HMGB1: LPS Delivery Vehicle for Caspase-11-Mediated Pyroptosis.

Recognition of cytoplasmic lipopolysaccharide (LPS) by caspase-11 leads to pyroptosis and secretion of inflammatory mediators. In this issue of Immunity, Deng et al. (2018) report that high-mobility group box 1 (HMGB1) secreted by hepatocytes delivers extracellular LPS into the cytoplasm and mediates pyroptosis.

Reconstruction of LPS Transfer Cascade Reveals Structural Determinants within LBP, CD14, and TLR4-MD2 for Efficient LPS Recognition and Transfer.

Lipopolysaccharide (LPS), the major component of the outer membrane of Gram-negative bacteria, binds Toll-like receptor 4 (TLR4)-MD2 complex and activates innate immune responses. LPS transfer to TLR4-MD2 is catalyzed by both LPS binding protein (LBP) and CD14. To define the sequential molecular interactions underlying this transfer, we reconstituted in vitro the entire LPS transfer process from LPS micelles to TLR4-MD2. Using electron microscopy and single-molecule approaches, we characterized the dynamic intermediate complexes for LPS transfer: LBP-LPS micelles, CD14-LBP-LPS micelle, and CD14-LPS-TLR4-MD2 complex. A single LBP molecule bound longitudinally to LPS micelles catalyzed multi-rounds of LPS transfer to CD14s that rapidly dissociated from LPB-LPS complex upon LPS transfer via electrostatic interactions. Subsequently, the single LPS molecule bound to CD14 was transferred to TLR4-MD2 in a TLR4-dependent manner. The definition of the structural determinants of the LPS transfer cascade to TLR4 may enable the development of targeted therapeutics for intervention in LPS-induced sepsis.

Plant cell-like tip-growing polymer precipitate with structurally embedded multistimuli sensing ability.

Soft systems that respond to external stimuli, such as heat, magnetic field, and light, find applications in a range of fields including soft robotics, energy harvesting, and biomedicine. However, most of the existing systems exhibit nondirectional, nastic movement as they can neither grow nor sense the direction of stimuli. In this regard, artificial systems are outperformed by organisms capable of directional growth in response to the sense of stimuli or tropic growth. Inspired by tropic growth schemes of plant cells and fungal hyphae, here we report an artificial multistimuli-responsive tropic tip-growing system based on nonsolvent-induced phase separation of polymer solution, where polymer precipitates as its solvent dissolves into surrounding nonsolvent. We provide a theoretical framework to predict the size and velocity of growing precipitates and demonstrate its capability of sensing the directions of gravity, mechanical contact, and light and adjusting its growing direction in response. Exploiting the embedded physical intelligence of sensing and responding to external stimuli, our soft material system achieves multiple tasks including printing 3D structures in a confined space, bypassing mechanical obstacles, and shielded transport of liquids within water.

Two different jumping mechanisms of water striders are determined by body size.

Current theory for surface tension-dominant jumps on water, created for small- and medium-sized water strider species and used in bioinspired engineering, predicts that jumping individuals are able to match their downward leg movement speed to their size and morphology such that they maximize the takeoff speed and minimize the takeoff delay without breaking the water surface. Here, we use empirical observations and theoretical modeling to show that large species (heavier than ~80 mg) could theoretically perform the surface-dominated jumps according to the existing model, but they do not conform to its predictions, and switch to using surface-breaking jumps in order to achieve jumping performance sufficient for evading attacks from underwater predators. This illustrates how natural selection for avoiding predators may break the theoretical scaling relationship between prey size and its jumping performance within one physical mechanism, leading to an evolutionary shift to another mechanism that provides protection from attacking predators. Hence, the results are consistent with a general idea: Natural selection for the maintenance of adaptive function of a specific behavior performed within environmental physical constraints leads to size-specific shift to behaviors that use a new physical mechanism that secure the adaptive function.

