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.

Segmenting Ischemic Penumbra and Infarct Core Simultaneously on Non-Contrast CT of Patients with Acute Ischemic Stroke Using Novel Convolutional Neural Network.

Differentiating between a salvageable Ischemic Penumbra (IP) and an irreversibly damaged Infarct Core (IC) is important for therapy decision making for acute ischemic stroke (AIS) patients. Existing methods rely on Computed Tomography Perfusion (CTP) or Diffusion-Weighted Imaging-Fluid Attenuated Inversion Recovery (DWI-FLAIR). We designed a novel Convolutional Neural Network named I2PC-Net, which relies solely on Non-Contrast Computed Tomography (NCCT) for the automatic and simultaneous segmentation of the IP and IC. In the encoder, Multi-Scale Convolution (MSC) blocks were proposed to capture effective features of ischemic lesions, and in the deep levels of the encoder, Symmetry Enhancement (SE) blocks were also designed to enhance anatomical symmetries. In the attention-based decoder, hierarchical deep supervision was introduced to address the challenge of differentiating between the IP and IC. We collected 197 NCCT scans from AIS patients to evaluate the proposed method. On the test set, I2PC-Net achieved Dice Similarity Scores of 42.76 ± 21.84%, 33.54 ± 24.13% and 65.67 ± 12.30% and lesion volume correlation coefficients of 0.95 (p < 0.001), 0.61 (p < 0.001) and 0.93 (p < 0.001) for the IP, IC and IP + IC, respectively. The results indicated that NCCT could potentially be used as a surrogate technique of CTP for the quantitative evaluation of the IP and IC.

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.

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.

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.

Harmonizing international quality standards for Andrographis paniculata: A comparative analysis of content determination methods across pharmacopeias.

The quality standards for Andrographis paniculata, a widely used medicinal herb, exhibited significant variations across different pharmacopeias. In this study, we compared the HPLC content determination methods and total lactone content of A. paniculata samples from different regions, as specified in the Chinese (CP), United States (USP), European (EP), Thai (TP), and Indian pharmacopeias (IP), as well as the Hong Kong Chinese Materia Medica Standards (HK). We aimed to assess the differences and similarities among these pharmacopeias and harmonized international quality standards for A. paniculata. The analysis revealed variations in sample preparation, liquid chromatographic conditions, fingerprint profiles, and total lactone content among the different pharmacopeias. Specifically, the CP and HK methods exhibited superior sample preparation and chromatographic separation. Further comparing the content of 20 A. paniculata samples with the CP, USP, EP and HK methods showed consistent determinations for the same components, indicating similar detection capabilities. The discrepancies in total lactone content primarily stemmed from differences in the number and types of detected compounds. Moreover, the acceptance criteria exhibited a stringency in the order CP > HK > EP > USP. In conclusion, this comparison analysis of content determination in CP, USP, HK, EP, TP and IP provided a scientific foundation for the international standardization and trade regulations of A. paniculata. It also served as a valuable reference for the development of international quality standards for other medicinal herbs, facilitating the harmonization of global pharmaceutical standards.

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.

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.

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.

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.

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.

Automated Collateral Scoring on CT Angiography of Patients with Acute Ischemic Stroke Using Hybrid CNN and Transformer Network.

Collateral scoring plays an important role in diagnosis and treatment decisions of acute ischemic stroke (AIS). Most existing automated methods rely on vessel prominence and amount after vessel segmentation. The purpose of this study was to design a vessel-segmentation free method for automating collateral scoring on CT angiography (CTA). We first processed the original CTA via maximum intensity projection (MIP) and middle cerebral artery (MCA) region segmentation. The obtained MIP images were fed into our proposed hybrid CNN and Transformer model (MPViT) to automatically determine the collateral scores. We collected 154 CTA scans of patients with AIS for evaluation using five-folder cross validation. Results show that the proposed MPViT achieved an intraclass correlation coefficient of 0.767 (95% CI: 0.68-0.83) and a Kappa of 0.6184 (95% CI: 0.4954-0.7414) for three-point collateral score classification. For dichotomized classification (good vs. non-good and poor vs. non-poor), it also achieved great performance.

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 â„ƒ. 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.

Targeted Perioperative Nursing Combined with Propofol and Fentanyl for Gynecological Laparoscopic Surgery.

