Local anesthetic tetracaine hydrochloride induces pyroptosis via caspase-3/gasdermin E in uveal melanoma.

BACKGROUND: Evasion of pyroptosis is an effective survival strategy employed by cancer cells to evade immune cell attacks and drug-induced cytotoxicity. Exploring potent molecules capable of inducing pyroptosis in cancer cells has significant clinical implications for the control of cancer progression. Unexpectedly, we found that the local anesthetic tetracaine hydrochloride (TTC) induced pyroptosis, specifically in uveal melanoma but not in acral or cutaneous melanoma. METHODS: We investigated the effects of TTC on various melanoma cell lines and performed transcriptome sequencing of TTC-treated uveal melanoma cells. The role of gasdermin E (GSDME), an executive protein responsible for pyroptosis, was explored using CRISPR-Cas13d knockdown, caspase-3 inhibitor treatment, and western blot analysis. Differential gene expression and pathway enrichment analyses were performed. Furthermore, we used tissue microarrays to assess GSDME expression levels in melanoma tissues from different anatomical sites. RESULTS: TTC significantly induced pyroptosis specifically in uveal melanoma cells with high GSDME expression levels. TTC treatment could lead to GSDME cleavage by the caspase-3 in uveal melanoma C918 cells. GSDME knockdown or caspase-3 inhibition suppressed TTC-induced pyroptosis. Transcriptome analysis revealed differentially expressed genes enriched in signaling pathways related to pyroptosis, immunity, and cytokines. CONCLUSIONS: This study showed that the local anesthetic TTC effectively induces pyroptosis in uveal melanoma through the caspase-3/GSDME pathway, highlighting its potential application in immunotherapy. Notably, the use of TTC has potential as an agent for inducing pyroptosis and as an adjuvant anticancer therapy in uveal melanoma.

Complete chloroplast genome and phylogenetic analysis of Amorphophallus paeoniifolius (Araceae).

Amorphophallus paeoniifolius (Dennst.) Nicolson, 1885, often known as elephant foot yam, is a tropical tuber crop that originates from south-east Asia and belongs to the Araceae family. It is known for its high production potential and popularity as a medicinal plant. However, the phylogeny and genes for this species are still unavailable. In this study, the first complete chloroplast genome of A. paeoniifolius was reported and phylogenetic analysis was conducted with Araceae species. The chloroplast genome was 176,258 bp in length with 34.80% overall GC content and includes a large single-copy (LSC) region (93,951 bp), a small single-copy (SSC) region (15,013 bp), and a pair of inverted repeat (IRs) regions (33,647 bp). The chloroplast genome has 130 genes, which include 85 protein-coding genes, 37 tRNA genes, and eight rRNA genes. A maximum-likelihood (ML) phylogenetic analysis indicated that all Amorphophallus species formed a single monophyletic clade with a high bootstrap value and A. paeoniifolius was closely related to A. konjac, A. albus, A. krausei, and A. titanum. The chloroplast genome reported in this study will be useful for further taxonomic and evolutionary studies of Amorphophallus.

Enhanced EPR effects by tumour stromal cell mimicking nanoplatform on invasive pituitary adenoma.

Rapid advances in nanomedicine have enabled potential applications in cancer therapy. The enhanced permeability and retention (EPR) effect is the primary rationale for the passive targeting of nanoparticles in oncology. However, growing evidence indicates that the accumulation of nanomaterials via the EPR effect could be more efficient. Inspired by our clinical observation of the Gap Junction connecpion between folliculostellate cells and pituitary adenoma cells, we designed a novel drug delivery system that targets tumours by coating folliculostellate cell (FS) membranes onto PLGA nanoparticles (NPs). The resulting FSNPs, inheriting membrane proteins from the folliculostellate cell membrane, significantly enhanced the EPR effect compared to nanoparticles without cancer cell membranes. We further demonstrated that mitotane encapsulation improved the therapeutic efficacy of mitotane in both heterotopic and orthotopic pituitary adenoma models. Owing to its significant efficacy, our FS cell membrane-coated nanoplatforms has the potential to be translated into clinical applications for the treatment of invasive pituitary adenoma.

