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The interactions between aromatic molecules and metal nanoparticles are ubiquitous in nanotechnology. Currently, π-metal interactions under ambient conditions are well appreciated for VIIIB but not for IB metals. Here, we demonstrate the direct probing of π-metal interactions under ambient conditions with molecular specificity using surface-enhanced Raman spectroscopy (SERS), which reveals that aromatic hydrocarbons adsorb strongly from solution onto the surfaces of Ag and Au nanoparticles, provided there is no surface oxidation. Theoretical modeling shows that this adsorption is driven by dispersive π-metal interactions and that the aromatic molecules co-adsorb alongside surface ligands that are present initially on the nanosurface. Finding direct evidence for this long-neglected interaction has significant implications for various applications. This is demonstrated with SERS sensing of an aromatic drug molecule whose structure would typically suggest it to be weakly adsorbing, and indeed it is not detected on conventional Ag colloids due to surface oxidation, but it is found to adsorb strongly onto Au particles.

Peritoneal recurrence is the predominant pattern of relapse after curative-intent surgery for gastric cancer and portends a dismal prognosis. Accurate individualised prediction of peritoneal recurrence is crucial to identify patients who might benefit from intensive treatment. We aimed to develop predictive models for peritoneal recurrence and prognosis in gastric cancer.In this retrospective multi-institution study of 2320 patients, we developed a multitask deep learning model for the simultaneous prediction of peritoneal recurrence and disease-free survival using preoperative CT images. Patients in the training cohort (n=510) and the internal validation cohort (n=767) were recruited from Southern Medical University, Guangzhou, China. Patients in the external validation cohort (n=1043) were recruited from Sun Yat-sen University Cancer Center, Guangzhou, China. We evaluated the prognostic accuracy of the model as well as its association with chemotherapy response. Furthermore, we assessed whether the model could improve the ability of clinicians to predict peritoneal recurrence.The deep learning model had a consistently high accuracy in predicting peritoneal recurrence in the training cohort (area under the receiver operating characteristic curve [AUC] 0·857; 95% CI 0·826-0·889), internal validation cohort (0·856; 0·829-0·882), and external validation cohort (0·843; 0·819-0·866). When informed by the artificial intelligence (AI) model, the sensitivity and inter-rater agreement of oncologists for predicting peritoneal recurrence was improved. The model was able to predict disease-free survival in the training cohort (C-index 0·654; 95% CI 0·616-0·691), internal validation cohort (0·668; 0·643-0·693), and external validation cohort (0·610; 0·583-0·636). In multivariable analysis, the model predicted peritoneal recurrence and disease-free survival independently of clinicopathological variables (p0·0001 for all). For patients with a predicted high risk of peritoneal recurrence and low survival, adjuvant chemotherapy was associated with improved disease-free survival in both stage II disease (hazard ratio [HR] 0·543 [95% CI 0·362-0·815]; p=0·003) and stage III disease (0·531 [0·432-0·652]; p0·0001). By contrast, chemotherapy had no impact on disease-free survival for patients with a predicted low risk of peritoneal recurrence and high survival. For the remaining patients, the benefit of chemotherapy depended on stage: only those with stage III disease derived benefit from chemotherapy (HR 0·637 [95% CI 0·484-0·838]; p=0·001).The deep learning model could allow accurate prediction of peritoneal recurrence and survival in patients with gastric cancer. Prospective studies are required to test the clinical utility of this model in guiding personalised treatment in combination with clinicopathological criteria.None.

Summary: Background: The tumour stroma microenvironment plays an important part in disease progression and its composition can influence treatment response and outcomes. Histological evaluation of tumour stroma is limited by access to tissue, spatial heterogeneity, and temporal evolution. We aimed to develop a radiological signature for non-invasive assessment of tumour stroma and treatment outcomes. Methods: In this multicentre, retrospective study, we analysed CT images and outcome data of 2209 patients with resected gastric cancer from five independent cohorts recruited from two centres (Nanfang Hospital of Southern Medical University [Guangzhou, China] and Sun Yat-sen University Cancer Center [Guangzhou, China]). Patients with histologically confirmed gastric cancer, at least 15 lymph nodes harvested, preoperative abdominal CT available, and complete clinicopathological and follow-up data were eligible for inclusion. Tumour tissue was collected for patients in the training cohort (321 patients), internal validation cohort one (246 patients), and external validation cohort one (128 patients). Four stroma classes were defined according to the protein expression of α-smooth muscle actin and periostin assessed by immunohistochemistry. The primary objective was to predict the histologically based stroma classes by using preoperative CT images. We trained a deep convolutional neural network model using the training cohort and tested the model in the internal and external validation cohort one. We evaluated the model's association with prognosis in the training cohort, two internal, and two external validation cohorts and compared outcomes of patients who received or did not receive adjuvant chemotherapy. Findings: The deep-learning model achieved a high diagnostic accuracy for assessing tumour stroma in both internal validation cohort one (area under the receiver operating characteristic curve [AUC] 0·96–0·98]) and external validation cohort one (AUC 0·89–0·94). The stromal imaging signature was significantly associated with disease-free survival and overall survival in all cohorts (p

