Interaction of gut microbiota with the tumor microenvironment: A new strategy for antitumor treatment and traditional Chinese medicine in colorectal cancer.

Colorectal cancer (CRC) is one of the most common malignancies worldwide and the second leading cause of cancer-related death. In recent years, the relationship between gut microbiota and CRC has attracted increasing attention from researchers. Studies reported that changes in the composition of gut microbiota, such as increase in the number of Fusobacterium nucleatum and Helicobacter hepaticus, impair the immune surveillance by affecting the intestinal mucosal immunity and increase the risk of tumor initiation and progression. The tumor microenvironment is the soil for tumor survival. Close contacts between gut microbiota and the tumor microenvironment may directly affect the progression of tumors and efficacy of antitumor drugs, thus influencing the prognosis of patients with CRC. Recently, many studies have shown that traditional Chinese medicine can safely and effectively improve the efficacy of antitumor drugs, potentially through remodeling of the tumor microenvironment by regulated gut microbiota. This article describes the effect of gut microbiota on the tumor microenvironment and possible mechanisms concerning the initiation and progression of CRC, and summarizes the potential role of traditional Chinese medicine.

Joint COVID-19 and influenza-like illness forecasts in the United States using internet search information.

BACKGROUND: As the prolonged COVID-19 pandemic continues, severe seasonal Influenza (flu) may happen alongside COVID-19. This could cause a "twindemic", in which there are additional burdens on health care resources and public safety compared to those occurring in the presence of a single infection. Amidst the raising trend of co-infections of the two diseases, forecasting both Influenza-like Illness (ILI) outbreaks and COVID-19 waves in a reliable and timely manner becomes more urgent than ever. Accurate and real-time joint prediction of the twindemic aids public health organizations and policymakers in adequate preparation and decision making. However, in the current pandemic, existing ILI and COVID-19 forecasting models face shortcomings under complex inter-disease dynamics, particularly due to the similarities in symptoms and healthcare-seeking patterns of the two diseases. METHODS: Inspired by the interconnection between ILI and COVID-19 activities, we combine related internet search and bi-disease time series information for the U.S. national level and state level forecasts. Our proposed ARGOX-Joint-Ensemble adopts a new ensemble framework that integrates ILI and COVID-19 disease forecasting models to pool the information between the two diseases and provide joint multi-resolution and multi-target predictions. Through a winner-takes-all ensemble fashion, our framework is able to adaptively select the most predictive COVID-19 or ILI signals. RESULTS: In the retrospective evaluation, our model steadily outperforms alternative benchmark methods, and remains competitive with other publicly available models in both point estimates and probabilistic predictions (including intervals). CONCLUSIONS: The success of our approach illustrates that pooling information between the ILI and COVID-19 leads to improved forecasting models than individual models for either of the disease.

Data from the internet enables the presence of infectious diseases such as influenza (flu) to be tracked and monitored. During the ongoing COVID-19 pandemic people will also be infected with flu, impacting health care providers. Predicting both COVID-19 and flu outbreaks in a timely manner enables health care providers and policymakers to prepare for the outbreaks. In this work, we develop a model to jointly predict cases of both COVID-19 and influenza-like illness that can be used at national and state levels in the USA. Our approach is more accurate than alternative similar approaches that predict cases of a single disease, showing the value of predicting the incidence of multiple diseases at the same time.

The impact of dentists' availability in delivering dental care in Florida Elementary Schools.

