Ether-Water Co-Solvent Electrolytes Enhanced Vanadium Oxide Cathode Cyclic Behaviors for Zinc Batteries.

Vanadium-based compounds are fantastic cathodes for aqueous zinc metal batteries due to the high specific capacity and excellent rate capability. Nevertheless, the practical application has been hampered by the dissolution of vanadium in traditional aqueous electrolytes owing to the strong polarity of water molecules. Herein, we propose a hybrid electrolyte made of Zn(ClO4)2 salt in tetraethylene glycol dimethyl ether (G4) and H2O solvents to upgrade the cycle life of Zn//K0.486V2O5 battery. The G4 jointly solvates with Zn2+ ions and replaces a portion of the H2O molecules in the Zn2+ solvation sheath. It forms a strong bond with H2O, reducing its activity, and significantly inhibiting vanadium dissolution and water-induced parasitic reaction. Consequently, the optimized electrolyte with H2O and G4 volume ratio of 5:5 enhances the cycling stability of Zn//K0.486V2O5 battery, enabling it to reach up to 600 cycles. In addition, the battery demonstrates a satisfactory reversible capacity of 475.7 mAh g-1 and excellent rate performance attributed to the moderate ionic conductivity (28.8 mS cm-1) of the hybrid electrolyte. Last but not least, in the optimized electrolyte, the symmetric Zn//Zn cells deliver a long cycling performance of 400 h, while the asymmetric Zn//Cu cells shows a high average coulombic efficiency of 97.4%.

Analysis of widely targeted metabolites of quinoa sprouts (Chenopodium quinoa Willd.) under saline-alkali stress provides new insights into nutritional value.

Quinoa sprouts are a green vegetable rich in bioactive chemicals, which have multiple health benefits. However, there is limited information on the overall metabolic profiles of quinoa sprouts and the metabolite changes caused by saline-alkali stress. Here, a UHPLC-MS/MS-based widely targeted metabolomics technique was performed to comprehensively evaluate the metabolic profiles of quinoa sprouts and characterize its metabolic response to saline-alkali stress. A total of 930 metabolites were identified of which 232 showed significant response to saline-alkali stress. The contents of lipids and amino acids were significantly increased, while the contents of flavonoids and phenolic acids were significantly reduced under saline-alkali stress. Moreover, the antioxidant activities of quinoa sprouts were significantly affected by saline-alkali stress. The enrichment analysis of the differentially accumulated metabolites revealed that flavonoid, amino acid and carbohydrate biosynthesis/metabolism pathways responded to saline-alkali stress. This study provided an important theoretical basis for evaluating the nutritional value of quinoa sprouts and the changes in metabolites in response to saline-alkali stress.

Metabolomic insights into the browning inhibition of fresh-cut apple by hydrogen sulfide.

Hydrogen sulfide (H2S) is known to effectively inhibit the browning of fresh-cut apples, but the mechanism at a metabolic level remains unclear. Herein, non-targeted metabolomics was used to analyze metabolic changes in surface and internal tissues of fresh-cut apple after H2S treatment. The results showed that prenol lipids were the most up-accumulated differential metabolites in both surface and inner tissue of fresh-cut apple during browning process, which significantly down-accumulated by H2S treatment. H2S treatment reduced the consumption of amino acid in surface tissue. Regarding inner tissue, H2S activated defense response through accumulation of lysophospholipid signaling and induced the biosynthesis of phenolic compounds. We therefore propose that H2S inhibited the surface browning of fresh-cut apple by reducing the accumulation of prenol lipids, directly delaying amino acid consumption in surface tissue and indirectly regulating defense response in inner tissue, which provides fundamental insights into browning inhibition mechanisms by H2S.

High-efficiency recovery of valuable metals from spent lithium-ion batteries: Optimization of SO2 pressure leaching and selective extraction of trace impurities.

