Clonal expansion of shared T cell receptors reveals the existence of immune commonality among different lesions of synchronous multiple primary lung cancer.

The increase in the detection rate of synchronous multiple primary lung cancer (MPLC) has posed remarkable clinical challenges due to the limited understanding of its pathogenesis and molecular features. Here, comprehensive comparisons of genomic and immunologic features between MPLC and solitary lung cancer nodule (SN), as well as different lesions of the same patient, were performed. Compared with SN, MPLC displayed a lower rate of EGFR mutation but higher rates of BRAF, MAP2K1, and MTOR mutation, which function exactly in the upstream and downstream of the same signaling pathway. Considerable heterogeneity in T cell receptor (TCR) repertoire exists among not only different patients but also among different lesions of the same patient. Invasive lesions of MPLC exhibited significantly higher TCR diversity and lower TCR expansion than those of SN. Intriguingly, different lesions of the same patient always shared a certain proportion of TCR clonotypes. Significant clonal expansion could be observed in shared TCR clonotypes, particularly in those existing in all lesions of the same patient. In conclusion, this study provided evidences of the distinctive mutational landscape, activation of oncogenic signaling pathways, and TCR repertoire in MPLC as compared with SN. The significant clonal expansion of shared TCR clonotypes demonstrated the existence of immune commonality among different lesions of the same patient and shed new light on the individually tailored precision therapy for MPLC.

Acute kidney injury in hospitalized patients with nonmalignant pleural effusions: a retrospective cohort study.

BACKGROUND: Nonmalignant pleural effusion (NMPE) is common and remains a definite health care problem. Pleural effusion was supposed to be a risk factor for acute kidney injury (AKI). Incidence of AKI in NMPE patients and whether there is correlation between the size of effusions and AKI is unknown. OBJECTIVE: To assess the incidence of AKI in NMPE inpatients and its association with effusion size. STUDY DESIGN AND METHOD: We conducted a retrospective cohort study of inpatients admitted to the Chinese PLA General Hospital with pleural effusion from 2018-2021. All patients with pleural effusions confirmed by chest radiography (CT or X-ray) were included, excluding patients with diagnosis of malignancy, chronic dialysis, end-stage renal disease (ESRD), community-acquired AKI, hospital-acquired AKI before chest radiography, and fewer than two serum creatinine tests during hospitalization. Multivariate logistic regression and LASSO logistic regression models were used to identify risk factors associated with AKI. Subgroup analyses and interaction tests for effusion volume were performed adjusted for the variables selected by LASSO. Causal mediation analysis was used to estimate the mediating effect of heart failure, pneumonia, and eGFR < 60 ml/min/1.73m2 on AKI through effusion volume. RESULTS: NMPE was present in 7.8% of internal medicine inpatients. Of the 3047 patients included, 360 (11.8%) developed AKI during hospitalization. After adjustment by covariates selected by LASSO, moderate and large effusions increased the risk of AKI compared with small effusions (moderate: OR 1.47, 95%CI 1.11-1.94 p = 0.006; large: OR 1.86, 95%CI 1.05-3.20 p = 0.028). No significant modification effect was observed among age, gender, diabetes, bilateral effusions, and eGFR. Volume of effusions mediated 6.8% (p = 0.005), 4.0% (p = 0.046) and 4.6% (p < 0.001) of the effect of heart failure, pneumonia and low eGFR on the development of AKI respectively. CONCLUSION: The incidence of AKI is high among NMPE patients. Moderate and large effusion volume is independently associated with AKI compared to small size. The effusion size acts as a mediator in heart failure, pneumonia, and eGFR.

Halofantrine Hydrochloride Acts as an Antioxidant Ability Inhibitor That Enhances Oxidative Stress Damage to Candida albicans.

Candida albicans, a prominent opportunistic pathogenic fungus in the human population, possesses the capacity to induce life-threatening invasive candidiasis in individuals with compromised immune systems despite the existence of antifungal medications. When faced with macrophages or neutrophils, C. albicans demonstrates its capability to endure oxidative stress through the utilization of antioxidant enzymes. Therefore, the enhancement of oxidative stress in innate immune cells against C. albicans presents a promising therapeutic approach for the treatment of invasive candidiasis. In this study, we conducted a comprehensive analysis of a library of drugs approved by the Food and Drug Administration (FDA). We discovered that halofantrine hydrochloride (HAL) can augment the antifungal properties of oxidative damage agents (plumbagin, menadione, and H2O2) by suppressing the response of C. albicans to reactive oxygen species (ROS). Furthermore, our investigation revealed that the inhibitory mechanism of HAL on the oxidative response is dependent on Cap1. In addition, the antifungal activity of HAL has been observed in the Galleria mellonella infection model. These findings provide evidence that targeting the oxidative stress response of C. albicans and augmenting the fungicidal capacity of oxidative damage agents hold promise as effective antifungal strategies.

