Combined therapy of 5-aminolevulinic acid photodynamic therapy and intense pulsed light for rosacea.

Rosacea is difficult to treat. Therefore, new alternative modalities are necessary to demonstrate. The present study was conducted to assess the efficacy and safety of the combined therapy of 5-aminolevulinic acid photodynamic therapy (ALA-PDT) and intense pulsed light (IPL) for rosacea to provide a new treatment option for rosacea. The study was conducted from November 2017 to April 2019 at the Department of Dermatology, The First Hospital of China Medical University. Patients aged 18-65 years and diagnosed clinically as erythematotelangiectatic (ET) or papulopustular (PP) rosacea were enrolled. Three times of ALA-PDT at 10 days interval followed by 3 times of IPL at 3-4 weeks interval were defined as 1 session and applied to the whole face of each patient. ALA-PDT: 5% ALA, red light (fluency dose 60-100 mW/cm2, 20 min); IPL: 560/590/640 nm, double/triple-pulse mode, pulse width 3.0 to 4.5 ms, delay time 30-40 ms, energy fluency 14-17 J/cm2. Ten patients were enrolled in the study. Among them, 4 patients received only 1 session, while 6 patients received 2 sessions. After all treatments, 50% of patients achieved 75-100% improvement, and 30% achieved 50-75% improvement. Forty percent of patients were graded very satisfaction and 30% graded moderate satisfaction. All noninvasive measurements showed no significant differences among all time points (p > 0.05). The side effects were pain, burning sensation, itching, erythema, desquamation, slight edema, slight exudation, and hyperpigmentation. All of which were tolerable and recovered in a few days. The combined therapy of ALA-PDT and IPL showed an effective option for rosacea with a safety profile.

CircRNA_0263 and circRNA_1507 are dysregulated in a rat model of atrial fibrosis induced by chronic intermittent hypoxia.

Aims: This study aimed to characterize circular RNA (circRNA) profiles associated with atrial fibrosis-related atrial fibrillation (AF) and reveal critical circRNAs for AF. Methods: Sprague Dawley rats were randomly divided into control and atrial fibrosis-related AF groups (n = 15 in each group). The rats in the atrial fibrosis-related AF group were induced by chronic intermittent hypoxia (CIH), and then confirmed by electrocardiograms, echocardiography, hematoxylin-eosin staining, Masson staining, immunohistochemistry assays and western blotting. After that, the atrial tissues were sent for circRNA sequencing, and the differentially expressed circRNAs were identified and validated by quantitative real-time polymerase chain reaction (qRT-PCR). Finally, a series of cell experiments were performed to explore the roles of two crucial circRNAs in rat atrial fibroblasts. Results: A CIH-induced AF model was successfully established in the rats. After sequencing, five upregulated and 11 downregulated circRNAs were identified in the CIH-induced AF group. These dysregulated circRNAs were primarily associated with "carbohydrate metabolism" and "cardiovascular diseases". Two circRNAs (circRNA_0263 and circRNA_1507) were predicted to regulate target gene expression by interacting with corresponding miRNAs, including rno-miR-29b-5p, rno-miR-29b-3p, rno-miR-496-5p, rno-miR-136-5p, and novel123-mature. Additionally, circRNA_0263 knockdown and circRNA_1507 overexpression inhibited the cell viability of fibroblasts, and downregulated the expression of fibrosis-related proteins. Conclusion: A series of circRNAs were identified as dysregulated in an AF rat model, and circRNA_0263 and circRNA_1507 might be crucial for atrial fibrosis-related AF development by competing with several miRNAs.

Integrated whole transcriptome analysis for the crucial regulators and functional pathways related to cardiac fibrosis in rats.

