Radiological Features of Primary Pulmonary Invasive Mucinous Adenocarcinoma Based on 312 Consecutive Patients.

BACKGROUND: The aim of this study is to investigate the radiological features of primary pulmonary invasive mucinous adenocarcinoma (IMA) in a relatively large population to help improve its further understanding and its accuracy of initial diagnosis. METHODS: This retrospective study included consecutive patients with pathologically confirmed primary pulmonary IMA from January 2019 to December 2021. According to tumor morphology, IMAs were divided into regular nodule/mass, irregular, and large consolidative types. According to tumor density, IMAs were divided into solid, halo, part-solid, pure ground-glass, and cystic types. ANOVA, chi-square, or Fisher exact tests were used to analyze the differences in radiological and clinicopathological characteristics of IMA according to morphological and density subtypes. RESULTS: We analyzed 312 patients. Pulmonary IMA tended to occur in the elderly, with a slightly higher number of women than men. IMA showed a predominance in the lower lobe and adjacent to pleura. IMA of regular nodule/mass, irregular, and large consolidative types accounted for 80.8% (252/312), 13.8% (43/312), and 5.4% (17/312), respectively. Solid, halo, part-solid, pure ground-glass, and cystic IMAs accounted for 55.8% (174/312), 28.2% (88/312), 11.2% (35/312), 1.3% (4/312), and 3.5% (11/312), respectively. The lobulated (76.9%), spiculated (63.5%), and air bronchogram (56.7%) signs were common in IMA. Dead branch sign (88.2%), angiogram sign (88.2%), and satellite nodules/skipping lesions (47.1%) were common in large-consolidative-type IMA. Kirsten rat sarcoma viral oncogene mutations were common (56.1%), whereas epidermal growth factor receptor mutations were relatively rare (2.3%). CONCLUSIONS: Pulmonary IMA of regular nodule/mass type and solid type were the most common at the initial diagnosis. Detailed radiological features can aid in the differential diagnosis of IMA.

A prediction model based on computed tomography characteristics for identifying malignant from benign sub-centimeter solid pulmonary nodules.

Background: Distinguishing benign from malignant sub-centimeter solid pulmonary nodules (SSPNs) continues to be challenging in clinical practice. Earlier diagnosis is crucial for improving patient survival and prognosis. This study aimed to investigate the risk factors of malignant SSPNs and establish and validate a prediction model based on computed tomography (CT) characteristics to assist in their early diagnosis. Methods: A total of 261 consecutive participants with 261 SSPNs were retrospectively recruited between January 2012 and July 2023 from National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College (Center 1), including 161 malignant lesions and 100 benign lesions. Patients were randomly assigned to the training set (n=183) and validation set (n=78) according to a 7:3 ratio. Malignant nodules were confirmed by pathology; and benign nodules were confirmed by follow-up or pathology. Clinical data and CT features were collected to estimate the independent predictors of malignancy of SSPN with multivariate logistic analysis. A clinical prediction model was subsequently established by logistic regression. Furthermore, an additional 69 consecutive patients with 69 SSPNs from The Fourth Hospital of Hebei Medical University (Center 2) between January 2022 and December 2022 were retrospectively included as an external cohort to validate the predictive efficacy of the model. The performance of the prediction model was assessed by sensitivity, specificity, and the area under the receiver operating characteristic curve. Results: There were 113 (61.7%), 48 (61.5%) and 28 (40.6%) malignant SSPNs in the training, internal and external validation sets, respectively. Multivariate logistic analysis revealed four independent predictors of malignant SSPNs: tumor-lung interface (P=0.002), spiculation (P=0.04), air bronchogram (P=0.047), and invisible at the mediastinal window (P=0.003). The area under the curve (AUC) for the prediction model in the training set was 0.875 [95% confidence interval (CI): 0.818, 0.933]; and the sensitivity and specificity were 94.7% and 68.6%, respectively. The AUCs in the internal and external validation set were (0.781; 95% CI: 0.664, 0.897) and (0.873; 95% CI: 0.791, 0.955), respectively; the sensitivity and specificity were 66.7% and 83.3% for the internal validation data, and 100.0% and 61.0% for the external validation data, respectively. Conclusions: The prediction model based on CT characteristics could be helpful for distinguishing malignant SSPNs from benign ones.

The Battle for Accuracy: Identifying the Most Effective Grading System for Lung Invasive Mucinous Adenocarcinoma.

