Corrigendum to 'Predicting post-resection recurrence by integrating imaging-based surrogates of distinct vascular patterns of hepatocellular carcinoma' (JHEP Reports 5 [2023] 100806).

[This corrects the article DOI: 10.1016/j.jhepr.2023.100806.].

Comparative analysis of risk factors associated with degeneration of adjacent segments: zero-profile anchored spacer vs. anterior cervical plate and cage construct.

Objective: Anterior cervical discectomy and fusion (ACDF) is an established treatment for cervical degenerative disc disease, but cervical spine surgery may affect sagittal alignment parameters and induce adjacent segment degeneration (ASD). This study aimed to determine the risk factors for developing ASD following anterior cervical plate and cage (ACPC) compared with the use of zero-profile anchored spacer (ROI-C). Methods: A retrospective contrastive study included 105 patients who underwent ACPC or ROI-C between January 2014 and October 2019 at our treatment centre. There were 50 cases in the ROI-C group and 55 patients in the ACPC group. Clinical and radiological results and the incidence of ASD were assessed after surgery. All patients were further divided into the ASD and non-ASD groups for subgroup analysis. Results: At each follow-up time, there was no statistically significant in radiographic parameters between the two groups. The overall ASD rate was higher in the ACPC group than in the ROI-C group (65.5% vs. 44.0%, p = 0.027). The low preoperative Cobb angle, low preoperative segment angle (SA), and loss of Cobb (ΔCobb) were significantly correlated with ASD. However, clinical outcomes were not associated with ASD at any postoperative follow-up visit. Conclusion: Equally good therapeutic effects were achieved with both the ROI-C and ACPC. The occurrence of ASD was considerably higher in the ACPC group than in the ROI-C group. The preoperative Cobb angle, preoperative SA, and ΔCobb were the most associated with an increase in the risk of ASD.

Signal enhancement ratio of multi-phase contrast-enhanced MRI: an imaging biomarker for survival in pancreatic adenocarcinoma.

OBJECTIVES: To evaluate signal enhancement ratio (SER) for tissue characterization and prognosis stratification in pancreatic adenocarcinoma (PDAC), with quantitative histopathological analysis (QHA) as the reference standard. METHODS: This retrospective study included 277 PDAC patients who underwent multi-phase contrast-enhanced (CE) MRI and whole-slide imaging (WSI) from three centers (2015-2021). SER is defined as (SIlt - SIpre)/(SIea - SIpre), where SIpre, SIea, and SIlt represent the signal intensity of the tumor in pre-contrast, early-, and late post-contrast images, respectively. Deep-learning algorithms were implemented to quantify the stroma, epithelium, and lumen of PDAC on WSIs. Correlation, regression, and Bland-Altman analyses were utilized to investigate the associations between SER and QHA. The prognostic significance of SER on overall survival (OS) was evaluated using Cox regression analysis and Kaplan-Meier curves. RESULTS: The internal dataset comprised 159 patients, which was further divided into training, validation, and internal test datasets (n = 60, 41, and 58, respectively). Sixty-five and 53 patients were included in two external test datasets. Excluding lumen, SER demonstrated significant correlations with stroma (r = 0.29-0.74, all p < 0.001) and epithelium (r = -0.23 to -0.71, all p < 0.001) across a wide post-injection time window (range, 25-300 s). Bland-Altman analysis revealed a small bias between SER and QHA for quantifying stroma/epithelium in individual training, validation (all within ± 2%), and three test datasets (all within ± 4%). Moreover, SER-predicted low stromal proportion was independently associated with worse OS (HR = 1.84 (1.17-2.91), p = 0.009) in training and validation datasets, which remained significant across three combined test datasets (HR = 1.73 (1.25-2.41), p = 0.001). CONCLUSION: SER of multi-phase CE-MRI allows for tissue characterization and prognosis stratification in PDAC. CLINICAL RELEVANCE STATEMENT: The signal enhancement ratio of multi-phase CE-MRI can serve as a novel imaging biomarker for characterizing tissue composition and holds the potential for improving patient stratification and therapy in PDAC. KEY POINTS: Imaging biomarkers are needed to better characterize tumor tissue in pancreatic adenocarcinoma. Signal enhancement ratio (SER)-predicted stromal/epithelial proportion showed good agreement with histopathology measurements across three distinct centers. Signal enhancement ratio (SER)-predicted stromal proportion was demonstrated to be an independent prognostic factor for OS in PDAC.

