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Objectives: To preoperatively evaluate the human epidermal growth factor 2 (HER2) status in breast cancer using mammographic radiomics features and clinical characteristics on a multi-vendor and multi-center basis. Methods: This multi-center study included a cohort of 1512 Chinese female with invasive ductal carcinoma of no special type (IDC-NST) from two different hospitals and five devices (1332 from Institution A, used for training and testing the models, and 180 women from Institution B, as the external validation cohort). The Gradient Boosting Machine (GBM) was employed to establish radiomics and multiomics models. Model efficacy was evaluated by the area under the curve (AUC). Results: The number of HER2-positive patients in the training, testing, and external validation cohort were 245(26.3%), 105 (26.3.8%), and 51(28.3%), respectively, with no statistical differences among the three cohorts (p = 0.842, chi-square test). The radiomics model, based solely on the radiomics features, achieved an AUC of 0.814 (95% CI, 0.784–0.844) in the training cohort, 0.776 (95% CI, 0.727–0.825) in the testing cohort, and 0.702 (95% CI, 0.614–0.790) in the external validation cohort. The multiomics model, incorporated radiomics features with clinical characteristics, consistently outperformed the radiomics model with AUC values of 0.838 (95% CI, 0.810–0.866) in the training cohort, 0.788 (95% CI, 0.741–0.835) in the testing cohort, and 0.722 (95% CI, 0.637–0.811) in the external validation cohort. Conclusions: Our study demonstrates that a model based on radiomics features and clinical characteristics has the potential to accurately predict HER2 status of breast cancer patients across multiple devices and centers. Clinical relevance statement: By predicting the HER2 status of breast cancer reliably, the presented model built upon radiomics features and clinical characteristics on a multi-vendor and multi-center basis can help in bolstering the model's applicability and generalizability in real-world clinical scenarios. Key Points: • The mammographic presentation of breast cancer is closely associated with the status of human epidermal growth factor receptor 2 (HER2). • The radiomics model, based solely on radiomics features, exhibits sub-optimal performance in the external validation cohort. • By combining radiomics features and clinical characteristics, the multiomics model can improve the prediction ability in external data. [ABSTRACT FROM AUTHOR]

Blastic plasmacytoid dendritic cell neoplasm (BPDCN) is a rare hematologic malignancy that is highly aggressive with a poor prognosis. There is no standard treatment for BPDCN. Although conventional chemotherapies are usually sensitive in the initial therapy, relapse and drug resistance are inevitable within a short duration. Targeted therapies have enlightened new prospects for the treatment of BPDCN, especially for those in a frail state and intolerable to standard chemotherapies or hematopoietic stem cell transplantation. Here, we report an 82-year-old man diagnosed with cutaneous-limited BPDCN. Considering the old age and limited involvement of the tumor, we reduced the dosage of venetoclax. His skin lesions subsided significantly after 1 cycle of azacytidine (100 mg d1-7) combined with reduced doses of venetoclax (200 mg d1-14). The reduction in the dose of venetoclax avoided severe myelosuppression while achieving satisfactory outcomes. The patient received 2 cycles of therapy with no skin lesions re-occurred for 7 months before relapsing. [ABSTRACT FROM AUTHOR]