Explicable prioritization of genetic variants by integration of rule-based and machine learning algorithms for diagnosis of rare Mendelian disorders.

BACKGROUND: In the process of finding the causative variant of rare diseases, accurate assessment and prioritization of genetic variants is essential. Previous variant prioritization tools mainly depend on the in-silico prediction of the pathogenicity of variants, which results in low sensitivity and difficulty in interpreting the prioritization result. In this study, we propose an explainable algorithm for variant prioritization, named 3ASC, with higher sensitivity and ability to annotate evidence used for prioritization. 3ASC annotates each variant with the 28 criteria defined by the ACMG/AMP genome interpretation guidelines and features related to the clinical interpretation of the variants. The system can explain the result based on annotated evidence and feature contributions. RESULTS: We trained various machine learning algorithms using in-house patient data. The performance of variant ranking was assessed using the recall rate of identifying causative variants in the top-ranked variants. The best practice model was a random forest classifier that showed top 1 recall of 85.6% and top 3 recall of 94.4%. The 3ASC annotates the ACMG/AMP criteria for each genetic variant of a patient so that clinical geneticists can interpret the result as in the CAGI6 SickKids challenge. In the challenge, 3ASC identified causal genes for 10 out of 14 patient cases, with evidence of decreased gene expression for 6 cases. Among them, two genes (HDAC8 and CASK) had decreased gene expression profiles confirmed by transcriptome data. CONCLUSIONS: 3ASC can prioritize genetic variants with higher sensitivity compared to previous methods by integrating various features related to clinical interpretation, including features related to false positive risk such as quality control and disease inheritance pattern. The system allows interpretation of each variant based on the ACMG/AMP criteria and feature contribution assessed using explainable AI techniques.

Recent application of CRISPR-Cas12 and OMEGA system for genome editing.

In 2012, it was discovered that precise gene editing could be induced in target DNA using the reprogrammable characteristics of the CRISPR system. Since then, several studies have investigated the potential of the CRISPR system to edit various biological organisms. For the typical CRISPR system obtained from bacteria and archaea, many application studies have been conducted and have spread to various fields. To date, orthologs with various characteristics other than CRISPR-Cas9 have been discovered and are being intensively studied in the field of gene editing. CRISPR-Cas12 and its varied orthologs are representative examples of genome editing tools and have superior properties in terms of in vivo target gene editing compared with Cas9. Recently, TnpB and Fanzor of the OMEGA (obligate mobile element guided activity) system were identified to be the ancestor of CRISPR-Cas12 on the basis of phylogenetic analysis. Notably, the compact sizes of Cas12 and OMEGA endonucleases allow adeno-associated virus (AAV) delivery; hence, they are set to challenge Cas9 for in vivo gene therapy. This review is focused on these RNA-guided reprogrammable endonucleases: their structure, biochemistry, off-target effects, and applications in therapeutic gene editing.

Associations Between Extreme Temperatures and Cardiovascular Cause-Specific Mortality: Results From 27 Countries.