Effect of polydimethylsiloxane surface morphology on osteogenic differentiation of mesenchymal stem cells through SIRT1 signalling pathway.

Constructing surface topography with a certain roughness is a widely used, non-toxic, cost-effective and effective method for improving the microenvironment of cells, promoting the proliferation and osteogenic differentiation of mesenchymal stem cells (MSCs), and promoting the osseointegration of grafts and further improving their biocompatibility under clinical environmental conditions. SIRT1 plays an important regulatory role in the osteogenic differentiation of bone marrow-derived MSCs (BM-MSCs). However, it remains unknown whether SIRT1 plays an important regulatory role in the osteogenic differentiation of BM-MSCs with regard to surface morphology. Polydimethylsiloxane (PDMS) with different surface morphologies were prepared using different grits of sandpaper. The value for BMSCs added on different surfaces was detected by cell proliferation assays. RT-qPCR and Western blotting were performed to detect SIRT1 activation and osteogenic differentiation of MSCs. Osteogenesis of MSCs was detected by alkaline phosphatase (ALP) and alizarin red S staining. SIRT1 inhibition experiments were performed to investigate the role of SIRT1 in the osteogenic differentiation of MSCs induced by surface morphology. We found that BM-MSCs have better value and osteogenic differentiation ability on a surface with roughness of PDMS-1000M. SIRT1 showed higher gene and protein expression on a PDMS-1000M surface with a roughness of 13.741 ± 1.388 µm. The promotion of the osteogenic differentiation of MSCs on the PDMS-1000M surface was significantly decreased after inhibiting SIRT1 expression. Our study demonstrated that a surface morphology with certain roughness can activate the SIRT1 pathway of MSCs and promote the osteogenic differentiation of BMSCs via the SIRT1 pathway.

Single-cell RNA Sequencing Analysis Reveals the Role of Cancer-associated Fibroblasts in Skin Melanoma.

AIMS: Mechanism of fibroblasts in skin melanoma (SKME) revealed by single-cell RNA sequencing data. BACKGROUND: SKME is responsible for more than 80% of skin-related cancer deaths. Cancer-associated fibroblasts (CAFs) generate inflammatory factors, growth factors and extracellular matrix proteins to facilitate cancer cell growth, metastasis, drug resistance and immune exclusion. However, molecular mechanisms of CAFs in SKME are still lacking. OBJECTIVE: Our goal was to reveal the role of CAFs in SKME. METHODS: We downloaded the single-cell RNA sequencing (scRNA-seq) dataset from the Gene Expression Omnibus (GSE215120) database. Then, the Seurat package was applied to analyze the single-cell atlas of SKME data, and cell subsets were annotated with the CellMarker database. The molecular mechanisms of CAFs in SKME were disclosed via differential gene expression and enrichment analysis, Cellchat and SCENIC methods. RESULTS: Using scRNA-seq data, three SKME cases were used and downscaled and clustered to identify 11 cell subgroups and 5 CAF subsets. The enrichment of highly expressed genes among the 5 CAF subsets suggests that cell migration-inducing hyaluronan-binding protein (CEMIP) + fibroblasts and naked cuticle homolog 1 (NKD1) + fibroblasts were closely associated with epithelial to mesenchymal transition. Cellchat analysis revealed that CAF subpopulations promoted melanocyte proliferation through Jagged1 (JAG1)-Notch homolog 1 (NOTCH1), JAG1-NOTCH3 and migration through pleiotrophin (PTN)-syndecan-3 (SDC3) receptor-ligand pairs. The SCENIC analysis identified that most of the transcription factors in each CAF subpopulation played a certain role in the metastasis of melanoma and were highly expressed in metastatic SKME samples. Specifically, we observed that CEMIP+ fibroblasts and NKD1+ fibroblasts had potential roles in participating in immune therapy resistance. Collectively, we uncovered a single-- cell atlas of SKME and revealed the molecular mechanisms of CAFs in SKME development, providing a base for immune therapy and prognosis assessment. CONCLUSION: Our study reveals that 5 CAFs in SKME have a promoting effect on melanocyte proliferation and metastasis. More importantly, CEMIP+ fibroblasts and NKD1+ fibroblasts displayed close connections with immune therapy resistance. These findings help provide a good basis for future immune therapy and prognosis assessment targeting CAFs in SKME.