OBJECTIVE: This study evaluates the dentists' availability to deliver preventive dental care to children in schools and the impact of school-based programs on access. METHODS: The study population included Florida elementary-school children, differentiated by dental insurance (Medicaid, CHIP, private, or none). We considered the implementation of school-based programs using optimization modeling to (re)allocate the dentists' caseload to schools to meet demand for preventive care under resource constraints. We considered multiple settings for school-based program implementation: (i) school prioritization; and (ii) dentists' participation in public insurance. Statistical inference was used to identify communities to improve access and reduce disparities. RESULTS: School-based programs reduced unmet demand (3%-12%), being more efficient if prioritizing schools in communities targeted to improve access. The access improvement varied by insurance status and geography. Uninsured urban children benefited most from school-based programs, with 15%-75% unmet need reduction. The percentage of urban communities targeted to improve access decreased by 12% against no-school program. Such percentage remained large for suburban (15%-100%) and rural (50%-100%) communities. Disparity in access for public-insured vs. private-insured children persisted under school-based programs (32%-84% identified communities). CONCLUSION: School-based programs improve dental care access; the improvement was however different by insurance status, with uninsured children benefiting the most. Accounting to the dentists' availability in prioritizing schools resulted in effective resource allocation to school-based programs. Access disparities between public and private-insured children did not improve; school-based programs shifted resources from public-insured to uninsured. School-based programs are effective in addressing access barriers to those children experiencing them most.

Lewis Acid-Base Adducts for Efficient and Stable Cesium-Based Lead Iodide-Rich Perovskite Solar Cells.

All-inorganic cesium-lead-iodide (CsPbI3 Br3- x (2 < x < 3)) perovskite presents preeminent photovoltaic performance and chemical stability. Unfortunately, this kind of material suffers from phase transition to a nonperovskite phase under oxidative chemical stresses. Herein, the introduction of a low concentration of Lewis acid-base adducts (LABAs) is reported to synergistically reduce defect density, optimize interfacial energy alignment, and improve device stability of CsPbI2.75 Br0.24 Cl0.01 (CsPbTh3 ) solar cells. Both theoretical simulations and experimental measurements reveal that the noncoordinating anions, PF6 - , as a Lewis base can more effectively bind with undercoordinated Pb2+ to passivate iodide vacancy defects than the BF4 - and absorbed I- , and thus the point defects are well suppressed. In addition, N-propyl-methyl piperidinium (NPMP+ ) is selected to assemble with PF6 - in CsPbTh3 film. The NPMP+ can regulate the crystal growth and finally homogenize the grain size and decrease the trap density. Consequently, the LABAs strategy can improve the power conversion efficiency of CsPbTh3 solar cells to 19.02% under 1-sun illumination (100 mW cm-2 ). Fortunately, the NPMP+ and PF6 - -treated CsPbTh3 film shows great phase stability after storage in ambient air for 250 days, and the power conversion efficiency of corresponding solar cells is almost 76% of the initial value after 60 days aging under ambient conditions.

COVID-19 forecasts using Internet search information in the United States.

As the COVID-19 ravaging through the globe, accurate forecasts of the disease spread are crucial for situational awareness, resource allocation, and public health decision-making. Alternative to the traditional disease surveillance data collected by the United States (US) Centers for Disease Control and Prevention (CDC), big data from Internet such as online search volumes also contain valuable information for tracking infectious disease dynamics such as influenza epidemic. In this study, we develop a statistical model using Internet search volume of relevant queries to track and predict COVID-19 pandemic in the United States. Inspired by the strong association between COVID-19 death trend and symptom-related search queries such as "loss of taste", we combine search volume information with COVID-19 time series information for US national level forecasts, while leveraging the cross-state cross-resolution spatial temporal framework, pooling information from search volume and COVID-19 reports across regions for state level predictions. Lastly, we aggregate the state-level frameworks in an ensemble fashion to produce the final state-level 4-week forecasts. Our method outperforms the baseline time-series model, while performing reasonably against other publicly available benchmark models for both national and state level forecast.

COVID-19 hospitalizations forecasts using internet search data.