BACKGROUND: The prognostic analysis of lung invasive mucinous adenocarcinoma (IMA) is deficient due to the lack of a universally recommended histological grading system, leading to unregulated treatment approaches. OBJECTIVE: We aimed to examine the clinical trajectory of IMA and assess the viability of utilizing the existing grading system for lung invasive non-mucinous adenocarcinoma in the context of IMA. METHODS: We retrospectively collected clinicopathological data from 265 IMA patients. Each case re-evaluated the tumor grade using the following three classification systems: the 4th Edition of the World Health Organization classification system, the International Association for the Study of Lung Cancer (IASLC) grading system, and a two-tier grading system. We performed a comparative analysis of these grading systems and identified the most effective grading system for IMA. RESULTS: The study comprised a total of 214 patients with pure IMA and 51 patients with mixed IMA. The 5-year overall survival (OS) rates for pure IMA and mixed IMA were 86.7% and 57.8%, respectively. All three grading systems proved to be effective prognostic classifiers for IMA. The value of area under the curve at 1-, 3-, and 5-year OS was highest for the IASLC grading system compared with the other grade systems and the clinical stage. The IASLC classification system was an independent prognostic predictor (p = 0.009, hazard ratio 2.243, 95% confidence interval 1.219-4.127). CONCLUSION: Mixed IMA is more aggressive than pure IMA, with an OS rate on par with that of high-grade pure IMA. The IASLC grading system can better indicate prognosis and is recommended for lung IMA.

Assessing the efficiency of eligibility criteria for low-dose computed tomography lung screening in China according to current guidelines.

BACKGROUND: Evidence from observational studies indicates that lung cancer screening (LCS) guidelines with high rates of lung cancer (LC) underdiagnosis, and although current screening guidelines have been updated and eligibility criteria for screening have been expanded, there are no studies comparing the efficiency of LCS guidelines in Chinese population. METHODS: Between 2005 and 2022, 31,394 asymptomatic individuals were screened using low-dose computed tomography (LDCT) at our institution. Demographic data and relevant LC risk factors were collected. The efficiency of the LCS for each guideline criteria was expressed as the efficiency ratio (ER). The inclusion rates, eligibility rates, LC detection rates, and ER based on the different eligibility criteria of the four guidelines were comparatively analyzed. The four guidelines were as follows: China guideline for the screening and early detection of lung cancer (CGSL), the National Comprehensive Cancer Network (NCCN), the United States Preventive Services Task Force (USPSTF), and International Early Lung Cancer Action Program (I-ELCAP). RESULTS: Of 31,394 participants, 298 (155 women, 143 men) were diagnosed with LC. For CGSL, NCCN, USPSTF, and I-ELCAP guidelines, the eligibility rates for guidelines were 13.92%, 6.97%, 6.81%, and 53.46%; ERe for eligibility criteria were 1.46%, 1.64%, 1.51%, and 1.13%, respectively; and for the inclusion rates, they were 19.0%, 9.5%, 9.3%, and 73.0%, respectively. LCs which met the screening criteria of CGSL, NCCN, USPSTF, and I-ELCAP guidelines were 29.2%, 16.4%, 14.8%, and 86.6%, respectively. The age and smoking criteria for CGSL were stricter, hence resulting in lower rates of LC meeting the screening criteria. The CGSL, NCCN, and USPSTF guidelines showed the highest underdiagnosis in the 45-49 age group (17.4%), while the I-ELCAP guideline displayed the highest missed diagnosis rate (3.0%) in the 35-39 age group. Males and females significantly differed in eligibility based on the criteria of the four guidelines (P < 0.001). CONCLUSIONS: The I-ELCAP guideline has the highest eligibility rate for both males and females. But its actual efficiency ratio for those deemed eligible by the guideline was the lowest. Whereas the NCCN guideline has the highest ERe value for those deemed eligible by the guideline.

Magnetic Resonance Elastography of Anterior Mediastinal Tumors.