Background To systematically investigate structural and functional abnormalities in subregions of the basal forebrain (BF) using structural and resting-state fMRI, and to examine their clinical relevance in short-term and chronic insomnia disorder (ID). Methods Thirty-four patients with short-term ID, 41 patients with chronic ID, and 46 healthy controls (HCs) were recruited. Grey matter volume and seed-based resting-state functional connectivity (RSFC) in each BF subregion (Ch1,2,3 and 4) were computed and compared among the three groups. Spearman correlation was used to estimate the relationships between MRI-based alterations and clinical variables. Results The short-term group exhibited lower RSFC with the bilateral striatum and bilateral Ch_4 than HCs and the chronic group. In the left Ch_4, subjects in the chronic group exhibited lower RSFC with the left middle cingulate cortex than HCs and the short-term group. The short-term group exhibited lower RSFC with the left parahippocampal gyrus (PHG) than HCs and the chronic group. The chronic group exhibited the highest RSFC with the left middle frontal gyrus (MFG), followed by HCs and the short-term group. In the right Ch_4, the chronic group exhibited the lowest RSFC with the right superior temporal gyrus, followed by HCs and the short-term group. Moreover, in the short-term group, negative correlations were found between the left Ch_4 and left MFG RSFC and Epworth Sleepiness Scale scores. Conclusions These findings suggest that the Ch_4 may be a key node for establishing diagnostic and categorical biomarkers of ID, which could be useful in developing more effective treatment strategies for insomnia.

Background The tumor immune microenvironment can provide prognostic and predictive information. A previously validated ImmunoScore of Gastric Cancer (ISGC) evaluates both lymphoid and myeloid cells in the tumor core and invasive margin with immunohistochemical staining of surgical specimens. We aimed to develop a noninvasive radiomics-based predictor of ISGC. Patients and methods In this retrospective study including four independent cohorts of 1778 patients, we extracted 584 quantitative features from the intratumoral and peritumoral regions on contrast-enhanced computed tomography images. A radiomic signature [radiomics ImmunoScore (RIS)] was constructed to predict ISGC using regularized logistic regression. We further evaluated its association with prognosis and chemotherapy response. Results A 13-feature radiomic signature for ISGC was developed and validated in three independent cohorts (area under the curve = 0.786, 0.745, and 0.766). The RIS signature was significantly associated with both disease-free and overall survival in the training and all validation cohorts [hazard ratio (HR) range: 0.296–0.487, all P Conclusion The RIS is a reliable tool for evaluation of immunoscore and retains the prognostic significance in gastric cancer. Future prospective studies are required to confirm its potential to predict treatment response and select patients who will benefit from chemotherapy.

Building easy-to-handle bulk materials with nanoproperties is crucial for many nanotechnology-based real-world applications. Here, we describe a simple one-pot method based on nanoparticle self-assembly of pickering emulsions and in situ polymer deposition for preparing particles consisting of a rigid micro-polymer core covered in exposed surface layers of nanoparticles, which we have named nano-micro-particles (NMPs). Unlike simple colloids, these NMPs can be filtered off from the aqueous suspensions in which they are prepared and dried to form free-flowing powders, which most importantly, retain the properties of the constituent nanoparticles in the surface layer. These NMPs can be stored for extended periods but then used either in the dry state or be re-suspended into liquid media as required. The preparation method is very general and can be readily extended to assemble various types of nanoparticles regardless of their material composition or morphology. In addition, functional components, such as magnetic particles or fluorescent tags, can be encapsulated within the polymer core. This method is a platform technology for building nanoparticles into bulk materials with nano-functionalities tailored toward real-life applications. This is illustrated with examples of the preparation of NMPs suitable for rapid and low-cost on-site water monitoring and remediation.

Purpose To assess the role of histogram analysis of apparent diffusion coefficient (ADC) maps based on whole-tumor in differentiating intracranial solitary fibrous tumor/hemangiopericytoma (SFT/HPC) from angiomatous meningioma (AM). Materials and methods Pathologically confirmed intracranial SFT/HPC (n = 15) and AM (n = 20) were retrospectively collected and their clinical and conventional MRI features were analyzed. Diffusion-weighted (DW) images (b = 0 and 1000 s/mm2) were processed with the mono-exponential model. Regions of interest covering the whole tumor were drawn on all slices of the ADC maps to obtain histogram parameters, including mean ADC (ADCmean), median ADC (ADCmedian), maximum ADC (ADCmax), minimum ADC (ADCmin), skewness and kurtosis, as well as the 5th, 10th, 25th, 75th, 90th and 95th percentile ADC (ADC5, ADC10, ADC25, ADC75, ADC90 and ADC95). Differences of histogram parameters between SFT/HPC and AM were compared using Mann-Whitney U test. Receiver operating characteristic (ROC) curve was used to determine the diagnostic performance. Results The ADCmin (P = 0.001) and ADC5 (P = 0.045) were significantly lower in SFT/HPCs than in AMs, while no significant difference was found in sex, age, conventional MRI features or any other histogram parameters between the two entities (P = 0.051−1.000). ADCmin showed the best diagnostic performance (area under curve [AUC], 0.86; sensitivity, 81.3%; specificity, 83.3%) in differentiating SFT/HPC from AM with optimal cutoff value being 569.00 × 10−6 mm2/s, followed by ADC5 (AUC, 0.72; sensitivity, 68.8%; specificity, 75%) with optimal cutoff value being 781.97 × 10−6 mm2/s. Conclusion SFT/HPC and AM share similar conventional MR appearances. Whole-tumor histogram analysis of ADC maps may be a useful tool for differential diagnosis, with ADCmin and ADC5 being potential parameters.

