Topotactic Conversion of Titanium-Oxo Clusters to a Stable TOC-Based Metal-Organic Framework with the Selective Adsorption of Cationic Dyes.

Titanium-oxo cluster (TOC)-based metal-organic frameworks (MOFs) have received considerable attention in recent years due to their ability to expand the application of TOCs to fields that require highly stable frameworks. Herein, a new cyclic TOC formulated as [Ti6O6(OiPr)8(TTFTC)(phen)2]2 (1, where TTFTC = tetrathiafulvalene tetracarboxylate and phen = phenanthroline) was crystallographically characterized. TOC 1 takes a rectangular ring structure with two phen-modified Ti6 clusters as the width and two TTFTC ligands as the length. An intracluster ligand-to-ligand (TTF-to-phen) charge transfer in 1 was found for TOCs for the first time. Compound 1 undergoes topotactic conversion to generate stable TOC-MOF P1, in which the rectangular framework in 1 formed by a TOC core and ligands is retained, as verified by comprehensive characterization. P1 shows an efficient and rapid selective adsorption capacity for cationic dyes. The experimental adsorption capacity (qex) of P1 reaches a value of up to 789.2 mg/g at 298 K for the crystal violet dye, which is the highest among those of various adsorbents. The calculated models are first used to reveal the structure-property relationship of the cyclic host to different guest dyes. The results further confirmed the host MOF structure of P1.

Amide Proton Transfer-weighted MRI combined with serum prostate-specific antigen levels for differentiating malignant prostate lesions from benign prostate lesions: a retrospective cohort study.

BACKGROUND: Early diagnosis of prostate cancer improves its prognosis, while it is essential to upgrade screening tools. This study aimed to explore the value of a novel functional magnetic resonance imaging (MRI) technique, namely amide proton transfer (APT)-weighted MRI, combined with serum prostate-specific antigen (PSA) levels to differentiate malignant prostate lesions from benign prostate lesions. METHODS: Data of patients who underwent prostate examinations at Chongqing University Cancer Hospital between July 2019 and March 2022 were retrospectively analyzed. All patients underwent T2-weighted imaging (T2WI), APT, diffusion-weighted imaging (DWI), and dynamic contrast-enhanced (DCE) MRI. Two radiologists analyzed the images independently. The ability of the quantitative parameters alone or in different combinations in differentiating malignant prostate lesions from benign prostate lesions were compared by using receiver operating characteristic (ROC) curves. According to the DeLong test, the combined parameters were significantly different from the corresponding single parameter (P < 0.05). RESULTS: A total of 79 patients were finally enrolled, including 52 patients in the malignant group and 27 patients in the benign group. The separate assessment of indexes revealed that APTmax, APTmean, mean apparent diffusion coefficient (ADCmean), ADCmax, ADCmin, tPAD, free prostate-specific antigen (FPSA), FPSA/total prostate-specific antigen (tPSA), and PSA density (PSAD) were significantly different between the two groups (P < 0.05), while APTmin was not significantly different between the two groups (P > 0.05). APTmax and APTmean had the high values of area under the ROC curve (AUC), which were 0.780 and 0.710, respectively. APTmax had a high sensitivity, and APTmean had a high specificity. The combination of APTmax, APTmean, ADCmean, and PSAD had the highest AUC value (AUC: 0.880, sensitivity: 86.540, specificity: 78.260). CONCLUSION: APTmax, APTmean, ADCmean, ADCmin, tPAD, FPSA, and PSAD showed to have a high value in differentiating malignant prostate lesions from benign prostate lesions in the separate assessment of indexes. The combination of APTmax, APTmean, ADCmean, and PSAD had the highest diagnostic value.

The Impact of Urban Construction Land Change on Carbon Emissions-A Case Study of Wuhan City.

Urban construction land (UCL) change is a significant cause of changes in urban carbon emissions. However, as the extent of this effect is currently unclear, cities cannot easily formulate reasonable carbon reduction policies in terms of land use. Taking the city of Wuhan, China, as an example, this paper combines data on land use and carbon emissions from 1995 to 2019 and uses spatial analysis, curve estimation, and correlation evaluation to explore the direct and indirect effects of the UCL changes on carbon emissions. The results show that: (1) Between 1995 and 2019, the UCL area in Wuhan increased by 193.44%, and carbon emissions increased by 78.63%; moreover, both changes showed a gradually increasing spatial correlation, and the quantitative relationship could be better fitted with a composite function model; (2) The UCL change had mainly an indirect impact on carbon emissions via factors such as population and energy use intensity per unit of carbon emissions; (3) The maximum value of carbon emissions inside a unit area decreased during the study period, with an average annual decrease of about 2.02%. Therefore, the city of Wuhan can promote the achievement of its carbon emissions reduction targets by improving the existing land use policies, for example, by dividing the city into multiple functional zones.

