Efficacy of high-dose-rate brachytherapy with different radiation source activities among cervical cancer patients and risk factors for long-term outcomes: A 6-year retrospective study.

PURPOSE: This study aimed to assess the impact of dose rates due to natural decay of Iridium-192 sources and the risk factors of clinical outcomes for cervical cancer patients treated with high-dose-rate (HDR) brachytherapy. METHODS AND MATERIALS: Four ninety-four patients were divided into relatively-high-radioactive (rHR), relatively-medium-radioactive (rMR), and relatively-low-radioactive (rLR) groups for retrospective treatment response comparison. The short-term outcomes were evaluated using the 1-month /3-month follow-up results based on RECIST 1.1. Local recurrence-free survival (LRFS) and metastatic recurrence-free survival (MRFS) were selected as long-term outcomes. A class of transformation models with adaptive lasso was applied to assess the risk factors of long-term outcomes. RESULTS: No significant difference was identified in short- or long-term outcomes of different radioactive groups. Subgroup analyses demonstrated similar findings. In multivariate factor analysis, advanced stage was significantly associated with higher risk of local recurrence and metastatic recurrence (HR = 1.66, 95%confidence interval [CI] = 1.14-2.43, p = 0.008; HR = 1.57, 95%CI = 1.23-2.00, p < 0.001). Significant associations were observed between local recurrence and pathology, and between metastatic recurrence and pre-treatment serum indices, respectively (HR = 8.62, 95%CI = 2.28-32.60, p = 0.002; HR = 1.98, 95%CI=1.20-2.26, p = 0.008). CONCLUSIONS: Overall, there was no significant difference in long- or short-term efficacy of the HDR brachytherapy among the groups with different levels of activity of radiation sources. Stage, pathology, and pretreatment serum indices were crucial factors that affected the long-term outcomes.

Non-oncology drug (meticrane) shows anti-cancer ability in synergy with epigenetic inhibitors and appears to be involved passively in targeting cancer cells.

Emerging evidence suggests that chemotherapeutic agents and targeted anticancer drugs have serious side effects on the healthy cells/tissues of the patient. To overcome this, the use of non-oncology drugs as potential cancer therapies has been gaining momentum. Herein, we investigated one non-oncology drug named meticrane (a thiazide diuretic used to treat essential hypertension), which has been reported to indescribably improve the therapeutic efficacy of anti-CTLA4 in mice with AB1 HA tumors. In our hypothesis-driven study, we tested anti-cancer potential meticrane in hematological malignance (leukemia and multiple myeloma) and liver cancer cell lines. Our analysis showed that: 1) Meticrane induced alteration in the cell viability and proliferation in leukemia cells (Jurkat and K562 cells) and liver cancer (SK-hep-1), however, no evidence of apoptosis was detectable. 2) Meticrane showed additive/synergistic effects with epigenetic inhibitors (DNMT1/5AC, HDACs/CUDC-101 and HDAC6/ACY1215). 3) A genome-wide transcriptional analysis showed that meticrane treatment induces changes in the expression of genes associated with non-cancer associated pathways. Of importance, differentially expressed genes showed favorable correlation with the survival-related genes in the cancer genome. 4) We also performed molecular docking analysis and found considerable binding affinity scores of meticrane against PD-L1, TIM-3, CD73, and HDACs. Additionally, we tested its suitability for immunotherapy against cancers, but meticrane showed no response to the cytotoxicity of cytokine-induced killer (CIK) cells. To our knowledge, our study is the first attempt to identify and experimentally confirm the anti-cancer potential of meticrane, being also the first to test the suitability of any non-oncology drug in CIK cell therapy. Beyond that, we have expressed some concerns confronted during testing meticrane that also apply to other non-oncology drugs when considered for future clinical or preclinical purposes. Taken together, meticrane is involved in some anticancer pathways that are passively targeting cancer cells and may be considered as compatible with epigenetic inhibitors.

scAnno: a deconvolution strategy-based automatic cell type annotation tool for single-cell RNA-sequencing data sets.

