A Poly(amino acid)-Based Nanomedicine Strategy: Telomere-Telomerase Axis Targeting and Magnetic Resonance Imaging in Hepatocellular Carcinoma Treatment.

Targeting telomere maintenance has emerged as a promising strategy for hepatocellular carcinoma (HCC) treatment. However, given the duality of the telomere-telomerase axis in telomere maintenance, a comprehensive strategy is urgently needed. Herein, we develop a poly(amino acid) (D-PAAs)-based strategy for spatiotemporal codelivery of telomerase inhibitor, BIBR1523, and AKT inhibitor, isobavachalcone. By leveraging D-PAAs' modifiability, we synthesize polymer-inhibitor conjugates (PB and PI) and a folic acid-decorated tumor-targeting vector (PF). These building blocks undergo micellization to fabricate a codelivery nanomedicine (P-BI@P-FA) by exploiting D-PAAs' noncovalent assembly. P-BI@P-FA improves the pharmacokinetics, tumor selectivity, and bioavailability of small molecule inhibitors and initiates a dual telomere-specific inhibition by combining telomerase deactivation with telomere disruption. Furthermore, a hybrid tumor-targeting magnetic nanosystem is designed using D-PAAs and manganese dioxide to showcase magnetic resonance imaging capacities. Our D-PAAs-based strategy addresses the pressing need for telomere-specific HCC treatment while allowing for diagnostic application, presenting a promising avenue for nanomedicine design.

Assessment of Right Atrial Function Measured with Cardiac MRI Feature Tracking for Predicting Outcomes in Patients with Dilated Cardiomyopathy.

Background Right atrial (RA) function strain is increasingly acknowledged as an important predictor of adverse events in patients with diverse cardiovascular conditions. However, the prognostic value of RA strain in patients with dilated cardiomyopathy (DCM) remains uncertain. Purpose To evaluate the prognostic value of RA strain derived from cardiac MRI (CMR) feature tracking (FT) in patients with DCM. Materials and Methods This multicenter, retrospective study included consecutive adult patients with DCM who underwent CMR between June 2010 and May 2022. RA strain parameters were obtained using CMR FT. The primary end points were sudden or cardiac death or heart transplant. Cox regression analysis was used to determine the association of variables with outcomes. Incremental prognostic value was evaluated using C indexes and likelihood ratio tests. Results A total of 526 patients with DCM (mean age, 51 years ± 15 [SD]; 381 male) were included. During a median follow-up of 41 months, 79 patients with DCM reached the primary end points. At univariable analysis, RA conduit strain was associated with the primary end points (hazard ratio [HR], 0.82 [95% CI: 0.76, 0.87]; P < .001). In multivariable Cox analysis, RA conduit strain was an independent predictor for the primary end points (HR, 0.83 [95% CI: 0.77, 0.90]; P < .001). A model combining RA conduit strain with other clinical and conventional imaging risk factors (C statistic, 0.80; likelihood ratio, 92.54) showed improved discrimination and calibration for the primary end points compared with models with clinical variables (C statistic, 0.71; likelihood ratio, 37.12; both P < .001) or clinical and imaging variables (C statistic, 0.75; likelihood ratio, 64.69; both P < .001). Conclusion CMR FT-derived RA conduit strain was an independent predictor of adverse outcomes among patients with DCM, providing incremental prognostic value when combined in a model with clinical and conventional CMR risk factors. Published under a CC BY 4.0 license. Supplemental material is available for this article.

Differentiating small (< 2 cm) pancreatic ductal adenocarcinoma from neuroendocrine tumors with multiparametric MRI-based radiomic features.