BACKGROUND: Cardiovascular disease is the leading cause of death worldwide. Existing studies on the association between temperatures and cardiovascular deaths have been limited in geographic zones and have generally considered associations with total cardiovascular deaths rather than cause-specific cardiovascular deaths. METHODS: We used unified data collection protocols within the Multi-Country Multi-City Collaborative Network to assemble a database of daily counts of specific cardiovascular causes of death from 567 cities in 27 countries across 5 continents in overlapping periods ranging from 1979 to 2019. City-specific daily ambient temperatures were obtained from weather stations and climate reanalysis models. To investigate cardiovascular mortality associations with extreme hot and cold temperatures, we fit case-crossover models in each city and then used a mixed-effects meta-analytic framework to pool individual city estimates. Extreme temperature percentiles were compared with the minimum mortality temperature in each location. Excess deaths were calculated for a range of extreme temperature days. RESULTS: The analyses included deaths from any cardiovascular cause (32 154 935), ischemic heart disease (11 745 880), stroke (9 351 312), heart failure (3 673 723), and arrhythmia (670 859). At extreme temperature percentiles, heat (99th percentile) and cold (1st percentile) were associated with higher risk of dying from any cardiovascular cause, ischemic heart disease, stroke, and heart failure as compared to the minimum mortality temperature, which is the temperature associated with least mortality. Across a range of extreme temperatures, hot days (above 97.5th percentile) and cold days (below 2.5th percentile) accounted for 2.2 (95% empirical CI [eCI], 2.1-2.3) and 9.1 (95% eCI, 8.9-9.2) excess deaths for every 1000 cardiovascular deaths, respectively. Heart failure was associated with the highest excess deaths proportion from extreme hot and cold days with 2.6 (95% eCI, 2.4-2.8) and 12.8 (95% eCI, 12.2-13.1) for every 1000 heart failure deaths, respectively. CONCLUSIONS: Across a large, multinational sample, exposure to extreme hot and cold temperatures was associated with a greater risk of mortality from multiple common cardiovascular conditions. The intersections between extreme temperatures and cardiovascular health need to be thoroughly characterized in the present day-and especially under a changing climate.

Automated Prediction of Proximal Middle Cerebral Artery Occlusions in Noncontrast Brain Computed Tomography.

BACKGROUND: Early identification of large vessel occlusion (LVO) in patients with ischemic stroke is crucial for timely interventions. We propose a machine learning-based algorithm (JLK-CTL) that uses handcrafted features from noncontrast computed tomography to predict LVO. METHODS: We included patients with ischemic stroke who underwent concurrent noncontrast computed tomography and computed tomography angiography in seven hospitals. Patients from 5 of these hospitals, admitted between May 2011 and March 2015, were randomly divided into training and internal validation (9:1 ratio). Those from the remaining 2 hospitals, admitted between March 2021 and September 2021, were designated for external validation. From each noncontrast computed tomography scan, we extracted differences in volume, tissue density, and Hounsfield unit distribution between bihemispheric regions (striatocapsular, insula, M1-M3, and M4-M6, modified from the Alberta Stroke Program Early Computed Tomography Score). A deep learning algorithm was used to incorporate clot signs as an additional feature. Machine learning models, including ExtraTrees, random forest, extreme gradient boosting, support vector machine, and multilayer perceptron, as well as a deep learning model, were trained and evaluated. Additionally, we assessed the models' performance after incorporating the National Institutes of Health Stroke Scale scores as an additional feature. RESULTS: Among 2919 patients, 83 were excluded. Across the training (n=2463), internal validation (n=275), and external validation (n=95) datasets, the mean ages were 68.5±12.4, 67.6±13.8, and 67.9±13.6 years, respectively. The proportions of men were 57%, 53%, and 59%, with LVO prevalences of 17.0%, 16.4%, and 26.3%, respectively. In the external validation, the ExtraTrees model achieved a robust area under the curve of 0.888 (95% CI, 0.850-0.925), with a sensitivity of 80.1% (95% CI, 72.0-88.1) and a specificity of 88.6% (95% CI, 84.7-92.5). Adding the National Institutes of Health Stroke Scale score to the ExtraTrees model increased sensitivity (from 80.1% to 92.1%) while maintaining specificity. CONCLUSIONS: Our algorithm provides reliable predictions of LVO using noncontrast computed tomography. By enabling early LVO identification, our algorithm has the potential to expedite the stroke workflow.

The Role of the Aryl Hydrocarbon Receptor in Vascular Factors Related to Preeclampsia in a Smoking Mouse Model.

