MR-based radiomics predictive modelling of EGFR mutation and HER2 overexpression in metastatic brain adenocarcinoma: a two-centre study.

OBJECTIVES: Magnetic resonance (MR)-based radiomics features of brain metastases are utilised to predict epidermal growth factor receptor (EGFR) mutation and human epidermal growth factor receptor 2 (HER2) overexpression in adenocarcinoma, with the aim to identify the most predictive MR sequence. METHODS: A retrospective inclusion of 268 individuals with brain metastases from adenocarcinoma across two institutions was conducted. Utilising T1-weighted imaging (T1 contrast-enhanced [T1-CE]) and T2 fluid-attenuated inversion recovery (T2-FLAIR) sequences, 1,409 radiomics features were extracted. These sequences were randomly divided into training and test sets at a 7:3 ratio. The selection of relevant features was done using the least absolute shrinkage selection operator, and the training cohort's support vector classifier model was employed to generate the predictive model. The performance of the radiomics features was evaluated using a separate test set. RESULTS: For contrast-enhanced T1-CE cohorts, the radiomics features based on 19 selected characteristics exhibited excellent discrimination. No significant differences in age, sex, and time to metastasis were observed between the groups with EGFR mutations or HER2 + and those with wild-type EGFR or HER2 (p > 0.05). Radiomics feature analysis for T1-CE revealed an area under the curve (AUC) of 0.98, classification accuracy of 0.93, sensitivity of 0.92, and specificity of 0.93 in the training cohort. In the test set, the AUC was 0.82. The 19 radiomics features for the T2-FLAIR sequence showed AUCs of 0.86 in the training set and 0.70 in the test set. CONCLUSIONS: This study developed a T1-CE signature that could serve as a non-invasive adjunctive tool to determine the presence of EGFR mutations and HER2 + status in adenocarcinoma, aiding in the direction of treatment plans. CLINICAL RELEVANCE STATEMENT: We propose radiomics features based on T1-CE brain MR sequences that are both evidence-based and non-invasive. These can be employed to guide clinical treatment planning in patients with brain metastases from adenocarcinoma.

Deep learning model to predict lupus nephritis renal flare based on dynamic multivariable time-series data.

OBJECTIVES: To develop an interpretable deep learning model of lupus nephritis (LN) relapse prediction based on dynamic multivariable time-series data. DESIGN: A single-centre, retrospective cohort study in China. SETTING: A Chinese central tertiary hospital. PARTICIPANTS: The cohort study consisted of 1694 LN patients who had been registered in the Nanjing Glomerulonephritis Registry at the National Clinical Research Center of Kidney Diseases, Jinling Hospital from January 1985 to December 2010. METHODS: We developed a deep learning algorithm to predict LN relapse that consists of 59 features, including demographic, clinical, immunological, pathological and therapeutic characteristics that were collected for baseline analysis. A total of 32 227 data points were collected by the sliding window method and randomly divided into training (80%), validation (10%) and testing sets (10%). We developed a deep learning algorithm-based interpretable multivariable long short-term memory model for LN relapse risk prediction considering censored time-series data based on a cohort of 1694 LN patients. A mixture attention mechanism was deployed to capture variable interactions at different time points for estimating the temporal importance of the variables. Model performance was assessed according to C-index (concordance index). RESULTS: The median follow-up time since remission was 4.1 (IQR, 1.7-6.7) years. The interpretable deep learning model based on dynamic multivariable time-series data achieved the best performance, with a C-index of 0.897, among models using only variables at the point of remission or time-variant variables. The importance of urinary protein, serum albumin and serum C3 showed time dependency in the model, that is, their contributions to the risk prediction increased over time. CONCLUSIONS: Deep learning algorithms can effectively learn through time-series data to develop a predictive model for LN relapse. The model provides accurate predictions of LN relapse for different renal disease stages, which could be used in clinical practice to guide physicians on the management of LN patients.

Reducing heat exposure from personal cooling strategies to green city construction in China's tropical city.