Stress-enhanced cardiac lncRNA Morrbid protects hearts from acute myocardial infarction.

Myeloid RNA regulator of Bim-induced death (Morrbid) is a newly identified leukocyte-specific long noncoding RNA (lncRNA). However, the expression and biological functions of Morrbid in cardiomyocytes and heart disease are currently unclear. This study was meant to determine the role of cardiac Morrbid in acute myocardial infarction (AMI) and to identify the potential cellular and molecular mechanisms involved. We found that both human and mouse cardiomyocytes could express a significant amount of Morrbid and that its expression was increased in cardiomyocytes with hypoxia or oxidative stress as well as in mouse hearts with AMI. Overexpression of Morrbid reduced the myocardial infarct size and cardiac dysfunction, whereas the infarct size and cardiac dysfunction deteriorated in cardiomyocyte-specific Morrbid-KO (Morrbidfl/fl/Myh6-Cre) mice. We identified that Morrbid had a protective effect against hypoxia- or H2O2-induced apoptosis; this was also confirmed in vivo in mouse hearts after AMI. We further discovered that serpine1 was a direct target gene of Morrbid that was involved in the Morrbid-mediated protective effect on cardiomyocytes. In summary, we have found, for the first time to our knowledge, that the cardiac Morrbid is a stress-enhanced lncRNA that protects hearts from AMI via antiapoptosis through its target gene serpine1. Morrbid may be a novel promising therapeutic target for ischemic heart diseases such as AMI.

A critical evaluation of compressed line-scan Raman imaging.

The weak signal strength of Raman imaging leads to long imaging times. To increase the speed of Raman imaging, line scanning and compressed Raman imaging methods have been proposed. Here we combine both line scanning and compressed sensing to further increase the speed. However, the direct combination leads to poor reconstruction results due to the missed coverage of the sample. To avoid this issue, "full-coverage" Compressed Line-scan Raman Imaging (FC-CLRI) is proposed, where line positions are random but constrained to measure each line position of the sample at least once. In proof-of-concept studies of polymer beads and yeast cells, FC-CLRI achieved reasonable image quality while making only 20-40% of the measurements of a fully-sampled line-scan image, achieving 640 µm2 FOV imaging in <2 min with 1.5 mW µm-2 laser power. Furthermore, we critically evaluate the CLRI method through comparison with simple downsampling, and have found that FC-CLRI preserves spatial resolution better while naïve downsampling provides an overall higher image quality for complex samples.

Multifactor dimensionality reduction method identifies novel SNP interactions in the WNT protein interaction networks that are associated with recurrence risk in colorectal cancer.

Background: Interactions among genetic variants are rarely studied but may explain a part of the variability in patient outcomes. Objectives: In this study, we aimed to identify 1 to 3 way interactions among SNPs from five Wnt protein interaction networks that predict the 5-year recurrence risk in a cohort of stage I-III colorectal cancer patients. Methods: 423 patients recruited to the Newfoundland Familial Colorectal Cancer Registry were included. Five Wnt family member proteins (Wnt1, Wnt2, Wnt5a, Wnt5b, and Wnt11) were selected. The BioGRID database was used to identify the proteins interacting with each of these proteins. Genotypes of the SNPs located in the interaction network genes were retrieved from a genome-wide SNP genotype data previously obtained in the patient cohort. The GMDR 0.9 program was utilized to examine 1-, 2-, and 3-SNP interactions using a 5-fold cross validation step. Top GMDR 0.9 models were assessed by permutation testing and, if significant, prognostic associations were verified by multivariable logistic regression models. Results: GMDR 0.9 has identified novel 1, 2, and 3-way SNP interactions associated with 5-year recurrence risk in colorectal cancer. Nine of these interactions were multi loci interactions (2-way or 3-way). Identified interaction models were able to distinguish patients based on their 5-year recurrence-free status in multivariable regression models. The significance of interactions was the highest in the 3-SNP models. Several of the identified SNPs were eQTLs, indicating potential biological roles of the genes they were associated with in colorectal cancer recurrence. Conclusions: We identified novel interacting genetic variants that associate with 5-year recurrence risk in colorectal cancer. A significant portion of the genes identified were previously linked to colorectal cancer pathogenesis or progression. These variants and genes are of interest for future functional and prognostic studies. Our results provide further evidence for the utility of GMDR models in identifying novel prognostic biomarkers and the biological importance of the Wnt pathways in colorectal cancer.