OBJECTIVES: To assess MR-based radiomic analysis in preoperatively discriminating small (< 2 cm) pancreatic ductal adenocarcinomas (PDACs) from neuroendocrine tumors (PNETs). METHODS: A total of 197 patients (146 in the training cohort, 51 in the validation cohort) from two centers were retrospectively collected. A total of 7338 radiomics features were extracted from T2-weighted, diffusion-weighted, T1-weighted, arterial phase, portal venous phase and delayed phase imaging. The optimal features were selected by the Mann-Whitney U test, Spearman's rank correlation test and least absolute shrinkage and selection operator method and used to construct the radiomic score (Rad-score). Conventional radiological and clinical features were also assessed. Multivariable logistic regression was used to construct a radiological model, a radiomic model and a fusion model. RESULTS: Nine optimal features were identified and used to build the Rad-score. The radiomic model based on the Rad-score achieved satisfactory results with AUCs of 0.905 and 0.930, sensitivities of 0.780 and 0.800, specificities of 0.906 and 0.952 and accuracies of 0.836 and 0.863 for the training and validation cohorts, respectively. The fusion model, incorporating CA19-9, tumor margins, pancreatic duct dilatation and the Rad-score, exhibited the best performance with AUCs of 0.977 and 0.941, sensitivities of 0.914 and 0.852, specificities of 0.954 and 0.950, and accuracies of 0.932 and 0.894 for the training and validation cohorts, respectively. CONCLUSIONS: The MR-based Rad-score is a novel image biomarker for discriminating small PDACs from PNETs. A fusion model combining radiomic, radiological and clinical features performed very well in differentially diagnosing these two tumors. CLINICAL RELEVANCE STATEMENT: A fusion model combining MR-based radiomic, radiological, and clinical features could help differentiate between small pancreatic ductal adenocarcinomas and pancreatic neuroendocrine tumors. KEY POINTS: Preoperatively differentiating small pancreatic ductal adenocarcinomas (PDACs) and pancreatic neuroendocrine tumors (PNETs) is challenging. Multiparametric MRI-based Rad-score can be used for discriminating small PDACs from PNETs. A fusion model incorporating radiomic, radiological, and clinical features differentiated small PDACs from PNETs well.

A convenient scoring system to distinguish intrahepatic mass-forming cholangiocarcinoma from solitary colorectal liver metastasis based on magnetic resonance imaging features.

OBJECTIVES: To develop and validate a diagnostic scoring system to differentiate intrahepatic mass-forming cholangiocarcinoma (IMCC) from solitary colorectal liver metastasis (CRLM). METHODS: A total of 366 patients (263 in the training cohort, 103 in the validation cohort) who underwent MRI examination with pathologically proven either IMCC or CRLM from two centers were included. Twenty-eight MRI features were collected. Univariate analyses and multivariate logistic regression analyses were performed to identify independent predictors for distinguishing IMCC from solitary CRLM. The independent predictors were weighted over based on regression coefficients to build a scoring system. The overall score distribution was divided into three groups to show the diagnostic probability of CRLM. RESULTS: Six independent predictors, including hepatic capsular retraction, peripheral hepatic enhancement, vessel penetrating the tumor, upper abdominal lymphadenopathy, peripheral washout at the portal venous phase, and rim enhancement at the portal venous phase were included in the system. All predictors were assigned 1 point. At a cutoff of 3 points, AUCs for this score model were 0.948 and 0.903 with sensitivities of 96.5% and 92.0%, specificities of 84.4% and 71.7%, positive predictive values of 87.7% and 75.4%, negative predictive values of 95.4% and 90.5%, and accuracies of 90.9% and 81.6% for the training and validation cohorts, respectively. An increasing trend was shown in the diagnostic probability of CRLM among the three groups based on the score. CONCLUSIONS: The established scoring system is reliable and convenient for distinguishing IMCC from solitary CRLM using six MRI features. CLINICAL RELEVANCE STATEMENT: A reliable and convenient scoring system was developed to differentiate between intrahepatic mass-forming cholangiocarcinoma from solitary colorectal liver metastasis using six MRI features. KEY POINTS: • Characteristic MRI features were identified to distinguish intrahepatic mass-forming cholangiocarcinoma (IMCC) from solitary colorectal liver metastasis (CRLM). • A model to distinguish IMCC from solitary CRLM was created based on 6 features, including hepatic capsular retraction, upper abdominal lymphadenopathy, peripheral washout at the portal venous phase, rim enhancement at the portal venous phase, peripheral hepatic enhancement, and vessel penetrating the tumor.

A CT-based nomogram established for differentiating gastrointestinal heterotopic pancreas from gastrointestinal stromal tumor: compared with a machine-learning model.