As the COVID-19 spread over the globe and new variants of COVID-19 keep occurring, reliable real-time forecasts of COVID-19 hospitalizations are critical for public health decisions on medical resources allocations. This paper aims to forecast future 2 weeks national and state-level COVID-19 new hospital admissions in the United States. Our method is inspired by the strong association between public search behavior and hospitalization admissions and is extended from a previously-proposed influenza tracking model, AutoRegression with GOogle search data (ARGO). Our LASSO-penalized linear regression method efficiently combines Google search information and COVID-19 related time series information with dynamic training and rolling window prediction. Compared to other publicly available models collected from COVID-19 forecast hub, our method achieves substantial error reduction in a retrospective out-of-sample evaluation from Jan 4, 2021, to Dec 27, 2021. Overall, we showed that our method is flexible, self-correcting, robust, accurate, and interpretable, making it a potentially powerful tool to assist healthcare officials and decision making for the current and future infectious disease outbreaks.

Evaluating access to pediatric oral health care in the southeastern states.

BACKGROUND: In this article, the authors addressed shortcomings in existing research on pediatric oral health care access using rigorous data and methods for identifying statistically significant disparities in oral health care access for children. METHODS: The study population included children, differentiated by insurance status (Medicaid, Children's Health Insurance Program, private, none). The authors measured provider-level supply as the number of oral health care visits, stratified by provider type and urbanicity-rurality. The authors defined demand as the number of dental visits for children and derived demand and supply mainly from 2019 and 2020 data. Using statistical modeling, the authors evaluated where disparities in travel distance across communities or by insurance status were statistically significant. RESULTS: Although Dental Health Professional Shortage Areas are primarily rural, this study found that the proportions of rural, suburban, and urban communities identified for access interventions ranged from 24% through 66% and from 8% through 86%, respectively. For some states (Florida, Louisiana, Texas), rural and suburban communities showed a need for interventions for all children, whereas in the remaining states, the lack of Medicaid and Children's Health Insurance Program access mainly contributed to these disparities. Variations in access disparities with respect to insurance status across states or by urbanicity-rurality were extensive, with the rate of communities identified for reducing disparities ranging from 1% through 100%. CONCLUSIONS: All states showed a need for access interventions and for reducing disparities due to geographic location or insurance status. The sources of disparities were different across states, suggesting need for different policies and interventions across the 10 states. PRACTICAL IMPLICATIONS: The study findings support the need for policies toward reducing disparities in oral health care access.

Highly Efficient and Stable CsPbTh3 (Th = I, Br, Cl) Perovskite Solar Cells by Combinational Passivation Strategy.

The distorted lead iodide octahedra of all-inorganic perovskite based on triple halide-mixed CsPb(I2.85 Br0.149 Cl0.001 ) framework have made a tremendous breakthrough in its black phase stability and photovoltaic efficiency. However, their performance still suffers from severe ion migration, trap-induced nonradiative recombination, and black phase instability due to lower tolerance factor and high total energy. Here, a combinational passivation strategy to suppress ion migration and reduce traps both on the surface and in the bulk of the CsPhTh3 perovskite film is developed, resulting in improved power conversion efficiency (PCE) to as high as 19.37%. The involvement of guanidinium (GA) into the CsPhTh3 perovskite bulk film and glycocyamine (GCA) passivation on the perovskite surface and grain boundary synergistically enlarge the tolerance factor and suppress the trap state density. In addition, the acetate anion as a nucleating agent significantly improves the thermodynamic stability of GA-doped CsPbTh3 film through the slight distortion of PbI6 octahedra. The decreased nonradiative recombination loss translates to a high fill factor of 82.1% and open-circuit voltage (VOC ) of 1.17 V. Furthermore, bare CsPbTh3 perovskite solar cells without any encapsulation retain 80% of its initial PCE value after being stored for one month under ambient conditions.

Global Sensitivity Analysis via a Statistical Tolerance Approach.