BACKGROUND: Preoperative differentiation of the types of mediastinal tumors is essential. Magnetic resonance (MR) elastography potentially provides a noninvasive method to assess the classification of mediastinal tumor subtypes. PURPOSE: To evaluate the use of MR elastography in anterior mediastinal masses and to characterize the mechanical properties of tumors of different subtypes. STUDY TYPE: Prospective. SUBJECTS: 189 patients with anterior mediastinal tumors (AMTs) confirmed by histopathology (62 thymomas, 53 thymic carcinomas, 57 lymphomas, and 17 germ cell tumors). FIELD STRENGTH/SEQUENCE: A gradient echo-based 2D MR elastography sequence and a diffusion-weighted imaging (DWI) sequence at 3.0 T. ASSESSMENT: Stiffness and apparent diffusion coefficients (ADC) were measured in AMTs using MR elastography-derived elastograms and DWI-derived ADC maps, respectively. The aim of this study is to identify whether MR elastography can differentiate between the histological subtypes of ATMs. STATISTICAL TESTS: One-way analysis of variance (ANOVA), two-way ANOVA, Pearson's linear correlation coefficient (r), receiver operating characteristic (ROC) curve analysis; P < 0.05 was considered significant. RESULTS: Lymphomas had significantly lower stiffness than other AMTs (4.0 ± 0.63 kPa vs. 4.8 ± 1.39 kPa). The mean stiffness of thymic carcinomas was significantly higher than that of other AMTs (5.6 ± 1.41 kPa vs. 4.2 ± 0.94 kPa). Using a cutoff value of 5.0 kPa, ROC analysis showed that lymphomas could be differentiated from other AMTs with an accuracy of 59%, sensitivity of 97%, and specificity of 38%. Using a cutoff value of 5.1 kPa, thymic carcinomas could be differentiated from other AMTs with an accuracy of 84%, sensitivity of 67%, and specificity of 90%. However, there was an overlap in the stiffness values of individual thymomas (4.2 ± 0.71; 3.9-4.5), thymic carcinomas (5.6 ± 1.41; 5.0-6.1), lymphomas (4.0 ± 0.63; 3.8-4.2), and germ cell tumors (4.5 ± 1.79; 3.3-5.6). DATA CONCLUSION: MR elastography-derived stiffness may be used to evaluate AMTs of various histologies. TECHNICAL EFFICACY: Stage 2.

A Self-supervised Learning-Based Fine-Grained Classification Model for Distinguishing Malignant From Benign Subcentimeter Solid Pulmonary Nodules.

RATIONALE AND OBJECTIVES: Diagnosing subcentimeter solid pulmonary nodules (SSPNs) remains challenging in clinical practice. Deep learning may perform better than conventional methods in differentiating benign and malignant pulmonary nodules. This study aimed to develop and validate a model for differentiating malignant and benign SSPNs using CT images. MATERIALS AND METHODS: This retrospective study included consecutive patients with SSPNs detected between January 2015 and October 2021 as an internal dataset. Malignancy was confirmed pathologically; benignity was confirmed pathologically or via follow-up evaluations. The SSPNs were segmented manually. A self-supervision pre-training-based fine-grained network was developed for predicting SSPN malignancy. The pre-trained model was established using data from the National Lung Screening Trial, Lung Nodule Analysis 2016, and a database of 5478 pulmonary nodules from the previous study, with subsequent fine-tuning using the internal dataset. The model's efficacy was investigated using an external cohort from another center, and its accuracy, sensitivity, specificity, and area under the receiver operating characteristic curve (AUC) were determined. RESULTS: Overall, 1276 patients (mean age, 56 ± 10 years; 497 males) with 1389 SSPNs (mean diameter, 7.5 ± 2.0 mm; 625 benign) were enrolled. The internal dataset was specifically enriched for malignancy. The model's performance in the internal testing set (316 SSPNs) was: AUC, 0.964 (95% confidence interval (95%CI): 0.942-0.986); accuracy, 0.934; sensitivity, 0.965; and specificity, 0.908. The model's performance in the external test set (202 SSPNs) was: AUC, 0.945 (95% CI: 0.910-0.979); accuracy, 0.911; sensitivity, 0.977; and specificity, 0.860. CONCLUSION: This deep learning model was robust and exhibited good performance in predicting the malignancy of SSPNs, which could help optimize patient management.

Transformation of a Viral Capsid from Nanocages to Nanotubes and Then to Hydrogels: Redirected Self-Assembly and Effects on Immunogenicity.

The ability to manipulate the self-assembly of proteins is essential to understanding the mechanisms of life and beneficial to fabricating advanced nanomaterials. Here, we report the transformation of the MS2 phage capsid from nanocages to nanotubes and then to nanotube hydrogels through simple point mutations guided by interfacial interaction redesign. We demonstrate that site 70, which lies in the flexible FG loop of the capsid protein (CP), is a "magic" site that can largely dictate the final morphology of assemblies. By varying the amino acid at site 70, with the aid of a cysteine-to-alanine mutation at site 46, we achieved the assembly of double-helical or single-helical nanotubes in addition to nanocages. Furthermore, an additional cysteine substitution on the surface of nanotubes mediated their cross-linking to form hydrogels with reducing agent responsiveness. The hierarchical self-assembly system allowed for the investigation of morphology-related immunogenicity of MS2 CPs, which revealed dramatic differences among nanocages, nanotubes, and nanotube hydrogels in terms of immune response types, antibody levels and T cell functions. This study provides insights into the assembly manipulation of protein nanomaterials and the customized design of nanovaccines and drug delivery systems.

