Recent Progress of Advanced Functional Separators in Lithium Metal Batteries.

As a representative in the post-lithium-ion batteries (LIBs) landscape, lithium metal batteries (LMBs) exhibit high-energy densities but suffer from low coulombic efficiencies and short cycling lifetimes due to dendrite formation and complex side reactions. Separator modification holds the most promise in overcoming these challenges because it utilizes the original elements of LMBs. In this review, separators designed to address critical issues in LMBs that are fatal to their destiny according to the target electrodes are focused on. On the lithium anode side, functional separators reduce dendrite propagation with a conductive lithiophilic layer and a uniform Li-ion channel or form a stable solid electrolyte interphase layer through the continuous release of active agents. The classification of functional separators solving the degradation stemming from the cathodes, which has often been overlooked, is summarized. Structural deterioration and the resulting leakage from cathode materials are suppressed by acidic impurity scavenging, transition metal ion capture, and polysulfide shuttle effect inhibition from functional separators. Furthermore, flame-retardant separators for preventing LMB safety issues and multifunctional separators are discussed. Further expansion of functional separators can be effectively utilized in other types of batteries, indicating that intensive and extensive research on functional separators is expected to continue in LIBs.

Photosystem II monomeric antenna CP26 plays a key role in nonphotochemical quenching in Chlamydomonas.

Thermal dissipation of excess excitation energy, called nonphotochemical quenching (NPQ), is 1 of the main photoprotective mechanisms in oxygenic photosynthetic organisms. Here, we investigated the function of the monomeric photosystem II (PSII) antenna protein CP26 in photoprotection and light harvesting in Chlamydomonas reinhardtii, a model organism for green algae. We used CRISPR/Cas9 genome editing and complementation to generate cp26 knockout mutants (named k6#) that did not negatively affect CP29 accumulation, which differed from previous cp26 mutants, allowing us to compare mutants specifically deprived of CP26, CP29, or both. The absence of CP26 partially affected PSII activity, causing reduced growth at low or medium light but not at high irradiances. However, the main phenotype observed in k6# mutants was a more than 70% reduction of NPQ compared to the wild type (Wt). This phenotype was fully rescued by genetic complementation and complemented strains accumulating different levels of CP26, demonstrating that ∼50% of CP26 content, compared to the Wt, was sufficient to restore the NPQ capacity. Our findings demonstrate a pivotal role for CP26 in NPQ induction, while CP29 is crucial for PSII activity. The genetic engineering of these 2 proteins could be a promising strategy to regulate the photosynthetic efficiency of microalgae under different light regimes.

Orbital-Selective Mott Transition Effects and Nontrivial Topology of Iron Chalcogenide.

The iron-based superconductor FeSe_{1-x}Te_{x} has recently gained significant attention as a host of two distinct physical phenomena: (i) Majorana zero modes that can serve as potential topologically protected qubits, and (ii) a realization of the orbital-selective Mott transition. In this Letter, we connect these two phenomena and provide new insights into the interplay between strong electronic correlations and nontrivial topology in FeSe_{1-x}Te_{x}. Using linearized quasiparticle self-consistent GW plus dynamical mean-field theory, we show that the topologically protected Dirac surface state has substantial Fe(d_{xy}) character. The proximity to the orbital-selective Mott transition plays a dual role: it facilitates the appearance of the topological surface state by bringing the Dirac cone close to the chemical potential but destroys the Z_{2} topological superconductivity when the system is too close to the orbital-selective Mott phase. We derive a reduced effective Hamiltonian that describes the topological band. Its parameters capture all the chemical trends found in the first principles calculation. Our findings provide a framework for further study of the interplay between strong electronic correlations and nontrivial topology in other iron-based superconductors.

Utilizing systems genetics to enhance understanding into molecular targets of skin cancer.