The location of metastatic lymph nodes and the evaluation of lymphadenectomy by near-infrared photoacoustic imaging with iridium complex nanoparticles.

Histopathology evaluation and lymphadenectomy of node-positive patients is the usual procedure in clinical therapy. However, it requires days for the histopathology result analysis, which impedes intraoperative decision-making and immediate treatment. Noninvasive real-time imaging of metastatic lymph nodes can overcome these defects and help medical workers evaluate lymph nodes and make the operation decision more efficiently. Herein we developed iridium(III)-cyanine complex/bovine serum albumin (BSA)-based nanoparticles which are conjugated with folic acid (FA) (IrCy-FA NPs). The synthesized IrCy-FA NPs exhibit good biocompatibility, strong near-infrared absorption, and impressive lymph node accumulation and can serve as a photoacoustic (PA) imaging probe for lymph node imaging. Besides, the lymph nodes enriched with IrCy-FA NPs showing green color are easily visible to the naked eye, suggesting their potential as an intraoperative indicator. The real-time PA imaging with excellent contrast and high spatial resolution can promote efficient and reliable quantitative analysis of lymph nodes in vivo. By employing IrCy-FA NPs as the PA agent for lymph node imaging, we achieve effective pre-operative and post-operative evaluations of metastatic lymph nodes in lymphadenectomy. This study may provide helpful information for PA imaging guided colocalization and evaluation of lymph nodes and facilitate this method towards clinical trials.

Hybrid Principal Component Analysis Denoising Enables Rapid, Label-Free Morpho-Chemical Quantification of Individual Nanoliposomes.

Laser tweezers Raman spectroscopy enables multiplexed, quantitative chemical and morphological analysis of individual bionanoparticles such as drug-loaded nanoliposomes, yet it requires minutes-scale acquisition times per particle, leading to a lack of statistical power in typical small-sized data sets. The long acquisition times present a bottleneck not only in measurement time but also in the analytical throughput, as particle concentration (and thus throughput) must be kept low enough to avoid swarm measurement. The only effective way to improve this situation is to reduce the exposure time, which comes at the expense of increased noise. Here, we present a hybrid principal component analysis (PCA) denoising method, where a small number (∼30 spectra) of high signal-to-noise ratio (SNR) training data construct an effective principal component subspace into which low SNR test data are projected. Simulations and experiments prove the method outperforms traditional denoising methods such as the wavelet transform or traditional PCA. On experimental liposome samples, denoising accelerated data acquisition from 90 to 3 s, with an overall 4.5-fold improvement in particle throughput. The denoised data retained the ability to accurately determine complex morphochemical parameters such as lamellarity of individual nanoliposomes, as confirmed by comparison with cryo-EM imaging. We therefore show that hybrid PCA denoising is an efficient and effective tool for denoising spectral data sets with limited chemical variability and that the RR-NTA technique offers an ideal path for studying the multidimensional heterogeneity of nanoliposomes and other micro/nanoscale bioparticles.

Examining SNP-SNP interactions and risk of clinical outcomes in colorectal cancer using multifactor dimensionality reduction based methods.