This study aimed to develop and validate a prognostic nomogram for recurrence-free survival (RFS) after surgery in the absence of adjuvant therapy to guide the selection for adjuvant imatinib therapy based on Residual Neural Network (ResNet).The ResNet model was developed based on contrast-enhanced computed tomography (CE-CT) in a training cohort consisted of 80 patients pathologically diagnosed gastrointestinal sromal tumors (GISTs) and validated in internal and external validation cohort respectively. Independent clinicopathologic factors were integrated with the ResNet model to construct the individualized nomogram. The performance of the nomogram was evaluated in regard to discrimination, calibration, and clinical usefulness.The ResNet model was significantly associated with RFS. Integrable predictors in the individualized ResNet nomogram included the tumor site, size, and mitotic count. Compared with modified NIH, AFIP, and clinicopathologic nomogram, both ResNet nomogram and ResNet model showed a better discrimination capability with AUCs of 0·947(95%CI, 0·910–0·984) for 3-year-RFS, 0·918(0·852–0·984) for 5-year-RFS, and AUCs of 0·912 (0·851–0·973) for 3-year-RFS, 0·887(0·816–0·960) for 5-year-RFS, respectively. Calibration curve shows the good calibration of the nomogram in terms of the agreement between the estimated and the observed 3- and 5- year outcomes. Decision curve analysis showed that the ResNet nomogram had a higher overall net benefit.In conclusion, we presented a deep learning-based prognostic nomogram to predict RFS after resection of localized primary GISTs with excellent performance and could be a potential tool to select patients for adjuvant imatinib therapy. Keywords: Gastrointestinal Stromal Tumors, Deep Learning, Residual Neural Network, Recurrence-free Survival, Imatinib

Thin, flexible, surface-active, polystyrene-based, optically transparent films, embedded with a coating of commercially sourced titanium dioxide nanoparticles (Evonik P25), are made by coupling protonated TiO2 particles with an anionic phase transfer agent (tetraphenylborate), to create an ion-paired species that is drawn to a water/dichloromethane (DCM) interface to form a monolayer. The latter is subsequently embedded in a thin polystyrene (PS) film, typically 2.5 μm thick, by allowing the DCM to evaporate. The resulting clear TiO2 Surface-Exposed Nanoparticle (TiO2-SEN) thin plastic films are characterised using scanning electron microscopy (SEM) and found to have 25.3 ± 5.4 nm TiO2 nanoparticles exposed to the air on one side and PS on the other. The photocatalytic activity of these films is demonstrated using a number of different tests including: the photo-oxidation of 4-chlorophenol (4-CP) and methylene blue (MB) and the photoreduction of resazurin (Rz) and MB. In most of these tests the photoactivity of the film is more than double compared to that of a commercial photocatalytic film, Activ™.

Often chemical analysis of solid materials begins with dissolving the sample in a solvent but this is undesirable, particularly if the physical form is important. In principle surface-enhanced Raman spectroscopy (SERS) should allow detection of solid analytes and offers attomolar sensitivity combined with molecular specificity. SERS requires the target molecules to sit in plasmonic hot-spots, which are normally nanojunctions, just a few nm across. This means that solid samples normally need to be dissolved in a solvent so they can diffuse into the enhancing region. Here, we show that SERS spectra of picograms of solid analytes can be directly obtained by pressing them into a flexible SERS substrate with a dense field of exposed nanojunction hot-spots anchored on its surface. We demonstrate that this can be a powerful tool for straightforward and non-destructive forensic analysis of layered materials (crossing ink lines), solid explosives and illicit drugs as well as for studying previously intractable samples such as pharmaceutical co-crystals, whose important solid state structure is lost when they are dissolved.

To develop and validate a radiomics signature for the prediction of gastric cancer (GC) survival and chemotherapeutic benefits. In this multicenter retrospective analysis, we analyzed the radiomics features of portal venous-phase computed tomography in 1591 consecutive patients. A radiomics signature was generated by using the Lasso-Cox regression model in 228 patients and validated in internal and external validation cohorts. Radiomics nomograms integrating the radiomics signature were constructed, demonstrating the incremental value of the radiomics signature to the traditional staging system for individualized survival estimation. The performance of the nomograms was assessed with respect to calibration, discrimination, and clinical usefulness. The radiomics signature consisted of 19 selected features and was significantly associated with DFS (disease-free survival) and OS (overall survival). Multivariate analysis demonstrated that the radiomics signature was an independent prognostic factor. Incorporating the radiomics signature into the radiomics-based nomograms resulted in better performance for the estimation of DFS and OS than the clinicopathological nomograms and TNM staging system, with improved accuracy of the classification of survival outcomes. Further analysis showed that stage II and III patients with higher radiomics scores exhibited a favorable response to chemotherapy. In conclusion, the newly developed radiomics signature is a powerful predictor of DFS and OS, and it may predict which patients with stage II and III GC benefit from chemotherapy.