Optical and Structural Properties of Aluminum Nitride Epi-Films at Room and High Temperature.

The high-quality aluminum nitride (AlN) epilayer is the key factor that directly affects the performance of semiconductor deep-ultraviolet (DUV) photoelectronic devices. In this work, to investigate the influence of thickness on the quality of the AlN epilayer, two AlN-thick epi-film samples were grown on c-plane sapphire substrates. The optical and structural characteristics of AlN films are meticulously examined by using high-resolution X-ray diffraction (HR-XRD), scanning electron microscopy (SEM), a dual-beam ultraviolet-visible spectrophotometer, and spectroscopic ellipsometry (SE). It has been found that the quality of AlN can be controlled by adjusting the AlN film thickness. The phenomenon, in which the thicker AlNn film exhibits lower dislocations than the thinner one, demonstrates that thick AlN epitaxial samples can work as a strain relief layer and, in the meantime, help significantly bend the dislocations and decrease total dislocation density with the thicker epi-film. The Urbach's binding energy and optical bandgap (Eg) derived by optical transmission (OT) and SE depend on crystallite size, crystalline alignment, and film thickness, which are in good agreement with XRD and SEM results. It is concluded that under the treatment of thickening film, the essence of crystal quality is improved. The bandgap energies of AlN samples obtained from SE possess larger values and higher accuracy than those extracted from OT. The Bose-Einstein relation is used to demonstrate the bandgap variation with temperature, and it is indicated that the thermal stability of bandgap energy can be improved with an increase in film thickness. It is revealed that when the thickness increases to micrometer order, the thickness has little effect on the change of Eg with temperature.

A machine learning-based model for clinical prediction of distal metastasis in chondrosarcoma: a multicenter, retrospective study.

Background: The occurrence of distant metastases (DM) limits the overall survival (OS) of patients with chondrosarcoma (CS). Early diagnosis and treatment of CS remains a great challenge in clinical practice. The aim of this study was to investigate metastatic factors and develop a risk stratification model for clinicians' decision-making. Methods: Six machine learning (ML) algorithms, including logistic regression (LR), plain Bayesian classifier (NBC), decision tree (DT), random forest (RF), gradient boosting machine (GBM) and extreme gradient boosting (XGBoost). A 10-fold cross-validation was performed for each model separately, multicenter data was used as external validation, and the best (highest AUC) model was selected to build the network calculator. Results: A total of 1,385 patients met the inclusion criteria, including 82 (5.9%) patients with metastatic CS. Multivariate logistic regression analysis showed that the risk of DM was significantly higher in patients with higher pathologic grades, T-stage, N-stage, and non-left primary lesions, as well as those who did not receive surgery and chemotherapy. The AUC of the six ML algorithms for predicting DM ranged from 0.911-0.985, with the extreme gradient enhancement algorithm (XGBoost) having the highest AUC. Therefore, we used the XGB model and uploaded the results to an online risk calculator for estimating DM risk. Conclusions: In this study, combined with adequate SEER case database and external validation with data from multicenter institutions in different geographic regions, we confirmed that CS, T, N, laterality, and grading of surgery and chemotherapy were independent risk factors for DM. Based on the easily available clinical risk factors, machine learning algorithms built the XGB model that predicts the best outcome for DM. An online risk calculator helps simplify the patient assessment process and provides decision guidance for precision medicine and long-term cancer surveillance, which contributes to the interpretability of the model.

Gold-Nanorod-Assisted Live Cell Nuclear Imaging Based on Near-Infrared II Dark-Field Microscopy.