Despite progress made with immune checkpoint inhibitors and targeted therapies, skin cancer remains a significant public health concern in the United States. The intricacies of the disease, encompassing genetics, immune responses, and external factors, call for a comprehensive approach. Techniques in systems genetics, including transcriptional correlation analysis, functional pathway enrichment analysis, and protein-protein interaction network analysis, prove valuable in deciphering intricate molecular mechanisms and identifying potential diagnostic and therapeutic targets for skin cancer. Recent studies demonstrate the efficacy of these techniques in uncovering molecular processes and pinpointing diagnostic markers for various skin cancer types, highlighting the potential of systems genetics in advancing innovative therapies. While certain limitations exist, such as generalizability and contextualization of external factors, the ongoing progress in AI technologies provides hope in overcoming these challenges. By providing protocols and a practical example involving Braf, we aim to inspire early-career experimental dermatologists to adopt these tools and seamlessly integrate these techniques into their skin cancer research, positioning them at the forefront of innovative approaches in combating this devastating disease.

Epigenetic modification and antibody-dependent expansion of memory-like NK cells in human cytomegalovirus-infected individuals.

Long-lived "memory-like" NK cells have been identified in individuals infected by human cytomegalovirus (HCMV), but little is known about how the memory-like NK cell pool is formed. Here, we have shown that HCMV-infected individuals have several distinct subsets of memory-like NK cells that are often deficient for multiple transcription factors and signaling proteins, including tyrosine kinase SYK, for which the reduced expression was stable over time and correlated with epigenetic modification of the gene promoter. Deficient expression of these proteins was largely confined to the recently discovered FcRγ-deficient NK cells that display enhanced antibody-dependent functional activity. Importantly, FcRγ-deficient NK cells exhibited robust preferential expansion in response to virus-infected cells (both HCMV and influenza) in an antibody-dependent manner. These findings suggest that the memory-like NK cell pool is shaped and maintained by a mechanism that involves both epigenetic modification of gene expression and antibody-dependent expansion.

A Recombinant Ig Fragment (IgCw-γεκ) Comprising the Cγ1-Cε2-4 and Cκ Domains Is an Alternative Reagent to Human IgE.

Human IgE is useful for immunological assays, such as sensitization of FcεRI-positive cells and IgE measurement. In this study, we report the development of a recombinant Ig fragment, designated IgCw-γεκ, as an alternative reagent to human IgE. IgCw-γεκ (∼130 kDa) comprises two hybrid constant H chain regions (Cγ1-Cε2-4, each ∼53 kDa) and two constant κ L chains (Cκ, each ∼12 kDa) and lacks a V domain. The presence of Cγ1 instead of Cε1 within the H chain increased the production yield and facilitated assembly of the H and L chains. IgCw-γεκ was produced in cultured human embryonic kidney 293F cells, with a yield of ∼27 mg/l. IgCw-γεκ bound to human FcεRIαRs expressed on the surface of rat basophilic leukemia-2H3 cells. A ß-hexosaminidase release assay revealed that the biological activity of IgCw-γεκ was comparable with that of IgE. The IgE concentration measured using IgCw-γεκ as a standard was similar to that measured using IgE as a standard. These results suggest that the IgCw-γεκ molecule retains the basic characteristics of IgE, but does not cross-react with Ags, making it an alternative to the IgE isotype references used in a variety of immunological assays.

Predictive coding across the left fronto-temporal hierarchy during language comprehension.

We used magnetoencephalography (MEG) and event-related potentials (ERPs) to track the time-course and localization of evoked activity produced by expected, unexpected plausible, and implausible words during incremental language comprehension. We suggest that the full pattern of results can be explained within a hierarchical predictive coding framework in which increased evoked activity reflects the activation of residual information that was not already represented at a given level of the fronto-temporal hierarchy ("error" activity). Between 300 and 500 ms, the three conditions produced progressively larger responses within left temporal cortex (lexico-semantic prediction error), whereas implausible inputs produced a selectively enhanced response within inferior frontal cortex (prediction error at the level of the event model). Between 600 and 1,000 ms, unexpected plausible words activated left inferior frontal and middle temporal cortices (feedback activity that produced top-down error), whereas highly implausible inputs activated left inferior frontal cortex, posterior fusiform (unsuppressed orthographic prediction error/reprocessing), and medial temporal cortex (possibly supporting new learning). Therefore, predictive coding may provide a unifying theory that links language comprehension to other domains of cognition.

