MiR-106a targets ATG7 to inhibit autophagy and angiogenesis after myocardial infarction.

BACKGROUND: Myocardial infarction (MI) is an acute condition in which the heart muscle dies due to the lack of blood supply. Previous research has suggested that autophagy and angiogenesis play vital roles in the prevention of heart failure after MI, and miR-106a is considered to be an important regulatory factor in MI. But the specific mechanism remains unknown. In this study, using cultured venous endothelial cells and a rat model of MI, we aimed to identify the potential target genes of miR-106a and discover the mechanisms of inhibiting autophagy and angiogenesis. METHODS: We first explored the biological functions of miR-106a on autophagy and angiogenesis on endothelial cells. Then we identified ATG7, which was the downstream target gene of miR-106a. The expression of miR-106a and ATG7 was investigated in the rat model of MI. RESULTS: We found that miR-106a inhibits the proliferation, cell cycle, autophagy and angiogenesis, but promoted the apoptosis of vein endothelial cells. Moreover, ATG7 was identified as the target of miR-106a, and ATG7 rescued the inhibition of autophagy and angiogenesis by miR-106a. The expression of miR-106a in the rat model of MI was decreased but the expression of ATG7 was increased in the infarction areas. CONCLUSION: Our results indicate that miR-106a may inhibit autophagy and angiogenesis by targeting ATG7. This mechanism may be a potential therapeutic treatment for MI.

Knockdown of DNMT1 Induces SLCO3A1 to Promote Follicular Growth by Enhancing the Proliferation of Granulosa Cells in Mammals.

In female mammals, the proliferation and apoptosis of granulosa cells (GCs) have been shown to determine the fate of follicles. DNA methyltransferases (DNMTs) and SLCO3A1 have been reported to be involved in the survival of GCs and follicular growth. However, the molecular mechanisms enabling DNMTs to regulate the expression of SLCO3A1 to participate in follicular growth are unclear. In this study, we found that the knockdown of DNMT1 enhanced the mRNA and protein levels of SLCO3A1 by regulating the chromatin accessibility probably. Moreover, SLCO3A1 upregulated the mRNA and protein levels of MCL1, PCNA, and STAR to promote the proliferation of GCs and facilitated cell cycle progression by increasing the mRNA and protein levels of CCNE1, CDK2, and CCND1, but it decreased apoptosis by downregulating the mRNA and protein levels of CASP3 and CASP8. Moreover, SLCO3A1 promoted the growth of porcine follicles and development of mice follicles. In conclusion, the knockdown of DNMT1 upregulated the mRNA and protein levels of SLCO3A1, thereby promoting the proliferation of GCs to facilitate the growth and development of ovarian follicles, and these results provide new insights into investigations of female reproductive diseases.

Global metabolomics revealed deviations from the metabolic aging clock in colorectal cancer patients.

Background: Markers of aging hold promise in the context of colorectal cancer (CRC) care. Utilizing high-resolution metabolomic profiling, we can unveil distinctive age-related patterns that have the potential to predict early CRC development. Our study aims to unearth a panel of aging markers and delve into the metabolomic alterations associated with aging and CRC. Methods: We assembled a serum cohort comprising 5,649 individuals, consisting of 3,002 healthy volunteers, 715 patients diagnosed with colorectal advanced precancerous lesions (APL), and 1,932 CRC patients, to perform a comprehensive metabolomic analysis. Results: We successfully identified unique age-associated patterns across 42 metabolic pathways. Moreover, we established a metabolic aging clock, comprising 9 key metabolites, using an elastic net regularized regression model that accurately estimates chronological age. Notably, we observed significant chronological disparities among the healthy population, APL patients, and CRC patients. By combining the analysis of circulative carcinoembryonic antigen levels with the categorization of individuals into the "hypo" metabolic aging subgroup, our blood test demonstrates the ability to detect APL and CRC with positive predictive values of 68.4% (64.3%, 72.2%) and 21.4% (17.8%, 25.9%), respectively. Conclusions: This innovative approach utilizing our metabolic aging clock holds significant promise for accurately assessing biological age and enhancing our capacity to detect APL and CRC.

Pig-eRNAdb: a comprehensive enhancer and eRNA dataset of pigs.