Undoubtedly, single-cell RNA sequencing (scRNA-seq) has changed the research landscape by providing insights into heterogeneous, complex and rare cell populations. Given that more such data sets will become available in the near future, their accurate assessment with compatible and robust models for cell type annotation is a prerequisite. Considering this, herein, we developed scAnno (scRNA-seq data annotation), an automated annotation tool for scRNA-seq data sets primarily based on the single-cell cluster levels, using a joint deconvolution strategy and logistic regression. We explicitly constructed a reference profile for human (30 cell types and 50 human tissues) and a reference profile for mouse (26 cell types and 50 mouse tissues) to support this novel methodology (scAnno). scAnno offers a possibility to obtain genes with high expression and specificity in a given cell type as cell type-specific genes (marker genes) by combining co-expression genes with seed genes as a core. Of importance, scAnno can accurately identify cell type-specific genes based on cell type reference expression profiles without any prior information. Particularly, in the peripheral blood mononuclear cell data set, the marker genes identified by scAnno showed cell type-specific expression, and the majority of marker genes matched exactly with those included in the CellMarker database. Besides validating the flexibility and interpretability of scAnno in identifying marker genes, we also proved its superiority in cell type annotation over other cell type annotation tools (SingleR, scPred, CHETAH and scmap-cluster) through internal validation of data sets (average annotation accuracy: 99.05%) and cross-platform data sets (average annotation accuracy: 95.56%). Taken together, we established the first novel methodology that utilizes a deconvolution strategy for automated cell typing and is capable of being a significant application in broader scRNA-seq analysis. scAnno is available at https://github.com/liuhong-jia/scAnno.

Comprehensive prognostic modeling of locoregional recurrence after radiotherapy for patients with locoregionally advanced hypopharyngeal squamous cell carcinoma.

Purpose: To propose and evaluate a comprehensive modeling approach combing radiomics, dosiomics and clinical components, for more accurate prediction of locoregional recurrence risk after radiotherapy for patients with locoregionally advanced HPSCC. Materials and methods: Clinical data of 77 HPSCC patients were retrospectively investigated, whose median follow-up duration was 23.27 (4.83-81.40) months. From the planning CT and dose distribution, 1321 radiomics and dosiomics features were extracted respectively from planning gross tumor volume (PGTV) region each patient. After stability test, feature dimension was further reduced by Principal Component Analysis (PCA), yielding Radiomic and Dosiomic Principal Components (RPCs and DPCs) respectively. Multiple Cox regression models were constructed using various combinations of RPC, DPC and clinical variables as the predictors. Akaike information criterion (AIC) and C-index were used to evaluate the performance of Cox regression models. Results: PCA was performed on 338 radiomic and 873 dosiomic features that were tested as stable (ICC1 > 0.7 and ICC2 > 0.95), yielding 5 RPCs and DPCs respectively. Three comprehensive features (RPC0, P<0.01, DPC0, P<0.01 and DPC3, P<0.05) were found to be significant in the individual Radiomic or Dosiomic Cox regression models. The model combining the above features and clinical variable (total stage IVB) provided best risk stratification of locoregional recurrence (C-index, 0.815; 95%CI, 0.770-0.859) and prevailing balance between predictive accuracy and complexity (AIC, 143.65) than any other investigated models using either single factors or two combined components. Conclusion: This study provided quantitative tools and additional evidence for the personalized treatment selection and protocol optimization for HPSCC, a relatively rare cancer. By combining complementary information from radiomics, dosiomics, and clinical variables, the proposed comprehensive model provided more accurate prediction of locoregional recurrence risk after radiotherapy.

System Matrix Reconstruction Algorithm for Thermoacoustic Imaging With Magnetic Nanoparticles Based on Acoustic Reciprocity Theorem.

OBJECTIVE: According to the acoustic reciprocity theorem (ART), we propose a system matrix reconstruction algorithm of thermoacoustic imaging for magnetic nanoparticles (MNPs) by a single-pulse magnetic field. METHODS: In both cases of inhomogeneous and homogeneous acoustic velocity, we respectively derive the linear equation between the sound pressure detection value and the distribution of MNPs. The image reconstruction problem is converted to an inverse matrix solution by using the truncated singular value decomposition (TSVD) method. RESULTS: In forward problem, the calculated forward results are consistent with the simulated thermoacoustic signal signals. In inverse problem, we build the two-dimensional breast cancer model. The TSVD method based on the ART faithfully reflects the distribution of abnormal tissue labeled by the MNPs. In the experiment, the biological sample injected with the MNPs is used as the imaging target. The reconstructed image well reflects the cross-sectional images of the MNPs area. CONCLUSION: The TSVD method based on the ART takes into account energy attenuation and inhomogeneous acoustic velocity, and use a non-focused broadband ultrasonic transducer as the receiver to obtain a larger imaging field-of-view (FOV). By comparing the image metrics, we prove that the algorithm is superior to the traditional time reversal method. SIGNIFICANCE: The TSVD method based on the ART can better suppress noise, which is expected to reduce the cost by reducing the number of detectors. It is of great significance for future clinical applications.