Magnetite particles accelerate methanogenic degradation of highly concentrated acetic acid in anaerobic digestion process.

The anaerobic digestion (AD) process has become significant for its capability to convert organic wastewater into biogas, a valuable energy source. Excessive acetic acid accumulation in the anaerobic digester can inhibit methanogens, ultimately leading to the deterioration of process performance. Herein, the effect of magnetite particles (MP) as an enhancer on the methanogenic degradation of highly-concentrated acetate (6 g COD/L) was examined through long-term sequential AD batch tests. Bioreactors with (AM) and without (AO) MP were compared. AO experienced inhibition and its methane production rate (qm) converged to 0.45 L CH4/g VSS/d after 10 sequential batches (AO10, the 10th batch in a series of the sequential batch tests conducted using bioreactors without MP addition). In contrast, AM achieved 3-425% higher qm through the sequential batches, indicating that MP could counteract the inhibition caused by the highly-concentrated acetate. MP addition to inhibited bioreactors (AO10) successfully restored them, achieving qm of 1.53 L CH4/g VSS/d, 3.4 times increase from AO10 after 8 days lag time, validating its potential as a recovery strategy for inhibited digesters with acetate accumulation. AM exhibited higher microbial populations (1.8-3.8 times) and intracellular activity (9.3 times) compared to AO. MP enriched Methanosaeta, Peptoclostridium, Paraclostridium, OPB41, and genes related to direct interspecies electron transfer and acetate oxidation, potentially driving the improvement of qm through MP-mediated methanogenesis. These findings demonstrated the potential of MP supplementation as an effective strategy to accelerate acetate-utilizing methanogenesis and restore an inhibited anaerobic digester with high acetate accumulation.

Survey Validation for Measuring Perceptions of Work-Related Factors That Influence Career Paths of Men and Women in Academic Anesthesiology.

BACKGROUND: Women's underrepresentation in positions of leadership in medicine has been attributed to environmental, structural, motivational, and situational factors. The purpose of this study was to design and validate a survey instrument based on these constructs, using a sample of men and women anesthesiologists from 3 urban academic medical centers. METHODS: Following institutional review board review, survey domains were defined based on a literature review. Items were developed, and content validation was performed by external experts. Anesthesiologists at 3 academic institutions were invited to complete the anonymous survey. Validation measures were performed on the collected responses, including reliability, convergent, and discriminant validity. In addition, differences between men and women respondents were evaluated. RESULTS: Content validation by external experts yielded 38 items with 5-point Likert scales, defining 3 constructs: environmental (14 items), structural (13 items), and motivational (11 items) factors, with single-item measures on situational factors. Content validity indices used Cohen's Kappa coefficients, with 0.85 as the acceptance cutoff. Two hundred seventy-four anesthesiologists in 3 academic institutions received the online survey. One hundred fifteen responses were received (42% response rate), yielding 103 complete survey responses, of which 86 cases included gender. Cronbach's α reliability estimates for the environmental, structural, and motivational scale scores were .88, .84, and .64, respectively, after scale revision. Evidence of convergent (Pearson's r = 0.68; P < .001) and discriminant validity (Pearson's r = 0.017; P = .84) confirmed theoretical expectations. Gender group differences showed statistically significant differences in perceptions toward environmental but not toward structural and motivational factors. CONCLUSIONS: The iterative design and validation processes yielded a 3-scale survey instrument with parsimonious item sets. The preliminary evidence of construct validity and reliability fills a gap in the instrumentation literature for assessing gender issues in medicine. Findings were consistent with theoretical expectations. Women are more likely than men to experience challenges in the work environment for career advancement. No differences were found between men and women on perceived resources and overall motivation factors. Investigations should continue with larger and more diverse samples and medical specialties.

How good are collimated Gaussian beams produced with engineered diffusers?

