Combining Early Ischemic Change and Collateral Extent for Functional Outcomes After Endovascular Therapy: An Analysis From AcT Trial

BACKGROUND

Early ischemic change and collateral extent are colinear with ischemic core volume (ICV). We investigated the relationship between a combined score using the Alberta Stroke Program Early Computed Tomography Score and multiphase computed tomography angiography (mCTA) collateral extent, named mCTA-ACE score, on functional outcomes in endovascular therapy-treated patients.

METHODS

We performed a post hoc analysis of a subset of endovascular therapy-treated patients from the Alteplase Compared to Tenecteplase trial which was conducted between December 2019 and January 2022 at 22 centers across Canada. Ten-point mCTA collateral corresponding to M2 to M6 regions of the Alberta Stroke Program Early Computed Tomography Score grid was evaluated as 0 (poor), 1 (moderate), or 2 (normal) and additively combined with the 10-point Alberta Stroke Program Early Computed Tomography Score to produce a 20-point mCTA-ACE score. We investigated the association of mCTA-ACE score with modified Rankin Scale score ≤2 and return to prestroke level of function at 90 to 120 days using mixed-effects logistic regression. In the subset of patients who underwent baseline computed tomography perfusion imaging, we compared the mCTA-ACE score and ICV for outcome prediction.

RESULTS

Among 1577 intention-to-treat population in the trial, 368 (23%; 179 men; median age, 73 years) were included, with Alberta Stroke Program Early Computed Tomography Score, mCTA collateral, and combination of both (mCTA-ACE score: median [interquartile range], 8 [7-10], 9 [8-10], and 17 [16-19], respectively). The probability of modified Rankin scale score ≤2 and return to prestroke level of function increased for each 1-point increase in mCTA-ACE score (odds ratio, 1.16 [95% CI, 1.06-1.28] and 1.22 [95% CI, 1.06-1.40], respectively). Among 173 patients in whom computed tomography perfusion data was assessable, the mCTA-ACE score was inversely correlated with ICV (ρ=-0.46; P<0.01). The mCTA-ACE score was comparable to ICV to predict a modified Rankin scale score ≤2 and return to prestroke level of function (C statistics 0.71 versus 0.69 and 0.68 versus 0.64, respectively).

CONCLUSIONS

The mCTA-ACE score had a significant positive association with functional outcomes after endovascular therapy and had a similar predictive performance as ICV.

Timing of Spot Sign Appearance, Spot Sign Volume, and Leakage Rate among Phases of Multiphase CTA Predict Intracerebral Hemorrhage Growth

BACKGROUND AND PURPOSE

The presence of spot sign is associated with a high risk of hematoma growth. Our aim was to investigate the timing of the appearance, volume, and leakage rate of the spot sign for predicting hematoma growth in acute intracerebral hemorrhage using multiphase CTA.

MATERIALS AND METHODS

In this single-center retrospective study, multiphase CTA in 3 phases was performed in acute intracerebral hemorrhage (defined as intraparenchymal ± intraventricular hemorrhages). Phases of the spot sign first appearance, spot sign volumes (microliter), and leakage rates among phases (microliter/second) were measured. Associations between baseline clinical and imaging variables including spot sign volume parameters (volume and leakage rate divided by median) and hematoma growth (>6 mL) were investigated using regression models. Receiver operating characteristic analysis was used as appropriate.

RESULTS

Two hundred seventeen patients (131 men; median age, 70 years) were included. The spot sign was detected in 21.7%, 30.0%, and 29.0% in the first, second, and third phases, respectively, with median volumes of 19.7, 31.4, and 34.8 μl in these phases. Hematoma growth was seen in 44 patients (20.3%). By means of modeling, the following variables, namely the spot sign appearing in the first phase, first phase spot sign volume, spot sign appearing in the second or third phase, and spot sign positive and negative leakage rates, were associated with hematoma growth. Among patients with a spot sign, the absolute leakage rate accounting for both positive and negative leakage rates was also associated with hematoma growth (per 1-μl/s increase; OR, 1.26; 95% CI, 1.04-1.52). Other hematoma growth predictors were stroke history, baseline NIHSS score, onset-to-imaging time, and baseline hematoma volume (all P values < .05).

CONCLUSIONS

The timing of the appearance of the spot sign, volume, and leakage rate were all associated with hematoma growth. Development of automated software to generate these spot sign volumetric parameters would be an important next step to maximize the potential of temporal intracerebral hemorrhage imaging such as multiphase CTA for identifying those most at risk of hematoma growth.

Full waveform inversion using frequency shift envelope-based global correlation norm for ultrasound computed tomography

Many studies have been carried out on ultrasound computed tomography (USCT) for its ability to offer quantitative measurements of tissue sound speed. Full waveform inversion (FWI) is a technique for reconstructing high-resolution sound speed images by iteratively minimizing the difference between the observed ultrasound data and the synthetic data based on the waveform equation. However, FWI suffers from cycle-skipping, which usually causes FWI convergence at a local minimum. Cycle-skipping occurs when the phase difference between the observed data and the synthetic data exceeds half a cycle. The simplest way to avoid cycle-skipping is to use low-frequency information for reconstruction. Nevertheless, in imaging systems, the response bandwidth of the probe is limited, and reliable low-frequency information often exceeds the response band. Therefore, it is a challenge to perform FWI imaging and avoid cycle-skipping problems without low-frequency information. In this paper, we propose a frequency shift envelope-based global correlation norm (FSEGCN), where an artificial source wavelet with a lower frequency is adopted to calculate synthetic data. FSEGCN compared with FWI, envelope inversion (EI), global correlation norm (GCN), envelope-based global correlation norm (EGCN) through concentric circle phantom without low-frequency information. The experimental results demonstrated the capability of the proposed method to recover the sound speed close to the exact model in the absence of low-frequency information, whereas FWI, EI, GCN, and EGCN cannot. Experiments on phantoms of the human head and calf show that artificial source wavelets can reduce image artifacts and enhance reconstruction robustness, when original low-frequency information is absent.

A coupling, stabilizing, and shaping strategy for breast ultrasound computed tomography (USCT) with a ring array transducer

Breast ultrasound computed tomography (USCT) has been gradually promoted to clinical application after years of rapid development. Compared with the traditional handheld ultrasound scanning method, the scanning plane of USCT is fixed at the coronal plane, and the scanning path is designed in advance; the acoustic window is not in direct contact with the breast, a lot of coupling medium (usually degassed water is used to fill the gaps between the probe and breast. The clinical application of breast USTC faces challenges: (1) the processes of water degassing, heating, filling, draining, and cleaning prolong the entire scan cycle and reduce patient throughput. (2) The breast is not stabilized and slight movements of the breast may cause motion artifacts in the USCT images. (3) The non-normal incidence of ultrasound into the breast causes reflected and transmitted signals received with a low signal-to-noise ratio (SNR) or even unable to be detected. This article proposes a coupling, stabilizing, and shaping strategy for the clinical application of USCT with a ring array transducer. The solid gel coupling agent (SGCA) is applied for coupling, and a set of SGCA moldings is designed to stabilize and shape the breast during scanning, the breast shape and size which vary from person to person are simplified into several models. The preparation time is reduced to less than 1 min by replacing disposable moldings. The results show that the breast after shaping is close to round in the coronal plane, and slopes of the breast skin are limited in the sagittal and transverse planes, the breast subcutaneous tissue (fat and glands) has a better contrast-to-noise ratio (CNR) and can be better distinguished in the reflection images than that of the breast without shaping. The mean value of the raw beamformed data which represents the reflection signal amplitude of breast subcutaneous tissue after shaping shows 1.5 times that of the breast without shaping, the signal-to-noise ratio (SNR) of the raw transmission signal data after breast shaping is overall higher than that of the breast without shaping. The application of SGCA moldings for breast coupling, stabilizing, and shaping also benefits establishing a standardized scanning process, the standardized diagnosis of the breast lesion, and the localization of breast lesions.

Magnetically driven capsules with multimodal response and multifunctionality for biomedical applications

Untethered capsules hold clinical potential for the diagnosis and treatment of gastrointestinal diseases. Although considerable progress has been achieved recently in this field, the constraints imposed by the narrow spatial structure of the capsule and complex gastrointestinal tract environment cause many open-ended problems, such as poor active motion and limited medical functions. In this work, we describe the development of small-scale magnetically driven capsules with a distinct magnetic soft valve made of dual-layer ferromagnetic soft composite films. A core technological advancement achieved is the flexible opening and closing of the magnetic soft valve by using the competitive interactions between magnetic gradient force and magnetic torque, laying the foundation for the functional integration of both drug release and sampling. Meanwhile, we propose a magnetic actuation strategy based on multi-frequency response control and demonstrate that it can achieve effective decoupled regulation of the capsule's global motion and local responses. Finally, through a comprehensive approach encompassing ideal models, animal ex vivo models, and in vivo assessment, we demonstrate the versatility of the developed magnetic capsules and their multiple potential applications in the biomedical field, such as targeted drug delivery and sampling, selective dual-drug release, and light/thermal-assisted therapy.

