Effect of intraoperative support mode on circulating inflammatory biomarkers after lung transplantation surgery.

BACKGROUND: Processes that activate the immune system during lung transplantation can lead to primary graft dysfunction (PGD) or allograft rejection. METHODS: We analyzed cytokine expression profiles after reperfusion and allograft outcomes in a cohort of patients (n = 59) who underwent lung transplantation off-pump (n = 26), with cardiopulmonary bypass (CPB; n = 18), or with extracorporeal membrane oxygenation (ECMO; n = 15). Peripheral blood was collected from patients at baseline and at 6 and 72 h after reperfusion. To adjust for clinical differences between groups, we utilized a linear mixed model with overlap weighting. RESULTS: PGD3 was present at 48 or 72 h after reperfusion in 7.7% (2/26) of off-pump cases, 20.0% (3/15) of ECMO cases, and 38.9% (7/18) of CPB cases (p = 0.04). The ECMO and CPB groups had greater reperfusion-induced increases in MIP-1B, IL-6, IL-8, IL-9, IL1-ra, TNF-alpha, RANTES, eotaxin, IP-10, and MCP-1 levels than the off-pump group. Cytokine expression profiles after reperfusion were not significantly different between ECMO and CPB groups. CONCLUSION: Our data suggest that, compared with an off-pump approach, the intraoperative use of ECMO or CPB during lung transplantation is associated with greater reperfusion-induced cytokine release and graft injury.

A rapid feature selection method for catalyst design: Iterative Bayesian additive regression trees (iBART).

Feature selection (FS) methods often are used to develop data-driven descriptors (i.e., features) for rapidly predicting the functional properties of a physical or chemical system based on its composition and structure. FS algorithms identify descriptors from a candidate pool (i.e., feature space) built by feature engineering (FE) steps that construct complex features from the system's fundamental physical properties. Recursive FE, which involves repeated FE operations on the feature space, is necessary to build features with sufficient complexity to capture the physical behavior of a system. However, this approach creates a highly correlated feature space that contains millions or billions of candidate features. Such feature spaces are computationally demanding to process using traditional FS approaches that often struggle with strong collinearity. Herein, we address this shortcoming by developing a new method that interleaves the FE and FS steps to progressively build and select powerful descriptors with reduced computational demand. We call this method iterative Bayesian additive regression trees (iBART), as it iterates between FE with unary/binary operators and FS with Bayesian additive regression trees (BART). The capabilities of iBART are illustrated by extracting descriptors for predicting metal-support interactions in catalysis, which we compare to those predicted in our previous work using other state-of-the-art FS methods (i.e., least absolute shrinkage and selection operator + l0, sure independence screening and sparsifying operator, and Bayesian FS). iBART matches the performance of these methods yet uses a fraction of the computational resources because it generates a maximum feature space of size O(102), as opposed to O(106) generated by one-shot FE/FS methods.

Analysis of sex-based differences in clinical and molecular responses to ischemia reperfusion after lung transplantation.

BACKGROUND: Sex and hormones influence immune responses to ischemia reperfusion (IR) and could, therefore, cause sex-related differences in lung transplantation (LTx) outcomes. We compared men's and women's clinical and molecular responses to post-LTx IR. METHODS: In 203 LTx patients, we used the 2016 International Society for Heart and Lung Transplantation guidelines to score primary graft dysfunction (PGD). In a subgroup of 40 patients with blood samples collected before LTx (T0) and 6, 24, 48 (T48), and 72 h (T72) after lung reperfusion, molecular response to IR was examined through serial analysis of circulating cytokine expression. RESULTS: After adjustment, women had less grade 3 PGD than men at T48, but not at T72. PGD grade decreased from T0 to T72 more often in women than men. The evolution of PGD (the difference in mean PGD between T72 and T0) was greater in men. However, the evolution of IL-2, IL-7, IL-17a, and basic fibroblast growth factor levels was more often sustained throughout the 72 h in women. In the full cohort, we noted no sex differences in secondary clinical outcomes, but women had significantly lower peak lactate levels than men across the 72 h. CONCLUSIONS: Men and women differ in the evolution of PGD and cytokine secretion after LTx: Women have a more sustained proinflammatory response than men despite a greater reduction in PGD over time. This interaction between cytokine and PGD responses warrants investigation. Additionally, there may be important sex-related differences that could be used to tailor treatment during or after transplantation.

Genetic and epigenetic alterations of SDH genes in patients with sporadic succinate dehydrogenase-deficient gastrointestinal stromal tumors.