With rapid industrialization and urbanization, the risk of summer heat exposure for urban dwellers has increased. The use of air conditioners (ACs) has become the most common personal cooling strategy, but further increasing fossil fuel consumption. As sustainable and affordable cooling strategies, urban parks can reduce heat exposure and substitute a part of air conditioners use. This study evaluates the heat exposure reduction from personal cooling to urban parks based on satellite images, questionnaire surveys, and network analysis in Liuzhou, one tropical city in China. We found that residents with lower income had a higher risk of heat exposure. Among the respondents, 85 % of residents chose to use ACs to alleviate high temperatures in summer, and 81.8 % among them were willing to access park cooling area (PCA) to cool off instead of using ACs. About one third parks could serve as potential alternatives (with temperatures <28 °C) to air conditioning, reducing carbon emissions by 175.93 tons per day during the hot summer and offsetting 2.5 % of urban fossil fuel carbon emissions. The design of parks should give more consideration to elder people and provide a good cooling platform for various social income groups. Future planning should also focus on accessibility to enable residents to fully utilize the parks. Building parks within 34.10 ha would provide a more efficient use of land. This research guides sustainable, high-quality growth in industrial cities and might contribute to promotion of low-carbon cities and social equity.

Radiation pneumonitis after concurrent aumolertinib and thoracic radiotherapy in EGFR-mutant non-small cell lung cancer patients.

BACKGROUND: The superior efficacy of concurrent thoracic radiotherapy (TRT) and epidermal growth factor receptor tyrosine kinase inhibitors (EGFR-TKIs) has been proven in locally advanced and advanced non-small cell lung cancer (NSCLC) patients with EGFR mutations. However, the high incidence of radiation pneumonitis (RP) reduced by concurrent TRT and TKIs has attracted widespread attention. Thus, this study was designed to investigate the rate and risk factors for RP in EGFR-positive NSCLC patients simultaneously treated with aumolertinib and TRT. METHODS: We retrospectively evaluated stage IIIA-IVB NSCLC patients treated with concurrent aumolertinib and TRT between May 2020 and December 2022 at Shandong Cancer Hospital and Institute, Shandong, China. RP was diagnosed by two senior radiologists and then graded from 1 to 5 according to the Common Terminology Criteria for Adverse Events v5.0. All risk factors were evaluated by univariate and multivariate logistic regression analyses. RESULTS: A total of 49 patients were included, the incidence of grade ≥ 2 RP was 42.9%. Grade 2 and 3 RP were observed in 28.6% and 14.3% of patients, respectively. Grade 4 to 5 RP were not observed. the gross total volume (GTV) ≥ 21 ml and ipsilateral lung V20 ≥ 25% were risk factors for RP. The median progression-free survival (PFS) in the first-line therapy group and second-line therapy group were 23.5 months and 17.2 months, respectively (p = 0.10). CONCLUSIONS: Better local control is achieved with concurrent TRT and aumolertinib, and special attention should be given to controlling ipsilateral lung V20 and GTV to reduce the risk of RP.

Differentiation between cerebral alveolar echinococcosis and brain metastases with radiomics combined machine learning approach.

BACKGROUND: Cerebral alveolar echinococcosis (CAE) and brain metastases (BM) share similar in locations and imaging appearance. However, they require distinct treatment approaches, with CAE typically treated with chemotherapy and surgery, while BM is managed with radiotherapy and targeted therapy for the primary malignancy. Accurate diagnosis is crucial due to the divergent treatment strategies. PURPOSE: This study aims to evaluate the effectiveness of radiomics and machine learning techniques based on magnetic resonance imaging (MRI) to differentiate between CAE and BM. METHODS: We retrospectively analyzed MRI images of 130 patients (30 CAE and 100 BM) from Xinjiang Medical University First Affiliated Hospital and The First People's Hospital of Kashi Prefecture, between January 2014 and December 2022. The dataset was divided into training (91 cases) and testing (39 cases) sets. Three dimensional tumors were segmented by radiologists from contrast-enhanced T1WI images on open resources software 3D Slicer. Features were extracted on Pyradiomics, further feature reduction was carried out using univariate analysis, correlation analysis, and least absolute shrinkage and selection operator (LASSO). Finally, we built five machine learning models, support vector machine, logistic regression, linear discrimination analysis, k-nearest neighbors classifier, and Gaussian naïve bias and evaluated their performance via several metrics including sensitivity (recall), specificity, positive predictive value (precision), negative predictive value, accuracy and the area under the curve (AUC). RESULTS: The area under curve (AUC) of support vector classifier (SVC), linear discrimination analysis (LDA), k-nearest neighbors (KNN), and gaussian naïve bias (NB) algorithms in training (testing) sets are 0.99 (0.94), 1.00 (0.87), 0.98 (0.92), 0.97 (0.97), and 0.98 (0.93), respectively. Nested cross-validation demonstrated the robustness and generalizability of the models. Additionally, the calibration plot and decision curve analysis demonstrated the practical usefulness of these models in clinical practice, with lower bias toward different subgroups during decision-making. CONCLUSION: The combination of radiomics and machine learning approach based on contrast enhanced T1WI images could well distinguish CAE and BM. This approach holds promise in assisting doctors with accurate diagnosis and clinical decision-making.