[Correlation analysis of urinary arsenic species and health effect indicators of occupational arsenic exposure workers]

Objective: To explore the correlation between urinary arsenic and health effects through the determination and analysis of urinary arsenic levels in occupational arsenic exposed workers. Methods: In November 2021, 95 workers exposed to arsenic and its inorganic compounds and 31 administrative personnel from a non-ferrous metal smelter in Yunnan Province were selected as the contact group and control group, respectively. Urine forms of arsenic, blood tumor markers, liver function were detected, and micronucleus test was used to analyze the chromosome damage. The correlation between urine forms of arsenic and health effects were analyzed. Results: Compared with the control group, the concentrations of urinary trivalent inorganic arsenic (iAs(3+)) , pentavalent inorganic arsenic (iAs(5+)) , inorganic arsenic (iAs=ΣiAs(3+)+iAs(5+)) , monomethyl arsenic (MMA) , dimethyl arsenic (DMA) and urinary arsenic (ΣiAs+MMA+DMA) at the end of class in contact group were higher (P<0.05) . There was no statistically significant difference in blood tumor markers and liver function indicators between the two groups (P>0.05) . Compared with the control group, the peripheral blood micronucleus rate and cell micronucleus rate in the contact group were significantly increased (P<0.05) . The urinary arsenic, iAs(5+), inorganic arsenic and DMA were positively correlated with peripheral blood micronucleus rate in contact group (r(s)=0.48, 0.34, 0.37, 0.23, P<0.05) , and the urinary arsenic, iAs(5+), DMA were positively correlated with peripheral blood micronucleus rate (r(s)=0.48, 0.34, 0.26, P<0.05) . Conclusion: There is a significant correlation between different valence states of arsenic in the urine and abnormal health effects of occupational arsenic exposed workers. It is necessary to strengthen the detection of arsenic species in the urine of occupational arsenic exposed workers to better protect their health.

An All-Protein Multisensory Highly Bionic Skin

To achieve a highly realistic robot, closely mimicking human skin in terms of materials and functionality is essential. This paper presents an all-protein silk fibroin bionic skin (SFBS) that emulates both fast-adapting (FA) and slow-adapting (SA) receptors. The mechanically different silk film and hydrogel, which exhibited skin-like properties, such as stretchability (>140%), elasticity, low modulus (<10 kPa), biocompatibility, and degradability, were prepared through mesoscopic reconstruction engineering to mimic the epidermis and dermis. Our SFBS, incorporating SA and FA sensors, demonstrated a highly sensitive (1.083 kPa-1) static pressure sensing performance (in vitro and in vivo), showed the ability to sense high-frequency vibrations (50-400 Hz), could discriminate materials and sliding, and could even identify the fine morphological differences between objects. As proof of concept, an SFBS-integrated rehabilitation glove was synthesized, which could help stroke patients regain sensory feedback. In conclusion, this work provides a practical approach for developing skin equivalents, prostheses, and smart robots.

Hybrid CNN-Transformer Network with Circular Feature Interaction for Acute Ischemic Stroke Lesion Segmentation on Non-contrast CT Scans

Lesion segmentation is a fundamental step for the diagnosis of acute ischemic stroke (AIS). Non-contrast CT (NCCT) is still a mainstream imaging modality for AIS lesion measurement. However, AIS lesion segmentation on NCCT is challenging due to low contrast, noise and artifacts. To achieve accurate AIS lesion segmentation on NCCT, this study proposes a hybrid convolutional neural network (CNN) and Transformer network with circular feature interaction and bilateral difference learning. It consists of parallel CNN and Transformer encoders, a circular feature interaction module, and a shared CNN decoder with a bilateral difference learning module. A new Transformer block is particularly designed to solve the weak inductive bias problem of the traditional Transformer. To effectively combine features from CNN and Transformer encoders, we first design a multi-level feature aggregation module to combine multi-scale features in each encoder and then propose a novel feature interaction module containing circular CNN-to-Transformer and Transformer-to-CNN interaction blocks. Besides, a bilateral difference learning module is proposed at the bottom level of the decoder to learn the different information between the ischemic and contralateral sides of the brain. The proposed method is evaluated on three AIS datasets: the public AISD, a private dataset and an external dataset. Experimental results show that the proposed method achieves Dices of 61.39% and 46.74% on the AISD and the private dataset, respectively, outperforming 17 state-of-the-art segmentation methods. Besides, volumetric analysis on segmented lesions and external validation results imply that the proposed method is potential to provide support information for AIS diagnosis.

Self-calibrating dual-sensing electrochemical sensors for accurate detection of carbon dioxide in blood

A paper-based electrochemical dual-function biosensor capable of determining pH and TCO2 was synthesized for the first time using an iridium oxide pH electrode and an all-solid-state ion electrode (ASIE). In the study, to obtain highly reliable results, the biosensor was equipped with a real-time pH correction function before TCO2 measurements. Compared to traditional liquid-filling carbon dioxide detection sensors, the utilization of ferrocene endows our novel sensor with abundant positive sites, and thus greatly improves its performance. Conversely, the introduction of MXene with conductivity close to that of metals reduces electrode resistance, which is beneficial for accelerating the electrochemical reaction of the sensor and reducing LOD. After optimization, the detection range of TCO2 is 0.095 nM-0.66 M, with a detection limit of as low as 0.023 nM. In addition, the sensor was used in real serum sample-spiked recovery experiments and comparison experiments with existing clinical blood gas analyzers, which confirmed the effectiveness of its clinical application. This study provides a method for the rational design of paper-based electrochemical biosensors and a new approach for the clinical detection of blood carbon dioxide.

Risk Stratification for Oropharyngeal Squamous Cell Carcinoma Using Texture Analysis on CT - A Step Beyond HPV Status

Background and Purpose: Human papillomavirus-associated oropharyngeal squamous cell carcinoma (OPSCC) is increasingly prevalent. Despite the overall more favorable outcome, the observed heterogeneous treatment response within this patient group highlights the need for additional means to prognosticate and guide clinical decision-making. Promising prediction models using radiomics from primary OPSCC have been derived. However, no model/s using metastatic lymphadenopathy exist to allow prognostication in those instances when the primary tumor is not seen. The aim of our study was to evaluate whether radiomics using metastatic lymphadenopathy allows for the development of a useful risk assessment model comparable to the primary tumor and whether additional knowledge of the HPV status further improves its prognostic efficacy. Materials and Methods: 80 consecutive patients diagnosed with stage III-IV OPSCC between February 2009 and October 2015, known human papillomavirus status, and pre-treatment CT images were retrospectively identified. Manual segmentation of primary tumor and metastatic lymphadenopathy was performed and the extracted texture features were used to develop multivariate assessment models to prognosticate treatment response. Results: Texture analysis of either the primary or metastatic lymphadenopathy from pre-treatment enhanced CT images can be used to develop models for the stratification of treatment outcomes in OPSCC patients. AUCs range from .78 to .85 for the various OPSCC groups tested, indicating high predictive capability of the models. Conclusions: This preliminary study can form the basis multi-centre trial that may help optimize treatment and improve quality of life in patients with OPSCC in the era of personalized medicine.

Exploring sex differences for acute ischemic stroke clinical, imaging and thrombus characteristics in the INTERRSeCT study

Women, especially following menopause, are known to have worse outcomes following acute ischemic stroke. One primary postulated biological mechanism for worse outcomes in older women is a reduction in the vasculoprotective effects of estrogen. Using the INTERRseCT cohort, a multicentre international observational cohort studying recanalization in acute ischemic stroke, we explored the effects of sex, and modifying effects of age, on neuroradiological predictors of recanalization including robustness of leptomeningeal collaterals, thrombus burden and thrombus permeability. Ordinal regression analyses were used to examine the relationship between sex and each of the neuroradiological markers. Further, we explored both multiplicative and additive interactions between age and sex. All patients (n = 575) from INTERRseCT were included. Mean age was 70.2 years (SD: 13.1) and 48.5% were women. In the unadjusted model, female sex was associated with better collaterals (OR 1.37, 95% CIs: 1.01-1.85), however this relationship was not significant after adjusting for age and relevant comorbidities. There were no significant interactions between age and sex. In a large prospective international cohort, we found no association between sex and radiological predictors of recanalization including leptomeningeal collaterals, thrombus permeability and thrombus burden.

Impact of vessel tortuosity and radiological thrombus characteristics on the choice of first-line thrombectomy strategy: Results from the ESCAPE-NA1 trial

INTRODUCTION

Despite improvements in device technology, only one-third of stroke patients undergoing endovascular thrombectomy (EVT) achieve first-pass effect (FPE). We investigated the effect of arterial tortuosity and thrombus characteristics on the relationship between first-line EVT strategy and angiographic outcomes.

PATIENTS AND METHODS

Patients with thin-slice baseline CT-angiography from the ESCAPE-NA1 trial (Efficacy and safety of nerinetide for the treatment of acute ischemic stroke) were included. Tortuosity was estimated using the tortuosity index extracted from catheter pathway, and radiological thrombus characteristics were length, non-contrast density, perviousness and hyperdense artery sign. We assessed the association of first-line EVT strategy (stent-retriever [SR] versus contact aspiration [CA] versus combined SR+CA) with FPE (eTICI score 2c/3 after one pass), final eTICI 2b/3, number of passes and procedure duration using multivariable regression. Interaction of tortuosity and thrombus characteristics with first-line technique were assessed using interaction terms.

RESULTS

Among 520 included patients, SR as a first-line modality was used in 165 (31.7%) patients, CA in 132 (25.4%), and combined SR+CA in 223 (42.9%). FPE was observed in 166 patients (31.9%). First-line strategy was not associated with FPE. Tortuosity had a significant effect on FPE only in the CA group (aOR = 0.90 [95% CI 0.83-0.98]) compared with stent-retrievers and combined first-line approach (p interaction = 0.03). There was an interaction between thrombus length and first-line strategy for number of passes (p interaction = 0.04). Longer thrombi were associated with higher number of passes only in the CA group (acOR 1.03 [95% CI 1.00-1.06]).

CONCLUSION

Our study suggests that vessel tortuosity and longer thrombi may negatively affect the performance of first-line contact aspiration catheters in acute stroke patients undergoing EVT.

Predicting DWI-FLAIR mismatch on NCCT: the role of artificial intelligence in hyperacute decision making

Background

The presence of diffusion-weighted imaging (DWI) and fluid-attenuated inversion recovery (FLAIR) mismatch was used to determine eligibility for intravenous thrombolysis in clinical trials. However, due to the restricted availability of MRI and the ambiguity of image assessment, it is not widely implemented in clinical practice.