Dark-field microscopy offers several advantages, including high image contrast, minimal cell damage, and the absence of photobleaching of nanoprobes, which make it highly advantageous for cell imaging. The NIR-II window has emerged as a prominent research focus in optical imaging in recent years, with its low autofluorescence background in biological samples and high imaging SBR. In this study, we initially compared dark-field imaging results of colorectal cancer cells in both visible and NIR-II wavelengths, confirming the superior performance of NIR-II imaging. Subsequently, we synthesized gold nanorods with localized surface plasmon resonance (LSPR) absorption peaks in the NIR-II window. After bio-compatible modification, we non-specifically labeled colorectal cancer cells for NIR-II dark-field scattering imaging. The imaging results revealed a sixfold increase in SBR, especially in the 1425-1475 nm wavelength range. Finally, we applied this imaging system to perform dark-field imaging of cell nuclei in the NIR-II region and used GNRs for specific nuclear labeling in colorectal cancer cells. The resulting images exhibited higher SBR than non-specifically-labeled cell imaging, and the probe's labeling was precise, confirming the potential application of this system in photothermal therapy and drug delivery for cancer cells.

Trapping and diffusion of hydrogen in iron-doped Y2O3.

Y2O3 is a promising material for use as a tritium permeation barrier (TPB) coating and as dispersed particles in oxide dispersion strengthened steels for experimental fusion reactors. By using first-principles approaches, we found that substituting Fe for Y in Y2O3 is the most energetically favourable under O-deficient and H-rich conditions, leading to easier formation of the nearby O vacancies. These O vacancies serve as effective trapping sites for H atoms with a formation energy of -2.36 eV. The presence of Fe defects also makes it more difficult for H atoms to migrate in Y2O3 from three possible H-related defects. These findings suggest that incorporating Fe into Y2O3 could yield a better TPB and provide insight into the improved H trapping ability of Y2O3 with Fe dopants.

Assessment of patients' preferences for new anticancer drugs in China: a best-worst discrete choice experiment on three common cancer types.

OBJECTIVES: Despite the advancement in anticancer drug therapies, cancer treatment decisions are often complex and preference-sensitive, making them well suited for studying shared decision-making (SDM). Our study aimed to assess preferences for new anticancer drugs among three common types of patients with cancer to inform SDM. DESIGN: We identified five attributes of new anticancer drugs and used a Bayesian-efficient design to generate choice sets for a best-worst discrete choice experiment (BWDCE). The mixed logit regression model was applied to estimate patient-reported preferences for each attribute. The interaction model was used to investigate preference heterogeneity. SETTING: The BWDCE was conducted in Jiangsu province and Hebei province in China. PARTICIPANTS: Patients aged 18 years or older, who had a definite diagnosis of lung cancer, breast cancer or colorectal cancer were recruited. RESULTS: Data from 468 patients were available for analysis. On average, the most valued attribute was the improvement in health-related quality of life (HRQoL) (p<0.001). The low incidence of severe to life-threatening side effects, prolonged progression-free survival and the low incidence of mild to moderate side effects were also positive predictors of patients' preferences (p<0.001). Out-of-pocket cost was a negative predictor of their preferences (p<0.001). According to subgroup analysis by type of cancer, the improvement in HRQoL remained the most valuable attribute. However, the relative importance of other attributes varied by type of cancer. Whether patients were newly diagnosed or previously diagnosed cancer cases played a dominant role in the preference heterogeneity within each subgroup. CONCLUSIONS: Our study can assist in the implementation of SDM by providing evidence on patients' preferences for new anticancer drugs. Patients should be informed of the multiattribute values of new drugs and encouraged to make decisions reflecting their values.

The PI3K-Akt-mTOR pathway mediates renal pericyte-myofibroblast transition by enhancing glycolysis through HKII.

BACKGROUND: Pericyte-myofibroblast transition (PMT) has been confirmed to contribute to renal fibrosis in several kidney diseases, and transforming growth factor-ß1 (TGF-ß1) is a well-known cytokine that drives PMT. However, the underlying mechanism has not been fully established, and little is known about the associated metabolic changes. METHODS: Bioinformatics analysis was used to identify transcriptomic changes during PMT. PDGFRß + pericytes were isolated using MACS, and an in vitro model of PMT was induced by 5 ng/ml TGF-ß1. Metabolites were analyzed by ultraperformance liquid chromatography (UPLC) and tandem mass spectrometry (MS). 2-Deoxyglucose (2-DG) was used to inhibit glycolysis via its actions on hexokinase (HK). The hexokinase II (HKII) plasmid was transfected into pericytes for HKII overexpression. LY294002 or rapamycin was used to inhibit the PI3K-Akt-mTOR pathway for mechanistic exploration. RESULTS: An increase in carbon metabolism during PMT was detected through bioinformatics and metabolomics analysis. We first detected increased levels of glycolysis and HKII expression in pericytes after stimulation with TGF-ß1 for 48 h, accompanied by increased expression of α-SMA, vimentin and desmin. Transdifferentiation was blunted when pericytes were pretreated with 2-DG, an inhibitor of glycolysis. The phosphorylation levels of PI3K, Akt and mTOR were elevated during PMT, and after inhibition of the PI3K-Akt-mTOR pathway with LY294002 or rapamycin, glycolysis in the TGF-ß1-treated pericytes was decreased. Moreover, PMT and HKII transcription and activity were blunted, but the plasmid-mediated overexpression of HKII rescued PMT inhibition. CONCLUSIONS: The expression and activity of HKII as well as the level of glycolysis were increased during PMT. Moreover, the PI3K-Akt-mTOR pathway regulates PMT by increasing glycolysis through HKII regulation.

