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Objectives: To explore the value of whole tumour- and subregion-based radiomics of contrast-enhanced mammography (CEM) in differentiating the HER2 expression status of breast cancers. Methods: 352 patients underwent preoperative CEM from two centres were consecutively enroled and divided into the training, internal validation, and external validation cohorts. The lesions were divided into HER2-positive and HER2-negative groups. Besides the radiological features, radiomics features capturing the whole tumour-based (wITH) and subregion-based intratumoral heterogeneity (sITH) were extracted from the craniocaudal view of CEM recombined images. The XGBoost classifier was applied to develop the radiological, sITH, and wITH models. A combined model was constructed by fusing the prediction results of the three models. Results: The mean age of the patients was 51.1 ± 10.7 years. Two radiological features, four wITH features, and three sITH features were selected to establish the models. The combined model significantly improved the AUC to 0.80 ± 0.03 (95% CI: 0.73–0.86), 0.79 ± 0.06 (95% CI: 0.67–0.90), and 0.79 ± 0.05 (95% CI: 0.69–0.89) in the training, internal validation, and external validation cohorts, respectively (All P < 0.05). The combined model showed good agreement between the predicted and observed probabilities and favourable net clinical benefit in the validation cohorts. Conclusions: Both whole tumour- and subregion-based ITH radiomics features of CEM exhibited potential for differentiating the HER2 expression status. Combining conventional radiological features and ITH features can improve the model's performance. [ABSTRACT FROM AUTHOR]

The estimation of postmortem interval (PMI) is a complex and challenging problem in forensic medicine. In recent years, many studies have begun to use machine learning methods to estimate PMI. However, research combining postmortem computed tomography (PMCT) with machine learning models for PMI estimation is still in early stages. This study aims to establish a multi-tissue machine learning model for PMI estimation using PMCT data from various tissues. We collected PMCT data of seven tissues, including brain, eyeballs, myocardium, liver, kidneys, erector spinae, and quadriceps femoris from 10 rabbits after death. CT images were taken every 12 h until 192 h after death, and HU values were extracted from the CT images of each tissue as a dataset. Support vector machine, random forest, and K-nearest neighbors were performed to establish PMI estimation models, and after adjusting the parameters of each model, they were used as first-level classification to build a stacking model to further improve the PMI estimation accuracy. The accuracy and generalized area under the receiver operating characteristic curve of the multi-tissue stacking model were able to reach 93% and 0.96, respectively. Results indicated that PMCT detection could be used to obtain postmortem change of different tissue densities, and the stacking model demonstrated strong predictive and generalization abilities. This approach provides new research methods and ideas for the study of PMI estimation. [ABSTRACT FROM AUTHOR]

To unravel the features of skin involvement in patients with systemic sclerosis (SSc) by high frequency ultrasound (HFU) and shear wave elastography (SWE). To assess the ultrasound capabilities to distinguish SSc patients from healthy controls (HCs). We recruited a cohort of SSc patients in this cross-sectional study. HFU and SWE were used to quantify skin thickness and skin stiffness. Receiver operating characteristic (ROC) curve analysis was used to assess the diagnostic capabilities of ultrasound in SSc. The correlation analysis was used to evaluate the clinical relevance of ultrasound measurements in SSc. 20 consecutive SSc patients and 20 age-, gender- and body mass index-matched HCs were included. The skin thickness and stiffness were significantly greater in SSc patients compared with HCs. Patients with high disease activity had higher skin thickness and stiffness compared with patients with low disease activity. The area under the ROC curve (AUC) of the dorsum of middle fingers assessed by HFU was 0.847 (95% CI, 0.761–0.933). The AUC of the forearms and dorsum of hands assessed by SWE were 0.909 (95% CI, 0.829–0.989) and 0.879 (95% CI, 0.807–0.951). Further, the combined HFU and SWE tests displayed the best diagnostic performance with an AUC of 0.980 (95% CI, 0.939–1.000). A significant positive correlation between the ultrasound measurements and the modified Rodnan skin score (mRSS) was observed. The application of ultrasound can assist with disease diagnosis, it is necessary to develop a standard operating protocol to help with future implementation of ultrasound in SSc.Key Points• The application of HFU and SWE can assist with SSc diagnosis.• The skin thickness and stiffness measured by HFU and SWE positively correlate with mRSS.• HFU and SWE enable quantitative measurement of skin thickness and stiffness of different skin sites. [ABSTRACT FROM AUTHOR]

We propose and experimentally investigate a spiral-polished single-multi-single-mode (SP-SMS) fiber sensor for the simultaneous measurement of strain and temperature. This special spiral shape on a multimode fiber is fabricated by a high-frequency CO2 laser, which excites higher order cladding modes in the interference process and leads to high strain sensitivity. Experimental results show that the strain sensitivity for the proposed structure in the transmission spectrum of two marked interference dips is − 17 pm/με and − 1 pm/με in the range of 0–600 με. Moreover, temperature sensitivities of 10 pm/℃ and 13.3 pm/℃ are obtained in the range of 30–150 ℃. Furthermore, the proposed sensor is inexpensive, is easy to fabricate and has a compact structure. [ABSTRACT FROM AUTHOR]

