Impaired T1 mapping and Tmax during the first 7 days after ischemic stroke. A retrospective observational study.

OBJECTIVE: To measure the relative T1 (rT1) value in different hypo-perfused regions after ischemic stroke using T1 mapping derived by Strategically Acquired Gradient Echo (STAGE) and assess its relationship with onset time and severity of ischemia. MATERIALS AND METHODS: Sixty-three patients with acute anterior circulation ischemic stroke from 2017 to 2022 who underwent STAGE, diffusion weighted imaging (DWI) and dynamic susceptibility contrast perfusion weighted imaging (DSC-PWI) within 7 days were retrospectively enrolled. The areas with reduced diffusion and hypo-perfusion were segmented based on apparent diffusion coefficient (ADC) value < 0.62 × 10-3mm2/s and time-to-maximum (Tmax) thresholds (4, 6, 8, and 10 seconds). We measured the T1 value in the diffusion reduced and every 2 s Tmax strata regions and calculated rT1 (T1ipsi/T1contra) to explore the relationship between rT1 value, Tmax, and onset time. RESULTS: rT1 value was increased in diffusion reduced (1.42) and hypo-perfused regions (1.02, 1.06, 1.12, 1.27, Tmax 4-6 s, 6-8 s, 8-10 s, > 10 s, respectively; all different from 1, P < 0.001). rT1 value was positively correlated with Tmax (rs = 0.61, P < 0.001) and onset time in area with reduced diffusion (rs = 0.39, P = 0.014). CONCLUSIONS: Increased rT1 value in different hypo-perfused brain regions using T1 mapping derived by STAGE may reflect the edema; it was associated with the severity of Tmax and showed a weak correlation with the onset time in diffusion reduced areas.

Dual-energy CT may predict post-operative recurrence in early-stage glottic laryngeal cancer: a novel nomogram and risk stratification system.

OBJECTIVES: To establish and validate a predictive model integrating with clinical and dual-energy CT (DECT) variables for individual recurrence-free survival (RFS) prediction in early-stage glottic laryngeal cancer (EGLC) after larynx-preserving surgery. METHODS: This retrospective study included 212 consecutive patients with EGLC who underwent DECT before larynx-preserving surgery between January 2015 and December 2018. Using Cox proportional hazard regression model to determine independent predictors for RFS and presented on a nomogram. The model's performance was assessed using Harrell's concordance index (C-index), time-dependent area under curve (TD-AUC) plot, and calibration curve. A risk stratification system was established using the nomogram with median scores of all cases to divide all patients into two prognostic groups. RESULTS: Recurrence occurred in 39/212 (18.4%) cases. Normalized iodine concentration in arterial (NICAP) and venous phases (NICVP) were verified as significant predictors of RFS in multivariate Cox regression (hazard ratio [HR], 4.2; 95% confidence interval [CI]: 2.3, 7.7, p < .001 and HR, 3.0; 95% CI: 1.5, 5.9, p = .002, respectively). Nomogram based on clinical and DECT variables was better than did only clinical variables. The prediction model proved well-calibrated and had good discriminative ability in the training and validation samples. A risk stratification system was built that could effectively classify EGLC patients into two risk groups. CONCLUSIONS: DECT could provide independent RFS indicators in patients with EGLC, and the nomogram based on DECT and clinical variables was useful in predicting RFS at several time points. KEY POINTS: • Dual-energy CT(DECT) variables can predict recurrence-free survival (RFS) after larynx-preserving surgery in patients with early-stage glottic laryngeal cancer (EGLC). • The model that integrates clinical and DECT variables predicted RFS better than did only clinical variables. • A risk stratification system based on the nomogram could effectively classify EGLC patients into two risk groups.

Radiomics of dual-energy computed tomography for predicting progression-free survival in patients with early glottic cancer.