Targeted VEGFA therapy in regulating early acute kidney injury and late fibrosis.

Damage to peritubular capillaries is a key process that contributes to acute kidney injury (AKI) progression. Vascular endothelial growth factor A (VEGFA) plays a critical role in maintaining the renal microvasculature. However, the physiological role of VEGFA in various AKI durations remains unclear. A severe unilateral ischemia‒reperfusion injury model was established to provide an overview of VEGFA expression and the peritubular microvascular density from acute to chronic injury in mouse kidneys. Therapeutic strategies involving early VEGFA supplementation protecting against acute injury and late anti-VEGFA treatment for fibrosis alleviation were analyzed. A proteomic analysis was conducted to determine the potential mechanism of renal fibrosis alleviation by anti-VEGFA. The results showed that two peaks of extraglomerular VEGFA expression were observed during AKI progression: one occurred at the early phase of AKI, and the other occurred during the transition to chronic kidney disease (CKD). Capillary rarefaction progressed despite the high expression of VEGFA at the CKD stage, and VEGFA was associated with interstitial fibrosis. Early VEGFA supplementation protected against renal injury by preserving microvessel structures and counteracting secondary tubular hypoxic insults, whereas late anti-VEGFA treatment attenuated renal fibrosis progression. The proteomic analysis highlighted an array of biological processes related to fibrosis alleviation by anti-VEGFA, which included regulation of supramolecular fiber organization, cell-matrix adhesion, fibroblast migration, and vasculogenesis. These findings establish the landscape of VEGFA expression and its dual roles during AKI progression, which provides the possibility for the orderly regulation of VEGFA to alleviate early acute injury and late fibrosis.

Anti-Quenching NIR-II J-Aggregates of Benzo[c]thiophene Fluorophore for Highly Efficient Bioimaging and Phototheranostics.

Molecular fluorophores with the second near-infrared (NIR-II) emission hold great potential for deep-tissue bioimaging owing to their excellent biocompatibility and high resolution. Recently, J-aggregates are used to construct long-wavelength NIR-II emitters as their optical bands show remarkable red shifts upon forming water-dispersible nano-aggregates. However, their wide applications in the NIR-II fluorescence imaging are impeded by the limited varieties of J-type backbone and serious fluorescence quenching. Herein, a bright benzo[c]thiophene (BT) J-aggregate fluorophore (BT6) with anti-quenching effect is reported for highly efficient NIR-II bioimaging and phototheranostics. The BT fluorophores are manipulated to have Stokes shift over 400 nm and aggregation-induced emission (AIE) property for conquering the self-quenching issue of the J-type fluorophores. Upon forming BT6 assemblies in an aqueous environment, the absorption over 800 nm and NIR-II emission over 1000 nm are boosted for more than 41 and 26 folds, respectively. In vivo visualization of the whole-body blood vessel and imaging-guided phototherapy results verify that BT6 NPs are excellent agent for NIR-II fluorescence imaging and cancer phototheranostics. This work develops a strategy to construct bright NIR-II J-aggregates with precisely manipulated anti-quenching properties for highly efficient biomedical applications.

Machine learning for acute kidney injury: Changing the traditional disease prediction mode.