Chemotherapy-associated steatohepatitis was concomitant with epicardial adipose tissue volume increasing in breast cancer patients who received neoadjuvant chemotherapy.

OBJECTIVES: To investigate the prevalence of chemotherapy-associated steatohepatitis, quantitate the epicardial adipose tissue (EAT) volume in breast cancer patients, and explore the mediating effect of liver fat content on EAT volume in breast cancer patients who received neoadjuvant chemotherapy (NAC). METHODS: From October 2018 to April 2020, patients were retrospectively reviewed and divided into breast cancer non-NAC and NAC groups. The prevalence of chemotherapy-associated steatohepatitis was evaluated through quantitative MRI mDIXON-Quant examinations by using defined proton density fat fraction cutoffs of liver fat. The EAT volume was quantified on chest CT by semi-automatic volume analysis software. Bootstrap analysis was used in the breast cancer NAC group to test the significance of the mediating effect of liver fat content on EAT volume. RESULTS: A total of 662 breast cancer patients (non-NAC group: 445 patients; NAC group: 217 patients) were included. The prevalence of chemotherapy-associated steatohepatitis in the NAC group was significantly higher than the prevalence of hepatic steatosis in the non-NAC group (42.8% vs. 33.3%, p < 0.001). EAT volume was measured in 561 of 662 breast cancer patients, and was significantly higher in the NAC group than in the non-NAC group (137.26 ± 53.48 mL vs. 125.14 ± 58.77 mL, p = 0.020). In the breast cancer NAC group, the indirect effect of liver fat content on EAT volume was 2.545 (p < 0.001), and the contribution rate to the effect was 69.1%. CONCLUSIONS: EAT volume was significantly higher in the BC-NAC group than in the BC-non-NAC group. KEY POINTS: • The prevalence of CASH was as high as 42.8% in BC patients. • NAC significantly increased the EAT volume in BC patients. • The liver fat content caused the change of EAT volume through mediating effect.

Low-dose CT with tin filter combined with iterative metal artefact reduction for guiding lung biopsy.

BACKGROUND: Computed tomography (CT) is currently the imaging modality of choice for guiding pulmonary percutaneous procedures. The use of a tin filter allows low-energy photons to be absorbed which contribute little to image quality but increases the radiation dose that a patient receives. Iterative metal artefact reduction (iMAR) was developed to diminish metal artefacts. This study investigated the impact of using tin filtration combined with an iMAR algorithm on dose reduction and image quality in CT-guided lung biopsy. METHODS: Ninety-nine consecutive patients undergoing CT-guided lung biopsy were randomly assigned to routine-dose CT protocols (groups A and B; without and with iMAR, respectively) or tin filter CT protocols (groups C and D; without or with iMAR, respectively). Subjective image quality was analysed using a 5-point Likert scale. Objective image quality was assessed, and the noise, contrast-to-noise ratio, and figure of merit were compared among the four groups. Metal artefacts were quantified using CT number reduction and metal diameter blurring. The radiation doses, diagnostic performance, and complication rates were also estimated. RESULTS: The subjective image quality of the two scan types was compared. Images with iMAR reconstruction were superior to those without iMAR reconstruction (group A: 3.49±0.65 vs. group B: 4.63±0.57; P<0.001, and group C: 3.88±0.66 vs. group D: 4.82±0.39; P<0.001). Images taken with a tin filter were found to have a significantly higher figure-of-merit than those taken without a tin filter (group A: 14,041±7,230 vs. group C: 21,866±10,656; P=0.001, and group B: 13,836±6,849 vs. group D: 21,639±9,964; P=0.001). In terms of metal artefact reduction, tin filtration combined with iMAR showed the lowest CT number reduction (116.62±103.48 HU) and metal diameter blurring (0.85±0.30) among the protocols. The effective radiation dose in the tin filter groups was 73.2% lower than that in the routine-dose groups. The complication rate and diagnostic performance (sensitivity, specificity, and overall accuracy) did not differ significantly between the tin filter and routine-dose groups (all P>0.05). CONCLUSIONS: Tin filtration combined with an iMAR algorithm may reduce the radiation dose compared to the routine-dose CT protocol, while maintaining comparable diagnostic accuracy and image quality and producing fewer metal artefacts.

