Radiomic biomarkers of locoregional recurrence: prognostic insights from oral cavity squamous cell carcinoma preoperative CT scans.

Introduction: This study aimed to identify CT-based imaging biomarkers for locoregional recurrence (LR) in Oral Cavity Squamous Cell Carcinoma (OSCC) patients. Methods: Computed tomography scans were collected from 78 patients with OSCC who underwent surgical treatment at a single medical center. We extracted 1,092 radiomic features from gross tumor volume in each patient's pre-treatment CT. Clinical characteristics were also obtained, including race, sex, age, tobacco and alcohol use, tumor staging, and treatment modality. A feature selection algorithm was used to eliminate the most redundant features, followed by a selection of the best subset of the Logistic regression model (LRM). The best LRM model was determined based on the best prediction accuracy in terms of the area under Receiver operating characteristic curve. Finally, significant radiomic features in the final LRM model were identified as imaging biomarkers. Results and discussion: Two radiomics biomarkers, Large Dependence Emphasis (LDE) of the Gray Level Dependence Matrix (GLDM) and Long Run Emphasis (LRE) of the Gray Level Run Length Matrix (GLRLM) of the 3D Laplacian of Gaussian (LoG σ=3), have demonstrated the capability to preoperatively distinguish patients with and without LR, exhibiting exceptional testing specificity (1.00) and sensitivity (0.82). The group with LRE > 2.99 showed a 3-year recurrence-free survival rate of 0.81, in contrast to 0.49 for the group with LRE ≤ 2.99. Similarly, the group with LDE > 120 showed a rate of 0.82, compared to 0.49 for the group with LDE ≤ 120. These biomarkers broaden our understanding of using radiomics to predict OSCC progression, enabling personalized treatment plans to enhance patient survival.

Generalized Multifunctional Coating Strategies Based on Polyphenol-Amine-Inspired Chemistry and Layer-by-Layer Deposition for Blood Contact Catheters.

Blood-contacting catheters play a pivotal role in contemporary medical treatments, particularly in the management of cardiovascular diseases. However, these catheters exhibit inappropriate wettability and lack antimicrobial characteristics, which often lead to catheter-related infections and thrombosis. Therefore, there is an urgent need for blood contact catheters with antimicrobial and anticoagulant properties. In this study, we employed tannic acid (TA) and 3-aminopropyltriethoxysilane (APTES) to create a stable hydrophilic coating under mild conditions. Heparin (Hep) and poly(lysine) (PL) were then modified on the TA-APTES coating surface using the layer-by-layer (LBL) technique to create a superhydrophilic TA/APTES/(LBL)4 coating on silicone rubber (SR) catheters. Leveraging the superhydrophilic nature of this coating, it can be effectively applied to blood-contacting catheters to impart antibacterial, antiprotein adsorption, and anticoagulant properties. Due to Hep's anticoagulant attributes, the activated partial thromboplastin time and thrombin time tests conducted on SR/TA-APTES/(LBL)4 catheters revealed remarkable extensions of 276 and 103%, respectively, when compared to uncoated commercial SR catheters. Furthermore, the synergistic interaction between PL and TA serves to enhance the resistance of SR/TA-APTES/(LBL)4 catheters against bacterial adherence, reducing it by up to 99.9% compared to uncoated commercial SR catheters. Remarkably, the SR/TA-APTES/(LBL)4 catheter exhibits good biocompatibility with human umbilical vein endothelial cells in culture, positioning it as a promising solution to address the current challenges associated with blood-contact catheters.

Study on Influence of Rare Earth Ce on Micro and Macro Properties of U75V Steel.