Sirt6 regulates the proliferation of neural precursor cells and cortical neurogenesis in mice.

Sirt6, a member of the class III histone deacetylases (HDACs), functions in the regulation of genomic stability, DNA repair, cancer, metabolism and aging. Sirt6 deficiency is lethal, and newborn SIRT6-null cynomolgus monkeys show unfinished brain development. After the generation of a cortex-specific Sirt6 conditional knockout mouse model, we investigated the specific deletion of Sirt6 in NPCs at E10.5. This study found that Sirt6 deficiency causes excessive proliferation of neural precursor cells (NPCs) and retards differentiation. The results suggest that endogenous Sirt6 in NPCs regulates histone acetylation and limits stemness-related genes, including Notch1, in order to participate in NPC fate determination. These findings help elucidate Sirt6's role in brain development and in NPC fate determination while providing data on species generality and differentiation.

Ovarian carcinoma immune-related microRNA affects the heterogeneity of the endocrine microenvironment and anti-tumor immune pattern.

BACKGROUND: The eighth-leading cause of cancer-related mortality and the seventh-most prevalent malignancy in women globally is ovarian cancer (OV). However, 5-year survival expectancy after conventional treatment is not good. Therefore, there is an urgent need for novel signatures to guide the designation of therapeutic schemes for OV patients. METHODS: We used univariate Cox analysis to screen hormone secretion regulation axis-related microRNAs (miRNAs), least absolute shrinkage and selection operator analysis to select candidate miRNAs and multivariate Cox analysis to build the risk model. To evaluate possible route and functional differences, enrichment analysis using Gene Ontology (GO) and the Kyoto Encyclopedia of Genes and Genomes (KEGG) were performed on the differentially expressed genes (DEGs) across various risk groups. We compared Tumor Immune Dysfunction and Exclusion (TIDE) scores across risk categories by analyzing immune cell infiltration, immune checkpoint gene expression, immunological function and TIDE scores. In the end, we determined the half maximal inhibitory concentration (IC50 ) of chemotherapy and targeted medicines for individual patients. Cell assays were determined to test the migration of the miRNA-target genes and western blotting was used to test the correlation of the miRNA-target genes and the pathways. RESULTS: We finally identified hormone secretion regulation axis-related 13 microRNAs to build a risk model. The validation of observed and anticipated values revealed a fair level of agreement. To evaluate the molecular pathways between various groups in accordance with the GO and KEGG analyses, we then discovered 173 DEGs between distinct risk groups. The risk score was shown to be inversely related to the number of immune cells, including myeloid dendritic, granulocytes, M1 and M2 macrophages, B cells, t-lymphocytes, and CD4+ and CD8+ cells, suggesting that immune cells are more frequent in the low-risk group. Immune cell infiltration investigation yielded these results. Finally, we recognized 11 chemotherapeutic drugs and 30 novels targeted drugs on the basis of IC50 between the different risk groups. GJB5 was determined to be the mir-219 target gene and was identified as promoting the cell cycle process. In addition, hormone secretion regulation axis related miRNAs were reported to affects the heterogeneity of endocrine microenvironment and anti-tumor immune pattern. CONCLUSIONS: In conclusion, a 13-miRNA prognostic model was constructed to know the immune status, prognosis, immunotherapeutic response and anti-tumor drug sensitivity for OV, which provides theoretical guidance for the effective and individualized treatment of OV patients.