The recovery of valuable metals from spent lithium-ion batteries (LIBs) is crucial for environmental protection and resource optimization. In the traditional recovery process of spent LIBs, the leaching of high-valence metals has the problems of high cost and limited reagent utilization, and some valuable metals are lost in the subsequent purification process of the leaching solution. To reduce the cost of reagents, this study proposes the use of low-cost SO2 as a reagent combined with pressure leaching to efficiently recover high-valence metals from delithiated materials of spent LIBs, while selective solvent extraction is used to remove trace impurities in the leaching solution to avoid the loss of valuable metals. Experimental results demonstrated that by optimizing the conditions to 0.25 MPa SO2 partial pressure and 60 min reaction time at 70 °C, the leaching efficiencies for Ni, Co, and Mn reached 99.6%, 99.3%, and 99.6%, respectively. The kinetic study indicated that the leaching process was diffusion-controlled. Furthermore, the delithiated materials were used to completely utilize the residual SO2 in the solution to obtain a high concentration Ni-Co-Mn rich solution. Subsequently, Fe and Al impurities were deeply removed through a synergistic extraction of Di-2-ethylhexyl phosphoric acid (D2EHPA) and tributyl phosphate (TBP) without loss of valuable metals, achieving a high-purity Ni-Co-Mn solution. The process developed based on this work has the characteristics of environmental friendliness, high valuable metal recovery, and high product purity, providing a reference technical method for the synergistic treatment of waste SO2 flue gas with spent LIBs and the deep purification of impurities in spent LIBs.

Activation of persulfate by g-C3N4/nZVI@SBC for degradation of total petroleum hydrocarbon in groundwater.

In this study, we synthesized a high removal efficiency catalyst using biochar-supported nanoscale zero-valent iron and g-C3N4, denoted as g-C3N4/nZVI@SBC, to activate persulfate (PS) for the degradation of total petroleum hydrocarbon (TPH) in groundwater. We characterized the morphology and physiochemical properties of g-C3N4/nZVI@SBC with scanning electron microscopy (SEM), X-ray diffraction (XRD), Fourier transform infrared (FTIR), BET surface area analysis, and X-ray photoelectron spectroscopy (XPS). To assess the performance of the g-C3N4/nZVI@SBC catalyst, we investigated various reaction parameters, such as the mass ratio of g-C3N4 to nZVI@SBC, PS concentration, initial pH, initial TPH concentration, and the presence of coexisting ions in the system. The results from batch experiments and repeated use trials indicate that g-C3N4/nZVI@SBC exhibited both excellent catalytic activation capability and impressive durability, making it a promising choice for TPH degradation. Specifically, when the PS concentration reached 1 mM, the catalyst dosage was 0.3 g/L, and the g-C3N4 to nZVI@SBC mass ratio was 2, we achieved a remarkable TPH removal efficiency of 93.8%. Through electron paramagnetic resonance (EPR) testing and quenching experiments, we identified sulfate radicals, hydroxyl radicals, and superoxide radicals as the primary active substance involved in the TPH degradation process. Moreover, the g-C3N4/nZVI@SBC composite proved highly effective for in-situ TPH removal from groundwater and displayed an 86% removal rate, making it a valuable candidate for applications in permeable reactive barriers (PRB) aimed at enhancing environmental remediation. In summary, by skillfully utilizing g-C3N4/nZVI@SBC, this study has made notable advancements in synthesis and characterization, presenting a feasible and innovative approach to addressing TPH pollution in groundwater.

Causal relationship between gut microbiota and polycystic ovary syndrome: a literature review and Mendelian randomization study.

Introduction: Numerous studies have suggested an association between gut microbiota and polycystic ovarian syndrome (PCOS). However, the causal relationship between these two factors remains unclear. Methods: A review of observational studies was conducted to compare changes in gut microbiota between PCOS patients and controls. The analysis focused on four levels of classification, namely, phylum, family, genus, and species/genus subgroups. To further investigate the causal relationship, Mendelian randomization (MR) was employed using genome-wide association study (GWAS) data on gut microbiota from the MiBioGen consortium, as well as GWAS data from a large meta-analysis of PCOS. Additionally, a reverse MR was performed, and the results were verified through sensitivity analyses. Results: The present review included 18 observational studies that met the inclusion and exclusion criteria. The abundance of 64 gut microbiota taxa significantly differed between PCOS patients and controls. Using the MR method, eight bacteria were identified as causally associated with PCOS. The protective effects of the genus Sellimonas on PCOS remained significant after applying Bonferroni correction. No significant heterogeneity or horizontal pleiotropy was found in the instrumental variables (IVs). Reverse MR analyses did not reveal a significant causal effect of PCOS on gut microbiota. Conclusion: The differences in gut microbiota between PCOS patients and controls vary across observational studies. However, MR analyses identified specific gut microbiota taxa that are causally related to PCOS. Future studies should investigate the gut microbiota that showed significant results in the MR analyses, as well as the underlying mechanisms of this causal relationship and its potential clinical significance.