Aim: This study aimed to predict progression-free survival (PFS) in patients with early glottic cancer using radiomic features on dual-energy computed tomography iodine maps. Methods: Radiomic features were extracted from arterial and venous phase iodine maps, and radiomic risk scores were determined by univariate Cox proportional hazards regression analysis and least absolute shrinkage and selection operator regression with tenfold cross-validation. The Kaplan-Meier method was used to evaluate the association between radiomic risk scores and PFS. Results: Patients were stratified into low-risk and high-risk groups using radiomics, the PFS corresponding rates with statistical significance between the two groups. The high-risk group showed better survival, benefiting from laryngectomy. Conclusion: Radiomics could provide a promising biomarker for predicting the PFS of early glottic cancer patients.

Prediction of ipsilateral lateral cervical lymph node metastasis in papillary thyroid carcinoma: a combined dual-energy CT and thyroid function indicators study.

BACKGROUND: Predicting the possibility of ipsilateral lateral cervical lymph node metastasis (ipsi-LLNM) was crucial to the operation plan for patients with papillary thyroid carcinoma (PTC). This study aimed to investigate the independent risk factors for ipsi-LLNM in PTC patients by combining dual-energy computed tomography (DECT) with thyroid function indicators. METHODS: We retrospectively enrolled 406 patients with a pathological diagnosis of PTC from Jan 2016 to Dec 2019. Ensure the DECT images were clear and the thyroid function indicators were complete. Univariate and multivariate logistic analyses explored the independent risk factors for ipsi-LLNM. To evaluate the cutoff value of each risk factor by using receiver operating characteristic (ROC) curves. RESULTS: A total of 406 patients with PTC were analyzed, including 128 with ipsi-LLNM and 278 without ipsi-LLNM. There were statistical differences of parameters between the two groups (P < .0001), including serum Tg, Anti-Tg, Anti-TPO, the volume of the primary lesion, calcification, extrathyroidal extension (ETE), and iodine concentration (IC) in the arterial and the venous phases. Independent risk factors for ipsi-LLNM included serum Tg, Anti-Tg, ETE, and IC in the arterial and the venous phases (P < .05). The combined application of the above independent risk factors can predict the possibility of ipsi-LLNM, with an AUC of 0.834. Ipsi-LLNM was more likely to occur when the following conditions were met: with ETE, Tg >  100.01 ng/mL, Anti-Tg >  89.43 IU/mL, IC in arterial phase > 3.4 mg/mL and IC in venous phase > 3.1 mg/mL. CONCLUSIONS: The combined application of DECT quantitative parameters and thyroid function indicators can help clinicians accurately predict ipsi-LLNM before surgery, thereby assisting the individualized formulation of surgical procedures.

Improving the Efficiencies of Water Splitting and CO2 Electrolysis by Anodic O2 Bubble Management.

This study systematically explores the impact of the anodic flow field design on the transport of O2 bubble and subsequent energy efficiency in electrolysis devices. Two distinct configurations, namely a conventional serpentine flow panel and an interdigitated flow panel, are integrated at the anode side of the electrolyzer. The interdigitated flow field exhibits superior performance in both alkaline water splitting and CO2 reduction despite the experience of an increased pressure drop. Numerical simulations reveal that the enhanced convective flow of the O2 bubbles induced by a forced anolyte flow through the porous electrode within the interdigitated panel design resulted in a 3 orders of magnitude increase in the level of the O2 bubble transport compared to the serpentine configuration. These findings not only underscore the significance of flow field design on bubble management but also provide a basis for advancing the electrolysis efficiency at industrial-level current densities.

Extreme gradient boosting model to assess risk of central cervical lymph node metastasis in patients with papillary thyroid carcinoma: Individual prediction using SHapley Additive exPlanations.

