrogels, which take advantage of the unique properties of functional DNA motifs, such as specific molecular recognition, programmable and high‐precision assembly, multifunctionality, and ...excellent biocompatibility, have attracted increasing research interest in the past two decades in diverse fields, especially in biosensing and biomedical applications. The responsiveness of smart DNA hydrogels to external stimuli by changing their swelling volume, crosslinking density, and optical or mechanical properties has facilitated the development of DNA‐hydrogel‐based in vitro biosensing systems and actuators. Furthermore, reducing the sizes of DNA hydrogels to the micro‐ and nanoscale leads to better responsiveness and delivery capacity, thereby making them excellent candidates for rapid detection, in vivo real‐time sensing, and drug release applications. Here, the recent progress in the development of smart DNA hydrogels and DNA microgels for biosensing and biomedical applications is summarized, and the current challenges as well as future prospects are also discussed.
Smart DNA hydrogels and microgels are promising materials for biosensing and biomedical applications because of the specific molecular recognition capability, high‐precision assembly, programmable functions, and excellent biocompatibility of functional DNA. Recent progress in the development and applications of smart DNA hydrogels and microgels is summarized and current challenges and future prospects are discussed.
In the early stages of the outbreak of coronavirus disease 2019 (COVID-19) in Hubei, China, the local health-care system was overwhelmed. Physicians and nurses who had no infectious disease expertise ...were recruited to provide care to patients with COVID-19. To our knowledge, no studies on their experiences of combating COVID-19 have been published. We aimed to describe the experiences of these health-care providers in the early stages of the outbreak.
We did a qualitative study using an empirical phenomenological approach. Nurses and physicians were recruited from five COVID-19-designated hospitals in Hubei province using purposive and snowball sampling. They participated in semi-structured, in-depth interviews by telephone from Feb 10 to Feb 15, 2020. Interviews were transcribed verbatim and analysed using Haase's adaptation of Colaizzi's phenomenological method.
We recruited nine nurses and four physicians. Three theme categories emerged from data analysis. The first was “being fully responsible for patients' wellbeing—‘this is my duty’”. Health-care providers volunteered and tried their best to provide care for patients. Nurses had a crucial role in providing intensive care and assisting with activities of daily living. The second category was “challenges of working on COVID-19 wards”. Health-care providers were challenged by working in a totally new context, exhaustion due to heavy workloads and protective gear, the fear of becoming infected and infecting others, feeling powerless to handle patients' conditions, and managing relationships in this stressful situation. The third category was “resilience amid challenges”. Health-care providers identified many sources of social support and used self-management strategies to cope with the situation. They also achieved transcendence from this unique experience.
The intensive work drained health-care providers physically and emotionally. Health-care providers showed their resilience and the spirit of professional dedication to overcome difficulties. Comprehensive support should be provided to safeguard the wellbeing of health-care providers. Regular and intensive training for all health-care providers is necessary to promote preparedness and efficacy in crisis management.
National Key R&D Program of China, Project of Humanities and Social Sciences of the Ministry of Education in China.
The SARS-CoV-2 B.1.1.529 (Omicron) variant contains 15 mutations of the receptor-binding domain (RBD). How Omicron evades RBD-targeted neutralizing antibodies requires immediate investigation. Here ...we use high-throughput yeast display screening
to determine the profiles of RBD escaping mutations for 247 human anti-RBD neutralizing antibodies and show that the neutralizing antibodies can be classified by unsupervised clustering into six epitope groups (A-F)-a grouping that is highly concordant with knowledge-based structural classifications
. Various single mutations of Omicron can impair neutralizing antibodies of different epitope groups. Specifically, neutralizing antibodies in groups A-D, the epitopes of which overlap with the ACE2-binding motif, are largely escaped by K417N, G446S, E484A and Q493R. Antibodies in group E (for example, S309)
and group F (for example, CR3022)
, which often exhibit broad sarbecovirus neutralizing activity, are less affected by Omicron, but a subset of neutralizing antibodies are still escaped by G339D, N440K and S371L. Furthermore, Omicron pseudovirus neutralization showed that neutralizing antibodies that sustained single mutations could also be escaped, owing to multiple synergetic mutations on their epitopes. In total, over 85% of the tested neutralizing antibodies were escaped by Omicron. With regard to neutralizing-antibody-based drugs, the neutralization potency of LY-CoV016, LY-CoV555, REGN10933, REGN10987, AZD1061, AZD8895 and BRII-196 was greatly undermined by Omicron, whereas VIR-7831 and DXP-604 still functioned at a reduced efficacy. Together, our data suggest that infection with Omicron would result in considerable humoral immune evasion, and that neutralizing antibodies targeting the sarbecovirus conserved region will remain most effective. Our results inform the development of antibody-based drugs and vaccines against Omicron and future variants.