Predicting epidermal growth factor receptor mutations in non-small cell lung cancer through dual-layer spectral CT: a prospective study.

OBJECTIVE: To determine whether quantitative parameters of detector-derived dual-layer spectral computed tomography (DLCT) can reliably identify epidermal growth factor receptor (EGFR) mutation status in patients with non-small cell lung cancer (NSCLC). METHODS: Patients with NSCLC who underwent arterial phase (AP) and venous phase (VP) DLCT between December 2021 and November 2022 were subdivided into the mutated and wild-type EGFR groups following EGFR mutation testing. Their baseline clinical data, conventional CT images, and spectral images were obtained. Iodine concentration (IC), iodine no water (INW), effective atomic number (Zeff), virtual monoenergetic images, the slope of the spectral attenuation curve (λHU), enhancement degree (ED), arterial enhancement fraction (AEF), and normalized AEF (NAEF) were measured for each lesion. RESULTS: Ninety-two patients (median age, 61 years, interquartile range [51, 67]; 33 men) were evaluated. The univariate analysis indicated that IC, normalized IC (NIC), INW and ED for the AP and VP, as well as Zeff and λHU for the VP were significantly associated with EGFR mutation status (all p < 0.05). INW(VP) showed the best diagnostic performance (AUC, 0.892 [95% confidence interval {CI}: 0.823, 0.960]). However, neither AEF (p = 0.156) nor NAEF (p = 0.567) showed significant differences between the two groups. The multivariate analysis showed that INW(AP) and NIC(VP) were significant predictors of EGFR mutation status, with the latter showing better performance (p = 0.029; AUC, 0.897 [95% CI: 0.816, 0.951] vs. 0.774 [95% CI: 0.675, 0.855]). CONCLUSION: Quantitative parameters of DLCT can help predict EGFR mutation status in patients with NSCLC. CRITICAL RELEVANCE STATEMENT: Quantitative parameters of DLCT, especially NIC(VP), can help predict EGFR mutation status in patients with NSCLC, facilitating appropriate and individualized treatment for them. KEY POINTS: Determining EGFR mutation status in patients with NSCLC before starting therapy is essential. Quantitative parameters of DLCT can predict EGFR mutation status in NSCLC patients. NIC in venous phase is an important parameter to guide individualized treatment selection for NSCLC patients.

Rapid translocation of NGR proteins driving polarization of PIN-activating D6 protein kinase during root gravitropism.

Root gravitropic bending represents a fundamental aspect of terrestrial plant physiology. Gravity is perceived by sedimentation of starch-rich plastids (statoliths) to the bottom of the central root cap cells. Following gravity perception, intercellular auxin transport is redirected downwards leading to an asymmetric auxin accumulation at the lower root side causing inhibition of cell expansion, ultimately resulting in downwards bending. How gravity-induced statoliths repositioning is translated into asymmetric auxin distribution remains unclear despite PIN auxin efflux carriers and the Negative Gravitropic Response of roots (NGR) proteins polarize along statolith sedimentation, thus providing a plausible mechanism for auxin flow redirection. In this study, using a functional NGR1-GFP construct, we visualized the NGR1 localization on the statolith surface and plasma membrane (PM) domains in close proximity to the statoliths, correlating with their movements. We determined that NGR1 binding to these PM domains is indispensable for NGR1 functionality and relies on cysteine acylation and adjacent polybasic regions as well as on lipid and sterol PM composition. Detailed timing of the early events following graviperception suggested that both NGR1 repolarization and initial auxin asymmetry precede the visible PIN3 polarization. This discrepancy motivated us to unveil a rapid, NGR-dependent translocation of PIN-activating AGCVIII kinase D6PK towards lower PMs of gravity-perceiving cells, thus providing an attractive model for rapid redirection of auxin fluxes following gravistimulation.

Radiological and clinical features of large consolidative-type pulmonary invasive mucinous adenocarcinoma.