Non-metallic inclusions in steel have great influence on the continuity of the steel matrix and the mechanical properties of steel. The precipitation sequence of Ce inclusions in molten steel is predicted by thermodynamic calculations. The results show that Ce content will affect the precipitation sequence of rare earth inclusions in molten steel, and the formation of CeO2, Ce2O3 and CeAlO3 will be inhibited with the increase in Ce content. Our laboratory smelted the test steel without rare earth additive and the test steel with rare earth Ce additive (0.0008%, 0.0013%, 0.0032%, 0.0042%). It was found that the MnS inclusions and inclusions containing Al, Ca, Mg and Si oxides or sulfides in the steel after rare earth addition were modified into complex inclusions containing CeAlO3 and Ce2O2S. The size of inclusion in steel was reduced and the aspect ratio of inclusion was improved. The addition of Ce also improved the grain size of U75V steel and significantly refined the pearlite lamellar spacing. After mechanical property testing of the test steel, it was found that when Ce is increased within 0.0042%, the tensile and impact properties of U75V steel are also improved.

Crosstalk of disulfidptosis-related subtypes identifying a prognostic signature to improve prognosis and immunotherapy responses of clear cell renal cell carcinoma patients.

BACKGROUND: Disulfidptosis is a novel form of programmed cell death induced by high SLC7A11 expression under glucose starvation conditions, unlike other known forms of cell death. However, the roles of disulfidptosis in cancers have yet to be comprehensively well-studied, particularly in ccRCC. METHODS: The expression profiles and somatic mutation of DGs from the TCGA database were investigated. Two DGs clusters were identified by unsupervised consensus clustering analysis, and a disulfidptosis-related prognostic signature (DR score) was constructed. Furthermore, the predictive capacity of the DR score in prognosis was validated by several clinical cohorts. We also developed a nomogram based on the DR score and clinical features. Then, we investigated the differences in the clinicopathological information, TMB, tumor immune landscapes, and biological characteristics between the high- and low-risk groups. We evaluated whether the DR score is a robust tool for predicting immunotherapy response by the TIDE algorithm, immune checkpoint genes, submap analysis, and CheckMate immunotherapy cohort. RESULTS: We identified two DGs clusters with significant differences in prognosis, tumor immune landscapes, and clinical features. The DR score has been demonstrated as an independent risk factor by several clinical cohorts. The high-risk group patients had a more complicated tumor immune microenvironment and suffered from more tumor immune evasion in immunotherapy. Moreover, patients in the low-risk group had better prognosis and response to immunotherapy, particularly in anti-PD1 and anti-CTLA-4 inhibitors, which were verified in the CheckMate immunotherapy cohort. CONCLUSION: The DR score can accurately predict the prognosis and immunotherapy response and assist clinicians in providing a personalized treatment regime for ccRCC patients.

Hybrid-supervised deep learning for domain transfer 3D protoacoustic image reconstruction.

Objective. Protoacoustic imaging showed great promise in providing real-time 3D dose verification of proton therapy. However, the limited acquisition angle in protoacoustic imaging induces severe artifacts, which impairs its accuracy for dose verification. In this study, we developed a hybrid-supervised deep learning method for protoacoustic imaging to address the limited view issue.Approach. We proposed a Recon-Enhance two-stage deep learning method. In the Recon-stage, a transformer-based network was developed to reconstruct initial pressure maps from raw acoustic signals. The network is trained in a hybrid-supervised approach, where it is first trained using supervision by the iteratively reconstructed pressure map and then fine-tuned using transfer learning and self-supervision based on the data fidelity constraint. In the enhance-stage, a 3D U-net is applied to further enhance the image quality with supervision from the ground truth pressure map. The final protoacoustic images are then converted to dose for proton verification.Main results. The results evaluated on a dataset of 126 prostate cancer patients achieved an average root mean squared errors (RMSE) of 0.0292, and an average structural similarity index measure (SSIM) of 0.9618, out-performing related start-of-the-art methods. Qualitative results also demonstrated that our approach addressed the limit-view issue with more details reconstructed. Dose verification achieved an average RMSE of 0.018, and an average SSIM of 0.9891. Gamma index evaluation demonstrated a high agreement (94.7% and 95.7% for 1%/3 mm and 1%/5 mm) between the predicted and the ground truth dose maps. Notably, the processing time was reduced to 6 s, demonstrating its feasibility for online 3D dose verification for prostate proton therapy.Significance. Our study achieved start-of-the-art performance in the challenging task of direct reconstruction from radiofrequency signals, demonstrating the great promise of PA imaging as a highly efficient and accurate tool forinvivo3D proton dose verification to minimize the range uncertainties of proton therapy to improve its precision and outcomes.

