Advancements in the treatment of non-alcoholic fatty liver disease (NAFLD)

Non-alcoholic fatty liver disease (NAFLD) is a series of diseases, involving excessive lipid deposition in the liver and is often accompanied by obesity, diabetes, dyslipidemia, abnormal blood pressure, and other metabolic disorders. In order to more accurately reflect its pathogenesis, an international consensus renamed NAFLD in 2020 as metabolic (dysfunction) associated with fatty liver disease (MAFLD). The changes in diet and lifestyle are recognized the non-drug treatment strategies; however, due to the complex pathogenesis of NAFLD, the current drug therapies are mainly focused on its pathogenic factors, key links of pathogenesis, and related metabolic disorders as targets. There is still a lack of specific drugs. In clinical studies, the common NAFLD treatments include the regulation of glucose and lipid metabolism to protect the liver and anti-inflammation. The NAFLD treatments based on the enterohepatic axis, targeting gut microbiota, are gradually emerging, and various new metabolism-regulating drugs are also under clinical development. Therefore, this review article has comprehensively discussed the research advancements in NAFLD treatment in recent years

PM2.5 induced liver lipid metabolic disorders in C57BL/6J mice

PM2.5 can cause adverse health effects via several pathways, such as inducing pulmonary and systemic inflammation, penetration into circulation, and activation of the autonomic nervous system. In particular, the impact of PM2.5 exposure on the liver, which plays an important role in metabolism and detoxification to maintain internal environment homeostasis, is getting more attention in recent years. In the present study, C57BL/6J mice were randomly assigned and treated with PM2.5 suspension and PBS solution for 8 weeks. Then, hepatic tissue was prepared and identified by metabolomics analysis and transcriptomics analysis. PM2.5 exposure can cause extensive metabolic disturbances, particularly in lipid and amino acids metabolic dysregulation.128 differential expression metabolites (DEMs) and 502 differently expressed genes (DEGs) between the PM2.5 exposure group and control group were detected. The Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses showed that DEGs were significantly enriched in two disease pathways, non-alcoholic fatty liver disease (NAFLD) and type II diabetes mellitus (T2DM), and three signaling pathways, which are TGF-beta signaling, AMPK signaling, and mTOR signaling. Besides, further detection of acylcarnitine levels revealed accumulation in liver tissue, which caused restricted lipid consumption. Furthermore, lipid droplet accumulation in the liver was confirmed by Oil Red O staining, suggesting hepatic steatosis. Moreover, the aberrant expression of three key transcription factors revealed the potential regulatory effects in lipid metabolic disorders, the peroxisomal proliferative agent-activated receptors (PPARs) including PPARα and PPARγ is inhibited, and the activated sterol regulator-binding protein 1 (SREBP1) is overexpressed. Our results provide a novel molecular and genetic basis for a better understanding of the mechanisms of PM2.5 exposure-induced hepatic metabolic diseases, especially in lipid metabolism

Excess Deaths of Gastrointestinal, Liver, and Pancreatic Diseases During the COVID-19 Pandemic in the United States

Objectives: To evaluate excess deaths of gastrointestinal, liver, and pancreatic diseases in the United States during the COVID-19 pandemic.Methods: We retrieved weekly death counts from National Vital Statistics System and fitted them with a quasi-Poisson regression model. Cause-specific excess deaths were calculated by the difference between observed and expected deaths with adjustment for temporal trend and seasonality. Demographic disparities and temporal-spatial patterns were evaluated for different diseases.Results: From March 2020 to September 2022, the increased mortality (measured by excess risks) for Clostridium difficile colitis, gastrointestinal hemorrhage, and acute pancreatitis were 35.9%; 24.8%; and 20.6% higher than the expected. For alcoholic liver disease, fibrosis/cirrhosis, and hepatic failure, the excess risks were 1.4–2.8 times higher among younger inhabitants than older inhabitants. The excess deaths of selected diseases were persistently observed across multiple epidemic waves with fluctuating trends for gastrointestinal hemorrhage and fibrosis/cirrhosis and an increasing trend for C. difficile colitis.Conclusion: The persistently observed excess deaths of digestive diseases highlights the importance for healthcare authorities to develop sustainable strategies in response to the long-term circulating of SARS-CoV-2 in the community

Source-Specific Volatile Organic Compounds and Emergency Hospital Admissions for Cardiorespiratory Diseases

