Polymorphisms in the human leukocyte antigen (HLA) class I genes can cause the rejection of pluripotent stem cell (PSC)-derived products in allogeneic recipients Disruption of the Beta-2 Microglobulin (B2M) gene eliminates surface expression of all class I molecules, but leaves the cells vulnerable to lysis by natural killer (NK) cells Here we show that this 'missing-self' response can be prevented by forced expression of minimally polymorphic HLA-E molecules We use adeno-associated virus (AAV)-mediated gene editing to knock in HLA-E genes at the B2M locus in human PSCs in a manner that confers inducible, regulated, surface expression of HLA-E single-chain dimers (fused to B2M) or trimers (fused to B2M and a peptide antigen), without surface expression of HLA-A, B or C These HLA-engineered PSCs and their differentiated derivatives are not recognized as allogeneic by CD8+ T cells, do not bind anti-HLA antibodies and are resistant to NK-mediated lysis Our approach provides a potential source of universal donor cells for applications where the differentiated derivatives lack HLA class II expression

/pdf/hla-e-expressing-pluripotent-stem-cells-escape-allogeneic-358a08b25k.pdf

HLA-E-expressing pluripotent stem cells escape allogeneic responses and lysis by NK cells

Abstract Objectives In this study, we developed a radiomic signature for the classification of benign lipid-poor adenomas, which may potentially help clinicians limit the number of unnecessary investigations in clinical practice. Indeterminate adrenal lesions of benign and malignant nature may exhibit different values of key radiomics features. Methods Patients who had available histopathology reports and a non-contrast-enhanced CT scan were included in the study. Radiomics feature extraction was done after the adrenal lesions were contoured. The primary feature selection and prediction performance scores were calculated using the least absolute shrinkage and selection operator (LASSO). To eliminate redundancy, the best-performing features were further examined using the Pearson correlation coefficient, and new predictive models were created. Results This investigation covered 50 lesions in 48 patients. After LASSO-based radiomics feature selection, the test dataset’s 30 iterations of logistic regression models produced an average performance of 0.72. The model with the best performance, made up of 13 radiomics features, had an AUC of 0.99 in the training phase and 1.00 in the test phase. The number of features was lowered to 5 after performing Pearson’s correlation to prevent overfitting. The final radiomic signature trained a number of machine learning classifiers, with an average AUC of 0.93. Conclusions Including more radiomics features in the identification of adenomas may improve the accuracy of NECT and reduce the need for additional imaging procedures and clinical workup, according to this and other recent radiomics studies that have clear points of contact with current clinical practice. Clinical relevance statement The study developed a radiomic signature using unenhanced CT scans for classifying lipid-poor adenomas, potentially reducing unnecessary investigations that scored a final accuracy of 93%. Key Points • Radiomics has potential for differentiating lipid-poor adenomas and avoiding unnecessary further investigations. • Quadratic mean, strength, maximum 3D diameter, volume density, and area density are promising predictors for adenomas. • Radiomics models reach high performance with average AUC of 0.95 in the training phase and 0.72 in the test phase. 

Radiomics in the characterization of lipid-poor adrenal adenomas at unenhanced CT: time to look beyond usual density metrics.

The glycoprotein CD2 is expressed on T and NK cells and contributes to cell-cell conjugation, agonistic signaling and actin cytoskeleton rearrangement. CD2 has previously been shown to have an important function in natural NK cell cytotoxicity but to be expendable in antibody-mediated cytotoxicity. Siplizumab is a monoclonal anti-CD2 IgG1 antibody that is currently undergoing clinical trials in the field of transplantation. This study investigated the effect of CD2 binding and Fc γ receptor binding by siplizumab (Fc-active) and Fc-silent anti-CD2 monoclonal antibodies in allogeneic mixed lymphocyte reaction and autologous lymphocyte culture. Further, induction of NK cell fratricide and inhibition of natural cytotoxicity as well as antibody-dependent cytotoxicity by these agents were assessed. Blockade of CD2 via monoclonal antibodies in the absence of Fc γ receptor binding inhibited NK cell activation in allogeneic mixed lymphocyte reaction. In contrast, siplizumab increased NK cell activation in both mixed lymphocyte reaction and autologous lymphocyte culture due to FcγRIIIA binding. However, experiments using purified NK cells did not show an inhibitory effect of CD2 blockade on natural cytotoxicity or antibody-dependent cytotoxicity. Lastly, it was shown that siplizumab induces NK cell fratricide. Concluding, siplizumab is a promising biopharmaceutical drug candidate for depletion of T and NK cells with minimal off-target effects.

