Deep Reinforcement Learning-Based Approach for Efficient and Reliable Droplet Routing on MEDA Biochips

The micro-electrode-dot-array (MEDA) architecture provides precise droplet control and real-time sensing in digital microfluidic biochips. Previous work has shown that trapped charge under microelectrodes (MCs) leads to droplets being stuck and failures in fluidic operations. A recent approach utilizes real-time sensing of MC health status, and attempts to avoid degraded electrodes during droplet routing. However, the problem with this solution is that the computational complexity is unacceptable for MEDA biochips of realistic size. Consequently, in this work, we introduce a deep reinforcement learning (DRL)-based approach to bypass degraded electrodes and enhance the reliability of routing. The DRL model utilizes the information of health sensing in real time to proactively reduce the likelihood of charge trapping and avoid using degraded MCs. Simulation results show that our approach provides effective routing strategies for COVID-19 testing protocols. We also validate our DRL-based approach using fabricated prototype biochips. Experimental results show that the developed DRL model completed the routing tasks using a fewer number of clock cycles and shorter total execution time, compared with a baseline routing method. Moreover, our DRL-based approach provides reliable routing strategies even in the presence of degraded electrodes. Our experimental results show that the proposed DRL-based routing is robust to occurrences of electrode faults, as well as increases the lifetime and usability of microfluidic biochips compared to existing strategies.

Effect of wearing medical protective masks on treadmill running performance in the postpandemic era: a randomised trial.

BACKGROUND: In the postpandemic era, wearing protective masks in public places will still be an important means of blocking popular viruses in the future. The purpose of this study was to explore whether sports performance was affected by mask wearing and exercise duration during 15-min treadmill running at a speed of 75% maximal aerobic speed. METHODS: Thirty-six males were randomly divided into mask and nonmask groups. The kinematic and kinetic data were obtained at four time points (RN0-1 min, RN5-6 min, RN9-10 min, and RN14-15 min) during running. Two-way mixed ANOVA was applied to examine the effects between groups and times with Bonferroni post hoc comparison and independent samples t-test. RESULTS: The results showed that there was no difference between mask and nonmask group during running (p > 0.05). As running time increased, hip joint ROM, hip joint flexion/extension max, and ankle joint plantarflexion max angles increased; knee joint flexion min and ankle joint dorsiflexion max angles decreased; average peak vertical ground reaction forces (PVGRF) increased after 9 min-running (p < 0.05). CONCLUSIONS: Wearing a medical protective mask does not affect the joint angle and touchdown PVGRF of lower extremities during treadmill running while affected by running time and changed after 9 min-treadmill running. Future studies will examine the effects of wearing masks during the pandemic on muscle activation and blood biochemical values during exercise. TRIAL REGISTRATION NO: ChiCTR2000040535 (date of registration on December 1, 2020). Prospectively registered in the Chinese Clinical Trial Registry.

ZBP1: A Powerful Innate Immune Sensor and Double-Edged Sword in Host Immunity.

Z-conformation nucleic acid binding protein 1 (ZBP1), a powerful innate immune sensor, has been identified as the important signaling initiation factor in innate immune response and the multiple inflammatory cell death known as PANoptosis. The initiation of ZBP1 signaling requires recognition of left-handed double-helix Z-nucleic acid (includes Z-DNA and Z-RNA) and subsequent signaling transduction depends on the interaction between ZBP1 and its adapter proteins, such as TANK-binding kinase 1 (TBK1), interferon regulatory factor 3 (IRF3), receptor-interacting serine/threonine-protein kinase 1 (RIPK1), and RIPK3. ZBP1 activated innate immunity, including type-I interferon (IFN-I) response and NF-κB signaling, constitutes an important line of defense against pathogenic infection. In addition, ZBP1-mediated PANoptosis is a double-edged sword in anti-infection, auto-inflammatory diseases, and tumor immunity. ZBP1-mediated PANoptosis is beneficial for eliminating infected cells and tumor cells, but abnormal or excessive PANoptosis can lead to a strong inflammatory response that is harmful to the host. Thus, pathogens and host have each developed multiplex tactics targeting ZBP1 signaling to maintain strong virulence or immune homeostasis. In this paper, we reviewed the mechanisms of ZBP1 signaling, the effects of ZBP1 signaling on host immunity and pathogen infection, and various antagonistic strategies of host and pathogen against ZBP1. We also discuss existent gaps regarding ZBP1 signaling and forecast potential directions for future research.