Radiomic Biomarkers of Locoregional Recurrence: Prognostic Insights from Oral Cavity Squamous Cell Carcinoma preoperative CT scans.

This study aimed to identify CT-based imaging biomarkers for locoregional recurrence (LR) in Oral Cavity Squamous Cell Carcinoma (OSCC) patients. Our study involved a retrospective review of 78 patients with OSCC who underwent surgical treatment at a single medical center. An approach involving feature selection and statistical model diagnostics was utilized to identify biomarkers. Two radiomics biomarkers, Large Dependence Emphasis (LDE) of the Gray Level Dependence Matrix (GLDM) and Long Run Emphasis (LRE) of the Gray Level Run Length Matrix (GLRLM) of the 3D Laplacian of Gaussian (LoG σ = 3), have demonstrated the capability to preoperatively distinguish patients with and without LR, exhibiting exceptional testing specificity (1.00) and sensitivity (0.82). The group with LRE > 2.99 showed a 3-year recurrence-free survival rate of 0.81, in contrast to 0.49 for the group with LRE ≤ 2.99. Similarly, the group with LDE > 120 showed a rate of 0.82, compared to 0.49 for the group with LDE ≤ 120. These biomarkers broaden our understanding of using radiomics to predict OSCC progression, enabling personalized treatment plans to enhance patient survival.

Seamless Integration of Rapid Separation and Ultrasensitive Detection for Complex Biological Samples Using Multistage Annular Functionalized Carbon Nanotube Arrays.

Efficient separation, enrichment, and detection of bacteria in diverse media are pivotal for identifying bacterial diseases and their transmission pathways. However, conventional bacterial detection methods that split the separation and detection steps are plagued by prolonged processing times. Herein, a multistage annular functionalized carbon nanotube array device designed for the seamless integration of complex biological sample separation and multimarker detection is introduced. This device resorts to the supersmooth fluidity of the liquid sample in the carbon nanotubes interstice through rotation assistance, achieving the ability to quickly separate impurities and capture biomarkers (1 mL sample cost time of 2.5 s). Fluid dynamics simulations show that the reduction of near-surface hydrodynamic resistance drives the capture of bacteria and related biomarkers on the functionalized surface of carbon nanotube in sufficient time. When further assembled as an even detection device, it exhibited fast detection (<30 min), robust linear correlation (101 -107 colony-forming units [CFU] mL-1 , R2 = 0.997), ultrasensitivity (limit of detection = 1.7 CFU mL-1 ), and multitarget detection (Staphylococcus aureus, extracellular vesicles, and enterotoxin proteins). Collectively, the material and system offer an expanded platform for real-time diagnostics, enabling integrated rapid separation and detection of various disease biomarkers.

A case report of abdominal metastatic dermatofibrosarcoma protuberans misdiagnosed as gastrointestinal stromal tumor.

Dermatofibrosarcoma protuberans (DFSP) is a low-grade malignant soft-tissue tumor that originates from the skin. It has a slow onset in the early stages, non-specific clinical symptoms, low specificity, and can easily be overlooked, missed, or misdiagnosed by clinicians and pathologists. In addition, DFSP is prone to recurrence after local surgical treatment; however, distant metastasis, especially abdominal metastasis, is rare, which is also a challenge for the accurate diagnosis of DFSP when it progresses distantly. Now a case of abdominal metastasis of DFSP is reported. The patient has been treated with imatinib for ten years, and the lesion has shrunk, but because the patient has been receiving imatinib treatment, his abdominal lesion was once misdiagnosed as gastrointestinal stromal tumor. Therefore, we report on this case to enhance the understanding of the diagnosis and treatment of DFSP, and to provide reference for the pathological diagnosis and precise treatment of such patients.

The study of DIEA three dimensional reconstruction technique based on CTA in preoperative perforator selection.