Objectives: Edema is a complication of gamma knife radiosurgery (GKS) in meningioma patients that leads to a variety of consequences. The aim of this study is to construct radiomics-based machine learning models to predict post-GKS edema development. Methods: In total, 445 meningioma patients who underwent GKS in our institution were enrolled and partitioned into training and internal validation datasets (8:2). A total of 150 cases from multicenter data were included as the external validation dataset. In each case, 1132 radiomics features were extracted from each pre-treatment MRI sequence (contrast-enhanced T1WI, T2WI, and ADC maps). Nine clinical features and eight semantic features were also generated. Nineteen random survival forest (RSF) and nineteen neural network (DeepSurv) models with different combinations of radiomics, clinical, and semantic features were developed with the training dataset, and evaluated with internal and external validation. A nomogram was derived from the model achieving the highest C-index in external validation. Results: All the models were successfully validated on both validation datasets. The RSF model incorporating clinical, semantic, and ADC radiomics features achieved the best performance with a C-index of 0.861 (95% CI: 0.748–0.975) in internal validation, and 0.780 (95% CI: 0.673–0.887) in external validation. It stratifies high-risk and low-risk cases effectively. The nomogram based on the predicted risks provided personalized prediction with a C-index of 0.962 (95%CI: 0.951–0.973) and satisfactory calibration. Conclusion: This RSF model with a nomogram could represent a non-invasive and cost-effective tool to predict post-GKS edema risk, thus facilitating personalized decision-making in meningioma treatment. Clinical relevance statement: The RSF model with a nomogram built in this study represents a handy, non-invasive, and cost-effective tool for meningioma patients to assist in better counselling on the risks, appropriate individual treatment decisions, and customized follow-up plans. Key Points: • Machine learning models were built to predict post-GKS edema in meningioma. The random survival forest model with clinical, semantic, and ADC radiomics features achieved excellent performance. • The nomogram based on the predicted risks provides personalized prediction with a C-index of 0.962 (95%CI: 0.951–0.973) and satisfactory calibration and shows the potential to assist in better counselling, appropriate treatment decisions, and customized follow-up plans. • Given the excellent performance and convenient acquisition of the conventional sequence, we envision that this non-invasive and cost-effective tool will facilitate personalized medicine in meningioma treatment. [ABSTRACT FROM AUTHOR]

Purpose: To explore the imaging changes of the liver and kidneys in COVID-19 survivors using variable flip angle (VFA) T1 mapping and intravoxel incoherent motion-diffusion weighted imaging (IVIM-DWI). Methods: This prospective study included 37 discharged COVID-19 participants and 24 age-matched non-COVID-19 volunteers who underwent abdominal MRI with VFA T1 mapping and IVIM-DWI sequencing as a COVID-19 group and control group, respectively. Among those discharged COVID-19 participants, 23 patients underwent two follow-up MRI scans, and were enrolled as the 3-month follow-up group and 1-year follow-up group, respectively. The demographics, clinical characteristics, and laboratory tests were collected. Imaging parameters of the liver and kidneys were measured. All collected values were compared among different groups. Results: The 3-month follow-up group had the lowest hepatic T1 value, which was significantly lower than the value in the control group (P < 0.001). Additionally, the 3-month follow-up group had the highest hepatic ADC and D values, cortical ADC and f values, which were significantly higher than those in the control group (for all, P < 0.05). The hepatic D value in the 1-year follow-up group decreased significantly in comparison with that in the 3-month follow-up group (P = 0.001). Compared to non-severe patients, severe cases had significantly higher hepatic D* and f*D* values (P = 0.031, P = 0.015, respectively). Conclusion: The dynamic alterations of hepatic and renal imaging parameters detected with T1 mapping and IVIM-DWI suggested that COVID-19 survivors might develop mild, non-symptomatic liver and kidney impairments, of which liver impairment could probably relieve over time and kidney impairment might be long-existing. [ABSTRACT FROM AUTHOR]

In patients with CH, 16.7% AA cases and 23.6% hMDS cases had two or more mutations while only one ITP patient had more than one mutation (Fig. The polyline represents the cumulative prevalence of CH in ITP patients, the bars show the percentage of patients with CH in different age groups. 1L), CH was positively correlated with bleeding severity as ITP patients with CH were 6.95 times more likely to develop severe bleeding than those without CH ( I P i = 0.008, Fig. N The initial response rate in patients with CH was lower compared with patients without CH though it did not reach statistical significance. [Extracted from the article]