Sensitivity analysis and multiparametric programming in optimization modeling study variations of optimal value and solutions in the presence of uncertain input parameters. In this paper, we consider simultaneous variations in the inputs of the objective and constraint (jointly called the RIM parameters), where the uncertainty is represented as a multivariate probability distribution. We introduce a tolerance approach based on principal component analysis, which obtains a tolerance region that is suited to the given distribution and can be considered a confidence set for the random input parameters. Since a tolerance region may contain parameters with different optimal bases, we extend the tolerance approach to the case where multiple optimal bases cover the tolerance region, by studying theoretical properties of critical regions (defined as the set of input parameters having the same optimal basis). We also propose a computational algorithm to find critical regions covering a given tolerance region in the RIM parameter space. Our theoretical results on geometric properties of critical regions contribute to the existing theory of parametric programming with an emphasis on the case where RIM parameters vary jointly, and provide deeper geometric understanding of critical regions. We evaluate the proposed framework using a series of experiments for sensitivity analysis, for model predictive control of an inventory management problem, and for large optimization problem instances.

Design of Driving Waveform for Shortening Response Time of Black Particles and White Particles in Three-Color Electrophoretic Displays.

The shortage of color in traditional electrophoretic displays (EPDs) can be compensated by three-color EPDs. However, the response time of black particles and white particles is increased. A new driving waveform based on the principle of three-color EPDs and electrophoresis theory was proposed to shorten the response time of black particles and white particles. The proposed driving waveform consisted of an erasing stage, an activation stage, a red driving stage, and a white or a black driving stage. The activation stage was mainly optimized in this paper. Firstly, the motion characteristics of the particles were analyzed using Stokes law and electrophoresis theory. Secondly, an optimal high frequency oscillation voltage was tested in order to improve the activity of the particles. Then, the influence of oscillation period and oscillation times on the activation stage were analyzed for optimizing the reference grayscale. According to the luminance of pixels, an oscillation period of 30 ms and an oscillation time of 30 were determined. The experimental results showed that the response time of black particles was shortened by 45%, and the response time of white particles was shortened by 40% compared with a traditional driving waveform.

Current status of group B Streptococcus infection in neonates: a multicenter prospective study. / 新生儿Bæ—é“¾çƒèŒæ„ŸæŸ“çŽ°çŠ¶çš„å¤šä¸­å¿ƒå‰çž»æ€§ç ”ç©¶.

OBJECTIVES: To investigate the incidence of maternal group B Streptococcus (GBS) colonization and neonatal early-onset GBS disease (GBS-EOD), and to study the factors associated with the development of GBS-EOD in the offspring of pregnant women with GBS colonization. METHODS: A total of 16 384 pregnant women and 16 634 neonates delivered by them were enrolled prospectively who had medical records in Xiamen Maternal and Child Care Hospital, Beijing Obstetrics and Gynecology Hospital of Capital Medical University, and Zhangzhou Zhengxing Hospital from May 1, 2019 to April 30, 2020. Unified GBS screening time, culture method, and indication for intrapartum antibiotic prophylaxis (IAP) were adopted in the three hospitals. The incidence rates of maternal GBS colonization and neonatal GBS-EOD were investigated. A multivariate logistic regression analysis was used to identify the factors associated with the development of GBS-EOD in the offspring of pregnant women with GBS colonization. RESULTS: In these three hospitals, the positive rate of GBS culture among the pregnant women in late pregnancy was 11.29% (1 850/16 384), and the incidence rate of neonatal GBS-EOD was 0.96‰ (16/16 634). The admission rate of live infants born to the GBS-positive pregnant women was higher than that of those born to the GBS-negative ones (P<0.05). The live infants born to the GBS-positive pregnant women had a higher incidence rate of GBS-EOD than those born to the GBS-negative ones [6.38‰ (12/1 881) vs 0.27‰ (4/14 725), P<0.05]. The multivariate logistic regression analysis showed that placental swabs positive for GBS and positive GBS in neonatal gastric juice at birth were independent predictive factors for the development of GBS-EOD (P<0.05), while adequate IAP was a protective factor (P<0.05) in the offspring of pregnant women with GBS colonization. CONCLUSIONS: GBS colonization of pregnant women in late pregnancy has adverse effects on their offspring. It is important to determine prenatal GBS colonization status of pregnant women and administer with adequate IAP based on the indications of IAP to reduce the incidence of neonatal GBS-EOD. Citation.