This study aimed to investigate the association of SDH gene mutations and promoter methylation with succinate dehydrogenase-deficient gastrointestinal stromal tumors (SDH-deficient GISTs) and to further discuss the potential molecular mechanisms underlying SDHB expression loss in these tumors. First, a total of 26 patients with SDH-deficient GISTs were selected by identifying the loss of SDHB protein expression and wild-type for KIT and PDGFRa mutations. Then SDH gene mutations and promoter methylation were detected by DNA sequencing and methylation-specific polymerase chain reaction, respectively, and the clinical and pathological data of SDH-deficient GISTs patients were collected and analyzed accordingly. The results of genetic testing demonstrated that 38.46% (10/26) of these patients harbored mutations in SDHB, SDHC, and SDHD genes (3 cases with double mutations). Besides, aberrant promoter methylation of SDH genes was detected in 10 out of 26 cases (38.46%), including 8 cases in SDHA gene, 3 cases in SDHB gene, 1 case in both SDHA and SDHB genes. It is suggested that SDH gene mutations and promoter methylation may contribute to the loss of SDH protein expression in sporadic SDH-deficient GISTs. This study indicated that the genetic and epigenetic alterations of SDH genes may occur during tumor formation.

EGFR gene mutation in gastrointestinal stromal tumours.

AIMS: The aim of this study was to evaluate the mutation status of epidermal growth factor receptor (EGFR) in gastrointestinal stromal tumours (GISTs) and its association with various clinicopathological variables, as well as to discuss further the effects of EGFR mutations on tumour formation and progression. METHODS AND RESULTS: A well-characterized cohort of 323 GISTs, obtained between 2010 and 2015 from the surgical pathology files of at the Department of Pathology of the Nanjing Jinling Hospital, was screened for mutations in exons 19 and 21 of the EGFR gene. Patient clinical data and clinicopathological features were collected if available in the medical records. Among the 323 primary GISTs, we identified three cases (0.93%) of EGFR mutations; these mutations never occurred together with KIT, PDGFRα, KRAS or BRAF mutations. In two cases, tumour cells exhibited spindle cell morphology and, in one case, epithelioid cell morphology. Additionally, the morphology and immunophenotype of these three cases did not show significant differences compared to common GISTs. The clinical results in summary were that two cases of EGFR-mutated GISTs occurred in females and in the stomach. The mean age of EGFR-mutated cases was 54.33 years, and the follow-up data indicated that these tumours were low risk and exhibited low recurrence. CONCLUSIONS: We first established that GISTs carrying EGFR mutation are relatively benign tumours. Although EGFR mutations were rarely present in GIST, EGFR seems to play a significant role in the development and progression of GIST.

Operator-induced structural variable selection for identifying materials genes.

In the emerging field of materials informatics, a fundamental task is to identify physicochemically meaningful descriptors, or materials genes, which are engineered from primary features and a set of elementary algebraic operators through compositions. Standard practice directly analyzes the high-dimensional candidate predictor space in a linear model; statistical analyses are then substantially hampered by the daunting challenge posed by the astronomically large number of correlated predictors with limited sample size. We formulate this problem as variable selection with operator-induced structure (OIS) and propose a new method to achieve unconventional dimension reduction by utilizing the geometry embedded in OIS. Although the model remains linear, we iterate nonparametric variable selection for effective dimension reduction. This enables variable selection based on ab initio primary features, leading to a method that is orders of magnitude faster than existing methods, with improved accuracy. To select the nonparametric module, we discuss a desired performance criterion that is uniquely induced by variable selection with OIS; in particular, we propose to employ a Bayesian Additive Regression Trees (BART)-based variable selection method. Numerical studies show superiority of the proposed method, which continues to exhibit robust performance when the input dimension is out of reach of existing methods. Our analysis of single-atom catalysis identifies physical descriptors that explain the binding energy of metal-support pairs with high explanatory power, leading to interpretable insights to guide the prevention of a notorious problem called sintering and aid catalysis design.

Mangrove reforestation provides greater blue carbon benefit than afforestation for mitigating global climate change.

Significant efforts have been invested to restore mangrove forests worldwide through reforestation and afforestation. However, blue carbon benefit has not been compared between these two silvicultural pathways at the global scale. Here, we integrated results from direct field measurements of over 370 restoration sites around the world to show that mangrove reforestation (reestablishing mangroves where they previously colonized) had a greater carbon storage potential per hectare than afforestation (establishing mangroves where not previously mangrove). Greater carbon accumulation was mainly attributed to favorable intertidal positioning, higher nitrogen availability, and lower salinity at most reforestation sites. Reforestation of all physically feasible areas in the deforested mangrove regions of the world could promote the uptake of 671.5-688.8 Tg CO2-eq globally over a 40-year period, 60% more than afforesting the same global area on tidal flats (more marginal sites). Along with avoiding conflicts of habitat conversion, mangrove reforestation should be given priority when designing nature-based solutions for mitigating global climate change.