The spike protein of SARS-CoV-2 has been undergoing mutations and is highly glycosylated. It is critically important to investigate the biological significance of these mutations. Here, we ...investigated 80 variants and 26 glycosylation site modifications for the infectivity and reactivity to a panel of neutralizing antibodies and sera from convalescent patients. D614G, along with several variants containing both D614G and another amino acid change, were significantly more infectious. Most variants with amino acid change at receptor binding domain were less infectious, but variants including A475V, L452R, V483A, and F490L became resistant to some neutralizing antibodies. Moreover, the majority of glycosylation deletions were less infectious, whereas deletion of both N331 and N343 glycosylation drastically reduced infectivity, revealing the importance of glycosylation for viral infectivity. Interestingly, N234Q was markedly resistant to neutralizing antibodies, whereas N165Q became more sensitive. These findings could be of value in the development of vaccine and therapeutic antibodies.
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•Over 100 mutations were selected for analyses on their infectivity and antigenicity•The dominant D614G itself and combined with other mutations are more infectious•Ablation of both N331 and N343 glycosylation at RBD drastically reduced infectivity•Ten mutations such as N234Q, L452R, A475V, and V483A was markedly resistant to some mAbs
Eighty natural variants and 26 glycosylation spike mutants of SARS-CoV-2 were analyzed in terms of infectivity and antigenicity using high throughput pseudovirus assay in conjunction with neutralizing antibodies.
Proportional hazards model with the biomarker–treatment interaction plays an important role in the survival analysis of the subset treatment effect. A threshold parameter for a continuous biomarker ...variable defines the subset of patients who can benefit or lose from a certain new treatment. In this article, we focus on a continuous threshold effect using the rectified linear unit and propose a gradient descent method to obtain the maximum likelihood estimation of the regression coefficients and the threshold parameter simultaneously. Under certain regularity conditions, we prove the consistency, asymptotic normality and provide a robust estimate of the covariance matrix when the model is misspecified. To illustrate the finite sample properties of the proposed methods, we simulate data to evaluate the empirical biases, the standard errors and the coverage probabilities for both the correctly specified models and misspecified models. The proposed continuous threshold model is applied to a prostate cancer data with serum prostatic acid phosphatase as a biomarker.
Le modèle à risques proportionnels pourvu d’un terme d’interaction entre les biomarqueurs et les traitements joue un rôle important dans l’analyse de survie pour obtenir l’effet du traitement pour des sous-groupes. Un paramètre établit un seuil sur la valeur continue d’un biomarqueur qui définit les sous-groupes qui pourront bénéficier ou pâtir d’un certain nouveau traitement. Les auteurs s’attardent à l’effet d’un seuil continu en utilisant les unités linéaires rectifiées (ReLU). Ils proposent une méthode de descente du gradient afin d’obtenir l’estimateur au maximum de vraisemblance des coefficients de régression et des paramètres de seuil simultanément. Sous certaines conditions de régularité, les auteurs prouvent la convergence et la normalité asymptotique de leurs estimés. Ils fournissent également un estimé robuste de la matrice de covariance lorsque le modèle est mal spécifié. Pour illustrer les propriétés de leurs méthodes sur des échantillons finis, ils simulent des données afin d’évaluer le biais empirique, les erreurs-types et les probabilités de couverture pour des modèles correctement et incorrectement spécifiés. Ils illustrent finalement leur modèle à seuil continu avec des données sur le cancer de la prostate où le sérum de phosphatase prostatique acide est utilisé comme biomarqueur.
Street trees are of great importance to urban green spaces. Quick and accurate segmentation of street trees from high-resolution remote sensing images is of great significance in urban green space ...management. However, traditional segmentation methods can easily miss some targets because of the different sizes of street trees. To solve this problem, we propose the Double-Branch Multi-Scale Contextual Network (DB-MSC Net), which has two branches and a Multi-Scale Contextual (MSC) block in the encoder. The MSC block combines parallel dilated convolutional layers and transformer blocks to enhance the network's multi-scale feature extraction ability. A channel attention mechanism (CAM) is added to the decoder to assign weights to features from RGB images and the normalized difference vegetation index (NDVI). We proposed a benchmark dataset to test the improvement of our network. Experimental research showed that the DB-MSC Net demonstrated good performance compared with typical methods like Unet, HRnet, SETR and recent methods. The overall accuracy (OA) was improved by at least 0.16% and the mean intersection over union was improved by at least 1.13%. The model's segmentation accuracy meets the requirements of urban green space management.