OBJECTIVE: To identify CT features and establish a nomogram, compared with a machine learning-based model for distinguishing gastrointestinal heterotopic pancreas (HP) from gastrointestinal stromal tumor (GIST). MATERIALS AND METHODS: This retrospective study included 148 patients with pathologically confirmed HP (n = 48) and GIST (n = 100) in the stomach or small intestine that were less than 3 cm in size. Clinical information and CT characteristics were collected. A nomogram on account of lasso regression and multivariate logistic regression, and a RandomForest (RF) model based on significant variables in univariate analyses were established. Receiver operating characteristic (ROC) curve, mean area under the curve (AUC), calibration curve and decision curve analysis (DCA) were carried out to evaluate and compare the diagnostic ability of models. RESULTS: The nomogram identified five CT features as independent predictors of HP diagnosis: age, location, LD/SD ratio, duct-like structure, and HU lesion/pancreas A. Five features were included in RF model and ranked according to their relevance to the differential diagnosis: LD/SD ratio, HU lesion/pancreas A, location, peritumoral hypodensity line and age. The nomogram and RF model yielded AUC of 0.951 (95% CI: 0.842-0.993) and 0.894 (95% CI: 0.766-0.966), respectively. The DeLong test found no statistically significant difference in diagnostic performance (p > 0.05), but DCA revealed that the nomogram surpassed the RF model in clinical usefulness. CONCLUSION: Two diagnostic prediction models based on a nomogram as well as RF method were reliable and easy-to-use for distinguishing between HP and GIST, which might also assist treatment planning.

Recent Advances in Well-Designed Therapeutic Nanosystems for the Pancreatic Ductal Adenocarcinoma Treatment Dilemma.

Pancreatic ductal adenocarcinoma (PDAC) is a highly malignant tumor with an extremely poor prognosis and low survival rate. Due to its inconspicuous symptoms, PDAC is difficult to diagnose early. Most patients are diagnosed in the middle and late stages, losing the opportunity for surgery. Chemotherapy is the main treatment in clinical practice and improves the survival of patients to some extent. However, the improved prognosis is associated with higher side effects, and the overall prognosis is far from satisfactory. In addition to resistance to chemotherapy, PDAC is significantly resistant to targeted therapy and immunotherapy. The failure of multiple treatment modalities indicates great dilemmas in treating PDAC, including high molecular heterogeneity, high drug resistance, an immunosuppressive microenvironment, and a dense matrix. Nanomedicine shows great potential to overcome the therapeutic barriers of PDAC. Through the careful design and rational modification of nanomaterials, multifunctional intelligent nanosystems can be obtained. These nanosystems can adapt to the environment's needs and compensate for conventional treatments' shortcomings. This review is focused on recent advances in the use of well-designed nanosystems in different therapeutic modalities to overcome the PDAC treatment dilemma, including a variety of novel therapeutic modalities. Finally, these nanosystems' bottlenecks in treating PDAC and the prospect of future clinical translation are briefly discussed.

Quantitative analysis of enhanced CT in differentiating well-differentiated pancreatic neuroendocrine tumors and poorly differentiated neuroendocrine carcinomas.

OBJECTIVE: To identify quantitative CT features for distinguishing well-differentiated pancreatic neuroendocrine tumors (PNETs) from poorly differentiated pancreatic neuroendocrine carcinomas (PNECs). MATERIALS AND METHODS: Seventeen patients with PNECs and 131 patients with PNETs confirmed by biopsy or surgery were retrospectively included. General demographic (sex, age) and CT quantitative parameters (arterial/portal absolute enhancement, arterial/portal relative enhancement ratio, arterial/portal enhancement ratio) were collected. Univariate and multivariate logistic regression analyses were performed to confirm independent variables for differentiating PNECs from PNETs. Receiver operating characteristic (ROC) curves for each quantitative parameter were generated to determine their diagnostic ability. RESULTS: PNECs had a much lower mean arterial/portal absolute enhancement value (19.5 ± 11.0 vs. 78.8 ± 47.2; 28.1 ± 15.8 vs. 77.0 ± 39.4), arterial/portal relative enhancement ratio (0.57 ± 0.36 vs. 2.03 ± 1.31; 0.80 ± 0.52 vs. 1.99 ± 1.13), and arterial/portal enhancement ratio (0.62 ± 0.27 vs. 1.22 ± 0.49; 0.74 ± 0.19 vs. 1.21 ± 0.36) than PNETs (all p < 0.001). After multivariable analysis, arterial absolute enhancement (odds ratio [OR]: 0.96, 95% confidence interval [CI]: 0.93, 0.99) and portal absolute enhancement (OR: 0.96, 95% CI: 0.92, 0.99) were independent factors for differentiating PNECs from PNETs. For each quantitative parameter, arterial lesion enhancement yielded the highest diagnostic performance, with an area under the curve (AUC) of 0.922 (95% CI: 0.867-0.960), followed by portal absolute enhancement. CONCLUSIONS: Arterial/portal absolute enhancements were independent predictors with good diagnostic accuracy for differentiating between PNETs and PNECs. Quantitative parameters of enhanced CT can distinguish PNECs from PNETs. KEY POINTS: • PNECs were hypovascular and had a much lower enhanced CT attenuation in both arterial and portal phases than well-differentiated PNETs. • Quantitative parameters derived from enhanced CT can be used to distinguish PNECs from PNETs. • Arterial absolute enhancement and portal absolute enhancement were independent predictive factors for differentiating between PNETs and PNECs.