A CT-based radiomics model for predicting renal capsule invasion in renal cell carcinoma.

BACKGROUND: Renal cell carcinoma (RCC) is a heterogeneous group of kidney cancers. Renal capsule invasion is an essential factor for RCC staging. To develop radiomics models from CT images for the preoperative prediction of capsule invasion in RCC patients. METHODS: This retrospective study included patients with RCC admitted to the Chongqing University Cancer Hospital (01/2011-05/2019). We built a radiomics model to distinguish patients grouped as capsule invasion versus non-capsule invasion, using preoperative CT scans. We evaluated effects of three imaging phases, i.e., unenhanced phases (UP), corticomedullary phases (CMP), and nephrographic phases (NP). Five different machine learning classifiers were compared. The effects of tumor and tumor margins are also compared. Five-fold cross-validation and the area under the receiver operating characteristic curve (AUC) are used to evaluate model performance. RESULTS: This study included 126 RCC patients, including 46 (36.5%) with capsule invasion. CMP exhibited the highest AUC (AUC = 0.81) compared to UP and NP, when using the forward neural network (FNN) classifier. The AUCs using features extracted from the tumor region were generally higher than those of the marginal regions in the CMP (0.81 vs. 0.73) and NP phase (AUC = 0.77 vs. 0.76). For UP, the best result was obtained from the marginal region (AUC = 0.80). The robustness analysis on the UP, CMP, and NP achieved the AUC of 0.76, 0.79, and 0.77, respectively. CONCLUSIONS: Radiomics features in renal CT imaging are associated with the renal capsule invasion in RCC patients. Further evaluation of the models is warranted.

Constructing a Flood-Adaptive Ecological Security Pattern from the Perspective of Ecological Resilience: A Case Study of the Main Urban Area in Wuhan.

The frequent occurrence of floods in urban areas caused by climate change challenges urban resilience. This research aims to construct an ecological security pattern (ESP) that is adaptive to floods to enhance urban resilience in the hope that it will help cities cope with floods better. In this research, the main urban area of Wuhan (WUH) represents the study area. The lakes were selected as the ecological sources and the Soil Conservation Service-Curve Number (SCS-CN) model was used to calculate the runoff volume corresponding to each land type and, based on this, assign resistance values to the land types; as such, the land type surface is referred to as the runoff resistance surface, and the runoff resistance surface is then modified by ecosystem service capabilities. The Minimum Cumulative Resistance (MCR) model was used to extract the connecting corridors between the sources. This research plan includes 18 ecological sources, 10 key ecological corridors, and 22 potential ecological corridors, with a total length of about 344.21 km. Finally, it provides a two-axis and three-core urban ecological resilience optimization strategy for decision makers and a new approach for controlling floods in urban areas from the perspective of ecological resilience.

Diagnostic performance of diffusion-weighted imaging combined with dynamic contrast-enhanced magnetic resonance imaging for prostate cancer: a systematic review and meta-analysis.

BACKGROUND: The diagnostic performance of diffusion-weighted imaging (DWI) combined with dynamic contrast-enhanced (DCE)-magnetic resonance imaging (MRI) for the detection of prostate cancer (PCa) has not been studied systematically to date. PURPOSE: To investigate the value of DWI combined with DCE-MRI quantitative analysis in the diagnosis of PCa. MATERIAL AND METHODS: A systematic search was conducted through PubMed, MEDLINE, the Cochrane Library, and EMBASE databases without any restriction to language up to 10 December 2019. Studies that used a combination of DWI and DCE-MRI for diagnosing PCa were included. RESULTS: Nine studies with 778 participants were included. The combination of DWI and DCE-MRI provide accurate performance in diagnosing PCa with pooled sensitivity, specificity, positive likelihood ratio, negative likelihood ratio, and diagnostic odds ratios of 0.79 (95% confidence interval [CI] = 0.76-0.81), 0.85 (95% CI = 0.83-0.86), 6.58 (95% CI = 3.93-11.00), 0.24 (95% CI = 0.17-0.34), and 36.43 (95% CI = 14.41-92.12), respectively. The pooled area under the summary receiver operating characteristic curve was 0.9268. Moreover, 1.5-T MR scanners demonstrated a slightly better performance than 3.0-T scanners. CONCLUSION: Combined DCE-MRI and DWI could demonstrate a highly accurate area under the curve, sensitivity, and specificity for detecting PCa. More studies with large sample sizes are warranted to confirm these results.