Background: CameL phase 3 study demonstrated the superiority of camrelizumab plus chemotherapy over chemotherapy alone for progression-free survival in patients with previously untreated advanced non-squamous non-small-cell lung cancer (NSCLC) without EGFR/ALK alterations. Here, we present the 5-year outcomes. Methods: Patients were randomized (1:1) and received 4–6 cycles of camrelizumab plus carboplatin and pemetrexed (n=205) or carboplatin and pemetrexed (n=207) every 3 weeks, followed by maintenance camrelizumab plus pemetrexed or pemetrexed only. Crossover from chemotherapy group to camrelizumab monotherapy was permitted after disease progression. Results: Median time from randomization to data cut-off was 65.2 months (range, 59.7–72.2). HR for overall survival (OS) was 0.74 (95% CI 0.58 to 0.93; one-sided p=0.0043), and was 0.62 (95% CI 0.49 to 0.79; one-sided p<0.0001) after adjustment for crossover. Five-year OS rates were 31.2% (95% CI 24.7% to 37.9%) with camrelizumab plus chemotherapy versus 19.3% (95% CI 13.9% to 25.3%) with chemotherapy alone. Among the 33 patients who completed 2 years of camrelizumab, 5-year OS rate was 84.3% (95% CI 66.4% to 93.2%), and 5-year duration of response rate was 46.5% (95% CI 24.9% to 65.6%) in the 32 responders. No new safety signals were noted. Conclusions: Camrelizumab plus carboplatin and pemetrexed as first-line therapy continued to demonstrate long-term OS benefit over carboplatin and pemetrexed, with manageable toxicity. Patients who completed 2 years of camrelizumab had enduring response and impressive OS. Current 5-year updated analysis further supports camrelizumab plus carboplatin and pemetrexed as a standard-of-care for previously untreated advanced non-squamous NSCLC without EGFR/ALK alterations. Trial registration number: NCT03134872.

Background: Silicosis, a severe lung disease caused by inhaling silica dust, predominantly affects workers in industries such as mining and construction, leading to a significant global public health challenge. The purpose of this study is to analyze the current disease burden of silicosis and to predict the development trend of silicosis in the future the world by extracting data from the GBD database.Methods: We extracted and analyzed silicosis prevalence, incidence, mortality, and disability-adjusted life years (DALYs) data from the Global Burden of Disease 2019 program for 204 countries and territories from 1990 to 2019. The association between the Sociodemographic Index (SDI) and the burden of age-standardized rates (ASRs) of DALYs has been examined at the regional level. Jointpoint regression analysis has been also performed to evaluate global burden trends of silicosis from 1990 to 2019. Furthermore, Nordpred age-period-cohort analysis has also been projected to predict future the burden of silicosis from 2019 to 2044.Results: In 2019, global ASRs for silicosis prevalence, incidence, mortality, and DALYs were 5.383, 1.650, 0.161, and 7.872%, respectively which are lower than that in 1990. The populations of 45–59 age group were more susceptible to silicosis, while those aged 80 or above suffered from higher mortality and DALY risks. In 2019, the most impacted nations by the burden of silicosis included China, the Democratic People’s Republic of Korea, and Chile. From 1990 to 2019, most regions observed a declining burden of silicosis. An “M” shaped association between SDI and ASRs of DALYs for silicosis was observed from 1990 to 2019. The age-period-cohort analysis forecasted a decreasing trend of the burden of silicosis from 2019 to 2044.Conclusion: Despite the overall decline in the global silicosis burden from 1990 to 2019, some regions witnessed a notable burden of this disease, emphasizing the importance of targeted interventions. Our results may provide a reference for the subsequent development of appropriate management strategies.

Pseudomonas aeruginosa strain 10265 was recovered from a patient with pneumonia in a Chinese public hospital, and it displays the carbapenem resistance phenotype due to the acquisition of a nonconjugative but mobilizable IncP-6-type plasmid p10265-KPC. p10265-KPC carries a Tn5563-borne defective mer locus and a novel ΔISEc33-associated blaKPC-2 gene cluster without paired invert repeats and direct repeats at both ends. Mobilization of this ΔISEc33-associated element in p10265-KPC would attribute to homologous recombination-based insertion of a foreign structure Tn3-ISApu1-orf7-ISApu2- ISKpn27-ΔblaTEM-1-blaKPC-2-ΔISKpn6-korC-orf6-klcA-ΔrepB into a pre-existent intact ISEc33, making ISEc33 truncated at the 3' end. The previously reported pCOL-1 represents the first sequenced KPC-producing IncP-6 plasmid, while p10265-KPC is the second one. These two plasmids carry two distinct blaKPC-2 gene clusters, which are inserted into the different sites of the IncP-6 backbone and have different evolutionary histories of assembly and mobilization. This is also the first report of identification of the IncP-6-type resistance plasmid in China.