Prognostic value of cranial radiotherapy and optimal timing stratified by lung-molGPA for NSCLC patients with brain metastases.

PURPOSE: The updated Graded Prognostic Assessment for Lung Cancer Using Molecular Markers (lung-molGPA) index provide more accurate survival prediction for patients diagnose with advanced non-small cell lung cancer (NSCLC) with brain metastases (BM). Given that the value of cranial radiotherapy (CRT) is still controversial for NSCLC patients with BM, this retrospective study aimed to evaluate the value of CRT and optimal timing in NSCLC patients with initial BM after stratified with lung-molGPA index. METHODS: This study screened NSCLC patients with initial BM in our cancer center from February 2012 to July 2018. The prognosis value of CRT and optimal timing was evaluated with Kaplan-Meier survival analysis and the patients were classified into lung-molGPA0-2 and lung-molGPA2.5-4 group. Upfront CRT was defined as received CRT within 3 months after initial diagnosis and without BM progression, other CRT was classified into deferred CRT. RESULTS: Overall, 288 patients were enrolled in our study, 156 patients received CRT. The median follow-up time was 47 months. In the entire cohort, the median PFS and OS were 9.2 and 17.0 months, respectively. In the lung-molGPA2.5-4 group, CRT can bring significantly overall survival benefit for NSCLC patients with initial BM (HR: 0.48, 95% CI: 0.34-0.68, P < 0.0001), and the upfront CRT can further expand this survival benefits compared with deferred CRT (HR: 0.49, 95% CI: 0.27-0.89, P = 0.0026). But this phenomenon was not observed in lung-molGPA0-2 group patients. CONCLUSION: Upfront CRT could bring significantly overall survival benefit for these patients with lung-molGPA2.5-4 but not for patients with lung-molGPA0-2.

The Value of the Cardiac Magnetic Resonance Intravoxel Incoherent Motion Technique in Evaluating Microcirculatory Dysfunction in Hypertrophic Cardiomyopathy.

Objective: To evaluate the value of the cardiac magnetic resonance intravoxel incoherent motion (IVIM) technique in microcirculatory dysfunction in patients with hypertrophic cardiomyopathy (HCM). Methods: The medical records of 19 patients with HCM in our hospital from January 2020 to May 2021 were collected retrospectively, and 23 healthy people with a similar age and gender distribution to the patients with HCM were included as controls. All the included subjects underwent clinical assessment and cardiac magnetic resonance imaging. The original IVIM images were analysed, and the imaging parameters of each segment were measured. The HCM group was divided into non-hypertrophic myocardium and hypertrophic myocardium groups. The differences in imaging parameters between the normal and HCM groups were compared. A Spearman correlation analysis was used to explore the correlation between end-diastolic thickness (EDTH) and each IVIM parameter. Results: The D∗ and f values in the HCM group were lower than those in the normal group (p < 0.0001 and p = 0.004, respectively). The f, D, D∗, and EDTH values of the hypertrophic segment, non-hypertrophic segment, and normal groups were statistically significant (p < 0.05). The difference in D∗ values among the mild, moderate, severe, and very severe HCM groups was statistically significant (p < 0.05). There was a statistically significant difference in EDTH among the mild, moderate, severe, and very severe groups (p < 0.001). There were significant differences in the values of D, D∗, and f between the non-delayed enhancement group and the delayed enhancement group (p < 0.05). The EDTH values of 304 segments in the HCM group were negatively correlated with f (r = -0.219, p = 0.028) and D∗ values (r = -0.310, p < 0.001). Conclusion: The use of IVIM technology can achieve a non-invasive early quantitative assessment of microvascular disease in HCM without the injection of a contrast agent and provide a reference for the early diagnosis of and intervention in myocardial ischemia in patients with HCM.