Acute kidney injury (AKI) is a serious clinical comorbidity with clear short-term and long-term prognostic implications for inpatients. The diversity of risk factors for AKI has been recognized in previous studies, and a series of predictive models have been developed using traditional statistical methods in conjunction with its preventability, but they have failed to meet the expectations in limited clinical applications, the rapid spread of electronic health records and artificial intelligence machine learning technology has brought new hope for the construction of AKI prediction models. In this article, we systematically review the definition and classification of machine learning methods, modeling ideas and evaluation methods, and the characteristics and current status of modeling studies. According to the modeling objectives, we subdivided them into critical care medical setting models, all medical environment models, special surgery models, special disease models, and special nephrotoxin exposure models. As the first review article to comprehensively summarize and analyze machine learning prediction models for AKI, we aim to objectively describe the advantages and disadvantages of machine learning approaches to modeling, and help other researchers more quickly and intuitively understand the current status of modeling research, inspire ideas and learn from experience, so as to guide and stimulate more research and more in-depth exploration in the future, which will ultimately provide greater help to improve the overall status of AKI diagnosis and treatment.

Accuracy of stroke volume variation and pulse pressure variation in predicting fluid responsiveness undergoing one-lung ventilation during thoracic surgery: a systematic review and meta-analysis.

Background: Stroke volume variation (SVV) and pulse pressure variation (PPV) are based on the interaction between the heart and lungs during mechanical ventilation. However, debate continues as to whether SVV and PPV can accurately predict fluid responsiveness during the one-lung ventilation (OLV). We therefore undertook a systematic review and meta-analysis of clinical trials that investigated the diagnostic value of SVV and PPV in predicting fluid responsiveness undergoing OLV during thoracic surgery. Methods: The MEDLINE, EMBASE, WANFANG, and CENTRAL databases were systematically searched for studies on the use of SVV and/or PPV in patients undergoing OLV from 2010 to 2021. Heterogeneity was assessed using I2 statistics. The funnel diagram analysis was used to test publication bias. A fixed-effects model was used to calculate the pooled values of sensitivity, specificity, the diagnostic odds ratio (DOR), and the relevant 95% confidence intervals (95% CIs). The summary receiver operating characteristic (SROC) curves were estimated, and the areas under the SROC curve were calculated. Results: In total nine studies, comprising 452 patients were ultimately included in this meta-analysis, including 217 (48%) responders and 235 (52%) nonresponders. After combining the correlation coefficients, a slight heterogeneity was found between SVV and PPV in these selected studies (I2 SVV =19.7%, I2 PPV =15.3%), and the funnel diagram also showed that the P values of SVV and PPV were 0.33 and 0.26. After the pooled analysis, the respective sensitivity of SVV and PPV in predicting fluid responsiveness was 0.66 and 0.61, the specificity was 0.62 and 0.53, the positive likelihood ratios were 1.7 and 1.3, the negative likelihood ratios were 0.55 and 0.74, and the DORs were 3 and 2. The areas under the SROC curve of SVV and PPV were 0.68 and 0.60, respectively, according to STATA SE16 software, and the combined areas under the receiver operating characteristic (ROC) curve of SVV and PPV were 0.681 and 0.604, respectively, according to MedCalc19.0.4 software. Conclusions: Current evidence suggests that SVV and PPV are not suitable for guiding intraoperative fluid therapy due to their poor ability to predict fluid responsiveness in patients undergoing OLV, and we need a better indicator instead.

An endoscopically compatible fast-gelation powder forms Janus-adhesive hydrogel barrier to prevent postoperative adhesions.

Postoperative adhesions occur widely in various tissues, bringing the risk of secondary surgery and increased medical burden. Hydrogel barriers with Janus-adhesive ability can achieve physical isolation of adjacent tissues and are therefore considered an ideal solution. However, integrating endoscopic delivery convenience and viscoelastic Janus hydrogel formation remains a great challenge. Here, we present a report of the in situ formation of Janus-adhesive hydrogel barrier using a sprayable fast-Janus-gelation (FJG) powder. We first methacrylate the polysaccharide macromolecules to break the intermolecular hydrogen bonds and impart the ability of rapid hydration. FJG powder can rapidly absorb interfacial water and crosslink through borate ester bonds, forming a toughly adhesive viscoelastic hydrogel. The Janus barrier can be simply formed by further hydrating the upper powder with cationic solution. We construct rat models to demonstrate the antiadhesions efficiency of viscoelastic FJG hydrogels in organs with different motion modalities (e.g., intestine, heart, liver). We also developed a low-cost delivery device with a standardized surgical procedure and further validated the feasibility and effectiveness of FJG powder in minimally invasive surgery using a preclinical translational porcine model. Considering the advantages in terms of therapeutic efficacy, clinical convenience, and commercialization, our results reveal the great potential of Janus-gelation powder materials as a next-generation antiadhesions barrier.