Purpose To evaluate the value of intravoxel incoherent motion (IVIM) histogram analysis based on whole tumor volume in predicting microvascular invasion (MVI) of single hepatocellular carcinoma (HCC). Materials and Methods The study enrolled 41 patients with pathologically proven HCCs who underwent IVIM diffusion-weighted imaging with nine b values and contrast-enhanced magnetic resonance imaging (MRI). Histogram parameters including mean; skewness; kurtosis; and percentiles (5th, 10th, 25th, 50th, 75th, 90th, 95th) were derived from apparent diffusion coefficient (ADC), perfusion fraction (f), true diffusion coefficient (D), and pseudo diffusion coefficient (D*). Quantitative histogram parameters and clinical data were compared between HCCs with and without MVI. For significant parameters, receiver operating characteristic (ROC) curves were further plotted to compare the diagnosis performance for identifying MVI. Results The mean, 5th, 10th, 25th, 50th, and 75th percentiles of D, and the 5th, 10th, and 25th percentiles of ADC between HCCs with and without MVI were statistically significant (all P＜0.05). The histogram parameters of D* and f showed no statistically significant differences between HCCs with and without MVI (all P＞0.05). The areas under the ROC curves (AUCs) were 0.707–0.874 for D and 0.668–0.720 for ADC. The largest AUC of D (5th percentile) showed significantly higher accuracy than that of ADC or tumor size (P = 0.009–0.046). With a cut-off of 0.403 × 10−3 mm²/s, the 5th percentile of D value provided a sensitivity of 81% and a specificity of 85% in the prediction of MVI. Conclusions Histogram analysis of IVIM based on whole tumor volume can be useful for predicting MVI. The 5th percentile of D was most useful value to predict MVI of HCC.

Ternary copper-based chalcogenide nanomaterials have become rather attractive due to the near-infrared (NIR) response in cancer theranostic fields. However, it is still challenging to further improve the theranostic efficiency of these nanomaterials. Herein, Cu-Sb-S nanoparticles (NPs) around 24 nm are synthesized facilely and functionalized with poly(vinylpyrrolidone) (PVP). Under the NIR irradiation, the resultant PVP-Cu-Sb-S NPs exhibit a relatively high photothermal conversion efficiency of 53.16% and a simultaneous reactive oxygen species (ROS) generation effect. Due to these outstanding photothermal/photodynamic effects, excellent tumor ablation results can be achieved by the combination of PVP-Cu-Sb-S NPs and 808 nm NIR laser treatments without obvious side effect. In addition, they show remarkable contrast enhancement according to in vitro and in vivo photoacoustic (PA) imaging. These PVP-Cu-Sb-S NPs could be served as a multifunctional nanotheranostic agent for PA imaging, photothermal/photodynamic cancer therapy. Statement of Significance Highly theranostic efficiency ternary copper-based chalcogenide nanomaterials has not been fully developed yet. Herein we report the PVP-Cu-Sb-S nanoparticles (NPs) with relatively high photothermal efficiency, simultaneous reactive oxygen species generation effect and photoacoustic imaging capability. The photothermal conversion efficiency of PVP-Cu-Sb-S NPs is higher than most of copper-based chalcogenide nanomaterials reported before. These findings provide a new kind of ternary copper-based chalcogenide with an enhanced theranostic effect, which could be served as a promising multifunctional nanotheranostic agent in the field of biomedical application.

To assess the value of T1ρ,T1ρ on hepatobiliary phase (HBP) and diffusion metrics in staging of Non-alcoholic fatty liver disease (NAFLD) activity scores, inflammation, fibrosis in NASH rabbits model. Non-alcoholic steatohepatitis (NASH) rabbits model was induced by feeding a varied duration of high-fat, high-cholesterol diet. T1ρ,T1ρ (HBP) 20min after administration of Gd-EOB-DTPA, and Intravoxel incoherent motion imaging (IVIM) diffusion-weighted imaging were performed on a 3.0T magnetic resonance (MR) imaging unit. The diagnostic value of each parameter for NAS, inflammation and fibrosis severity were determined. T1ρ (r=0.658) and T1ρ (HBP) (r=0.750) have strong association with NASH overall activity, T1ρ (HBP) is strongly relevant to inflammation stage (r=0.812). There was negative association between f and inflammation (r=-0.480), whilst no significant relation between other three parameters (apparent diffusion coefficient (ADC), pseudo-diffusion coefficient (D*) and true diffusion coefficient (D)) and inflammation or overall activity. The areas under the receiver operating characteristic curves (AUCs) of f, ADC, T1ρ and T1ρ-HBP were 0.871, 0.728, 0.849 and 0.949 for differentiating NASH; 0.731, 0.552, 0.925 and 0.922 for G2-3 inflammation; and 0.767, 0.625, 0.816, and 0.882 for S1-2 fibrosis. Comparison of ROC curve showed T1ρ (HBP) had an optimal diagnostic performance for NASH [T1ρ (HBP) vs ADC, AUC:0.949 vs 0.728, P=0.043], inflammation [T1ρ (HBP) vs ADC, AUC:0.922 vs 0.552, P=0.003], fibrosis [T1ρ (HBP) vs ADC, AUC:0.882 vs 0.625, P=0.046]. The combination of T1ρ (HBP)+perfusion fraction (f) showed highest diagnostic value for NASH (AUC:0.971), inflammation (AUC:0.935). Among T1ρ imaging and IVIM diffusion metrics, combination of T1rho (HBP)+f was found to be superior noninvasive imaging biomarker for NASH activity assessment.