Smoking cigarettes is known to lower the risk of preeclampsia. The objective of this study is to evaluate the effect of smoking on the expression of soluble FMS-like tyrosine kinase-1 (sFlt-1), vascular endothelial growth factor (VEGF), and endoglin (sEng)-1 and the role of the aryl hydrocarbon receptor (AhR) in pregnant mice. We developed a smoking mouse model using a gas-filling system. One or two cigarettes per day were exposed to each of the five pregnant mice for five days a week throughout pregnancy. AhR agonist and antagonist were injected. Serum levels and expression in the placenta of sFlt-1, VEGF, and sEng-1 were analyzed and compared among the cigarette smoke and no-exposure groups after delivery. Compared to the no-smoke exposure group, the serum level of sFlt-1 was significantly decreased in the two-cigarette-exposed group (p < 0.001). When the AhR antagonist was added to the two-cigarette-exposed group, sFlt-1 levels were significantly increased compared to the two-cigarette group (p = 0.002). The levels of sFlt-1 in the AhR antagonist group did not change regardless of two-cigarette exposure (p = 0.064). With the AhR agonist, sFlt-1 decreased significantly compared to the control (p = 0.001) and AhR antagonist group (p = 0.002). The sFlt-1 level was significantly decreased after the injection of the AhR agonist compared to the control group (p = 0.001). Serum levels of VEGF were significantly decreased in the one-cigarette-exposed group compared to the control group; however, there was no difference between the control and the two-cigarette-exposed groups. The placental expression of sFlt-1, VEGF, and sEng were inconsistent. This study offers insights into the potential role of AhR on antiangiogenic sFlt-1 associated with preeclampsia. It may support the invention of a new treatment strategy for preeclampsia using AhR activation.

Efficacy of GV1001 with gemcitabine/capecitabine in previously untreated patients with advanced pancreatic ductal adenocarcinoma having high serum eotaxin levels (KG4/2015): an open-label, randomised, Phase 3 trial.

BACKGROUND: The TeloVac study indicated GV1001 did not improve the survival of advanced pancreatic ductal adenocarcinoma (PDAC). However, the cytokine examinations suggested that high serum eotaxin levels may predict responses to GV1001. This Phase III trial assessed the efficacy of GV1001 with gemcitabine/capecitabine for eotaxin-high patients with untreated advanced PDAC. METHODS: Patients recruited from 16 hospitals received gemcitabine (1000 mg/m2, D 1, 8, and 15)/capecitabine (830 mg/m2 BID for 21 days) per month either with (GV1001 group) or without (control group) GV1001 (0.56 mg; D 1, 3, and 5, once on week 2-4, 6, then monthly thereafter) at random in a 1:1 ratio. The primary endpoint was overall survival (OS) and secondary end points included time to progression (TTP), objective response rate, and safety. RESULTS: Total 148 patients were randomly assigned to the GV1001 (n = 75) and control groups (n = 73). The GV1001 group showed improved median OS (11.3 vs. 7.5 months, P = 0.021) and TTP (7.3 vs. 4.5 months, P = 0.021) compared to the control group. Grade >3 adverse events were reported in 77.3% and 73.1% in the GV1001 and control groups (P = 0.562), respectively. CONCLUSIONS: GV1001 plus gemcitabine/capecitabine improved OS and TTP compared to gemcitabine/capecitabine alone in eotaxin-high patients with advanced PDAC. CLINICAL TRIAL REGISTRATION: NCT02854072.

Efficient computation of Faith's phylogenetic diversity with applications in characterizing microbiomes.

The number of publicly available microbiome samples is continually growing. As data set size increases, bottlenecks arise in standard analytical pipelines. Faith's phylogenetic diversity (Faith's PD) is a highly utilized phylogenetic alpha diversity metric that has thus far failed to effectively scale to trees with millions of vertices. Stacked Faith's phylogenetic diversity (SFPhD) enables calculation of this widely adopted diversity metric at a much larger scale by implementing a computationally efficient algorithm. The algorithm reduces the amount of computational resources required, resulting in more accessible software with a reduced carbon footprint, as compared to previous approaches. The new algorithm produces identical results to the previous method. We further demonstrate that the phylogenetic aspect of Faith's PD provides increased power in detecting diversity differences between younger and older populations in the FINRISK study's metagenomic data.