The Rice Aspartyl-tRNA Synthetase YLC3 Regulates Amino Acid Homeostasis and Chloroplast Development Under Low Temperature.

Aminoacyl tRNA synthetases primarily function to attach specific amino acids to the corresponding tRNAs during protein translation. However, their roles in regulating plant growth and development still remain elusive. Here we reported a rice thermo-sensitive mutant yellow leaf chlorosis3 (ylc3) with reduced chlorophyll content, altered thylakoid structure, and substantially elevated levels of free aspartate, asparagine and glutamine in leaves under low temperature condition. Map-based cloning identified that YLC3 encodes an aspartyl-tRNA synthetase which is localized in cytosol and mitochondria. In addition, quantitative proteomics analysis revealed that both nuclear and chloroplast-encoded thylakoid proteins were significantly down-regulated in the mutant. On the other hand, proteins involved in amino acid metabolism and the process of protein synthesis were up-regulated in ylc3, particularly for key enzymes that convert aspartate to asparagine. Moreover, uncharged tRNA-Asp accumulation and phosphorylation of the translation initiation factor eIF2α was detected in the mutant, suggesting that YLC3 regulates the homeostasis of amino acid metabolism and chloroplast thylakoid development through modulation of processes during protein synthesis.

Brain disorder prediction with dynamic multivariate spatio-temporal features: Application to Alzheimer's disease and autism spectrum disorder.

The dynamic functional connectivity (dFC) in functional magnetic resonance imaging (fMRI) is beneficial for the analysis and diagnosis of neurological brain diseases. The dFCs between regions of interest (ROIs) are generally delineated by a specific template and clustered into multiple different states. However, these models inevitably fell into the model-driven self-contained system which ignored the diversity at spatial level and the dynamics at time level of the data. In this study, we proposed a spatial and time domain feature extraction approach for Alzheimer's disease (AD) and autism spectrum disorder (ASD)-assisted diagnosis which exploited the dynamic connectivity among independent functional sub networks in brain. Briefly, independent sub networks were obtained by applying spatial independent component analysis (SICA) to the preprocessed fMRI data. Then, a sliding window approach was used to segment the time series of the spatial components. After that, the functional connections within the window were obtained sequentially. Finally, a temporal signal-sensitive long short-term memory (LSTM) network was used for classification. The experimental results on Alzheimer's Disease Neuroimaging Initiative (ADNI) and Autism Brain Imaging Data Exchange (ABIDE) datasets showed that the proposed method effectively predicted the disease at the early stage and outperformed the existing algorithms. The dFCs between the different components of the brain could be used as biomarkers for the diagnosis of diseases such as AD and ASD, providing a reliable basis for the study of brain connectomics.

Regulator of G Protein Signaling 20 Correlates with Long Intergenic Non-Coding RNA (lincRNAs) Harboring Oncogenic Potential and Is Markedly Upregulated in Hepatocellular Carcinoma.

Hepatocellular carcinoma (HCC) is at the forefront of the global cancer burden, and biomarkers for HCC are constantly being sought. Interestingly, RGS (Regulators of G protein signaling) proteins, which negatively regulate GPCR signaling, have been associated with various cancers, with some members of the RGS family being associated with liver cancer as well. Considering this, we investigated the role of RGS20 as a potential prognostic marker in 28 different cancer types with special emphasis on HCC. By using the Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) data, our analysis revealed that (a) RGS20 was strongly upregulated in tumor tissue compared with adjacent normal tissue of HCC patients; (b) RGS20 was strongly associated with some important clinical parameters such as alpha-fetoprotein and tumor grade in the HCC patients; (c) besides HCC (p < 0.001), RGS20 was found to be an important factor for survival in four other cancers (clear renal cell carcinoma: p < 0.001, lung adenocarcinoma: p = 0.004, mesothelioma: p = 0.039, ovarian serous cystadenocarcinoma: p = 0.048); (d) RGS20 was found to be significantly associated with some tumor-related signaling pathways and long intergenic non-coding RNAs (lincRNAs: LINC00511, PVT1, MIR4435-2HG, BCYRN1, and MAPKAPK5-AS1) that exhibit oncogenic potential. Taken together, we showed that RGS20 correlates with a few HCC-associated lincRNAs harboring oncogenic potential and is markedly upregulated in HCC patients. Our analysis further supports the putative function of RGS proteins, particularly RGS20, in cancer.