Collimating a Gaussian beam from an uncollimated laser source has been achieved via the deployment of engineered diffusers (EDs)-also referred to as light shaping diffusers. When compared to conventional pinhole-based optical collimation systems, this method of beam collimation ensures high optical transmission efficiency at the expense of the introduction of additional speckle and a resulting reduction in spatial coherence. Despite a lower collimation quality, these ED-produced collimated beams are attractive and promising in terms of their deployment in various benchtop or tabletop systems that involve shorter beam propagation distances of up to a few meters while requiring a high optical power throughput. This paper aims to further the understanding of collimation quality and propagation properties of ED-produced Gaussian collimated beams via carefully designed experiments and accompanying analysis. We measure and document the beam divergence, Rayleigh distance, and M 2 factor, as well as evolution of the wavefront radius of curvature (RoC), of these ED-generated beams over a few meters of propagation-a propagation distance which encapsulates a vast majority of optical systems. We further investigate the changes in the beam profile with the addition of a laser speckle reducer (SR) and compare the ED-produced beams with a near-ideal collimated beam produced with spatial filtering systems.

Measuring the radius of curvature of spherical surfaces with actively tunable Fizeau and Twyman-Green interferometers.

Accurate and repeatable measurement of the radius of curvature (RoC) of spherical sample surfaces is of great importance in optics. This importance lies in the ubiquitous use of spherical optical elements such as curved mirrors and lenses. Due to a high measurement sensitivity, interferometric techniques are often deployed for accurate characterization of the sample surface RoC. One method by which a typical commercial Fizeau or Twyman-Green (TG) interferometer measures surface RoC is via scanning between two principal retroreflective optical configurations-namely, the confocal and catseye configurations. Switching between these two configurations is typically achieved by moving an optical head along the axis of the propagating laser beam and the RoC is estimated by measuring the magnitude of mechanical motion to switch between the two principal configurations. In this paper, we propose a motion-free catseye/confocal-imaging-based sample RoC measurement system. The necessity of bulk motion to switch between the two configurations is circumvented via the use of an actively controlled varifocal lens. We demonstrate the usefulness of the proposed innovation in RoC measurements with either the TG or the Fizeau interferometer. Furthermore, we convert a commercial motion-based Zygo RoC measurement system into a motion-free one by introducing a tunable lens inside the apparatus and using it to accurately characterize the RoC of different test samples. We also compute the wavefront aberrations for all spherical sample surfaces from the recorded measurement data.

Deep learning-based EEG analysis to classify normal, mild cognitive impairment, and dementia: Algorithms and dataset.

For automatic EEG diagnosis, this paper presents a new EEG data set with well-organized clinical annotations called Chung-Ang University Hospital EEG (CAUEEG), which has event history, patient's age, and corresponding diagnosis labels. We also designed two reliable evaluation tasks for the low-cost, non-invasive diagnosis to detect brain disorders: i) CAUEEG-Dementia with normal, mci, and dementia diagnostic labels and ii) CAUEEG-Abnormal with normal and abnormal. Based on the CAUEEG dataset, this paper proposes a new fully end-to-end deep learning model, called the CAUEEG End-to-end Deep neural Network (CEEDNet). CEEDNet pursues to bring all the functional elements for the EEG analysis in a seamless learnable fashion while restraining non-essential human intervention. Extensive experiments showed that our CEEDNet significantly improves the accuracy compared with existing methods, such as machine learning methods and Ieracitano-CNN (Ieracitano et al., 2019), due to taking full advantage of end-to-end learning. The high ROC-AUC scores of 0.9 on CAUEEG-Dementia and 0.86 on CAUEEG-Abnormal recorded by our CEEDNet models demonstrate that our method can lead potential patients to early diagnosis through automatic screening.

Efficacy and safety of adhesion barrier in living-donor liver transplantation with right liver graft to prevent delayed gastric emptying.