Knowledge gaps remain regarding the cardiorespiratory impacts of ambient volatile organic compounds (VOCs) for the general population. This study identified contributing sources to ambient VOCs and estimated the short-term effects of VOC apportioned sources on daily emergency hospital admissions for cardiorespiratory diseases in Hong Kong from 2011 to 2014. We estimated VOC source contributions using fourteen organic chemicals by positive matrix factorization. Then, we examined the associations between the short-term exposure to VOC apportioned sources and emergency hospital admissions for cause-specific cardiorespiratory diseases using generalized additive models with polynomial distributed lag models while controlling for meteorological and co-pollutant confounders. We identified six VOC sources: gasoline emissions, liquefied petroleum gas (LPG) usage, aged VOCs, architectural paints, household products, and biogenic emissions. We found that increased emergency hospital admissions for chronic obstructive pulmonary disease were positively linked to ambient VOCs from gasoline emissions (excess risk (ER%): 2.1%; 95% CI: 0.9% to 3.4%), architectural paints (ER%: 1.5%; 95% CI: 0.2% to 2.9%), and household products (ER%: 1.5%; 95% CI: 0.2% to 2.8%), but negatively associated with biogenic VOCs (ER%: −6.6%; 95% CI: −10.4% to −2.5%). Increased congestive heart failure admissions were positively related to VOCs from architectural paints and household products in cold seasons. This study suggested that source-specific VOCs might trigger the exacerbation of cardiorespiratory diseases

Trends and Disparities in Stage-specific Incidence of Hepatocellular Carcinoma among US Adults, 2004-2019

Introduction: To determine the stage-specific incidence trend of hepatocellular carcinoma (HCC) among US adults. Methods: The age-adjusted incidence rate was extracted from Surveillance, Epidemiology, and End Results database for localized, regional and distant HCC. Trend analyses were conducted in the overall population and stratified by demographic and sociodemographic variables. The annual percentage change (APC) in 2014-2019 was estimated to determine the stage-specific incidence trend. Results: Although the incidence in localized HCC significantly declined, the incidence for regional and distant HCC plateaued in 2014-2019 (APCs, 4.4% [95% CI, -0.2% to 9.3%] and -0.7% [95% CI, -1.8% to 0.5%], respectively) with age and race/ethnicity disparities. More pronounced increases for regional and distant HCC were observed among the elderly (APCs, 8.4% [95% CI, 4.8% to 12.2%] and 2.2% [95% CI, 1.7% to 2.7%] for regional and distant HCC, respectively), non-Hispanic White individuals (APCs, 4.0% [95% CI, 2.9% to 5.1%] and 1.5% [95% CI, 0.7% to 2.4%] for regional and distant HCC, respectively). Conclusions: Disparities in incidence trends may reflect the inequalities in access to primary health care. More efforts are still in great demand for the vulnerable population

The Association Between Clinical Severity and Incubation Period of SARS-CoV-2 Delta Variants: Retrospective Observational Study

BackgroundAs of August 25, 2021, Jiangsu province experienced the largest COVID-19 outbreak in eastern China that was seeded by SARS-CoV-2 Delta variants. As one of the key epidemiological parameters characterizing the transmission dynamics of COVID-19, the incubation period plays an essential role in informing public health measures for epidemic control. The incubation period of COVID-19 could vary by different age, sex, disease severity, and study settings. However, the impacts of these factors on the incubation period of Delta variants remains uninvestigated. ObjectiveThe objective of this study is to characterize the incubation period of the Delta variant using detailed contact tracing data. The effects of age, sex, and disease severity on the incubation period were investigated by multivariate regression analysis and subgroup analysis. MethodsWe extracted contact tracing data of 353 laboratory-confirmed cases of SARS-CoV-2 Delta variants’ infection in Jiangsu province, China, from July to August 2021. The distribution of incubation period of Delta variants was estimated by using likelihood-based approach with adjustment for interval-censored observations. The effects of age, sex, and disease severity on the incubation period were expiated by using multivariate logistic regression model with interval censoring. ResultsThe mean incubation period of the Delta variant was estimated at 6.64 days (95% credible interval: 6.27-7.00). We found that female cases and cases with severe symptoms had relatively longer mean incubation periods than male cases and those with nonsevere symptoms, respectively. One-day increase in the incubation period of Delta variants was associated with a weak decrease in the probability of having severe illness with an adjusted odds ratio of 0.88 (95% credible interval: 0.71-1.07). ConclusionsIn this study, the incubation period was found to vary across different levels of sex, age, and disease severity of COVID-19. These findings provide additional information on the incubation period of Delta variants and highlight the importance of continuing surveillance and monitoring of the epidemiological characteristics of emerging SARS-CoV-2 variants as they evolve