Background: SNP interactions may explain the variable outcome risk among colorectal cancer patients. Examining SNP interactions is challenging, especially with large datasets. Multifactor Dimensionality Reduction (MDR)-based programs may address this problem. Objectives: 1) To compare two MDR-based programs for their utility; and 2) to apply these programs to sets of MMP and VEGF-family gene SNPs in order to examine their interactions in relation to colorectal cancer survival outcomes. Methods: This study applied two data reduction methods, Cox-MDR and GMDR 0.9, to study one to three way SNP interactions. Both programs were run using a 5-fold cross validation step and the top models were verified by permutation testing. Prognostic associations of the SNP interactions were verified using multivariable regression methods. Eight datasets, including SNPs from MMP family genes (n = 201) and seven sets of VEGF-family interaction networks (n = 1,517 SNPs) were examined. Results: ∼90 million potential interactions were examined. Analyses in the MMP and VEGF gene family datasets found several novel 1- to 3-way SNP interactions. These interactions were able to distinguish between the patients with different outcome risks (regression p-values 0.03-2.2E-09). The strongest association was detected for a 3-way interaction including CHRM3.rs665159_EPN1.rs6509955_PTGER3.rs1327460 variants. Conclusion: Our work demonstrates the utility of data reduction methods while identifying potential prognostic markers in colorectal cancer.

High-Resolution Low-Power Hyperspectral Line-Scan Imaging of Fast Cellular Dynamics Using Azo-Enhanced Raman Scattering Probes.

Small-molecule Raman probes for cellular imaging have attracted great attention owing to their sharp peaks that are sensitive to environmental changes. The small cross section of molecular Raman scattering limits dynamic cellular Raman imaging to expensive and complex coherent approaches that acquire single-channel images and lose hyperspectral Raman information. We introduce a new method, dynamic azo-enhanced Raman imaging (DAERI), to couple the new class of azo-enhanced Raman probes with a high-speed line-scan Raman imaging system. DAERI achieved high-resolution low-power imaging of fast cellular dynamics resolved at ∼270 nm along the confocal direction, 75 µW/µm2 and 3.5 s/frame. Based on the azo-enhanced Raman probes with characteristic signals 102-104 stronger than classic Raman labels, DAERI was not restricted to the cellular Raman-silent region as in prior work and enabled multiplex visualization of organelle motions and interactions. We anticipate DAERI to be a powerful tool for future studies in biophysics and cell biology.

Storax protected primary cortical neurons from oxygen-glucose deprivation/reoxygenation injury via inhibiting the TLR4/TRAF6/NF-κB signaling pathway.

Storax is a traditional Chinese herb that is widely applied in stroke treatment. However, its neuroprotective effects and mechanisms are yet to be fully elucidated. This study aimed to elucidate the neuroprotective effects and underlying mechanisms of storax on oxygen-glucose deprivation/reoxygenation (OGD/R) in injured cortical neurons. The cortical neurons of Wistar rats were primarily cultured in vitro. TheTUNELmethod and CM-H2DCFDA probe were used to detect cell apoptosis and reactive oxygen species (ROS) expression. Enzyme-linked immunosorbent assay, reverse transcription-polymerase chain reaction, and Western blot were used to detect the expression of inflammatory cytokines and proteins of the TLR4/TRAF6/NF-κB signaling pathway. Immunofluorescence was used to measure NF-κB nuclear translocation. Transfection of TLR4 siRNA was used to detect the potential anti-inflammatory mechanisms of storax. The present results have shown that storax protected primary cortical neurons from OGD/R-induced injury by suppressing ROS generation and cell apoptosis; alleviating HMGB-1, TNF-α, IL-1ß, and ICAM-1 expression; and promoting IL-10 expression. In addition, storax inhibited the activation of TLR4, TRAF6, IκBα, IKKß, and NF-κBp65 caused by OGD/R. It is suggested that storax prevents OGD/R-induced primary cortical neuron injury by inhibiting the TLR4/TRAF6/NF-κB signaling pathway.

A Drop-in, Focus-Extending Phase Mask Simplifies Microscopic and Microfluidic Imaging Systems for Cost-Effective Point-of-Care Diagnostics.

Microscopic imaging and imaging flow cytometry have wide potential in point-of-care assays; however, their narrow depth of focus necessitates precise mechanical or fluidic focus control of a sample in order to acquire high-quality images that can be used for downstream analysis, increasing the cost and complexity of the imaging system. This complexity represents a barrier to miniaturization and translation of point-of-care assays based on microscopic imaging or imaging flow cytometry. To address this challenge, we present a simple drop-in phase mask with a physics-informed, circularly symmetric asphere phase profile that extends the depth of focus by >5-fold while largely preserving the image quality compared to other depth extending methods. We show that such a focus-extended system overcomes manufacturing tolerances in low-cost sample chambers, enlarges the useable field-of-view of low-cost objectives, and permits increased throughput and precision in flow imaging systems without the need for complex flow-focusing. As the image quality is preserved without the need for postacquisition image restoration, our solution is also highly appropriate for on-line applications such as cell sorting.