MRI Scoring Systems for Predicting Isocitrate Dehydrogenase Mutation and Chromosome 1p/19q Codeletion in Adult-type Diffuse Glioma Lacking Contrast Enhancement.

Background According to 2021 World Health Organization criteria, adult-type diffuse gliomas include glioblastoma, isocitrate dehydrogenase (IDH)-wildtype; oligodendroglioma, IDH-mutant and 1p/19q-codeleted; and astrocytoma, IDH-mutant, even when contrast enhancement is lacking. Purpose To develop and validate simple scoring systems for predicting IDH and subsequent 1p/19q codeletion status in gliomas without contrast enhancement using standard clinical MRI sequences. Materials and Methods This retrospective study included adult-type diffuse gliomas lacking contrast at contrast-enhanced MRI from two tertiary referral hospitals between January 2012 and April 2022 with diagnoses confirmed at pathology. IDH status was predicted primarily by using T2-fluid-attenuated inversion recovery (FLAIR) mismatch sign, followed by 1p/19q codeletion prediction. A visual rating of MRI features, apparent diffusion coefficient (ADC) ratio, and relative cerebral blood volume was measured. Scoring systems were developed through univariable and multivariable logistic regressions and underwent calibration and discrimination, including internal and external validation. Results For the internal validation cohort, 237 patients were included (mean age, 44.4 years ± 14.4 [SD]; 136 male patients; 193 patients in IDH prediction and 163 patients in 1p/19q prediction). For the external validation cohort, 35 patients were included (46.1 years ± 15.3; 20 male patients; 28 patients in IDH prediction and 24 patients in 1p/19q prediction). The T2-FLAIR mismatch sign demonstrated 100% specificity and 100% positive predictive value for IDH mutation. IDH status prediction scoring system for tumors without mismatch sign included age, ADC ratio, and morphologic characteristics, whereas 1p/19q codeletion prediction for IDH-mutant gliomas included ADC ratio, cortical involvement, and mismatch sign. For IDH status and 1p/19q codeletion prediction, bootstrap-corrected areas under the receiver operating characteristic curve were 0.86 (95% CI: 0.81, 0.90) and 0.73 (95% CI: 0.65, 0.81), respectively, whereas at external validation they were 0.99 (95% CI: 0.98, 1.0) and 0.88 (95% CI: 0.63, 1.0). Conclusion The T2-FLAIR mismatch sign and scoring systems using standard clinical MRI predicted IDH and 1p/19q codeletion status in gliomas lacking contrast enhancement. © RSNA, 2024 Supplemental material is available for this article. See also the editorial by Badve and Hodges in this issue.

Challenges in benchmarking metagenomic profilers.

Accurate microbial identification and abundance estimation are crucial for metagenomics analysis. Various methods for classification of metagenomic data and estimation of taxonomic profiles, broadly referred to as metagenomic profilers, have been developed. Nevertheless, benchmarking of metagenomic profilers remains challenging because some tools are designed to report relative sequence abundance while others report relative taxonomic abundance. Here we show how misleading conclusions can be drawn by neglecting this distinction between relative abundance types when benchmarking metagenomic profilers. Moreover, we show compelling evidence that interchanging sequence abundance and taxonomic abundance will influence both per-sample summary statistics and cross-sample comparisons. We suggest that the microbiome research community pay attention to potentially misleading biological conclusions arising from this issue when benchmarking metagenomic profilers, by carefully considering the type of abundance data that were analyzed and interpreted and clearly stating the strategy used for metagenomic profiling.

Ravulizumab in Aquaporin-4-Positive Neuromyelitis Optica Spectrum Disorder.