Preoperative selection of perforator is one of the key steps for successful surgery. The purpose of this study is to simulate the selection process of the perforator of the flap using the 3D models of the deep inferior epigastric artery (DIEA). A retrospective study was performed of women who underwent deep inferior epigastric perforator flap breast reconstruction from January 2011 to July 2021. Construct 3D models of the DIEA using computerized tomography angiography images, and then computational fluid dynamics simulations were performed. Correlation and regression analyses were used to analyze the geometric and hemodynamic parameters. Statistical analysis suggested that the outlet flow was positively correlated with the inlet area (r = 0.338, p = 0.000), outlet area (r = 0.840, p = 0.000), the average radius of the perforator (r = 0.592, p = 0.000), and negatively correlated with the length of perforator(r = -0.210, p = 0.024). The results of linear regression analysis showed that the outlet area (p = 0.000), the average radius (p = 0.000), and the length (p = 0.044) of the perforator were the influencing factors on outlet flow. In multiple perforators analysis, there was a significant difference in the total outlet flow among single perforator, double perforators, and triple perforators (p = 0.002). The successful implementation of this experiment provides a new approach for the selection of dominant perforators in the future.

Circular RNA AGAP1 Stimulates Immune Escape and Distant Metastasis in Renal Cell Carcinoma.

Clear cell renal cell carcinoma (ccRCC) is the most representative subtype of renal cancer, with a highly aggressive phenotype and extremely poor prognosis. Immune escape is one of the main reasons for ccRCC growth and metastasis, in which circular RNAs (circRNAs) play critical roles. Therefore, this research studied circAGAP1-associated mechanisms in immune escape and distant metastasis in ccRCC. circAGAP1/miR-216a-3p/MKNK2 was overexpressed or down-regulated by cell transfection. EdU assay, colony formation assay, scratch assay, Transwell assay, immunoblotting, and flow cytometry were used to evaluate cell proliferation, migration, invasion, EMT, and immune escape, respectively. Dual-luciferase reporting assay and RIP assay were used to evaluate the targeting relationship between circAGAP1/miR-216a-3p/MKNK2. Xenotransplantation in nude mice was used to evaluate the growth of ccRCC tumors in vivo. Here, circAGAP1 high expression was positively correlated with higher histological grade and distant metastasis and was a prognostic indicator for ccRCC. Depleting circAGAP1 effectively hampered the proliferative, invasive, and migratory capacities, EMT, and immune escape of ccRCC cells. Correspondingly, silencing circAGAP1 delayed tumor growth, distant metastasis, and immune escape in vivo. Mechanistically, circAGAP1 sponged the tumor suppressor miR-216a-3p, thereby preventing miR-216a-3p from inhibiting MAPK2. Collectively, our findings demonstrate that circAGAP1 exerts a tumor suppressor function through miR-216a-3p/MKNK2 during the immune escape and distant metastasis in ccRCC, and suggest that circAGAP1 may be a novel prognostic marker and therapeutic target for ccRCC.

Artificial Neural Network Analysis of Determinants of Tacrolimus Pharmacokinetics in Liver Transplant Recipients.