Promoting economic and environmental resilience in the post-COVID-19 era through the city and regional on-road fuel sustainability development

How to control the global temperature rise within 1.5 °C in the post-COVID-19 era has attracted attention. Road transport accounts for nearly a quarter of global CO2 emissions, and the related sulfur dioxide (SO2) emissions also trigger air pollution issues in population-intensive cities and areas. Many cities and states have announced a timetable for phasing out urban-based fossil fuel vehicles. By combining a Markov-chain model with a dynamic stochastic general equilibrium (DSGE) model, the impacts of on-road energy structural change led by phasing out fossil fuel vehicles in the road transportation sector are evaluated. The impact of automobile emissions (both CO2 and SO2) on the environment is evaluated, taking into consideration of variation between cities, regions, and countries. Two other major driving forces in addition to CO2 emissions reduction in promoting fossil fuel vehicles' transition toward net-zero carbon are identified and analyzed with multiple different indicators. Under the framework of the DSGE model, climate policy instruments' effects on economic development, energy consumption, and their link to economic and environmental resilience are evaluated under exogenous shocks as well.

Airport terminal passenger forecast under the impact of COVID-19 outbreaks: A case study from China

Passengers significantly affect airport terminal energy consumption and indoor environmental quality. Accurate passenger forecasting provides important insights for airport terminals to optimize their operation and management. However, the COVID-19 pandemic has greatly increased the uncertainty in airport passenger since 2020. There are insufficient studies to investigate which pandemic-related variables should be considered in forecasting airport passenger trends under the impact of COVID-19 outbreaks. In this study, the interrelationship between COVID-19 pandemic trends and passenger traffic at a major airport terminal in China was analyzed on a day-by-day basis. During COVID-19 outbreaks, three stages of passenger change were identified and characterized, i.e., the decline stage, the stabilization stage, and the recovery stage. A typical "sudden drop and slow recovery” pattern of passenger traffic was identified. A LightGBM model including pandemic variables was developed to forecast short-term daily passenger traffic at the airport terminal. The SHapley Additive exPlanations (SHAP) values was used to quantify the contribution of input pandemic variables. Results indicated the inclusion of pandemic variables reduced the model error by 27.7% compared to a baseline model. The cumulative numbers of COVID-19 cases in previous weeks were found to be stronger predictors of future passenger traffic than daily COVID-19 cases in the most recent week. In addition, the impact of pandemic control policies and passengers' travel behavior was discussed. Our empirical findings provide important implications for airport terminal operations in response to the on-going COVID-19 pandemic.

Path to sustainable development: Does digital economy matter in manufacturing green total factor productivity?

In the context of the outbreak of the COVID-19 pandemic and China's "digital power" strategy, the realization of a green shift of manufacturing has become a necessary condition to promote the economy, and the digital factor has increasingly become a new driving force. The DEA-Malmquist index and entropy method were used to measure the manufacturing green total factor productivity (GTFP) and the level of digital economy level from 2011 to 2018, respectively. This study then explored the impact of digital economy on manufacturing GTFP based on the system generalized method of moments (GMM) model, as well as the adjustment effects of talent aggregation and financial scale according to the moderating model. This research came to four conclusions. (1) The digital economy can significantly improve the manufacturing GTFP of China, and the influence shows the characteristic of a "marginal increase";(2) notably, the perspective of manufacturing GTFP decomposition indicates that the digital economy exerts a significant positive effect on manufacturing technical efficiency during the current period but obviously hinders technical progress;(3) interestingly, a mechanistic test showed that the two dimensions of innovation environment-talent aggregation (0.385) and financial scale (0.359)-play critical moderating roles in the influencing process;and (4) the influence has evident regional heterogeneity-it is significantly positive in the east and negative in the central region and west. Finally, corresponding policy suggestions are suggested.

Factors influencing parents' willingness to vaccinate their preschool children against COVID-19: Results from the mixed-method study in China.