Plasma protein biomarkers for primary graft dysfunction after lung transplantation: a single-center cohort analysis.

The clinical use of circulating biomarkers for primary graft dysfunction (PGD) after lung transplantation has been limited. In a prospective single-center cohort, we examined the use of plasma protein biomarkers as indicators of PGD severity and duration after lung transplantation. The study comprised 40 consecutive lung transplant patients who consented to blood sample collection immediately pretransplant and at 6, 24, 48, and 72 h after lung transplant. An expert grader determined the severity and duration of PGD and scored PGD at T0 (6 h after reperfusion), T24, T48, and T72 h post-reperfusion using the 2016 ISHLT consensus guidelines. A bead-based multiplex assay was used to measure 27 plasma proteins including cytokines, growth factors, and chemokines. Enzyme-linked immunoassay was used to measure cell injury markers including M30, M65, soluble receptor of advanced glycation end-products (sRAGE), and plasminogen activator inhibitor-1 (PAI-1). A pairwise comparisons analysis was used to assess differences in protein levels between PGD severity scores (1, 2, and 3) at T0, T24, T48, and T72 h. Sensitivity and temporal analyses were used to explore the association of protein expression patterns and PGD3 at T48-72 h (the most severe, persistent form of PGD). We used the Benjamini-Hochberg method to adjust for multiple testing. Of the 40 patients, 22 (55%) had PGD3 at some point post-transplant from T0 to T72 h; 12 (30%) had PGD3 at T48-72 h. In the pairwise comparison, we identified a robust plasma protein expression signature for PGD severity. In the sensitivity analysis, using a linear model for microarray data, we found that differential perioperative expression of IP-10, MIP1B, RANTES, IL-8, IL-1Ra, G-CSF, and PDGF-BB correlated with PGD3 development at T48-72 h (FDR < 0.1 and p < 0.05). In the temporal analysis, using linear mixed modeling with overlap weighting, we identified unique protein patterns in patients who did or did not develop PGD3 at T48-72 h. Our findings suggest that unique inflammatory protein expression patterns may be informative of PGD severity and duration. PGD biomarker panels may improve early detection of PGD, predict its clinical course, and help monitor treatment efficacy in the current era of lung transplantation.

P16 overexpression in BRAF-mutated gastrointestinal stromal tumors.

BACKGROUND: The aims of this study were to analyze the histopathology, immunophenotype, molecular features, and prognosis in cases of BRAF-mutated gastrointestinal stromal tumors (GISTs) and to examine the p16 expression in these tumors, and further discuss its effects on tumor formation and progression. METHODS: In all, 283 GIST cases (201 KIT mutants, 12 PDGFRA mutants and 70 wild-type) from the 2010 to 2014 surgical pathology files of the Department of Pathology at Nanjing Jinling Hospital were analyzed for mutations in BRAF exon 15. Patient follow-up and clinical data were collected if available in the medical records. To determine the clinicopathological features and potential molecular mechanism, the authors examined 10 BRAF-mutated GIST cases for KIT, DOG1, SMA, desmin, S-100, Ki-67 and p16 expression. RESULTS: The authors identified 10 cases (3.5%) of BRAF (V600E) mutations in a series of 283 primary GISTs, without KIT (exons 9, 11, 13, 17) or PDGFRA (exons 12, 18) gene mutations. All 10 cases exhibited spindle-cell features, and the morphology and immunophenotype of these cases were no different from those in cases of KIT-mutated GISTs. The clinical results indicated that BRAF-mutated GISTs tended to occur more frequently in females (7/10), older individuals (mean age, 54.9 years) and the stomach (7/10), and that these tumors were low risk and exhibited low recurrence and mortality rates. Two different forms of p16 were identified, which presented with simultaneously strong and diffuse nuclear and cytoplasmic expression patterns. CONCLUSION: GISTs with the BRAF V600E mutation are relatively benign tumors with a distinctive molecular mechanism. The expression of the nuclear and cytoplasmic forms of p16 represent two independent mechanisms, and both seemed to control proliferation in response to oncogenic stimuli, protecting the cell from malignant transformation in BRAF-mutated GISTs.