BACKGROUND AND OBJECTIVES: Central cervical lymph node metastasis (CLNM) is considered a risk factor for recurrence in patients with papillary thyroid carcinoma (PTC). Traditional machine learning models suffered from "black-box" problems, which could not exactly explain the interactive effects of the risk factors. We aimed to develop an eXtreme Gradient Boosting (XGBoost) model to assess CLNM, including positive and negative effects. METHODS: 1,122 patients with PTC admitted at Tianjin First Central Hospital from 2016 to 2020 were retrospectively selected. They were randomly divided into the training and test datasets with an 8:2 ratio. 108 patients with PTC admitted at Binzhou Medical University Hospital in 2020 served as the validation dataset. The XGBoost model was used to assess CLNM. The 10-fold cross-validation was utilized for model selection, and the metric used to evaluate classification performance was the average area under the curve (AUC) of 10-fold cross-validation. Interpretation and transparency of the "black-box" problem were performed. SHapley Additive exPlanations (SHAP) and local interpretable model-agnostic explanation (LIME) were used to ensure the stability and reliability of the model. RESULTS: The XGBoost model based on ultrasound and dual-energy computed tomography images of the solitary primary lesion had an excellent performance for assessing CLNM, with average AUCs of 0.918, 0.903, and 0.881 in the training, test, and validation datasets, respectively. SHAP plots showed the influence of each parameter on the XGBoost model, including positive (i.e., capsular invasion, diameter, iodine concentration in the venous phase, and calcification) and negative (i.e., sex and age) impacts. For all cases, the capsular invasion prediction weight was the highest; for individual cases, different predictors were assigned different weights. Moreover, the performance of the XGBoost model was better than classical machine-learning models. CONCLUSIONS: This study developed and validated an XGBoost model for assessing CLNM in patients with PTC. The ability to visually interpret the positive and negative effects made the XGBoost model an effective tool for guiding clinical treatment.

A Novel Combined Nomogram Model for Predicting the Pathological Complete Response to Neoadjuvant Chemotherapy in Invasive Breast Carcinoma of No Specific Type: Real-World Study.

Objective: To explore the value of a predictive model combining the multiparametric magnetic resonance imaging (mpMRI) radiomics score (RAD-score), clinicopathologic features, and morphologic features for the pathological complete response (pCR) to neoadjuvant chemotherapy (NAC) in invasive breast carcinoma of no specific type (IBC-NST). Methods: We enrolled, retrospectively and consecutively, 206 women with IBC-NST who underwent surgery after NAC and obtained pathological results from August 2018 to October 2021. Four RAD-scores were constructed for predicting the pCR based on fat-suppression T2-weighted imaging (FS-T2WI), diffusion-weighted imaging (DWI), contrast-enhanced T1-weighted imaging (T1WI+C) and their combination, which was called mpMRI. The best RAD-score was combined with clinicopathologic and morphologic features to establish a nomogram model through binary logistic regression. The predictive performance of the nomogram was evaluated using the area under receiver operator characteristic (ROC) curve (AUC) and calibration curve. The clinical net benefit of the model was evaluated using decision curve analysis (DCA). Results: The mpMRI RAD-score had the highest diagnostic performance, with AUC of 0.848 among the four RAD-scores. T stage, human epidermal growth factor receptor-2 (HER2) status, RAD-score, and roundness were independent factors for predicting the pCR (P < 0.05 for all). The combined nomogram model based on these factors achieved AUCs of 0.930 and 0.895 in the training cohort and validation cohort, respectively, higher than other models (P < 0.05 for all). The calibration curve showed that the predicted probabilities of the nomogram were in good agreement with the actual probabilities, and DCA indicated that it provided more net benefit than the treat-none or treat-all scheme by decision curve analysis in both training and validation datasets. Conclusion: The combined nomogram model based on the mpMRI RAD-score combined with clinicopathologic and morphologic features may improve the predictive performance for the pCR of NAC in patients with IBC-NST.

3D Printed Nickel-Molybdenum-Based Electrocatalysts for Hydrogen Evolution at Low Overpotentials in a Flow-Through Configuration.