Risk Factors for Level-VII Lymph Node Metastases of Thyroid Neoplasms: A Meta-Analysis.

OBJECTIVE: The present study conducted a meta-analysis to forecast the risk factors associated with level-VII lymph node metastases in case of thyroid neoplasms, intending to assist in determining the requirement for level-VII lymph node lymphadenectomy during the surgery. METHODS: Electronic databases, PubMed, Embase, the Cochrane Library, CNKI, Wanfang Data, VIP, and CBM electronic databases were searched for studies focused on level-VII lymph node metastases in thyroid neoplasms, published up to April 2021. Stata 13.1 software was used for analyses. RESULTS: The literature search identified a total of 997 studies. Among these, 8 studies, involving 1813 patients, were included in the present case. All these studies were case-control studies. Results for meta-analysis showed that male (OR = 1.340, 95% CI: 1.018-1.764, P = .037), age < 45 years (OR = 4.178, 95% CI: 1.601-10.908, P = .003), tumor size ≥ 2.0 cm (OR = 1.960, 95% CI: 1.079-3.562, P = .027), extrathyroidal extension (OR = 2.037, 95% CI: 1.578-2.630, P < .001), distant metastasis (OR = 2.775, 95% CI: 2.005-3.840, P < .001), central lymph node metastasis (OR = 3.500, 95% CI: 1.127-10.874, P = .03), contralateral cervicolateral metastasis (OR = 2.119, 95% CI: 1.514-2.965, P < .001), and bilateral nodal metastasis (OR = 4.651, 95% CI: 2.697-8.020, P < .001) acted as risk factors for level-VII lymph node metastases. In addition to this, sensitivity analyses and bias test showed that the results of meta-analysis were reliable and stable and involved no publication bias. CONCLUSION: In the present study, male gender, age < 45 years, tumor size ≥ 2.0 cm, extrathyroidal extension, distant metastasis, central lymph node metastasis, contralateral cervicolateral metastasis, and bilateral nodal metastasis were identified as risk factors for level-VII lymph node metastases in case of thyroid neoplasms.

Preoperative Assessment of Blood Vessels and Intratumoral Microbleeds in Brain Tumors Based on a 3D Contrast-Enhanced T1 -Weighted Flow-Sensitive Black-Blood Sequence.

BACKGROUND: Three-dimensional (3D) contrast-enhanced T1 -weighted flow-sensitive black-blood (CE-T1 WI FSBB) is a newly developed black blood sequence by adding motion probing gradient pulses to gradient echo (GRE) sequences, which has important value for the preoperative assessment of tumor brain blood supply vessels and intratumoral microbleeds. PURPOSE: To compare 3D CE-T1 WI FSBB and 3D contrast-enhanced fast spin echo (FSE) sequence for T1 WI for preoperative assessment of blood vessels and microbleeds in brain tumors and to investigate the correlation between visible vessels and microbleeds. STUDY TYPE: Prospective. SUBJECTS: One hundred and seventy-five patients with brain tumors, 65 were male, 110 were female. Including histologically confirmed 73 meningiomas, 23 schwannomas, 20 gliomas, 7 hemangioblastomas, 5 metastases, 2 lymphomas, 2 hemangiopericytomas, 2 germ cell tumors, 1 craniopharyngioma, and 1 cholesteatoma. FIELD STRENGTH/SEQUENCE: A 3-T, CE-T1 WI FSBB, GRE; 3-T, CE-T1 WI, FSE. ASSESSMENT: Three neuroradiologists counted the number of intratumoral vessels on CE-T1 WI and CE-T1 WI FSBB images separately, and they counted the number of intratumoral microbleeds on CE-T1 WI FSBB images. Brain tumors were classified into grade I, grade II, and grade IV according to the World Health Organization (WHO) grading. Differences in the ability of CE-T1 WI FSBB and CE-T1 WI to display intratumoral vessels were compared. The mean counts of three observers were used to study the correlation between vessels and microbleeds. STATISTICAL TESTS: Two-way random intraclass correlation coeficient (ICC) was used for inter-reader agreement regarding intratumoral vessel and microbleed counts, and the linear regression analysis (with F-test) was used to study the correlation between intratumoral vessels and microbleeds based on CE-T1 WI FSBB (α = 0.05). RESULTS: Inter-reader agreements for intratumoral vessel count on CE-T1 WI (ICC = 0.93) and CE-T1 WI FSBB (ICC = 0.92), and the agreement for intratumoral microbleed count on CE-T1 WI FSBB (ICC = 0.99) were excellent. There were statistically significant differences in intratumoral vessel counts between CE-T1 WI and CE-T1 WI FSBB using Mann-Whitney U -test: image readers could identify more intratumoral vessels on CE-T1 WI FSBB images, particularly for meningiomas, schwannomas, gliomas, and WHO grade I tumors. The number of intratumoral vessels had a significant positive effect on the number of intratumoral microbleeds (microbleeds = 5.024 + 1.665 × vessels; F = 11.51). DATA CONCLUSION: More intratumoral vessels could potentially be identified using a 3D CE-T1 WI FSBB sequence compared to a CE-T1 WI sequence, and the number of intratumoral vessels showed a positive linear relationship with the number of intratumoral microbleeds, which might suggest that brain tumors with rich blood supply were more prone to intratumoral microbleeds. EVIDENCE LEVEL: 2 TECHNICAL EFFICACY: Stage 3.