Incremental value of amyloid PET in a tertiary memory clinic setting in China.

INTRODUCTION: The objective of this study is to investigate the incremental value of amyloid positron emission tomography (Aß-PET) in a tertiary memory clinic setting in China. METHODS: A total of 1073 patients were offered Aß-PET using 18F-florbetapir. The neurologists determined a suspected etiology (Alzheimer's disease [AD] or non-AD) with a percentage estimate of their confidence and medication prescription both before and after receiving the Aß-PET results. RESULTS: After disclosure of the Aß-PET results, etiological diagnoses changed in 19.3% of patients, and diagnostic confidence increased from 69.3% to 85.6%. Amyloid PET results led to a change of treatment plan in 36.5% of patients. Compared to the late-onset group, the early-onset group had a more frequent change in diagnoses and a higher increase in diagnostic confidence. DISCUSSION: Aß-PET has significant impacts on the changes of diagnoses and management in Chinese population. Early-onset cases are more likely to benefit from Aß-PET than late-onset cases. HIGHLIGHTS: Amyloid PET contributes to diagnostic changes and its confidence in Chinese patients. Amyloid PET leads to a change of treatment plans in Chinese patients. Early-onset cases are more likely to benefit from amyloid PET than late-onset cases.

Hydrophilic molecularly imprinted resin-hexagonal boron nitride composite as a new adsorbent for selective extraction and determination of a carcinoid tumor biomarker in urine.

BACKGROUND: The detection of disease biomarkers in biological samples plays an important role in early diagnosis and treatment of carcinoid tumor. However, due to the complexity of biological samples and the extremely low concentration of disease biomarkers, sample pretreatment is still the bottleneck of achieving accurate quantitative determination. In this work, new hydrophilic molecularly imprinted resin-hexagonal boron nitride (HMIR-h-BN) composites were developed and used as a new solid phase extraction (SPE) adsorbent for selective detection of 5-hydroxyindoleacetic acid (5-HIAA), a biomarker of carcinoid tumor, in urine. RESULTS: Twenty-two types of HMIR-h-BN were successfully synthesized through growing hydrophilic molecularly imprinted resin on surface of activated two-dimensional h-BN nanosheets, and preparation parameters affecting the adsorption performance of HMIR-h-BN were investigated and optimized through adsorption experiments. HMIR-h-BN #19 (the ratio of resorcinol to hexamethylenetetramine: 6:3; the dosage of h-BN: 300 mg; the dosage of dummy template: 0.12 mmol; the imprinting time: 4 h) has demonstrated to be the optimal material for efficient separation and extraction of 5-HIAA. Combined with HPLC-UV, the limit of detection and the limit of quantification of 5-HIAA in real urine samples were 9.4 ng mL-1 and 31.3 ng mL-1, respectively, the coefficient of determination (R2) was 0.9996 in the linear range of 0.1-300 µg mL-1 and the relative recoveries ranged from 86.9 % to 97.7 % with RSD ≤5.1 %. Moreover, after being processed by HMIR-h-BN-SPE, there are no interferences from other peaks at the peak position of 5-HIAA. SIGNIFICANCE: The HMIR-h-BN composite has been demonstrated to be capable of selective extraction of 5-HIAA from urine samples and have a significant purification effect. Based on the established HMIR-h-BN-SPE-HPLC-UV method, accurate quantitative determination of 5-HIAA in urine samples was achieved, which is expected to be applied in the early diagnostic of carcinoid tumor.

Interpretable predictions of chaotic dynamical systems using dynamical system deep learning.