BACKGROUND: The efficacy and toxicity of tacrolimus are closely related to its trough blood concentrations. Identifying the influencing factors of pharmacokinetics of tacrolimus in the early postoperative period is conducive to the optimization of the individualized tacrolimus administration protocol and to help liver transplant (LT) recipients achieve the target blood concentrations. OBJECTIVE: This study aimed to develop an artificial neural network (ANN) for predicting the blood concentration of tacrolimus soon after liver transplantation and for identifying determinants of the concentration based on Shapley additive explanation (SHAP). METHODS: In this retrospective study, we enrolled 31 recipients who were first treated with liver transplantation from the Department of Liver Transplantation and Hepatic Surgery, the First Affiliated Hospital of Shandong First Medical University (Shandong Provincial Qianfoshan Hospital) from November 2020 to May 2021. The basic information, biochemical indexes, use of concomitant drugs, and genetic factors of organ donors and recipients were used for the ANN model inputs, and the output was the steady-state trough concentration (C0) of tacrolimus after oral administration in LT recipients. The ANN model was established to predict C0 of tacrolimus, SHAP was applied to the trained model, and the SHAP value of each input was calculated to analyze quantitatively the influencing factors for the output C0. RESULTS: A back-propagation ANN model with 3 hidden layers was established using deep learning. The mean prediction error was 0.27 ± 0.75 ng/mL; mean absolute error, 0.60 ± 0.52 ng/mL; correlation coefficient between predicted and actual C0 values, 0.9677; and absolute prediction error of all blood concentrations obtained by the ANN model, ≤3.0 ng/mL. The results indicated that the following factors had the most significant effect on C0: age, daily drug dose, genotype at CYP3A5 polymorphism rs776746 in both recipient and donor, and concomitant use of caspofungin. The predicted C0 value of tacrolimus in LT recipients increased in a dose-dependent manner when the daily dose exceeded 3 mg, whereas it decreased with age when LT recipients were older than 48 years. The predicted C0 was higher when recipients and donors had the genotype CYP3A5*3*3 than when they had the genotype CYP3A5*1. The predicted C0 value also increased with the use of caspofungin or Wuzhi capsule. CONCLUSION AND RELEVANCE: The established ANN model can be used to predict the C0 value of tacrolimus in LT recipients with high accuracy and good predictive ability, serving as a reference for personalized treatment in the early stage after liver transplantation.

Proteomic Characterization Identifies Clinically Relevant Subgroups of Gastrointestinal Stromal Tumors.

BACKGROUND & AIMS: Gastrointestinal stromal tumor (GIST) is the most common mesenchymal tumor of the gastrointestinal tract, and it has high metastatic and recurrence rates. We aimed to characterize the proteomic features of GIST to understand biological processes and treatment vulnerabilities. METHODS: Quantitative proteomics and phosphoproteomics analyses were performed on 193 patients with GIST to reveal the biological characteristics of GIST. Data-driven hypotheses were tested by performing functional experiments using both GIST cell lines and xenograft mouse models. RESULTS: Proteomic analysis revealed differences in the molecular features of GISTs from different locations or with different histological grades. MAPK7 was identified and functionally proved to be associated with tumor cell proliferation in GIST. Integrative analysis revealed that increased SQSTM1 expression inhibited the patient response to imatinib mesylate. Proteomics subtyping identified 4 clusters of tumors with different clinical and molecular attributes. Functional experiments confirmed the role of SRSF3 in promoting tumor cell proliferation and leading to poor prognosis. CONCLUSIONS: Our study provides a valuable data resource and highlights potential therapeutic approaches for GIST.

Identification of CT-based non-invasive radiomic biomarkers for overall survival prediction in oral cavity squamous cell carcinoma.

This study addresses the limited non-invasive tools for Oral Cavity Squamous Cell Carcinoma (OSCC) survival prediction by identifying Computed Tomography (CT)-based biomarkers to improve prognosis prediction. A retrospective analysis was conducted on data from 149 OSCC patients, including CT radiomics and clinical information. An ensemble approach involving correlation analysis, score screening, and the Sparse-L1 algorithm was used to select functional features, which were then used to build Cox Proportional Hazards models (CPH). Our CPH achieved a 0.70 concordance index in testing. The model identified two CT-based radiomics features, Gradient-Neighboring-Gray-Tone-Difference-Matrix-Strength (GNS) and normalized-Wavelet-LLL-Gray-Level-Dependence-Matrix-Large-Dependence-High-Gray-Level-Emphasis (HLE), as well as stage and alcohol usage, as survival biomarkers. The GNS group with values above 14 showed a hazard ratio of 0.12 and a 3-year survival rate of about 90%. Conversely, the GNS group with values less than or equal to 14 had a 49% survival rate. For normalized HLE, the high-end group (HLE > - 0.415) had a hazard ratio of 2.41, resulting in a 3-year survival rate of 70%, while the low-end group (HLE ≤ - 0.415) had a 36% survival rate. These findings contribute to our knowledge of how radiomics can be used to predict the outcome so that treatment plans can be tailored for patients people with OSCC to improve their survival.

Optimization of Three Extraction Methods and Their Effect on the Structure and Antioxidant Activity of Polysaccharides in Dendrobium huoshanense.