Purpose: Our study aims to delineate the epidemiological distribution of pulmonary carcinoids, including atypical carcinoid (AC) and typical carcinoid (TC), identify independent prognostic factors, develop an integrative nomogram and examine the effects of various surgical modalities on atypical carcinoid‐specific survival (ACSS).Methods: Joinpoint regression model and age‐group distribution diagram were applied to determine the epidemiological trend of the pulmonary carcinoids. Univariate and least absolute shrinkage and selection operator (LASSO)‐based Cox regression models were used to identify independent factors, and a nomogram and web‐based predictor were developed to evaluate prognosis of AC patients individually. We performed Kaplan–Meier survival analyses to compare the scope of various surgical interventions, with and without G‐computation adjustment, utilising restricted mean survival time (RMST) to assess survival disparities.Results: A total of 1132 patients were recruited from the Surveillance, Epidemiology, and End Results database (SEER) and a separate medical centre in China. The mean age of AC patients was 63.4 years and a smoking history was identified in 79.8% of AC patients. Joinpoint analysis shows rising annual rates of new AC and carcinoid cases among lung cancers. Both the proportion of pulmonary TC and AC within the total lung cancer population exhibits an L‐shaped trend across successive age groups. The nomogram predicted 1, 3 and 5 years of AC with excellent accuracy and discrimination. Kaplan–Meier survival analyses, conducted both pre‐ and post‐adjustment, demonstrated that sublobar resection's survival outcomes were not inferior to those of lobectomy in patients with stage I‐II and stage III disease.Conclusion: This study is the first to reveal epidemiological trends in pulmonary carcinoids over the past decade and across various age cohorts. For patients with early‐stage AC, sublobar resection may be a viable surgical recommendation. The established nomogram and web‐based calculator demonstrated decent accuracy and practicality.

A complete diagnostic autopsy is the gold-standard to gain insight into Coronavirus disease 2019 (COVID-19) pathogenesis. To delineate the in situ immune responses to SARS-CoV-2 viral infection, here we perform comprehensive high-dimensional transcriptional and spatial immune profiling in 22 COVID-19 decedents from Wuhan, China. We find TIM-3-mediated and PD-1-mediated immunosuppression as a hallmark of severe COVID-19, particularly in men, with PD-1⁺ cells being proximal rather than distal to TIM-3⁺ cells. Concurrently, lymphocytes are distal, while activated myeloid cells are proximal, to SARS-CoV-2 viral antigens, consistent with prevalent SARS-CoV-2 infection of myeloid cells in multiple organs. Finally, viral load positively correlates with specific immunosuppression and dendritic cell markers. In summary, our data show that SARS-CoV-2 viral infection induces lymphocyte suppression yet myeloid activation in severe COVID-19, so these two cell types likely have distinct functions in severe COVID-19 disease progression, and should be targeted differently for therapy.

Background: This study aimed to develop diagnostic and prognostic models for patients with pulmonary sarcomatoid carcinoma (PSC) and distant metastasis (DM).Methods: Patients from the Surveillance, Epidemiology, and End Results (SEER) database were divided into a training set and internal test set at a ratio of 7 to 3, while those from the Chinese hospital were assigned to the external test set, to develop the diagnostic model for DM. Univariate logistic regression was employed in the training set to screen for DM-related risk factors, which were included into six machine learning (ML) models. Furthermore, patients from the SEER database were randomly divided into a training set and validation set at a ratio of 7 to 3 to develop the prognostic model which predicts survival of patients PSC with DM. Univariate and multivariate Cox regression analyses have also been performed in the training set to identify independent factors, and a prognostic nomogram for cancer-specific survival (CSS) for PSC patients with DM.Results: For the diagnostic model for DM, 589 patients with PSC in the training set, 255 patients in the internal and 94 patients in the external test set were eventually enrolled. The extreme gradient boosting (XGB) algorithm performed best on the external test set with an area under the curve (AUC) of 0.821. For the prognostic model, 270 PSC patients with DM in the training and 117 patients in the test set were enrolled. The nomogram displayed precise accuracy with AUC of 0.803 for 3-month CSS and 0.869 for 6-month CSS in the test set.Conclusion: The ML model accurately identified individuals at high risk for DM who needed more careful follow-up, including appropriate preventative therapeutic strategies. The prognostic nomogram accurately predicted CSS in PSC patients with DM.