Methods

A total of 222 acute ischemic stroke patients underwent non-contrast computed tomography (NCCT), DWI, and FLAIR within 1 h of one another. Human experts manually segmented ischemic lesions on DWI and FLAIR images and independently graded the presence of DWI-FLAIR mismatch. Deep learning (DL) models based on the nnU-net architecture were developed to predict ischemic lesions visible on DWI and FLAIR images using NCCT images. Inexperienced neurologists evaluated the DWI-FLAIR mismatch on NCCT images without and with the model's results.

Results

The mean age of included subjects was 71.8 ± 12.8  years, 123 (55%) were male, and the baseline NIHSS score was a median of 11 [IQR, 6-18]. All images were taken in the following order: NCCT - DWI - FLAIR, starting after a median of 139 [81-326] min after the time of the last known well. Intravenous thrombolysis was administered in 120 patients (54%) after NCCT. The DL model's prediction on NCCT images revealed a Dice coefficient and volume correlation of 39.1% and 0.76 for DWI lesions and 18.9% and 0.61 for FLAIR lesions. In the subgroup with 15  mL or greater lesion volume, the evaluation of DWI-FLAIR mismatch from NCCT by inexperienced neurologists improved in accuracy (from 0.537 to 0.610) and AUC-ROC (from 0.493 to 0.613).

Conclusion

The DWI-FLAIR mismatch may be reckoned using NCCT images through advanced artificial intelligence techniques.

Automated Segmentation of Intracranial Thrombus on NCCT and CTA in Patients with Acute Ischemic Stroke Using a Coarse-to-Fine Deep Learning Model

BACKGROUND AND PURPOSE

Identifying the presence and extent of intracranial thrombi is crucial in selecting patients with acute ischemic stroke for treatment. This article aims to develop an automated approach to quantify thrombus on NCCT and CTA in patients with stroke.

MATERIALS AND METHODS

A total of 499 patients with large-vessel occlusion from the Safety and Efficacy of Nerinetide in Subjects Undergoing Endovascular Thrombectomy for Stroke (ESCAPE-NA1) trial were included. All patients had thin-section NCCT and CTA images. Thrombi contoured manually were used as reference standard. A deep learning approach was developed to segment thrombi automatically. Of 499 patients, 263 and 66 patients were randomly selected to train and validate the deep learning model, respectively; the remaining 170 patients were independently used for testing. The deep learning model was quantitatively compared with the reference standard using the Dice coefficient and volumetric error. The proposed deep learning model was externally tested on 83 patients with and without large-vessel occlusion from another independent trial.

RESULTS

The developed deep learning approach obtained a Dice coefficient of 70.7% (interquartile range, 58.0%-77.8%) in the internal cohort. The predicted thrombi length and volume were correlated with those of expert-contoured thrombi (r = 0.88 and 0.87, respectively; P < .001). When the derived deep learning model was applied to the external data set, the model obtained similar results in patients with large-vessel occlusion regarding the Dice coefficient (66.8%; interquartile range, 58.5%-74.6%), thrombus length (r = 0.73), and volume (r = 0.80). The model also obtained a sensitivity of 94.12% (32/34) and a specificity of 97.96% (48/49) in classifying large-vessel occlusion versus non-large-vessel occlusion.

CONCLUSIONS

The proposed deep learning method can reliably detect and measure thrombi on NCCT and CTA in patients with acute ischemic stroke.

Bioinspired Conductive Enhanced Polyurethane Ionic Skin as Reliable Multifunctional Sensors

Ionogels prepared from ionic liquid (IL) have the characteristics of nonevaporation and stable performance relative to traditional hydrogels. However, the conductivities of commonly used ionogels are at very low relative to traditional hydrogels because the large sizes of the cation and anion in an IL impedes ion migration in polymer networks. In this study, ultradurable ionogels with suitable mechanical properties and high conductivities are prepared by impregnating IL into a safe, environmentally friendly water-based polyurethane (WPU) network by mimicking the ion transport channels in the phospholipid bilayer of the cell membrane. The increase in electrical conductivity is attributed to the introduction of carboxylic acid in the hard segment of WPU; this phenomenon regularly arranges hard segment structural domains by hydrogen bonding, forming ionic conduction channels. The conductivities of their ionogels are >28-39 mS cm^-1 . These ionogels have adjustable mechanical properties that make the Young's modulus value (0.1-0.6 MPa) similar to that of natural skin. The strain sensor has an ultrahigh sensitivity that ranges from 0.99 to 1.35, with a wide sensing range of 0.1%-200%. The findings are promising for various ionotronics requiring environmental stability and high conductivity characteristics.

Analysis of the reports of low-concentration atropine in controlling myopia in children

PURPOSE

To evaluate the efficacy of 0.01% atropine to slow the progression of myopia in children.

METHODS

We searched PubMed, Embase, ClinicalTrials.gov, CNKI, Cqvip and Wan fang databases from inception to January 2022, including RCTs (randomized controlled trials) and non-RCTs (non-randomized controlled trials). The search strategy was 'myopia' OR 'refractive error' and 'atropine.' Two researchers independently reviewed the articles, and stata12.0 was used for meta-analysis. The Jadad score was used to assess the quality of RCT, and the Newcastle-Ottawa scale was used for non-RCTs.

RESULTS

Five RCTs and two non-RCTs (1 prospective non-randomized controlled study, 1 retrospective cohort study) were identified (including 1000 eyes). Results of the meta-analysis showed statistical heterogeneity among the 7 included studies (P=0. 026, I2 =47.1%). According to different durations of atropine use - 4 months, 6 months and greater than 8 months, subgroup analysis results showed that the axial elongation of all experimental groups relative to control groups were respectively -0.03mm (95% [CI], (confidence interval), -0.07 to 0.01), -0.07mm (95% [CI], -0.10 to -0.05), -0.09mm (95% [CI], -0.12 to -0.06). Each P was greater than 0.05, which indicated that there is little heterogeneity among the subgroups.

CONCLUSIONS

In this meta-analysis of the short-term efficacy of atropine in myopia patients, it was found that there was little heterogeneity when grouped by usage time. It is suggested that the use of atropine in the treatment of myopia is not only related to its concentration but also related to the duration of use.

Abstract TMP87: A Novel Approach For Automated First Pass Effect Prediction On Computed Tomographic Angiography In Acute Ischemic Stroke Patients

Background and Purpose: First pass effect (FPE), or effective reperfusion with a single pass of endovascular thrombectomy (EVT) for acute ischemic stroke (AIS), is strongly associated with good functional outcome (mRS≤2) and can aid in optimal device selection for EVT. We aim to investigate the arterial tortuosity from great vessel origin to the intracranial occlusion location and predict first pass effect, automatically by a novel neural network, on computed tomographic angiography (CTA).

Materials and Methods: Patients with thin-slice (≤2.5 mm) neck CTA from the ESCAPE-NA1 trial (Efficacy and safety of nerinetide for the treatment of AIS) were included. Arterial centerlines from the aortic arch to the intracranial occlusion site were manually traced by three experienced readers on CTA. The centerlines were modeled and organized by tortuosity. A model based on graph neural network (GNN) was proposed to predict FPE on the processed data. Model performance was compared to manual annotations and traditional classification algorithms using diagnostic statistics.

Results: 539 patients were included, with a 429/110 training/testing-ratio. FPE was observed in 136(31.7%, training set) and 35 (31.8%, testing set). The suggested model showed an overall good performance with an area under the receiver operating characteristic curve (AUC-ROC) of 0.66 (95% CI=0.65-0.67), precision of 0.46(17/37), sensitivity of 0.71(17/35), specificity of 0.61(55/75) and accuracy of 0.65(72/110), whereas the manually annotated features with traditional classification methods had an AUC-ROC of 0.54 (95%CI=0.53, 0.55), precision of 0.42(8/19), sensitivity of 0.23(8/35), specificity of 0.85(64/75) and accuracy of 0.65(72/110).

Conclusion: An automated model for FPE prediction on CTA had better performance and higher sensitivity as compared to manual annotations and traditional machine learning algorithms, suggesting that it could be used in routine clinical practice prior to EVT.

Distal Embolization in Relation to Radiological Thrombus Characteristics, Treatment Details, and Functional Outcome

BACKGROUND

Distal embolization (DE) is a common complication of endovascular treatment (EVT). We investigated the association of radiological thrombus characteristics and treatment details with DE.

METHODS

Patients with thin-slice (≤2.5 mm) baseline noncontrast computed tomography and computed tomography angiography from the ESCAPE-NA1 trial (Efficacy and Safety of Nerinetide for the Treatment of Acute Ischemic Stroke) were included. Thrombus annotation was performed manually on coregistered scans by experienced readers. We assessed thrombus location, distance from internal carotid artery terminus, length, perviousness, absolute attenuation, and hyperdense artery sign. In addition, we evaluated balloon guide catheter use during EVT, first-line EVT approach, the number of thrombectomy passes, and prior intravenous thrombolysis administration. DE was defined as the occurrence of emboli distal to the target artery or in new territories during EVT. The association between thrombus characteristics, treatment details, and DE was evaluated using descriptive statistics and multivariable mixed-effects logistic regression, resulting in adjusted odds ratios (aOR) with 95% CI. Interaction between IVT and radiological thrombus characteristics was assessed by adding interaction terms in separate models.

RESULTS

In total, 496 out of 1105 (44.9%) ESCAPE-NA1 patients were included. DE was detected in 251 out of 496 patients (50.6%). Patients with DE had longer thrombi (median, 28.5 [interquartile range, 20.8-42.3] mm versus 24.4 [interquartile range, 17.1-32.4] mm; P<0.01). There were no statistically significant differences in the other thrombus characteristics. Factors associated with DE were thrombus length (aOR, 1.02 [95% CI, 1.01-1.04]), balloon guide catheter use (aOR, 0.49 [95% CI, 0.29-0.85]), and number of passes (aOR, 1.24 [95% CI, 1.04-1.47]). In patients with hyperdense artery sign, IVT was associated with reduced odds of DE (aOR, 0.55 [95% CI, 0.31-0.97]), P for interaction=0.04.