Enhancers and the enhancer RNAs (eRNAs) have been strongly implicated in regulations of transcriptions. Based the multi-omics data (ATAC-seq, ChIP-seq and RNA-seq) from public databases, Pig-eRNAdb is a dataset that comprehensively integrates enhancers and eRNAs for pigs using the machine learning strategy, which incorporates 82,399 enhancers and 37,803 eRNAs from 607 samples across 15 tissues of pigs. This user-friendly dataset covers a comprehensive depth of enhancers and eRNAs annotation for pigs. The coordinates of enhancers and the expression patterns of eRNAs are downloadable. Besides, thousands of regulators on eRNAs, the target genes of eRNAs, the tissue-specific eRNAs, and the housekeeping eRNAs are also accessible as well as the sequence similarity of eRNAs with humans. Moreover, the tissue-specific eRNA-trait associations encompass 652 traits are also provided. It will crucially facilitate investigations on enhancers and eRNAs with Pig-eRNAdb as a reference dataset in pigs.

Altered expression of the L-arginine/nitric oxide pathway in ovarian cancer: metabolic biomarkers and biological implications.

MOTIVATION: Ovarian cancer (OC) is a highly lethal gynecological malignancy. Extensive research has shown that OC cells undergo significant metabolic alterations during tumorigenesis. In this study, we aim to leverage these metabolic changes as potential biomarkers for assessing ovarian cancer. METHODS: A functional module-based approach was utilized to identify key gene expression pathways that distinguish different stages of ovarian cancer (OC) within a tissue biopsy cohort. This cohort consisted of control samples (n = 79), stage I/II samples (n = 280), and stage III/IV samples (n = 1016). To further explore these altered molecular pathways, minimal spanning tree (MST) analysis was applied, leading to the formulation of metabolic biomarker hypotheses for OC liquid biopsy. To validate, a multiple reaction monitoring (MRM) based quantitative LCMS/MS method was developed. This method allowed for the precise quantification of targeted metabolite biomarkers using an OC blood cohort comprising control samples (n = 464), benign samples (n = 3), and OC samples (n = 13). RESULTS: Eleven functional modules were identified as significant differentiators (false discovery rate, FDR < 0.05) between normal and early-stage, or early-stage and late-stage ovarian cancer (OC) tumor tissues. MST analysis revealed that the metabolic L-arginine/nitric oxide (L-ARG/NO) pathway was reprogrammed, and the modules related to "DNA replication" and "DNA repair and recombination" served as anchor modules connecting the other nine modules. Based on this analysis, symmetric dimethylarginine (SDMA) and arginine were proposed as potential liquid biopsy biomarkers for OC assessment. Our quantitative LCMS/MS analysis on our OC blood cohort provided direct evidence supporting the use of the SDMA-to-arginine ratio as a liquid biopsy panel to distinguish between normal and OC samples, with an area under the ROC curve (AUC) of 98.3%. CONCLUSION: Our comprehensive analysis of tissue genomics and blood quantitative LC/MSMS metabolic data shed light on the metabolic reprogramming underlying OC pathophysiology. These findings offer new insights into the potential diagnostic utility of the SDMA-to-arginine ratio for OC assessment. Further validation studies using adequately powered OC cohorts are warranted to fully establish the clinical effectiveness of this diagnostic test.

A comparative study of gastric adenocarcinoma HER2 IHC phenotype and mass spectrometry-based quantification.

Introduction: Gastric cancer is a highly heterogeneous malignant tumor of the digestive system. Anti-HER2 treatment can inhibit downstream signaling pathways and improve clinical treatment and outcomes in patients with HER2 protein overexpression. Currently, two standard methods for evaluating HER2 expression status are immunohistochemistry (IHC) and fluorescence in situ hybridization (FISH). However, these low-throughput assays often produce discordant or equivocal results. Methods: In this study, we presented a new HER2 protein detection method based on mass spectrometry selected reaction monitoring (MS-SRM) and validated the method. We conducted a retrospective study on 118 formalin-fixed paraffin-embedded (FFPE) tissues from patients with advanced gastric adenocarcinoma in northern China, and we compared the MS-SRM results with those from IHC and correlated them with FISH. Results: We established and validated the upper and lower detection limits (300-700 amol/µg) for abnormal HER2 protein expression in advanced gastric cancer. We also found that, among samples with mixed Lauren subtypes, those with a high level of HER2 expression had typical intestinal type features in pathology. Discussion: This study demonstrated that the MS-SRM method can overcome the limitations and deficiencies of IHC, directly quantify the expression of HER2 protein in tumor cells and be used as a supplement to IHC. It has the potential to be used as a companion diagnosis for new drugs used to treat advanced gastric cancer. Large-scale clinical validation is required.