The hydrogen evolution reaction (HER), which generates molecular hydrogen through the electrochemical reduction of water, is an important clean-energy technology. Platinum (Pt) is an ideal material for HER electrocatalysts in terms of low overpotential and fast kinetics. An effective method to improve the atom utilization efficiency of Pt is to fabricate Pt-based core-shell or nanocage structures with ultra-thin walls. This paper describes the construction of bilayer palladium (Pd)-Pt alloy nanocages catalyst with enhanced HER catalytic activity. The nanocages were fabricated by etching away the Pd templates of multishelled nanocubes composed of alternate shells of Pd and Pt with well-defined (100) facets. The bilayer Pd-Pt nanocages with sub-nanometer shells have a high dispersion of the active atoms on the outside and inside surfaces of outer layer and inner layer, respectively. Moreover, the Pd-Pt alloy lowers the overpotential for HER and speeds up the reaction rate of HER due to the synergies between Pd and Pt. The rational design of bilayer nanocages provided a novel route for boosting the atom utilization efficiency of Pt catalysts. [ABSTRACT FROM AUTHOR]

Objective: To explore the value of texture analysis based on diffusion-weighted imaging (DWI), blood oxygen level-dependent MRI (BOLD), and susceptibility-weighted imaging (SWI) in evaluating renal dysfunction.Methods: Seventy-two patients (mean age 53.72 ± 13.46 years) underwent MRI consisting of DWI, BOLD, and SWI. According to their estimated glomerular filtration rate (eGFR), the patients were classified into either severe renal function impairment (sRI, eGFR < 30 mL/min/1.73 m2), non-severe renal function impairment (non-sRI, eGFR ≥ 30 mL/min/1.73 m2, and < 80 mL/min/1.73 m2), or control (CG, eGFR ≥ 80 mL/min/1.73 m2) groups. Thirteen texture features were extracted and then were analyzed to select the most valuable for discerning the three groups with each imaging method. A ROC curve was performed to compare the capacities of the features to differentiate non-sRI from sRI or CG.Results: Six features proved to be the most valuable for assessing renal dysfunction: 0.25QuantileDWI, 0.5QuantileDWI, HomogeneityDWI, EntropyBOLD, SkewnessSWI, and CorrelationSWI. Three features derived from DWI (0.25QuantileDWI, 0.5QuantileDWI, and HomogeneityDWI) were smaller in sRI than in non-sRI; EntropyBOLD and CorrelationSWI were smaller in non-sRI than in CG (p < 0.05). 0.25QuantileDWI, 0.5QuantileDWI, and HomogeneityDWI showed similar capacities for differentiating sRI from non-sRI. Similarly, EntropyBOLD and CorrelationSWI showed equal capacities for differentiating non-sRI from CG.Conclusion: Texture analysis based on DWI, BOLD, and SWI can assist in assessing renal dysfunction, and texture features based on BOLD and SWI may be suitable for assessing renal dysfunction during early stages.Key Points: • Texture analysis based on MRI techniques allowed for assessing renal dysfunction. • Texture features based on BOLD and SWI, but not DWI, may be suitable for assessing renal function impairment during early stages. • SWI exhibited a similar capacity to BOLD for assessing renal dysfunction. [ABSTRACT FROM AUTHOR]

Purpose: This study aimed to explore the feasibility of susceptibility-weighted imaging (SWI) for evaluating delayed graft function (DGF) during the early posttransplantation period.Methods: Sixty-nine recipients who accepted allograft renal transplantation underwent SWI during the second posttransplantation week. Renal allograft function was estimated via the glomerular filtration rate. Recipients with and without DGF were identified. For each transplanted kidney, the presence of abnormal signal intensity lesions (ASILs), excluding benign lesions, on SWI was assessed. Renal allograft function was compared between the recipients with and without ASILs. The correlation between ASILs and renal allograft function was tested by Spearman's rank correlation analysis.Results: Thirty-four recipients were diagnosed with DGF, while 35 recipients showed no DGF. In the DGF group, 16 recipients had low-intensity ASILs, primarily at the corticomedullary junction of transplanted kidneys on SWI, and no ASILs were found in 18 recipients. In the non-DGF group, none of the recipients showed ASILs on SWI. In the DGF group, the renal allograft function among the 16 recipients with low-intensity ASILs was significantly lower than that among the other 18 recipients (8.5 ± 4.2 vs. 19.7 ± 9.7 mL/min, P < 0.001). The presence of low-intensity ASILs on SWI showed a moderate negative correlation with renal allograft function in recipients with DGF (r = − 0.553, P = 0.001).Conclusion: SWI can be used to evaluate DGF in the early post-kidney transplantation period. [ABSTRACT FROM AUTHOR]