Macrophage polarization: an important role in inflammatory diseases.

Macrophages are crucial cells in the human body's innate immunity and are engaged in a variety of non-inflammatory reactions. Macrophages can develop into two kinds when stimulated by distinct internal environments: pro-inflammatory M1-like macrophages and anti-inflammatory M2-type macrophages. During inflammation, the two kinds of macrophages are activated alternatively, and maintaining a reasonably steady ratio is critical for maintaining homeostasis in vivo. M1 macrophages can induce inflammation, but M2 macrophages suppress it. The imbalance between the two kinds of macrophages will have a significant impact on the illness process. As a result, there are an increasing number of research being conducted on relieving or curing illnesses by altering the amount of macrophages. This review summarizes the role of macrophage polarization in various inflammatory diseases, including autoimmune diseases (RA, EAE, MS, AIH, IBD, CD), allergic diseases (allergic rhinitis, allergic dermatitis, allergic asthma), atherosclerosis, obesity and type 2 diabetes, metabolic homeostasis, and the compounds or drugs that have been discovered or applied to the treatment of these diseases by targeting macrophage polarization.

Purine salvage-associated metabolites as biomarkers for early diagnosis of esophageal squamous cell carcinoma: a diagnostic model-based study.

Esophageal squamous cell carcinoma (ESCC) remains an important health concern in developing countries. Patients with advanced ESCC have a poor prognosis and survival rate, and achieving early diagnosis remains a challenge. Metabolic biomarkers are gradually gaining attention as early diagnostic biomarkers. Hence, this multicenter study comprehensively evaluated metabolism dysregulation in ESCC through an integrated research strategy to identify key metabolite biomarkers of ESCC. First, the metabolic profiles were examined in tissue and serum samples from the discovery cohort (n = 162; ESCC patients, n = 81; healthy volunteers, n = 81), and ESCC tissue-induced metabolite alterations were observed in the serum. Afterward, RNA sequencing of tissue samples (n = 46) was performed, followed by an integrated analysis of metabolomics and transcriptomics. The potential biomarkers for ESCC were further identified by censoring gene-metabolite regulatory networks. The diagnostic value of the identified biomarkers was validated in a validation cohort (n = 220), and the biological function was verified. A total of 457 dysregulated metabolites were identified in the serum, of which 36 were induced by tumor tissues. The integrated analyses revealed significant alterations in the purine salvage pathway, wherein the abundance of hypoxanthine/xanthine exhibited a positive correlation with HPRT1 expression and tumor size. A diagnostic model was developed using two purine salvage-associated metabolites. This model could accurately discriminate patients with ESCC from normal individuals, with an area under the curve (AUC) (95% confidence interval (CI): 0.680-0.843) of 0.765 in the external cohort. Hypoxanthine and HPRT1 exerted a synergistic effect in terms of promoting ESCC progression. These findings are anticipated to provide valuable support in developing novel diagnostic approaches for early ESCC and enhance our comprehension of the metabolic mechanisms underlying this disease.

HHCDB: a database of human heterochromatin regions.

Heterochromatin plays essential roles in eukaryotic genomes, such as regulating genes, maintaining genome integrity and silencing repetitive DNA elements. Identifying genome-wide heterochromatin regions is crucial for studying transcriptional regulation. We propose the Human Heterochromatin Chromatin Database (HHCDB) for archiving heterochromatin regions defined by specific or combined histone modifications (H3K27me3, H3K9me2, H3K9me3) according to a unified pipeline. 42 839 743 heterochromatin regions were identified from 578 samples derived from 241 cell-types/cell lines and 92 tissue types. Genomic information is provided in HHCDB, including chromatin location, gene structure, transcripts, distance from transcription start site, neighboring genes, CpG islands, transposable elements, 3D genomic structure and functional annotations. Furthermore, transcriptome data from 73 single cells were analyzed and integrated to explore cell type-specific heterochromatin-related genes. HHCDB affords rich visualization through the UCSC Genome Browser and our self-developed tools. We have also developed a specialized online analysis platform to mine differential heterochromatin regions in cancers. We performed several analyses to explore the function of cancer-specific heterochromatin-related genes, including clinical feature analysis, immune cell infiltration analysis and the construction of drug-target networks. HHCDB is a valuable resource for studying epigenetic regulation, 3D genomics and heterochromatin regulation in development and disease. HHCDB is freely accessible at http://hhcdb.edbc.org/.