Dendrobium huoshanense is a famous edible and medicinal herb, and polysaccharides are the main bioactive component in it. In this study, response surface methodology (RSM) combined with a Box-Behnken design (BBD) was used to optimize the enzyme-assisted extraction (EAE), ultrasound-microwave-assisted extraction (UMAE), and hot water extraction (HWE) conditions and obtain the polysaccharides named DHP-E, DHP-UM, and DHP-H. The effects of different extraction methods on the physicochemical properties, structure characteristics, and bioactivity of polysaccharides were compared. The differential thermogravimetric curves indicated that DHP-E showed a broader temperature range during thermal degradation compared with DHP-UM and DHP-H. The SEM results showed that DHP-E displayed an irregular granular structure, but DHP-UM and DHP-H were sponge-like. The results of absolute molecular weight indicated that polysaccharides with higher molecular weight detected in DHP-H and DHP-UM did not appear in DHP-E due to enzymatic degradation. The monosaccharide composition showed that DHPs were all composed of Man, Glc, and Gal but with different proportions. Finally, the glycosidic bond types, which have a significant effect on bioactivity, were decoded with methylation analysis. The results showed that DHPs contained four glycosidic bond types, including Glcp-(1→, →4)-Manp-(1→, →4)-Glcp-(1→, and →4,6)-Manp-(1→ with different ratios. Furthermore, DHP-E exhibited better DPPH and ABTS radical scavenging activities. These findings could provide scientific foundations for selecting appropriate extraction methods to obtain desired bioactivities for applications in the pharmaceutical and functional food industries.

Photodynamic therapy augments oxaliplatin-induced immunogenic cell death in colorectal cancer.

Colorectal cancer is one of the most frequently diagnosed cancers. Immunotherapy has been proven to be a potential treatment option for colorectal cancer. Colorectal cancer maintains immune escape by expressing low immunogenicity and following the tolerogenic cell death pathway. There is also emerging evidence that oxaliplatin and photodynamic therapy (PDT) can promote anti-tumor immunity. However, the effect of PDT combined with oxaliplatin on colorectal cancer remains elusive. Here, we analyzed the viability of HCT116 and DLD-1 cell lines after treatment with the combination of PDT and oxaliplatin. We found that the viability decreased significantly after the combination treatment. Meanwhile, we also detected that sinoporphyrin sodium (DVDMS)-derived PDT could amplify oxaliplatin-induced immunogenic cell death (ICD) in different colorectal cancer cell lines. More importantly, the combination of DVDMS-derived PDT and oxaliplatin presented strong immunogenic potential in immunocompetent BALB/c mice in the vaccination assay. Taken together, our data demonstrated that the combination of DVDMS-derived PDT and oxaliplatin is a potential novel therapy for colorectal cancer.

Identification of subclusters and prognostic genes based on glycolysis/gluconeogenesis in hepatocellular carcinoma.

Background: This study aimed to examine glycolysis/gluconeogenesis-related genes in hepatocellular carcinoma (HCC) and evaluate their potential roles in HCC progression and immunotherapy response. Methods: Data analyzed in this study were collected from GSE14520, GSE76427, GSE174570, The Cancer Genome Atlas (TCGA), PXD006512, and GSE149614 datasets, metabolic pathways were collected from MSigDB database. Differentially expressed genes (DEGs) were identified between HCC and controls. Differentially expressed glycolysis/gluconeogenesis-related genes (candidate genes) were obtained and consensus clustering was performed based on the expression of candidate genes. Bioinformatics analysis was used to evaluate candidate genes and screen prognostic genes. Finally, the key results were tested in HCC patients. Results: Thirteen differentially expressed glycolysis/gluconeogenesis-related genes were validated in additional datasets. Consensus clustering analysis identified two distinct patient clusters (C1 and C2) with different prognoses and immune microenvironments. Immune score and tumor purity were significantly higher in C1 than in C2, and CD4+ memory activated T cell, Tfh, Tregs, and macrophage M0 were higher infiltrated in HCC and C1 group. The study also identified five intersecting DEGs from candidate genes in TCGA, GSE14520, and GSE141198 as prognostic genes, which had a protective role in HCC patient prognosis. Compared with the control group, the prognostic genes all showed decreased expression in HCC patients in RT-qPCR and Western blot analyses. Flow cytometry verified the abnormal infiltration level of immune cells in HCC patients. Conclusion: Results showed that glycolysis/gluconeogenesis-related genes were associated with patient prognosis, immune microenvironment, and response to immunotherapy in HCC. It suggests that the model based on five prognostic genes may valuable for predicting the prognosis and immunotherapy response of HCC patients.