The inflammatory response-related robust machine learning signature in endometrial cancer: Based on multi-cohort studies.

Uterine corpus endometrial carcinoma (UCEC) is a prevalent form of cancer in women, affecting the inner lining of the uterus. Inflammation plays a crucial role in the progression and prognosis of cancer, making it important to identify inflammatory response-related subtypes in UCEC for targeted therapy and personalized medicine. This study discovered significant variation in immune response within UCEC tumors based on molecular subtypes of inflammatory response-related genes. Subtype A showed a more favorable prognosis and better response to immunotherapies like anti-CTLA4 and anti-PDCD1 therapy. Functional analysis revealed subtype-specific differences in immune response, with subtype A exhibiting higher expression of genes related to cytokine signaling pathways, NK cell-mediated cytotoxicity pathways and inflammatory processes. Subtype A also showed increased sensitivity to three chemotherapeutic agents. A 12-gene inflammatory response-related signature was found to have prognostic value for 1, 2 and 3 year survival in UCEC patients. Additionally, a validated machine learning-based signature demonstrated significant differences in clinical traits between low-risk and high-risk cohorts. Elevated risk scores were associated with higher pathological grading, older age, advanced stage and immune subtype C2. Low-risk groups had higher infiltration of immune cell types such as CD8 + T cells and activated CD4 + cells. However, the abundance of cytotoxic immune cells decreased with increasing risk scores. Finally, PCR was applied to test the different expression in P2PX4. P2RX4 knockdown inhibited the proliferation and proliferation of the endometrial carcinoma Ishikawa cell line. In conclusion, this developed signature can serve as a clinical prediction index and reveal distinct immune expression patterns. Ultimately, this study has the potential to enhance targeted therapy and personalized medicine for UCEC patients.

Predicting post-resection recurrence by integrating imaging-based surrogates of distinct vascular patterns of hepatocellular carcinoma.

Background & Aims: Distinct vascular patterns, including microvascular invasion (MVI) and vessels encapsulating tumour clusters (VETC), are associated with poor outcomes of hepatocellular carcinoma (HCC). Imaging surrogates of these vascular patterns potentially help to predict post-resection recurrence. Herein, a prognostic model integrating imaging-based surrogates of these distinct vascular patterns was developed to predict postoperative recurrence-free survival (RFS) in patients with HCC. Methods: Clinico-radiological data of 1,285 patients with HCC from China undergoing surgical resection were retrospectively enrolled from seven medical centres between 2014 and 2020. A prognostic model using clinical data and imaging-based surrogates of MVI and VETC patterns was developed (n = 297) and externally validated (n = 373) to predict RFS. The surrogates (i.e. MVI and VETC scores) were individually built from preoperative computed tomography using two independent cohorts (n = 360 and 255). Whether the model's stratification was associated with postoperative recurrence following anatomic resection was also evaluated. Results: The MVI and VETC scores demonstrated effective performance in their respective training and validation cohorts (AUC: 0.851-0.883 for MVI and 0.834-0.844 for VETC). The prognostic model incorporating serum alpha-foetoprotein, tumour multiplicity, MVI score, and VETC score achieved a C-index of 0.748-0.764 for the developing and external validation cohorts and generated three prognostically distinct strata. For patients at model-predicted medium risk, anatomic resection was associated with improved RFS (p <0.05). By contrast, anatomic resection had no impact on RFS in patients at model-predicted low or high risk (both p >0.05). Conclusions: The proposed model integrating imaging-based surrogates of distinct vascular patterns enabled accurate prediction for RFS. It can potentially be used to identify HCC surgical candidates who may benefit from anatomic resection. Impact and implications: MVI and VETC are distinct vascular patterns of HCC associated with aggressive biological behaviour and poor outcomes. Our multicentre study provided a model incorporating imaging-based surrogates of these patterns for preoperatively predicting RFS. The proposed model, which uses imaging detection to estimate the risk of MVI and VETC, offers an opportunity to help shed light on the association between tumour aggressiveness and prognosis and to support the selection of the appropriate type of surgical resection.