Three-dimensional (3D) printed, hierarchically porous nickel molybdenum (NiMo) electrocatalysts were synthesized and evaluated in a flow-through configuration for the hydrogen evolution reaction (HER) in 1.0 M KOH(aq) in a simple electrochemical H-cell. 3D NiMo electrodes possess hierarchically porous structures because of the resol-based aerogel precursor, which generates superporous carbon aerogel as a catalyst support. Relative to a traditional planar electrode configuration, the flow-through configuration allowed efficient removal of the hydrogen bubbles from the catalyst surface, especially at high operating current densities, and significantly decreased the overpotentials required for HER. An analytical model that accounted for the electrokinetics of HER as well as the mass transport with or without the flow-through configuration was developed to quantitatively evaluate voltage losses associated with kinetic overpotentials and ohmic resistance due to bubble formation in the porous electrodes. The chemical composition, electrochemical surface area (ECSA), and roughness factor (RF) were also systematically studied to assess the electrocatalytic performance of the 3D printed, hierarchically porous NiMo electrodes. An ECSA of 25163 cm2 was obtained with the highly porous structures, and an average overpotential of 45 mV at 10 mA cm-2 was achieved over 24 h by using the flow-through configuration. The flow-through configuration evaluated in the simple H-cell achieved high electrochemical accessible surface areas for electrochemical reactions and provided useful information for adaption of the porous electrodes in flow cells.

Plastome characteristics of Cannabaceae.

Cannabaceae is an economically important family that includes ten genera and ca. 117 accepted species. To explore the structure and size variation of their plastomes, we sequenced ten plastomes representing all ten genera of Cannabaceae. Each plastome possessed the typical angiosperm quadripartite structure and contained a total of 128 genes. The Inverted Repeat (IR) regions in five plastomes had experienced small expansions (330-983 bp) into the Large Single-Copy (LSC) region. The plastome of Chaetachme aristata has experienced a 942-bp IR contraction and lost rpl22 and rps19 in its IRs. The substitution rates of rps19 and rpl22 decreased after they shifted from the LSC to IR. A 270-bp inversion was detected in the Parasponia rugosa plastome, which might have been mediated by 18-bp inverted repeats. Repeat sequences, simple sequence repeats, and nucleotide substitution rates varied among these plastomes. Molecular markers with more than 13% variable sites and 5% parsimony-informative sites were identified, which may be useful for further phylogenetic analysis and species identification. Our results show strong support for a sister relationship between Gironniera and Lozanell (BS = 100). Celtis, Cannabis-Humulus, Chaetachme-Pteroceltis, and Trema-Parasponia formed a strongly supported clade, and their relationships were well resolved with strong support (BS = 100). The availability of these ten plastomes provides valuable genetic information for accurately identifying species, clarifying taxonomy and reconstructing the intergeneric phylogeny of Cannabaceae.

Comparison of 18FDG PET/PET-CT and bone scintigraphy for detecting bone metastases in patients with nasopharyngeal cancer: a meta-analysis.

OBJECTIVE: We performed a meta-analysis to compare the diagnostic efficacy of 18FDG PET/PET-CT and bone scintigraphy (BS) for diagnosing bone metastatic cancers in nasopharyngeal cancer patients. RESULTS: 6 studies (1238 patients) fulfilled the inclusion criteria. The pooled sensitivities for 18FDG PET/PET-CT and BS were 0.81 (95% confidence interval [CI] = 0.70 to 0.98) and 0.39 (95% CI = 0.26 to 0.54), specificities were 0.99 (95% CI = 0.98 to 0.99) and 0.98 (95% CI = 0.96 to 0.99), and the areas under curve were 0.98 (95% CI = 0.97 to 0.99) and 0.84 (95% CI = 0.81 to 0.87). MATERIALS AND METHODS: Several databases were searched for all available articles. We calculated the sensitivities, specificities, diagnostic odds ratios, likelihood ratios, and area under summary receiver operating characteristic curves for 18FDG PET/PET-CT and BS, respectively. CONCLUSIONS: 18FDG PET/PET-CT is superior to BS for diagnosing bone metastases in nasopharyngeal cancer patients.18FDG PET/PET-CT may enhance the diagnosis of bone metastases and provide more accurate information for the optimal management of nasopharyngeal cancer.