Delayed gastric emptying (DGE) is a common complication of liver transplantation. This study aimed to clarify the efficacy and safety of the application of an adhesion barrier for preventing DGE in living-donor liver transplantation. This retrospective study included 453 patients who underwent living-donor liver transplantation using a right lobe graft between January 2018 and August 2019, and the incidence of postoperative DGE and complications was compared between patients in whom adhesion barrier was used (n=179 patients) and those in whom adhesion barrier was not used (n=274 patients). We performed 1:1 propensity score matching between the 2 groups, and 179 patients were included in each group. DGE was defined according to the International Study Group for Pancreatic Surgery classification. The use of adhesion barrier was significantly associated with a lower overall incidence of postoperative DGE in liver transplantation (30.7 vs. 17.9%; p =0.002), including grades A (16.8 vs. 9.5%; p =0.03), B (7.3 vs. 3.4%; p =0.08), and C (6.6 vs. 5.5%; p =0.50). After propensity score matching, similar results were observed for the overall incidence of DGE (29.6 vs. 17.9%; p =0.009), including grades A (16.8 vs. 9.5%; p =0.04), B (6.7 vs. 3.4%; p =0.15), and C (6.1 vs. 5.0%; p =0.65). Univariate and multivariate analyses showed a significant correlation between the use of adhesion barrier and a low incidence of DGE. There were no statistically significant differences in postoperative complications between the 2 groups. The application of an adhesion barrier could be a safe and feasible method to reduce the incidence of postoperative DGE in living-donor liver transplantation.

Favorable Prognostic Factors for Survival Outcomes of Hepatocellular Carcinoma with Portal Vein Tumor Thrombosis After Hepatectomy.

BACKGROUND: This study aimed to investigate prognostic factors of recurrence and survival associated with hepatocellular carcinoma (HCC) with portal vein tumor thrombosis (PVTT). PATIENTS AND METHODS: This retrospective study included 161 patients with HCC with PVTT who underwent hepatectomy between January 2003 and January 2014 at the Asan Medical Center. Regression analyses were conducted to identify favorable predictive factors for overall survival (OS) and recurrence-free survival (RFS). RESULTS: The median follow-up was 15.9 months, while 1-, 3-, and 5-year OS was 65.0%, 38.4%, and 36.0%, respectively, and 1-year RFS was 25.5%. There were no significant differences in OS and RFS between the patients with portal vein invasion (Vp) 1-2 and Vp3-4 PVTT. Patients with intrahepatic recurrence had significantly better overall survival than patients with extrahepatic recurrence. Transcatheter arterial chemoembolization and radiofrequency ablation were the most effective treatments for intrahepatic metastasis, and surgery was the most effective treatment for extrahepatic metastasis. On multivariate analysis, absence of esophageal varices, maximal tumor size < 5 cm, tumor location in single lobe, and anatomical resection were favorable prognostic factors for OS and R0 resection, and absence of microvascular invasion was a favorable prognostic factor for RFS. CONCLUSION: The long-term outcome of patients with HCC with PVTT can be improved under consideration of favorable prognostic factors including absence of esophageal varices, maximal tumor size < 5 cm, tumor location in single lobe, and anatomical resection, R0 resection, and absence of microvascular invasion. In addition, recurrent HCC required aggressive management to prolong overall survival.

Intersite Coulomb Interactions in Charge-Ordered Systems.

Using ab initio approaches for extended Hubbard interactions coupled to phonons, we reveal that the intersite Coulomb interaction plays important roles in determining various distinctive phases of the paradigmatic charge-ordered materials of Ba_{1-x}K_{x}AO_{3} (A=Bi and Sb). We demonstrated that all their salient doping dependent experiment features such as breathing instabilities, anomalous phonon dispersions, and transition between charge-density wave and superconducting states can be accounted for very well if self-consistently obtained nearest neighbor Hubbard interactions are included, thus establishing a minimal criterion for reliable descriptions of spontaneous charge orders in solids.

Multiparametric MRI-based radiomics model for predicting human papillomavirus status in oropharyngeal squamous cell carcinoma: optimization using oversampling and machine learning techniques.