BACKGROUND: This study aimed to investigate the radiological, pathological, and prognostic characteristics of large consolidative-type pulmonary invasive mucinous adenocarcinomas (IMA). METHODS: We retrospectively reviewed 738 patients who confirmed IMA between January 2010 and August 2022, and two radiologists reviewed imaging data to determine subtypes. We included 41 patients with pathologically large consolidative-type IMA. We analyzed their radiological, pathological, and prognostic characteristics. The recurrence-free survival (RFS) and overall survival (OS) were determined using the Kaplan-Meier method. RESULTS: Most lesions were located in the lower lobe, with 46.3% patients showing multiple lesions. Halo, angiogram, vacuole, air bronchogram, and dead branch sign were observed in 97.6%, 73.2%, 63.4%, 61.0%, and 61.0% of the cases, respectively. Unevenly low enhancement was observed in 88.89% of patients. T3 and T4 pathological stages were observed in 50.0% and 30.6% of patients, respectively. Lymph node metastasis was observed in 16.7% patients, with no distant metastasis. Spread-through air spaces and intrapulmonary dissemination were observed in 27.8% and 19.4% patients, respectively. Moreover, Kirsten rat sarcoma viral oncogene mutations were found in 68.6% of cases, and no epidermal growth factor receptor mutations were seen. Among all mutation sites, G12V mutation is the most common, accounting for 40%. The average RFS and OS were 19.4 and 66.4 months, respectively, with 3-year RFS and OS rates of 30.0% and 75.0%, respectively. Pleural invasion and lymph node metastasis were independent risk factors for diagnosis. CONCLUSION: Halo, vacuole, angiogram, and dead branch signs were frequently observed in consolidative-type IMA. Kirsten rat sarcoma viral oncogene mutations are common in consolidative-type IMA, especially site G12V, whereas epidermal growth factor receptor mutations were rare; therefore, gene immunotherapy was more difficult. Most patients were in stage T3-T4; however, lymph node metastasis was rare.

Dual-energy CT-based radiomics in predicting EGFR mutation status non-invasively in lung adenocarcinoma.

Objectives: Patients with epidermal growth factor receptor (EGFR) mutations in lung adenocarcinoma (LUAD) can benefit from individualized targeted therapy. This study aims to develop, compare, analyse prediction models based on dual-energy spectral computed tomography (DESCT) and CT-based radiomic features to non-invasively predict EGFR mutation status in LUAD. Materials and methods: Patients with LUAD (n = 175), including 111 patients with and 64 patients without EGFR mutations, were enrolled in the current study. All patients were randomly divided into a training dataset (122 cases) and validation dataset (53 cases) at a ratio of 7:3. After extracting CT-based radiomic, DESCT and clinical features, we built seven prediction models and a nomogram of the best prediction. Receiver operating characteristic (ROC) curves and the mean area under the curve (AUC) values were used for comparisons among the models to obtain the best prediction model for predicting EGFR mutations. Results: The best distinguishing ability is the combined model incorporating radiomic, DESCT and clinical features for predicting the EGFR mutation status with an AUC of 0.86 (95 % CI: 0.79-0.92) in the training group and an AUC value of 0.83 (95 % CI: 0.73, 0.96) in the validation group. Conclusions: Our study provides a predictive nomogram non-invasively with a combination of CT-based radiomic, DESCT and clinical features, which can provide image-based biological information for targeted therapy of LUAD with EGFR mutations.

Development of a combined radiomics and CT feature-based model for differentiating malignant from benign subcentimeter solid pulmonary nodules.

BACKGROUND: We aimed to develop a combined model based on radiomics and computed tomography (CT) imaging features for use in differential diagnosis of benign and malignant subcentimeter (≤ 10 mm) solid pulmonary nodules (SSPNs). METHODS: A total of 324 patients with SSPNs were analyzed retrospectively between May 2016 and June 2022. Malignant nodules (n = 158) were confirmed by pathology, and benign nodules (n = 166) were confirmed by follow-up or pathology. SSPNs were divided into training (n = 226) and testing (n = 98) cohorts. A total of 2107 radiomics features were extracted from contrast-enhanced CT. The clinical and CT characteristics retained after univariate and multivariable logistic regression analyses were used to develop the clinical model. The combined model was established by associating radiomics features with CT imaging features using logistic regression. The performance of each model was evaluated using the area under the receiver-operating characteristic curve (AUC). RESULTS: Six CT imaging features were independent predictors of SSPNs, and four radiomics features were selected after a dimensionality reduction. The combined model constructed by the logistic regression method had the best performance in differentiating malignant from benign SSPNs, with an AUC of 0.942 (95% confidence interval 0.918-0.966) in the training group and an AUC of 0.930 (0.902-0.957) in the testing group. The decision curve analysis showed that the combined model had clinical application value. CONCLUSIONS: The combined model incorporating radiomics and CT imaging features had excellent discriminative ability and can potentially aid radiologists in diagnosing malignant from benign SSPNs. RELEVANCE STATEMENT: The model combined radiomics features and clinical features achieved good efficiency in predicting malignant from benign SSPNs, having the potential to assist in early diagnosis of lung cancer and improving follow-up strategies in clinical work. KEY POINTS: • We developed a pulmonary nodule diagnostic model including radiomics and CT features. • The model yielded the best performance in differentiating malignant from benign nodules. • The combined model had clinical application value and excellent discriminative ability. • The model can assist radiologists in diagnosing malignant from benign pulmonary nodules.