Objective: The aim of this study is to investigate the clinical effects of targeted perioperative nursing combined with propofol and fentanyl in gynecological laparoscopic surgery. Methods: Patients who were admitted to our hospital for gynecological laparoscopic surgeries from October 1, 2019 to November 30, 2021 were included in this retrospective study. Patients in group A received routine propofol and fentanyl. Patients in group B received targeted perioperative nursing on the basis of interventions in group A. The anesthetic effects, clinical indicators, mental health status, and adverse reactions were compared between the two groups. Results: A total of 84 qualified patients were retrieved. The total effective anesthesia rate, extubation time, operation time, consciousness recovery time, intraoperative blood loss, hospital stay, SAS score, SDS score, health status indicators, and adverse events in group B were all significantly better than those in group A (P < 0.05 for all comparisons). Conclusion: Combined intervention (propofol + fentanyl + targeted perioperative care) for gynecological laparoscopic surgery patients has a significant anesthesia effect, which can effectively improve the patient's clinical indicators and mental health status and can also reduce the occurrence of adverse events. It has good safety and can be widely used in clinical practice.

Acacetin Prevents Bone Loss by Disrupting Osteoclast Formation and Promoting Type H Vessel Formation in Ovariectomy-Induced Osteoporosis.

Osteoporosis, characterized by the destruction of bone resorption and bone formation, is a serious disease that endangers human health. Osteoporosis prevention and treatment has become one of the important research contents in the field of medicine. Acacetin, a natural flavonoid compound, could promote osteoblast differentiation, and inhibit osteoclast formation in vitro. However, the mechanisms of acacetin on osteoclast differentiation and type H vessel formation, as well as the effect of preventing bone loss, remain unclear. Here, we firstly used primary bone marrow derived macrophages (BMMs), endothelial progenitor cells (EPCs), and ovariectomized (OVX) mice to explore the function of acacetin on bone remodeling and H type vessel formation. In this study, we found that acacetin inhibits osteoclast formation and bone resorption of BMMs induced by the macrophage colony stimulating factor (M-CSF) and receptor activator of nuclear factor-κB ligand (RANKL) in a concentration of 20 µM without exerting cytotoxic effects. It was accompanied by downregulation of osteoclast differentiation marker genes (Ctsk, Acp5, and Mmp9) and cell fusion genes (CD9, CD47, Atp6v0d2, Dc-stamp, and Oc-stamp). Moreover, acacetin disrupted actin ring formation and extracellular acidification in osteoclasts. Mechanistic analysis revealed that acacetin not only inhibits the expression of the major transcription factor NFATc1 and NF-κB during RANKL-induced osteoclast formation, but also suppresses RANKL-induced the phosphorylation of Akt, GSK3ß, IκBα, and p65. Additionally, acacetin enhanced the ability of M-CSF and RANKL-stimulated BMMs to promote angiogenesis and migration of EPCs. We further established that, in vivo, acacetin increased trabecular bone mass, decreased the number of osteoclasts, and showed more type H vessels in OVX mice. These data demonstrate that acacetin prevents OVX-induced bone loss in mice through inhibition of osteoclast function and promotion of type H vessel formation via Akt/GSK3ß and NF-κB signalling pathway, suggesting that acacetin may be a novel therapeutic agent for the treatment of osteoporosis.

Validation of a machine learning software tool for automated large vessel occlusion detection in patients with suspected acute stroke.

PURPOSE: CT angiography (CTA) is the imaging standard for large vessel occlusion (LVO) detection in patients with acute ischemic stroke. StrokeSENS LVO is an automated tool that utilizes a machine learning algorithm to identify anterior large vessel occlusions (LVO) on CTA. The aim of this study was to test the algorithm's performance in LVO detection in an independent dataset. METHODS: A total of 400 studies (217 LVO, 183 other/no occlusion) read by expert consensus were used for retrospective analysis. The LVO was defined as intracranial internal carotid artery (ICA) occlusion and M1 middle cerebral artery (MCA) occlusion. Software performance in detecting anterior LVO was evaluated using receiver operator characteristics (ROC) analysis, reporting area under the curve (AUC), sensitivity, and specificity. Subgroup analyses were performed to evaluate if performance in detecting LVO differed by subgroups, namely M1 MCA and ICA occlusion sites, and in data stratified by patient age, sex, and CTA acquisition characteristics (slice thickness, kilovoltage tube peak, and scanner manufacturer). RESULTS: AUC, sensitivity, and specificity overall were as follows: 0.939, 0.894, and 0.874, respectively, in the full cohort; 0.927, 0.857, and 0.874, respectively, in the ICA occlusion cohort; 0.945, 0.914, and 0.874, respectively, in the M1 MCA occlusion cohort. Performance did not differ significantly by patient age, sex, or CTA acquisition characteristics. CONCLUSION: The StrokeSENS LVO machine learning algorithm detects anterior LVO with high accuracy from a range of scans in a large dataset.

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.