In this work, a new benzothiazole based mitochondrial tracker, Bth-Mito, is synthesized by with 2-benzothiazoleacetonitrile and 4-(diethylamino)-benzaldehyde. Bth-Mito is weakly fluorescent when dissolved in the good solvent but becomes highly emissive in poor solvents, showing a phenomenon of aggregation-induced emission. Bth-Mito shows the greatest potentials for bioimaging applications in view of low cytotoxicity and high photostability. Bth-Mito could penetrate cells to give stable green fluorescence, even after continuous irradiation, making it suitable candidate for time-lapse and long-term bioimaging application. Moreover, Bth-Mito could specifically localize in mitochondrial. Furthermore, in vivo imaging studies on nude mice have revealed that Bth-Mito could be used as optical imaging probe for in vivo imaging. Histological assessment of tissues treated with Bth-Mito also further confirmed the low toxicity and good biocompatibility of Bth-Mito.

A novel fluorescence probe 1 based on triphenylamine was synthesized and characterized by NMR, IR, high resolution mass spectrometry and elemental analysis. Its fluorescence was quenched when pH below 2. There was a linear relationship between the fluorescence intensity and pH value ranged from 2 to 7. And its fluorescence emission was reversibility in acidic and alkaline solution. Furthermore, it exhibited remarkable selectivity and high sensitivity to Fe 3 + and was able to detect Fe 3 + in aqueous solution with low detection limit of 0.511 μM. Job plot showed that the binding stoichiometry of 1 with Fe 3 + was 1:1. Further observations of 1 H NMR titration suggested that coordination interaction between Fe 3 + and nitrogen atom on C N bond promoted the intramolecular charge transfer (ICT) or energy transfer process causing fluorescence quenching. Additionally, 1 was also able to be applied for detecting Fe 3 + in living cell and bioimaging.

Purpose Systemic lupus erythematosus (SLE) is a chronic inflammatory female-predominant autoimmune disease that can affect the central nervous system and exhibit neuropsychiatric symptoms. In SLE patients without neuropsychiatric symptoms (non-NPSLE), recent diffusion tensor imaging studies showed white matter abnormalities in their brains. The present study investigated the entire brain white matter structural connectivity in non-NPSLE patients by using probabilistic tractography and connectivity-based analyses. Methods Whole-brain structural networks of 29 non-NPSLE patients and 29 healthy controls (HCs) were examined. The structural networks were constructed with interregional probabilistic connectivity. Graph theory analysis was performed to investigate the topological properties, and network-based statistic was employed to assess the alterations of the interregional connections among non-NPSLE patients and controls. Results Compared with HCs, non-NPSLE patients demonstrated significantly decreased global and local network efficiencies and showed increased characteristic path length. This finding suggests that the global integration and local specialization were impaired. Moreover, the regional properties (nodal efficiency and degree) in the frontal, occipital, and cingulum regions of the non-NPSLE patients were significantly changed and negatively correlated with the disease activity index. The distribution pattern of the hubs measured by nodal degree was altered in the patient group. Finally, the non-NPSLE group exhibited decreased structural connectivity in the left median cingulate-centered component and increased connectivity in the left precuneus-centered component and right middle temporal lobe-centered component. Conclusion This study reveals an altered topological organization of white matter networks in non-NPSLE patients. Furthermore, this research provides new insights into the structural disruptions underlying the functional and neurocognitive deficits in non-NPSLE patients., Highlights • The global integration and local specialization of the white matter networks were disrupted in non-NPSLE patients. • The brain regions with significantly altered nodal properties were mainly involved in language, visual, and DMN systems. • The properties of some identified regions presented negative correlations with the SLE disease activity index scores. • The distribution pattern of the hubs measured by nodal degree was altered in the non-NPSLE patients. • The non-NPSLE group exhibited a subnetwork of decreased connectivity and a subnetwork of increased connectivity.