Diagnostic performance of a deep learning-based method in differentiating malignant from benign subcentimeter (≤10 mm) solid pulmonary nodules.

Background: This study assessed the diagnostic performance of a deep learning (DL)-based model for differentiating malignant subcentimeter (≤10 mm) solid pulmonary nodules (SSPNs) from benign ones in computed tomography (CT) images compared against radiologists with 10 and 15 years of experience in thoracic imaging (medium-senior seniority). Methods: Overall, 200 SSPNs (100 benign and 100 malignant) were retrospectively collected. Malignancy was confirmed by pathology, and benignity was confirmed by follow-up or pathology. CT images were fed into the DL model to obtain the probability of malignancy (range, 0-100%) for each nodule. According to the diagnostic results, enrolled nodules were classified into benign, malignant, or indeterminate. The accuracy and diagnostic composition of the model were compared with those of the radiologists using the McNemar-Bowker test. Enrolled nodules were divided into 3-6-, 6-8-, and 8-10-mm subgroups. For each subgroup, the diagnostic results of the model were compared with those of the radiologists. Results: The accuracy of the DL model, in differentiating malignant and benign SSPNs, was significantly higher than that of the radiologists (71.5% vs. 38.5%, P<0.001). The DL model reported more benign or malignant deterministic results and fewer indeterminate results. In subgroup analysis of nodule size, the DL model also yielded higher performance in comparison with that of the radiologists, providing fewer indeterminate results. The accuracy of the two methods in the 3-6-, 6-8-, and 8-10-mm subgroups was 75.5% vs. 28.3% (P<0.001), 62.0% vs. 28.2% (P<0.001), and 77.6% vs. 55.3% (P=0.001), respectively, and the indeterminate results were 3.8% vs. 66.0%, 8.5% vs. 66.2%, and 2.6% vs. 35.5% (all P<0.001), respectively. Conclusions: The DL-based method yielded higher performance in comparison with that of the radiologists in differentiating malignant and benign SSPNs. This DL model may reduce uncertainty in diagnosis and improve diagnostic accuracy, especially for SSPNs smaller than 8 mm.

ZNT1 and Zn 2+ control TLR4 and PD-L1 endocytosis in macrophages to improve chemotherapy efficacy against liver tumor.

BACKGROUND AND AIMS: HCC is closely associated with inflammation and immune modulation, and combined chemotherapy with other strategies is under extensive investigation to achieve better efficacy. HCC is accompanied by zinc (Zn) deficiency. This study aims to understand how Zn could affect macrophage function and its application for HCC therapy. APPROACH AND RESULTS: Zn 2+ and the Zn transporter 1 (ZNT1, solute carrier family 30 member 1) were markedly reduced in intrahepatic macrophages from patients with HCC and from mouse liver tumors. Lower ZNT1 expression was associated with higher IL-6 production and shorter survival time in patients with HCC. Critically, ZNT1 regulated endosomal Zn 2+ levels for endocytosis of toll-like receptor 4 and programmed cell death ligand 1, thereby decreasing macrophage-induced inflammation and immunosuppression to protect from liver tumors. Myeloid-specific deletion of ZNT1 in mice increased chronic inflammation, liver fibrosis, tumor numbers, and size. Notably, Zn supplementation could reduce inflammation and surface programmed cell death ligand 1 expression in macrophages with the increased CD8 + T cell cytotoxicity, which synergized the antitumor efficacy of Sorafenib/Lenvatinib. CONCLUSIONS: Our study proposes a new concept that ZNT1 and Zn regulate endosome endocytosis to maintain surface receptors, and Zn supplements might be synergized with chemotherapy to treat inflammation-associated tumors, especially those containing programmed cell death ligand 1 + myeloid cells.