Extracellular matrix modulating enzyme functionalized biomimetic Au nanoplatform-mediated enhanced tumor penetration and synergistic antitumor therapy for pancreatic cancer.

BACKGROUND: Excessive extracellular matrix (ECM) deposition in pancreatic ductal adenocarcinoma (PDAC) severely limits therapeutic drug penetration into tumors and is associated with poor prognosis. Collagen is the most abundant matrix protein in the tumor ECM, which is the main obstacle that severely hinders the diffusion of chemotherapeutic drugs or nanomedicines. METHODS: We designed a collagenase-functionalized biomimetic drug-loaded Au nanoplatform that combined ECM degradation, active targeting, immune evasion, near-infrared (NIR) light-triggered drug release, and synergistic antitumor therapy and diagnosis into one nanoplatform. PDAC tumor cell membranes were extracted and coated onto doxorubicin (Dox)-loaded Au nanocages, and then collagenase was added to functionalize the cell membrane through lipid insertion. We evaluated the physicochemical properties, in vitro and in vivo targeting, penetration and therapeutic efficacy of the nanoplatform. RESULTS: Upon intravenous injection, this nanoplatform efficiently targeted the tumor through the homologous targeting properties of the coated cell membrane. During penetration into the tumor tissue, the dense ECM in the PDAC tissues was gradually degraded by collagenase, leading to a looser ECM structure and deep penetration within the tumor parenchyma. Under NIR irradiation, both photothermal and photodynamic effects were produced and the encapsulated chemotherapeutic drugs were released effectively, exerting a strong synergistic antitumor effect. Moreover, this nanoplatform has X-ray attenuation properties that could serve to guide and monitor treatment by CT imaging. CONCLUSION: This work presented a unique and facile yet effective strategy to modulate ECM components in PDAC, enhance tumor penetration and tumor-killing effects and provide therapeutic guidance and monitoring.

Ultra-thin layered double hydroxide-mediated photothermal therapy combine with asynchronous blockade of PD-L1 and NR2F6 inhibit hepatocellular carcinoma.

BACKGROUND: The efficacy of immune checkpoint blockade (ICB), in the treatment of hepatocellular carcinoma (HCC), is limited due to low levels of tumor-infiltrating T lymphocytes and deficient checkpoint blockade in this immunologically "cool" tumor. Thus, combination approaches are needed to increase the response rates of ICB and induce synergistic antitumor immunity. METHODS: Herein, we designed a pH-sensitive multifunctional nanoplatform based on layered double hydroxides (LDHs) loaded with siRNA to block the intracellular immune checkpoint NR2F6, together with the asynchronous blockade surface receptor PD-L1 to induce strong synergistic antitumor immunity. Moreover, photothermal therapy (PTT) generated by LDHs after laser irradiation modified an immunologically "cold" microenvironment to potentiate Nr2f6-siRNA and anti-PD-L1 immunotherapy. Flow cytometry was performed to assess the immune responses initiated by the multifunctional nanoplatform. RESULTS: Under the slightly acidic tumor extracellular environment, PEG detached and the re-exposed positively charged LDHs enhanced tumor accumulation and cell uptake. The accumulated siRNA suppressed the signal of dual protumor activity in both immune and H22 tumor cells by silencing the NR2F6 gene, which further reduced the tumor burden and enhanced systemic antitumor immunity. The responses include enhanced tumor infiltration by CD4+ helper T cells, CD8+ cytotoxic T cells, and mature dendritic cells; the significantly decreased level of immune suppressed regulator T cells. The therapeutic responses were also attributed to the production of IL-2, IFN-γ, and TNF-α. The prepared nanoparticles also exhibited potential magnetic resonance imaging (MRI) ability, which could serve to guide synergistic immunotherapy treatment. CONCLUSIONS: In summary, the three combinations of PTT, NR2F6 gene ablation and anti-PD-L1 can promote a synergistic immune response to inhibit the progression of primary HCC tumors and prevent metastasis. This study can be considered a proof-of-concept for the targeting of surface and intracellular immune checkpoints to supplement the existing HCC immunotherapy treatments.

