Highlights d Liver Cancer Model Repository (LIMORE) consists of 81 liver cancer cell models d LIMORE recapitulated genetic heterogeneity of human liver cancers d Molecular and drug screenings provide a pharmacogenomic landscape in liver cancers d Interrogation of the landscape informs biomarkers for liver cancer treatment

Currently, high-throughput approaches are lacking in the isolation of antibodies with functional readouts beyond simple binding. This situation has impeded the next generation of cancer immunotherapeutics, such as bispecific T cell engager (BiTE) antibodies or agonist antibodies against costimulatory receptors, from reaching their full potential. Here, we developed a highly efficient droplet-based microfluidic platform combining a lentivirus transduction system that enables functional screening of millions of antibodies to identify potential hits with desired functionalities. To showcase the capacity of this system, functional antibodies for CD40 agonism with low frequency (<0.02%) were identified with two rounds of screening. Furthermore, the versatility of the system was demonstrated by combining an anti-Her2 × anti-CD3 BiTE antibody library with functional screening, which enabled efficient identification of active anti-Her2 × anti-CD3 BiTE antibodies. The platform could revolutionize next-generation cancer immunotherapy drug development and advance medical research.

COVID-19 pandemic caused by SARS-CoV-2 constitutes a global public health crisis with enormous economic consequences. Monoclonal antibodies against SARS-CoV-2 can provide an important treatment option to fight COVID-19, especially for the most vulnerable populations. In this work, potent antibodies binding to SARS-CoV-2 Spike protein were identified from COVID-19 convalescent patients. Among them, P4A1 interacts directly with and covers majority of the Receptor Binding Motif of the Spike Receptor-Binding Domain, shown by high-resolution complex structure analysis. We further demonstrate the binding and neutralizing activities of P4A1 against wild type and mutant Spike proteins or pseudoviruses. P4A1 was subsequently engineered to reduce the potential risk for Antibody-Dependent Enhancement of infection and to extend its half-life. The engineered antibody exhibits an optimized pharmacokinetic and safety profile, and it results in complete viral clearance in a rhesus monkey model of COVID-19 following a single injection. These data suggest its potential against SARS-CoV-2 related diseases.

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ImportanceThe ongoing pandemic of COVID-19 is still affecting our life, but the effects of lockdown measures on gestational diabetes mellitus (GDM) in pregnant women remain unclear.AimTo investigate the association between COVID-19 lockdown and GDM.Subjects and MethodsMedical records of 140844 pregnant women during 2015-2020 were extracted from 5 hospitals in Guangdong Province, China. Pregnant women who underwent the COVID-19 Level I lockdown (1/23 - 2/24/2020) during pregnancy were defined as the exposed group (N=20472) and pregnant women who underwent the same calendar months during 2015-2019 (1/23 - 2/24) were defined as the unexposed group (N=120372). Subgroup analyses were used to explore the potential susceptible exposure window of COVID-19 lockdown on GDM. Cumulative exposure is quantitatively estimated by assigning different weights to response periods with different exposure intensities. A logistic regression model was used to estimate the association between COVID-19 lockdown exposure and GDM.ResultsThe rates of GDM in the exposed and unexposed groups were 15.2% and 12.4%, respectively. The overall analyses showed positive associations (odds ratio, OR=1.22, 95%CI: 1.17, 1.27) between lockdown exposure and GDM risk in all pregnant women. More pronounced associations were found in women who underwent the COVID-19 lockdown in their first four months of pregnancy, and the adjusted OR values ranged from 1.24 (95%CI: 1.10, 1.39) in women with 5-8 gestational weeks (GWs) to 1.35 (95%CI: 1.20, 1.52) with &lt; 5 GWs. In addition, we found a positive exposure-response association of cumulative lockdown exposure with the risk of GDM.ConclusionsThe COVID-19 lockdown was associated with an increased risk of GDM, and the first four months of pregnancy may be the window for sensitive exposure.

