Characterization of AST-001 non-clinical pharmacokinetics: A novel selective AKR1C3-activated prodrug in mice, rats, and cynomolgus monkeys.

AST-001 is a chemically synthesized inactive nitrogen mustard prodrug that is selectively cleaved to a cytotoxic aziridine (AST-2660) via aldo-keto reductase family 1 member C3 (AKR1C3). The purpose of this study was to investigate the pharmacokinetics and tissue distribution of the prodrug, AST-001, and its active metabolite, AST-2660, in mice, rats, and monkeys. After single and once daily intravenous bolus doses of 1.5, 4.5, and 13.5 mg/kg AST-001 to Sprague-Dawley rats and once daily 1 h intravenous infusions of 0.5, 1.5, and 4.5 mg/kg AST-001 to cynomolgus monkeys, AST-001 exhibited dose-dependent pharmacokinetics and reached peak plasma levels at the end of the infusion. No significant accumulation and gender differences were observed after 7 days of repeated dosing. In rats, the half-life of AST-001 was dose independent and ranged from 4.89 to 5.75 h. In cynomolgus monkeys, the half-life of AST-001 was from 1.66 to 5.56 h and increased with dose. In tissue distribution studies conducted in Sprague-Dawley rats and in liver cancer PDX models in female athymic nude mice implanted with LI6643 or LI6280 HepG2-GFP tumor fragments, AST-001 was extensively distributed to selected tissues. Following a single intravenous dose, AST-001 was not excreted primarily as the prodrug, AST-001 or the metabolite AST-2660 in the urine, feces, and bile. A comprehensive analysis of the preclinical data and inter-species allometric scaling were used to estimate the pharmacokinetic parameters of AST-001 in humans and led to the recommendation of a starting dose of 5 mg/m2 in the first-in-human dose escalation study.

A national survey on current state and development needs of clinical and academic emergency medicine in China.

BACKGROUND: To characterize the current state of emergency medicine (EM) and the requirements for advancing EM clinical practice, education and research in China. METHODS: An anonymous electronic survey was conducted by Chinese Society of Emergency Medicine during September to October 2021. The survey contained 30 questions divided into 2 sections: the current state of EM development and the requirements for EM growth. RESULTS: 722 hospitals were included, of 487 were Level III and 235 were Level II hospitals. We found that after 40 years of development, EM had established a mature disciplinary system and refined sub-specialties including critical care, cardiopulmonary resuscitation, toxicology, disaster and emergency rescue. In Level III hospitals, 70.8% of EDs were standardized training centers for EM residents, but master's degree program, Doctor Degree program and post-doctoral degree program was approved in only 37.8%, 8.4% and 2.9% of EDs respectively and postgraduate curriculum was available in 1/4 of EDs. Only 8% have national or provincial key laboratories. In addition to advance clinical practice, there was also a high demand to improve teaching and research capacities, mainly focusing on literature review, research design and delivery, paper writing, residency training. CONCLUSIONS: EM has built a mature discipline system and refined sub-specialties in China. Teaching and research developed parallel with clinical practice. However, there was still a lack of EM master's and doctoral programs and research capacities need to be improved. More outstanding clinical and academic training should be provided to promote the rapid growth of EM in China.

Machine learning model for the prediction of gram-positive and gram-negative bacterial bloodstream infection based on routine laboratory parameters.

BACKGROUND: Bacterial bloodstream infection is responsible for the majority of cases of sepsis and septic shock. Early recognition of the causative pathogen is pivotal for administration of adequate empiric antibiotic therapy and for the survival of the patients. In this study, we developed a feasible machine learning (ML) model to predict gram-positive and gram-negative bacteremia based on routine laboratory parameters. METHODS: Data for 2118 patients with bacteremia were obtained from the Medical Information Mart for Intensive Care dataset. Patients were randomly split into the training set and test set by stratified sampling, and 374 routine laboratory blood test variables were retrieved. Variables with missing values in more than 40% of the patients were excluded. Pearson correlation test was employed to eliminate redundant features. Five ML algorithms were used to build the model based on the selected features. Additionally, 132 patients with bacteremia who were treated at Qilu Hospital of Shandong University were included in an independent test cohort to evaluate the model. RESULTS: After feature selection, 32 variables remained. All the five ML algorithms performed well in terms of discriminating between gram-positive and gram-negative bacteremia, but the performance of convolutional neural network (CNN) and random forest (RF) were better than other three algorithms. Consider of the interpretability of models, RF was chosen for further test (ROC-AUC = 0.768; 95%CI = 0.715-0.798, with a sensitivity of 75.20% and a specificity of 63.79%). To expand the application of the model, a decision tree (DT) was built utilizing the major variables, and it achieved an AUC of 0.679 (95%CI = 0.632-0.723), a sensitivity of 66%, and a specificity of 67.82% in the test cohort. When tested in the Qilu Hospital cohort, the ROC-AUC of the RF and DT models were 0.666 (95%CI = 0.579-0.746) and 0.615 (95%CI = 0.526-0.698), respectively. Finally, a software was developed to make the RF- and DT-based prediction models easily accessible. CONCLUSION: The present ML-based models could effectively discriminate between gram-positive and gram-negative bacteremia based on routine laboratory blood test results. This simple model would be beneficial in terms of guiding timely antibiotic selection and administration in critically ill patients with bacteremia before their pathogen test results are available.