Traditional Chinese medicine use in the pathophysiological processes of intracerebral hemorrhage and comparison with conventional therapy.

Intracerebral hemorrhage (ICH) refers to hemorrhage caused by non-traumatic vascular rupture in the brain parenchyma, which is characterized by acute onset, severe illness, and high mortality and disability. The influx of blood into the brain tissue after cerebrovascular rupture causes severe brain damage, including primary injury caused by persistent hemorrhage and secondary brain injury (SBI) induced by hematoma. The mechanism of brain injury is complicated and is a significant cause of disability after ICH. Therefore, it is essential to understand the mechanism of brain injury after ICH to develop drugs to prevent and treat ICH. Studies have confirmed that many traditional Chinese medicines (TCM) can reduce brain injury by improving neurotoxicity, inflammation, oxidative stress (OS), blood-brain barrier (BBB), apoptosis, and neurological dysfunction after ICH. Starting from the pathophysiological process of brain injury after ICH, this paper summarizes the mechanisms by which TCM improves cerebral injury after ICH and its comparison with conventional western medicine, so as to provide clues and a reference for the clinical application of TCM in the prevention and treatment of hemorrhagic stroke and further research and development of new drugs.

Super-resolved Raman imaging via galvo-painted structured line illumination.

Traditional line-scan Raman imaging features a rapid imaging speed while preserving complete spectral information, yet has diffraction-limited resolution. Sinusoidally structured line excitation can yield an improvement in the lateral resolution of the Raman image along the line's direction. However, given the need for the line and spectrometer slit to be aligned, the resolution in the perpendicular direction remains diffraction limited. To overcome this, we present here a galvo-modulated structured line imaging system, where a system of three galvos can arbitrarily orient the structured line on the sample plane, while keeping the beam aligned to the spectrometer slit in the detection plane. Thus, a two-fold isotropic improvement in the lateral resolution fold is possible. We demonstrate the feasibility using mixtures of microspheres as chemical and size standards. The results prove an improvement in the lateral resolution of 1.8-fold (limited by line contrast at higher frequencies), while preserving complete spectral information of the sample.

A comprehensive analysis of SNPs and CNVs identifies novel markers associated with disease outcomes in colorectal cancer.

We aimed to examine the associations of a genome-wide set of single nucleotide polymorphisms (SNPs) and 254 copy number variations (CNVs) and/or insertion/deletions (INDELs) with clinical outcomes in colorectal cancer patients (n = 505). We also aimed to investigate whether their associations changed (e.g., appeared, diminished) over time. Multivariable Cox proportional hazards and piece-wise Cox regression models were used to examine the associations. The Cancer Genome Atlas (TCGA) datasets were used for replication purposes and to examine the gene expression differences between tumor and nontumor tissue samples. A common SNP (WBP11-rs7314075) was associated with disease-specific survival with P-value of 3.2 × 10-8 . Association of this region with disease-specific survival was also detected in the TCGA patient cohort. Two expression quantitative trait loci (eQTLs) were identified in this locus that were implicated in the regulation of ERP27 expression. Interestingly, expression levels of ERP27 and WBP11 were significantly different between colorectal tumors and nontumor tissues. Three SNPs predicted the risk of recurrent disease only after 5 years postdiagnosis. Overall, our study identified novel variants, one of which also showed an association in the TCGA dataset, but no CNVs/INDELs, that associated with outcomes in colorectal cancer. Three SNPs were candidate predictors of long-term recurrence/metastasis risk.

Feasibility study of 3D time-reversal reconstruction of proton-induced acoustic signals for dose verification in the head and the liver: A simulation study.