Modelling the effective reproduction number of vector-borne diseases: the yellow fever outbreak in Luanda, Angola 2015–2016 as an example

The burden of vector-borne diseases (Dengue, Zika virus, yellow fever, etc.) gradually increased in the past decade across the globe. Mathematical modelling on infectious diseases helps to study the transmission dynamics of the pathogens. Theoretically, the diseases can be controlled and eventually eradicated by maintaining the effective reproduction number, (Reff), strictly less than 1. We established a vector-host compartmental model, and derived (Reff) for vector-borne diseases. The analytic form of the (Reff) was found to be the product of the basic reproduction number and the geometric average of the susceptibilities of the host and vector populations. The (Reff) formula was demonstrated to be consistent with the estimates of the 2015–2016 yellow fever outbreak in Luanda, and distinguished the second minor epidemic wave. For those using the compartmental model to study the vector-borne infectious disease epidemics, we further remark that it is important to be aware of whether one or two generations is considered for the transition “from host to vector to host” in reproduction number calculation

Microarray Expression Profile of Circular RNAs in Peripheral Blood Mononuclear Cells from Rheumatoid Arthritis Patients

Background/Aims: Circular RNAs (circRNAs) compose a large class of RNAs that can be used as biomarkers in clinical blood samples. This study aimed to determine the expression of circRNAs in peripheral blood mononuclear cells (PBMCs) from rheumatoid arthritis (RA) patients to identify novel biomarkers for RA screening. Methods: We started with a microarray screening of circRNA changes in PBMCs from 5 RA patients and 5 healthy controls. We then confirmed the selected circRNA changes in PBMCs from 30 RA patients and 25 age- and sex-matched controls using the real-time quantitative reverse transcription-polymerase chain reaction (qRT-PCR). Spearman correlation test was performed to assess the correlation of circRNAs and clinical variables. Receiver operating characteristic (ROC) curve was calculated to evaluate the diagnostic value. Results: We identified and verified five circRNAs (092516, 003524, 103047, 104871, 101873) that were significantly elevated in PBMCs from RA patients. Among these RA patients, we detected no significant correlation between the five circRNAs and the disease severity, including disease activity score (DAS28), erythrocyte sedimentation rate (ESR), C-reactive protein (CRP), and health assessment questionnaire (HAQ). Yet, ROC curve analysis suggested that circRNA_104871 has significant value of RA diagnosis (AUC=0.833, P<0.001), followed by circRNA_003524 (AUC = 0.683, P = 0.020), circRNA_101873 (AUC = 0.676, P = 0.026), and circRNA_103047 (AUC = 0.671, P = 0.030). Conclusions: This study suggests that increased expression of circRNAs circRNA_104871, circRNA_003524, circRNA_101873 and circRNA_103047 in PBMC from RA patients may serve as potential biomarkers for RA patient diagnosis

Superspreading potentials of SARS-CoV-2 Delta variants across different contact settings in Eastern China: A retrospective observational study

Objectives: As the genetic variants of SARS-CoV-2 continuously pose threats to global health, evaluating superspreading potentials of emerging genetic variants is of importance for region-wide control of COVID-19 outbreaks. Methods: By using detailed epidemiological contact tracing data of test-positive COVID-19 cases collected between July and August 2021 in Nanjing and Yangzhou, China, we assessed the superspreading potential of outbreaks seeded by SARS-CoV-2 Delta variants. The transmission chains and case-clusters were constructed according to the individual-based surveillance data. We modelled the disease transmission as a classic branching process with transmission heterogeneity governed by negative binomial models. Subgroup analysis was conducted by different contact settings and age groups. Results: We reported a considerable heterogeneity in the contact patterns and transmissibility of Delta variants in eastern China. We estimated an expected 14% (95% CI: 11–16%) of the most infectious cases generated 80% of the total transmission. Conclusions: Delta variants demonstrated a significant potential of superspreading under strict control measures and active COVID-19 detecting efforts. Enhancing the surveillance on disease transmissibility especially in high-risk settings, along with rapid contact tracing and case isolations would be one of the key factors to mitigate the epidemic caused by the emerging genetic variants of SARS-CoV-2