Clinical Utility of Automated Structural Brain Volume Analysis in MRI for Evaluating Temporal Lobe Epilepsy in Fitness Athletes

Background: Investigating alterations in brain volumes among individuals with magnetic resonance-negative temporal lobe epilepsy (MRIn-MTLE) is of particular interest in the context of athletes and fitness enthusiasts. In this study, we aimed to examine these brain volume changes and their potential implications. Methods: We conducted a retrospective analysis of T1-weighted brain images from MRIn-MTLE patients and healthy controls (HC) who were actively engaged in athletics or fitness activities. Brain regions were segmented and quantified using FreeSurfer software, and we compared the volumes of ipsilateral brain regions between patients and controls. We employed Feature Explorer software, based on Pyradiomics, to construct a classification model using volume parameters and assessed its effectiveness in distinguishing between MRIn-MTLE patients and controls. Results: Significant differences in brain volumes were observed in various regions of the brain, both on the left and right sides, among both HC and MRIn-MTLE patients. Notably, these differences varied by gender. In males, the estimated total intracranial volume (eTIV) and the volumes of specific regions in the left hemisphere were larger in the HC group than in the MRIn-MTLE group. In females, certain brain regions in the right hemisphere were smaller in MRIn-MTLE patients compared to the HC group. The classification model achieved an area under the curve (AUC) of 0.780 and an accuracy of 0.721. Conclusions: Our study identified notable reductions in brain volumes among MRIn-MTLE patients who are athletes or fitness enthusiasts. Further investigations are needed to understand the underlying physiological and anatomical factors contributing to these differences. The findings suggest that brain volume measurements can serve as valuable features for constructing classification models to differentiate MRIn-MTLE patients from healthy individuals in the athletic and fitness community. (AU)

Climate gentrification along with parks' cooling performance in one of China's tropical industrial cities.

Industrialization processes have promoted economic development at the cost of climate change and heat hazards. Urban parks are effective nature-based cooling strategies, but may also bring about climate gentrification. Our study explored climate gentrification along with park cooling performance based on land surface temperature retrieved from satellite images and housing prices in Liuzhou, one of China's tropical industrial cities. We found that urban parks were with average cooling distance of 166.17 ± 11.69 m, cooling intensity of 2.85 ± 0.28 °C, covering about five times park area. The cooling lapse was 3.97 ± 0.40 °C/km. The climate gentrification was related to different accessibility to park cooling area. Residents in the urban center had better access to park cooling range than those outside the second ring road. Housing prices went up near cooling range of urban parks. To abate climate gentrification, measures should be taken, such as improving parks' cooling performance and building affordable houses. This study has significant implications for quality, efficiency and equity of park construction, and also provides suggestions for urban heat mitigation and sustainable urban development.

Vegetation growth enhancement modulated by urban development status.

Cities are natural laboratories for studying the vegetation response to global change due to their own climatic, atmospheric, and biological conditions. However, whether the urban environment promoted vegetation growth is still uncertain. Using the Yangtze River Delta (YRD), an economic powerhouse of modern China, as a case study, this paper investigated the impact of urban environment on vegetation growth at three scales: cities, sub-cities (rural-urban gradient) -pixels. Based on the satellite observations of vegetation growth indicated during 2000-2020, we explored the direct (replacement of original land by impervious surfaces) and indirect impact (e.g., climatic environment) of urbanization on vegetation growth and their trends with urbanization level. We found that significant greening accounted for 43.18 %, and significant browning accounted for 3.60 % of the pixels in the YRD. Urban area was turning green faster than suburban area. Moreover, land use change intensity (D) was a representation of the direct impact ωd of urbanization. The direct impact of urbanization on vegetation growth was positively correlated with the intensity of land use change. Furthermore, vegetation growth enhancement due to indirect impact ωi occurred in 31.71 %, 43.90 % and 41.46 % of the YRD cities in 2000, 2010 and 2020. And vegetation enhancement occurred in 94.12 % of highly urbanized cities in 2020, while in medium and low urbanization cities, the averaged indirect impact was near zero or even negative, proving that vegetation growth enhancement was modulated by urban development status. Also, the growth offset (τ) was most pronounced in high urbanization cities (4.92 %), but there was no growth compensation in medium urbanization cities (-4.48 %) and low urbanization cities (-57.47 %). When urbanization intensity reached a threshold value of 50 % in highly urbanized cities, the growth offset (τ) tended to saturate and remained unchanged. Our findings have important implications for understanding the vegetation response to continuing urbanization process and future climate change.