Background: The aim of this study is to evaluate whether radiomic feature-based computed tomography (CT) imaging signatures could predict peritoneal metastasis (PM) in gastric cancer (GC) and to develop a preoperative nomogram for predicting PM status. Methods: We retrospectively analyzed radiomics features of CT images in 955 consecutive patients in pathological T4 gastric cancer from two cancer centers. The prediction model which was built from 292 quantitative image features was developed in the training cohort and validated in internal and external validation cohorts. Lasso regression model was used for feature selection and radiomics signature building. Predicting model was developed by multivariable logistic regression analysis. Radiomics signature, clinical T and N stage were incorporated and presented with a radiomics nomogram. We use calibration, discrimination, and clinical usefulness to assess the performance of the nomogram. Results: The radiomics signature was significantly associated with PM status in training and validation cohorts. Multivariable logistic analysis found the radiomics signature was an independent predictor for peritoneal metastasis. The discrimination accuracies of radiomic signature for predicting PM were 0.751(95%CI, 0.703-0.799), 0.802(95%CI, 0.691-0.912), and 0.745(95%CI, 0.683-0.806) for training cohort, internal and external validation cohort, respectively. Further, the discrimination accuracies of radiomic nomogram for predicting PM were 0.792(95%CI, 0.748-0.836), 0.870(95%CI, 0.795-0.946) and 0.815(95%CI, 0.763-0.867) for training cohort, internal and external validation cohort, respectively. Conclusions: CT-based radiomic signature was a powerful predictor of peritoneal metastasis and the radiomics nomogram could facilitate the preoperative individualized prediction of PM status. Funding Statement: This work was supported by grants from: National Natural Science Foundation of China 81672446, 81600510. The Outstanding Youths Development Scheme of Nanfang Hospital, Southern Medical University (2018J007). Director’s Foundation of Nanfang Hospital, 2016B010. Declaration of Interests: None of the authors had any potential conflicts of interest, including relevant financial interests, activities, relationships, and affiliations. Ethics Approval Statement: This study was approved by the ethics committee at every participating center, and the informed consent requirement was waived.

Aims N6-Methyladenosine (m6A) is the most frequent posttranscriptional modification and plays important roles in tumorigenesis and metastasis. The roles of fat mass and obesity-associated (FTO) in metabolic diseases have been widely explored. However, the molecular mechanisms and physiological functions of FTO in prostate cancer remain largely unknown. This study aimed to explore the exact functions of FTO in the progression of prostate cancer metastasis. Main methods Dot blot and m6A RNA methylation quantification assays were performed to determine m6A levels. The protein and mRNA expression levels were detected using immunoblot (IB) and reverse transcription-quantitative polymerase chain reaction (RT-qPCR) analyses. Cell invasion and migration abilities were measured using transwell and wound healing assays. Bioinformatics was used to measure the expression level of FTO and possible correlation between FTO levels and advanced tumor stage. Immunofluorescence (IF) was performed to measure the cellular localization of FTO. Key findings FTO was downregulated in prostate cancer tissues and cell lines, and the m6A content was increased. Importantly, patients with lower FTO expression had advanced tumor stage and higher Gleason scores. Gain- and loss-of-function assays revealed that FTO inhibits prostate cancer cell invasion and migration in vitro. Moreover, we confirmed that FTO can decrease the total m6A level. Significance The present study revealed that the FTO m6A demethylase inhibits prostate cancer cell invasion and migration by regulating total m6A levels.

Thermo-chemical conversion is a promising technology for the recycle of waste plastics, as it can produce high-value products such as carbon nanotubes (CNTs) and hydrogen. However, the low yield of CNTs is one of the challenges. In this work, the addition of Mn (0 wt.%, 1 wt.%, 5 wt.%, and 10 wt.%) to Fe-based catalyst to improve the production of CNTs has been investigated. Results show that the increase of Mn content from 0 wt.% to 10 wt.% significantly promotes CNTs yield formed on the catalyst from 23.4 wt.% to 32.9 wt.%. The results show that Fe-particles in the fresh catalysts are between 10−25 nm. And the addition of Mn in the Fe-based catalyst enhanced the metal-support interactions and the dispersion of metal particles, thus leading to the improved catalytic performance in relation to filamentous carbon growth. In addition, the graphitization of CNTs is promoted with the increase of Mn content. Overall, in terms of the quantity and quality of the produced CNTs, 5 wt.% of Mn in Fe-based catalyst shows the best catalytic performance, due to the further increase of Mn content from 5 wt.% to 10 wt.% led to a dramatic decrease of purity by 10 wt.%.

Organo-soluble tetraphenylethylene derived monolayer-protected gold nanorods were prepared and characterized. The prepared gold nanorods covered with tetraphenylethylene thiol via the strong covalent Au–S linkage were found to be soluble and stable in organic solvents. The successful thiol exchange and modification of tetraphenylethylene derivative molecules on gold nanorods were confirmed from UV–Vis, Raman and FT-IR spectra. The gold nanorods were found to have a quenching effect on the aggregation-induced emission of the tetraphenylethylene thiol molecule modified on their surfaces.