Self-amplification of oxidative stress with tumour microenvironment-activatable iron-doped nanoplatform for targeting hepatocellular carcinoma synergistic cascade therapy and diagnosis.

BACKGROUND: Hepatocellular carcinoma is insensitive to many chemotherapeutic agents. Ferroptosis is a form of programmed cell death with a Fenton reaction mechanism. It converts endogenous hydrogen peroxide into highly toxic hydroxyl radicals, which inhibit hepatocellular carcinoma progression. METHODS: The morphology, elemental composition, and tumour microenvironment responses of various organic/inorganic nanoplatforms were characterised by different analytical methods. Their in vivo and in vitro tumour-targeting efficacy and imaging capability were analysed by magnetic resonance imaging. Confocal microscopy, flow cytometry, and western blotting were used to investigate the therapeutic efficacy and mechanisms of complementary ferroptosis/apoptosis mediated by the nanoplatforms. RESULTS: The nanoplatform consisted of a silica shell doped with iron and disulphide bonds and an etched core loaded with doxorubicin that generates hydrogen peroxide in situ and enhances ferroptosis. It relied upon transferrin for targeted drug delivery and could be activated by the tumour microenvironment. Glutathione-responsive biodegradability could operate synergistically with the therapeutic interaction between doxorubicin and iron and induce tumour cell death through complementary ferroptosis and apoptosis. The nanoplatform also has a superparamagnetic framework that could serve to guide and monitor treatment under T2-weighted magnetic resonance imaging. CONCLUSION: This rationally designed nanoplatform is expected to integrate cancer diagnosis, treatment, and monitoring and provide a novel clinical antitumour therapeutic strategy.

Development of a Novel Multiparametric MRI Radiomic Nomogram for Preoperative Evaluation of Early Recurrence in Resectable Pancreatic Cancer.

BACKGROUND: In pancreatic cancer, methods to predict early recurrence (ER) and identify patients at increased risk of relapse are urgently required. PURPOSE: To develop a radiomic nomogram based on MR radiomics to stratify patients preoperatively and potentially improve clinical practice. STUDY TYPE: Retrospective. POPULATION: We enrolled 303 patients from two medical centers. Patients with a disease-free survival ≤12 months were assigned as the ER group (n = 130). Patients from the first medical center were divided into a training cohort (n = 123) and an internal validation cohort (n = 54). Patients from the second medical center were used as the external independent validation cohort (n = 126). FIELD STRENGTH/SEQUENCE: 3.0T axial T1 -weighted (T1 -w), T2 -weighted (T2 -w), contrast-enhanced T1 -weighted (CET1 -w). ASSESSMENT: ER was confirmed via imaging studies as MRI or CT. Risk factors, including clinical stage, CA19-9, and radiomic-related features of ER were assessed. In addition, to determine the intra- and interobserver reproducibility of radiomic features extraction, the intra- and interclass correlation coefficients (ICC) were calculated. STATISTICAL TESTS: The area under the receiver-operator characteristic (ROC) curve (AUC) was used to evaluate the predictive accuracy of the radiomic signature in both the training and test groups. The results of decision curve analysis (DCA) indicated that the radiomic nomogram achieved the most net benefit. RESULTS: The AUC values of ER evaluation for the radiomics signature were 0.80 (training cohort), 0.81 (internal validation cohort), and 0.78 (external validation cohort). Multivariate logistic analysis identified the radiomic signature, CA19-9 level, and clinical stage as independent parameters of ER. A radiomic nomogram was then developed incorporating the CA19-9 level and clinical stage. The AUC values for ER risk evaluation using the radiomic nomogram were 0.87 (training cohort), 0.88 (internal validation cohort), and 0.85 (external validation cohort). DATA CONCLUSION: The radiomic nomogram can effectively evaluate ER risks in patients with resectable pancreatic cancer preoperatively, which could potentially improve treatment strategies and facilitate personalized therapy in pancreatic cancer. LEVEL OF EVIDENCE: 4 Technical Efficacy: Stage 4 J. Magn. Reson. Imaging 2020;52:231-245.