Effectiveness of Different Telerehabilitation Strategies on Pain and Physical Function in Patients With Knee Osteoarthritis: Systematic Review and Meta-Analysis.

BACKGROUND: Knee osteoarthritis (OA) is a chronic, degenerative bone and joint disease. It can lead to major pressure to the quality of life and mental health of patients, and also brings a serious economic burden to society. However, it is difficult for patients with knee OA to access rehabilitation when discharging from the hospital. Internet-based rehabilitation is one of the promising telemedicine strategies for the improvement of knee OA, but the effect of different telerehabilitation strategies on knee OA is not clear. OBJECTIVE: The aim of this systematic review and meta-analysis was to identify telerehabilitation strategies attributing to the improvement of pain and physical function outcomes in patients with knee OA. METHODS: We reviewed and analyzed telerehabilitation strategies from randomized controlled trials (RCTs) comparing telerehabilitation with conventional treatment or usual care. For each strategy, we examined whether RCTs that applied the telerehabilitation strategy resulted in a significant improvement in pain or physical function compared with conventional treatment or usual care. RESULTS: We included 6 RCTs (n=734) incorporating 8 different telerehabilitation strategies. The duration of the interventions ranged from 1 to 48 weeks, and sample sizes ranged from 20 to 350 patients. The results showed that RCTs that provided telerehabilitation were found to be more effective than conventional treatments for improving pain (P=.003; standardized mean difference [SMD] -0.21, 95% CI -0.35 to -0.07), but not physical function (P=.24; SMD -0.09, 95% CI -0.25 to 0.06). Furthermore, this systematic review and meta-analysis indicated that there is no significant correlation between different telerehabilitation strategies and the pain and physical function of patients with knee OA. CONCLUSIONS: This systematic review and meta-analysis showed that telerehabilitation programs could relieve pain but not improve physical function for patients with knee OA. These results indicated that telerehabilitation is beneficial for the implementation of home rehabilitation exercises for patients with knee OA, thereby reducing the economic burden of health. However, there were limitations in terms of the number of search results and the number of studies that were eligible for this review and meta-analysis. Therefore, the results need to be interpreted with caution, and more high-quality studies with large samples are needed to focus on the long-term outcomes of telerehabilitation for patients with knee OA to address this limitation.

Effects of high-altitude hypoxia on embryonic developmental potential in women undergoing IVF/ICSI procedures.