Identification of New Candidate Genes Related to Semen Traits in Duroc Pigs through Weighted Single-Step GWAS.

Semen traits play a key role in the pig industry because boar semen is widely used in purebred and crossbred pigs. The production of high-quality semen is crucial to ensuring a good result in artificial insemination. With the wide application of artificial insemination in the pig industry, more and more attention has been paid to the improvement of semen traits by genetic selection. The purpose of this study was to identify the genetic regions and candidate genes associated with semen traits of Duroc boars. We used weighted single-step GWAS to identify candidate genes associated with sperm motility, sperm progressive motility, sperm abnormality rate and total sperm count in Duroc pigs. In Duroc pigs, the three most important windows for sperm motility-sperm progressive motility, sperm abnormality rate, and total sperm count-explained 12.45%, 9.77%, 15.80%, and 12.15% of the genetic variance, respectively. Some genes that are reported to be associated with spermatogenesis, testicular function and male fertility in mammals have been detected previously. The candidate genes CATSPER1, STRA8, ZSWIM7, TEKT3, UBB, PTBP2, EIF2B2, MLH3, and CCDC70 were associated with semen traits in Duroc pigs. We found a common candidate gene, STRA8, in sperm motility and sperm progressive motility, and common candidate genes ZSWIM7, TEKT3 and UBB in sperm motility and sperm abnormality rate, which confirms the hypothesis of gene pleiotropy. Gene network enrichment analysis showed that STRA8, UBB and CATSPER1 were enriched in the common biological process and participated in male meiosis and spermatogenesis. The SNPs of candidate genes can be given more weight in genome selection to improve the ability of genome prediction. This study provides further insight into the understanding the genetic structure of semen traits in Duroc boars.

A Poly(dA:dT) Tract in the IGF1 Gene Is a Genetic Marker for Growth Traits in Pigs.

Insulin-like growth factor 1 (IGF1) is an important regulator of body growth, development, and metabolism. The poly(dA:dT) tract affects the accessibility of transcription factor binding sites to regulate transcription. Therefore, this study assessed the effects of two poly(dA:dT) tracts on the transcriptional activity of porcine IGF1. The luciferase assay results demonstrated that the poly(dA:dT) tract 2 (−264/−255) was a positive regulatory element for IGF1 gene expression, and the activities between the different lengths of the poly(dA:dT) tract 2 were significant (p<0.01). The transcription factor C/EBPα inhibited the transcription of IGF1 by binding to tract 2, and the expression levels between the lengths of tract 2 after C/EBPα binding were also statistically different (p<0.01). Only the alleles 10T and 11T were found in the tract 2 in commercial pig breeds, while the 9T, 10T, and 11T alleles were found in Chinese native pig breeds. The allele frequencies were in Hardy−Weinberg equilibrium in all pig breeds. The genotypes of tract 2 were significantly associated with the growth traits (days to 115 kg and average daily gain) (p<0.05) in commercial pig breeds. Based on these findings, it can be concluded that the tract 2 mutation could be applied as a candidate genetic marker for growth trait selection in pig breeding programs.

Serological Phenotyping Analysis Uncovers a Unique Metabolomic Pattern Associated With Early Onset of Type 2 Diabetes Mellitus.