PURPOSE: In vivo range and dose verification based on proton-induced acoustics (protoacoustics) is potentially a useful tool for proton therapy. Built upon our previous study with two-dimensional reconstruction, the time reversal (TR) method was extended to three-dimensional (3D) and evaluated at two treatment sites (head and liver) through simulation, with the emphasis on a number of aspects such as increased spatial coverage, computational workload, and signal interference among slices. METHODS: Two mono-energetic pencil beams were modeled in each site. The k-Wave toolbox was used to investigate the propagation and TR reconstruction of acoustic waves. The performance was quantitatively assessed based on mean square error (MSE) for dose verification and Bragg peak localization error (ΔBP ) for range verification, with regard to five parameters: number of sensors, sampling duration, sampling timestep, spill time, and noise level. RESULTS: The respective impacts of five parameters are examined. Under the optimum setting, the achievable ΔBP can be limited within 1 voxel (voxel size: 3 × 3 × 3 mm3 ) and the achievable MSE can be limited below 0.02, for the head case (56 sensors) and the liver case (204 sensors), respectively. CONCLUSIONS: The feasibility of range and dose verification utilizing the 3D TR method is demonstrated, as the very first step. In spite of several challenges unique to the 3D case (spatial coverage, computational workload, and signal interference among slices, etc.), promising performance is found and can be further improved through optimizing the deployment of sensors. The proposed approach may find potential use in several applications: beam diagnostics, in vivo dosimetry, and treatment monitoring.

Tremella-Like ZnO@Col-I-Decorated Titanium Surfaces with Dual-Light-Defined Broad-Spectrum Antibacterial and Triple Osteogenic Properties.

The growing population of peri-implant diseases (PIDs) has become a public obsession, mainly due to the lack of antibacterial ability and osteogenic promotion of titanium (Ti) implants. Herein, inspired by tremella, we reported zinc oxide (ZnO)@collagen type I (Col-I)-decorated Ti for PIDs treatments. Compared with pure Ti implants, ZnO@Col-I-decorated Ti could be activated by a safe visible yellow light and showed excellent broad-spectrum antibacterial properties. The proliferation and osteogenic gene expression of bone marrow mesenchymal stem cells (BMSCs) indicated that the triple osseointegration of implants was realized through (I) the remarkedly improved surface hydrophilicity of ZnO@Col-I-decorated Ti, (II) the function of Col-I, and (III) the excellent near-infrared (NIR)-induced photothermal performance of ZnO. Collectively, the proposed dual-light-defined ZnO@Col-I coating was a promising implant surface modification system to provide customized treatments for each PID patient.

Technical Note: Machine learning approaches for range and dose verification in proton therapy using proton-induced positron emitters.

PURPOSE/OBJECTIVE(S): Online proton range/dose verification based on measurements of proton-induced positron emitters is a promising strategy for quality assurance in proton therapy. Because of the nonlinear correlation between the dose distribution and the activity distribution of positron emitters in addition to the presence of noise, machine learning approaches were proposed to establish their relationship. MATERIALS/METHODS: Simulations were carried out with a spot-scanning proton system using GATE-8.0 and Geant4-10.3 toolkit with a computed tomography (CT)-based patient phantom. The one-dimensional (1D) distributions of positron emitters and radiation dose were obtained. A feedforward neural network classification model comprising two hidden layers, was developed to estimate whether the range is within a preset threshold. A recurrent neural network (RNN) regression model comprising three layers and ten neurons in each hidden layer was developed to estimate dose distribution. The performance was quantitatively studied in terms of mean squared error (MSE) and mean absolute error (MAE) under different signal-to-noise ratio (SNR) values. RESULTS: The feasibility of proton range and dose verification using the proposed neural network framework was demonstrated. The feedforward NN model achieves high classification accuracy close to 100% for individual classes without bias. The RNN model is able to accurately predict the 1D dose distribution for different energies and irradiation positions. When the SNR of the input activity profiles is above 4, the framework is able to predict with an MAE of ~0.60 mm and an MSE of ~0.066. Moreover, the model demonstrates a good capability of generalization. CONCLUSIONS: The RNN model is found to be effective in identifying the relationship between the distributions of dose and positron emitters. The machine learning-based framework and RNN models may be a useful tool to allow for accurate online range and dose verification based on proton-induced positron emitters.