PURPOSE: In this study we examined the effects of long-term adaptation to hypoxia on embryonic developmental potential of oocytes collected from women who underwent IVF/ICSI procedures. METHODS: We selected young infertile women who lived in a low-altitude normoxic environment (n = 80, altitude < 500 m) or high-altitude hypoxic environment (n = 100, altitude > 2500 m) for a lengthy period of time and who planned to undergo IVF/ICSI procedures. We then determined the baseline reproductive hormone levels, gonadotropin (Gn) dose and Gn treatment duration during controlled ovarian hyperstimulation (COH), number of oocytes retrieved, number of mature oocytes, oocyte maturation rate, fertilization rate, normal fertilization rate, day (D3) embryo-formation rate, blastocyst formation rate, good-quality formation rate, D5 blastocyst formation rate, and D6 blastocyst formation rate between the two groups. RESULTS: Compared with the low-altitude normoxic group, the various reproductive hormone markers of women in the high-altitude hypoxia group were lower, with LH and T levels significantly reduced (P < 0.05) at 72.29 and 72.44% of the normoxic group, respectively (normoxic group vs. hypoxic group, 5.24 ± 1.61 vs. 3.79 ± 1.21; 0.61 ± 0.18 vs. 0.42 ± 0.15; P < 0.05). During ovarian hyperstimulation, a greater Gn dose and longer Gn treatment duration were required for the hypoxic group to complete COH (normoxic group vs. hypoxic group, 2152.08 IU ± 52.76 vs. 2622.09 IU ± 123.28; 9.96 days ± 1.27 vs. 11.54 days ± 1.34, respectively; P < 0.05). The fertilization, cleavage, and D3 embryo-formation rates tended to be higher in the normoxic group than in the hypoxic group (P > 0.05); while the normal fertilization rate tended to lower than in the hypoxic group (P > 0.05). When we conducted an analysis of blastocyst formation rates at different timepoints, we ascertained that the blastocyst formation rate, usable blastocyst rate, and good-quality blastocyst rate of the hypoxic group were all lower than in the normoxic group, with the difference in usable blastocyst rate the most highly significant (normoxic group vs. hypoxic group, 75.31 ± 5.53 vs. 56.04 ± 6.10%, respectively; P < 0.05). In addition, the D5 and D6 blastocyst-formation rates in the normoxic group were slightly higher than in the hypoxic group, revealing that not only were fewer blastocysts formed in the hypoxic group but that there was also a delay in blastocyst formation. CONCLUSION: In young women undergoing IVF/ICSI treatment, long-term hypoxic adaptation required augmented Gn dose and Gn treatment duration during COH, and blastocyst developmental potential was also attenuated.

Influence of Differences in the Density of Seawater on the Measurement of the Underwater Gravity Gradient.

In preparing gravity gradient reference maps for navigation purposes, researchers have tended to use a constant value for the density of seawater. However, the actual seawater density at a particular location may vary due to the effects of longitude, latitude and bathymetry. In this study, the right rectangular prism method was used to calculate the disturbing gravity gradient caused by the mass deficiency of seawater for three different seawater profiles in an area east of Taiwan. For this purpose, two seawater density models were used as alternatives to the constant seawater density model, and the alteration in the gravity gradient was calculated to quantify the error in the gravity gradient as a result of using a constant seawater density. The results demonstrated that the error in the gravity gradient can reach 1E for water at large depths. Moreover, the difference between the amplitude of the error of the corrected thermocline and that for the uncorrected seawater density model was found to be quite small. If a gravity gradient reference map with accuracy better than 1E is to be realized, the seawater density cannot be taken as constant during forward modeling.

Constituents from Chloranthus multistachys and their cytotoxic activities against various human cancer cell lines.

Two new furanoeremophilane sesquiterpenoids, namely, 6,9-dioxo-1α,4α-dihydroxy-furanoeremophilane (1) and 4α,5α-epoxy-6,9-dioxo-1α-hydroxyl-furanoeremophilane (2), and 10 known compounds were isolated from the whole plant of Chloranthus multistachys, and compound 3 was converted to derivative 3a. Their structures were determined based on extensive spectroscopic analysis. All compounds were evaluated by using five cancer cell lines: PC3, LNcap, A549, K562, and HEL. The derivative 3a exhibited excellent cytotoxic activities, with the IC50 against HEL cells being the lowest at 1.322 ± 0.08 µM, which was comparable to that of the positive control (doxorubicin). Mechanism studies showed that the anticancer activity of 3a may be associated with cell cycle regulation.

Treatment of multidrug-resistant Klebsiella pneumoniae pneumonia in rats with the Wen Run Fei Ning formula: A preliminary study.