Design of Driving Waveform Based on a Damping Oscillation for Optimizing Red Saturation in Three-Color Electrophoretic Displays.

At present, three-color electrophoretic displays (EPDs) have problems of dim brightness and insufficient color saturation. In this paper, a driving waveform based on a damping oscillation was proposed to optimize the red saturation in three-color EPDs. The optimized driving waveform was composed of an erasing stage, a particles activation stage, a red electrophoretic particles purification stage, and a red display stage. The driving duration was set to 360 ms, 880 ms, 400 ms, and 2400 ms, respectively. The erasing stage was used to erase the current pixel state and refresh to a black state. The particles' activation stage was set as two cycles, and then refreshed to the black state. The red electrophoretic particles' purification stage was a damping oscillation driving waveform. The red and black electrophoretic particles were separated by changing the magnitude and polarity of applied electric filed, so that the red electrophoretic particles were purified. The red display stage was a low positive voltage, and red electrophoretic particles were driven to the common electrode to display a red state. The experimental results showed that the maximum red saturation could reach 0.583, which was increased by 27.57% compared with the traditional driving waveform.

HBV infection exacerbates PTEN defects in hepatocellular carcinoma through upregulation of miR-181a/382/362/19a.

A high hepatitis B virus (HBV) load and chronic hepatitis B infection are well-recognized risk factors for the development of hepatocellular carcinoma (HCC), highlighting the need for research into the mechanisms underlying the role of HBV infection in HCC. Because phosphatase and tensin homolog (PTEN) has been implicated in HCC development, we explored whether PTEN has a role in HBV-related hepatocarcinogenesis. We found that PTEN expression was correlated with advanced clinicopathological features and that HBV infection exacerbates PTEN defects in HCC. Using an integrated approach, we then investigated if miRNAs linked HBV infection to PTEN downregulation in HCC and found that PTEN was a target of miR-181a/382/362/19a. We also show that miR-181a/382/362/19a-mediated inhibition of PTEN led to an enhanced malignant phenotype and stimulation of AKT signaling in HCC cells. Collectively, our results indicate that HBV infection exacerbates PTEN defects in hepatocellular carcinoma through upregulation of miR-181a/362/382/19a. Our work implicates miR-181a/362/382/19a and PTEN as potential biomarkers and targets for novel prognostic, diagnostic, and therapeutic strategies targeting HBV-related HCC.

Clinical characteristics of critically ill patients co-infected with SARS-CoV-2 and the influenza virus in Wuhan, China.

OBJECTIVE: To delineate the clinical characteristics of critically ill COVID-19 patients co-infected with influenza. METHODS: This study included adult patients with laboratory-confirmed COVID-19 form Tongji Hospital (Wuhan, China), with or without influenza, and compared their clinical characteristics. RESULTS: Among 93 patients, 44 died and 49 were discharged. Forty-four (47.3%) were infected with influenza virus A and two (2.2%) with influenza virus B. Twenty-two (50.0%) of the non-survivors and 24 (49.0%) of the survivors were infected with the influenza virus. Critically ill COVID-19 patients with influenza were more prone to cardiac injury than those without influenza. For the laboratory indicators at admission the following were higher in non-survivors with influenza than in those without influenza: white blood cell counts, neutrophil counts, levels of tumor necrosis factor-α, D-dimer value, and proportion of elevated creatinine. CONCLUSION: The results showed that a high proportion of COVID-19 patients were co-infected with influenza in Tongji Hospital, with no significant difference in the proportion of co-infection between survivors and non-survivors. The critically ill COVID-19 patients with influenza exhibited more severe inflammation and organ injury, indicating that co-infection with the influenza virus may induce an earlier and more frequently occurring cytokine storm.

Etiological serotype and genotype distributions and clinical characteristics of group B streptococcus-inducing invasive disease among infants in South China.