During the COVID-19 pandemic, little is known about parental hesitancy to receive the COVID-19 vaccine for preschool children who are the potential vaccinated population in the future. The purpose of this mixed-method study was to explore the factors influencing Chinese parents' decision to vaccinate their children aged 3-6 years old against COVID-19. In July 2021, we conducted semi-structured interviews (n = 19) and a cross-sectional survey (n = 2605) with parents of kindergarten children in an urban-rural combination pilot area in China. According to the qualitative study, most parents were hesitant to vaccinate their children with the COVID-19 vaccine. In the quantitative study, we found that three-fifths of 2605 participants were unwilling to vaccinate their children against COVID-19. Furthermore, the main predictors of parents' intention to vaccinate their children were fathers, lower level of education, and positive attitudes toward vaccination. Based on our findings, targeted health education techniques may be able to boost childhood COVID-19 immunization rates.

A multitope SARS-CoV-2 vaccine provides long-lasting B cell and T cell immunity against Delta and Omicron variants.

BackgroundThe Delta and Omicron variants of SARS-CoV-2 are currently responsible for breakthrough infections due to waning immunity. We report phase I/II trial results of UB-612, a multitope subunit vaccine containing S1-RBD-sFc protein and rationally designed promiscuous peptides representing sarbecovirus conserved helper T cell and cytotoxic T lymphocyte epitopes on the nucleocapsid (N), membrane (M), and spike (S2) proteins.MethodWe conducted a phase I primary 2-dose (28 days apart) trial of 10, 30, or 100 µg UB-612 in 60 healthy young adults 20 to 55 years old, and 50 of them were boosted with 100 µg of UB-612 approximately 7 to 9 months after the second dose. A separate placebo-controlled and randomized phase II study was conducted with 2 doses of 100 µg of UB-612 (n = 3,875, 18-85 years old). We evaluated interim safety and immunogenicity of phase I until 14 days after the third (booster) dose and of phase II until 28 days after the second dose.ResultsNo vaccine-related serious adverse events were recorded. The most common solicited adverse events were injection site pain and fatigue, mostly mild and transient. In both trials, UB-612 elicited respective neutralizing antibody titers similar to a panel of human convalescent sera. The most striking findings were long-lasting virus-neutralizing antibodies and broad T cell immunity against SARS-CoV-2 variants of concern (VoCs), including Delta and Omicron, and a strong booster-recalled memory immunity with high cross-reactive neutralizing titers against the Delta and Omicron VoCs.ConclusionUB-612 has presented a favorable safety profile, potent booster effect against VoCs, and long-lasting B and broad T cell immunity that warrants further development for both primary immunization and heterologous boosting of other COVID-19 vaccines.Trial RegistrationClinicalTrials.gov: NCT04545749, NCT04773067, and NCT04967742.FundingUBI Asia, Vaxxinity Inc., and Taiwan Centers for Disease Control, Ministry of Health and Welfare.

Aberrant Cholesterol Metabolic Genes Regulation in a Negative Feedback Loop Induced by an Alphacoronavirus.

Porcine epidemic diarrhea virus (PEDV) is an alphacoronavirus that causes acute inflammation and severe diarrhea in newborn piglets with a high mortality rate. Given that cholesterol is required for coronavirus infection in vitro, the role of endogenous cholesterol metabolism in regulating coronavirus infection and the mechanism behind it ought to be elucidated. In this study, we found that the levels of cholesterol and bile acids were both elevated in the livers of PEDV-infected piglets compared to those of the control group. Consistently, in the livers of PEDV-infected piglets, the expression of key genes involved in cholesterol metabolism was significantly increased. Transcriptomic analysis indicated that the cholesterol homeostasis pathway was among the most enriched pathways in the livers of PEDV-infected piglets. Unexpectedly, the expression of key genes in the cholesterol metabolic pathway was downregulated at the messenger RNA (mRNA) level, but upregulated at the protein level. While the primary transcriptional factors (TFs) of cholesterol metabolism, including SREBP2 and FXR, were upregulated at both mRNA and protein levels in response to PEDV infection. Further Chromatin Immunoprecipitation Quantitative Real-time PCR (ChIP-qPCR) analysis demonstrated that the binding of these TFs to the locus of key genes in the cholesterol metabolic pathway was remarkably inhibited by PEDV infection. It was also observed that the occupancies of histone H3K27ac and H3K4me1, at the locus of the cholesterol metabolic genes HMGCR and HMGCS1, in the livers of PEDV-infected piglets, were suppressed. Together, the PEDV triggers an aberrant regulation of cholesterol metabolic genes via epigenetic inhibition of SREBP2/FXR-mediated transcription, which provides a novel antiviral target against PEDV and other coronaviruses.