BACKGROUND & OBJECTIVES: To determine the effect of Wen Run Fei Ning formula (WRFNF) intervention in class I integron-mediated carbapenem-resistant Klebsiella pneumoniae. METHODS: A drug-susceptibility test and PCR amplification were used to screen for carbapenem-resistant K. pneumoniae containing class I integrons. Following nasal drip and tail vein injection to infect healthy male rats with carbapenem-resistant K. pneumoniae, three models were created: control (group A); model (group B, tail vein injection); and model-WRFNF treatment group (group C, by tail vein injection). Rats in Group C were gavaged with pre-warmed WRFNF extract. On the third, fifth, and seventh days after the experiment, the rats in groups A and B were gavaged with an equal quantity of saline and killed in batches. RESULTS: Group C showed considerably higher serum IL-6 and TNF- levels on days 3, 5, and 7 compared to group A, as well as a significant increase in peripheral blood leukocyte count and a histopathologic inflammatory cell infiltration of the lungs. As the WRFNF delivery duration was prolonged, group C's histopathologic inflammatory cell infiltration gradually improved in contrast to group B, with the biggest improvement occurring on day 7. Compared to group B, group C's serum IL-6 and TNF- levels were lower. When the trial's duration was increased to 7 days, the levels of IL-6 and TNF- in group C decreased on day 7 compared to on day 5. INTERPRETATION & CONCLUSION: WRFNF decreased inflammatory cell infiltration as well as IL-6 and TNF expression in the lung of the rats infected with carbapenem-resistant K. pneumoniae.

Impact of percutaneous coronary intervention on renal function in patients with coronary heart disease.

The relationship between cardiac and renal function is complicated. The impact of percutaneous coronary intervention (PCI) on renal function in patients with coronary artery disease is still unclear. The current study sought to assess renal function change, including the time course of renal function, after elective PCI in patients with improved renal function and to identify renal function predictors of major adverse cardiovascular events. We examined data from 1572 CHD patients who had coronary angiography (CAG) or PCI in this retrospective cohort study. Patients receiving elective PCI (n=1240) and CAG (n=332) between January 2013 and December 2018 were included. Pre-PCI and procedural variables associated with post-PCI eGFR, change in renal function after post-PCI follow-up, and post-PCI eGFR association with major adverse cardiovascular events were investigated. Following the procedure, 88.7 percent of PCI group patients had unchanged or improved renal function. The treatment of PCI was found to independently correlate with IRF following coronary angiography in an analysis of patients undergoing PCI [OR 4.561 (95% CI:2 .556-8.139); p<0.001]. The area under the receiver operating characteristic (ROC) curve is 0.763 (model with the treatment of PCI). Improved renal function (IRF) and stable renal function were both associated with a lower risk of a major cardiovascular event.

A hierarchical opportunistic screening model for osteoporosis using machine learning applied to clinical data and CT images.

BACKGROUND: Osteoporosis is a common metabolic skeletal disease and usually lacks obvious symptoms. Many individuals are not diagnosed until osteoporotic fractures occur. Bone mineral density (BMD) measured by dual-energy X-ray absorptiometry (DXA) is the gold standard for osteoporosis detection. However, only a limited percentage of people with osteoporosis risks undergo the DXA test. As a result, it is vital to develop methods to identify individuals at-risk based on methods other than DXA. RESULTS: We proposed a hierarchical model with three layers to detect osteoporosis using clinical data (including demographic characteristics and routine laboratory tests data) and CT images covering lumbar vertebral bodies rather than DXA data via machine learning. 2210 individuals over age 40 were collected retrospectively, among which 246 individuals' clinical data and CT images are both available. Irrelevant and redundant features were removed via statistical analysis. Consequently, 28 features, including 16 clinical data and 12 texture features demonstrated statistically significant differences (p < 0.05) between osteoporosis and normal groups. Six machine learning algorithms including logistic regression (LR), support vector machine with radial-basis function kernel, artificial neural network, random forests, eXtreme Gradient Boosting and Stacking that combined the above five classifiers were employed as classifiers to assess the performances of the model. Furthermore, to diminish the influence of data partitioning, the dataset was randomly split into training and test set with stratified sampling repeated five times. The results demonstrated that the hierarchical model based on LR showed better performances with an area under the receiver operating characteristic curve of 0.818, 0.838, and 0.962 for three layers, respectively in distinguishing individuals with osteoporosis and normal BMD. CONCLUSIONS: The proposed model showed great potential in opportunistic screening for osteoporosis without additional expense. It is hoped that this model could serve to detect osteoporosis as early as possible and thereby prevent serious complications of osteoporosis, such as osteoporosis fractures.

Sirt6 regulates autophagy in AGE-treated endothelial cells via KLF4.