Mitochondria are essential organelles in eukaryotic cells and act as the energy powerhouse and biosynthetic compartment. Fluorescent dyes are widely used powerful molecular tools for analytical sensing and optical imaging. Low photostability, short excitation and emission wavelengths, and aggregation-induced quenching effects restrict the application of traditional commercial mitochondrial fluorescent probes for bioimaging. In this study, using rhodamine as the acceptor and phenothiazine as the donor, we synthesized a novel mitochondrial-targeted near infrared (NIR) fluorescent probe, MIT-PZR. Due to low cytotoxicity, great photostability and high specificity for mitochondria targeting, MIT-PZR has enormous potential for cell imaging. Furthermore, with a sizeable Stokes shift (emission peak at 705 nm), MIT-PZR penetrated tissues providing stable red fluorescence for imaging in vivo. The histological assessment of various tissues after treatment with MIT-PZR indicated that it has good biocompatibility. Thus, MIT-PZR is a promising mitochondrial NIR fluorescent probe for future application in clinical diagnosis and modern biological research.

Purpose To determine whether imaging parameters derived from intravoxel incoherent motion (IVIM) diffusion weighted imaging (DWI) vary according to tumor-stroma ratio(TSR) or dominant stroma type of breast cancer. Methods We prospectively enrolled 77 patients with breast cancer who underwent IVIM DWI on a 3.0 T MR scanner. The values of IVIM parameters (D, D* and f) were measured. After surgery, TSR or dominant stroma type was evaluated. The relationship between imaging parameters and tumor stroma characteristics was analyzed. Results The mean D and f values were lower in stroma-poor tumor than in stroma-rich tumor (P = 0.012, 0.015). The mean D value was lower in the collagen-dominant type than in fibroblast-dominant or lymphocyte-dominant type (P = 0.032, 0.043). According to multivariate linear regression analyses, tumor size (P = 0.007), TSR (P = 0.008), dominant stroma type (collagen dominant, P = 0.012), and histological grade (P = 0.031) were independently correlated with D value; and tumor size (P = 0.011), TSR (P = 0.021) and histological grade (P = 0.037) were independently correlated with f value. Conclusion In breast cancer, D and f values show significant differences according to TSR, and D value is lower in collagen dominant type than in fibroblast dominant or lymphocyte dominant types.

To develop and validate a radiomics signature for prediction of gastric cancer (GC) survival and chemotherapeutic benefits. In this multicenter retrospective analysis, we analyzed radiomics features of portal venous-phase computed tomography in 1,591 consecutive patients. A radiomics signature was generated by using the Lasso-Cox regression model in 228 patients and validated in internal and external validation cohorts. Radiomics nomograms integrating the radiomics signature were constructed, demonstrating the incremental value of the radiomics signature to the traditional staging system for individualized survival estimation. The performance of the nomograms was assessed with respect to calibration, discrimination, and clinical usefulness. The radiomics signature consisted of 19 selected features and was significantly associated with DFS and OS. Multivariate analysis demonstrated that the radiomics signature was an independent prognostic factor. Incorporating the radiomics signature into the radiomics-based nomograms resulted in better performance for the estimation of DFS than the clinicopathologic nomograms and the TNM staging system, with improved accuracy of the classification of survival outcomes. Further analysis showed stage II and III patients with higher radiomics scores exhibited a favorable response to chemotherapy. In conclusion, the newly developed radiomics signature was a powerful predictor of OS and DFS. Moreover, the radiomics signature could predict which patients with stage II and III GC benefit from chemotherapy. Funding Statement: This work was supported by grants from: National Natural Science Foundation of China 81672446, 81600510, 81370575, 81570593. Natural Science Foundation of Guangdong Province, 2014A030313131. Science and Technology Planning Project of Guangzhou, 2014B020228003, 2014B030301041, 2015A030312013. Science and Technology Program of Guangzhou, 158100076, 201400000001-3. Public welfare in Health Industry, National Health and Family Planning Commission of China (201402015, 201502039). Key Clinical Specialty Discipline Construction Program. Declaration of Interests: The author(s) indicated no potential conflicts of interest. Ethics Approval Statement: Ethical approval was obtained for this retrospective analysis at every participating center, and the informed consent requirement was waved.

Introduction Several epidemiological studies have found a positive association between chronic hepatitis B virus (CHB) infection and the risk of placental abruption and placenta previa, but various studies have reported conflicting findings. The objective was to systematically review the literature to determine a possible association between CHB infection and these two placental complications. Methods We conducted a computerized search in electronic database through March 1, 2014, supplemented with a manual search of reference lists, to identify original published research on placental abruption and placenta previa rates in women with CHB infection. Data were independently extracted, and relative risks were calculated. The meta-analysis was performed using Stata version 10.0 software. Results Five studies involving 9088 placenta previa cases were identified. No significant association between CHB infection and placenta previa was identified (OR = 0.98, 95% CI = 0.60–1.62). Five studies involving 15571 placental abruption cases were identified. No significant association between CHB infection and placental abruption was identified (OR = 1.42, 95% CI, 0.93–2.15). Discussion The immune response against the virus represents a key factor in determining infection outcomes. No observation of significant increased risk of the placental complications could be partially explained by the complex immune response during CHB infection. Conclusions Our meta-analysis found no evidence of significant associations between CHB infection and increased risk of placental abruption as well as placenta previa. Further well-designed studies were warranted to assess any potential association between CHB infection and increased risk of placental abruption as well as placenta previa.