Construction of a risk stratification model integrating ctDNA to predict response and survival in neoadjuvant-treated breast cancer.

BACKGROUND: The pathological complete response (pCR) to neoadjuvant chemotherapy (NAC) of breast cancer is closely related to a better prognosis. However, there are no reliable indicators to accurately identify which patients will achieve pCR before surgery, and a model for predicting pCR to NAC is required. METHODS: A total of 269 breast cancer patients in Shandong Cancer Hospital and Liaocheng People's Hospital receiving anthracycline and taxane-based NAC were prospectively enrolled. Expression profiling using a 457 cancer-related gene sequencing panel (DNA sequencing) covering genes recurrently mutated in breast cancer was carried out on 243 formalin-fixed paraffin-embedded tumor biopsies samples before NAC from 243 patients. The unique personalized panel of nine individual somatic mutation genes from the constructed model was used to detect and analyze ctDNA on 216 blood samples. Blood samples were collected at indicated time points including before chemotherapy initiation, after the 1st NAC and before the 2nd NAC cycle, during intermediate evaluation, and prior to surgery. In this study, we characterized the value of gene profile mutation and circulating tumor DNA (ctDNA) in combination with clinical characteristics in the prediction of pCR before surgery and investigated the prognostic prediction. The median follow-up time for survival analysis was 898 days. RESULTS: Firstly, we constructed a predictive NAC response model including five single nucleotide variant (SNV) mutations (TP53, SETBP1, PIK3CA, NOTCH4 and MSH2) and four copy number variation (CNV) mutations (FOXP1-gain, EGFR-gain, IL7R-gain, and NFKB1A-gain) in the breast tumor, combined with three clinical factors (luminal A, Her2 and Ki67 status). The tumor prediction model showed good discrimination of chemotherapy sensitivity for pCR and non-pCR with an AUC of 0.871 (95% CI, 0.797-0.927) in the training set, 0.771 (95% CI, 0.649-0.883) in the test set, and 0.726 (95% CI, 0.556-0.865) in an extra test set. This tumor prediction model can also effectively predict the prognosis of disease-free survival (DFS) with an AUC of 0.749 at 1 year and 0.830 at 3 years. We further screened the genes from the tumor prediction model to establish a unique personalized panel consisting of 9 individual somatic mutation genes to detect and analyze ctDNA. It was found that ctDNA positivity decreased with the passage of time during NAC, and ctDNA status can predict NAC response and metastasis recurrence. Finally, we constructed the chemotherapy prediction model combined with the tumor prediction model and pretreatment ctDNA levels, which has a better prediction effect of pCR with the AUC value of 0.961. CONCLUSIONS: In this study, we established a chemotherapy predictive model with a non-invasive tool that is built based on genomic features, ctDNA status, as well as clinical characteristics for predicting pCR to recognize the responders and non-responders to NAC, and also predicting prognosis for DFS in breast cancer. Adding pretreatment ctDNA levels to a model containing gene profile mutation and clinical characteristics significantly improves stratification over the clinical variables alone.

Dynamic analysis of circulating tumor DNA to predict the prognosis and monitor the treatment response of patients with metastatic triple-negative breast cancer: A prospective study.

Background: Limited data are available on applying circulating tumor DNA (ctDNA) in metastatic triple-negative breast cancer (mTNBC) patients. Here, we investigated the value of ctDNA for predicting the prognosis and monitoring the treatment response in mTNBC patients. Methods: We prospectively enrolled 70 Chinese patients with mTNBC who had progressed after ≤2 lines of chemotherapy and collected blood samples to extract ctDNA for 457-gene targeted panel sequencing. Results: Patients with ctDNA+, defined by 12 prognosis-relevant mutated genes, had a shorter progression-free survival (PFS) than ctDNA- patients (5.16 months vs. 9.05 months, p=0.001), and ctDNA +was independently associated with a shorter PFS (HR, 95% CI: 2.67, 1.2-5.96; p=0.016) by multivariable analyses. Patients with a higher mutant-allele tumor heterogeneity (MATH) score (≥6.316) or a higher ctDNA fraction (ctDNA%≥0.05) had a significantly shorter PFS than patients with a lower MATH score (5.67 months vs.11.27 months, p=0.007) and patients with a lower ctDNA% (5.45 months vs. 12.17 months, p<0.001), respectively. Positive correlations with treatment response were observed for MATH score (R=0.24, p=0.014) and ctDNA% (R=0.3, p=0.002), but not the CEA, CA125, or CA153. Moreover, patients who remained ctDNA +during dynamic monitoring tended to have a shorter PFS than those who did not (3.90 months vs. 6.10 months, p=0.135). Conclusions: ctDNA profiling provides insight into the mutational landscape of mTNBC and may reliably predict the prognosis and treatment response of mTNBC patients. Funding: This work was supported by the National Natural Science Foundation of China (Grant No. 81902713), Natural Science Foundation of Shandong Province (Grant No. ZR2019LZL018), Breast Disease Research Fund of Shandong Provincial Medical Association (Grant No. YXH2020ZX066), the Start-up Fund of Shandong Cancer Hospital (Grant No. 2020-PYB10), Beijing Science and Technology Innovation Fund (Grant No. KC2021-ZZ-0010-1).