BACKGROUND AND AIMS: High glucose and its byproducts are important factors causing dysfunction of endothelial cells. Autophagy is critical for endothelial cellular homeostasis. However, the specific molecular mechanism of how autophagy is regulated in endothelial cells under high-glucose condition remains unknown. We aim to explore the role Sirt6 plays in regulating autophagy in AGE-treated endothelial cells and how this function is exerted via KLF4. METHODS AND RESULTS: Our results indicate that autophagy level increased in AGE-treated endothelial cells alongside with higher Sirt6 and KLF4 expression level. What's more, knock-in of Sirt6 by adenovirus led to augmented autophagy level while knockdown of Sirt6 led to the opposite. We also verified that Sirt6 affected KLF4 expression positively but KLF4 didn't influence Sirt6 expression level while knocking out of KLF4 impaired Sirt6-enhanced autophagy. Finally we found that STZ-induced diabetic mice showed more autophagosomes in endothelium and Sirt6 knockdown by adeno-associated virus reduced the number of autophagosomes. Knockdown of Sirt6 also caused impaired endothelium integrity but echocardiography indicated there were no significant functional differences. CONCLUSION: Our research reveals more about how Sirt6 regulates autophagy in endothelial cells under high-glucose simulated condition and provides further insight into the relationships between Sirt6 and KLF4.

Aspiration versus Stent Retriever Thrombectomy in Posterior Circulation Stroke: A Systematic Review and Meta-Analysis.

INTRODUCTION: The management of posterior circulation stroke is primarily carried out by endovascular approaches including aspiration or stent retrevier thrombectomy. Existing reviews have attempted to comparatively evaluate their efficacy in terms of morbidity and mortality-related outcomes, however, with several limitations. Therefore, in this review, we attempt to address the gap in the existing literature by evaluating the comparative impact of stent retriever-based and aspiration-based thrombectomy interventions in posterior circulation stroke patients on the following parameters: overall procedure duration, recanalization time, rescue therapy usage, complication risk, and mortality risk. METHODS: A systematic search of the academic literature was performed according to PRISMA guidelines across five databases. We conducted a random-effect meta-analysis to evaluate comparative outcomes, including procedural duration, time to recanalization, risk of complications, use of rescue therapy, and risk of mortality in patients with posterior circulation stroke undergoing stent retriever- and aspiration-based thrombectomies. We also performed comparative subgroup analyses to evaluate differences in outcomes between contact and manual aspiration interventions. RESULTS: From 963 studies, we found nine eligible studies containing data on 840 patients. Meta-analysis revealed a large-to-medium size positive effect for stent retriever-based thrombectomy on overall procedure duration and recanalization compared to aspiration-based thrombectomy. Additional analysis revealed higher risk of complications and mortality in posterior circulation stroke patients undergoing stent retriever-based thrombectomy as compared to aspiration-based thrombectomy. We also observed that the use of rescue therapy was elevated in patients undergoing aspiration-based thrombectomy compared to stent retriever-based thrombectomy. CONCLUSION: This study provides preliminary evidence for improved morbidity and mortality outcomes in posterior circulation stroke patients undergoing aspiration-based thrombectomies as compared to stent retriever-based thrombectomy. The study also provides evidence for improved endovascular outcomes for patients undergoing aspiration-based thrombectomies. The findings from this study can have implications in developing awareness among neurosurgeons for stratifying patients to manage posterior circulation stroke according to the risks associated with aspiration and stent retriever-based thrombectomies.

Influence of Sea Level Anomaly on Underwater Gravity Gradient Measurements.

Considering the theoretical research needs of gravity gradient detection and navigation, this study uses the right rectangular prism method to calculate the disturbing gravity gradient from sea level anomalies in the range of 5° × 5° in the Kuroshio extension area of the western Pacific with large sea level anomalies. The disturbing gravity gradient is obtained in different directions within a depth of 50 m below the mean sea level based on the principle of the disturbing gravity gradient. The calculation results show that the sea level anomalies at local positions significantly impact the underwater gravity gradient measurements, with the maximum contribution exceeding 10 E and the maximum difference between different locations exceeding 20 E. The change of the sea level anomaly over time also significantly impacts the measurement of the underwater gravity gradient, with the maximum change value exceeding 20 E. The impact will have a corresponding change with the seasonal change of the sea level anomaly. Therefore, the underwater carrier needs to consider the disturbing gravity gradient caused by sea level anomalies when using the gravity gradient for underwater detection and navigation.

Classification of Gravity Matching Areas Using PSO-BP Neural Networks based on PCA and Satellite Altimetry Data over the Western Pacific.