Making accurate predictions of chaotic dynamical systems is an essential but challenging task with many practical applications in various disciplines. However, the current dynamical methods can only provide short-term precise predictions, while prevailing deep learning techniques with better performances always suffer from model complexity and interpretability. Here, we propose a new dynamic-based deep learning method, namely the dynamical system deep learning (DSDL), to achieve interpretable long-term precise predictions by the combination of nonlinear dynamics theory and deep learning methods. As validated by four chaotic dynamical systems with different complexities, the DSDL framework significantly outperforms other dynamical and deep learning methods. Furthermore, the DSDL also reduces the model complexity and realizes the model transparency to make it more interpretable. We firmly believe that the DSDL framework is a promising and effective method for comprehending and predicting chaotic dynamical systems.

Purine Metabolism and Hexosamine Biosynthetic Pathway Abnormalities in Diarrheal Weaned Piglets Identified Using Metabolomics.

Post-weaning diarrhea significantly contributes to the high mortality in pig production, but the metabolic changes in weaned piglets with diarrhea remain unclear. This study aimed to identify the differential metabolites in the urine of diarrheal weaned piglets and those of healthy weaned piglets to reveal the metabolic changes associated with diarrhea in weaned piglets. Nine 25-day-old piglets with diarrhea scores above 16 and an average body weight of 5.41 ± 0.18 kg were selected for the diarrhea group. Corresponding to the body weight and sex of the diarrhea group, nine 25-month-old healthy piglets with similar sex and body weights of 5.49 ± 0.21 kg were selected as the control group. Results showed that the serum C-reactive protein and cortisol of piglets in the diarrhea group were higher than those in the control group (p < 0.05). The mRNA expression of TNF-α, IFN-γ in the jejunum and colon, and IL-1ß in the jejunum were increased in diarrhea piglets (p < 0.05), accompanied by a reduction in the mRNA expression of ZO-1, ZO-2, and CLDN1 in the jejunum and colon (p < 0.05); mRNA expression of OCLN in the colon also occurred (p < 0.05). Metabolomic analysis of urine revealed increased levels of inosine, hypoxanthine, guanosine, deoxyinosin, glucosamine, glucosamine-1-p, N-Acetylmannosamine, chitobiose, and uric acid, identified as differential metabolites in diarrhea piglets compared to the controls. In summary, elevated weaning stress and inflammatory disease were associated with the abnormalities of purine metabolism and the hexosamine biosynthetic pathway of weaned piglets. This study additionally indicated the presence of energy metabolism-related diseases in diarrheal weaned piglets.

Microbiomic signatures of anal fistula and putative sources of microbes.

Anal fistula is a common perianal disease that typically develops from an abscess caused by in-flammation in the area. It has long been believed that intestinal microbes play a significant role in its development, considering its close relation to the intestinal environment. This work attempts to identify the microbiomic signatures of anal fistula, and putative sources of microbes by analyzing microbiomes of 7 anal fistula-associated sites in 12 patients. This study found that microbes in anal fistulas may originate from the skin surface in addition to the intestinal tract. This finding was further validated by NMDS analysis, which also indicated that the microbial communities in the inner and outer openings of the fistula were more similar to their surrounding environments. Using MaAslin2, the characteristics of the microbiome were examined, demonstrating a higher similarity between the abundant bacteria in the anal fistula samples and those found on the skin surface. Moreover, pin-to-pair analysis conducted on all subjects consistently showed a higher abundance of skin-sourced bacteria in anal fistulas. This study identifies the microbiomic signatures of anal fistula, and provides novel insights into the origin of microorganisms in anal fistulas.

Significant Impact of AcrB Amino Acid Polymorphism at Residue 716 on Susceptibility to Tigecycline and Other Antibiotics in Klebsiella pneumoniae.

AcrAB-TolC is a multidrug RND-type efflux pump that is widespread in Gram-negative bacteria. As the substrate-binding subunit, AcrB was shown to modulate antimicrobial resistance in Escherichia coli, but the influence of AcrB mutation on Klebsiella pneumoniae, a major clinical pathogen, has not been well-studied. The finding of an R716L mutation in AcrB in a clinical tigecycline-nonsusceptible K. pneumoniae S1 strain inspired us to probe the role of AcrB residue 716 in antimicrobial resistance. This residue was subsequently subjected to saturation mutagenesis, followed by antibiotic susceptibility tests, survival assays, and antibiotic accumulation assays, showing strong influences of AcrB mutation on antimicrobial resistance. In particular, resistance levels to azithromycin, tetracycline, tigecycline, and cefoxitin were significantly changed by AcrB mutation at residue 716. Mutations to charged residues, polar residues, and residues that disrupt secondary structures have particularly reduced the antimicrobial susceptibility of bacteria, except for azithromycin, and the impact is not due to the abolishment of the efflux function of the pump. Therefore, it is concluded that residue 716 is an important residue that significantly influences antimicrobial resistance in K. pneumoniae, adding to our understanding of antimicrobial resistance mechanisms in this key clinical pathogen.