Oncogenic signaling pathway-related long non-coding RNAs for predicting prognosis and immunotherapy response in breast cancer.

Background: The clinical outcomes of breast cancer (BC) are unpredictable due to the high level of heterogeneity and complex immune status of the tumor microenvironment (TME). When set up, multiple long non-coding RNA (lncRNA) signatures tended to be employed to appraise the prognosis of BC. Nevertheless, predicting immunotherapy responses in BC is still essential. LncRNAs play pivotal roles in cancer development through diverse oncogenic signal pathways. Hence, we attempted to construct an oncogenic signal pathway-based lncRNA signature for forecasting prognosis and immunotherapy response by providing reliable signatures. Methods: We preliminarily retrieved RNA sequencing (RNA-seq) data from The Cancer Genome Atlas (TCGA) database and extracted lncRNA profiles by matching them with GENCODE. Following this, Gene Set Variation Analysis (GSVA) was used to identify the lncRNAs closely associated with 10 oncogenic signaling pathways from the TCGA-BRCA (breast-invasive carcinoma) cohort and was further screened by the least absolute shrinkage and selection operator Cox regression model. Next, an lncRNA signature (OncoSig) was established through the expression level of the final 29 selected lncRNAs. To examine survival differences in the stratification described by the OncoSig, the Kaplan-Meier (KM) survival curve with the log-rank test was operated on four independent cohorts (n = 936). Subsequently, multiple Cox regression was used to investigate the independence of the OncoSig as a prognostic factor. With the concordance index (C-index), the time-dependent receiver operating characteristic was employed to assess the performance of the OncoSig compared to other publicly available lncRNA signatures for BC. In addition, biological differences between the high- and low-risk groups, as portrayed by the OncoSig, were analyzed on the basis of statistical tests. Immune cell infiltration was investigated using gene set enrichment analysis (GSEA) and deconvolution tools (including CIBERSORT and ESTIMATE). The combined effect of the Oncosig and immune checkpoint genes on prognosis and immunotherapy was elucidated through the KM survival curve. Ultimately, a pan-cancer analysis was conducted to attest to the prevalence of the OncoSig. Results: The OncoSig score stratified BC patients into high- and low-risk groups, where the latter manifested a significantly higher survival rate and immune cell infiltration when compared to the former. A multivariate analysis suggested that OncoSig is an independent prognosis predictor for BC patients. In addition, compared to the other four publicly available lncRNA signatures, OncoSig exhibited superior predictive performance (AUC = 0.787, mean C-index = 0.714). The analyses of the OncoSig and immune checkpoint genes clarified that a lower OncoSig score meant significantly longer survival and improved response to immunotherapy. In addition to BC, a high OncoSig score in several other cancers was negatively correlated with survival and immune cell infiltration. Conclusions: Our study established a trustworthy and discriminable prognostic signature for BC patients with similar clinical profiles, thus providing a new perspective in the evaluation of immunotherapy responses. More importantly, this finding can be generalized to be applicable to the vast majority of human cancers.

Deep learning-based synthetization of real-time in-treatment 4D images using surface motion and pretreatment images: A proof-of-concept study.

PURPOSE: To develop a deep learning model that maps body surface motion to internal anatomy deformation, which is potentially applicable to dose-free real-time 4D virtual image-guided radiotherapy based on skin surface data. METHODS: Body contours were segmented out of 4DCT images. Deformable image registration algorithm was used to register the end-of-exhalation (EOE) phase to other phases. Deformation vector field was dimension-reduced to the first two principal components (PCs). A deep learning model was trained to predict the two PC scores of each phase from surface displacement. The instant deformation field can then be reconstructed, warping EOE image to obtain real-time CT image. This approach was validated on 4D XCAT phantom, the public DIR-Lab, and 4D-Lung dataset respectively, with and without simulated noise. RESULTS: Validation accuracy of the tumor centroid trajectory was observed as 0.04 ± 0.02 mm on XCAT phantom. For the DIR-Lab dataset, 300 landmarks were annotated on the end-of-inhalation (EOI) images of each patient, and the mean displacements between their predicted and reference positions were below 2 mm for all studied cases. For the 4D-Lung dataset, the average dice coefficients ± std between predicted and reference tumor contours at EOI phase were 0.835 ± 0.092 for all studied cases. CONCLUSIONS: A deep learning-based approach was proposed and validated to predict internal anatomy deformation from the surface motion, which is potentially applicable to on-line target navigation for accurate radiotherapy based on real-time 4D skin surface data and pretreatment images.