Visualized Analyses of Investigations Upon Mesenchymal Stem/stromal Cell-based Cytotherapy and Underlying Mechanisms for COVID-19 Associated ARDS.

The outbreak of coronavirus disease 2019 (COVID-19) triggered by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has become a widespread pandemic globally and seriously threatened public health. Patients with COVID-19 infection, and in particular, those with severe pneumonia-associated acute respiratory distress syndrome (ARDS) manifested rapid disease progression and the resultant high mortality and morbidity. Advances in fundamental and clinical studies have suggested the feasibility of mesenchymal stem/stromal cell (MSC)-based therapy as an inspiring alternative for ARDS administration. However, the systematic characteristics of the MSC-based cytotherapy and underlying mechanism for COVID-19 associated ARDS by bibliometric analyses are still unknowable. Herein, we took advantage of visual analyses to reveal the overview of ARDS-associated updates, core authors and focused issues, as well as to summarize the comprehensive knowledge of the keywords, authors, institutions with the aid of indicated software. Meanwhile, we have provided a brief overview on the molecular mechanisms and discussed the safety and efficacy of MSC-based therapy for ARDS on the basis of clinical trials.

Potent Anti-Delta Effect By a Booster Third-Dose of UB-612, a Precision-Designed SARS-CoV-2 Multitope Protein-Peptide Vaccine (preprint)

SARS-CoV-2 breakthrough infection occurs due to waning immunity time-to-vaccine, to which the globally-dominant, highly-contagious Delta variant is behind the scene. In the primary 2-dose and booster series of clinical Phase-1 trial, UB-612 vaccine, which contains S1-RBD and synthetic Th/CTL peptide pool for activation of humoral and T-cell immunity, induces substantial, prolonged viral-neutralizing antibodies that goes parallel with a long-lasting T-cell immunity; and a booster (3rd ) dose can prompt recall of memory immunity to induce profound, striking antibodies with the highest level of 50% viral-neutralizing GMT titers against live Delta variant reported for any vaccine. The unique design of S1-RBD only plus multitope T-cell peptides may have underpinned UB-612’s potent anti-Delta effect, while the other full S protein-based vaccines are affected additionally by mutations in the N-terminal domain sequence which contains additional neutralizing epitopes. UB-612, safe and well-tolerated, could be effective for boosting other vaccine platforms that have shown modest homologous boosting. [Funded by United Biomedical Inc., Asia; ClinicalTrials.gov ID: NCT04967742 and NCT04545749]

Energy consumption structural adjustment and carbon neutrality in the post-COVID-19 era.

Since the spread of COVID-19 pandemic all over the world, a significant recession has broken out with no precedent. China has brought up a new voluntary contribution target that achieving carbon neutrality by 2060. How to achieve climate change mitigation targets without heavily hindering economic development is of great importance in the future. In this study, a Markov chain model is employed to forecast primary energy consumption (PEC) structure and verify whether the carbon intensity target would be achieved under three scenarios with different economic growth rates, such as 6.1%, 4.2%, and 2.3%, respectively. A multi-sector dynamic stochastic general equilibrium (DSGE) model is employed to simulate and evaluate economic development, fossil and non-fossil energy consumption, and CO2 emissions under three scenarios using data calibration according to the Markov chain prediction result. The prediction results from the Markov chain show that energy structural adjustment can help us achieve the carbon intensity target of 2030 under both steady and mid-speed development scenarios. As long as the economic growth rate is higher than 4.2%, the carbon intensity target can be achieved mainly through energy consumption structural change, which provides a way to achieve the carbon neutrality target of 2060. The simulation results from the DSGE model show that energy structural adjustment can also smooth the volatility of the economic fluctuation when exogenous stochastic shocks happened.

Asymmetric impact of temperature on COVID-19 spread in India: Evidence from quantile-on-quantile regression approach.