Predicting Microvascular Invasion in Hepatocellular Carcinoma Using CT-based Radiomics Model.

Background Prediction of microvascular invasion (MVI) may help determine treatment strategies for hepatocellular carcinoma (HCC). Purpose To develop a radiomics approach for predicting MVI status based on preoperative multiphase CT images and to identify MVI-associated differentially expressed genes. Materials and Methods Patients with pathologically proven HCC from May 2012 to September 2020 were retrospectively included from four medical centers. Radiomics features were extracted from tumors and peritumor regions on preoperative registration or subtraction CT images. In the training set, these features were used to build five radiomics models via logistic regression after feature reduction. The models were tested using internal and external test sets against a pathologic reference standard to calculate area under the receiver operating characteristic curve (AUC). The optimal AUC radiomics model and clinical-radiologic characteristics were combined to build the hybrid model. The log-rank test was used in the outcome cohort (Kunming center) to analyze early recurrence-free survival and overall survival based on high versus low model-derived score. RNA sequencing data from The Cancer Image Archive were used for gene expression analysis. Results A total of 773 patients (median age, 59 years; IQR, 49-64 years; 633 men) were divided into the training set (n = 334), internal test set (n = 142), external test set (n = 141), outcome cohort (n = 121), and RNA sequencing analysis set (n = 35). The AUCs from the radiomics and hybrid models, respectively, were 0.76 and 0.86 for the internal test set and 0.72 and 0.84 for the external test set. Early recurrence-free survival (P < .01) and overall survival (P < .007) can be categorized using the hybrid model. Differentially expressed genes in patients with findings positive for MVI were involved in glucose metabolism. Conclusion The hybrid model showed the best performance in prediction of MVI. © RSNA, 2023 Supplemental material is available for this article. See also the editorial by Summers in this issue.

Comparison of 3-level anterior cervical discectomy and fusion and open-door laminoplasty in cervical sagittal balance: A retrospective study.

Objective: To compare the clinical efficacy and radiological outcomes of 3-level anterior cervical discectomy and fusion (ACDF) and open-door laminoplasty (LP). Methods: A total of 74 patients from January 2017 to January 2020 were enrolled in this retrospective study. There were two groups. Group A (30 cases) received 3-level ACDF, while Group B (44 cases) received open-door LP. Clinical evaluation included perioperative parameters, Neck Disability Index (NDI), and Japanese Orthopaedic Association (JOA) scores. Radiological evaluation included cervical curve depth (CCD), C2-7 angle, C2-7 sagittal vertical axis (cSVA), C7 slope (C7S), and T1 slope (T1S). Results: Perioperative parameters such as blood loss, drainage volume after surgery, and hospital stay of patients in Group A were significantly less than those in Group B (P < .001). NDI scores decreased and JOA scores increased significantly after surgery in both groups (P < .05). There was a significant difference in both scores postoperatively and at 1 month after surgery between the two groups (P < .05). CCD and C2-7 angle of Group A increased significantly postoperatively at 1 month after surgery and at final follow-up (FFU) (P < .05). There was a significant difference in CCD and the C2-7 angle between the two groups postoperatively at 1 month after surgery and at FFU (P < .05). T1S increased significantly in Group A postoperatively and at 1 month after surgery (P < .05). Conclusion: 3-level ACDF and open-door LP achieved favorable clinical outcomes and ACDF benefited patients in the early stage of rehabilitation. Compared with open-door LP, 3-level ACDF had advantages of reconstructing cervical lordosis with increased CCD and C2-7 angle.