Fungal-induced fossil biomineralization.

Exceptional preservation of fossils has often been attributed to the actions of bacteria that aid in the preservation of soft tissues that normally decay rapidly. However, it is well known that fungi play a major role in organic matter decomposition, biogeochemical cycling of elements, and metal-mineral transformations in modern ecosystems. Although the fungal fossil record can be traced back over a billion years, there are only a few recorded examples of fungal roles in fossilization. In this research, we have carried out a detailed geobiological investigation on early Pleistocene hyena coprolites (fossilized dung) in an attempt to ascertain possible fungal involvement in their formation. Using an advanced microscopic and mineralogical approach, we found that numerous hydroxyapatite nanofibers (25-34 nm on average), interwoven to form spheroidal structures, constituted the matrix of the coprolites in addition to food remains. These structures were found to be extremely similar in texture and mineral composition to biominerals produced during laboratory culture of a common saprophytic and geoactive fungus, Aspergillus niger, in the presence of a solid source of calcium (Ca) and phosphorus (P). This observation, and our other data obtained, strongly suggests that fungal metabolism can provide a mechanism that can result in fossil biomineralization, and we hypothesize, therefore, that this may have contributed to the formation of well-preserved fossils (Lagerstätten) in the geological record. The characteristic polycrystalline nanofibers may also have served as a potential biosignature for fungal life in early Earth and extraterrestrial environments.

Potential predictive value of circulating tumor DNA (ctDNA) mutations for the efficacy of immune checkpoint inhibitors in advanced triple-negative breast cancer.

Background: In recent years, tumor immunotherapy has become a viable treatment option for triple negative breast cancer (TNBC). Among these, immune checkpoint inhibitors (ICIs) have demonstrated good efficacy in advanced TNBC patients with programmed death-ligand 1 (PD-L1) positive expression. However, only 63% of PD-L1-positive individuals showed any benefit from ICIs. Therefore, finding new predictive biomarkers will aid in identifying patients who are likely to benefit from ICIs. In this study, we used liquid biopsies and next-generation sequencing (NGS) to dynamically detect changes in circulating tumor DNA (ctDNA) in the blood of patients with advanced TNBC treated with ICIs and focused on its potential predictive value. Methods: From May 2018 to October 2020, patients with advanced TNBC treated with ICIs at Shandong Cancer Hospital were included prospectively. Patient blood samples were obtained at the pretreatment baseline, first response evaluation, and disease progression timepoints. Furthermore, 457 cancer-related genes were evaluated by NGS, and patients' ctDNA mutations, gene mutation rates, and other indicators were determined and coupled with clinical data for statistical analysis. Results: A total of 11 TNBC patients were included in this study. The overall objective response rate (ORR) was 27.3%, with a 6.1-month median progression-free survival (PFS) (95% confidence interval: 3.877-8.323 months). Of the 11 baseline blood samples, 48 mutations were found, with the most common mutation types being frame shift indels, synonymous single-nucleotide variations (SNVs), frame indel missenses, splicing, and stop gains. Additionally, univariate Cox regression analysis revealed that advanced TNBC patients with one of 12 mutant genes (CYP2D6 deletion and GNAS, BCL2L1, H3F3C, LAG3, FGF23, CCND2, SESN1, SNHG16, MYC, HLA-E, and MCL1 gain) had a shorter PFS with ICI treatment (p < 0.05). To some extent, dynamic changes of ctDNA might indicate the efficacy of ICIs. Conclusion: Our data indicate that ICI efficacy in patients with advanced TNBC may be predicted by 12 mutant ctDNA genes. Additionally, dynamic alterations in peripheral blood ctDNA might be used to track the effectiveness of ICI therapy in those with advanced TNBC.