For inertial navigation systems (INS), as one of the major methods for underwater navigation, errors diverge over time. With the development of geophysical navigation technology, gravity navigation has become an effective method of navigation. Significant changes in the gravity characteristic of the matching region ensure that gravity matching navigation works effectively. In this paper, we combine artificial intelligence algorithms and statistical metrics to classify gravity-matching navigation regions. Firstly, this paper analyzes and extracts gravity anomaly data from a matching region in different ways. Then, a particle swarm optimization (PSO) algorithm is used to optimize the network weights of a back propagation (BP) NN. Finally, based on principal component analysis (PCA) theory and PSO-BP NN, this paper proposes the PPBA method to classify the matching area. Moreover, the Terrain Contour Matching (TERCOM) matching algorithm and gravity anomaly data from the Western Pacific are used to verify the classification performance of the PPBA method. The experiments prove that the PPBA method has a high classification accuracy, and the classification results are consistent with the matching navigation experimental results. This work can provide a reference for designing navigation regions and navigation routes for submarines.

A method to mitigate spatio-temporally varying task-correlated motion artifacts from overt-speech fMRI paradigms in aphasia.

Quantifying accurate functional magnetic resonance imaging (fMRI) activation maps can be dampened by spatio-temporally varying task-correlated motion (TCM) artifacts in certain task paradigms (e.g., overt speech). Such real-world tasks are relevant to characterize longitudinal brain reorganization poststroke, and removal of TCM artifacts is vital for improved clinical interpretation and translation. In this study, we developed a novel independent component analysis (ICA)-based approach to denoise spatio-temporally varying TCM artifacts in 14 persons with aphasia who participated in an overt language fMRI paradigm. We compared the new methodology with other existing approaches such as "standard" volume registration, nonselective motion correction ICA packages (i.e., AROMA), and combining the novel approach with AROMA. Results show that the proposed methodology outperforms other approaches in removing TCM-related false positive activity (i.e., improved detectability power) with high spatial specificity. The proposed method was also effective in maintaining a balance between removal of TCM-related trial-by-trial variability and signal retention. Finally, we show that the TCM artifact is related to clinical metrics, such as speech fluency and aphasia severity, and the implication of TCM denoising on such relationship is also discussed. Overall, our work suggests that routine bulkhead motion based denoising packages cannot effectively account for spatio-temporally varying TCM. Further, the proposed TCM denoising approach requires a one-time front-end effort to hand label and train the classifiers that can be cost-effectively utilized to denoise large clinical data sets.

Gradient Architecture-Enabled Capacitive Tactile Sensor with High Sensitivity and Ultrabroad Linearity Range.

The sensitivity and linearity are critical parameters that can preserve the high pressure-resolution across a wide range and simplify the signal processing process of flexible tactile sensors. Although extensive micro-structured dielectrics have been explored to improve the sensitivity of capacitive sensors, the attenuation of sensitivity with increasing pressure is yet to be fully resolved. Herein, a novel dielectric layer based on the gradient micro-dome architecture (GDA) is presented to simultaneously realize the high sensitivity and ultrabroad linearity range of capacitive sensors. The gradient micro-dome pixels with rationally collocated amount and height can effectively regulate the contact area and hence enable the linear variation in effective dielectric constant of the GDA dielectric layer under varying pressures. With systematical optimization, the sensor exhibits the high sensitivity of 0.065 kPa-1 in an ultrabroad linearity range up to 1700 kPa, which is first reported. Based on the excellent sensitivity and linearity, the high pressure-resolution can be preserved across the full scale of pressure spectrum. Therefore, potential applications such as all-round physiological signal detection in diverse scenarios, control instruction transmission with combinatorial force inputs, and convenient Morse code communication with non-overlapping capacitance signals are successfully demonstrated through a single sensor device.

Magnon-mediated nonreciprocal microwave transmission based on quantum interference.

Nonreciprocity has always been a subject of interest and plays a key role in a variety of applications like signal processing and noise isolation. In this work, we propose a simple and feasible scheme to implement nonreciprocal microwave transmission in a high-quality-factor superconducting cavity with ferrimagnetic materials. We derive necessary requirements to create nonreciprocity in our system where a magnon mode and two microwave modes are coupled to each other, highlighting the adjustability of a static magnetic field controlled nonreciprocal transmission based on quantum interference between different transmission paths, which breaks time-reversal symmetry of the three-mode cavity magnonics system. The high light isolation adjusted within a range of different magnetic fields can be obtained by modulating the photon-magnon coupling strength. Due to the simplicity of the device and the system tunability, our results may facilitate potential applications for light magnetic sensing and coherent information processing.