Background: Type 2 diabetes mellitus (T2DM) is a multifaceted disorder affecting epidemic proportion at global scope. Defective insulin secretion by pancreatic ß-cells and the inability of insulin-sensitive tissues to respond effectively to insulin are the underlying biology of T2DM. However, circulating biomarkers indicative of early diabetic onset at the asymptomatic stage have not been well described. We hypothesized that global and targeted mass spectrometry (MS) based metabolomic discovery can identify novel serological metabolic biomarkers specifically associated with T2DM. We further hypothesized that these markers can have a unique pattern associated with latent or early asymptomatic stage, promising an effective liquid biopsy approach for population T2DM risk stratification and screening. Methods: Four independent cohorts were assembled for the study. The T2DM cohort included sera from 25 patients with T2DM and 25 healthy individuals for the biomarker discovery and sera from 15 patients with T2DM and 15 healthy controls for the testing. The Pre-T2DM cohort included sera from 76 with prediabetes and 62 healthy controls for the model training and sera from 35 patients with prediabetes and 27 healthy controls for the model testing. Both global and targeted (amino acid, acylcarnitine, and fatty acid) approaches were used to deep phenotype the serological metabolome by high performance liquid chromatography-high resolution mass spectrometry. Different machine learning approaches (Random Forest, XGBoost, and ElasticNet) were applied to model the unique T2DM/Pre-T2DM metabolic patterns and contrasted with their effectiness to differentiate T2DM/Pre-T2DM from controls. Results: The univariate analysis identified unique panel of metabolites (n = 22) significantly associated with T2DM. Global metabolomics and subsequent structure determination led to the identification of 8 T2DM biomarkers while targeted LCMS profiling discovered 14 T2DM biomarkers. Our panel can effectively differentiate T2DM (ROC AUC = 1.00) or Pre-T2DM (ROC AUC = 0.84) from the controls in the respective testing cohort. Conclusion: Our serological metabolite panel can be utilized to identifiy asymptomatic population at risk of T2DM, which may provide utility in identifying population at risk at an early stage of diabetic development to allow for clinical intervention. This early detection would guide ehanced levels of care and accelerate development of clinical strategies to prevent T2DM.

Early-pregnancy prediction of risk for pre-eclampsia using maternal blood leptin/ceramide ratio: discovery and confirmation.

OBJECTIVE: This study aimed to develop a blood test for the prediction of pre-eclampsia (PE) early in gestation. We hypothesised that the longitudinal measurements of circulating adipokines and sphingolipids in maternal serum over the course of pregnancy could identify novel prognostic biomarkers that are predictive of impending event of PE early in gestation. STUDY DESIGN: Retrospective discovery and longitudinal confirmation. SETTING: Maternity units from two US hospitals. PARTICIPANTS: Six previously published studies of placental tissue (78 PE and 95 non-PE) were compiled for genomic discovery, maternal sera from 15 women (7 non-PE and 8 PE) enrolled at ProMedDx were used for sphingolipidomic discovery, and maternal sera from 40 women (20 non-PE and 20 PE) enrolled at Stanford University were used for longitudinal observation. OUTCOME MEASURES: Biomarker candidates from discovery were longitudinally confirmed and compared in parallel to the ratio of placental growth factor (PlGF) and soluble fms-like tyrosine kinase (sFlt-1) using the same cohort. The datasets were generated by enzyme-linked immunosorbent and liquid chromatography-tandem mass spectrometric assays. RESULTS: Our discovery integrating genomic and sphingolipidomic analysis identified leptin (Lep) and ceramide (Cer) (d18:1/25:0) as novel biomarkers for early gestational assessment of PE. Our longitudinal observation revealed a marked elevation of Lep/Cer (d18:1/25:0) ratio in maternal serum at a median of 23 weeks' gestation among women with impending PE as compared with women with uncomplicated pregnancy. The Lep/Cer (d18:1/25:0) ratio significantly outperformed the established sFlt-1/PlGF ratio in predicting impending event of PE with superior sensitivity (85% vs 20%) and area under curve (0.92 vs 0.52) from 5 to 25 weeks of gestation. CONCLUSIONS: Our study demonstrated the longitudinal measurement of maternal Lep/Cer (d18:1/25:0) ratio allows the non-invasive assessment of PE to identify pregnancy at high risk in early gestation, outperforming the established sFlt-1/PlGF ratio test.

Quantitative Multiplexed Proteomics Could Assist Therapeutic Decision Making in Non-Small Cell Lung Cancer Patients with Ambiguous ALK Test Results.