Serum CIRP increases the risk of acute kidney injury after cardiac surgery.

Introduction: Acute kidney injury (AKI) is a frequent perioperative complication. The underlying mechanisms of cardiac surgery-associated AKI are still not completely elucidated. Cold-induced RNA-binding protein (CIRP) has been subsequently found to be regulated by various stress conditions. During cardiac surgery and cardiopulmonary bypass (CPB), the host is subjected to hypothermia and inadequate organ perfusion, resulting in an upregulation of CIRP secretion. The aim of this study is to evaluate the role of elevated extracellular CIRP level as a contributing factor in the development of AKI. Methods: A total of 292 patients who underwent cardiac surgery were retrospectively enrolled and their serum samples were collected preoperative and postoperative. Demographic data, intraoperative data, in-hospital outcomes, and the occurrence of AKI were also collected for the patients. The correlation between CIRP and intraoperative procedures, as well as its association with postoperative outcomes were analyzed. Results: In multivariable analysis, higher ΔCIRP (p = 0.036) and body mass index (p = 0.015) were independent risk factors for postoperative AKI. Meanwhile, patients with postoperative AKI exhibited lower survival rate in 2-year follow-up (p = 0.008). Compared to off-pump coronary artery bypass grafting surgery, patients who underwent on-pump coronary artery bypass grafting, valve surgery, aortic dissection and other surgery showed higher ΔCIRP, measuring 1,093, 666, 914 and 258 pg/mL, respectively (p < 0.001). The levels of ΔCIRP were significantly higher in patients who underwent CPB compared to those who did not (793.0 ± 648.7 vs. 149.5 ± 289.1 pg/mL, p < 0.001). Correlation analysis revealed a positive correlation between ΔCIRP levels and the duration of CPB (r = 0.502, p < 0.001). Patients with higher CIRP levels are at greater risk of postoperative AKI (OR: 1.67, p = 0.032), especially the stage 2-3 AKI (OR: 2.11, p = 0.037). Conclusion: CIRP secretion increases with prolonged CPB time after cardiac surgery, and CIRP secretion is positively correlated with the duration of CPB. Cardiac surgeries with CPB exhibited significantly higher levels of CIRP compared to non-CPB surgeries. Elevation of CIRP level is an independent risk factor for the incidence of AKI, especially the severe AKI, and were associated with adverse in-hospital outcomes.

Identifying Patients at Risk of Acute Kidney Injury among Patients Receiving Immune Checkpoint Inhibitors: A Machine Learning Approach.