Grade 3 Pancreatic Neuroendocrine Tumors on MDCT: Establishing a Diagnostic Model and Comparing Survival Against Pancreatic Ductal Adenocarcinoma.

OBJECTIVE. The purpose of this study is to establish a diagnostic model for differentiating grade 3 (G3) pancreatic neuroendocrine tumors (PNETs) from pancreatic ductal adenocarcinomas (PDACs) and to analyze survival outcomes. MATERIALS AND METHODS. Twenty patients with G3 PNETs and 58 patients with PDACs confirmed by surgery or biopsy were retrospectively included. Demographic and radiologic information was collected. Univariate analyses and binary logistic regression analyses were performed to identify independent factors and establish a diagnostic model. An ROC curve was created to determine diagnostic ability. Kaplan-Meier survival analysis was performed. RESULTS. Patients with G3 PNETs were more likely to present with normal carbohydrate antigen (CA) 19-9 levels, normal pancreatic ducts, and round tumors with well-defined margins and higher portal enhancement ratios than were patients with PDAC (p < 0.05). After multivariate analysis, a normal CA 19-9 level (odds ratio, 0.0125; 95% CI, 0.0008-0.2036), round tumor shape (odds ratio, 0.0143; 95% CI, 0.0004-0.5461), and pancreatic duct dilation of 4 mm or less (odds ratio, 17.9804; 95% CI, 1.0098-320.1711) were independent predictors of G3 PNETs. The AUC of the ROC curve was 0.916, and sensitivity and specificity were 90.0% and 81.0%, respectively. Furthermore, patients with G3 PNETs had better overall survival than patients with PDACs. Among patients in the G3 PNET subgroup, patients with liver or lymph node metastases had worse overall survival than patients without metastases. CONCLUSION. A diagnostic model was established to differentiate G3 PNETs from PDACs. A normal CA 19-9 level, round tumor shape, and pancreatic duct dilation of 4 mm or less were factors that were strongly predictive of G3 PNET.

A prognostic nomogram in patients with distant metastasis of pancreatic neuroendocrine tumors: a population-based study.

Aim: Prognostic factors in patients with distant metastatic pancreatic neuroendocrine tumors (PNETs) remain uncertain. The purpose of our study is to establish a nomogram to predict survival outcomes in patients with metastatic PNETs. Methods: A total of 878 patients diagnosed with PNETs in the Surveillance, Epidemiology and End Results database between 2004 and 2016 were retrospectively identified. The Kaplan-Meier survival analysis with log-rank test was used to analyze survival outcomes. The nomogram was established after a univariate and multivariate Cox analysis. Results: The independent prognostic variables, including age, tumor grade and primary site surgery were applied to develop a nomogram. The original concordance index was 0.773 (95% CI: 0.751-0.795), and the bias-corrected concordance index was 0.769 (95% CI: 0.748-0.791). The internal calibration curves showed well consistency and veracity in predicting cancer-specific survival probabilities. Conclusion: A nomogram was constructed and verified to predict survival outcomes in patients with distant-stage PNETs.

Polysialic-Acid-Based Micelles Promote Neural Regeneration in Spinal Cord Injury Therapy.

Spinal cord injury (SCI) routinely causes the immediate loss and disruption of neurons followed by complicated secondary injuries, including inflammation, oxidative stress, and dense glial scar formation. Inhibitory factors in the lesion scar and poor intrinsic neural regeneration capacity restrict functional recovery after injury. Minocycline, which has neuroprotective activity, can alleviate secondary injury, but the long-term administration of this drug may cause toxicity. Polysialic acid (PSA) is a large cell-surface carbohydrate that is critical for central nervous system development and is capable of promoting precursor cell migration, axon path finding, and synaptic remodeling; thus, PSA plays a vital role in tissue repair and regeneration. Here, we developed a PSA-based minocycline-loaded nanodrug delivery system (PSM) for the synergistic therapy of spinal cord injury. The prepared PSM exerted marked anti-inflammatory and neuroprotective activities both in vitro and in vivo. The administration of PSM could significantly protect neurons and myelin sheaths from damage, reduce the formation of glial scar, recruit endogenous neural stem cells to the lesion site, and promote the regeneration of neurons and the extension of long axons throughout the glial scar, thereby largely improving the locomotor function of SCI rats and exerting a superior therapeutic effect. The findings might provide a novel strategy for SCI synergistic therapy and the utilization of PSA in other central nervous system diseases.