The emergence of new coronavirus (SARS-CoV-2) has become a significant public health issue worldwide. Some researchers have identified a positive link between temperature and COVID-19 cases. However, no detailed research has highlighted the impact of temperature on COVID-19 spread in India. This study aims to fill this research gap by investigating the impact of temperature on COVID-19 spread in the five most affected Indian states. Quantile-on-Quantile regression (QQR) approach is employed to examine in what manner the quantiles of temperature influence the quantiles of COVID-19 cases. Empirical results confirm an asymmetric and heterogenous impact of temperature on COVID-19 spread across lower and higher quantiles of both variables. The results indicate a significant positive impact of temperature on COVID-19 spread in the three Indian states (Maharashtra, Andhra Pradesh, and Karnataka), predominantly in both low and high quantiles. Whereas, the other two states (Tamil Nadu and Uttar Pradesh) exhibit a mixed trend, as the lower quantiles in both states have a negative effect. However, this negative effect becomes weak at middle and higher quantiles. These research findings offer valuable policy recommendations.

What is the relationship between government response and COVID-19 pandemics? Global evidence of 118 countries.

Using daily data of novel coronavirus pneumonia (COVID-19) covering 118 countries from January 1 to April 13, 2021, this research examines the relationship between the government response stringency index (GRSI) and COVID-19 pandemic. The empirical results show that GRSI significantly negatively impacts confirmed cases, and the effects are especially larger around 14 to 21 days after the implementation of the government response. These results are robust through analysis with sub-samples of Asian countries and non-Asian countries, proving that public prevention policies of being isolated for 14 days and being observed for 7 days are effective. The Dumitrescu-Hurlin causality test uncovers a statistically significant bi-directional correlation between government response stringency and COVID-19 pandemic when analyzing the full samples. In terms of the sub-samples, a bi-directional relationship exists between government response stringency and confirmed cases, while one-way causality runs only from government response stringency to deaths in Asian countries. We offer a policy implication that countries all over the world should continue to carry out public prevention policies, and governments in non-Asian countries should be more concerned about confirmed cases.

Does temperature matter for COVID-19 transmissibility? Evidence across Pakistani provinces.

The outbreak of novel coronavirus (COVID-19) has become a global concern that is deteriorating environmental quality and damaging human health. Though some researchers have investigated the linkage between temperature and COVID-19 transmissibility across different geographical locations and over time, yet these studies are scarce. This study aims to bridge this gap using daily temperature and COVID-19 cases (transmissibility) by employing grey incidence analysis (GIA) models (i.e., Deng's grey incidence analysis (DGIA), the absolute degree GIA (ADGIA), the second synthetic degree GIA (SSDGIA), the conservative (maximin) model) and correlation analysis. Data on temperature are accessed from the NASA database, while the data on COVID-19 cases are collected from the official website of the government of Pakistan. Empirical results reveal the existence of linkages between temperature and COVID-19 in all Pakistani provinces. These linkages vary from a relatively stronger to a relatively weaker linkage. Based on calculated weights, the strength of linkages is ranked across provinces as follows: Gilgit Baltistan (0.715301) > Baluchistan (0.675091) > Khyber Pakhtunkhwa (0.619893) > Punjab (0.619286) > Sindh (0.601736). The disparity in the strength of linkage among provinces is explained by the discrepancy in the intensity of temperature. Besides, the diagrammatic correlation analysis shows that temperature is inversely linked to COVID-19 cases (per million persons) over time, implying that low temperatures are associated with high COVID-19 transmissibility and vice versa. This study is among the first of its kind to consider the linkages between temperature and COVID-19 transmissibility for a tropical climate country (Pakistan) using the advanced GIA models. Research findings provide an up-to-date glimpse of the outbreak and emphasize the need to raise public awareness about the devastating impacts of the COVID-19. The educational syllabus should provide information on the causes, signs, and precautions of the pandemic. Additionally, individuals should practice handwashing, social distancing, personal hygiene, mask-wearing, and the use of hand sanitizers to ensure a secure and supportive atmosphere for preventing and controlling the current pandemic.

Symptomatic features and prognosis of 932 hospitalized patients with coronavirus disease 2019 in Wuhan.