OBJECTIVES: To develop and validate a multiparametric MRI-based radiomics model with optimal oversampling and machine learning techniques for predicting human papillomavirus (HPV) status in oropharyngeal squamous cell carcinoma (OPSCC). METHODS: This retrospective, multicenter study included consecutive patients with newly diagnosed and pathologically confirmed OPSCC between January 2017 and December 2020 (110 patients in the training set, 44 patients in the external validation set). A total of 293 radiomics features were extracted from three sequences (T2-weighted images [T2WI], contrast-enhanced T1-weighted images [CE-T1WI], and ADC). Combinations of three feature selection, five oversampling, and 12 machine learning techniques were evaluated to optimize its diagnostic performance. The area under the receiver operating characteristic curve (AUC) of the top five models was validated in the external validation set. RESULTS: A total of 154 patients (59.2 ± 9.1 years; 132 men [85.7%]) were included, and oversampling was employed to account for data imbalance between HPV-positive and HPV-negative OPSCC (86.4% [133/154] vs. 13.6% [21/154]). For the ADC radiomics model, the combination of random oversampling and ridge showed the highest diagnostic performance in the external validation set (AUC, 0.791; 95% CI, 0.775-0.808). The ADC radiomics model showed a higher trend in diagnostic performance compared to the radiomics model using CE-T1WI (AUC, 0.604; 95% CI, 0.590-0.618), T2WI (AUC, 0.695; 95% CI, 0.673-0.717), and a combination of both (AUC, 0.642; 95% CI, 0.626-0.657). CONCLUSIONS: The ADC radiomics model using random oversampling and ridge showed the highest diagnostic performance in predicting the HPV status of OPSCC in the external validation set. CLINICAL RELEVANCE STATEMENT: Among multiple sequences, the ADC radiomics model has a potential for generalizability and applicability in clinical practice. Exploring multiple oversampling and machine learning techniques was a valuable strategy for optimizing radiomics model performance. KEY POINTS: • Previous radiomics studies using multiparametric MRI were conducted at single centers without external validation and had unresolved data imbalances. • Among the ADC, CE-T1WI, and T2WI radiomics models and the ADC histogram models, the ADC radiomics model was the best-performing model for predicting human papillomavirus status in oropharyngeal squamous cell carcinoma. • The ADC radiomics model with the combination of random oversampling and ridge showed the highest diagnostic performance.

Impact of lesion size on reproducibility of quantitative measurement and radiomic features in vessel wall MRI.

OBJECTIVES: To investigate reproducibility of quantitative measurement and radiomic features in vessel wall MRI (VW-MRI), evaluate the impact of lesion size, and identify reproducible radiomic features. METHODS: This retrospective, single-center study included 251 patients (mean age, 53 ± 12 years; 128 women) with atherosclerosis, dissection, aneurysm, moyamoya disease, and vasculitis of the intracranial arteries who underwent three-dimensional turbo spin echo T1-weighted image. Lesion thickness, volume, and signal intensity were measured, and 157 radiomic features were extracted. Intra-observer reproducibility of quantitative measurement and radiomic features was evaluated by calculating the concordance correlation coefficient (CCC) and proportion of radiomic features above the predefined CCC. The reproducibility of quantitative measurement and radiomic features according to lesion size (binary comparison and stratification into 5 and 18 groups) was evaluated. RESULTS: There was an overall serial increase in CCC for thickness measurement when stratified by lesion thickness and volume. There was an overall serial increase in the median CCC for radiomic features and proportion of radiomic features with CCC > 0.85 when stratified by lesion thickness and volume. Reproducibility of radiomic features was higher in the lesions with thickness ≥ 2.5 mm (median CCC, 0.97 vs. 0.89, p < .001; proportion with CCC > 0.85, 88.5% vs. 59.6%, p < .001) and volume ≥ 50 mm3 (median CCC, 0.97 vs. 0.88, p < .001; proportion with CCC > 0.85, 90.4% vs. 59.0%, p < .001). Intensity-based statistical features remained most reproducible in the thinnest and smallest lesions. CONCLUSIONS: Intra-observer reproducibility of thickness measurement and radiomic features was affected by lesion size in VW-MRI although intensity-based statistical features remained most reproducible. KEY POINTS: • There was an overall serial increase in CCC for thickness measurement when stratified by lesion size. • There was an overall serial increase in the median CCC for radiomic features and proportion of radiomic features with CCC > 0.85 when stratified by lesion size. • Intensity-based statistical features remained most reproducible in the thinnest and smallest lesions.

