ILT4 drives B7-H3 expression via PI3K/AKT/mTOR signalling and ILT4/B7-H3 co-expression correlates with poor prognosis in non-small cell lung cancer

AbstractImmunoglobulin-like transcript (ILT) 4 is critical for the inhibitory function of certain immune cells. We previously demonstrated that ILT4 is over-expressed in human non-small cell lung cancer (NSCLC) cells and is involved in tumour evasion via an unknown mechanism. In this report, we demonstrate that ILT4 increases the expression of the co-inhibitory molecule B7-H3 through PI3K/AKT/mTOR signalling. In primary human NSCLC tissues, a significant positive relationship is observed between ILT4 and B7-H3 expression. ILT4/B7-H3 co-expression is significantly associated with a reduction in T infiltrating lymphoid cells and lower overall survival. In summary, ILT4 increases B7-H3 expression and ILT4/B7-H3 co-expression may be involved in NSCLC progression

Actively implementing an evidence-based feeding guideline for critically ill patients (NEED): a multicenter, cluster-randomized, controlled trial

Background: Previous cluster-randomized controlled trials evaluating the impact of implementing evidence-based guidelines for nutrition therapy in critical illness do not consistently demonstrate patient benefits. A large-scale, sufficiently powered study is therefore warranted to ascertain the effects of guideline implementation on patient-centered outcomes. Methods: We conducted a multicenter, cluster-randomized, parallel-controlled trial in intensive care units (ICUs) across China. We developed an evidence-based feeding guideline. ICUs randomly allocated to the guideline group formed a local "intervention team", which actively implemented the guideline using standardized educational materials, a graphical feeding protocol, and live online education outreach meetings conducted by members of the study management committee. ICUs assigned to the control group remained unaware of the guideline content. All ICUs enrolled patients who were expected to stay in the ICU longer than seven days. The primary outcome was all-cause mortality within 28 days of enrollment. Results: Forty-eight ICUs were randomized to the guideline group and 49 to the control group. From March 2018 to July 2019, the guideline ICUs enrolled 1399 patients, and the control ICUs enrolled 1373 patients. Implementation of the guideline resulted in significantly earlier EN initiation (1.20 vs. 1.55 mean days to initiation of EN; difference − 0.40 [95% CI − 0.71 to − 0.09]; P = 0.01) and delayed PN initiation (1.29 vs. 0.80 mean days to start of PN; difference 1.06 [95% CI 0.44 to 1.67]; P = 0.001). There was no significant difference in 28-day mortality (14.2% vs. 15.2%; difference − 1.6% [95% CI − 4.3% to 1.2%]; P = 0.42) between groups. Conclusions: In this large-scale, multicenter trial, active implementation of an evidence-based feeding guideline reduced the time to commencement of EN and overall PN use but did not translate to a reduction in mortality from critical illness. Trial registration: ISRCTN, ISRCTN12233792. Registered November 20th, 2017

Actively implementing an evidence-based feeding guideline for critically ill patients (NEED): a multicenter, cluster-randomized, controlled trial.

BackgroundPrevious cluster-randomized controlled trials evaluating the impact of implementing evidence-based guidelines for nutrition therapy in critical illness do not consistently demonstrate patient benefits. A large-scale, sufficiently powered study is therefore warranted to ascertain the effects of guideline implementation on patient-centered outcomes.MethodsWe conducted a multicenter, cluster-randomized, parallel-controlled trial in intensive care units (ICUs) across China. We developed an evidence-based feeding guideline. ICUs randomly allocated to the guideline group formed a local "intervention team", which actively implemented the guideline using standardized educational materials, a graphical feeding protocol, and live online education outreach meetings conducted by members of the study management committee. ICUs assigned to the control group remained unaware of the guideline content. All ICUs enrolled patients who were expected to stay in the ICU longer than seven days. The primary outcome was all-cause mortality within 28 days of enrollment.ResultsForty-eight ICUs were randomized to the guideline group and 49 to the control group. From March 2018 to July 2019, the guideline ICUs enrolled 1399 patients, and the control ICUs enrolled 1373 patients. Implementation of the guideline resulted in significantly earlier EN initiation (1.20 vs. 1.55 mean days to initiation of EN; difference - 0.40 [95% CI - 0.71 to - 0.09]; P = 0.01) and delayed PN initiation (1.29 vs. 0.80 mean days to start of PN; difference 1.06 [95% CI 0.44 to 1.67]; P = 0.001). There was no significant difference in 28-day mortality (14.2% vs. 15.2%; difference - 1.6% [95% CI - 4.3% to 1.2%]; P = 0.42) between groups.ConclusionsIn this large-scale, multicenter trial, active implementation of an evidence-based feeding guideline reduced the time to commencement of EN and overall PN use but did not translate to a reduction in mortality from critical illness.Trial registrationISRCTN, ISRCTN12233792 . Registered November 20th, 2017

Actively implementing an evidence-based feeding guideline for critically ill patients (NEED): a multicenter, cluster-randomized, controlled trial (vol 26, 46, 2022)