Background: The ongoing COVID-19 pandemic has brought significant challenges to health system and consumed a lot of health resources. However, evidence on the hospitalization costs and their associated factors in COVID-19 cases is scarce.Objectives: To describe the total and components of hospitalization costs of COVID-19 cases, and investigate the associated factors of costs.Methods: We included 876 confirmed COVID-19 cases admitted to 33 designated hospitals from January 15th to April 27th, 2020 in Guangdong, China, and collected their demographic and clinical information. A multiple linear regression model was performed to estimate the associations of hospitalization costs with potential associated factors.Results: The median of total hospitalization costs of COVID-19 cases was $2,869.4 (IQR: $3,916.8). We found higher total costs in male (% difference: 29.7, 95% CI: 15.5, 45.6) than in female cases, in older cases than in younger ones, in severe cases (% difference: 344.8, 95% CI: 222.5, 513.6) than in mild ones, in cases with clinical aggravation than those without, in cases with clinical symptoms (% difference: 47.7, 95% CI: 26.2, 72.9) than those without, and in cases with comorbidities (% difference: 21.1%, 21.1, 95% CI: 4.4, 40.6) than those without. We also found lower non-pharmacologic therapy costs in cases treated with traditional Chinese medicine (TCM) therapy (% difference: −47.4, 95% CI: −64.5 to −22.0) than cases without.Conclusion: The hospitalization costs of COVID-19 cases in Guangdong were comparable to the national level. Factors associated with higher hospitalization costs included sex, older age, clinical severity and aggravation, clinical symptoms and comorbidities at admission. TCM therapy was found to be associated with lower costs for some non-pharmacologic therapies.

Although strict lockdown measurements implemented during the COVID-19 pandemic have dramatically reduced the anthropogenic-based emissions, changes in air quality and its health impacts remain unclear in China. We comprehensively described air pollution during and after the lockdown periods in 2020 compared with 2018–2019, and estimated the mortality burden indicated by the number of deaths and years of life lost (YLL) related to the air pollution changes. The mean air quality index (AQI), PM 10 , PM 2.5 , NO 2 , SO 2 and CO concentrations during the lockdown across China declined by 18.2 (21.2%), 27.0 μg/m 3 (28.9%), 10.5 μg/m 3 (18.3%), 8.4 μg/m 3 (44.2%), 13.1 μg/m 3 (38.8%), and 0.3 mg/m 3 (27.3%) respectively, when compared to the same periods during 2018–2019. We observed an increase in O 3 concentration during the lockdown by 5.5 μg/m 3 (10.4%), and a slight decrease after the lockdown by 3.4 μg/m 3 (4.4%). As a result, there were 51.3 (95%CI: 32.2, 70.1) thousand fewer premature deaths (16.2 thousand during and 35.1 thousand after the lockdown), and 1066.8 (95%CI: 668.7, 1456.8) thousand fewer YLLs (343.3 thousand during and 723.5 thousand after the lockdown) than these in 2018–2019. Our findings suggest that the COVID-19 lockdown has caused substantial decreases in air pollutants except for O 3 , and that substantial human health benefits can be achieved when strict control measures for air pollution are taken to reduce emissions from vehicles and industries. Stricter tailored policy solutions of air pollution are urgently needed in China and other countries, especially in well-developed industrial regions, such as upgrading industry structure and promoting green transportation.

Although previous studies have proposed an association between maternal exposure to fine particulate matter (PM2.5) and the risk of gestational diabetes mellitus (GDM), such evidence remains rare. Additionally, the effects of PM2.5 on glycemic control in GDM patients are poorly known. In this study, we conducted a prospective birth cohort study in China, and aimed to investigate the association between maternal exposure to PM2.5 and the risk of GDM, identify the susceptible exposure window, and quantify the exposure-response relationships between PM2.5 and fasting glucose in GDM patients. A spatiotemporal land-use-regression model was used to estimate individual weekly PM2.5 exposure during pregnancy. A distributed lag nonlinear model incorporated with a Cox proportional hazard model was used to estimate the association between maternal exposure to PM2.5 and the risk of GDM. Among the 4174 pregnant women in our study, 1018 (24.4%) were diagnosed with GDM. Each 10 μg m−3 increment in PM2.5 exposures during the 24th gestational week was significantly associated with a higher risk of GDM [hazard ratio (HR) = 1.03, 95% CI (confidence interval): 1.01, 1.06]. Compared to the lowest quartile (Q1) of PM2.5 exposure, participants with the highest quartile (Q4) during the 21st–24th gestational weeks had a higher risk of GDM, and the strongest association was observed in the 22nd gestational week (HR = 1.15, 95%Cl: 1.02, 1.28). The mean PM2.5 exposures during the 21st–24th weeks were positively associated with fasting plasma glucose in pregnant women with GDM. Each 10 μg m−3 increase in the mean PM2.5 exposure was associated with a 0.07 mmol l−1 (95% CI: 0.04, 0.11 mmol l−1) increase in the fasting glucose level. Our findings suggest that maternal exposure to higher PM2.5 during pregnancy may increase the risk of GDM, and result in poor glycemic control among pregnant women with GDM. The 21st–24th gestational week period might be the (most)? susceptible exposure window of PM2.5.