Therapeutic guidance in non-small cell lung cancer (NSCLC) tumors that are positive for anaplastic lymphoma kinase (ALK) fluorescent in situ hybridization (FISH), but negative for ALK immunohistochemistry, is still challenging. Parallel routine screening of 4588 NSCLC cases identified 22 discordant cases. We rechecked these samples using ALK antibodies and selected reaction monitoring (SRM) quantitative multiplexed proteomics screening multiple protein targets, including ALK and MET for the ALK tyrosine kinase inhibitor (TKI), and FR-alpha, hENT1, RRM1, TUBB3, ERCC1, and XRCC1 for chemotherapy. The presence of ALK (31.8%), MET (36.4%), FR-alpha (72.7%), hENT1 (18.2%), RRM1 (31.8%), TUBB3 (72.9%), ERCC1 (4.5%), and a low level of XRCC1 (54.4%) correlated with clinical outcomes. SRM was more sensitive than the ALK D5F3 assay. Among the eight cases receiving ALK TKI, four cases with ALK or MET detected by SRM had complete or partial responses, whereas four cases without ALK or MET showed progression. Twenty-seven treatment outcomes from 20 cases were assessed and cases expressing more than half of the specific predictive proteins were sensitive to matching therapeutic agents and showed longer progression-free survival than the other cases (p < 0.001). SRM showed a potential role in therapeutic decision making in NSCLC patients with ambiguous ALK test results.

EGFR Blockade Reverts Resistance to KRASG12C Inhibition in Colorectal Cancer.

Most patients with KRAS G12C-mutant non-small cell lung cancer (NSCLC) experience clinical benefit from selective KRASG12C inhibition, whereas patients with colorectal cancer bearing the same mutation rarely respond. To investigate the cause of the limited efficacy of KRASG12C inhibitors in colorectal cancer, we examined the effects of AMG510 in KRAS G12C colorectal cancer cell lines. Unlike NSCLC cell lines, KRAS G12C colorectal cancer models have high basal receptor tyrosine kinase (RTK) activation and are responsive to growth factor stimulation. In colorectal cancer lines, KRASG12C inhibition induces higher phospho-ERK rebound than in NSCLC cells. Although upstream activation of several RTKs interferes with KRASG12C blockade, we identify EGFR signaling as the dominant mechanism of colorectal cancer resistance to KRASG12C inhibitors. The combinatorial targeting of EGFR and KRASG12C is highly effective in colorectal cancer cells and patient-derived organoids and xenografts, suggesting a novel therapeutic strategy to treat patients with KRAS G12C colorectal cancer. SIGNIFICANCE: The efficacy of KRASG12C inhibitors in NSCLC and colorectal cancer is lineage-specific. RTK dependency and signaling rebound kinetics are responsible for sensitivity or resistance to KRASG12C inhibition in colorectal cancer. EGFR and KRASG12C should be concomitantly inhibited to overcome resistance to KRASG12C blockade in colorectal tumors.See related commentary by Koleilat and Kwong, p. 1094.This article is highlighted in the In This Issue feature, p. 1079.

HER2-Mediated Internalization of Cytotoxic Agents in ERBB2 Amplified or Mutant Lung Cancers.

Amplification of and oncogenic mutations in ERBB2, the gene encoding the HER2 receptor tyrosine kinase, promote receptor hyperactivation and tumor growth. Here we demonstrate that HER2 ubiquitination and internalization, rather than its overexpression, are key mechanisms underlying endocytosis and consequent efficacy of the anti-HER2 antibody-drug conjugates (ADC) ado-trastuzumab emtansine (T-DM1) and trastuzumab deruxtecan (T-DXd) in lung cancer cell lines and patient-derived xenograft models. These data translated into a 51% response rate in a clinical trial of T-DM1 in 49 patients with ERBB2-amplified or -mutant lung cancers. We show that cotreatment with irreversible pan-HER inhibitors enhances receptor ubiquitination and consequent ADC internalization and efficacy. We also demonstrate that ADC switching to T-DXd, which harbors a different cytotoxic payload, achieves durable responses in a patient with lung cancer and corresponding xenograft model developing resistance to T-DM1. Our findings may help guide future clinical trials and expand the field of ADC as cancer therapy. SIGNIFICANCE: T-DM1 is clinically effective in lung cancers with amplification of or mutations in ERBB2. This activity is enhanced by cotreatment with irreversible pan-HER inhibitors, or ADC switching to T-DXd. These results may help address unmet needs of patients with HER2-activated tumors and no approved targeted therapy.See related commentary by Rolfo and Russo, p. 643.This article is highlighted in the In This Issue feature, p. 627.

Risk factors for postdischarge growth retardation among very-low-birth-weight infants: A nationwide registry study in Taiwan.