BACKGROUND: Group B streptococcus (GBS)-induced invasive disease is a major cause of illness and death among infants aged under 90 days in China; however, invasive GBS infection remains unknown in China. We aimed to describe the serotype and genotype distributions of early-onset disease (EOD) and late-onset disease (LOD), and to show the clinical correlations among various GBS serotypes and genotypes obtained from infants with invasive GBS infections. METHODS: Between June 1, 2016 and June 1, 2018, 84 GBS strains were collected from patients younger than 90 days at seven Chinese hospitals. Clinical data were retrospectively reviewed. GBS serotyping was conducted and multi-locus sequence typing was performed. RESULTS: Serotypes Ia, Ib, II, III, and V were detected. Serotype III (60.71%) was the most common, followed by Ia (16.67%) and Ib (14.29%). Intrapartum temperature ≥ 37.5 °C, chorioamnionitis, and mortality were noted in 28.57, 42.86, and 28.57% of patients with serotype Ia, respectively, and these rates were higher than those in patients with serotypes Ib and III (P = 0.041, P = 0.031, and P = 0.023, respectively). The incidence of respiratory distress was lower (P = 0.039) while that of purulent meningitis was higher (P = 0.026) in the serotype III group. Eighteen sequence types were detected among isolates, and ST17 [42.86% (36/84)] was the most prevalent. CONCLUSIONS: GBS isolates belonging to serotypes Ia, Ib, and III are common in southern mainland China, and ST17 is highly prevalent. Differences were found in the clinical manifestations of invasive GBS disease induced by serotypes Ia and III.

Model-Free Lens Distortion Correction Based on Phase Analysis of Fringe-Patterns.

The existing lens correction methods deal with the distortion correction by one or more specific image distortion models. However, distortion determination may fail when an unsuitable model is used. So, methods based on the distortion model would have some drawbacks. A model-free lens distortion correction based on the phase analysis of fringe-patterns is proposed in this paper. Firstly, the mathematical relationship of the distortion displacement and the modulated phase of the sinusoidal fringe-pattern are established in theory. By the phase demodulation analysis of the fringe-pattern, the distortion displacement map can be determined point by point for the whole distorted image. So, the image correction is achieved according to the distortion displacement map by a model-free approach. Furthermore, the distortion center, which is important in obtaining an optimal result, is measured by the instantaneous frequency distribution according to the character of distortion automatically. Numerical simulation and experiments performed by a wide-angle lens are carried out to validate the method.

LINC01149 variant modulates MICA expression that facilitates hepatitis B virus spontaneous recovery but increases hepatocellular carcinoma risk.

Interpreting disease-causing variants, especially in noncoding regions by genome-wide association studies (GWAS), has become one of the most challenging and demanding tasks. We hypothesized that functional lncRNAs variants in GWAS-identified loci might alter expression level of genes associated with persistent HBV infection and hepatocellular carcinoma (HCC). Integrated bioinformatics approaches were used to prioritize potentially functional variants and a two-stage case-control study (2473 HBV positive HCC patients, 2248 persistent HBV carriers and 2294 spontaneously recovered subjects) was performed to assess the roles of these variants. The rs2844512 G > C variant in LINC01149 was identified to facilitate HBV spontaneous recovery (OR = 0.84, 95% CI = 0.77-0.92) but increase the risk of HCC (OR = 1.21, 95% CI = 1.11-1.32) in combined samples. Subsequent biological assays indicated this variant created a binding site for miR-128-3p and upregulated MICA expression by serving as a miRNA sponge, which might recruit NK-cells to lyse infected cells, but release highly soluble MICA by shedding to induce NK-cells exhaustion and tumor immune evasion. These findings highlight a regulatory circuit between LINC01149 and MICA, mediating by miR-128-3p, and the important role of upregulated MICA in conferring susceptibility to persistent HBV infection and HCC.