OBJECTIVE: CHAMPION-NMOSD (NCT04201262) is a phase 3, open-label, externally controlled interventional study evaluating the efficacy and safety of the terminal complement inhibitor ravulizumab in adult patients with anti-aquaporin-4 antibody-positive (AQP4+) neuromyelitis optica spectrum disorder (NMOSD). Ravulizumab binds the same complement component 5 epitope as the approved therapeutic eculizumab but has a longer half-life, enabling an extended dosing interval (8 vs 2 weeks). METHODS: The availability of eculizumab precluded the use of a concurrent placebo control in CHAMPION-NMOSD; consequently, the placebo group of the eculizumab phase 3 trial PREVENT (n = 47) was used as an external comparator. Patients received weight-based intravenous ravulizumab on day 1 and maintenance doses on day 15, then once every 8 weeks. The primary endpoint was time to first adjudicated on-trial relapse. RESULTS: The primary endpoint was met; no patients taking ravulizumab (n = 58) had an adjudicated relapse (during 84.0 patient-years of treatment) versus 20 patients with adjudicated relapses in the placebo group of PREVENT (during 46.9 patient-years; relapse risk reduction = 98.6%, 95% confidence interval = 89.7%-100.0%, p < 0.0001). Median (range) study period follow-up time was 73.5 (11.0-117.7) weeks for ravulizumab. Most treatment-emergent adverse events were mild/moderate; no deaths were reported. Two patients taking ravulizumab experienced meningococcal infections. Both recovered with no sequelae; one continued ravulizumab treatment. INTERPRETATION: Ravulizumab significantly reduced relapse risk in patients with AQP4+ NMOSD, with a safety profile consistent with those of eculizumab and ravulizumab across all approved indications. ANN NEUROL 2023;93:1053-1068.

Immunosuppressive therapy in elderly patients with neuromyelitis optica spectrum disorder: a retrospective multicentre study.

BACKGROUND: The risk-benefit relationship of immunosuppressive therapies (ISTs) for elderly patients with neuromyelitis optica spectrum disorder (NMOSD) is not well established. This study aimed to investigate the safety and efficacy of IST in elderly patients with NMOSD. METHODS: This retrospective study analysed IST efficacy and safety in 101 patients with aquaporin-4 antibody-positive NMOSD aged over 65 years, treated for at least 6 months at five Korean referral centres, focusing on relapse rates, infection events and discontinuation due to adverse outcomes. RESULTS: The mean age at disease onset was 59.8 years, and female-to-male ratio was 4:1. Concomitant comorbidities at NMOSD diagnosis were found in 87 patients (86%). The median Expanded Disability Status Scale score at the initiation of IST was 3.5. The administered ISTs included azathioprine (n=61, 60%), mycophenolate mofetil (MMF) (n=48, 48%) and rituximab (n=41, 41%). Over a median of 5.8 years of IST, 58% of patients were relapse-free. The median annualised relapse rate decreased from 0.76 to 0 (p<0.001), and 81% experienced improved or stabilised disability. Patients treated with rituximab had a higher relapse-free rate than those treated with azathioprine or MMF (p=0.022). During IST, 21 patients experienced 25 severe infection events (SIEs) over the age of 65 years, and 3 died from pneumonia. 14 patients (14%) experienced 17 adverse events that led to switching or discontinuation of IST. When comparing the incidence rates of SIEs and adverse events, no differences were observed among patients receiving azathioprine, MMF and rituximab. CONCLUSION: In elderly patients with NMOSD, IST offers potential benefits in reducing relapse rates alongside a tolerable risk of adverse events.

Deep learning-based detection and quantification of brain metastases on black-blood imaging can provide treatment suggestions: a clinical cohort study.