The long-term survival characteristics of a cohort of colorectal cancer patients and baseline variables associated with survival outcomes with or without time-varying effects.

BACKGROUND: Colorectal cancer is the third most common cancer in the world. In this study, we assessed the long-term survival characteristics and prognostic associations and potential time-varying effects of clinico-demographic variables and two molecular markers (microsatellite instability (MSI) and BRAF Val600Glu mutation) in a population-based patient cohort followed up to ~ 19 years. METHODS: The patient cohort included 738 incident cases diagnosed between 1999 and 2003. Cox models were used to analyze the association between the variables and a set of survival outcome measures (overall survival (OS), disease-specific survival (DSS), recurrence-free survival (RFS), metastasis-free survival (MFS), recurrence/metastasis-free survival (RMFS), and event-free survival (EFS)). Cox proportional hazard (PH) assumption was tested for all variables, and Cox models with time-varying effects were used if any departure from the PH assumption was detected. RESULTS: During the follow-up, ~ 61% patients died from any cause, ~ 26% died from colorectal cancer, and ~ 10% and ~ 20% experienced recurrences and distant metastases, respectively. Stage IV disease and post-diagnostic recurrence or metastasis were strongly linked to risk of death from colorectal cancer. If a patient had survived the first 6 years without any disease-related event (i.e., recurrence, metastasis, or death from colorectal cancer), their risks became very minimal after this time period. Distinct sets of markers were associated with different outcome measures. In some cases, the effects by variables were constant throughout the follow-up. For example, MSI-high tumor phenotype and older age at diagnosis predicted longer MFS times consistently over the follow-up. However, in some other cases, the effects of the variables varied with time. For example, adjuvant radiotherapy treatment was associated with increased risk of metastasis in patients who received this treatment after 5.5 years post-diagnosis, but not before that. CONCLUSIONS: This study describes the long-term survival characteristics of a prospective cohort of colorectal cancer patients, relationships between baseline variables and a detailed set of patient outcomes over a long time, and time-varying effects of a group of variables. The results presented advance our understanding of the long-term prognostic characteristics in colorectal cancer and are expected to inspire future studies and clinical care strategies.

Simulation studies of time reversal-based protoacoustic reconstruction for range and dose verification in proton therapy.

PURPOSE: In vivo range verification in proton therapy is a critical step to help minimize range and dose uncertainty. We propose to employ a time reversal (TR)-based approach using proton-induced acoustics (protoacoustics) to reconstruct pressure/dose distribution in heterogeneous tissues. METHODS: The dose distribution of mono-energetic proton pencil beam in a CT-based patient phantom was calculated by Monte Carlo simulation. K-wave toolbox was used to investigate protoacoustic pressurization, propagation and reconstruction in 2D. To address the tissue heterogeneity effect, a number of physical parameters, including mass density (ρ), speed of sound (c), volumetric thermal expansion coefficient (αV ), isobaric specific heat capacity (Cp ) and attenuation power law prefactor (α0 ), were empirically converted from CT number. The performance was evaluated using two figures of merit: mean square error (MSE) of pressure profiles and Bragg peak localization error (ΔBP ). The impact of six parameters of the TR inversion was examined, including number of sensors, sampling duration, sampling timestep, spill time, noise level and number of iterations. RESULTS: The quantitative accuracy of TR reconstruction and its dependency on the selected parameters is presented. Under optimum conditions, the positioning accuracy of the Bragg peak can be controlled below 1 mm. For instance, MSE is 0.0123 and ΔBP is 0.59 mm under the following conditions (32 sensors, sampling duration: 600 µs, sampling timestep: 40 ns, spill time: 1 µs, no noise). CONCLUSIONS: The feasibility of TR-based protoacoustic reconstruction in 2D for proton range verification was first demonstrated. The approach is not only applicable to pencil beam, but also has potential to be extended to passive scattering systems.