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Fungal infections, especially candidiasis and aspergillosis, claim a high fatality rate. Fungal cell growth and function requires ATP, which is synthesized mainly through oxidative phosphorylation, with the key enzyme being F1Fo-ATP synthase. Here, we show that deletion of the Candida albicans gene encoding the δ subunit of the F1Fo-ATP synthase (ATP16) abrogates lethal infection in a mouse model of systemic candidiasis. The deletion does not substantially affect in vitro fungal growth or intracellular ATP concentrations, because the decrease in oxidative phosphorylation-derived ATP synthesis is compensated by enhanced glycolysis. However, the ATP16-deleted mutant displays decreased phosphofructokinase activity, leading to low fructose 1,6-bisphosphate levels, reduced activity of Ras1-dependent and -independent cAMP-PKA pathways, downregulation of virulence factors, and reduced pathogenicity. A structure-based virtual screening of small molecules leads to identification of a compound potentially targeting the δ subunit of fungal F1Fo-ATP synthases. The compound induces in vitro phenotypes similar to those observed in the ATP16-deleted mutant, and protects mice from succumbing to invasive candidiasis. Our findings indicate that F1Fo-ATP synthase δ subunit is required for C. albicans lethal infection and represents a potential therapeutic target. F1Fo-ATP synthase is a key enzyme for energy production in fungi. Here, the authors show that the δ subunit of the enzyme is required for Candida albicans lethal infection and represents a potential therapeutic target. [ABSTRACT FROM AUTHOR]

Using the surface molecular imprinting technique, a thermo-sensitive molecularly imprinted fluorescent sensor was constructed for bovine hemoglobin (BHb) detection with the silanized carbon dots (CD@SiO2) as fluorescent signal, N-isopropylacrylamide as monomer sensitive to temperature, and BHb as template. The silanized carbon dots coated by the molecularly imprinted polymer (CD@SiO2@MIP) were characterized by high-resolution transmission electron microscopy, Fourier transform infrared spectroscopy, and fluorescence spectroscopy. Owing to the combination of the strong fluorescence sensitivity of CDs and the high selectivity of the molecular imprinting shell, the prepared sensor showed good recognition and detection performance to the target protein BHb, with a linear range of 0.31–1.55 μM and a detection limit of 1.55 μM. Furthermore, the sensor was utilized to detect the content of BHb in real urine with a recovery of 98.6–100.5%. The CD@SiO2@MIP sensors present a high potential for applications in the detection of BHb in biological systems. [ABSTRACT FROM AUTHOR]

The abnormal concentration of lysozyme in body fluids and tissues is a potential indicator for diseases such as leukemia and meningitis. In this work, by combining the excellent optical properties of carbon dots (CDs) with the favorable selectivity of molecularly imprinted polymer (MIP), a novel fluorescent probe for lysozyme detection and cell imaging was constructed, where silanized CDs with low cytotoxicity (CDs/SiO2) were used as the fluorescence signal reporter and N-isopropylacrylamide (NIPAM) was used as the temperature-sensitive monomer. The as-prepared CDs/SiO2/MIP showed a thermo-sensitive property for the response to lysozyme. Moreover, this probe could be used for quantitative detection of lysozyme, with a wider detection range (0.001~0.01 mg/mL), a low detection limit (0.55 μg/mL), and a high selectivity. Importantly, the MTT assay testified that the fluorescent CDs/SiO2/MIP probe had low cytotoxicity. In addition, human hepatoma carcinoma cells (HepG-2 cells) could be stained by the CDs/SiO2/MIP, and showed a bright intracellular green fluorescence, indicating that the imaging of live cells was possible. This study provides a new way to detect lysozyme in vitro and an attractive perspective to probe intracellular lysozyme in vivo. [ABSTRACT FROM AUTHOR]

In this paper, the effects of doping with GeO on the synthesis temperature, phase structure and morphology of (KNa)NbO (KNN) ceramic powders were studied using XRD and SEM. The results show that KNN powders with good crystallinity and compositional homogeneity can be obtained after calcination at up to 900°C for 2 h. Introducing 0.5 mol.% GeO into the starting mixture improved the synthesis of the KNN powders and allowed the calcination temperature to be decreased to 800°C, which can be ascribed to the formation of the liquid phase during the synthesis. [ABSTRACT FROM AUTHOR]