CONCLUSIONS

DE was associated with longer thrombi, no balloon guide catheter use, and more EVT passes. IVT was associated with a reduced risk of DE in patients with hyperdense artery sign. These findings may support treatment decisions on IVT and EVT approaches.

A switchable temperature-responsive ionic liquid-based surfactant-free microemulsion for extraction and separation of hydrophilic and lipophilic compounds from Camptotheca acuminata and extraction mechanism

In this study, a switchable temperature-responsive ionic liquid-based surfactant-free microemulsion (TRIL-SFME) for extraction and in-situ separation of hydrophilic and lipophilic compounds from Camptotheca acuminata was firstly developed and systematically characterized. This TRIL-SFME was obtained using 1-hexyl-3-methylimidazolium tetrafluoroborate ([HMIM][BF₄]), 1,2-propanediol and H₂O. The prepared TRIL-SFME presented low viscosity and rapid response to temperature. Firstly, the effect of temperatures on TRIL-SFME phase behavior was studied followed by determination of effect of liquid/solid ratio and extraction time on the extraction yields of the targeted compounds. The TRIL-SFME demulsified rapidly by thermal stimulus, resulting in in-situ separation and enrichment of compounds with varying polarity. The results of present study revealed that TRIL-SFME had higher extraction yields (1.50-5.79 folds) compared to traditional solvents and individual components of TRIL-SFME. Besides, in-situ separation and enrichment of hydrophilic compounds (phenolic acids) and lipophilic compounds (alkaloids) was accomplished in short time (within 3 min) by cooling the system to 4 ℃. Furthermore, the mesoscopic behavior between TRIL-SFME and targeted compounds was simulated by dissipative particle dynamics (DPD) to explore the extraction mechanism for the first time. The results illustrated the formation of W/IL structure of TRIL-SFME and clarified solubilization mechanism of TRIL-SFME system for targeted compounds, which is related to its special "water pool" structure. This novel and switchable TRIL-SFME is an environmentally friendly and promising alternative to simultaneously extract, in-situ separate and enrich the natural active compounds with different polarity from plant matrices.

Abstract WP108: A Novel Multiphase CTA Perfusion Tool Compared To CTP In Patients With Suspected Acute Ischemic Stroke

Introduction: We recently published a Machine Learning-based algorithm using mCTA (mCTAp) that generates perfusion maps of the brain, similar to CTP. Here, we aim to validate the clinical utility of mCTAp in detection of ischemia, it’s side, extent and location.

Methods: One hundred and twenty-one subjects were included in the test dataset. These subjects had completed mCTAp (StrokeSENS) and CTP (4D; GE Healthcare) at baseline. After excluding 2/121 subjects due to poor image quality, a multi-reader-multi-case (n=119) study design was conducted with 3 experienced radiologists, reading post-processed maps (Tmax and rCBF) generated by both mCTAp and CTP. Both reading sessions were separated by a few days. All readers were blinded to modality and clinical information and the reading order was randomized between sessions. Core lab imaging assessments that used NCCT, mCTA and CTP were considered as ground truth. A mixed effect regression model with the reader as random effect variable was used to calculate the AUC, sensitivity, and specificity for both imaging arms regarding ischemia detection, ischemia side, and occlusion site selection (i.e., ICA/M1[considered LVO], M2 or distal, ACA or PCA). The time required for image interpretation was compared between the two modalities.

Results: The AUCs for detecting ischemia were comparable between mCTAp and CTP (0.85 [95%CI:0.8-0.9] and 0.84 [95%CI:0.8-0.9] respectively; p=0.43), the affected ischemic side (0.94 [0.92-0.97] and 0.96 [0.94-0.98] respectively; p=0.69), detecting a LVO (0.84 [0.8-0.9] and 0.86 [0.8-0.9]; p=0.31) and M2 or distal occlusions (0.8 [0.7-0.8] and 0.9 [0.84-0.92]; p=0.22). The median (IQR) time for interpretation was 62s (46-78) and 59s (42-69) for mCTAp and CTP respectively (p=0.15).

Conclusion: mCTAp shows similar performances when compared to CTP in assisting readers to detect ischemia, location, and extent by using Tmax and rCBF perfusion maps.

Investigating the mechanism of interactive regulation of B-cell lymphoma-2/Beclin 1 through electroacupuncture intervention during reperfusion in myocardial ischemia-reperfusion injury in a rat model

To observe the regulation of B-cell lymphoma-2 (Bcl-2)/Beclin 1 interaction through electroacupuncture (EA) intervention during reperfusion and to investigate the EA mechanism of apoptosis-autophagy interactive regulation against myocardial ischemia-reperfusion injury (MIRI). A total of 48 adult Sprague Dawley (SD) rats were randomly divided into the sham-operated group (group Sham), the model group (group Model), the EA group (group EA), and the JNK inhibitor (SP600125) group (group JNK), with 12 rats in each group. Biospecimens were collected randomly from six rats in each group four hours after reperfusion. Evans Blue and triphenyl tetrazolium chloride double-staining were applied to observe each group's myocardial damage area and risk area. We collected 4 ml of blood by abdominal aortic method to detect serum troponin cTnI level by enzyme-linked immunosorbent assay (ELISA). For the remaining six in each group, a part of myocardial tissue below the ligation line was stored in 4% paraformaldehyde for immunohistochemistry and TUNEL staining; the other amount of myocardial tissue was detected by Western blotting to determine the expression levels of Bcl-2, Beclin1, and the phosphorylation levels of Thr69, Ser70, and Ser87 in Bcl-2. In results: electroacupuncture (EA) intervention during reperfusion significantly reduced the myocardial infarction area, cTnI level, and myocardial apoptosis, upregulated Bcl-2 expression, downregulated Beclin 1 expression and inhibited phosphorylation levels of Thr69, Ser70, and Ser87 in Bcl-2. We concluded that EA effectively inhibited apoptosis by upregulating Bcl-2 expression and inhibiting the phosphorylation of Thr69, Ser70, and Ser87 in Bcl-2. This reduced the separation of Bcl-2 and Beclin 1, restrains excessive autophagy, alleviates MIRI, and has a protective effect on myocardial tissue.

Multiphase CTA-derived tissue maps aid in detection of medium vessel occlusions

PURPOSE

Medium vessel occlusions (MeVOs) can be challenging to detect on imaging. Multiphase computed tomography angiography (mCTA) has been shown to improve large vessel occlusion (LVO) detection and endovascular treatment (EVT) selection. The aims of this study were to determine if mCTA-derived tissue maps can (1) accurately detect MeVOs and (2) predict infarction on 24-h follow-up imaging with comparable accuracy to CT perfusion (CTP).

METHODS

Two readers assessed mCTA tissue maps of 116 ischemic stroke patients (58 MeVOs, 58 non-MeVOs) and determined by consensus: (1) MeVO (yes/no) and (2) occlusion site, blinded to clinical or imaging data. Sensitivity, specificity, and area under the curve (AUC) for MeVO detection were estimated in comparison to reference standards of (1) expert readings of baseline mCTA and (2) CTP maps. Volumetric and spatial agreement between mCTA- and CTP-predicted infarcts was assessed using concordance/intraclass correlation and Dice coefficients. Interrater agreement for MeVO detection on mCTA tissue maps was estimated with Cohen's kappa.

RESULTS

MeVO detection from mCTA-derived tissue maps had a sensitivity of 91% (95% CI: 80-97), specificity of 82% (95% CI: 70-90), and AUC of 0.87 (95% CI: 0.80-0.93) compared to expert reads of baseline mCTA. Interrater reliability was good (0.72, 95% CI: 0.60-0.85). Compared to CTP maps, sensitivity was 87% (95% CI: 75-95), specificity was 78% (95%CI: 65-88), and AUC was 0.83 (95% CI: 0.76-0.90). The mean difference between mCTA- and CTP-predicted final infarct volume was 4.8 mL (limits of agreement: - 58.5 to 68.1) with a Dice coefficient of 33.5%.

CONCLUSION

mCTA tissue maps can be used to reliably detect MeVO stroke and predict tissue fate.

Abstract 39: Ability Of Radiomics Versus Humans In Predicting First-pass Effect After Endovascular Treatment In The Escape-na1 Trial

Introduction: First-pass effect (FPE), i.e., achieving reperfusion with a single thrombectomy device pass, is associated with better clinical outcomes in patients with acute stroke. FPE is therefore increasingly being used as a marker of device and procedural efficacy. We evaluated the ability of thrombus-based radiomics models to predict FPE in patients undergoing endovascular thrombectomy (EVT) and compare performance to experts and non-radiomics thrombus characteristics.

Methods: Patients with thin-slice non-contrast CT and CT angiography from The Efficacy and Safety of Nerinetide for the Treatment of Acute Ischemic Stroke (ESCAPE-NA1) trial were included. Thrombi were manually segmented on all images. Data was randomly split into a derivation set that included a training and a validation subset and an independent test set. Radiomics features were extracted from the derivation data set. Three expert stroke physicians reviewed baseline imaging and clinical data for the test set. The machine learning (ML) models were compared to the three experts in predicting the primary outcome (FPE) in the test set using area under the receiver operating characteristic curves (AUC-ROC).

Results: A total of 554 patients with available thin-slice images comprised of a derivation set (training subset [n=388, 70%]), validation subset [n=55, 10%]), and a test set (n=111, 20%). FPE was seen in 31.8% in the derivation set and 31.5 % in the test set. AUC of the best radiomics model was 0.74 (95% CI: 0.64, 0.84), which was higher than the mean AUC of the three experts 0.60 (95% CI: 0.50, 0.71) ( P =0.009). Specificity of radiomics was better than the mean specificity of the three experts, 46 of 76 (60%) vs. 35 of 76 (46.4%), P =0.004, whereas sensitivity was not significantly different between radiomics (28 of 35 [79%]) and experts (27 of 35 [77%]). Moreover, radiomics features performed better than non-radiomics features such as thrombus volume and permeability measurements in predicting FPE ( P <0.05).