BACKGROUND: Cardiac fibrosis has gradually gained significance in the field of cardiovascular disease; however, its specific pathogenesis remains unclear. This study aims to establish the regulatory networks based on whole-transcriptome RNA sequencing analyses and reveal the underlying mechanisms of cardiac fibrosis. METHODS: An experimental model of myocardial fibrosis was induced using the chronic intermittent hypoxia (CIH) method. Expression profiles of long non-coding RNA (lncRNA), microRNA (miRNA), and messenger RNA (mRNA) were acquired from right atrial tissue samples of rats. Differentially expressed RNAs (DERs) were identified, and functional enrichment analysis was performed. Moreover, a protein-protein interaction (PPI) network and competitive endogenous RNA (ceRNA) regulatory network that are related to cardiac fibrosis were constructed, and the relevant regulatory factors and functional pathways were identified. Finally, the crucial regulators were validated using qRT-PCR. RESULTS: DERs, including 268 lncRNAs, 20 miRNAs, and 436 mRNAs, were screened. Further, 18 relevant biological processes, such as "chromosome segregation, " and 6 KEGG signaling pathways, such as "cell cycle, " were significantly enriched. The regulatory relationship of miRNA-mRNA-KEGG pathways showed eight overlapping disease pathways, including "pathways in cancer." In addition, crucial regulatory factors, such as Arnt2, WNT2B, GNG7, LOC100909750, Cyp1a1, E2F1, BIRC5, and LPAR4, were identified and verified to be closely related to cardiac fibrosis. CONCLUSION: This study identified the crucial regulators and related functional pathways in cardiac fibrosis by integrating the whole transcriptome analysis in rats, which might provide novel insights into the pathogenesis of cardiac fibrosis.

Associations between modifiable risk factors and frailty: a Mendelian randomisation study.

BACKGROUND: Early identification of modifiable risk factors is essential for the prevention of frailty. This study aimed to explore the causal relationships between a spectrum of genetically predicted risk factors and frailty. METHODS: Univariable and multivariable Mendelian randomisation (MR) analyses were performed to explore the relationships between 22 potential risk factors and frailty, using summary genome-wide association statistics. Frailty was accessed by the frailty index. RESULTS: Genetic liability to coronary artery disease (CAD), type 2 diabetes mellitus (T2DM), ischaemic stroke, atrial fibrillation and regular smoking history, as well as genetically predicted 1-SD increase in body mass index, systolic blood pressure, diastolic blood pressure, low-density lipoprotein cholesterol, triglycerides, alcohol intake frequency and sleeplessness were significantly associated with increased risk of frailty (all p<0.001). In addition, there was a significant inverse association between genetically predicted college or university degree with risk of frailty (beta -0.474; 95% CI (-0.561 to -0.388); p<0.001), and a suggestive inverse association between high-density lipoprotein cholesterol level with risk of frailty (beta -0.032; 95% CI (-0.055 to -0.010); p=0.004). However, no significant causal associations were observed between coffee consumption, tea consumption, serum level of total testosterone, oestradiol, 25-hydroxyvitamin D, C reactive protein or moderate to vigorous physical activity level with frailty (all p>0.05). Results of the reverse directional MR suggested bidirectional causal associations between T2DM and CAD with frailty. CONCLUSIONS: This study provided genetic evidence for the causal associations between several modifiable risk factors with lifetime frailty risk. A multidimensional approach targeting these factors may hold a promising prospect for prevention frailty.

Cfa-circ002203 was upregulated in rapidly paced atria of dogs and involved in the mechanisms of atrial fibrosis.

