Abstract Background and Purpose Pneumoconiosis, especially silicosis has emerged as a prominent occupational disease with remarkable global implications with no definitive cure available. While pirfenidone and nintedanib have been approved in treating idiopathic pulmonary fibrosis, their potential efficacy as anti-fibrotic agents in advanced silicosis warrants further investigation. Thus, we aimed to assess the individual and combined effects of pirfenidone and nintedanib in treating advanced silicosis mice and further elucidate the underlying mechanisms involved in their therapeutic actions. Experimental Approach We administrated monotherapy or combination therapy of pirfenidone and nintedanib with low and high doses in silicosis mouse models established after 6 weeks and then evaluated lung function, inflammatory responses, and fibrotic status. Moreover, we employed transcriptomic and metabolomic analyses to unravel the mechanisms underlying different therapeutic strategies. Key Results Both pirfenidone and nintedanib were demonstrated to be effective for advanced silicosis, with superior outcomes when used in combination. Transcriptomic and metabolomic analyses revealed that pirfenidone and nintedanib primarily exerted their therapeutic effects through modulation of immune responses, signaling cascades, circadian rhythm, and metabolic processes of substances including lipid, amino acids, nucleotides, and carbohydrates. Conclusion and Implications In conclusion, pirfenidone and nintedanib, either administered individually or in combination, exhibit remarkable potential in advanced silicosis mouse models. Further, combined therapy outperformed monotherapy even at a half dose. These therapeutic benefits are attributed to their influence on diverse signaling pathways and metabolic processes. Keywords: silicosis, pulmonary fibrosis, pirfenidone, nintedanib, multi-omics.

Backgrounds To our knowledge, there is no available nationwide data on omicron symptom patterns in China mainland. We aim to determine the acute and long COVID-19 symptoms in the omicron-dominant period and to evaluate its association with age, sex and smoking status. Methods We designed a cross-sectional nationwide study and data about self-reported symptoms were collected by an online platform named Wenjuanxing. Eligible participants were aged 25 - 65 years and were symptomatic. To improve the representativeness of sample size, the ratios of the number of people of different ages and genders were weighted by the data from the Seventh National Census (2020 years), and validated by a published nationwide representative study through comparing smoking rates. Descriptive analysis was conducted to report information on demographic characteristics, diagnosis ways and duration time, acute symptoms, hospitalization, severity and long COVID-19 symptoms. And, multivariate Logistic regression models were used to explore the effect of age, sex and smoking on acute and long COVID-19 symptoms. Results A total of 32,528 individuals diagnosed as COVID-19 infection from October 1, 2022 to February 21, 2023 were included. The top three acute symptoms of COVID-19 infection were fever (69.90%), headache (62.63%), sore throat (54.29%). The rates of hospitalization within 7 days, symptoms disappear within 21 days were 3.07% and 68.84%, respectively. Among 3983 COVID-19 patients with 3 months or more time difference between first infection and participation into the study, the long COVID-19 rate was 19.68% and the primary symptoms were muscle weakness (19.39%), headache (17.98%) and smell/taste disorder (15.18%). Compared with male and never smokers, female and current smokers were risk factors for each acute CVOID-19 symptoms, and also had a higher risk for fatigue among long COVID-19 symptoms. Lastly, female and current smokers also were related with more number of symptoms during acute infection period. Conclusions Omicron variant to be milder in terms of severity in China mainland. And, more attention should be given to high-risk population (current smokers and women) to control disease burden caused by COVID-19.