BACKGROUND: Very-low-birth-weight (VLBW) infants have a high risk of postdischarge growth retardation (GR). Continued GR might exert negative long-term effects on their health. This study examined the prevalence and the risk factors for postdischarge GR among VLBW infants in Taiwan. METHODS: Nationwide data from the Taiwan Premature Infant Follow-up Network between 2007 and 2011 were analyzed. Infants with a gestational age (GA) < 37 weeks and birth body weight (BBW) < 1500 g were enrolled. They were followed up after discharge at the corrected ages of 6, 12, and 24 months. Associations between postdischarge GR at the follow-ups and possible risk factors were analyzed. RESULTS: The prevalence of postdischarge GR among 2124 VLBW infants was 17.3%, 19.4%, and 13.8% at the corrected age (CA) of 6, 12, and 24 months, respectively. The significant perinatal factors of postdischarge GR were being small for gestational age (SGA) and extremely low birth weight (ELBW). ELBW infant with extra-uterine growth retardation (EUGR) at discharge or longer length of hospital stay (LOS) had poorer growth outcomes. Among non-ELBW infants, EUGR at discharge and surgical necrotizing enterocolitis (NEC) were the main influencing factors of unfavorable growth outcomes. RDS with surfactant therapy had a positive effect of postdischarge growth outcomes in ELBW infants. CONCLUSION: Postdischarge GR is still a serious problem in Taiwan. Being SGA and ELBW and EUGR were significant risk factors for postdischarge GR throughout the first two years of life in VLBW infants. An integrated and organized team for postdischarge care as well as scheduled follow-ups, detailed nutritional education, and thorough inspection are necessary.

Translation and evaluation of a pre-clinical 5-protein response prediction signature in a breast cancer phase Ib clinical trial.

Human protein biomarker discovery relies heavily on pre-clinical models, in particular established cell lines and patient-derived xenografts, but confirmation studies in primary tissue are essential to demonstrate clinical relevance. We describe in this study the process that was followed to clinically translate a 5-protein response signature predictive for the activity of an anti-HER3 monoclonal antibody (lumretuzumab) originally measured in fresh frozen xenograft tissue. We detail the development, qualification, and validation of the multiplexed targeted mass spectrometry assay used to assess the signature performance in formalin-fixed, paraffin-embedded human clinical samples collected in a phase Ib trial designed to evaluate lumretuzumab in patients with metastatic breast cancer. We believe that the strategy delineated here provides a path forward to avoid the time- and cost-consuming step of having to develop immunological reagents against unproven targets. We expect that mass spectrometry-based platforms may become part of a rational process to rapidly test and qualify large number of candidate biomarkers to identify the few that stand a chance for further development and validation.

Data-Independent Acquisition Mass Spectrometry To Quantify Protein Levels in FFPE Tumor Biopsies for Molecular Diagnostics.

Mass spectrometry-based protein quantitation is currently used to measure therapeutically relevant protein biomarkers in CAP/CLIA setting to predict likely responses of known therapies. Selected reaction monitoring (SRM) is the method of choice due to its outstanding analytical performance. However, data-independent acquisition (DIA) is now emerging as a proteome-scale clinical assay. We evaluated the ability of DIA to profile the patient-specific proteomes of sample-limited tumor biopsies and to quantify proteins of interest in a targeted fashion using formalin-fixed, paraffin-embedded (FFPE) tumor biopsies ( n = 12) selected from our clinical laboratory. DIA analysis on the tumor biopsies provided 3713 quantifiable proteins including actionable biomarkers currently in clinical use, successfully separated two gastric cancers from colorectal cancer specimen solely on the basis of global proteomic profiles, and identified subtype-specific proteins with prognostic or diagnostic value. We demonstrate the potential use of DIA-based quantitation to inform therapeutic decision-making using TUBB3, for which clinical cutoff expression levels have been established by SRM. Comparative analysis of DIA-based proteomic profiles and mRNA expression levels found positively and negatively correlated protein-gene pairs, a finding consistent with previously reported results from fresh-frozen tumor tissues.

Author Correction: Targeting wild-type KRAS-amplified gastroesophageal cancer through combined MEK and SHP2 inhibition.

In the Supplementary Information originally published with this article, a lane was missing in the ß-actin blot in Supplementary Fig. 2. The lane has been added. The error has been corrected in the Supplementary Information associated with this article.