Background and aims: The role of circular RNAs (circRNAs) in the pathophysiology of cardiovascular disease is gradually being elucidated; however, their roles in atrial fibrillation (AF)-related fibrosis are largely unknown. This study aimed to characterize the different circRNA profiles in the rapid-pacing atria of dogs and explore the mechanisms involved in atrial fibrosis. Methods: A rapid right atrial-pacing model was established using electrical stimulation from a pacemaker. After 14 days, atrial tissue was collected for circRNA sequencing analysis. In vitro fibrosis was established by stimulating canine atrial fibroblasts with angiotensin II (Ang II). The fibroblasts were transfected with siRNA and overexpressing plasmids to explore the effects of cfa-circ002203 on fibroblast proliferation, migration, differentiation, and the expression of fibrosis-related proteins. Results: In total, 146 differentially expressed circRNAs were screened, of which 106 were upregulated and 40 were downregulated. qRT-PCR analysis showed that cfa-circ002203 was upregulated in both in vivo and in vitro fibroblast fibrosis models. The upregulation of cfa-circ002203 enhanced proliferation and migration while weakening the apoptosis of fibroblasts. Western blotting showed that cfa-circ002203 overexpression increased the protein expression levels of fibrosis-related indicators (Col I, Col III, MMP2, MMP9, and α-SMA) and decreased the protein expression levels of pro-apoptotic factors (Bax and Caspase 3) in Ang II-induced fibroblast fibrosis. Conclusion: Cfa-circ002203 might serve as an active promoter of the proliferation, migration, and fibrosis of atrial fibroblasts and is involved in AF-induced fibroblast fibrosis.

Effects of radiofrequency balloon angioplasty on the abdominal aorta in atherosclerotic rabbits.

OBJECTIVES: A novel temperature-controlled intravascular radiofrequency balloon angioplasty (RFBA) technique was designed and developed for atherosclerosis (AS) management. METHODS: After establishing an AS model based on a balloon denudation injury of the abdominal aorta and a high cholesterol diet in rabbits, 46 animals were randomly assigned to the RFBA group (n = 28) or the plain balloon angioplasty (PBA) group (n = 28). The groups were further subdivided based on post-treatment euthanasia times (1 hour, 7 days, 14 days, and 28 days). Histopathological changes were observed by hematoxylin and eosin and Masson's staining. Immunohistochemistry, western blotting, and real-time quantitative polymerase chain reaction were used to detect changes in pro-inflammatory, anti-inflammatory, and apoptotic factors; TGF-ß/Smad-2 pathway protein Immune levels; and mRNA levels in tissues, respectively. RESULTS: The vascular lumen area in the RFBA group was larger than that in the PBA group at the same time points, although the change in the vascular lumen area was not different between groups. The expression of Bax, TGF-ß, Smad-2, and Caspase-3 in the RFBA group was significantly higher than that in the PBA group. The expression levels of Bcl-2 in the RFBA group were significantly lower than those in the PBA group. CONCLUSIONS: At 28 days, RFBA dilated the atherosclerotic blood vessels and thickened the fibrous cap of atherosclerotic plaques to promote plaque stability. RFBA was also found to activate apoptotic factors and the TGF-/Smad-2 inflammatory pathway.

Proteomic sequencing analysis in a rat model of atrial fibrosis caused by chronic intermittent hypoxia.

Background: Atrial fibrosis caused by long-term atrial fibrillation influences the outcomes of clinical treatment. An improved understanding of the mechanisms underlying atrial fibrillation may reveal new therapeutic targets. This study was conducted to analyze the changes in protein levels in the atrial tissue of a rat model of atrial fibrillation based on proteome sequencing. Methods: Sprague-Dawley rats were used to develop a model of atrial fibrillation induced by chronic intermittent hypoxia (CIH). Histopathological changes were detected using hematoxylin and eosin staining and Masson's staining, and immunohistochemistry and western blotting for the levels of fibrosis biomarkers. Atrial fibrosis tissue samples were also evaluated by proteome sequencing. Differentially expressed proteins (DEPs) between the CIH and control groups were evaluated in functional assay. The expression levels of several key proteins were validated using western blotting. Results: CIH resulted in atrial fibrosis and induced atrial fibrillation. We identified 145 DEPs between the CIH and control groups. These included Myh7, Myl2, Myl3, and Atpla3, which are involved in signaling pathways related to hypertrophic cardiomyopathy, glycerolipid metabolism, and cardiac muscle contraction. Western blotting revealed the upregulation of Myh7, Myl2, and Myl3 and the downregulation of Atpla3 in the CIH group compared with the control group. These results were consistent with the sequencing results. Conclusions: Myh7, Myl2, Myl3, and Atpla3 may play key roles in the progression of atrial fibrillation through their involvement in cardiovascular-disease-related signaling pathways.