The Oxysterol Receptor EBI2 Links Innate and Adaptive Immunity to Limit IFN Response and Systemic Lupus Erythematosus.

Systemic lupus erythematosus (SLE) is a complex autoimmune disease with abnormal activation of the immune system. Recent attention is increasing about how aberrant lipid and cholesterol metabolism is linked together with type I interferon (IFN-I) signaling in the regulation of the pathogenesis of SLE. Here, a metabonomic analysis is performed and increased plasma concentrations of oxysterols, especially 7α, 25-dihydroxycholesterol (7α, 25-OHC), are identified in SLE patients. The authors find that 7α, 25-OHC binding to its receptor Epstein-Barr virus-induced gene 2 (EBI2) in macrophages can suppress STAT activation and the production of IFN-ß, chemokines, and cytokines. Importantly, monocytes/macrophages from SLE patients and mice show significantly reduced EBI2 expression, which can be triggered by IFN-γ produced in activated T cells. Previous findings suggest that EBI2 enhances immune cell migration. Opposite to this effect, the authors demonstrate that EBI2-deficient macrophages produce higher levels of chemokines and cytokines, which recruits and activates myeloid cells,T and B lymphocytes to exacerbate tetramethylpentadecane-induced SLE. Together, via sensing the oxysterol 7α, 25-OHC, EBI2 in macrophages can modulate innate and adaptive immune responses, which may be used as a potential diagnostic marker and therapeutic target for SLE.

Tale of cAMP as a second messenger in auxin signaling and beyond.

The 3',5'-cyclic adenosine monophosphate (cAMP) is a versatile second messenger in many mammalian signaling pathways. However, its role in plants remains not well-recognized. Recent discovery of adenylate cyclase (AC) activity for transport inhibitor response 1/auxin-signaling F-box proteins (TIR1/AFB) auxin receptors and the demonstration of its importance for canonical auxin signaling put plant cAMP research back into spotlight. This insight briefly summarizes the well-established cAMP signaling pathways in mammalian cells and describes the turbulent and controversial history of plant cAMP research highlighting the major progress and the unresolved points. We also briefly review the current paradigm of auxin signaling to provide a background for the discussion on the AC activity of TIR1/AFB auxin receptors and its potential role in transcriptional auxin signaling as well as impact of these discoveries on plant cAMP research in general.

Longitudinal assessment of cardiac parameters through MRI in breast cancer patients treated with anti-HER2 therapy.

BACKGROUND: We evaluated the early changes in left ventricular (LV) volumetric, functional, and tissue characteristics in human epidermal growth factor receptor 2 (HER2)-positive breast cancer patients treated with trastuzumab and/or pertuzumab at cardiac magnetic resonance imaging (MRI). METHODS: HER2-positive breast cancer patients undergoing planned anti-HER2 therapy and nonanthracycline-based chemotherapy were enrolled and subdivided into dual anti-HER2 (trastuzumab plus pertuzumab) group and trastuzumab group. Cardiac MRI was performed before treatment and three months after starting, covering ventricular volumes, cardiac function, systolic myocardial strain, myocardial oedema, and T1 and T2 relaxation times. Cardiac dysfunction was primarily defined as a > 10% reduction in LV ejection fraction (LVEF) to < 55% and/or a > 15% global longitudinal strain (GLS) change at the follow-up MRI examination. RESULTS: Twenty-four HER2-positive patients were evaluated (16 in the dual anti-HER2 group, 8 in the trastuzumab group). Six patients developed cardiac dysfunction at follow-up, five of them in the dual anti-HER2 group. One patient developed symptomatic heart failure, and five patients developed asymptomatic cardiac dysfunction. Patients displayed significantly decreased systolic function and increased T1 and T2 relaxation time at follow-up (p ≤ 0.031). Systolic dysfunction remained significant in the dual anti-HER2 group. The decrease in GLS in the trastuzumab group was not significant (p = 0.169). T1 and T2 relaxation times tended to increase, but this was not significant at subgroup analysis. CONCLUSIONS: Cardiac MRI scans showed frequent signs of subclinical cardiotoxicity after short-term anti-HER2 therapy and nonanthracycline-based chemotherapy; the effect was slightly stronger in patients treated with dual therapy. KEY POINTS: • A frequent subclinical cardiotoxicity was detected by cardiac magnetic resonance imaging after short-term anti-human epidermal growth factor receptor 2 (HER2) therapy. • The change in myocardial strain was more marked in patients treated with dual (trastuzumab plus pertuzumab) than with trastuzumab only anti-HER2 therapy. • Cardiotoxicity surveillance through MRI is an interesting option particularly in patients treated with dual anti-HER2 therapy.