Background: The benefits of immune checkpoint inhibitors (ICPis) in the treatment of patients with malignancies emerged recently, but immune-related adverse events (IRAEs), including acute kidney injury (AKI), cannot be ignored. The present study established and validated an ICPi-AKI prediction model based on machine learning algorithms to achieve early prediction of AKI events and timely intervention adjustment. Methods: We performed a retrospective study based on data from the First Medical Center of the PLA General Hospital. Patients with malignancy who received at least one dose of ICPi between January 2014 and December 2019 were included in the study. The characteristics of available variables were included after case review, and the baseline characteristics and clinical data of ICPi AKI and non-AKI patients were compared. After variable preprocessing, eight machine learning algorithms were used to construct a full variable availability model. Variable simplification models were constructed after screening important variables using the random forest recursive feature elimination method, and the performance of different machine learning methods and two types of modeling strategies were evaluated using multiple indicators. Results: Among the 1616 patients receiving checkpoint inhibitors, the overall incidence of AKI was 6.9% during the total follow-up time. Sixty-eight patients were associated with ICPi treatment after chart review, primarily in AKI stage 1 (70.5%), with a median time from first ICPi administration to AKI of 12.7 (IQR 2 to 56) weeks. The demographic characteristics, comorbidities, and proportions of malignancy types were similar between the ICPi-AKI and non-AKI groups, but there were significant differences in multiple characteristics, such as concomitant medications and laboratory test indicators. For model performance evaluation and comparison, the AUC values of all 38 variable availability models ranged from 0.7204−0.8241, and the AUC values of the simplicity model constructed using 16 significant variables ranged from 0.7528−0.8315. The neural networks model (NNs) and support vector machine (SVM) model had the best performance in the two types of modeling strategies, respectively; however, there was no significant difference in model performance comparison (p > 0.05). In addition, compared with the full variable availability model, the performance of the variable simplicity model was slightly improved. We also found that concomitant medications contributed more to the model prediction performance by screening the optimal feature combination. Conclusion: We successfully developed a machine learning-based ICPi-AKI prediction model and validated the best prediction performance of each machine model. It is reasonable to believe that clinical decision models driven by artificial intelligence can improve AKI prediction in patients with malignancies treated with ICPi. These models can be used to assist clinicians in the early identification of patients at high risk of AKI, support effective prevention and intervention, and ultimately improve the overall benefit of antitumor therapy in the target population.

Erratum: Excretable IR-820 for in vivo NIR-II fluorescence cerebrovascular imaging and photothermal therapy of subcutaneous tumor: Erratum.

[This corrects the article DOI: 10.7150/thno.31332.].

Early and late recurrence after hepatectomy in patients with low-level HBV-DNA hepatocellular carcinoma under antiviral therapy.

BACKGROUND: Antiviral therapy has been shown to benefit long-term survival after curative hepatectomy in patients with hepatitis B virus (HBV)-associated hepatocellular carcinoma (HCC) with high levels of HBV-DNA, but the impact of antiviral therapy on patient recurrence in patients with low levels of HBV-DNA remains less clear. METHODS: This was a retrospective cohort study analyzing 296 patients with HBV-associated HCC with HBV-DNA levels < 2000 IU/mL who underwent hepatectomy at Zhongnan Hospital of Wuhan University between March 2013 and December 2017, of whom 157 patients received antiviral therapy (antiviral group) and 139 patients did not receive antiviral therapy (non-antiviral group), propensity score matching was used for survival analysis of patients in both groups, and subgroup analysis of major risk factors was performed. RESULTS: The baseline characteristics of the two groups were comparable. At a median follow-up of 54 months, the 1-, 3-, and 5-year overall survival rates after propensity score matching (PSM) were 94.9%, 80.8%, 66.5%, and 90.9%, 64.6%, 49.4% for the antiviral and non-antiviral groups, respectively, p = 0.009, and the corresponding 1-, 3-, and 5-year RFS for the two groups were 81.8%, 76.8%, 76.8%, and 67.7%, 55.6%, 55.6%, respectively. p = 0.001, and the overall survival and recurrence-free survival were significantly better in the antiviral group than in the non-antiviral group. Multi-factor COX regression analysis showed that prothrombin time ≥ 13 s, methemoglobin level ≥ 20 ng/ml, platelet count ≥ 100 × 109/L, tumor size > 5 cm, tumor multiplicity was associated with early recurrence, and antiviral treatment was an independent protective factor for early recurrence of HCC (HR, 0.431; 95% CI 0.274-0.679; p < 0.001), but not associated with a low risk of late relapse (HR, 0.822; 95% CI 0.526-1.284; p = 0.389), and the main risk factors for late relapse included AST levels > 40 IU/ml, ALP levels > 130 IU/L, and the presence of satellite nodules, and subgroup analysis showed that compared to HBeAg-positive patients, antiviral therapy could significantly prolonged the recurrence-free survival of HBeAg-negative patients. CONCLUSION: Antiviral therapy reduces early tumor recurrence after hepatectomy in patients with low levels of HBV-DNA.