Vessel size and perfusion-derived vascular habitat refines prediction of treatment failure to bevacizumab in recurrent glioblastomas: validation in a prospective cohort.

OBJECTIVES: Anti-angiogenic therapy may not benefit all patients with recurrent glioblastomas, and imaging biomarker predicting treatment response to anti-angiogenic therapy is currently limited. We aimed to develop and validate vascular habitats based on perfusion and vessel size to predict time to progression (TTP) in patients with recurrent glioblastomas treated with bevacizumab. METHODS: Sixty-nine patients with recurrent glioblastomas treated with bevacizumab who underwent pretreatment MRI with dynamic susceptibility contrast imaging and vessel architectural imaging were enrolled. Vascular habitats were constructed using vessel size index (VSI) and relative cerebral blood volume (rCBV). Associations with vascular habitats and TTP were analyzed using Cox proportional hazard regression analysis. In a prospectively enrolled validation cohort consisting of 15 patients ( ClinicalTrials.gov identifier; NCT04143425), stratification of TTP was demonstrated by the Kaplan-Meier method (log-rank test) using vascular habitats. RESULTS: Three vascular habitats consisting of high, intermediate, and low angiogenic habitats were identified with rCBV and VSI. Both high angiogenic and intermediate angiogenic habitats were significantly associated with a shorter TTP (hazard ratio [HR], 2.78 and 1.82, respectively; largest p = .003) and so was rCBV (HR, 2.15; p = .02). Concordance probability index of vascular habitat combining high and intermediate angiogenic habitats was 0.74. Vascular habitats stratified patients as good or poor responder in a prospective cohort (p = .059). CONCLUSIONS: Perfusion- and vessel size-derived vascular habitats predicted TTP in recurrent glioblastomas treated with anti-angiogenic therapy and aided patient stratification in a prospective validation cohort. TRIAL REGISTRATION: ClinicalTrials.gov identifier: NCT04143425 KEY POINTS: • High and intermediate angiogenic habitats predicted TTP in recurrent glioblastomas treated with anti-angiogenic therapy. • Vascular habitats combining high and intermediate angiogenic habitats aided patient stratification for anti-angiogenic therapy in recurrent glioblastomas.

Natural language processing to predict isocitrate dehydrogenase genotype in diffuse glioma using MR radiology reports.

OBJECTIVES: To evaluate the performance of natural language processing (NLP) models to predict isocitrate dehydrogenase (IDH) mutation status in diffuse glioma using routine MR radiology reports. MATERIALS AND METHODS: This retrospective, multi-center study included consecutive patients with diffuse glioma with known IDH mutation status from May 2009 to November 2021 whose initial MR radiology report was available prior to pathologic diagnosis. Five NLP models (long short-term memory [LSTM], bidirectional LSTM, bidirectional encoder representations from transformers [BERT], BERT graph convolutional network [GCN], BioBERT) were trained, and area under the receiver operating characteristic curve (AUC) was assessed to validate prediction of IDH mutation status in the internal and external validation sets. The performance of the best performing NLP model was compared with that of the human readers. RESULTS: A total of 1427 patients (mean age ± standard deviation, 54 ± 15; 779 men, 54.6%) with 720 patients in the training set, 180 patients in the internal validation set, and 527 patients in the external validation set were included. In the external validation set, BERT GCN showed the highest performance (AUC 0.85, 95% CI 0.81-0.89) in predicting IDH mutation status, which was higher than LSTM (AUC 0.77, 95% CI 0.72-0.81; p = .003) and BioBERT (AUC 0.81, 95% CI 0.76-0.85; p = .03). This was higher than that of a neuroradiologist (AUC 0.80, 95% CI 0.76-0.84; p = .005) and a neurosurgeon (AUC 0.79, 95% CI 0.76-0.84; p = .04). CONCLUSION: BERT GCN was externally validated to predict IDH mutation status in patients with diffuse glioma using routine MR radiology reports with superior or at least comparable performance to human reader. CLINICAL RELEVANCE STATEMENT: Natural language processing may be used to extract relevant information from routine radiology reports to predict cancer genotype and provide prognostic information that may aid in guiding treatment strategy and enabling personalized medicine. KEY POINTS: • A transformer-based natural language processing (NLP) model predicted isocitrate dehydrogenase mutation status in diffuse glioma with an AUC of 0.85 in the external validation set. • The best NLP models were superior or at least comparable to human readers in both internal and external validation sets. • Transformer-based models showed higher performance than conventional NLP model such as long short-term memory.