An Intelligent Motor Assessment Method Utilizing a Bi-Lateral Virtual-Reality Task for Stroke Rehabilitation on Upper Extremity.

Virtual reality (VR) has been widely adopted by therapists to provide rich motor training tasks. Time series data of motion trajectory accompanied with the interaction of VR system may contain important clues in regard to the assessment of motor function, however, clinical evaluation scales such as Fugl-Meyer Assessment (FMA), Wolf Motor Function Test (WMFT), and Test D'évaluation Des Membres Supérieurs Des Personnes Âgées (TEMPA) are highly depended in clinic. Further, there is not yet an assessment method that simultaneously consider motion trajectory and clinical evaluation scales. The objective of this study is to establish an evidence-based assessment model by machine-learning method that integrated motion trajectory of a VR task with clinical evaluation scales. In this study, a VR system for upper-limb motor training was proposed for stroke rehabilitation. Clinical trials with 20 stroke patients were performed. A variety of motor indicators that derived via motion trajectory were proposed. The correlations between motor indicators and clinical evaluation scales were examined. Further, motor indicators were integrated with evaluation scales to develop a machine-learning based model that represents an evidence-based motor assessment approach. Clinical evaluation scales, FMA, TEMPA and WMFT, were significantly progressed. A few motor indicators were found significantly correlated with clinical evaluation scales. The accuracy of machine-learning based assessment model was up to 86%. The proposed VR system is validated to be effective in motor rehabilitation. Motor indicators derived from motor trajectory were with potential for clinical motor assessment. Machine learning could be a promising tool to perform automatic assessment. Clinical and Translational Impact Statement-A VR task for motor rehabilitation was exanimated via clinical trials. Integrating motor indices with clinical assessment, a machine-learning model with accuracy of 86% was developed to evaluate motor function.

Classification of Subgroups with Immune Characteristics Based on DNA Methylation in Luminal Breast Cancer.

Luminal breast cancer (BC) accounts for a large proportion of patients in BC, with high heterogeneity. Determining the precise subtype and optimal selection of treatment options for luminal BC is a challenge. In this study, we proposed an MSBR framework that integrate DNA methylation profiles and transcriptomes to identify immune subgroups of luminal BC. MSBR was implemented both on a key module scoring algorithm and "Boruta" feature selection method by DNA methylation. Luminal A was divided into two subgroups and luminal B was divided into three subgroups using the MSBR. Furthermore, these subgroups were defined as different immune subgroups in luminal A and B respectively. The subgroups showed significant differences in DNA methylation levels, immune microenvironment (immune cell infiltration, immune checkpoint PD1/PD-L1 expression, immune cell cracking activity (CYT)) and pathology features (texture, eccentricity, intensity and tumor-infiltrating lymphocytes (TILs)). The results also showed that there is a subgroup in both luminal A and B that has the benefit from immunotherapy. This study proposed a classification of luminal BC from the perspective of epigenetics and immune characteristics, which provided individualized treatment decisions.

Identification of mRNA Signature for Predicting Prognosis Risk of Rectal Adenocarcinoma.

Background: The immune system plays a crucial role in rectal adenocarcinoma (READ). Immune-related genes may help predict READ prognoses. Methods: The Cancer Genome Atlas dataset and GSE56699 were used as the training and validation datasets, respectively, and differentially expressed genes (DEGs) were identified. The optimal DEG combination was determined, and the prognostic risk model was constructed. The correlation between optimal DEGs and immune infiltrating cells was evaluated. Results: Nine DEGs were selected for analysis. Moreover, ADAMDEC1 showed a positive correlation with six immune infiltrates, most notably with B cells and dendritic cells. F13A1 was also positively correlated with six immune infiltrates, particularly macrophage and dendritic cells, whereas LGALS9C was negatively correlated with all immune infiltrates except B cells. Additionally, the prognostic risk model was strongly correlated with the actual situation. We retained only three prognosis risk factors: age, pathologic stage, and prognostic risk model. The stratified analysis revealed that lower ages and pathologic stages have a better prognosis with READ. Age and mRNA prognostic factors were the most important factors in determining the possibility of 3- and 5-year survival. Conclusion: In summary, we identified a nine-gene prognosis risk model that is applicable to the treatment of READ. Altogether, characteristics such as the gene signature and age have a strong predictive value for prognosis risk.