High post-chemotherapy TIL and increased CD4+TIL are independent prognostic factors of surgically resected NSCLC following neoadjuvant chemotherapy.

Neoadjuvant chemotherapy (NCT) has significantly improved the overall survival of patients with operable non-small cell lung cancer (NSCLC). Chemotherapy can remodel the tumor immune microenvironment (TIME) and has an important influence on antitumor immunity. For patients who underwent surgery for resected NSCLC following NCT (NCT-NSCLC), a prognostic value comparison between naïve and post-chemotherapy TIME is absent. We enrolled 89 patients with NCT-NSCLC in this study; the tumor-infiltrating lymphocyte (TIL), CD4+TIL, and CD8+TIL levels in naïve and post-chemotherapy tumor tissues were detected using immunohistochemistry staining and divided into high and low groups. Kaplan-Meier analysis revealed that major pathology response, pathological tumor, node, and metastasis stage post-NCT (ypTNM), high post-chemotherapy TIL, high post-chemotherapy CD8+TIL, low naïve CD4+TIL, low naïve CD4+/CD8+TIL ratio, and increased CD4+TIL levels post-chemotherapy were favorable prognostic factors in patients with NCT-NSCLC. Multivariate Cox analysis found that ypTNM, high post-chemotherapy TIL, and increased CD4+TIL levels post-chemotherapy were independent prognostic factors in patients with NCT-NSCLC. These results indicate that a TIME remodeled by chemotherapy plays an important role in antitumor immunity and has a better prognostic value than the naïve TIME.

End-of-Life Communication Skills Training for Undergraduate Nursing Students to Address Cultural Obstacles in China.

Nurses face many difficulties and challenges related to how patients and their families deal with communication about end-of-life (EOL) care in China because of the strong influence of traditional Chinese culture. Moreover, education and training opportunities in EOL communication skills for nursing students are rare in mainland China. This study designed a progressive case involving a common EOL communication dilemma related to traditional Chinese culture and trained 50 undergraduate nursing students in EOL communication skills. A quasi-experimental design was used to compare the training outcomes of nursing students who were divided into a standardized patient simulation group and a role-playing group. The role-playing group (23 participants) was trained via group case discussion and role-playing among classmates, while the standardized patient simulation group (27 participants) completed EOL communication training by interacting with standardized patients and their families in a high-fidelity simulation. Attitudes toward death, self-confidence in EOL communication, and communication learning were evaluated in both groups during preintervention and postintervention. The results showed that all 3 variables improved after the intervention. This study shows that EOL communication skills training has a positive effect on nursing students to a certain extent.

Associations between Lifestyle Changes, Risk Perception and Anxiety during COVID-19 Lockdowns: A Case Study in Xi'an.

The outbreak of COVID-19 dramatically changed individuals' lifestyles, which in turn triggered psychological stress and anxiety. Many previous studies have discussed the relationships between lifestyle changes and anxiety and risk perception and anxiety independently. However, few papers have discussed these factors in a comprehensive and systematic manner. We established a six-dimensional system to assess changes in individuals' lifestyles, which include dietary habits, physical activity (PA), sleep, screen time, smoking and alcohol consumption, and interaction with neighbors. Then, we collected information relating to socio-demographics, lifestyle changes, risk perception, and anxiety, and discussed their associations using multilinear and stepwise logistic regressions. The results show that not all lifestyle changes had an influence on anxiety. Changes in PA and interaction with neighbors were not significantly associated with anxiety. Risk perception was found to be inversely related to anxiety. Changes in dietary habits, family harmony, and net income were negatively related to anxiety among the group with higher risk perception. As individuals perceived a higher severity of COVID-19, the impact of their financial status on anxiety increased. These findings provide a valuable resource for local governments seeking to refine their pandemic strategies by including approaches such as advocating healthy lifestyles and stabilizing the job market to improve individuals' mental health during lockdowns.