Conclusion: A radiomics-based ML model of thrombus characteristics on non-contrast CT and CT angiography performs better than experts and non-radiomics image characteristics in predicting FPE in patients with acute stroke treated with EVT.

Abstract 131: Multiphase CT Angiography Perfusion Vs. CT Perfusion In Predicting Final Infarction In Acute Stroke Patients

Background: In acute ischemic stroke (AIS), Computed Tomography Perfusion (CT, CTP) is the most widely used technique for determining extent of tissue likely to die even after successful reperfusion. However, CTP results in higher radiation dose to the patient, is affected by motion, and is not widely available. Multiphase CT Angiography (mCTA), by contrast, is a low radiation extension to the ubiquitous CT Angiography workflow. Here, we evaluate StrokeSENS mCTA Perfusion, a software tool that uses mCTA to estimate brain tissue perfusion, and compare it to CTP in its ability to predict final infarction.

Methods: 551 subjects with baseline mCTA, Non-contrast CT (NCCT), and CTP were included. Of these, 480 were part of the development dataset used to derive the mCTA Perfusion algorithm while the remaining 71 were included in the test dataset. T max and CBF perfusion maps were generated on CTP using GE CTP-4D Perfusion, and on mCTA using StrokeSENS mCTA Perfusion. Final infarction was manually segmented on 24-48h MRI/NCCT by 2 experts using ITK-SNAP. Voxel values from CTP and mCTA were assessed in their ability to predict final infarction at an individual patient level (AUC calculated for each patient, then averaged across patients) and for the combined patient data (voxels pooled across patients, then one AUC calculated), then compared (two-sided difference test p-value, p).

Results: At patient level, mCTA Perfusion T max AUC was 77.7% (95% c.i.: [74%, 82%]) while CTP T max AUC was 74.6% (95% c.i.: [71%, 79%]), p=0.15. mCTA Perfusion CBF AUC was 68.5% (95% c.i.: [65%, 72%]) while CTP CBF AUC was 69.8% (95% c.i.: [67%, 73%]), p=0.43. In combined patient data analysis, mCTA perfusion T max AUC was 84.13% while CTP T max AUC was 81.36%, p=0. mCTA perfusion CBF AUC was 74.44% while CTP CBF AUC was 72.51%, p=0.

Conclusion: StrokeSENS mCTA Perfusion software is similar to traditional CT Perfusion in its ability to predict final infarction in patients with acute ischemic stroke.

Interrater Agreement and Detection Accuracy for Medium-Vessel Occlusions Using Single-Phase and Multiphase CT Angiography

BACKGROUND AND PURPOSE

Accurate and reliable detection of medium-vessel occlusions is important to establish the diagnosis of acute ischemic stroke and initiate appropriate treatment with intravenous thrombolysis or endovascular thrombectomy. However, medium-vessel occlusions are often challenging to detect, especially for unexperienced readers. We aimed to evaluate the accuracy and interrater agreement of the detection of medium-vessel occlusions using single-phase and multiphase CTA.

MATERIALS AND METHODS

Single-phase and multiphase CTA of 120 patients with acute ischemic stroke (20 with no occlusion, 44 with large-vessel occlusion, and 56 with medium-vessel occlusion in the anterior and posterior circulation) were assessed by 3 readers with varying levels of experience (session 1: single-phase CTA; session 2: multiphase CTA). Interrater agreement for occlusion type (large-vessel occlusion versus medium-vessel occlusion versus no occlusion) and for detailed occlusion sites was calculated using the Fleiss κ with 95% confidence intervals. Accuracy for the detection of medium-vessel occlusions was calculated for each reader using classification tables.

RESULTS

Interrater agreement for occlusion type was moderate for single-phase CTA (κ  = 0.58; 95% CI, 0.56-0.62) and almost perfect for multiphase CTA (κ = 0.81; 95% CI, 0.78-0.83). Interrater agreement for detailed occlusion sites was moderate for single-phase CTA (κ = 0.55; 95% CI, 0.53-0.56) and substantial for multiphase CTA (κ = 0.71; 95% CI, 0.67-0.74). On single-phase CTA, readers 1, 2, and 3 classified 33/56 (59%), 34/56 (61%), and 32/56 (57%) correctly as medium-vessel occlusions. On multiphase CTA, 48/56 (86%), 50/56 (89%), and 50/56 (89%) medium-vessel occlusions were classified correctly.

CONCLUSIONS

Interrater agreement for medium-vessel occlusions is moderate when using single-phase CTA and almost perfect with multiphase CTA. Detection accuracy is substantially higher with multiphase CTA compared with single-phase CTA, suggesting that multiphase CTA might be a valuable tool for assessment of medium-vessel occlusion stroke.

Evaluating nnU-Net for early ischemic change segmentation on non-contrast computed tomography in patients with Acute Ischemic Stroke

Identifying the presence and extent of early ischemic changes (EIC) on Non-Contrast Computed Tomography (NCCT) is key to diagnosing and making time-sensitive treatment decisions in patients that present with Acute Ischemic Stroke (AIS). Segmenting EIC on NCCT is however a challenging task. In this study, we investigated a 3D CNN based on nnU-Net, a self-adapting CNN technique that has become the state-of-the-art in medical image segmentation, for segmenting EIC in NCCT of AIS patients. We trained and tested this model on a sizeable and heterogenous dataset of 534 patients, split into 438 for training and validation and 96 for testing. On this test set, we additionally assessed the inter-rater performance by comparing the proposed approach against two reference segmentation annotations by expert neuroradiologist readers, using this as the benchmark against which to compare our model. In terms of spatial agreement, we report median Dice Similarity Coefficients (DSCs) of 39.8% for the model vs. Reader-1, 39.4% for the model vs. Reader-2, and 55.6% for Reader-2 vs. Reader-1. In terms of lesion volume agreement, we report Intraclass Correlation Coefficients (ICCs) of 83.4% for model vs. Reader-1, 80.4% for model vs. Reader-2, and 94.8% for Reader-2 vs. Reader-1. Based on these results, we conclude that our model performs well relative to expert human performance and therefore may be useful as a decision-aid for clinicians.

Impact of Multiphase Computed Tomography Angiography for Endovascular Treatment Decision-Making on Outcomes in Patients with Acute Ischemic Stroke

BACKGROUND AND PURPOSE

Various imaging paradigms are used for endovascular treatment (EVT) decision-making and outcome estimation in acute ischemic stroke (AIS). We aim to compare how these imaging paradigms perform for EVT patient selection and outcome estimation.

METHODS

Prospective multi-center cohort study of patients with AIS symptoms with multi-phase computed tomography angiography (mCTA) and computed tomography perfusion (CTP) baseline imaging. mCTA-based EVT-eligibility was defined as presence of large vessel occlusion (LVO) and moderate-to-good collaterals on mCTA. CTP-based eligibility was defined as presence of LVO, ischemic core (defined on relative cerebral blood flow, absolute cerebral blood flow, and cerebral blood volume maps) <70 mL, mismatch-ratio >1.8, absolute mismatch >15 mL. EVT-eligibility and adjusted rates of good outcome (modified Rankin Scale 0-2) based on these imaging paradigms were compared.

RESULTS

Of 289/464 patients with LVO, 263 (91%) were EVT-eligible by mCTA-criteria versus 63 (22%), 19 (7%) and 103 (36%) by rCBF, aCBF, and CBV-CTP-criteria. CTP and mCTA-criteria were discordant in 40% to 53%. Estimated outcomes were best in patients who met both mCTA and CTP eligibility-criteria and were treated with EVT (62% to 87% good outcome). Patients eligible for EVT by mCTA-criteria and not by CTP-criteria receiving EVT achieved good outcome rates of 53% to 57%. Few patients met CTP-criteria and not mCTA-criteria for EVT.

CONCLUSIONS

Simpler imaging selection criteria that rely on little else than detection of the occluded blood vessel may be more sensitive and less specific, thus resulting in more patients being offered EVT and arguably benefiting from it.

Stretchable, Stable, and Degradable Silk Fibroin Enabled by Mesoscopic Doping for Finger Motion Triggered Color/Transmittance Adjustment

As a kind of biocompatible material with long history, silk fibroin is one of the ideal platforms for on-skin and implantable electronic devices, especially for self-powered systems. In this work, to solve the intrinsic brittleness as well as poor chemical stability of pure silk fibroin film, mesoscopic doping of regenerated silk fibroin is introduced to promote the secondary structure transformation, resulting in huge improvement in mechanical flexibility (∼250% stretchable and 1000 bending cycles) and chemical stability (endure 100 °C and 3-11 pH). Based on such doped silk film (SF), a flexible, stretchable and fully bioabsorbable triboelectric nanogenerator (TENG) is developed to harvest biomechanical energy in vitro or in vivo for intelligent wireless communication, for example, such TENG can be attached on the fingers to intelligently control the electrochromic function of rearview mirrors, in which the transmittance can be easily adjusted by changing contact force or area. This robust TENG shows great potential application in intelligent vehicle, smart home and health care systems.

Strength of Association between Infarct Volume and Clinical Outcome Depends on the Magnitude of Infarct Size: Results from the ESCAPE-NA1 Trial

BACKGROUND AND PURPOSE

Infarct volume is an important predictor of clinical outcome in acute stroke. We hypothesized that the association of infarct volume and clinical outcome changes with the magnitude of infarct size.

MATERIALS AND METHODS

Data were derived from the Safety and Efficacy of Nerinetide in Subjects Undergoing Endovascular Thrombectomy for Stroke (ESCAPE-NA1) trial, in which patients with acute stroke with large-vessel occlusion were randomized to endovascular treatment plus either nerinetide or a placebo. Infarct volume was manually segmented on 24-hour noncontrast CT or DWI. The relationship between infarct volume and good outcome, defined as mRS 0-2 at 90 days, was plotted. Patients were categorized on the basis of visual grouping at the curve shoulders of the infarct volume/outcome plot. The relationship between infarct volume and adjusted probability of good outcome was fitted with linear or polynomial functions as appropriate in each group.