Evaluating the survival of Aspergillus niger in a highly polluted red soil with addition of Phosphogypsum and bioorganic fertilizer.

Phosphate-solubilizing fungi (PSF) can enhance P release from phosphate minerals to immobilize heavy metals. However, this promotion substantially depends on their survival in highly polluted soils. The aim of this study was to investigate the survival of PSF after addition of phosphogypsum (PG) and bioorganic fertilizer (BF) in the soil with coexistence of multiple heavy metals, e.g., Pb, As, Cd, Sb, etc. Addition of typical PSF (Aspergillus niger) did not promote the formation of pyromorphite (the most stable form of Pb), possibly due to the buffering effect of the soil (the secreted oxalic acid was neutralized) and limited P supply. Meanwhile, despite that A. niger has high tolerance to heavy metal stress, its survival was significantly declined due to the deficiency of available P. It was also shown that PG, as the major by-product in phoschemical industry, still has relatively high available P compared with common natural soils. PG addition dramatically increased available P (up to 93.87 mg/kg) and the subsequent fungal growth. However, sole PG did not promote the formation of pyromorphite, probably as the abundant Fe2+ and Mn2+ prevented the contact between PO43- and Pb2+ in the soil system. The enhanced soil respiration after addition of BF and PG confirmed the promoted microbial activity (elevated to 3465.58 µg C kg h-1). This study showed PG's potential as P source for both microbial growth and heavy metal remediation in soil system. A combination of PG, A. niger, and BF can hence achieve long-term bioremediation of heavy metals.

Weakened Cd toxicity to fungi under coexistence of Pb in solution.

The coexistence of heavy metals in aquatic systems causes complex toxicity in microorganisms. In this study, we explored the influences of Pb2+ addition on Cd2+ toxicity in Rhodotorula mucilaginosa (Rho). Cd toxicity alone was tested with up to 200 mg/L Cd2+ to induce stress. Cell counts and Cd2+ removal rates declined to a minimum when the Cd2+ concentration reached 150 mg/L, confirming strong Cd-induced toxicity. Then, co-existence of Pb2+ and Cd2+ was established as Pb-CdH (Pb/Cd = 1, molar ratio), Pb-CdM (Pb/Cd = 10), and Pb-CdL (Pb/Cd = 100). The Pb-CdL and Pb-CdM treatments showed clear similarities in terms of their effects on cell counts, polysaccharide concentrations, and cell morphology. There was also no significant difference in their gene expression profiles. The competition between the two types of cations caused preferential extra/intracellular sorption of less toxic Pb2+. Moreover, the expression of genes related to glycolysis, the TCA cycle, and oxidative phosphorylation was significantly enhanced in the cells with Pb-CdH treatment, suggesting that these cells were functional. Furthermore, the excitability-caused increase in the cell count after Pb-CdH treatment (Cd2+ = 112.4 mg/L) was 30% higher than that of the 100 mg/L Cd2+ treatment. These results proved that the addition of Pb2+ in solution significantly weakened the toxicity of Cd2+.

Electron microscopic imaging and NanoSIMS investigation on physiological responses of Aspergillus niger under Pb(II) and Cd(II) stress.

In the bioremediation process, coexistence of lead (Pb) and cadmium causes complex toxicity, resulting in the difficulty of bioremediation. This study investigated the physiological responses and bioaccumulation mechanisms of the typical filamentous fungus Aspergillus niger under the coexistence of Pb and Cd. Four treatments were set up, i.e., control, sole Pb, sole Cd, and coexistence of Pb and Cd. The morphology of A. niger were observed by scanning electron microscopy (SEM) and transmission electron microscopy (TEM), respectively. Then, nano-scale secondary ion mass spectrometry (NanoSIMS) was applied to accurately investigate the distribution of heavy metals in the fungal cells under the coexistence of Pb and Cd. Finally, the metallogenic process and mineral types were simulated by Geochemist's Workbench (GWB). The electron microscopic and NanoSIMS imaging showed that Pb and Cd were accumulated in both the extracellular and intracellular regions of the A. niger cells. In particular, the accumulated Pb content was ten times higher than that of Cd. However, Cd showed stronger toxicity than Pb to A. niger. Compared with the control treatment, Cd stress resulted in a two-fold increase of cell diameter and more extracellular substances, whereas the cell diameter increased nearly four times in the coexistence treatment. Moreover, the bioaccumulation of Pb was more intense than that of Cd during competitive sorption. The GWB simulation confirmed that Pb2+ can form multiple minerals (e.g., PbC2O4, PbHPO4, and Pb3(PO4)2, etc.), which significantly weakened its toxicity on the cell surface. This study elucidated the morphological characteristics of A. niger and competitive bioaccumulation under the coexistence of Pb and Cd, which would facilitate the application of microorganisms to the bioremediation of coexisted metals.