Long noncoding RNA MAFG-AS1 promotes proliferation, migration and invasion of hepatocellular carcinoma cells through downregulation of miR-6852.

Long noncoding RNAs (lncRNAs) have been shown to participate in the development and progression of a number of different types of cancer, including hepatocellular carcinoma (HCC). A recent report has indicated that lncRNA MAFG-antisense 1 (AS1) promotes colorectal cancer. However, the role of MAFG-AS1 in other types of cancer remains unclear. The aim of the present study was to examine the effect of lncRNA MAFG-AS1 in HCC. Based on The Cancer Genome Atlas database and reverse transcription-quantitative PCR results, it was determined that lncRNA MAFG-AS1 expression was increased in HCC tissues and cell lines. Following knockdown of lncRNA MAFG-AS1, a Cell Counting Kit-8 assay and Transwell assay demonstrated that the proliferation, migration and invasion of HCC cell lines were significantly inhibited. It was additionally demonstrated that there was a negative regulatory association between lncRNA MAFG-AS1 and miR-6852. Inhibition of miR-6852 increased proliferation, migration and invasion of HCC cell lines. LncRNA MAFG-AS1 promoted HCC development by dampening miR-6852 function and may thus be a novel target for treating patients with HCC.

IL-23 enhances the malignant properties of hepatoma cells by attenuation of HNF4α.

Chronic infection with hepatitis B virus (HBV) is one of the major risk factors for hepatocellular carcinoma. HBV infection can induce the expression of IL-23. However, the effects of IL-23 on carcinogenesis are rare and contradictory. To investigate the potential role of IL-23 on malignant properties of hepatoma cells, in the present study, first, we confirmed that HBV drove infected hepatoma cells to produce more IL-23. And then we found that at low concentration, human recombinant IL-23 (hrIL-23) enhanced malignant properties of hepatoma cells through increasing the proportion of stem/progenitor cells, promoting proliferation and colony formation, reducing apoptosis and inducing motility and invasivity of them. Hepatocyte nuclear factor 4 alpha (HNF4α), which is essential for liver development and hepatocyte function, was found to be downregulated in HBV integrated or transiently transfected hepatoma cells. Its expression was also decreased in cells treated by hrIL-23 or by HepG2.215 culture supernatant and this decrease could be abolished by supplementation of anti-IL-23p19 antibody. Hence, it is speculated that HBV related IL-23 can enhance malignant properties of hepatoma cells through attenuation of HNF4α. The findings identified a potential target of interventional strategies for treating hepatitis B patients through manipulation of the IL-23.

GRP78 Impairs Production of Lipopolysaccharide-Induced Cytokines by Interaction with CD14.

The 78-kDa glucose-regulated protein (GRP78) is a stress-inducible chaperone that resides primarily in the endoplasmic reticulum. GRP78 has been described to be released at times of cellular stress and as having extracellular properties that are anti-inflammatory or favor the resolution of inflammation. In the current study, we confirmed that GRP78 impaired the production of lipopolysaccharide-induced pro-inflammatory cytokines in GRP78-treated bone-marrow-derived dendritic cells (DCs). To explore the underlying mechanism, first of all, GRP78 was checked to be bound to the plasma membrane. Interestingly, such binding promoted endocytosis of toll-like receptor (TLR) 4 and reduction in TLR4 on the plasma surface had a key role in desensitization of GRP78-treated DCs to lipopolysaccharide. Given that cluster of differentiation (CD)14 is a crucial regulator of TLR4 endocytosis, interaction of GRP78 with CD14 was investigated next. Data showed that GRP78 co-localized with CD14 on the plasma membrane and glutathione-S-transferase-GRP78 precipitated CD14. In CD14 knockout mice, down-regulation of tumor necrosis factor-α and reduction in TLR4 on the plasma surface were abrogated in GRP78-treated DCs. Overall, these data suggested that GRP78 mediates endocytosis of TLR4 by targeting CD14 to favor the resolution of inflammation.