WNT/ß-Catenin-Mediated Resistance to Glucose Deprivation in Glioblastoma Stem-like Cells.

Isocitrate dehydrogenase (IDH)-wildtype glioblastoma is the most common primary malignant brain tumor. It is associated with a particularly poor prognosis, as reflected by an overall median survival of only 15 months in patients who undergo a supramarginal surgical reduction of the tumor mass followed by combined chemoradiotherapy. The highly malignant nature of IDH-wildtype glioblastoma is thought to be driven by glioblastoma stem-like cells (GSCs) that harbor the ability of self-renewal, survival, and adaptability to challenging environmental conditions. The wingless (WNT) signaling pathway is a phylogenetically highly conserved stemness pathway, which promotes metabolic plasticity and adaptation to a nutrient-limited tumor microenvironment. To unravel the reciprocal regulation of the WNT pathway and the nutrient-limited microenvironment, glioblastoma cancer stem-like cells were cultured in a medium with either standard or reduced glucose concentrations for various time points (24, 48, and 72 h). Glucose depletion reduced cell viability and facilitated the survival of a small population of starvation-resistant tumor cells. The surviving cells demonstrated increased clonogenic and invasive properties as well as enhanced chemosensitivity to pharmacological inhibitors of the WNT pathway (LGK974, berberine). Glucose depletion partially led to the upregulation of WNT target genes such as CTNNB1, ZEB1, and AXIN2 at the mRNA and corresponding protein levels. LGK974 treatment alone or in combination with glucose depletion also altered the metabolite concentration in intracellular compartments, suggesting WNT-mediated metabolic regulation. Taken together, our findings suggest that WNT-mediated metabolic plasticity modulates the survival of GSCs under nutrient-restricted environmental conditions.

Crosstalk between ß-Catenin and CCL2 Drives Migration of Monocytes towards Glioblastoma Cells.

Isocitrate dehydrogenase (IDH)-wildtype glioblastoma (GBM) is a fast growing and highly heterogeneous tumor, often characterized by the presence of glioblastoma stem cells (GSCs). The plasticity of GSCs results in therapy resistance and impairs anti-tumor immune response by influencing immune cells in the tumor microenvironment (TME). Previously, ß-catenin was associated with stemness in GBM as well as with immune escape mechanisms. Here, we investigated the effect of ß-catenin on attracting monocytes towards GBM cells. In addition, we evaluated whether CCL2 is involved in ß-catenin crosstalk between monocytes and tumor cells. Our analysis revealed that shRNA targeting ß-catenin in GBMs reduces monocytes attraction and impacts CCL2 secretion. The addition of recombinant CCL2 restores peripheral blood mononuclear cells (PBMC) migration towards medium (TCM) conditioned by shß-catenin GBM cells. CCL2 knockdown in GBM cells shows similar effects and reduces monocyte migration to a similar extent as ß-catenin knockdown. When investigating the effect of CCL2 on ß-catenin activity, we found that CCL2 modulates components of the Wnt/ß-catenin pathway and alters the clonogenicity of GBM cells. In addition, the pharmacological ß-catenin inhibitor MSAB reduces active ß-catenin, downregulates the expression of associated genes and alters CCL2 secretion. Taken together, we showed that ß-catenin plays an important role in attracting monocytes towards GBM cells in vitro. We hypothesize that the interactions between ß-catenin and CCL2 contribute to maintenance of GSCs via modulating immune cell interaction and promoting GBM growth and recurrence.

Systematic discrimination of the repetitive genome in proximity of ferroptosis genes and a novel prognostic signature correlating with the oncogenic lncRNA CRNDE in multiple myeloma.