Exosomes play a role as mediators of cell-to-cell communication, thus exhibiting pleiotropic activities to homeostasis regulation. Exosomal non-coding RNAs (ncRNAs), mainly microRNAs (miRNAs), long ...non-coding RNAs (lncRNAs), and circular RNAs (circRNAs), are closely related to a variety of biological and functional aspects of human health. When the exosomal ncRNAs undergo tissue-specific changes due to diverse internal or external disorders, they can cause tissue dysfunction, aging, and diseases. In this review, we comprehensively discuss the underlying regulatory mechanisms of exosomes in human diseases. In addition, we explore the current knowledge on the roles of exosomal miRNAs, lncRNAs, and circRNAs in human health and diseases, including cancers, metabolic diseases, neurodegenerative diseases, cardiovascular diseases, autoimmune diseases, and infectious diseases, to determine their potential implication in biomarker identification and therapeutic exploration.
Postpartum depression (PPD) is the most common psychological condition following childbirth, and may have a detrimental effect on the social and cognitive health of spouses, infants, and children. ...The aim of this study was to complete a comprehensive overview of the current literature on the global epidemiology of PPD. A total of 565 studies from 80 different countries or regions were included in the final analysis. Postpartum depression was found in 17.22% (95% CI 16.00-18.51) of the world's population. Meta-regression analysis showed that study size, country or region development, and country or region income were the causes of heterogeneity. Multivariable meta-regression analysis found that study size and country or area development were the most important predictors. Varied prevalence rates were noted in geographic regions with the highest rate found in Southern Africa (39.96%). Of interested was a significantly lower rate of PPD in developed countries or high-income countries or areas. Furthermore, the findings showed that there was a substantial difference in rates of PPD when marital status, educational level, social support, spouse care, violence, gestational age, breast feeding, child mortality, pregnancy plan, financial difficulties, partnership, life stress, smoking, alcohol intake, and living conditions were considered in the pooled estimates. Our results indicated that one out of every five women experiences PPD which is linked to income and geographic development. It is triggered by a variety of causes that necessitate the attention and committed intervention of primary care providers, clinicians, health authorities, and the general population.
Analysis of instrumental variables is an effective approach to dealing with endogenous variables and unmeasured confounding issue in causal inference. We propose using the piecewise linear model to ...fit the relationship between the continuous instrumental variable and the continuous explanatory variable, as well as the relationship between the continuous explanatory variable and the outcome variable, which generalizes the traditional linear instrumental variable models. The two-stage least square and limited information maximum likelihood methods are used for the simultaneous estimation of the regression coefficients and the threshold parameters. Furthermore, we study the limiting distribution of the estimators in the correctly specified and misspecified models and provide a robust estimation of the variance-covariance matrix. We illustrate the finite sample properties of the estimation in terms of the Monte Carlo biases, standard errors, and coverage probabilities via the simulated data. Our proposed model is applied to an education-salary data, which investigates the causal effect of children’s years of schooling on estimated hourly wage with father’s years of schooling as the instrumental variable.
Pipeline transportation is an economical, safe, and efficient transportation method for transporting oil, natural gas, mineral slurry, and other fluids. Welding is the most critical construction ...process in pipeline engineering and is crucial in the safe operation and service of an entire pipeline system. Theoretically, the girth welded joint is the weakest link in a pipeline system. The unevenness of the structure and performance of the joint caused by welding frequently results in the failure of the welded joint before the failure of the base material of the pipe body, causing the pipeline to leak or even break. For steel pipes used in an acidic corrosive medium environment, the integration of the corrosive medium and mechanical load will accelerate the failure of the welded joint. This article reviews the failure modes of pipeline welded joints in acidic corrosive media, including stress corrosion cracking, hydrogen-induced cracking, and corrosion fracture, and corrosion fatigue considering the diffusion and accumulation of H+ at the crack tip. It also reviews service pipelines in acidic corrosive media. The general processing technology of pipe joint engineering critical assessment (ECA) is investigated to provide a reference for the future development of technology in this field.
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