The value of intravoxel incoherent motion magnetic resonance imaging and texture analysis for predicting BRAF gene mutation in rectal cancer / 中华消化外科杂志

Objective:To investigate the value of intravoxel incoherent motion (IVIM) magnetic resonance imaging (MRI) and texture analysis for predicting BRAF gene mutation in rectal cancer.Methods:The clinical diagnositic trial was conducted. The clinicopathological data of 36 rectal cancer patients who were admitted to the First People's Hospital of Shangqiu from January 2016 to June 2021 were collected. There were 28 males and 8 females, aged (50±4)years. All the 36 patients were confirmed by pathological examination. After genetic testing, 12 patients with BRAF mutant type of BRAF V600E mutation were allocated into the mutation group, and 24 patients with BRAF wild type were allocated into the non-mutation group. All patients underwent MRI scan before surgery, and IVIM related post-processing images were received by Function Tool post-processing software. Observation indicators: (1) consistency test between observers of IVIM para-meters and texture parameters; (2) comparison of IVIM parameters on MRI between the two groups; (3) comparison of texture parameters on MRI between the two groups; (4) diagnostic efficacy of IVIM and texture parameters. The intraclass correlation coefficient (ICC) was used to evaluate the consistency between observers, with ICC >0.80 as good consistency. The average values of para-meters with ICC >0.80 were included for further analysis. Measurement data with normal distribu-tion were represented as Mean± SD, and comparison between groups was analyzed by the indepen-dent sample t test. Measurement data with skewed distribution were represented as M( Q1, Q3), and comparison between groups was analyzed using the Mann-Whitney U test. Count data were described as absolute numbers, and comparison between groups was analyzed by the chi-square test. Comparison of ordinal data was analyzed by the non-parameter rank sum test. The texture parameters were combined using the Logistic regression model. Receiver operating charac-teristic curve was used to analyze the predictive performance and calculate the sensitivity and specificity. Results:(1) Consistency test between observers of IVIM parameters and texture parameters: the ICCs between two observers of IVIM parameters including apparent diffusion coefficient, diffusion related coefficient, perfusion-related diffusion coefficient and perfusion-related parameter were 0.91, 0.90, 0.91, 0.89, respectively. The ICCs of texture parameters including the minimum value, the maximum value, the 10th percentile and the 25th percentile between two observers were <0.80 while the ICCs of texture parameters including mean value, the 50th percentile, the 75th percentile, the 90th percentile, energy, entropy, skewness and kurtosis between two observers were >0.80. (2) Comparison of IVIM parameters on MRI between the two groups: IVIM parameters of diffusion related coefficient and perfusion-related parameter on MRI were (0.70±0.13)×10 -3 mm 2/s and 0.39±0.30 for the mutation group, versus (0.79±0.12)×10 -3 mm 2/s and 0.17±0.10 for the non-mutation group, showing significant differences between the two groups ( t=-2.17, 2.46, P<0.05). (3) Comparison of texture parameters on MRI between the two groups: the texture parameters of mean value and energy on diffusion related coefficient image were 0.54±0.23 and 0.00(0.00,0.01) for the mutation group, versus 0.77±0.34 and 0.01(0.00,0.01) for the non-mutation group, showing significant differences between the two groups ( t=-2.12, Z=-1.35, P<0.05). (4) Diagnostic efficacy of IVIM and texture parameters: the areas under the curve (AUCs) of diffusion related coefficient, perfusion-related parameter, IVIM parameters combination, mean value of diffu-sion related coefficient image, energy value of diffusion related coefficient image, texture parameters combination were 0.69[95% confidence interval ( CI) as 0.52-0.84], 0.76(95% CI as 0.59-0.88), 0.79(95% CI as 0.62-0.91), 0.71(95% CI as 0.52-0.85), 0.79(95% CI as 0.62-0.91), 0.84(95% CI as 0.68-0.94), which were all lower than the AUC of IVIM and texture parameters combination as 0.92(95% CI as 0.79-0.99). Conclusions:IVIM parameters and texture parameters of MRI can non-invasively predict the mutation status of BRAF gene in rectal cancer. The combination of IVIM and texture parameters has a better predictive efficacy.