Radiation-induced acoustic signal denoising using a supervised deep learning framework for imaging and therapy monitoring.

Radiation-induced acoustic (RA) imaging is a promising technique for visualizing the invisible radiation energy deposition in tissues, enabling new imaging modalities and real-time therapy monitoring. However, RA imaging signal often suffers from poor signal-to-noise ratios (SNRs), thus requiring measuring hundreds or even thousands of frames for averaging to achieve satisfactory quality. This repetitive measurement increases ionizing radiation dose and degrades the temporal resolution of RA imaging, limiting its clinical utility. In this study, we developed a general deep inception convolutional neural network (GDI-CNN) to denoise RA signals to substantially reduce the number of frames needed for averaging. The network employs convolutions with multiple dilations in each inception block, allowing it to encode and decode signal features with varying temporal characteristics. This design generalizes GDI-CNN to denoise acoustic signals resulting from different radiation sources. The performance of the proposed method was evaluated using experimental data of x-ray-induced acoustic, protoacoustic, and electroacoustic signals both qualitatively and quantitatively. Results demonstrated the effectiveness of GDI-CNN: it achieved x-ray-induced acoustic image quality comparable to 750-frame-averaged results using only 10-frame-averaged measurements, reducing the imaging dose of x-ray-acoustic computed tomography (XACT) by 98.7%; it realized proton range accuracy parallel to 1500-frame-averaged results using only 20-frame-averaged measurements, improving the range verification frequency in proton therapy from 0.5 to 37.5 Hz; it reached electroacoustic image quality comparable to 750-frame-averaged results using only a single frame signal, increasing the electric field monitoring frequency from 1 fps to 1k fps. Compared to lowpass filter-based denoising, the proposed method demonstrated considerably lower mean-squared-errors, higher peak-SNR, and higher structural similarities with respect to the corresponding high-frame-averaged measurements. The proposed deep learning-based denoising framework is a generalized method for few-frame-averaged acoustic signal denoising, which significantly improves the RA imaging's clinical utilities for low-dose imaging and real-time therapy monitoring.

Arterial Resection for Pancreatic Cancer: Feasibility and Current Standing in a High-Volume Center.

Background: Arterial resection (AR) during pancreatectomy for curative R0 resection of pancreatic ductal adenocarcinoma (PDAC) remains a controversial procedure with high morbidity. Objective: To investigate the feasibility and oncological outcomes of pancreatectomy combined with AR at a high-volume center for pancreatic surgery. Methods: We retrospectively analyzed our experience in PDAC patients, who underwent pancreatic resection with AR and/or venous resection (VR) between 2007 and 2021. Results: In total 259 PDAC patients with borderline resectable (n = 138) or locally advanced (n = 121) PDAC underwent vascular resection during tumor resection. From these, 23 patients had AR (n = 4 due to intraoperative injury, n = 19 due to suspected arterial infiltration). However, 12 out of 23 patients (52.2%) underwent simultaneous VR including 1 case with intraoperative arterial injury. In comparison, 11 patients (47.8%) underwent AR only including 3 intraoperative arterial injury patients. Although the operation time and bleeding rate of patients with AR were respectively longer and higher than in VR, no significant difference was detected in postoperative complications between VR and AR (P = 0.11). The final histopathological findings of PDAC patients were similar, including M stage, regional lymph node metastases, and R0 margin resection. The mortality of the entire cohort was 6.2% (16/259), with a tendency to increase mortality in the AR cohort, yet without statistical significance (VR: 5% vs AR: 21.1%; P = 0.05). Although 19 (82.6%) patients had PDAC in the final histopathology, only 6 were confirmed to have infiltrated arteria. The microscopic distribution of PDAC in these infiltrated arterial walls on hematoxylin-eosin staining was classified into 3 patterns. Strikingly, the perivascular nerves frequently exhibited perineural invasion. Conclusions: AR can be performed in high-volume centers for pancreatic surgery with an acceptable morbidity, which is comparable to that of VR. However, the likelihood of arterial infiltration seems to be rather overestimated, and as such, AR might be avoidable or replaced by less invasive techniques such as divestment during PDAC surgery.