Association of Modified-FOLFIRINOX-Regimen-Based Neoadjuvant Therapy with Outcomes of Locally Advanced Pancreatic Cancer in Chinese Population.

LESSONS LEARNED: Modification of FOLFIRINOX significantly improves safety and tolerability in Chinese patients with locally advanced pancreatic cancer.Patients with locally advanced pancreatic cancer benefit from neoadjuvant therapy and experience a much better survival than patients with upfront surgery. BACKGROUND: The objective of this study was to evaluate the efficacy of modified-FOLFIRINOX (mFOLFIRINOX) regimens in Chinese patients with locally advanced pancreatic cancer (LAPC) and to compare outcomes between patients with LAPC treated with mFOLFIRINOX-based neoadjuvant therapy (LAPC-N) and patients with LAPC who underwent upfront surgery (LAPC-S). METHODS: Forty-one patients with LAPC-N were enrolled prospectively. Imaging features, chemotherapy response, adverse events, perioperative complications, histology, and survival were analyzed. Seventy-four patients with resectable pancreatic cancer (RPC) (from April 2012 to November 2017) and 19 patients with LAPC-S (from April 2012 to March 2014) were set as observational cohorts, and data were collected retrospectively. LAPC-N patients with adequate response underwent surgical treatment, whereas continuous chemotherapy was given to LAPC-N patients who were not deemed resectable after treatment, and the response was re-evaluated every 2 months. RESULTS: Forty-one patients with LAPC received mFOLFIRINOX with a response rate of 37.1%. The most common severe adverse events were neutropenia and anemia. mFOLFIRINOX-based neoadjuvant therapy contributed to a remarkable decrease in CA19-9 level and tumor diameter. Fourteen LAPC-N patients underwent surgery (LAPC-N-S) after downstaging. Compared with LAPC-N-S cases, LAPC-S patients had longer operative time, more blood loss, and a higher risk of grade 5 complications. The median overall survival (OS) and progression-free survival (PFS) of LAPC-N-S patients were 27.7 months and 19.3 months, respectively, which were similar to those of patients with RPC (30.0 months and 23.0 months) and much longer than those of patients with LAPC-S (8.9 months and 7.6 months), respectively. CONCLUSION: Neoadjuvant chemotherapy such as the mFOLFIRINOX regimen can be recommended for Chinese patients with LAPC after dose modification. Patients with LAPC-N who underwent surgery obtained significantly improved survival compared with patients in the observational LAPC-S cohort, who did not undergo neoadjuvant therapy.

Targeting Pancreatic Cancer Cells with Peptide-Functionalized Polymeric Magnetic Nanoparticles.

Pancreatic cancer is a concealed and highly malignant tumor, and its early diagnosis plays an increasingly weighty role during the course of cancer treatment. In this study, we developed a polymeric magnetic resonance imaging (MRI) nanoplatform for MRI contrast agents. To improve tumor-targeting delivery of MRI contrast agents, we employed a pancreatic cancer targeting CKAAKN peptide to prepare a peptide-functionalized amphiphilic hyaluronic acid-vitamin E succinate polymer (CKAAKN-HA-VES) for delivering ultra-small superparamagnetic iron oxide (USPIO), namely, CKAAKN-HA-VES@USPIO. With the modification of the CKAAKN peptide, CKAAKN-HA-VES@USPIO could specifically internalize into CKAAKN-positive BxPC-3 cells. The CKAAKN-HA-VES@USPIO nanoparticles presented a more specific accumulation into pancreatic cancer cells than normal pancreatic cells, and an obvious decrease in signal intensity was observed in CKAAKN-positive BxPC-3 cells, compared with CKAAKN-negative HPDE6-C7 cells and non-targeting HA-VES@USPIO nanoparticles. The results demonstrated that our polymeric MRI nanoplatform could selectively internalize into CKAAKN-positive pancreatic cancer cells by the specific binding of CKAAKN peptide with pancreatic cancer cell membrane receptors, which provided a novel polymeric MRI contrast agent with high specificity for pancreatic cancer diagnosis, and makes it a very promising candidate for magnetic resonance imaging contrast enhancement.