BackgroundPrevious cluster-randomized controlled trials evaluating the impact of implementing evidence-based guidelines for nutrition therapy in critical illness do not consistently demonstrate patient benefits. A large-scale, sufficiently powered study is therefore warranted to ascertain the effects of guideline implementation on patient-centered outcomes.MethodsWe conducted a multicenter, cluster-randomized, parallel-controlled trial in intensive care units (ICUs) across China. We developed an evidence-based feeding guideline. ICUs randomly allocated to the guideline group formed a local "intervention team", which actively implemented the guideline using standardized educational materials, a graphical feeding protocol, and live online education outreach meetings conducted by members of the study management committee. ICUs assigned to the control group remained unaware of the guideline content. All ICUs enrolled patients who were expected to stay in the ICU longer than seven days. The primary outcome was all-cause mortality within 28 days of enrollment.ResultsForty-eight ICUs were randomized to the guideline group and 49 to the control group. From March 2018 to July 2019, the guideline ICUs enrolled 1399 patients, and the control ICUs enrolled 1373 patients. Implementation of the guideline resulted in significantly earlier EN initiation (1.20 vs. 1.55 mean days to initiation of EN; difference - 0.40 [95% CI - 0.71 to - 0.09]; P = 0.01) and delayed PN initiation (1.29 vs. 0.80 mean days to start of PN; difference 1.06 [95% CI 0.44 to 1.67]; P = 0.001). There was no significant difference in 28-day mortality (14.2% vs. 15.2%; difference - 1.6% [95% CI - 4.3% to 1.2%]; P = 0.42) between groups.ConclusionsIn this large-scale, multicenter trial, active implementation of an evidence-based feeding guideline reduced the time to commencement of EN and overall PN use but did not translate to a reduction in mortality from critical illness.Trial registrationISRCTN, ISRCTN12233792 . Registered November 20th, 2017

Multi-Color Channels Based Group Sparse Model for Image Restoration

The group sparse representation (GSR) model combines local sparsity and nonlocal similarity in image processing, and achieves excellent results. However, the traditional GSR model and all subsequent improved GSR models convert the RGB space of the image to YCbCr space, and only extract the Y (luminance) channel of YCbCr space to change the color image to a gray image for processing. As a result, the image processing process cannot be loyal to each color channel, so the repair effect is not ideal. A new group sparse representation model based on multi-color channels is proposed in this paper. The model processes R, G and B color channels simultaneously when processing color images rather than processing a single color channel and then combining the results of different channels. The proposed multi-color-channels-based GSR model is compared with state-of-the-art methods. The experimental contrast results show that the proposed model is an effective method and can obtain good results in terms of objective quantitative metrics and subjective visual effects

Multi-Color Channels Based Group Sparse Model for Image Restoration

The group sparse representation (GSR) model combines local sparsity and nonlocal similarity in image processing, and achieves excellent results. However, the traditional GSR model and all subsequent improved GSR models convert the RGB space of the image to YCbCr space, and only extract the Y (luminance) channel of YCbCr space to change the color image to a gray image for processing. As a result, the image processing process cannot be loyal to each color channel, so the repair effect is not ideal. A new group sparse representation model based on multi-color channels is proposed in this paper. The model processes R, G and B color channels simultaneously when processing color images rather than processing a single color channel and then combining the results of different channels. The proposed multi-color-channels-based GSR model is compared with state-of-the-art methods. The experimental contrast results show that the proposed model is an effective method and can obtain good results in terms of objective quantitative metrics and subjective visual effects

A Hybrid Sparse Representation Model for Image Restoration

Group-based sparse representation (GSR) uses image nonlocal self-similarity (NSS) prior to grouping similar image patches, and then performs sparse representation. However, the traditional GSR model restores the image by training degraded images, which leads to the inevitable over-fitting of the data in the training model, resulting in poor image restoration results. In this paper, we propose a new hybrid sparse representation model (HSR) for image restoration. The proposed HSR model is improved in two aspects. On the one hand, the proposed HSR model exploits the NSS priors of both degraded images and external image datasets, making the model complementary in feature space and the plane. On the other hand, we introduce a joint sparse representation model to make better use of local sparsity and NSS characteristics of the images. This joint model integrates the patch-based sparse representation (PSR) model and GSR model, while retaining the advantages of the GSR model and the PSR model, so that the sparse representation model is unified. Extensive experimental results show that the proposed hybrid model outperforms several existing image recovery algorithms in both objective and subjective evaluations

Magnesium isotope constraints on the Holocene hydromagnesite formation in alkaline Lake Dujiali, central Qinghai‐Tibetan Plateau

Hydromagnesite (Mg5(CO3)4(OH)2 4H2O) is a common hydrated magnesium carbonate mineral found in alkaline lakes on Earth, potentially present on Mars, and is also a key mineral for carbon capture and storage. However, the mechanisms governing its formation in alkaline lakes remain enigmatic. Extensive hydromagnesite formed during the Holocene in the alkaline Dujiali Lake, central Qinghai-Tibetan Plateau, making it an ideal field site to constrain the process of hydromagnesite formation in a modern environmental context. In this study, we report a set of magnesium isotope ratios (26Mg/24Mg expressed as δ26Mg) data from Dujiali Lake on abiotic hydromagnesite (mean=−1.35 ± 0.14‰) modern lake waters (−0.07 to +0.46‰), rivers and groundwater (−0.53 to −1.46‰). These differences in δ26Mg (and also Mg/Ca) are most likely caused by low-Mg carbonate precipitation, a process which fractionates Mg/Ca and δ26Mg. A semi-quantitative box model of the lake chemistry was developed based on carbonate equilibria to investigate the behavior of Mg isotopes during the evolution of the lake chemistry. The modeling results indicate that evaporation concentrates solutes in the lake driving saturation of multiple minerals. Aragonite reaches saturation before hydromagnesite, preferentially removing Ca relative to Mg via aragonite precipitation. This process elevates the Mg/Ca of the lake and the saturation index of hydromagnesite increasing the likelihood of hydromagnesite formation. Given that the Mg/Ca ratio of many alkaline lakes is far below that required for the formation of hydromagnesite, our findings suggest that low-Mg carbonate precipitation may be a common precursor process for abiotic hydromagnesite precipitation in evaporative environments in addition to a high Mg source likely derived from ultramafic rocks