Preoperative Microvascular Invasion Prediction to Assist in Surgical Plan for Single Hepatocellular Carcinoma: Better Together with Radiomics.

BACKGROUND: Prediction models with or without radiomic analysis for microvascular invasion (MVI) in hepatocellular carcinoma (HCC) have been reported, but the potential for model-predicted MVI in surgical planning is unclear. Therefore, we aimed to explore the effect of predicted MVI on early recurrence after anatomic resection (AR) and non-anatomic resection (NAR) to assist surgical strategies. METHODS: Patients with a single HCC of 2-5 cm receiving curative resection were enrolled from 2 centers. Their data were used to develop (n = 230) and test (n = 219) two prediction models for MVI using clinical factors and preoperative computed tomography images. The two prediction models, clinico-radiologic model and clinico-radiologic-radiomic (CRR) model (clinico-radiologic variables + radiomic signature), were compared using the Delong test. Early recurrence based on model-predicted high-risk MVI was evaluated between AR (n = 118) and NAR (n = 85) via propensity score matching using patient data from another 2 centers for external validation. RESULTS: The CRR model showed higher area under the curve values (0.835-0.864 across development, test, and external validation) but no statistically significant improvement over the clinico-radiologic model (0.796-0.828). After propensity score matching, difference in 2-year recurrence between AR and NAR was found in the CRR model predicted high-risk MVI group (P = 0.005) but not in the clinico-radiologic model predicted high-risk MVI group (P = 0.31). CONCLUSIONS: The prediction model incorporating radiomics provided an accurate preoperative estimation of MVI, showing the potential for choosing the more appropriate surgical procedure between AR and NAR.

A retrospective study of distribution of HIV associated malignancies among inpatients from 2007 to 2020 in China.

HIV-associated malignancies are responsible for morbidity and mortality increasingly in the era of potent antiretroviral therapy. This study aimed to investigate the distribution of HIV-associated malignancies among inpatients, the immunodeficiency and the effect of antiretroviral therapy (ART) on spectrum of HIV-associated malignancies. A total of 438 cases were enrolled from 2007 to 2020 in Beijing Ditan Hospital. Demographic, clinical and laboratory data, managements, and outcomes were collected and analyzed retrospectively. Of 438 cases, 433 were assigned to non-AIDS-defining cancers (NADCs) (n = 200, 45.7%) and AIDS-defining cancers (ADCs) (n = 233, 53.2%), 5 (1.1%) with lymphoma were not specified further. No significant change was observed in the proportion of NADCs and ADCs as time goes on. Of NADCs, lung cancer (n = 38, 19%) was the most common type, followed by thyroid cancer (n = 17, 8.5%). Patients with ADCs had lower CD4 counts(104.5/µL vs. 314/µL), less suppression of HIVRNA(OR 0.23, 95%CI 0.16-0.35) compared to those with NADCs. ART did not affect spectrum of NADCs, but affect that of ADCs (between patients with detectable and undetectable HIVRNA). ADCs remain frequent in China, and NADCs play an important role in morbidity and mortality of HIV positive population.

Pentagalloylglucose reduces AGE-induced inflammation by activating Nrf2/HO-1 and inhibiting the JAK2/STAT3 pathway in mesangial cells.

Pentagalloylglucose (PGG), a gallotannin polyphenolic compound, has been found to possess a host of beneficial pharmacologic activities, such as anti-inflammatory and antioxidative activities. We previously demonstrated that PGG is capable of binding to the cell membrane of renal mesangial cells, but the pharmacological effect of PGG on diabetic renal injury and the underlying mechanisms are still not yet clear. In this study, the effects of PGG on Nrf2/HO-1 and JAK2/STAT3 signaling were explored in AGE-stimulated mesangial cells. Furthermore, the Nrf2 transcriptional inhibitor ML385 was used to verify the involvement of Nrf2 in the PGG-mediated inhibition of the JAK2/STAT3 cascade. Our results showed that PGG significantly inhibited AGE-induced ROS generation and activated AGE-inhibited Nrf2/HO-1 signaling. Moreover, AGE-induced inflammatory cytokines (IL-1ß and TNF-α) and their signaling through JAK2/STAT3 were blocked by PGG. Furthermore, ML385 suppressed Nrf2/HO-1 signaling, elevated ROS and cytokine production, and activated JAK2/STAT3 cascade were reversed by PGG. These findings indicate that PGG inhibits the JAK2/STAT3 cascade by activating Nrf2/HO-1 signaling.