Fatal toxicity induced by anti-PD-1 immune checkpoint inhibitor in thymic epithelial tumor.

A standard treatment for advanced thymic epithelial tumors (TETs) after initial treatment remains unavailable to date. Targeted immune checkpoint inhibitors (ICIs) of the programmed cell death-1 (PD-1) pathway may produce objective responses in TETs, notably thymic carcinoma. Findings of clinical trials suggested ICIs are a practical choice. However, the risk of severe immuno-related adverse events is higher in TETs. Concerning histologic subtypes, thymomas are more frequently associated with autoimmune disorders than carcinomas, so close monitoring is needed for thymomas. In this article, we describe four cases of fatal toxicity caused by anti-PD-1 therapy in TETs. Four patients with metastatic thymomas or carcinoma difficult to treat with first-line standard chemotherapy were treated with the anti-PD-1 drug pembrolizumab or sintilimab. The association of PD-1 inhibitors with a high proportion of severe immuno-related adverse events in TETs necessitates attentive monitoring during treatment.

Thymic epithelial tumors are the most common malignancy of the anterior mediastinum in adults, with the occurrence of approximately 1.5 cases/million. Surgery is usually the treatment of choice. However, treatment options for advanced disease are poorly understood, and data are limited. Several studies have assessed the objective responses of immune checkpoint inhibitors in patients with advanced thymic epithelial tumors. Anti-cancer immunity also increases the risk of developing adverse events related to immunotherapy. Some patients can experience lethal toxicity. This article presents four cases of developing severe adverse events to exercise caution in prescribing these agents for thymic epithelial tumor, in particular thymoma.

Early diagnosis of spinal tuberculosis by magnetic resonance: perfusion weighted imaging in a rabbit model.

BACKGROUND: This study aimed to analyze the application value of magnetic resonance (MR)-perfusion weighted imaging (PWI) in the early imaging diagnosis of rabbit spinal tuberculosis. METHODS: Spinal tuberculosis model was established using ATCC25177 Mycobacterium tuberculosis strain in the lumbar spine of rabbits. Forty rabbits were divided into 2 groups: rabbits in the experiment group were injected with 0.2 ml of 5.0 mg/ml tuberculosis suspension (n = 30) and those in the control group were injected with 0.2 ml of normal saline (n = 10) after vertebrae drilling surgery. Routine MRI and MR-PWI were performed at 4, 6, and 8 weeks after surgery. The statistical difference in terms of perfusion parameter values in the early MR-PWI scan of spinal tuberculosis between two groups was analyzed. The receiver operating characteristic (ROC) curve analysis was conducted for the accuracy of MR-PWI parameters in the early diagnosis of spinal tuberculosis. RESULTS: Except time to peak, the other perfusion parameters in the experiment group were all increased with time. In addition, the difference between the two groups, as well as the differences at each time point was statistically significant (all P < 0.05). First-pass enhancement rate (Efirst), early enhancement rate (Ee), peak height (PH), maximum slope of increase (MSI), maximum signal enhancement rate (Emax) and signal enhancement rate (SER) showed high values in early diagnosing spinal tuberculosis. CONCLUSION: The parameters including Efirst, Ee, PH, MSI, Emax and SER may provide valuable imaging evidence for the early diagnosis of spinal tuberculosis in clinical application.

Severe Pulmonary Toxicity With Concurrent Anlotinib and Chemoradiotherapy in Stage III NSCLC: The ALTER-L042 Phase 1 Clinical Trial.