OBJECTIVE: To discern the symptomatic features of coronavirus disease 2019 (COVID-19) and to evaluate the severity and prognosis of the disease. METHODS: In this retrospective cohort study, 932 hospitalized patients with COVID-19 in Wuhan were enrolled, including 52 severe and 880 non-severe cases. All patients were followed up for 3 months after discharge. The symptomatic features and follow-up data of the patients in both groups were analyzed and compared. RESULTS: Of the 932 patients, fever (60.0%), cough (50.8%) and fatigue (36.4%) were the most common symptoms. In total, 32.7% of the severe cases presented with gastrointestinal symptoms at disease onset, including anorexia, nausea, vomiting or diarrhea, which was significantly higher than that of the non-severe group (P = 0.0015). The incidence of olfactory disturbance and dysgeusia was only 3.1% and 6.2%, respectively. After adjusting for age and sex, multivariate regression analysis showed that fever lasting for over 5 days (odds ratio [OR] 1.90, 95% confidence interval [CI] 1.00-3.62, P = 0.0498), anorexia at onset (OR 2.61, 95% CI 1.26-5.40, P = 0.0096), and modified Medical Research Council level above grade 2 when dyspnea occurred (OR 14.19, 95% CI 7.01-28.71, P < 0.0001) were symptomatic risk factors for severe COVID-19. During the follow-up, cough (6.2%), dyspnea (7.2%), fatigue (1.8%), olfactory disturbance and dysgeusia (1.5%) were the significant remaining symptoms. CONCLUSIONS: COVID-19 causes clusters of symptoms with multiple systems involved. Certain symptomatic characteristics have predictive value for severe COVID-19. Short-term follow-up data reveal that most patients have a good prognosis.

Combined intravenous immunoglobulin and baricitinib treatment for severe COVID-19 with rhabdomyolysis: A case report.

Since December 2019, the outbreak of coronavirus disease 2019 (COVID-19) has spread rapidly around the world. The severity of COVID-19 ranges from asymptomatic carriers to severe acute respiratory distress syndrome (ARDS). Accumulating evidence has shown that COVID-19 may be associated with multiple organ complications including cardiac injury, viral myositis and neurological deficits. Numerous laboratory biomarkers including lymphocytes, platelets, lactate dehydrogenase and creatine kinase (CK) have been associated with the prognostic outcomes of patients with COVID-19. However, dynamic correlations between levels of biomarkers and clinical course have not been studied. Herein, we report a 74-year-old female patient with severe COVID-19 which progressed to ARDS requiring intubation and mechanical ventilation. The laboratory findings showed lymphopenia, hypogammaglobulinemia, and elevated inflammatory biomarkers and CK. She received intensive therapy with hydroxychloroquine, lopinavir/ritonavir, and azithromycin with limited effects. Immunomodulatory treatments with high dose intravenous immunoglobulin and baricitinib were prescribed with satisfactory biochemical, radiographic and clinical recovery. We found an interesting correlation between serum CK elevation and inflammatory biomarkers, which reflected clinical improvement. This case demonstrates that inflammatory biomarkers, cytokines, and CK level correlated with disease severity and treatment response, and combined use of intravenous immunoglobulin and baricitinib is a potential treatment in patients with severe COVID-19.

Acidic preconditioning reduces lipopolysaccharide-induced acute lung injury by upregulating the expression of angiotensin-converting enzyme 2.

Acid preconditioning (APC) through carbon dioxide inhalation can exert protective effects during acute lung injury (ALI) triggered by ischemia-reperfusion. Angiotensin-converting enzyme 2 (ACE2) has been identified as a receptor for severe acute respiratory syndrome coronavirus and the novel coronavirus disease-19. Downregulation of ACE2 plays an important role in the pathogenesis of severe lung failure after viral or bacterial infections. The aim of the present study was to examine the anti-inflammatory mechanism through which APC alleviates lipopolysaccharide (LPS)-induced ALI in vivo and in vitro. The present results demonstrated that LPS significantly downregulated the expression of ACE2, while APC significantly reduced LPS-induced ALI and provided beneficial effects. In addition, bioinformatics analysis indicated that microRNA (miR)-200c-3p directly targeted the 3'untranslated region of ACE2 and regulated the expression of ACE2 protein. LPS exposure inhibited the expression of ACE2 protein in A549 cells by upregulating the levels of miR-200c-3p. However, APC inhibited the upregulation of miR-200c-3p induced by LPS, as well as the downregulation of ACE2 protein, through the NF-κB pathway. In conclusion, although LPS can inhibit the expression of ACE2 by upregulating the levels of miR-200c-3p through the NF-κB pathway, APC inhibited this effect, thus reducing inflammation during LPS-induced ALI.