OBJECTIVES: We aimed to evaluate whether deep learning-based detection and quantification of brain metastasis (BM) may suggest treatment options for patients with BMs. METHODS: The deep learning system (DLS) for detection and quantification of BM was developed in 193 patients and applied to 112 patients that were newly detected on black-blood contrast-enhanced T1-weighted imaging. Patients were assigned to one of 3 treatment suggestion groups according to the European Association of Neuro-Oncology (EANO)-European Society for Medical Oncology (ESMO) recommendations using number and volume of the BMs detected by the DLS: short-term imaging follow-up without treatment (group A), surgery or stereotactic radiosurgery (limited BM, group B), or whole-brain radiotherapy or systemic chemotherapy (extensive BM, group C). The concordance between the DLS-based groups and clinical decisions was analyzed with or without consideration of targeted agents. The performance of distinguishing high-risk (B + C) was calculated. RESULTS: Among 112 patients (mean age 64.3 years, 63 men), group C had the largest number and volume of BM, followed by group B (4.4 and 851.6 mm3) and A (1.5 and 15.5 mm3). The DLS-based groups were concordant with the actual clinical decisions, with an accuracy of 76.8% (86 of 112). Modified accuracy considering targeted agents was 81.3% (91 of 112). The DLS showed 95% (82/86) sensitivity and 81% (21/26) specificity for distinguishing the high risk. CONCLUSION: DLS-based detection and quantification of BM have the potential to be helpful in the determination of treatment options for both low- and high-risk groups of limited and extensive BMs. CLINICAL RELEVANCE STATEMENT: For patients with newly diagnosed brain metastasis, deep learning-based detection and quantification may be used in clinical settings where prompt and accurate treatment decisions are required, which can lead to better patient outcomes. KEY POINTS: • Deep learning-based brain metastasis detection and quantification showed excellent agreement with ground-truth classifications. • By setting an algorithm to suggest treatment based on the number and volume of brain metastases detected by the deep learning system, the concordance was 81.3%. • When dividing patients into low- and high-risk groups, the sensitivity for detecting the latter was 95%.

Achieving imaging and computational reproducibility on multiparametric MRI radiomics features in brain tumor diagnosis: phantom and clinical validation.

OBJECTIVES: The Image Biomarker Standardization Initiative has helped improve the computational reproducibility of MRI radiomics features. Nonetheless, the MRI sequences and features with high imaging reproducibility are yet to be established. To determine reproducible multiparametric MRI radiomics features across test-retest, multi-scanner, and computational reproducibility comparisons, and to evaluate their clinical value in brain tumor diagnosis. METHODS: To assess reproducibility, T1-weighted imaging (T1WI), T2-weighted imaging (T2WI), and diffusion-weighted imaging (DWI) were acquired from three 3-T MRI scanners using standardized phantom, and radiomics features were extracted using two computational algorithms. Reproducible radiomics features were selected when the concordance correlation coefficient value above 0.9 across multiple sessions, scanners, and computational algorithms. Random forest classifiers were trained with reproducible features (n = 117) and validated in a clinical cohort (n = 50) to evaluate whether features with high reproducibility improved the differentiation of glioblastoma from primary central nervous system lymphomas (PCNSLs). RESULTS: Radiomics features from T2WI demonstrated higher repeatability (65-94%) than those from DWI (38-48%) or T1WI (2-92%). Across test-retest, multi-scanner, and computational comparisons, T2WI provided 41 reproducible features, DWI provided six, and T1WI provided two. The performance of the classification model with reproducible features was higher than that using non-reproducible features in both training set (AUC, 0.916 vs. 0.877) and validation set (AUC, 0.957 vs. 0.869). CONCLUSION: Radiomics features with high reproducibility across multiple sessions, scanners, and computational algorithms were identified, and they showed higher diagnostic performance than non-reproducible radiomics features in the differentiation of glioblastoma from PCNSL. CLINICAL RELEVANCE STATEMENT: By identifying the radiomics features showing higher multi-machine reproducibility, our results also demonstrated higher radiomics diagnostic performance in the differentiation of glioblastoma from PCNSL, paving the way for further research designs and clinical application in neuro-oncology. KEY POINTS: • Highly reproducible radiomics features across multiple sessions, scanners, and computational algorithms were identified using phantom and applied to clinical diagnosis. • Radiomics features from T2-weighted imaging were more reproducible than those from T1-weighted and diffusion-weighted imaging. • Radiomics features with good reproducibility had better diagnostic performance for brain tumors than features with poor reproducibility.