Introduction: Anlotinib has brought about marked progression-free survival and overall survival benefit compared with placebos as third-line or further treatment in advanced NSCLC. Nevertheless, the safety and efficacy of concurrent anlotinib and chemoradiotherapy are still unclear. Methods: Patients with histologically or cytologically confirmed stage III NSCLC suitable for concurrent chemoradiotherapy were enrolled in this study. The enrolled patients were treated with concurrent two cycles of anlotinib and chemoradiotherapy followed by anlotinib consolidation until disease progression or intolerance toxicity. The primary end point was the maximum tolerance dose of anlotinib, whereas the secondary end point was the overall response rate. Results: Seven patients were enrolled in this study. Six patients completed concurrent anlotinib and chemoradiotherapy and then entered the consolidation period. Among the patients, 28.57% (two of seven patients) developed fatal treatment-related adverse events (fatal pneumonitis and fatal hemoptysis). In addition, two other patients developed grade 3 radiation pneumonitis; one was induced by a cold, and the patient received only 18 Gy per nine fractions of radiotherapy. This study was terminated early owing to the high rate of fatal adverse events and radiation pneumonitis. Conclusions: This study presented severe pulmonary toxicity with concurrent anlotinib and chemoradiotherapy. Several previous clinical trials evaluated the safety of concurrent bevacizumab and radiotherapy or chemoradiotherapy; all were terminated owing to severe treatment-related toxicity. Results of these studies suggest that concurrent antiangiogenic and thoracic radiotherapy should be avoided until appropriate safety data are presented, at least for bevacizumab and anlotinib.

How can urban parks be planned to maximize cooling effect in hot extremes? Linking maximum and accumulative perspectives.

How to maximize the cooling effect of urban parks in hot extremes has been closely linked to well-beings of citizens. Few studies have quantified urban parks' cooling effect in hot extremes from both maximum and accumulative perspectives. Here, we explored 65 urban parks' cooling effect based on spatially continuous cooling curves using multiple satellite images of Greater Xi'an (34°06' ∼34°34' N, 108°33' ∼109°15' E), one of China's metropolises with frequent hot extremes during July and August in 2019 summer. From maximum perspective, the urban parks cool down as far as 151.4 m, and covering 63.62 ha area, circa five times their own area in hot extremes; from accumulative perspective, the average cooling intensity is 0.78 °C along the whole continuous cooling distance spectrum, accumulated as 153.87 °C•m. And the urban parks show stronger accumulative cooling effect in hot extremes than the relative moderate temperatures. The cooling range could be maximized in large parks with dense trees, also in complex-shaped parks with strong interaction with surrounding environment. Small parks such as neighborhood parks located in the densely populated area are with maximum efficiency, cooling down about nine times their own area, which could serve as highly efficient cooling networks. Enhancing vegetation growth and coupling both blue and green infrastructures are always effective to increase accumulative cooling intensity in hot extremes. Our findings provide nature-based solutions (NBS) to counteracting heat stresses from the intense and frequent hot extremes in the future, also helpful for energy saving in the continuing climate change scenario.

A Study of Spontaneous Brain Activity on Resting-State Functional Magnetic Resonance Imaging in Adults with MRI-Negative Temporal Lobe Epilepsy.

Purpose: Patients with magnetic resonance imaging (MRI)-negative temporal lobe epilepsy (TLE-N) represent an important subgroup of temporal lobe epilepsy (TLE). Here, we aimed to combine three voxel-based local brain area analysis methods of resting-state functional MRI (rs-fMRI), to examine the TLE-N patients' resting brain function based on neural synchronization and intensity of local brain areas. Methods: The study included 47 patients with TLE, including 28 cases of drug-controlled TLE (cTLE-N) and 19 cases of drug-resistant TLE-N (rTLE-N), as well as 30 participants in the healthy control (HC) group. To comprehensively assess the altered brain function associated with TLE-N patients, we analyzed three data-driven rs-fMRI algorithms for amplitude of low-frequency fluctuations (ALFF), fractional ALFF (fALFF) and regional homogeneity (ReHo). Results: Compared to the HC group, the distribution of abnormal functional brain areas in cTLE-N patients was dominated by occipital lobe activation, as measured by increased fALFF values in the superior occipital gyrus (SOG) and increased ReHo values in the lingual gyrus (Lin), fusiform gyrus, and middle occipital gyrus. Patients with rTLE-N exhibited a diffuse distribution of abnormal functional brain areas, showing increased fALFF values in the SOG, Lin, superior temporal gyrus, and postcentral gyrus, and decreased fALFF values in the inferior frontal gyrus orbital, parahippocampal gyrus, and superior frontal gyrus orbital. The ReHo values were reduced in the orbital region of the middle frontal gyrus, the precuneus, and the parietal inferior angular gyrus; while ReHo values were elevated values in several frontal, temporal, occipital, and subcortical brain areas. Conclusion: Patients with rTLE-N have local brain activity changes in the prefrontal limbic system and default model network dysfunction, while cTLE-N patients have local brain activity changes in the visual functional areas. Different epilepsy networks exist between cTLE-N and rTLE-N.