A retrospective study of FQSRL and IPL in the treatment of Café-au-lait macule.

BACKGROUND: The application of fractional Q-switched ruby laser (FQSRL) or intense pulsed light (IPL) on Café-au-lait macule (CALM) is rational and the data are lacking. OBJECTIVE: To evaluate the efficacy and safety of FQSRL and IPL in CALM. METHODS: The patients with CALM who were treated with FQSRL or IPL were retrospectively observed from April 2016 to April 2019. The laser/light treatments were conducted at an interval of 3-4 weeks. RESULTS: For FQSRL (N = 67), 88.23%, 95.46%, 100% patients achieved >50% improvement by three sessions, four sessions, and more than four sessions of treatment, respectively. A better and better efficacy was shown with the increasing number of sessions (χ2 = 89.51, p < .01). For IPL (N = 54), 45% and 87.5% achieved >50% improvement by three sessions and more than four sessions of treatments, respectively. More than four sessions achieved better efficacy than less sessions (p < .01). Under various time-points, FQSRL presented more favorable responses than IPL (p < .05). All the adverse effects were tolerable and acceptable. CONCLUSIONS: FQSRL or IPL would be an alternative and safe modality for CAML in Chinese patients.

Toward a Country-Based Prediction Model of COVID-19 Infections and Deaths Between Disease Apex and End: Evidence From Countries With Contained Numbers of COVID-19.

The complexity of COVID-19 and variations in control measures and containment efforts in different countries have caused difficulties in the prediction and modeling of the COVID-19 pandemic. We attempted to predict the scale of the latter half of the pandemic based on real data using the ratio between the early and latter halves from countries where the pandemic is largely over. We collected daily pandemic data from China, South Korea, and Switzerland and subtracted the ratio of pandemic days before and after the disease apex day of COVID-19. We obtained the ratio of pandemic data and created multiple regression models for the relationship between before and after the apex day. We then tested our models using data from the first wave of the disease from 14 countries in Europe and the US. We then tested the models using data from these countries from the entire pandemic up to March 30, 2021. Results indicate that the actual number of cases from these countries during the first wave mostly fall in the predicted ranges of liniar regression, excepting Spain and Russia. Similarly, the actual deaths in these countries mostly fall into the range of predicted data. Using the accumulated data up to the day of apex and total accumulated data up to March 30, 2021, the data of case numbers in these countries are falling into the range of predicted data, except for data from Brazil. The actual number of deaths in all the countries are at or below the predicted data. In conclusion, a linear regression model built with real data from countries or regions from early pandemics can predict pandemic scales of the countries where the pandemics occur late. Such a prediction with a high degree of accuracy provides valuable information for governments and the public.

A cost-effective plan for global testing - an infection rate stratified, algorithm guided, multiple-level, continuously pooled testing strategy.

The most effective measure to prevent or stop the spread of infectious diseases is the early identification and isolation of infected individuals through comprehensive screening. At present, in the COVID-19 pandemic, such screening is often limited to isolated regions as determined by local governments. Screening of potentially infectious individuals should be conducted through coordinated national or global unified actions. Our current research focuses on using resources to conduct comprehensive national and regional regular testing with a risk rate based, algorithmic guided, multiple-level, pooled testing strategy. Here, combining methodologies with mathematical logistic models, we present an analytic procedure of an overall plan for coordinating state, national, or global testing. The proposed plan includes three parts 1) organization, resource allocation, and distribution; 2) screening based on different risk levels and business types; and 3) algorithm guided, multiple level, continuously screening the entire population in a region. This strategy will overcome the false positive and negative results in the polymerase chain reaction (PCR) test and missing samples during initial tests. Based on our proposed protocol, the population screening of 300,000,000 in the US can be done weekly with between 15,000,000 and 6,000,000 test kits. The strategy can be used for population screening for current COVID-19 and any future severe infectious disease when drugs or vaccines are not available.