RESULTS

We included 1099 individuals in the study. Median infarct volume at 24 hours was 24.9 mL (interquartile range [IQR] = 6.6-92.2 mL). On the basis of the infarct volume/outcome plot, 4 infarct volume groups were defined (IQR = 0-15 mL, 15.1-70 mL, 70.1-200 mL, >200 mL). Proportions of good outcome in the 4 groups were 359/431 (83.3%), 219/337 (65.0%), 71/201 (35.3%), and 16/130 (12.3%), respectively. In small infarcts (IQR = 0-15 mL), no relationship with outcome was appreciated. In patients with intermediate infarct volume (IQR = 15-200 mL), there was progressive importance of volume as an outcome predictor. In infarcts of > 200 mL, outcomes were overall poor.

CONCLUSIONS

The relationship between infarct volume and clinical outcome varies nonlinearly with the magnitude of infarct size. Infarct volume was linearly associated with decreased chances of achieving good outcome in patients with moderate-to-large infarcts, but not in those with small infarcts. In very large infarcts, a near-deterministic association with poor outcome was seen.

Radiologic Patterns of Intracranial Hemorrhage and Clinical Outcome after Endovascular Treatment in Acute Ischemic Stroke: Results from the ESCAPE-NA1 Trial

Background Intracranial hemorrhage is a known complication after endovascular treatment in patients with acute ischemic stroke due to large vessel occlusion, but the association between radiologic hemorrhage severity and outcome is controversial. Purpose To investigate the prevalence and impact on outcome of intracranial hemorrhage and hemorrhage severity after endovascular stroke treatment. Materials and Methods The Efficacy and Safety of Nerinetide for the Treatment of Acute Ischemic Stroke (ESCAPE-NA1) trial enrolled participants with acute large vessel occlusion stroke who underwent endovascular treatment from March 1, 2017, to August 12, 2019. Evidence of any intracranial hemorrhage, hemorrhage multiplicity, and radiologic severity, according to the Heidelberg classification (hemorrhagic infarction type 1 [HI1], hemorrhagic infarction type 2 [HI2], parenchymal hematoma type 1 [PH1], and parenchymal hematoma type 2 [PH2]) was assessed at CT or MRI 24 hours after endovascular treatment. Good functional outcome, defined as a modified Rankin score of 0-2 at 90 days, was compared between participants with intracranial hemorrhage and those without intracranial hemorrhage at follow-up imaging and between hemorrhage subtypes. Poisson regression was performed to obtain adjusted effect size estimates for the presence of any intracranial hemorrhage and hemorrhage subtypes at good functional outcome. Results Of 1097 evaluated participants (mean age, 69 years ± 14 [standard deviation]; 551 men), any degree of intracranial hemorrhage was observed in 372 (34%). Good outcomes were less often achieved among participants with hemorrhage than among those without hemorrhage at follow-up imaging (164 of 372 participants [44%] vs 500 of 720 [69%], respectively; P < .01). After adjusting for baseline variables and infarct volume, intracranial hemorrhage was not associated with decreased chances of good outcome (adjusted risk ratio [RR] = 0.91 [95% CI: 0.82, 1.02], P = .10), but there was a graded relationship of radiologic hemorrhage severity and outcomes, whereby PH1 (RR = 0.77 [95% CI: 0.61, 0.97], P = .03) and PH2 (RR = 0.41 [95% CI: 0.21, 0.81], P = .01) were associated with decreased chances of good outcome. Conclusion Any degree of intracranial hemorrhage after endovascular treatment was seen in one-third of participants. A graded association existed between radiologic hemorrhage severity and outcome. Hemorrhagic infarction was not associated with outcome, whereas parenchymal hematoma was strongly associated with poor outcome, independent of infarct volume. © RSNA, 2021 Clinical trial registration no. NCT01778335 Online supplemental material is available for this article.

Automated Prediction of Ischemic Brain Tissue Fate from Multiphase Computed Tomographic Angiography in Patients with Acute Ischemic Stroke Using Machine Learning

Background and Purpose

Multiphase computed tomographic angiography (mCTA) provides time variant images of pial vasculature supplying brain in patients with acute ischemic stroke (AIS). To develop a machine learning (ML) technique to predict tissue perfusion and infarction from mCTA source images.

Methods

284 patients with AIS were included from the Precise and Rapid assessment of collaterals using multi-phase CTA in the triage of patients with acute ischemic stroke for Intra-artery Therapy (Prove-IT) study. All patients had non-contrast computed tomography, mCTA, and computed tomographic perfusion (CTP) at baseline and follow-up magnetic resonance imaging/non-contrast-enhanced computed tomography. Of the 284 patient images, 140 patient images were randomly selected to train and validate three ML models to predict a pre-defined Tmax thresholded perfusion abnormality, core and penumbra on CTP. The remaining 144 patient images were used to test the ML models. The predicted perfusion, core and penumbra lesions from ML models were compared to CTP perfusion lesion and to follow-up infarct using Bland-Altman plots, concordance correlation coefficient (CCC), intra-class correlation coefficient (ICC), and Dice similarity coefficient.

Results

Mean difference between the mCTA predicted perfusion volume and CTP perfusion volume was 4.6 mL (limit of agreement [LoA], –53 to 62.1 mL; P=0.56; CCC 0.63 [95% confidence interval [CI], 0.53 to 0.71; P<0.01], ICC 0.68 [95% CI, 0.58 to 0.78; P<0.001]). Mean difference between the mCTA predicted infarct and follow-up infarct in the 100 patients with acute reperfusion (modified thrombolysis in cerebral infarction [mTICI] 2b/2c/3) was 21.7 mL, while it was 3.4 mL in the 44 patients not achieving reperfusion (mTICI 0/1). Amongst reperfused subjects, CCC was 0.4 (95% CI, 0.15 to 0.55; P<0.01) and ICC was 0.42 (95% CI, 0.18 to 0.50; P<0.01); in non-reperfused subjects CCC was 0.52 (95% CI, 0.20 to 0.60; P<0.001) and ICC was 0.60 (95% CI, 0.37 to 0.76; P<0.001). No difference was observed between the mCTA and CTP predicted infarct volume in the test cohort (P=0.67).

Conclusions

A ML based mCTA model is able to predict brain tissue perfusion abnormality and follow-up infarction, comparable to CTP.

A Detailed Analysis of Infarct Patterns and Volumes at 24-hour Noncontrast CT and Diffusion-weighted MRI in Acute Ischemic Stroke Due to Large Vessel Occlusion: Results from the ESCAPE-NA1 Trial

Background The effect of infarct pattern on functional outcome in acute ischemic stroke is incompletely understood. Purpose To investigate the association of qualitative and quantitative infarct variables at 24-hour follow-up noncontrast CT and diffusion-weighted MRI with 90-day clinical outcome. Materials and Methods The Safety and Efficacy of Nerinetide in Subjects Undergoing Endovascular Thrombectomy for Stroke, or ESCAPE-NA1, randomized controlled trial enrolled patients with large-vessel-occlusion stroke undergoing mechanical thrombectomy from March 1, 2017, to August 12, 2019. In this post hoc analysis of the trial, qualitative infarct variables (predominantly gray [vs gray and white] matter involvement, corticospinal tract involvement, infarct structure [scattered vs territorial]) and total infarct volume were assessed at 24-hour follow-up noncontrast CT or diffusion-weighted MRI. White and gray matter infarct volumes were assessed in patients by using follow-up diffusion-weighted MRI. Infarct variables were compared between patients with and those without good outcome, defined as a modified Rankin Scale score of 0-2 at 90 days. The association of infarct variables with good outcome was determined with use of multivariable logistic regression. Separate regression models were used to report effect size estimates with adjustment for total infarct volume. Results Qualitative infarct variables were assessed in 1026 patients (mean age ± standard deviation, 69 years ± 13; 522 men) and quantitative infarct variables were assessed in a subgroup of 358 of 1026 patients (mean age, 67 years ± 13; 190 women). Patients with gray and white matter involvement (odds ratio [OR] after multivariable adjustment, 0.19; 95% CI: 0.14, 0.25; P < .001), corticospinal tract involvement (OR after multivariable adjustment, 0.06; 95% CI: 0.04, 0.10; P < .001), and territorial infarcts (OR after multivariable adjustment, 0.22; 95% CI: 0.14, 0.32; P < .001) were less likely to achieve good outcome, independent of total infarct volume. Conclusion Infarct confinement to the gray matter, corticospinal tract sparing, and scattered infarct structure at 24-hour noncontrast CT and diffusion-weighted MRI were highly predictive of good 90-day clinical outcome, independent of total infarct volume. Clinical trial registration no. NCT02930018 © RSNA, 2021 Online supplemental material is available for this article. See also the editorial by Mossa-Basha in this issue.

MRI Diffusion-Weighted Imaging to Measure Infarct Volume: Assessment of Manual Segmentation Variability

BACKGROUND AND PURPOSE

Manual segmentation of infarct volume on follow-up MRI diffusion-weighted imaging (MRI-DWI) is considered the gold standard but is prone to rater variability. We assess the variability of manual segmentations of MRI-DWI infarct volume.

METHODS

Consecutive patients (May 2018 to May 2019) with the anterior circulation stroke and endovascularly treated were enrolled. All patients underwent 24- to 32-hour follow-up MRI. Three users manually segmented DWI infarct volumes slice by slice twice. The reference standard of DWI infarct volume was generated by the STAPLE algorithm. Intra- and interrater reliability was evaluated using the intraclass correlation coefficient (ICC) by comparing manual segmentations with the reference standard. Spatial measurements were evaluated using metrics of the Dice similarity coefficient (DSC). Volumetric measurements were compared using the lesion volume.

