New insights into autophagy in inflammatory subtypes of asthma

Asthma is a heterogeneous airway disease characterized by airway inflammation and hyperresponsiveness. Autophagy is a self-degrading process that helps maintain cellular homeostasis. Dysregulation of autophagy is involved in the pathogenesis of many diseases. In the context of asthma, autophagy has been shown to be associated with inflammation, airway remodeling, and responsiveness to drug therapy. In-depth characterization of the role of autophagy in asthma can enhance the understanding of the pathogenesis, and provide a theoretical basis for the development of new biomarkers and targeted therapy for asthma. In this article, we focus on the relationship of autophagy and asthma, and discuss its implications for asthma pathogenesis and treatment

The Coupled Within- and Between-Host Dynamics in the Evolution of HIV/AIDS in China

In this work, we develop and analyze mathematical models for the coupled within-host and between-host dynamics caricaturing the evolution of HIV/AIDS. The host population is divided into susceptible, the infected without receiving treatment and the infected receiving ART treatment in accordance with China’s Four-Free-One-Care Policy. The within-host model is a typical ODE model adopted from literatures. The between-host model incorporates age-since-infection described by a system of integrodifferential equations. The two models are coupled via the viral load and number of CD4+ T cells of within the hosts. For the between-host model with an arbitrarily selected HIV infected individual, we focus on the analyses of the basic reproduction number R0 and the stabilities of equilibria. Through simulations we also find that the within-host dynamics does influence the between-host dynamics, and the nesting of within-host and between-host play a very important role in the HIV/AIDS evolution

Relationship of chest CT score with clinical characteristics of 108 patients hospitalized with COVID-19 in Wuhan, China

BACKGROUND: In December 2019, the outbreak of a disease subsequently termed COVID-19 occurred in Wuhan, China. The number of cases increased rapidly and spread to six continents. However, there is limited information on the chest computed tomography (CT) results of affected patients. Chest CT can assess the severity of COVID-19 and has sufficient sensitivity to assess changes in response to glucocorticoid therapy. OBJECTIVE: Analyze COVID-19 patients to determine the relationships of clinical characteristics, chest CT score, and levels of inflammatory mediators. METHODS: This retrospective, single-center case series of 108 consecutive hospitalized patients with confirmed COVID-19 at Tongji Hospital, Tongji Medical College of HUST (Wuhan, China) examined patients admitted from January 28 to February 20, 2020. Patient demographics, comorbidities, clinical findings, chest CT results, and CT scores of affected lung parenchyma were recorded. The relationships between chest CT score with levels of systemic inflammatory mediators were determined. RESULTS: All patients exhibited signs of significant systemic inflammation, including increased levels of C-reactive protein (CRP), erythrocyte sedimentation rate (ESR), procalcitonin, chest CT score, and a decreased lymphocyte (LY) count. Chest CT score had positive associations with white blood cell (WBC) count, CRP, ESR, procalcitonin, and abnormal coagulation function, and a negative association with LY count. Treatment with a glucocorticoid increased the LY count, reduced the CT score and CRP level, and improved coagulation function. CONCLUSIONS: COVID-19 infection is characterized by a systemic inflammatory response that affects the lungs, blood, digestive system, and circulatory systems. The chest CT score is a good indicator of the extent of systemic inflammation. Glucocorticoid treatment appears to reduce systemic inflammation in these patients

Transcriptional changes in litchi (<i>Litchi chinensis</i> Sonn.) inflorescences treated with uniconazole

<div><p>In <i>Arabidopsis</i>, treating shoots with uniconazole can result in enhanced primary root elongation and bolting delay. Uniconazole spraying has become an important cultivation technique in controlling the flowering and improving the fruit-setting of litchi. However, the mechanism by which uniconazole regulates the complicated developmental processes in litchi remains unclear. This study aimed to determine which signal pathways and genes drive the responses of litchi inflorescences to uniconazole treatment. We monitored the transcriptional activity in inflorescences after uniconazole treatment by Illumina sequencing technology. The global expression profiles of uniconazole-treated litchi inflorescences were compared with those of the control, and 4051 differentially expressed genes were isolated. KEGG pathway enrichment analysis indicated that the plant hormone signal transduction pathway served key functions in the flower developmental stage under uniconazole treatment. Basing on the transcriptional analysis of genes involved in flower development, we hypothesized that uniconazole treatment increases the ratio of female flowers by activating the transcription of pistil-related genes. This phenomenon increases opportunities for pollination and fertilization, thereby enhancing the fruit-bearing rate. In addition, uniconazole treatment regulates the expression of unigenes involved in numerous transcription factor families, especially the bHLH and WRKY families. These findings suggest that the uniconazole-induced morphological changes in litchi inflorescences are related to the control of hormone signaling, the regulation of flowering genes, and the expression levels of various transcription factors. This study provides comprehensive inflorescence transcriptome data to elucidate the molecular mechanisms underlying the response of litchi flowers to uniconazole treatment and enumerates possible candidate genes that can be used to guide future research in controlling litchi flowering.</p></div

Differentially expressed genes encoding transcription factors following uniconazole treatment.

<p>Different shades of red and green express the extent of change according to the color bar provided in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0176053#pone.0176053.g004" target="_blank">Fig 4</a>. Red and green indicate upregulation and downregulation of genes, respectively, whereas white indicates that no change was detected after uniconazole treatment.</p

Effects of uniconazole on inflorescence development and flowering in litchi.

<p>(A) Inflorescence state before uniconazole application (30 days after floral evocation); (B) Inflorescence states from untreated control (B1) and uniconazole-treated (B2) plants four weeks after treatment (full-bloom stage of untreated control); (C) Clusters from untreated control (C1) and uniconazole-treated (C2) plants six weeks after treatment (fruitlet stage after abscission); (D) D1 and D2 represent the magnification of the portions of C1 and C2, respectively; (E) Effects of uniconazole on the blossoming process of male flower and female flower.</p

Functional analysis of DEGs based on the KEGG pathway.

<p>Pathways with a <i>Q</i>-value ≤ 0.05 significantly enriched in DEGs were analyzed in the comparison between treatment and control at the flowering stages. The degrees of KEGG enrichment can be measured by the richness factor, <i>Q</i>-value, and gene number enriched in this pathway. The right <i>y</i>-axis represents the KEGG pathway, and the <i>x</i>-axis shows the richness factor, which denotes the ratio of the number of DEGs to the number of annotated genes enriched in this pathway.</p

Effects of uniconazole treatment on flowering and fruiting in litchi.

<p>Effects of uniconazole treatment on flowering and fruiting in litchi.</p

Heat map diagrams of relative expression levels of DEGs in the hormone signal transduction pathways.

<p>DEGs in the signal transduction pathways identified in KEGG pathway enrichment analysis are shown as auxin (A), ethylene (B), abscisic acid brassinosteroid (C), brassinosteroid (D), salicylic acid (E), and jasmonic acid (F). Ratios are expressed as log2 RPKM (treatment/control) values. Red and green colors indicate gene upregulation and downregulation, respectively.</p