Dynamics of self-propelled particles in vibrated dense granular media.

We study a system consisting of a few self-propelled particles (SPPs) placed among a crowd of densely packed granular particles that are vertically vibrated in a two-dimensional circular confinement. Our experiments reveal two important findings. First, an SPP exhibits a fractal renewal process within the dense granular medium, which induces a superdiffusive behavior whose diffusion exponent increases with its aspect ratio. Second, the SPPs eventually reach the boundary and form a moving cluster, which transitions from the moving state to the static state as the number of SPPs is increased. These results suggest a simple and effective method of modulating the fluidity and directionality of granular systems via controlling the shape and the number of SPPs.

Outcomes of Lung Transplantation in Patients With Right Ventricular Dysfunction: A Single-Center Retrospective Analysis Comparing ECMO Configurations in a Bridge-to-Transplant Setting.

This study aimed to assess the lung transplantation (LT) outcomes of patients with right ventricular dysfunction (RVD), focusing on the impact of various extracorporeal membrane oxygenation (ECMO) configurations. We included adult patients who underwent LT with ECMO as a bridge-to-transplant from 2011 to 2021 at a single center. Among patients with RVD (n = 67), veno-venous (V-V) ECMO was initially applied in 79% (53/67) and maintained until LT in 52% (35/67). Due to the worsening of RVD, the configuration was changed from V-V ECMO to veno-arterial (V-A) ECMO or a right ventricular assist device with an oxygenator (Oxy-RVAD) in 34% (18/67). They showed that lactic acid levels (2-6.1 mmol/L) and vasoactive inotropic score (6.6-22.6) increased. V-A ECMO or Oxy-RVAD was initiated and maintained until LT in 21% (14/67) of cases. There was no significant difference in the survival rates among the three configuration groups (V-V ECMO vs. configuration changed vs. V-A ECMO/Oxy-RVAD). Our findings suggest that the choice of ECMO configuration for LT candidates with RVD should be determined by the patient's current hemodynamic status. Vital sign stability supports the use of V-V ECMO, while increasing lactic acid levels and vasopressor needs may require a switch to V-A ECMO or Oxy-RVAD.

The discriminative role of PROX-1 immunohistochemistry between venous malformation and lymphatic malformation of the deep type with no visible diagnostic surface skin lesion.

BACKGROUND: Venous malformations (VMs) are distinguished from lymphatic malformations (LMs) when specific diagnostic skin lesions are present. In the deep type, this is difficult by clinico-radiologic evaluation alone. We aimed to investigate the usefulness of lymphatic vessel endothelial cell (LEC) markers for the differential diagnosis of the deep VMs and LMs. METHODS: A retrospective study was conducted based on the medical records of patients with VMs and LMs who underwent biopsy with both D2-40 and PROX-1 immunohistochemistry. We compared the initial clinico-radiological diagnosis with the final pathological diagnosis and identified which ones showed a difference. RESULTS: From 261 patients who had VMs and LMs, 111 remained after the exclusion of those who showed definite surface diagnostic features. After pathological diagnosis with the expressions of D2-40 and PROX-1, 38 of 111 (34.2%) patients' final diagnoses were changed. Among these 38 cases, diagnosis was not changed by D2-40 positivity alone, but changed by PROX-1 positivity alone (52.6%) or by both (47.4%). The diagnostic changes were more frequent in the deep category (43.7%) than in the superficial category. CONCLUSIONS: Identifying the expression of D2-40, and especially PROX-1, in the differential diagnosis of VMs and LMs may provide important treatment guidelines and understanding their natural course.