A Prognostic Signature of Glycolysis-Related Long Noncoding RNAs for Molecular Subtypes in the Tumor Immune Microenvironment of Lung Adenocarcinoma.

PURPOSE: Long noncoding RNAs (lncRNAs) and glycolysis regulate multiple types of cancer. However, the prognostic roles and biological functions of glycolysis-related lncRNAs in lung adenocarcinoma (LUAD) remain unclear. In this study, we investigated the role of glycolysis-related lncRNAs in LUAD. PATIENTS AND METHODS: We retrieved glycolysis-related genes from the Molecular Signatures Database and screened for prognostic glycolysis-related lncRNAs from The Cancer Genome Atlas. RESULTS: We identified three LUAD subtypes (clusters 1-3) by univariate Cox regression analysis and consensus clustering. Patients in cluster 1 had the best overall survival rates. Immune, stromal, and cytolytic-activity scores were the highest in cluster 1. The expression of immune checkpoint molecules (programmed cell death protein 1 and cytotoxic T-lymphocyte-associated protein 4) and other immune-related indicators was the highest in cluster 1, whereas that of epithelial cell biomarkers (Cadherin 1, Cadherin 2, and MET) was the lowest. Therefore, patients in cluster 1 may benefit from immunotherapy. Lasso-Cox regression and multivariate Cox regression analyses were used to select nine lncRNAs to build a robust prognostic model of LUAD. The area under the curve classifier values and a nomogram performed well in predicting survival times for patients with LUAD. The expression levels of nine lncRNAs were validated by quantitative reverse transcriptase-polymerase chain reaction analysis, and most of these lncRNAs were significantly related to immune-related mRNAs. Gene set enrichment analysis revealed that the high-risk group was enriched for cell cycle-related pathways and the low-risk group was enriched for pathways associated with immunity or immune-related diseases. CONCLUSION: The LUAD subtypes and prognostic model developed here may help in clinical risk stratification, prognosis management, and treatment decisions for patients with LUAD.

The dissolution of fluorapatite by phosphate-solubilizing fungi: a balance between enhanced phosphorous supply and fluorine toxicity.

Fluorapatite (FAp) is the largest phosphorous (P) reservoir on Earth. However, due to its low solubility, dissolved P is severely deficient in the pedosphere. Fungi play a significant role in P dissolution via excretion of organic acids, and in this regard, it is important to understand their impact on P cycling. The object of this study was to elucidate the balance between P release and F toxicity during FAp dissolution. The bioweathering of FAp was assisted by a typical phosphate-solubilizing fungus, Aspergillus niger. The release of elements and microbial activities were monitored during 5-day incubation. We found that the release of fluorine (F) was activated after day 1 (~90 mg/L), which significantly lowered the phosphate-solubilizing process by day 2. Despite P release from FAp being enhanced over the following 3 days, decreases in both the amount of biomass (52% decline) and the respiration rate (81% decline) suggest the strong inhibitory effect of F on the fungus. We thus concluded that F toxicity outweighs P supply, which in turn inhibits fungi growth and prevents further dissolution of FAp. This mechanism might reflect an underappreciated cause for P deficiency in soils.

Accurate Prediction of Prognosis by Integrating Clinical and Molecular Characteristics in Colon Cancer.

Various factors affect the prognosis of patients with colon cancer. Complicated factors are found to be conducive to accurate assessment of prognosis. In this study, we developed a series of prognostic prediction models for survival time of colon cancer patients after surgery. Analysis of nine clinical characteristics showed that the most important factor was the positive lymph node ratio (LNR). High LNR was the most important clinical factor affecting 1- and 3-year survival; M0&age < 70 was the most important feature for 5 years. The performance of the model was improved through the integration of clinical characteristics and four types of molecule features (mRNA, lncRNA, miRNA, DNA methylation). The model provides guidance for clinical practice. According to the high-risk molecular features combined with age ≥ 70&T3, poorly differentiated or undifferentiated, M0&well differentiated, M0&T2, LNR high, T4&poorly differentiated, or undifferentiated, the survival time may be less than 1 year; for patients with high risk of molecular features combined with M0&T2, M0&T4, LNR 0& M0, LNR median &T3, and LNR high, the survival is predicted less than 3 years; and the survival of patients with M1&T3, M0 and high risk molecular features is less than 5 years. Using multidimensional and complex patient information, this study establishes potential criteria for clinicians to evaluate the survival of patients for colon cancer.