Emerging insights into iron-dependent form of regulated cell death ferroptosis in cancer have opened a perspective for its use in cancer therapy. Of interest, a systematic profiling of ferroptosis gene signatures as prognostic factors has gained special attention in several cancers. Herein, we sought to investigate the presence of repetitive genomes in the vicinity of ferroptosis genes that may influence their expression and to establish a prognostic gene signature associated with multiple myeloma (MM). Our analysis showed that genes associated with ferroptosis were enriched with the repetitive genome in their vicinity, with a strong predominance of the SINE family, followed by LINE, of which the most significant discriminant values were SINE/Alu and LINE/L1, respectively. In addition, we examined in detail the performance of these genes as a cancer risk prediction model and specified fourteen ferroptosis-related gene signatures, which identified MM high-risk patients with lower immune/stromal scores with higher tumor purity in their immune microenvironment. Of interest, we also found that lncRNA CRNDE correlated with a risk score and was highly associated with the majority of genes comprising the signature. Taken together, we propose to investigate the molecular impact of the repetitive genome we have highlighted on the local transcriptome of ferroptosis genes in cancer. Furthermore, we revealed a genomic signature/biomarker related to ferroptosis that can be used to predict the risk of survival in MM patients.

Deficiency in flavonoid biosynthesis genes CHS, CHI, and CHIL alters rice flavonoid and lignin profiles.

Lignin is a complex phenylpropanoid polymer deposited in the secondary cell walls of vascular plants. Unlike most gymnosperm and eudicot lignins that are generated via the polymerization of monolignols, grass lignins additionally incorporate the flavonoid tricin as a natural lignin monomer. The biosynthesis and functions of tricin-integrated lignin (tricin-lignin) in grass cell walls and its effects on the utility of grass biomass remain largely unknown. We herein report a comparative analysis of rice (Oryza sativa) mutants deficient in the early flavonoid biosynthetic genes encoding CHALCONE SYNTHASE (CHS), CHALCONE ISOMERASE (CHI), and CHI-LIKE (CHIL), with an emphasis on the analyses of disrupted tricin-lignin formation and the concurrent changes in lignin profiles and cell wall digestibility. All examined CHS-, CHI-, and CHIL-deficient rice mutants were largely depleted of extractable flavones, including tricin, and nearly devoid of tricin-lignin in the cell walls, supporting the crucial roles of CHS and CHI as committed enzymes and CHIL as a noncatalytic enhancer in the conserved biosynthetic pathway leading to flavone and tricin-lignin formation. In-depth cell wall structural analyses further indicated that lignin content and composition, including the monolignol-derived units, were differentially altered in the mutants. However, regardless of the extent of the lignin alterations, cell wall saccharification efficiencies of all tested rice mutants were similar to that of the wild-type controls. Together with earlier studies on other tricin-depleted grass mutant and transgenic plants, our results reflect the complexity in the metabolic consequences of tricin pathway perturbations and the relationships between lignin profiles and cell wall properties.

Thermoacoustic tomography from magnetic nanoparticles by single-pulse magnetic field.

PURPOSE: A mechanism of single-pulse magnetic field (SMF) inducing magnetic nanoparticles (MNPs) to generate the thermoacoustic (TA) wave is proposed, and its feasibility is proved by simulation and experiment. METHODS: According to the principle of dimensional consistency, it is proposed that the internal energy variation of MNPs under the adiabatic condition mainly stems from the accumulation of magnetization energy, which leads to the magnetothermal effect, and then the TA wave is excited by thermal expansion. The analytical model of the forward problem is derived based on the method of space-time separation. The magnetization curve of MNPs is obtained from Langevin theory, and a three-dimension simulation model based on the magnetization curve is established to analyze the generation process of the TA wave. In the Experimental section, a gel phantom with a 0.5 mm gap is prepared with the magnetic fluid injecting into the gap, and the cross-sectional image of the gel phantom is reconstructed by the image fusion algorithm based on B-scan imaging. RESULTS: The simulation analysis shows that the generated TA signal can reflect the boundary information of the MNPs region, and when the MNPs are in the unsaturated magnetized region, the intensity of the TA signal is positively correlated with the concentration of MNPs. The B-scan imaging along the X-axis and Y-axis directions are obtained through the experimental data. After that, the phantom with 0.5 mm gap labeled by MNPs is faithfully reconstructed by combining image morphology processing and image fusion technology based on wavelet transform. CONCLUSIONS: The results show that the TA tomography from MNPs by SMF uses MNPs as a contrast agent to reconstruct the size and shape of the marked phantom with submillimeter resolution, which is expected to reconstruct the image of the tumor labeled by MNPs in the future. However, it is also a certain challenge to use low-concentration MNPs to image in vivo.