Objectives To evaluate the performance of region-of-interest (ROI)-based MRI R2* measurements by using the first-moment noise-corrected model (M1NCM) to correct the non-central Chi noise in magnitude images from phased arrays for hepatic iron content (HIC) assessment. Methods R2* values were quantified using the M1NCM model. Three approaches were employed to determine the representative R2*: fitting of the ROI-averaged signal (average-then-fit, ATF); outputting the median and mean of R2*s from the pixel-wise fitting of decay signals within the ROI (denoted as PWFmed and PWFmea, respectively). The accuracy and precision of the three approaches were evaluated on synthesized data. The agreement among these approaches and their intra- and inter-observer reproducibility were assessed on 105 thalassaemia major patients. Results Simulations showed that ATF consistently yielded the highest accuracy and precision at varying noise levels. By contrast, PWFmed and PWFmea slightly and significantly overestimated high R2* at poor signal-to-noise ratios, respectively. Patient study showed that ATF agreed well with PWFmed, whereas PWFmea produced high R2* measurements for patients with severe HIC. No significant difference was observed in the reproducibility of the three approaches. Conclusions PWFmea tends to overestimate high R2*, whereas ATF and PWFmed can produce more accurate R2* measurements for HIC assessment.

This study aimed to evaluate the amide proton transfer (APT) values in neonates with mild hypoxic-ischemic encephalopathy (HIE) using APT imaging.A total of 30 full-term neonates with mild HIE (16 males and 14 females; mean postnatal age 4.2 days, age range 2-7 days) and 12 normal neonates (six males and six females; mean postnatal age 3.3 days, age range 2-5 days) underwent conventional magnetic resonance imaging and APT imaging. APT measurements were performed in multiple regions of interest (ROIs) in the brain. APT values were statistically analyzed to assess for significant differences between the mild HIE and normal neonates in different regions of the brain, and correlation with neonatal gestational age.In 30 neonates with mild HIE, 10% (3/30) of the HIE patients had normal conventional MRI. There were significant differences in APT values of the HIE group in bilateral caudate, bilateral thalamus, bilateral centrum semiovale and left globus pallidus/putamen (p 0.05), and no statistical difference was observed in right globus pallidus/putamen (p = 0.051) and brainstem (p = 0.073) between the two groups. Furthermore, APT values in bilateral caudate, bilateral globus pallidus/putamen, bilateral thalamus, and brainstem regions (p 0.05) exhibited positive linear correlations with gestational age in the control group, except for bilateral centrum semiovale (right: Pearson's r = 0.554, p = 0.062; left: Pearson's r = 0.561, p = 0.058). In the mild HIE groups, no significant correlation with gestational age was found in all regions.APT imaging is a feasible and useful technique with diagnostic capability for neonatal HIE.

Objective To demonstrate the use of 3D-enhanced T2* weighted angiography (ESWAN) imaging for the observation and quantification of the evolution of brain injury induced by a recently developed model of hypoxic-ischemic brain injury (HI/R) in neonatal piglets. Methods For these experiments, newborn piglets were subjected to HI/R injury, during which ESWAN scanning was performed, followed by H&E staining and immunohistochemistry of AQP-4 expression. Results In the striatum, values from T2* weighted magnetic resonance imaging (MRI) increased and reached their highest level at 3 days post injury, whereas T2* values increased and peaked at 24 h in the subcortical region. The change in T2* values was concordant with brain edema. Phase values in the subcortical border region were not dependent on time post-injury. Magnitude values were significantly different from the control group, and increased gradually over time in the subcortical border region. Susceptibility-weighted images (SWI) indicated small petechial hemorrhages in the striatum and thalamus, as well as dilated intramedullary veins. Conclusion SWI images can be used to detect white and gray matter microhemorrhages and dilated intramedullary veins. The T2*, phase, and magnitude map can also reflect the development of brain injury. Our data illustrate that ESWAN imaging can increase the diagnostic sensitivity and specificity of MRI in neonatal hypoxic-ischemic encephalopathy.

Aim To compare intravoxel incoherent motion (IVIM) magnetic resonance imaging (MRI)-derived true diffusion (D) and perfusion fraction (f)-values of the two hemispheres to detect the presence of asymmetrical differences. Materials and methods Forty-seven healthy right-handed volunteers were assessed using IVIM imaging. The interhemispheric D- and f-values were compared using paired t-tests and two related-samples Wilcoxon's test. Results Comparison of the interhemispheric D- and f-values of the grey matter revealed a significant difference in the D-value of the frontal lobe and the f-value of the temporal lobe (p=0.028, p=0.030, respectively). A significant difference in the D-values of the frontal, temporal, and occipital lobes (p=0.003, p=0.005, and p=0.001, respectively) was seen, whereas no significant difference in f-values was seen. Conclusions The distribution of the IVIM-derived D- and f-values in the two hemispheres was not completely symmetrical. Radiologists should consider this difference when the contralateral region is used as internal reference to normalise the IVIM imaging results. Average values of the interhemispheric white matter within the same lobe as the lesion may be the best internal reference.