EphA2 super-enhancer promotes tumor progression by recruiting FOSL2 and TCF7L2 to activate the target gene EphA2.

Super-enhancers or stretch enhancers (SEs) consist of large clusters of active transcription enhancers which promote the expression of critical genes that define cell identity during development and disease. However, the role of many super-enhancers in tumor cells remains unclear. This study aims to explore the function and mechanism of a new super-enhancer in various tumor cells. A new super-enhancer that exists in a variety of tumors named EphA2-Super-enhancer (EphA2-SE) was found using multiple databases and further identified. CRISPR/Cas9-mediated deletion of EphA2-SE results in the significant downregulation of its target gene EphA2. Mechanistically, we revealed that the core active region of EphA2-SE comprises E1 component enhancer, which recruits TCF7L2 and FOSL2 transcription factors to drive the expression of EphA2, induce cell proliferation and metastasis. Bioinformatics analysis of RNA-seq data and functional experiments in vitro illustrated that EphA2-SE deletion inhibited cell growth and metastasis by blocking PI3K/AKT and Wnt/ß-catenin pathway in HeLa, HCT-116 and MCF-7 cells. Overexpression of EphA2 in EphA2-SE-/- clones rescued the effect of EphA2-SE deletion on proliferation and metastasis. Subsequent xenograft animal model revealed that EphA2-SE deletion suppressed tumor proliferation and survival in vivo. Taken together, these findings demonstrate that EphA2-SE plays an oncogenic role and promotes tumor progression in various tumors by recruiting FOSL2 and TCF7L2 to drive the expression of oncogene EphA2.

Clay-assisted protection of Enterobacter sp. from Pb (II) stress.

Clay minerals can adsorb both microorganisms and heavy metals. In this study, typical soil bacterium, Enterobacter sp. was applied to investigate the potential protection of the bacterial cells from Pb2+ stress by clay minerals. The sorption by two representative types of montmorillonite (Mt) were contrasted, i.e., Mts/Mtw with strong/weak CEC. There was no significant difference between the two clay minerals regarding their adsorption of Pb2+ cations in water (i.e., ~55 mg L-1). However, the sorption of bacterial cells on the two clay minerals showed evident contrasts, which resulted in the different capacity of Pb sorption. Mts with high CEC preferentially adsorbed abundant bacterial cells (rather than Pb2+) on its surface. The residual Pb2+ concentration in solution actually raised by 7.5% after the addition of Enterobacter sp. In addition, both the Pb-contaminated cells and "healthy" cells (with low Pb contamination) could be adsorbed onto Mt surface, whereas the latter dominated the adsorbents on Mts. This was due to that the Mts with high CEC could provide more exchangeable cations, building more cation bridging ligands between the microbial cells (whatever the types of cells) and clay surface. Furthermore, the adsorbed "healthy" bacterial cells might escape from clay surface via "self-liberating" mechanism, i.e., increasing electrostatic repulsion between the bacteria and clay during microbial decomposition of the medium. This study hence elucidated the protection of microorganisms from Pb2+ stress by Mt.

Influences of phosphate addition on fungal weathering of carbonate in the red soil from karst region.

Carbonate in soil from karst region is a substantial carbon sink on Earth. Many karst regions are covered by P-deficient soil. This study evaluated the influences of phosphate addition on fungal weathering (by typical phosphate-solubilizing fungus Aspergillus niger) of carbonate in the soil with red color from karst region. Two weathering pathways were recognized, i.e., biochemical and biomechanical deterioration. The biochemical pathway was performed by dissolving carbonate via secreting organic acids. Meanwhile, the dominant organic acid, i.e., oxalic acid, induced the formation of calcium oxalate, which prevented the loss of Ca2+ cations. It was estimated that the ideal carbonate solubilization driven by geological fluorapatite and fungal weathering is up to 3.3% per year, based on the equation of 12 × (RBase + RPSF) × m × (Areal/APSF). Moreover, fungal weathering of carbonate is very sensitive to the solubility of phosphates. Phosphates supply essential P source for the fungal growth and subsequently raise water-soluble P content in the soil. The addition of bioapatite (a variety of natural apatite with relatively high solubility) elevated the value to 4.6% (a ~ 40% enhancement compared with FAp). This research hence elucidated the tight correlation between carbonate weathering and P supply. Inorganic C release driven by P availability and microbial weathering should be addressed in karst region.