The Data set for Patient Information Based Algorithm to Predict Mortality Cause by COVID-19.

The data of COVID-19 disease in China and then in South Korea were collected daily from several different official websites. The collected data included 33 death cases in Wuhan city of Hubei province during early outbreak as well as confirmed cases and death toll in some specific regions, which were chosen as representatives from the perspective of the coronavirus outbreak in China. Data were copied and pasted onto Excel spreadsheets to perform data analysis. A new methodology, Patient Information Based Algorithm (PIBA) [1], has been adapted to process the data and used to estimate the death rate of COVID-19 in real-time. Assumption is that the number of days from inpatients to death fall into a pattern of normal distribution and the scores in normal distribution can be obtained by observing 33 death cases and analysing the data [2]. We selected 5 scores in normal distribution of these durations as lagging days, which will be used in the following estimation of death rate. We calculated each death rate on accumulative confirmed cases with each lagging day from the current data and then weighted every death rate with its corresponding possibility to obtain the total death rate on each day. While the trendline of these death rate curves meet the curve of current ratio between accumulative death cases and confirmed cases at some points in the near future, we considered that these intersections are within the range of real death rates. Six tables were presented to illustrate the PIBA method using data from China and South Korea. One figure on estimated rate of infection and patients in serious condition and retrospective estimation of initially occurring time of CORID-19 based on PIBA.

Real-time estimation and prediction of mortality caused by COVID-19 with patient information based algorithm.

The global COVID-19 outbreak is worrisome both for its high rate of spread, and the high case fatality rate reported by early studies and now in Italy. We report a new methodology, the Patient Information Based Algorithm (PIBA), for estimating the death rate of a disease in real-time using publicly available data collected during an outbreak. PIBA estimated the death rate based on data of the patients in Wuhan and then in other cities throughout China. The estimated days from hospital admission to death was 13 (standard deviation (SD), 6 days). The death rates based on PIBA were used to predict the daily numbers of deaths since the week of February 25, 2020, in China overall, Hubei province, Wuhan city, and the rest of the country except Hubei province. The death rate of COVID-19 ranges from 0.75% to 3% and may decrease in the future. The results showed that the real death numbers had fallen into the predicted ranges. In addition, using the preliminary data from China, the PIBA method was successfully used to estimate the death rate and predict the death numbers of the Korean population. In conclusion, PIBA can be used to efficiently estimate the death rate of a new infectious disease in real-time and to predict future deaths. The spread of 2019-nCoV and its case fatality rate may vary in regions with different climates and temperatures from Hubei and Wuhan. PIBA model can be built based on known information of early patients in different countries.

Molecular network of important genes for systemic sclerosis-related progressive lung fibrosis.

BACKGROUND: Considerable progress has been made in illuminating the pathological events for systemic sclerosis (SSc)-related progressive lung fibrosis. The molecular events that lead to SSc-related progressive lung fibrosis need to be defined. Some important genes have been identified from a recent study in humans. We aim to construct and compare the similarities and differences of molecular pathways between SSc-related progressive lung fibrosis and normal lungs of humans and mice. METHODS: We used the analytical approach of association of key genes in SSc-related progressive lung fibrosis. We first identified the probes for genes of SSc-related progressive lung fibrosis and analyzed the pathways in human lung using data generated by microarray. We then analyzed the gene pathways in mouse lung for similar sets of probes. Gene expression data from livers were used to compare with that in lung in both humans and mice. RESULTS: Our analysis indicated that, in humans, the expression levels of genes for macrophage activation are more strongly associated with each other than that in mice. In both humans and mice, the associations of these genes are much greater in the lung than that in the liver. The association in gene expression between humans and mice are similar for IFN-regulated genes and profibrotic/Tgfß-regulated genes. CONCLUSION: Our analysis reveals the differences and similarities of the network of key genes between humans and mice during the molecular processes that eventually lead to fibrosis in the lung.