Comparative Analysis of the Performance of Electroencephalogram Parameters for Monitoring the Depth of Sedation During Remimazolam Target-Controlled Infusion.

BACKGROUND: The changes in hypnotic indicators in remimazolam sedation remain unclear. We investigated the correlation of the electroencephalogram (EEG) parameters with the effect-site remimazolam concentration and the depth of sedation in patients receiving a target-controlled infusion of remimazolam. METHODS: This prospective observational study enrolled 35 patients (32 analyzed) who underwent lower extremity varicose vein surgery or lower extremity orthopedic surgery under spinal anesthesia. We administered remimazolam by target-controlled infusion using the pharmacokinetic model introduced by Schüttler et al. The EEG data were continuously recorded, including the bispectral index (BIS), patient state index (PSI), spectral edge frequency (SEF), and raw EEG signals. The relative beta ratio (RBR), defined as log (spectral power [30-47 Hz]/spectral power [11-20 Hz]), was obtained by analyzing raw EEG. The level of sedation corresponding to each effect-site remimazolam concentration was assessed using the Modified Observer's Assessment of Alertness/Sedation (MOAA/S). The prediction probability (Pk) and Spearman's correlation coefficients (R) were calculated between effect-site remimazolam concentration, MOAA/S, and EEG parameters. RESULTS: BIS and PSI showed significantly higher Pk for effect-site remimazolam concentration (Pk = 0.76 [0.72-0.79], P < .001 for BIS; Pk = 0.76 [0.73-0.79], P < .001 for PSI) compared to RBR (Pk = 0.71 [0.68-0.74], P < .001) and SEF (Pk = 0.58 [0.53-0.63], P = .002). BIS, PSI, and RBR showed significantly higher correlation coefficients for effect-site remimazolam concentration (R = -0.70 [-0.78 to -0.63], P < .001 for BIS; R = -0.72 [-0.79 to -0.66], P < .001 for PSI; R = -0.61 [-0.69 to -0.54], P < .001 for RBR) compared to SEF (R = -0.22 [-0.36 to -0.08], P = .002). BIS and PSI also had significantly higher Pk and correlation coefficients for MOAA/S (Pk = 0.81 [0.79-0.83], P < .001; R = 0.84 [0.81-0.88], P < .001 for BIS) (Pk = 0.80 [0.78-0.83], P < .001; R = 0.82 [0.78-0.87], P < .001 for PSI) compared to RBR (Pk = 0.74 [0.72-0.77], P < .001; R = 0.72 [0.65-0.78], P < .001) and SEF (Pk = 0.55 [0.50-0.59], P = .041; R = 0.13 [-0.01 to 0.27], P = .067). CONCLUSIONS: BIS, PSI, and RBR showed an acceptable correlation with the effect-site remimazolam concentration and depth of sedation in this study, suggesting that these EEG-derived parameters are potentially reliable hypnotic indicators during remimazolam sedation. BIS and PSI showed superior performance as hypnotic indicators to RBR and SEF in patients receiving target-controlled infusion of remimazolam.