/pdf/siplizumab-induces-nk-cell-fratricide-through-antibody-9tof7wsp62.pdf

Siplizumab Induces NK Cell Fratricide Through Antibody-Dependent Cell-Mediated Cytotoxicity

To explore the feasibility of unenhanced CT images for endoleak detection of abdominal aortic aneurysm (AAA) after endovascular repair (EVAR).Patients who visited our hospital after EVAR from July 2014 to September 2021 were retrospectively collected. Two radiologists evaluated the presence or absence of endoleaks using the combination of contrast-enhanced and unenhanced CT as the referenced standard. After segmenting the aneurysm sac of the unenhanced CT, the radiomic features were automatically extracted from the region of interest. Histogram features of patients with and without endoleak were statistically analyzed to explore the differences between the two groups. Twelve common machine learning (ML) models based on radiomic features were constructed to evaluate the performance of endoleak detection with unenhanced CT images.The study included 216 patients (69 ± 8 years; 191 men) with AAA, including 64 patients with endoleaks. A total of 1955 radiomic features of unenhanced CT were extracted. Compared with patients without endoleak, the aneurysm sac outside the stent of patients with endoleak had higher CT attenuation (41.7 vs. 33.6, p < 0.001) with smaller dispersion (51.5 vs. 58.8, p < 0.001). The average area under the curve (AUC) of the ML models constructed with unenhanced CT radiomics was 0.86 ± 0.05, the accuracy was 81% ± 4, the sensitivity was 88% ± 10, and the specificity was 78% ± 5. When fixing the sensitivity to > 90% (92% ± 2), the models retained specificity at 72% ± 10.Unenhanced CT features exhibit significant differences between patients with and without endoleak and can help detect endoleaks in AAA after EVAR with high sensitivity.Unenhanced CT radiomics can help provide an alternative method of endoleak detection in patients who have adverse reactions to contrast media. This study further exploits the value of unenhanced CT examinations in the clinical management and surveillance of postoperative abdominal aortic aneurysm.• Unenhanced CT features of the aneurysm sac outside the stent exhibit significant differences between patients with and without endoleak. The endoleak group showed higher unenhanced CT attenuation (41.7 vs 33.6, p < .001) with smaller dispersion (51.5 vs 58.8, p < .001) than the nonendoleak group. • Unenhanced CT radiomics can help detect endoleaks after intervention. The average area under the curve (AUC) of twelve common machine learning models constructed with unenhanced CT radiomics was 0.86 ± 0.05, the average accuracy was 81% ± 4. • When fixing the sensitivity to > 90% (92% ± 2), the machine learning models retained average specificity at 72% ± 10. 

pdf/unenhanced-computed-tomography-radiomics-help-detect-4xcxxjtx39.pdf

Unenhanced computed tomography radiomics help detect endoleaks after endovascular repair of abdominal aortic aneurysm

Purpose To investigate the influence of reduced glutathione (GSH) in liver function, oxidative stress, inflammatory response, immune function and quality of life of patients after an interventional therapy for hepatocellular carcinoma. Methods 96 hepatocellular carcinoma patients undergoing hepatic arterial intervention chemotherapy were selected and randomly divided into the control group (n=48) and the observation group (n=48). The patients in the control group were given conventional treatment after operation, while those in the observation group were treated with GSH based on the treatment in the control group. The liver function, oxidative stress, inflammation, quality of life and adverse reactions were compared before and after treatment between the two groups. Results The levels of superoxide dismutase (SOD), cluster of differentiation (CD)3+, CD4+ and CD4+/CD8+ as well as physical, emotion and social function scores after treatment were higher in the observation group than in the control group. The observation group had lower levels of alanine aminotransferase (ALT), aspartate aminotransferase (AST), alkaline phosphatase (ALP), total bilirubin (TBiL), malondialdehyde (MDA), advanced oxidation protein product (AOPP), C-reactive protein (CRP), interleukin-6 (IL-6), tumor necrosis factor-alpha (TNF-α) and CD8+ as well as pain score than the control group (p 0.05). Conclusions GSH can evidently ameliorate the liver function and immune function, reduce oxidative stress and inflammatory response and improve the postoperative quality of life of the patients after the interventional therapy for hepatocellular carcinoma, with satisfactory clinical therapeutic effects, so it is worthy of further application and generalization.