Spectral Wavelet-feature Analysis and Classification Assisted Denoising for enhancing magnetic resonance spectroscopy.

Magnetic resonance spectroscopy (MRS) is capable of revealing important biochemical and metabolic information of tissues noninvasively. However, the low concentrations of metabolites often lead to poor signal-to-noise ratio (SNR) and a long acquisition time. Therefore, the applications of MRS in detection and quantitative measurements of metabolites in vivo remain limited. Reducing or even eliminating noise can improve SNR sufficiently to obtain high quality spectra in addition to increasing the number of signal averaging (NSA) or the field strength, both of which are limited in clinical applications. We present a Spectral Wavelet-feature ANalysis and Classification Assisted Denoising (SWANCAD) approach to differentiate signal and noise peaks in magnetic resonance spectra based on their respective wavelet features, followed by removing the identified noise components to improve SNR. The performance of this new denoising approach was evaluated by measuring and comparing SNRs and quantified metabolite levels of low NSA spectra (e.g. NSA = 8) before and after denoising using the SWANCAD approach or by conventional spectral fitting and denoising methods, such as LCModel and wavelet threshold methods, as well as the high NSA spectra (e.g. NSA = 192) recorded in the same sampling volumes. The results demonstrated that SWANCAD offers a more effective way to detect the signals and improve SNR by removing noise from the noisy spectra collected with low NSA or in the subminute scan time (e.g. NSA = 8 or 16 s). The potential applications of SWANCAD include using low NSA to accelerate MRS acquisition while maintaining adequate spectroscopic information for detection and quantification of the metabolites of interest when a limited time is available for an MRS examination in the clinical setting.

Type of Necrosis Influences Prognosis in Hepatocellular Carcinoma After the First Transarterial Chemoembolization.

BACKGROUND Hepatocellular carcinoma (HCC) is one of the most common tumors. Transarterial chemoembolization (TACE) is the first choice of treatment for intermediate HCC and an important treatment option for advanced HCC. This retrospective study compared the prognosis between patients showing coagulative necrosis and patients showing liquefactive necrosis after the first TACE procedure. MATERIAL AND METHODS We divided 171 patients with Barcelona Clinic Liver Cancer (BCLC) Stage B or C HCC into 2 groups; a coagulative necrosis group (79 patients) and a liquefactive necrosis group (92 patients). The coagulative and liquefactive necroses were identified by computed tomography after the first TACE procedure. Kaplan-Meier analysis was used to identify the differences in the overall survival (OS) and progression-free survival (PFS) between the 2 groups, and the associated risk factors and safety of TACE were analyzed. RESULTS The median OS durations were 23.27±1.40 months and 8.83±2.15 months (P=0.004) and the median PFS durations were 9.33±0.96 months and 3.70±0.44 months (P=0.002) in the coagulative necrosis and liquefactive necrosis groups, respectively. Intrahepatic in situ progression, new intrahepatic metastasis, and extrahepatic progression occurred significantly earlier in the liquefactive necrosis group (P<0.05). Univariate analysis and multivariate analyses showed liquefactive necrosis was the main risk factor for OS. There was no significant difference in the hepatic function impairment or post-embolism syndrome after TACE. CONCLUSIONS After the first TACE procedure, the patients with liquefactive necrosis experienced recurrence and metastasis earlier and had a worse prognosis. Therefore, these patients should be considered for earlier administration of targeted therapies or immunotherapies after TACE.

An Intelligence Method for Recognizing Multiple Defects in Rail.

Ultrasonic guided waves are sensitive to many different types of defects and have been studied for defect recognition in rail. However, most fault recognition algorithms need to extract features from the time domain, frequency domain, or time-frequency domain based on experience or professional knowledge. This paper proposes a new method for identifying many different types of rail defects. The segment principal components analysis (S-PCA) is developed to extract characteristics from signals collected by sensors located at different positions. Then, the Support Vector Machine (SVM) model is used to identify different defects depending on the features extracted. Combining simulations and experiments of the rails with different kinds of defects are established to verify the effectiveness of the proposed defect identification techniques, such as crack, corrosion, and transverse crack under the shelling. There are nine channels of the excitation-reception to acquire guided wave detection signals. The results show that the defect classification accuracy rates are 96.29% and 96.15% for combining multiple signals, such as the method of single-point excitation and multi-point reception, or the method of multi-point excitation and reception at a single point.