Identifying and characterizing lincRNA genomic clusters reveals its cooperative functions in human cancer.

BACKGROUND: Emerging evidence has revealed that some long intergenic non-coding RNAs (lincRNAs) are likely to form clusters on the same chromosome, and lincRNA genomic clusters might play critical roles in the pathophysiological mechanism. However, the comprehensive investigation of lincRNA clustering is rarely studied, particularly the characterization of their functional significance across different cancer types. METHODS: In this study, we firstly constructed a computational method basing a sliding window approach for systematically identifying lincRNA genomic clusters. We then dissected these lincRNA genomic clusters to identify common characteristics in cooperative expression, conservation among divergent species, targeted miRNAs, and CNV frequency. Next, we performed comprehensive analyses in differentially-expressed patterns and overall survival outcomes for patients from The Cancer Genome Atlas (TCGA) and The Genotype-Tissue Expression (GTEx) across multiple cancer types. Finally, we explored the underlying mechanisms of lincRNA genomic clusters by functional enrichment analysis, pathway analysis, and drug-target interaction. RESULTS: We identified lincRNA genomic clusters according to the algorithm. Clustering lincRNAs tended to be co-expressed, highly conserved, targeted by more miRNAs, and with similar deletion and duplication frequency, suggesting that lincRNA genomic clusters may exert their effects by acting in combination. We further systematically explored conserved and cancer-specific lincRNA genomic clusters, indicating they were involved in some important mechanisms of disease occurrence through diverse approaches. Furthermore, lincRNA genomic clusters can serve as biomarkers with potential clinical significance and involve in specific pathological processes in the development of cancer. Moreover, a lincRNA genomic cluster named Cluster127 in DLK1-DIO3 imprinted locus was discovered, which contained MEG3, MEG8, MEG9, MIR381HG, LINC02285, AL132709.5, and AL132709.1. Further analysis indicated that Cluster127 may have the potential for predicting prognosis in cancer and could play their roles by participating in the regulation of PI3K-AKT signaling pathway. CONCLUSIONS: Clarification of the lincRNA genomic clusters specific roles in human cancers could be beneficial for understanding the molecular pathogenesis of different cancer types.

Diallyl Trisulfide, the Antifungal Component of Garlic Essential Oil and the Bioactivity of Its Nanoemulsions Formed by Spontaneous Emulsification.

The aim of this study was to evaluate the chemical compounds of garlic essential oil (EO), and determine the antifungal efficacy of garlic EO and its major components, diallyl trisulfide and its nanoemulsions against wood-rotting fungi, Trametes hirsuta and Laetiporus sulphureus. GC-MS analysis revealed that the major constituents of garlic EO were diallyl trisulfide (39.79%), diallyl disulfide (32.91%), and diallyl sulfide (7.02%). In antifungal activity, the IC50 value of garlic EO against T. hirsuta and L. sulphureus were 137.3 and 44.6 µg/mL, respectively. Results from the antifungal tests demonstrated that the three major constituents were shown to have good antifungal activity, in which, diallyl trisulfide was the most effective against T. hirsuta and L. sulphureus, with the IC50 values of 56.1 and 31.6 µg/mL, respectively. The diallyl trisulfide nanoemulsions showed high antifungal efficacy against the examined wood-rotting fungi, and as the amount of diallyl trisulfide in the lipid phase increases, the antifungal efficacy of the nanoemulsions increases. These results showed that the nanoemulsions and normal emulsion of diallyl trisulfide have potential to develop into a natural wood preservative.

Tricin Biosynthesis and Bioengineering.

Tricin (3',5'-dimethoxyflavone) is a specialized metabolite which not only confers stress tolerance and involves in defense responses in plants but also represents a promising nutraceutical. Tricin-type metabolites are widely present as soluble tricin O-glycosides and tricin-oligolignols in all grass species examined, but only show patchy occurrences in unrelated lineages in dicots. More strikingly, tricin is a lignin monomer in grasses and several other angiosperm species, representing one of the "non-monolignol" lignin monomers identified in nature. The unique biological functions of tricin especially as a lignin monomer have driven the identification and characterization of tricin biosynthetic enzymes in the past decade. This review summarizes the current understanding of tricin biosynthetic pathway in grasses and tricin-accumulating dicots. The characterized and potential enzymes involved in tricin biosynthesis are highlighted along with discussion on the debatable and uncharacterized steps. Finally, current developments of bioengineering on manipulating tricin biosynthesis toward the generation of functional food as well as modifications of lignin for improving biorefinery applications are summarized.