VEGFR-3 signaling restrains the neuron-macrophage crosstalk during neurotropic viral infection.

Upon recognizing danger signals produced by virally infected neurons, macrophages in the central nervous system (CNS) secrete multiple inflammatory cytokines to accelerate neuron apoptosis. The understanding is limited about which key effectors regulate macrophage-neuron crosstalk upon infection. We have used neurotropic-virus-infected murine models to identify that vascular endothelial growth factor receptor 3 (VEGFR-3) is upregulated in the CNS macrophages and that virally infected neurons secrete the ligand VEGF-C. When cultured with VEGF-C-containing supernatants from virally infected neurons, VEGFR-3+ macrophages suppress tumor necrosis factor α (TNF-α) secretion to reduce neuron apoptosis. Vegfr-3ΔLBD/ΔLBD (deletion of ligand-binding domain in myeloid cells) mice or mice treated with the VEGFR-3 kinase inhibitor exacerbate the severity of encephalitis, TNF-α production, and neuron apoptosis post Japanese encephalitis virus (JEV) infection. Activating VEGFR-3 or blocking TNF-α can reduce encephalitis and neuronal damage upon JEV infection. Altogether, we show that the inducible VEGF-C/VEGFR-3 module generates protective crosstalk between neurons and macrophages to alleviate CNS viral infection.

Adenylate cyclase activity of TIR1/AFB auxin receptors in plants.

The phytohormone auxin is the major coordinative signal in plant development1, mediating transcriptional reprogramming by a well-established canonical signalling pathway. TRANSPORT INHIBITOR RESPONSE 1 (TIR1)/AUXIN-SIGNALING F-BOX (AFB) auxin receptors are F-box subunits of ubiquitin ligase complexes. In response to auxin, they associate with Aux/IAA transcriptional repressors and target them for degradation via ubiquitination2,3. Here we identify adenylate cyclase (AC) activity as an additional function of TIR1/AFB receptors across land plants. Auxin, together with Aux/IAAs, stimulates cAMP production. Three separate mutations in the AC motif of the TIR1 C-terminal region, all of which abolish the AC activity, each render TIR1 ineffective in mediating gravitropism and sustained auxin-induced root growth inhibition, and also affect auxin-induced transcriptional regulation. These results highlight the importance of TIR1/AFB AC activity in canonical auxin signalling. They also identify a unique phytohormone receptor cassette combining F-box and AC motifs, and the role of cAMP as a second messenger in plants.

Micronodular thymoma with lymphoid stroma: Contrast-enhanced CT features with histopathological correlation in 10 patients.

Objectives: This study aimed to evaluate and summarize the contrast-enhanced computed tomography (CECT) imaging features of micronodular thymoma with lymphoid stroma (MTWLS) based on all MTWLS patients at our institution and was the first imaging study of MTWLS worldwide. Methods: This retrospective study included 10 MTWLS patients who underwent CECT between April 2012 and November 2021. We collected and analyzed the CECT imaging features, including the location, size, shape, tumor density, classification, and CT value of the solid component. Descriptive statistical analysis was performed using the SPSS software (version 26.0; IBM). Results: Ten patients (five males [50%], five females [50%]; median age, 61.4 years; range, 54-72 years) underwent CECT. Of the 10 cases, one case was purely cystic, seven cases were cystic-solid, and two cases were purely solid. Six cases were round/oval in shape, and four cases were irregularly shaped. Excluding a purely cystic tumor with an unmeasurable degree of enhancement, two cases showed moderate enhancement, and seven cases showed significant enhancement. Among the solid or cystic-solid cases, the mean CT value of the measurable solid component on the enhanced scan was 93.9 HU. Nine masses were located adjacent to the mediastinal pleura, pericardium, or large vessels. Additionally, there were no malignant tumor signs in any patient, including penetration of the mediastinal pleura or involvement of the pericardium, pleural effusion, elevation of the diaphragm, or direct vascular invasion. Conclusion: MTWLS demonstrates certain features on CECT, such as a high rate of cystic change, significant solid component enhancement, and no malignant, invasive imaging features. These CECT features are helpful for diagnosing MTWLS.