Comprehensive Analysis and Validation of Competing Endogenous RNA Network and Tumor-infiltrating Immune Cells in Lung Adenocarcinoma.

OBJECTIVE: The potential pathogenesis of LUAD remains largely unknown. In the present study, we evaluated the competing endogenous RNA (ceRNA) regulatory network and tumorinfiltrating immune cells in LUAD. METHODS: We obtained the RNA profiles and corresponding clinical information of LUAD patients from the TCGA data portal, and identified differentially expressed mRNAs (DEmRNAs), lncRNAs (DElncRNAs), and miRNAs (DEmiRNAs) between LUAD samples and normal controls to build a ceRNA network. Additionally, the CIBERSORT algorithm was employed to analyze the patterns of immune cell infiltration. Then, two survival-predicting models were constructed based on the ceRNA network and tumor-infiltrating immune cells, which were validated by an independent GEO dataset GSE50081. Moreover, the correlation between prognosis-related ceRNAs and immune cells was also evaluated. RESULTS: In total, 484 LUAD samples and 59 normal controls were included in this study, and 15 DEmiRNAs, 94 DEmRNAs, and 7 DElncRNAs were integrated to construct the ceRNA network of LUAD. Meanwhile, differentially expressed tumor-infiltrating immune cells were also identified, and the expressions of monocytes and regulatory T cells were related to the overall survival (OS) of LUAD patients. Moreover, the prognostic prediction model based on ceRNA network or tumor-infiltrating immune cells exhibited significant power in predicting the survival of LUAD patients. Furthermore, co-expression analysis revealed that some prognosis-related ceRNAs, such as CCT6A, E2F7, SLC16A1, and SNHG3, were positively or negatively correlated with several tumorinfiltrating immune cells, such as monocytes and M1 macrophages. CONCLUSION: This study improves our understanding of the pathogenesis of LUAD and is helpful in exploring the potential therapeutic targets and prognostic biomarkers for LUAD.

Predictive power of high-resolution vessel wall magnetic resonance imaging in ischemic stroke.

BACKGROUND AND OBJECTIVE: Intracranial atherosclerotic disease (ICAD) is a key contributor to ischemic stroke and has a high recurrence rate. This study aimed to investigate the function of high-resolution vessel wall MRI (HR-VW-MRI) and evaluate plaque characteristics in patients with ICAD. METHODS: A consecutive series of patients with ICAD who underwent HR-VW-MRI were enrolled, and imaging measurements were acquired. Baseline clinical characteristics were identified. Telephone follow-up was conducted every three months. The endpoint events were the first onset or recurrence of ischemic stroke and new clinical vascular events. Patients were divided into groups with or without events according to whether the endpoint event occurred. RESULTS: A total of 70 patients (mean age = 57.6 years old) were enrolled. The median follow-up duration was 182 days. During the follow-up, 10 patients developed ischemic stroke, experienced endpoint events, and were found with 44 plaques in the artery area. A total of 169 plaques were further found in 70 patients. There were significant differences in EI, HST1, surface features, and WA reference between the two groups (P < 0.05). Logistic analysis showed that grade 2 enhancements, stenosis degree ≥ 50%, HST1, and surface features were independent prognostic factors of the onset of stroke, caused by ICAD. CONCLUSION: This prospective study demonstrates that HR-VW-MRI can identify atherosclerotic plaques in the cerebral artery and high-risk plaques, which may contribute to the prevention of ICAD and guide clinical treatment.