Lnc2Cancer 3.0: an updated resource for experimentally supported lncRNA/circRNA cancer associations and web tools based on RNA-seq and scRNA-seq data.

An updated Lnc2Cancer 3.0 (http://www.bio-bigdata.net/lnc2cancer or http://bio-bigdata.hrbmu.edu.cn/lnc2cancer) database, which includes comprehensive data on experimentally supported long non-coding RNAs (lncRNAs) and circular RNAs (circRNAs) associated with human cancers. In addition, web tools for analyzing lncRNA expression by high-throughput RNA sequencing (RNA-seq) and single-cell RNA-seq (scRNA-seq) are described. Lnc2Cancer 3.0 was updated with several new features, including (i) Increased cancer-associated lncRNA entries over the previous version. The current release includes 9254 lncRNA-cancer associations, with 2659 lncRNAs and 216 cancer subtypes. (ii) Newly adding 1049 experimentally supported circRNA-cancer associations, with 743 circRNAs and 70 cancer subtypes. (iii) Experimentally supported regulatory mechanisms of cancer-related lncRNAs and circRNAs, involving microRNAs, transcription factors (TF), genetic variants, methylation and enhancers were included. (iv) Appending experimentally supported biological functions of cancer-related lncRNAs and circRNAs including cell growth, apoptosis, autophagy, epithelial mesenchymal transformation (EMT), immunity and coding ability. (v) Experimentally supported clinical relevance of cancer-related lncRNAs and circRNAs in metastasis, recurrence, circulation, drug resistance, and prognosis was included. Additionally, two flexible online tools, including RNA-seq and scRNA-seq web tools, were developed to enable fast and customizable analysis and visualization of lncRNAs in cancers. Lnc2Cancer 3.0 is a valuable resource for elucidating the associations between lncRNA, circRNA and cancer.

A Preliminary Simulation Study of Dose-Guided Adaptive Radiotherapy Based on Halcyon MV Cone-Beam CT Images With Retrospective Data From a Phase II Clinical Trial.

Background and purpose: To evaluate the feasibility of dose-guided adaptive radiotherapy (ART) based on deformable image registration (DIR) using fractional megavoltage cone-beam CT (MVCBCT) images from Halcyon system that uses identical beams for treatment and imaging and to retrospectively investigate the influence of anatomic changes on target coverage and organ-at-risk (OAR) sparing across various tumor sites. Materials and Methods: Four hundred twenty-two MVCBCT images from 16 patients (three head and neck, seven thoracic, three abdominal, and three pelvic cases) treated in a phase II clinical trial for Halcyon were selected. DIR between the planning CT and daily MVCBCT image was implemented by Velocity software to create pseudo CT. To investigate the accuracy of dose calculation on pseudo CT, three evaluation patients with rescanned CT and adaptive plans were selected. Dose distribution of adaptive plans calculated on pseudo CT was compared with that calculated on the rescanned planning CT on the three evaluation patients. To investigate the impact of inter-fractional anatomic changes on target dose coverage and dose to OARs of the 16 patients, fractional dose was calculated and accumulated incrementally based on deformable registration between planning CT and daily MVCBCT images. Results: Passing rates using 3 mm/3%/10% threshold local gamma analysis were 93.04, 96.00, and 91.68%, respectively, for the three evaluation patients between the reconstructed dose on pseudo CT (MVCBCT) and rescanned CT, where accumulated dose deviations of over 97% voxels were smaller than 0.5 Gy. Planning target volume (PTV) D95% and D90% (the minimum dose received by at least 95/90% of the volume) of the accumulated dose could be as low as 93.8 and 94.5% of the planned dose, respectively. OAR overdose of various degrees were observed in the 16 patients relative to the planned dose. In most cases, OARs' dose volume histogram (DVH) lines of accumulated and planned dose were very close to each other if not overlapping. Among cases with visible deviations, the differences were bilateral without apparent patterns specific to tumor sites or organs. Conclusion: As a confidence building measure, this simulation study suggested the possibility of ART for Halcyon based on DIR between planning CT and MVCBCT. Preliminary clinical data suggested the benefit of patient-specific dose reconstruction and ART to avoid unacceptable target underdosage and OAR overdosage.