RESULTS

The dataset consisted of 44 patients, mean (SD) age was 70.1 years (±10.3), 43% were women, and median baseline NIHSS score was 16. Among three users, the mean DSC for MRI-DWI infarct volume segmentations ranged from 80.6% ± 11.7% to 88.6% ± 7.5%, and the mean absolute volume difference was 2.8 ± 6.8 to 13.0 ± 14.0 ml. Interrater ICC among the users for DSC and infarct volume was .86 (95% confidence interval [95% CI]: .78-.91) and .997 (95% CI: .995-.998). Intrarater ICC for the three users was .83 (95% CI: .69-.93), .84 (95% CI: .72-.91), and .80 (95% CI: .64-.89) for DSC, and .99 (95% CI: .987-.996), .991 (95% CI: .983-.995), and .996 (95% CI: .993-.998) for infarct volume.

CONCLUSIONS

Manual segmentation of infarct volume on follow-up MRI-DWI shows excellent agreement and good spatial overlap with the reference standard, suggesting its usefulness for measuring infarct volume on 24- to 32-hour MRI-DWI.

Biomimetic Salinity Power Generation Based on Silk Fibroin Ion-Exchange Membranes

Powering implanted medical devices (IMDs) is a long-term challenge since their use in biological environments requires a long-term and stable supply of power and a biocompatible and biodegradable battery system. Here, silk fibroin-based ion-exchange membranes are developed using bionics principles for reverse electrodialysis devices (REDs). Silk fibroin nanofibril (SNF) membranes are negatively and positively modified, resulting in strong cation and anion selectivity that regulates ion diffusion to generate electric power. These oppositely charged SNF membranes are assembled with Ag/AgCl electrodes into a multicompartment RED. By filling them with 10 and 0.001 mM NaCl solutions, a maximum output power density of 0.59 mW/m² at an external loading resistance of 66 kΩ is obtained. In addition, 10 pairs of SNF membranes produce a considerable voltage of 1.58 V. This work is a proof of concept that key components of battery systems can be fabricated with protein materials. Combined with the emergence of water-based battery technologies, the findings in this study provide insights for the construction of tissue-integrated batteries for the next generation of IMDs.

EIS-Net: Segmenting early infarct and scoring ASPECTS simultaneously on non-contrast CT of patients with acute ischemic stroke

Detecting early infarct (EI) plays an essential role in patient selection for reperfusion therapy in the management of acute ischemic stroke (AIS). EI volume at acute or hyper-acute stage can be measured using advanced pre-treatment imaging, such as MRI and CT perfusion. In this study, a novel multi-task learning approach, EIS-Net, is proposed to segment EI and score Alberta Stroke Program Early CT Score (ASPECTS) simultaneously on baseline non-contrast CT (NCCT) scans of AIS patients. The EIS-Net comprises of a 3D triplet convolutional neural network (T-CNN) for EI segmentation and a multi-region classification network for ASPECTS scoring. T-CNN has triple encoders with original NCCT, mirrored NCCT, and atlas as inputs, as well as one decoder. A comparison disparity block (CDB) is designed to extract and enhance image contexts. In the decoder, a multi-level attention gate module (MAGM) is developed to recalibrate the features of the decoder for both segmentation and classification tasks. Evaluations using a high-quality dataset comprising of baseline NCCT and concomitant diffusion weighted MRI (DWI) as reference standard of 260 patients with AIS show that the proposed EIS-Net can accurately segment EI. The EIS-Net segmented EI volume strongly correlates with EI volume on DWI (r=0.919), and the mean difference between the two volumes is 8.5 mL. For ASPECTS scoring, the proposed EIS-Net achieves an intraclass correlation coefficient of 0.78 for total 10-point ASPECTS and a kappa of 0.75 for dichotomized ASPECTS (≤ 4 vs. >4). Both EI segmentation and ASPECTS scoring tasks achieve state-of-the-art performances.

Clinical outcomes of isolated deep grey matter infarcts after endovascular treatment of large vessel occlusion stroke

PURPOSE

There are few data on the prevalence and impact of isolated deep grey matter infarction in acute stroke. In this study, we aimed to investigate the prevalence of isolated deep grey matter infarcts and their impact on the outcome.

METHODS

Infarcts on 24-h follow-up imaging (non-contrast head CT or diffusion-weighted MRI) in the ESCAPE-NA1 trial were categorized into predominantly deep grey matter infarcts vs. infarcts involving additional territories ("other infarcts"). Total infarct volume was manually segmented. Baseline characteristics and proportions of good outcome (primary outcome, defined as modified Rankin Score [mRS] 0-2 at 90 days), excellent outcome (mRS 0-1) and mortality were compared between patients with and without predominantly deep grey matter infarcts. Multivariable logistic regression with adjustment for baseline variables and total infarct volume was used to determine a possible association of predominantly deep grey matter infarcts and clinical outcome.

RESULTS

Predominantly deep grey matter infarcts were seen in 316/1026 patients (30.8%). Compared to other patients, their ASPECTS was higher, collateral status and reperfusion quality were better and time to treatment was shorter. Good outcome was seen in 239/316 (75.6%) with vs. 374/704 (53.1%) without predominantly deep grey matter infarcts. After adjusting for baseline variables and total infarct volume, predominantly deep grey matter infarcts were independently associated with excellent outcome (_adjOR: 1.45 [CI₉₅: 1.04-2.02]), but not with good outcome (_adjOR: 1.24 [CI₉₅: 0.86-1.80]) or mortality (_adjOR: 0.73 [CI₉₅:0.39-1.35]) CONCLUSION: Predominantly deep grey matter infarct patterns were seen in 1/3rd of patients and were significantly associated with increased chances of excellent outcome, independent of patient baseline status and infarct size.

[A comparative study on diagnosis of silicosis by digital and high kV film-screen chest radiography]

Objective: To explore the feasibility of soft copy image of chest digital radiography (DR(SC)) in pneumoconiosis diagnosis by observing the reading effect of DR(SC) and comparing it with high kV film-screen chest radiography (FSR(HkV)) . To provide a basis for the establishment of a regional information network platform for pneumoconiosis diagnosis. Methods: A total of 119 miners who were exposed to silica dust and engaged in copper or lead-zinc mining were collected by the Third People's Hospital of Yunnan from October 2017 to August 2019. The pulmonary X-ray findings of DRSC and FSR(HkV) in each case were independently judged and diagnosed by three experienced diagnostic physicians, and the final decision was made according to the consensus of most doctors. The consistency of the two imaging methods was analyzed by observing the main small opacity shape, the overall density, the range of distribution, the aggregation of the small opacity and the big opacity, and the diagnosis stage. Results: there were 118 males and 1 female with an average age of 46.21 years. Average exposure time 7.38 years. The pulmonary X-ray findings of 113 cases with two imaging methods were mainly the round small opacity of p,q and r,but the reticular irregular opacity were not prominent, Only one case of FSR(HkV) judgment p shape and DR(SC) judgment q shape were observed, The coincidence rate was 99.12% (112/113) . huger opacity were observed in the other 6 cases. The coincidence rate was 95.51% (4/89) between pneumoconiosis-free and stageⅠ, and there was no significant difference between stageⅡand stage Ⅲ (30/30, P>0.05) . Conclusion: The x-ray findings of Silicosis with small round shadow in lung can be used by DR(SC) in diagnosis and staging.

Computed Tomography Perfusion-Based Machine Learning Model Better Predicts Follow-Up Infarction in Patients With Acute Ischemic Stroke

BACKGROUND AND PURPOSE

Prediction of infarct extent among patients with acute ischemic stroke using computed tomography perfusion is defined by predefined discrete computed tomography perfusion thresholds. Our objective is to develop a threshold-free computed tomography perfusion-based machine learning (ML) model to predict follow-up infarct in patients with acute ischemic stroke.

METHODS

Sixty-eight patients from the PRoveIT study (Measuring Collaterals With Multi-Phase CT Angiography in Patients With Ischemic Stroke) were used to derive a ML model using random forest to predict follow-up infarction voxel by voxel, and 137 patients from the HERMES study (Highly Effective Reperfusion Evaluated in Multiple Endovascular Stroke Trials) were used to test the derived ML model. Average map, T_max, cerebral blood flow, cerebral blood volume, and time variables including stroke onset-to-imaging and imaging-to-reperfusion time, were used as features to train the ML model. Spatial and volumetric agreement between the ML model predicted follow-up infarct and actual follow-up infarct were assessed. Relative cerebral blood flow <0.3 threshold using RAPID software and time-dependent T_max thresholds were compared with the ML model.

RESULTS

In the test cohort (137 patients), median follow-up infarct volume predicted by the ML model was 30.9 mL (interquartile range, 16.4-54.3 mL), compared with a median 29.6 mL (interquartile range, 11.1-70.9 mL) of actual follow-up infarct volume. The Pearson correlation coefficient between 2 measurements was 0.80 (95% CI, 0.74-0.86, P<0.001) while the volumetric difference was -3.2 mL (interquartile range, -16.7 to 6.1 mL). Volumetric difference with the ML model was smaller versus the relative cerebral blood flow <0.3 threshold and the time-dependent T_max threshold (P<0.001).

CONCLUSIONS

A ML using computed tomography perfusion data and time estimates follow-up infarction in patients with acute ischemic stroke better than current methods.

Anti-N-methyl-D-aspartate receptor (NMDAR) encephalitis is associated with IRF7, BANK1 and TBX21 polymorphisms in two populations

BACKGROUND AND PURPOSE

Autoantibodies targeting the GluN1(NR1) subunit of the anti-N-methyl-D-aspartate receptor (NMDAR) cause encephalitis. Although it has been shown that anti-NMDAR encephalitis is associated with human leukocyte antigen (HLA) loci, susceptibility genes for the disease outside the HLA loci remain unidentified. In this study, we aimed to explore the association of anti-NMDAR encephalitis with non-HLA genes.

METHODS

Two Chinese anti-NMDAR encephalitis cohorts from Han populations were recruited for this study. The North Chinese case-control set consisted of 98 patients and 460 controls, while the South Chinese case-control set included 78 patients and 541 controls. All participants were genotyped for 28 single nucleotide polymorphisms that are associated with autoimmune disorders or infectious diseases.