Terpyridine Zn(II) Complexes with Azide Units for Visualization of Histone Deacetylation in Living Cells under STED Nanoscopy.

Histones are the alkali proteins in eukaryotic somatic chromatin cells which constitute the nucleosome structure together with DNA. Their abnormality is often associated with multiple tumorigenesis and other human diseases. Nevertheless, a simple and efficient super-resolution method to visualize histone distribution at the subcellular level is still unavailable. Herein, a Zn(II) terpyridine complex with rich-electronic azide units, namely, TpZnA-His, was designed and synthesized. The initial in vitro and in silico studies suggested that this complex is able to detect histones rapidly and selectively via charge-charge interactions with the histone H3 subunit. Its live cell nuclear localization, red-emission tail, and large Stokes shift allowed super-resolution evaluation of histone distributions with a clear distinction against nuclear DNA. We were able to quantitatively conclude three histone morphology alternations in live cells including condensation, aggregation, and cavity during activating histone acetylation. This work offers a better understanding as well as a versatile tool to study histone-involved gene transcription, signal transduction, and differentiation in cells.

Comparison of MRI and CT for the Prediction of Microvascular Invasion in Solitary Hepatocellular Carcinoma Based on a Non-Radiomics and Radiomics Method: Which Imaging Modality Is Better?

BACKGROUND: Computed tomography (CT) and magnetic resonance imaging (MRI) are both capable of predicting microvascular invasion (MVI) in hepatocellular carcinoma (HCC). However, which modality is better is unknown. PURPOSE: To intraindividually compare CT and MRI for predicting MVI in solitary HCC and investigate the added value of radiomics analyses. STUDY TYPE: Retrospective. SUBJECTS: Included were 402 consecutive patients with HCC (training set:validation set = 300:102). FIELD STRENGTH/SEQUENCE: T2-weighted, diffusion-weighted, and contrast-enhanced T1-weighted imaging MRI at 3.0T and contrast-enhanced CT. ASSESSMENT: CT- and MR-based radiomics signatures (RS) were constructed using the least absolute shrinkage and selection operator regression. CT- and MR-based radiologic (R) and radiologic-radiomics (RR) models were developed by univariate and multivariate logistic regression. The performance of the RS/models was compared between two modalities. To investigate the added value of RS, the performance of the R models was compared with the RR models in HCC of all sizes and 2-5 cm in size. STATISTICAL TESTS: Model performance was quantified by the area under the receiver operating characteristic curve (AUC) and compared using the Delong test. RESULTS: Histopathologic MVI was identified in 161 patients (training set:validation set = 130:31). MRI-based RS/models tended to have a marginally higher AUC than CT-based RS/models (AUCs of CT vs. MRI, P: RS, 0.801 vs. 0.804, 0.96; R model, 0.809 vs. 0.832, 0.09; RR model, 0.835 vs. 0.872, 0.54). The improvement of RR models over R models in all sizes was not significant (P = 0.21 at CT and 0.09 at MRI), whereas the improvement in 2-5 cm was significant at MRI (P < 0.05) but not at CT (P = 0.16). DATA CONCLUSION: CT and MRI had a comparable predictive performance for MVI in solitary HCC. The RS of MRI only had significant added value for predicting MVI in HCC of 2-5 cm. LEVEL OF EVIDENCE: 3 TECHNICAL EFFICACY: Stage 2.

Photodynamic Therapy Directed by Three-Photon Active Rigid Plane Organic Photosensitizer.