Reduced glutathione ameliorates liver function, oxidative stress and inflammation after interventional therapy for hepatocellular carcinoma.

Background It is difficult for radiologists to differentiate adrenal lipid-poor adenomas from non-adenomas; nevertheless, this differentiation is important as the clinical interventions required are different for adrenal lipid-poor adenomas and non-adenomas. Purpose To develop an unenhanced computed tomography (CT)-based radiomics model for identifying adrenal lipid-poor adenomas to assist in clinical decision-making. Materials and methods Patients with adrenal lesions who underwent CT between January 2015 and August 2021 were retrospectively recruited from two independent institutions. Patients from institution 1 were randomly divided into training and test sets, while those from institution 2 were used as the external validation set. The unenhanced attenuation and tumor diameter were measured to build a conventional model. Radiomics features were extracted from unenhanced CT images, and selected features were used to build a radiomics model. A nomogram model combining the conventional and radiomic features was also constructed. All the models were developed in the training set and validated in the test and external validation sets. The diagnostic performance of the models for identifying adrenal lipid-poor adenomas was compared. Results A total of 292 patients with 141 adrenal lipid-poor adenomas and 151 non-adenomas were analyzed. Patients with adrenal lipid-poor adenomas tend to have lower unenhanced attenuation and smoother image textures. In the training set, the areas under the curve of the conventional, radiomic, and nomogram models were 0.94, 0.93, and 0.96, respectively. There was no difference in diagnostic performance between the conventional and nomogram models in all datasets (all p < 0.05). Conclusions Our unenhanced CT-based nomogram model could effectively distinguish adrenal lipid-poor adenomas. The diagnostic power of conventional unenhanced CT imaging features may be underestimated, and further exploration is worthy.

/pdf/can-radiomics-provide-additional-diagnostic-value-for-hu90eg47.pdf

Can Radiomics Provide Additional Diagnostic Value for Identifying Adrenal Lipid-Poor Adenomas From Non-Adenomas on Unenhanced CT?

Liver cancer caused by diet or life style is a significant public health problem. Liver transplantation (LT) is a commonly used method of treatment for the liver cancer. The present study aimed to determine whether assessing the net state of natural killer (NK) cell function following LT distinguishes patients at risk for transplantation rejection. A total of 53 patients were involved; all underwent LT for hepatocellular carcinoma with (n=13) or without (n=40) transplantation rejection. The density of interferon-γ (IFN-γ) in blood serum was examined and patients were divided into two groups: Higher (H) and lower (L), on the basis of IFN-γ density. The percentage of NK cells and their producing cytokines was detected using fluorescence-activated cell sorting in peripheral blood and liver samples. As evaluation indexes of liver function, aspartate transaminase (AST) and alanine transaminase (ALT) were detected in blood serum. NK cell activation of the H-group was observed to be higher than the L-group, specifically the expression of NK group 2D, cluster of differentiation 69 and IFN-γ were higher than the L-group. The H-group exhibited a higher level of AST and ALT, which indicates the potential for acute transplantation rejection. The results of the present study indicate that NK cells and NK-derived IFN-γ serve an important function in regulating the rejection of LT and tumor metastasis in response to LT.

/pdf/role-of-natural-killer-cells-in-liver-transplantation-2ttp1hmrqv.pdf

Role of natural killer cells in liver transplantation treatment of liver cancer.

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Can Radiomics Provide Additional Diagnostic Value for Identifying Adrenal Lipid-Poor Adenomas From Non-Adenomas on Unenhanced CT?

Role of natural killer cells in liver transplantation treatment of liver cancer.