RESULTS

In two independent case-control sets, we identified significant associations of anti-NMDAR encephalitis with IRF7 rs1131665 (odds ratio [OR] 3.34, 95% confidence interval [CI] 1.99-5.63; P < 0.000001, P^adjusted  = 0.00004), BANK1 rs4522865 (OR 1.44, 95% CI 1.15-1.82; P = 0.0017, P^adjusted  = 0.0149), and TBX21 rs17244587 (OR 2.03, 95% CI 1.35-3.05; P = 0.00051, P^adjusted  = 0.0066). Furthermore, analysis of the three polymorphisms with clinical features of the disease revealed that the IRF7 rs1131665 was associated with tumor status.

CONCLUSION

The present study has for the first time identified non-HLA susceptibility genes for anti-NMDAR encephalitis. The association of IRF7, BANK1 and TBX21 with anti-NMDAR encephalitis suggests that B-cell activation, Th1 responses, virus infection and the type I interferon signaling pathway are involved in the pathogenesis of the disease.

Automated stroke lesion segmentation in non-contrast CT scans using dense multi-path contextual generative adversarial network

Stroke lesion volume is a key radiologic measurement in assessing prognosis of acute ischemic stroke (AIS) patients. The aim of this paper is to develop an automated segmentation method for accurately segmenting follow-up ischemic and hemorrhagic lesion from multislice non-contrast CT (NCCT) volumes of AIS patients. This paper proposes a 2D dense multi-path contextual generative adversarial network (MPC-GAN) where a dense multi-path 2D U-Net is utilized as the generator and a discriminator network is applied to regularize the generator. Contextual information (i.e. bilateral intensity difference, distance map and lesion location probability) are input into the generator and discriminator. The proposed method is validated separately on follow-up NCCT volumes of 60 patients with ischemic infarcts and NCCT volumes of 70 patients with hemorrhages. Quantitative results demonstrated that the proposed MPC-GAN method obtained a Dice coefficient (DC) of 70.6% for ischemic infarct segmentation and a DC of 76.5% for hemorrhage segmentation compared with manual segmented lesions, outperforming several benchmark methods. Additional volumetric analyses demonstrated that the MPC-GAN segmented lesion volume correlated well with manual measurements (Pearson correlation coefficients were 0.926 and 0.927 for ischemic infarcts and hemorrhages, respectively). The proposed MPC-GAN method can accurately segment ischemic infarcts and hemorrhages from NCCT volumes of AIS patients.

Targeting Toll-like receptor 4 with CLI-095 (TAK-242) enhances the antimetastatic effect of the estrogen receptor antagonist fulvestrant on non-small cell lung cancer

PURPOSE

Estrogen plays a critical role in the invasiveness and metastasis of non-small cell lung cancer (NSCLC) through estrogen receptor β (ERβ). However, the antimetastatic effect of the ERβ antagonist fulvestrant was still limited in NSCLC patients. Recently, Toll-like receptor 4 (TLR4) signaling was implicated in NSCLC metastasis. Our present study aimed to evaluate the synergistic antimetastatic effect of a combination of fulvestrant and the TLR4-specific inhibitor CLI-095 (TAK-242) on human NSCLC cells.

METHODS

The expression levels of ERβ and TLR4 were detected by immunohistochemical (IHC) analysis of 180 primary NSCLC and 30 corresponding metastatic lymph node samples. The association between ERβ and TLR4 expression was analyzed. The aggressiveness of NSCLC cells treated with fulvestrant, CLI-095 or the drug combination and formation status of their invadopodia, invasion-associated structures, were investigated. The protein levels in NSCLC cells in different groups were determined by Western blot and immunofluorescence analyses.

RESULTS

Here, a positive correlation between ERβ and TLR4 expression was observed in both primary NSCLC tissue (Spearman's Rho correlation coefficient = 0.411, p < 0.001) and metastatic lymph node tissue (Spearman's Rho correlation coefficient = 0.374, p = 0.009). The protein levels of ERβ in NSCLC cell lines were decreased by fulvestrant, and this suppressive effect was significantly enhanced when fulvestrant was combined with CLI-095 (p < 0.05). Both the migration and invasion of NSCLC cells were suppressed by fulvestrant or CLI-095 alone, and the combination of fulvestrant + CLI-095 showed the strongest inhibitory effect (p < 0.05). In addition, the results demonstrated that CLI-095 also helped fulvestrant restrict the formation and function of invadopodia in NSCLC cells (p < 0.05).

CONCLUSIONS

Collectively, our study results suggested that CLI-095 enhances the antimetastatic effect of fulvestrant on NSCLC and provided support for further investigation of the antitumor activity of combined therapy with antiestrogen and anti-TLR4 agents in the clinic.

MOTS-c improves osteoporosis by promoting the synthesis of type I collagen in osteoblasts via TGF-β/SMAD signaling pathway

OBJECTIVE

To investigate whether MOTS-c can regulate the synthesis of type I collagen in osteoblasts by regulating TGF-β/SMAD pathway, thereby improving osteoporosis.

MATERIALS AND METHODS

Viability of hFOB1.19 cells treated with MOTS-c was detected by CCK-8 assay. The mRNA and protein levels of TGF-β, SMAD7, COL1A1 and COL1A2 in hFOB1.19 cells were detected by quantitative Real-time polymerase chain reaction (qRT-PCR) and Western blot, respectively. We then changed expressions of TGF-β and SMAD7 by plasmids transfection to detect levels of COL1A1 and COL1A2 in hFOB1.19 cells by qRT-PCR and Western blot, respectively.

RESULTS

Cell viability was significantly increased after treatment of 1.0 μM MOTS-c for 24 h or 0.5 μM MOTS-c for 48 h in a time-dependent manner. The mRNA and protein expressions of TGF-β, SMAD7, COL1A1 and COL1A2 in hFOB1.19 cells were dependent on the concentration of MOTS-c. In addition, MOTS-c increased the expressions of COL1A1 and COL1A2, which were partially reversed by knockdown of TGF-β or SMAD7.

CONCLUSIONS

MOTS-c could promote osteoblasts to synthesize type I collagen via TGF-β/SMAD pathway.

Predicting soil pH changes in response to application of urea and sheep urine

Volatilization of NH₃ following urea application or livestock urine deposition can result in significant loss of N to the environment. Urea hydrolysis to NH₄ ⁺ results in an increase in pH, which in turn promotes transformation of NH₄ ⁺ to NH₃ . Accurately predicting changes in soil pH following urea (or urine) application will allow successful simulation of NH₃ volatilization. The magnitude of the pH change depends on the soil's pH buffering capacity (pHBC). However, as actual pHBC values are not generally available, pHBC proxies (e.g., cation exchange capacity) have been used in modeling studies. In a 34-d laboratory incubation study, we measured soil pH and mineral N (NH₄ ⁺ and NO₃ ^- ) following a large application of urea (800 mg N kg^-1 soil) to four soils with a range of pHBC values. In a second incubation, pH changes and mineral N dynamics were monitored in soil treated with sheep urine (773 mg N kg^-1 soil) in the absence and presence of the nitrification inhibitor dicyandiamide. In both incubations, pH changes associated with urea hydrolysis and subsequent nitrification of NH₄ ⁺ were predicted well using measured pHBC data. Our results confirmed that pHBC is base-type dependent (values greater when measured using KOH than NH₄ OH). Soil pHBC is easily measured, and the use of a measured value (determined using NH₄ OH) can improve model simulations of pH in the field and, potentially, lead to improved estimates of NH₃ loss from animal-deposited urine patches and urea-treated soil.

From Molecular Reconstruction of Mesoscopic Functional Conductive Silk Fibrous Materials to Remote Respiration Monitoring

Turning insulating silk fibroin materials into conductive ones turns out to be the essential step toward achieving active silk flexible electronics. This work aims to acquire electrically conductive biocompatible fibers of regenerated Bombyx mori silk fibroin (SF) materials based on carbon nanotubes (CNTs) templated nucleation reconstruction of silk fibroin networks. The electronical conductivity of the reconstructed mesoscopic functional fibers can be tuned by the density of the incorporated CNTs. It follows that the hybrid fibers experience an abrupt increase in conductivity when exceeding the percolation threshold of CNTs >35 wt%, which leads to the highest conductivity of 638.9 S m^-1 among organic-carbon-based hybrid fibers, and 8 times higher than the best available materials of the similar types. In addition, the silk-CNT mesoscopic hybrid materials achieve some new functionalities, i.e., humidity-responsive conductivity, which is attributed to the coupling of the humidity inducing cyclic contraction of SFs and the conductivity of CNTs. The silk-CNT materials, as a type of biocompatible electronic functional fibrous material for pressure and electric response humidity sensing, are further fabricated into a smart facial mask to implement respiration condition monitoring for remote diagnosis and medication.

Tailoring the Meso-Structure of Gold Nanoparticles in Keratin-Based Activated Carbon Toward High-Performance Flexible Sensor

Flexible biosensors with high accuracy and reliable operation in detecting pH and uric acid levels in body fluids are fabricated using well-engineered metal-doped porous carbon as electrode material. The gold nanoparticles@N-doped carbon in situ are prepared using wool keratin as both a novel carbon precursor and a stabilizer. The conducting electrode material is fabricated at 500 °C under customized parameters, which mimics A-B type (two different repeating units) polymeric material and displays excellent deprotonation performance (pH sensitivity). The obtained pH sensor exhibits high pH sensitivity of 57 mV/pH unit and insignificant relative standard deviation of 0.088%. Conversely, the composite carbon material with sp² structure prepared at 700 °C is doped with nitrogen and gold nanoparticles, which exhibits good conductivity and electrocatalytic activity for uric acid oxidation. The uric acid sensor has linear response over a range of 1-150 µM and a limit of detection 0.1 µM. These results will provide new avenues where biological material will be the best start, which can be useful to target contradictory applications through molecular engineering at mesoscale.