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Cancer is one of the most dangerous diseases worldwide. Accurate cancer subtype classification facilitates both diagnosis and prognosis. Currently, studies focused on cancer subtype classification mainly utilize invasive histopathological images. However, non-invasive PET/CT images are often the first choice for initial screening and diagnosis of tumors. In addition, existing deep learning models strive to find accurate classification boundaries. It is difficult to make a definitive diagnosis with radiological imaging studies alone. To address these issues, we proposed a classification method embedding atypical patterns for distinguishing tumor subtypes in PET/CT images. First, we introduced a novel pattern class division method, including the original classes representing typical patterns and the extended classes representing atypical patterns. We optimized the distribution of feature vectors through a deep metric learning-based method. Then, we proposed a fuzzy classification loss that employs one or more proxies to represent a pattern class. This loss optimizes the spatial distribution of proxies with their corresponding subsets. Finally, we proposed a fuzzy classification method to predict the class of a sample. The experimental results on two datasets show that the proposed model can separate the samples with atypical features and has high accuracy for samples with typical features. For more difficult tasks, the improvement using the proposed model is more obvious. Furthermore, using the proposed model has good noise immunity and interpretability, which is helpful for clinical auxiliary diagnosis. • Develop a PET/CT tumor subtypes classification method embedding atypical patterns. • Introduce a novel pattern class division method. • Propose a fuzzy classification loss that can separate samples with atypical features. • The proposed method can effectively alleviate the label noise. • The proposed method is more consistent with the diagnostic workflow. [ABSTRACT FROM AUTHOR]

[Display omitted] Ferroptosis is considered as a potential target in cancer treatment including chemotherapy and radiotherapy, however, its regulatory mechanism on pancreatic cancer (PC) is not fully understood. Herein, we explored the role of upstream stimulatory factor 2 (USF2) and pyruvate kinase M2 (PKM2) in ferroptosis in PC cells. USF2 and PKM2 were highly expressed in PC tissues and USF2 was positively correlated with PKM2. PC cell lines BxpC-3 and AsPC-1 were transfected with small interfering RNAs against USF2/PKM2 or USF2 overexpressing plasmids or co-transfected with small interfering RNAs against PKM2 and USF2 overexpressing plasmids. Twenty-four hours after cell transfection, ferroptotic cell death was induced by incubation with 20 μmol/l erastin for 24 h. Ferroptotic cell death was promoted by USF2 knockdown and inhibited by USF2 overexpression. USF2 knockdown increased lipid reactive oxygen species and malonaldehyde generation and decreased glutathione concentration and glutathione peroxidase 4 expressions, indicating the enhanced lipid peroxidation. USF2 knockdown also increased ferrous iron levels and ferritin heavy chain expressions and reduced solute carrier family 7 member 11 expressions. However, USF2 overexpression reversed these changes. Furthermore, dual-luciferase reporter assay, chromatin immunoprecipitation assay and DNA pull down assay validated that USF2 transcriptionally regulated PKM2 expression through binding to its promoter. Interestingly, PKM2 also negatively regulated ferroptosis and PKM2 knockdown markedly impaired the effects of USF2 on lipid peroxidation and ferroptotic cell death. This study demonstrated that USF2 negatively regulated ferroptosis in PC cells through transcriptional regulation of PKM2, providing new evidences for uncovering the regulatory mechanism of ferroptosis on PC. [ABSTRACT FROM AUTHOR]

Purpose: This study is aimed to compare the diagnostic power of using quantitative analysis or visual analysis with single time point imaging (STPI) PET/CT and dual time point imaging (DTPI) PET/CT for the classification of solitary pulmonary nodules (SPN) lesions in granuloma-endemic regions.Methods: SPN patients who received early and delayed (18)F-FDG PET/CT at 60min and 180min post-injection were retrospectively reviewed. Diagnoses are confirmed by pathological results or follow-ups. Three quantitative metrics, early SUVmax, delayed SUVmax and retention index(the percentage changes between the early SUVmax and delayed SUVmax), were measured for each lesion. Three 5-point scale score was given by blinded interpretations performed by physicians based on STPI PET/CT images, DTPI PET/CT images and CT images, respectively. ROC analysis was performed on three quantitative metrics and three visual interpretation scores.Result: One-hundred-forty-nine patients were retrospectively included. The areas under curve (AUC) of the ROC curves of early SUVmax, delayed SUVmax, RI, STPI PET/CT score, DTPI PET/CT score and CT score are 0.73, 0.74, 0.61, 0.77 0.75 and 0.76, respectively. There were no significant differences between the AUCs in visual interpretation of STPI PET/CT images and DTPI PET/CT images, nor in early SUVmax and delayed SUVmax. The differences of sensitivity, specificity and accuracy between STPI PET/CT and DTPI PET/CT were not significantly different in either quantitative analysis or visual interpretation.Conclusion: In granuloma-endemic regions, DTPI PET/CT did not offer significant improvement over STPI PET/CT in differentiating malignant SPNs in both quantitative analysis and visual interpretation. [ABSTRACT FROM AUTHOR]