c-MYC/METTL3/LINC01006 positive feedback loop promotes migration, invasion and proliferation of non-small cell lung cancer.

BACKGROUND: This study aims to clarify the N6-methyladenosine (m6A) modification of LINC01006, which is involved in migration, invasion and proliferation of non-small cell lung cancer (NSCLC). MATERIALS AND METHODS: LINC01006 and METTL3 expressions were analyzed in TCGA-LUAD cohort. Colony formation assay, wound-healing assay and transwell assay were performed to evaluate the ability of colony formation, migration and invasion. Q-PCR and western blot analysis determined gene expressions. M6A-RNA immunoprecipitation and m6A quantification assay were used to evaluate m6A modification. qChIP assay was used to validate transcriptional target. Luciferase assay validated the miRNA targets and transcriptional targets. In-situ xenograft model were included to evaluate tumor proliferation in vivo. RESULTS: LINC01006 and METTL3 expressions were elevated in NSCLC cells and tissues. LINC01006 promoted the migration and invasion of NSCLC via epithelial - mesenchymal transition (EMT). The expression of LINC01006 was positively correlated to the expression of METTL3. METTL3 promoted tumor formation and proliferation in the in-situ xenograft model of NSCLC. The expression of LINC01006 was increased by METTL3 via m6A modification. c-MYC directly induced METTL3. Both c-MYC and LINC01006 were commonly targeted by miR-34a/b/c and miR-2682, and thereby c-MYC/METTL3/LINC01006 formed a positive feedback loop through miRNA targets in NSCLC. CONCLUSIONS: LINC01006 is an oncogenic lncRNA, which induces migration, invasion and proliferation of NSCLC. METTL3 increases LINC01006 expression through stabilizing LINC01006 mRNA. c-MYC, as a transcription factor, activates METTL3, which results in an elevated level of LINC01006. c-MYC, METTL3 and LINC01006 form a positive feedback loop through multiple miRNA targets in NSCLC.

Identification of CT-based non-invasive Radiographic Biomarkers for Overall Survival Stratification in Oral Cavity Squamous Cell Carcinoma.

This study addresses the limited non-invasive tools for Oral Cavity Squamous Cell Carcinoma OSCC survival prediction by identifying Computed Tomography (CT)-based biomarkers for improved prognosis. A retrospective analysis was conducted on data from 149 OSCC patients, including radiomics and clinical. An ensemble approach involving correlation analysis, score screening, and the Sparse-L1 algorithm was used to select functional features, which were then used to build Cox Proportional Hazards models (CPH). Our CPH achieved a 0.70 concordance index in testing. The model identified two CT-based radiomics features, Gradient-Neighboring-Gray-Tone-Difference-Matrix-Strength (GNS) and normalized-Wavelet-LLL-Gray-Level-Dependence-Matrix-Large-Dependence-High-Gray-Level-Emphasis (HLE), as well as smoking and alcohol usage, as survival biomarkers. The GNS group with values above 14 showed a hazard ratio of 0.12 and a 3-year survival rate of about 90%. Conversely, the GNS group with values less than or equal to 14 had a 49% survival rate. For normalized HLE, the high-end group (HLE > -0.415) had a hazard ratio of 2.41, resulting in a 3-year survival rate of 70%, while the low-end group (HLE <= -0.415) had a 36% survival rate. These findings contribute to our knowledge of how radiomics can be used to anticipate the outcome and tailor treatment plans from people with OSCC.