Visual targeted therapy of hepatic cancer using homing peptide modified calcium phosphate nanoparticles loading doxorubicin guided by T1 weighted MRI.

Effective treatment and real-time monitoring of hepatic cancer are essential. A multifunctional calcium phosphate nanoparticles loading chemotherapeutic agent doxorubicin and magnetic resonance imaging contrast agent diethylenetriaminepentaacetic acid gadolinium (A54-CaP/Gd-DTPA/DOX) was developed for visual targeted therapy of hepatic cancer via T1-weighted MRI in real-time. A54-CaP/Gd-DTPA/DOX exhibited a higher longitudinal relaxivity (6.02 mM-1 s-1) than commercial MR contrast agent Gd-DTPA (3.3765 mM-1 s-1). The DOX release from the nanoparticles exhibited a pH dependent behavior. The cellular uptake results showed that the internalization of A54-CaP/Gd-DTPA/DOX into BEL-7402 cells was1.9-fold faster than that of HepG2 cells via A54 binding. In vivo experiments presented that A54-CaP/Gd-DTPA/DOX had higher distribution and longer retention time in tumor tissue than CaP/Gd-DTPA/DOX and free DOX, and also displayed great antitumor efficacy (95.38% tumor inhibition rate) and lower toxicity. Furthermore, the Gd-DTPA entrapped in the nanoparticles could provide T1-weighted MRI for real-time monitoring the progress of tumor treatment.

A preoperative nomogram predicts prognosis of up front resectable patients with pancreatic head cancer and suspected venous invasion.

BACKGROUND: Pancreatic head adenocarcinoma is commonly diagnosed at an advanced stage when adjacent vascular invasion is present. This study aimed to establish a preoperative prognostic nomogram for patients who underwent attempted curative resectional surgery for pancreatic head cancer with suspected peripancreatic venous invasion. METHODS: Data on all consecutive patients were retrospectively collected from 2012 to 2016 at four academic institutions. The demographic and radiological parameters were analyzed using univariate and multivariate Cox regression analyses. The final nomogram was established using the concordance Harrell's C-indices and calibration curves from data obtained in three institutions and validated in the cohort of patients coming from the fourth institution. RESULTS: The nomogram was constructed using data from 178 patients while the validation cohort consisted of 61 patients. Age, length of tumor contact, peripancreatic venous abnormalities and lymph node staging were independent factors of overall survival. The nomogram showed good probabilities of survival on calibration curves. The C-index of the model in predicting overall survival (OS) was 0.824 for the validation cohort. CONCLUSIONS: The nomogram accurately predicted OS in patients with pancreatic head cancer with suspected peripancreatic venous invasion after attempted curative pancreatic resectional surgery.

Overactivation of corticotropin-releasing factor receptor type 1 and aquaporin-4 by hypoxia induces cerebral edema.

Cerebral edema is a potentially life-threatening illness, but knowledge of its underlying mechanisms is limited. Here we report that hypobaric hypoxia induces rat cerebral edema and neuronal apoptosis and increases the expression of corticotrophin releasing factor (CRF), CRF receptor type 1 (CRFR1), aquaporin-4 (AQP4), and endothelin-1 (ET-1) in the cortex. These effects, except for the increased expression of CRF itself, could all be blocked by pretreatment with an antagonist of the CRF receptor CRFR1. We also show that, in cultured primary astrocytes: (i) both CRFR1 and AQP4 are expressed; (ii) exogenous CRF, acting through CRFR1, triggers signaling of cAMP/PKA, intracellular Ca(2+), and PKCε; and (iii) the up-regulated cAMP/PKA signaling contributes to the phosphorylation and expression of AQP4 to enhance water influx into astrocytes and produces an up-regulation of ET-1 expression. Finally, using CHO cells transfected with CRFR1(+) and AQP4(+), we show that transfected CRFR1(+) contributes to edema via transfected AQP4(+). In conclusion, hypoxia triggers cortical release of CRF, which acts on CRFR1 to trigger signaling of cAMP/PKA in cortical astrocytes, leading to activation of AQP4 and cerebral edema.