Multi-photon photosensitizers (PSs) could significantly improve the efficacy of photodynamic therapy due to the long-wavelength favorability for deeper tissue penetration and lower biological damage. However, most studies are limited to single-photon or two-photon PSs at a relatively short-wave excitation window. To overcome this barrier, we rationally design a series of rigid plane compounds with efficient reactive oxygen species (ROS) production in vitro under laser irradiation. Furthermore, the studies show that one of the compounds (U-TsO) could induce rapid multi-types of cell death under three-photon exposure, suggesting a promising clinical outcome in ex vivo 3D multicellular tumor spheroid. This work offers a novel strategy to construct functional materials with competitive multi-photon photodynamic therapy (PDT) outcome.

HCF-1 promotes cell cycle progression by regulating the expression of CDC42.

The eukaryotic cell cycle involves a highly orchestrated series of events in which the cellular genome is replicated during a synthesis (S) phase and each of the two resulting copies are segregated properly during mitosis (M). Host cell factor-1 (HCF-1) is a transcriptional co-regulator that is essential for and has been implicated in basic cellular processes, such as transcriptional regulation and cell cycle progression. Although a series of HCF-1 transcriptional targets have been identified, few functional clues have been provided, especially for chromosome segregation. Our results showed that HCF-1 activated CDC42 expression by binding to the -881 to -575 region upstream of the CDC42 transcription start site, and the regulation of CDC42 expression by HCF-1 was correlated with cell cycle progression. The overexpression of a spontaneously cycling and constitutively active CDC42 mutant (CDC42F28L) rescued G1 phase delay and multinucleate defects in mitosis upon the loss of HCF-1. Therefore, these results establish that HCF-1 ensures proper cell cycle progression by regulating the expression of CDC42, which indicates a possible mechanism of cell cycle coordination and the regulation mode of typical Rho GTPases.

Radiomics Analysis on Multiphase Contrast-Enhanced CT: A Survival Prediction Tool in Patients With Hepatocellular Carcinoma Undergoing Transarterial Chemoembolization.

Patients with HCC receiving TACE have various clinical outcomes. Several prognostic models have been proposed to predict clinical outcomes for patients with hepatocellular carcinomas (HCC) undergoing transarterial chemoembolization (TACE), but establishing an accurate prognostic model remains necessary. We aimed to develop a radiomics signature from pretreatment CT to establish a combined radiomics-clinic (CRC) model to predict survival for these patients. We compared this CRC model to the existing prognostic models in predicting patient survival. This retrospective study included multicenter data from 162 treatment-naïve patients with unresectable HCC undergoing TACE as an initial treatment from January 2007 and March 2017. We randomly allocated patients to a training cohort (n = 108) and a testing cohort (n = 54). Radiomics features were extracted from intra- and peritumoral regions on both the arterial phase and portal venous phase CT images. A radiomics signature (Rad-signature) for survival was constructed using the least absolute shrinkage and selection operator method in the training cohort. We used univariate and multivariate Cox regressions to identify associations between the Rad- signature and clinical factors of survival. From these, a CRC model was developed, validated, and further compared with previously published prognostic models including four-and-seven criteria, six-and-twelve score, hepatoma arterial-embolization prognostic scores, and albumin-bilirubin grade. The CRC model incorporated two variables: The Rad-signature (composed of features extracted from intra- and peritumoral regions on the arterial phase and portal venous phase) and tumor number. The CRC model performed better than the other seven well-recognized prognostic models, with concordance indices of 0.73 [95% confidence interval (CI) 0.68-0.79] and 0.70 [95% CI 0.62-0.82] in the training and testing cohorts, respectively. Among the seven models tested, the six-and-12 score and four-and-seven criteria performed better than the other models, with C-indices of 0.64 [95% CI 0.58-0.70] and 0.65 [95% CI 0.55-0.75] in the testing cohort, respectively. The CT radiomics signature represents an independent biomarker of survival in patients with HCC undergoing TACE, and the CRC model displayed improved predictive performance.