Methotrexate (MTX) is a first-line drug for rheumatoid arthritis (RA). Targeting of MTX to inflamed joints is essential to the prevention of potential toxicity and improving therapeutic effects. Gold nanoparticles (GNPs) are characterized by controllable particle sizes and good biocompatibilities, therefore, they are promising drug delivery systems. We aimed at developing a GNPs drug delivery system incorporating MTX and folic acid (FA) with strong efficacies against RA. MTX-Cys-FA was synthesized through solid-phase organic synthesis. Then, it was coupled with sulfhydryl groups in GNPs, thereby successfully preparing a GNPs/MTX-Cys-FA nanoconjugate with targeting properties. Physical and chemical techniques were used to characterize it. Moreover, we conducted its stability, release, pharmacokinetics, biodistribution and cell cytotoxicity, cell uptake, cell migration, as well as its therapeutic effect on CIA rats. The histopathology was conducted to investigate anti-RA effects of GNPs/MTX-Cys-FA nanoconjugates. The GNPs/MTX-Cys-FA nanoconjugate exhibited a spherical appearance, had a particle size of 103.06 nm, a zeta potential of -33.68 mV, drug loading capacity of 11.04 %, and an encapsulation efficiency of 73.61%. Cytotoxicity experiments revealed that GNPs had good biocompatibilities while GNPs/MTX-Cys-FA exhibited excellent drug-delivery abilities. Cell uptake and migration experiment showed that nanoconjugates containing FA by LPS activated mouse mononuclear macrophages (RAW264.7) was significantly increased, and they exerted significant inhibitory effects on human fibroblast-like synoviocytes (HFLS) of RA (p <0.01). In addition, the nanoconjugate prolonged blood circulation time of MTX in collagen-induced arthritis (CIA) rats (p <0.01), enhanced MTX accumulation in inflamed joints (p <0.01), enhanced their therapeutic effects (p <0.01), and reduced toxicity to major organs (p <0.01). GNPs/MTX-Cys-FA nanoconjugates provide effective approaches for RA targeted therapeutic strategies. [Display omitted] [ABSTRACT FROM AUTHOR]

Abstract: Objective: To explore the presence, clinical characteristics, anatomical foci in image and mechanism of hemispatial neglect (HSN), neglect test battery and single-photon emission computed tomography (SPECT) regional cerebral blood flow (rCBF) imaging were performed on patients with stroke. Methods: Thirty dextromanual patients who were diagnosed as having unilateral stroke clinically were recruited. A neglect test battery including line bisection test, star cancellation test and drawing test was performed on the subjects. The severity of neglect was measured on neglect tests. The lowest rCBF, the range with decreased rCBF, number of the foci with decreased rCBF, the flow deficit size and the total number of pixels in the foci were measured on SPECT rCBF imaging. Results: Twenty-five patients were diagnosed as having HSN by the neglect test battery. Contralateral neglect (CN) and ipsilateral neglect (IN) were observed in both right and left hemisphere strokes. On SPECT imaging, the patients with neglect had decreased rCBF in the frontal cortex most often; followed by the parietal, occipital and temporal cortices; and basal ganglia and thalamus in some cases. The patients who had two or more regions damaged showed neglect more often and severity. The correlation coefficients between rCBF in the foci, the decreased percentage of rCBF of the foci and the severity of neglect were −0.119 (P>.05) and 0.221 (P>.05). The correlation coefficients between the range, number of foci, the flow deficit size, the total number of pixels of the foci and the severity of neglect were 0.537 (P<.05), 0.493 (P<.05), 0.561 (P<.05), 0.466 (P<.05), respectively. No difference between CN and IN on SPECT images reached statistical significance. Conclusions: The severity of neglect did not correlate with rCBF and the decreased percentage of rCBF in the foci, while it was significantly correlated with the range, number of foci, the flow deficit size and the total numbers of pixels of the foci significantly. And the patients with CN and IN did not show any difference in the presence of HSN, the manifestation on the neglect test battery and SPECT images. HSN showed damage on multiple sites, with combined damages resulting in more severe neglect. [Copyright &y& Elsevier]