Diagnostic and prognostic risk factors analysis for distant metastasis in melanoma: a population-based study.

BACKGROUND: We aimed to develop tools that could predict the occurrence of distant metastases in melanoma and its prognosis based on clinical and pathological characteristics. MATERIALS AND METHODS: We obtained data from the Surveillance, Epidemiology, and End Results (SEER) database of melanoma patients diagnosed between 2010 and 2019. Logistic analyses were performed to identify independent risk factors associated with distant metastasis. Additionally, multivariate Cox analyses were conducted to determine independent prognostic factors for patients with distant metastasis. Two nomograms were established and evaluated with the receiver operating characteristic (ROC) curves, calibration curves, and decision curve analysis (DCA). Furthermore, we performed a retrospective analysis of melanoma with distant metastasis from our institute between March 2018 and June 2022. RESULTS: Of the total 19 396 melanoma patients, 352 (1.8%) had distant metastases at the time of diagnosis. The following clinical and pathological characteristics were identified as independent risk factors for distant metastasis in melanoma: N stage, tumor size, ulceration, mitosis, primary tumor site, and pathological subtype. Furthermore, tumor size, pathological subtype, and radiotherapy were identified as independent prognostic factors. The results of the training and validation cohorts' ROC curves, calibration, DCA, and Kaplan-Meier survival curves demonstrate the effectiveness of the two nomograms. The retrospective study results from our center supported the results from the SEER database. CONCLUSION: The clinical and pathological characteristics of melanoma can predict a patient's risk of metastasis and prognosis, and the two nomograms are expected to be effective tools to guide therapy decisions.

A widespread single amino acid mutation in AcrA reduces tigecycline susceptibility in Klebsiella pneumoniae.

IMPORTANCE: Tigecycline, a glycecycline antibiotic with broad-spectrum activity against almost all Gram-positive and Gram-negative bacteria, is a highly concerned "last-resort" antibiotic. In addition to plasmid-hosted mobile tet(X) conferring high-level resistance to tigecycline, there are many reports suggesting increased expression of AcrAB-TolC efflux pump leads to tigecycline non-susceptibility. However, the role of mutations in AcrAB-TolC on tigecycline resistance has not been identified. This study reports a novel T188A mutation of the AcrA subunit of AcrAB-TolC complex in a clinical tigecycline-resistant Klebsiella pneumoniae strain and reveals the role of AcrA mutation on tigecycline resistance in K. pneumoniae. High prevalence of A188 type AcrA in hypervirulent multidrug-resistant K. pneumoniae indicates that mutations of the AcrAB-TolC complex may play a larger role in determining bacterial pathogenesis and antibiotic susceptibility than previously expected.

Noninvasive identification of HER2-low-positive status by MRI-based deep learning radiomics predicts the disease-free survival of patients with breast cancer.

OBJECTIVE: This study aimed to establish a MRI-based deep learning radiomics (DLR) signature to predict the human epidermal growth factor receptor 2 (HER2)-low-positive status and further verified the difference in prognosis by the DLR model. METHODS: A total of 481 patients with breast cancer who underwent preoperative MRI were retrospectively recruited from two institutions. Traditional radiomics features and deep semantic segmentation feature-based radiomics (DSFR) features were extracted from segmented tumors to construct models separately. Then, the DLR model was constructed to assess the HER2 status by averaging the output probabilities of the two models. Finally, a Kaplan‒Meier survival analysis was conducted to explore the disease-free survival (DFS) in patients with HER2-low-positive status. The multivariate Cox proportional hazard model was constructed to further determine the factors associated with DFS. RESULTS: First, the DLR model distinguished between HER2-negative and HER2-overexpressing patients with AUCs of 0.868 and 0.763 in the training and validation cohorts, respectively. Furthermore, the DLR model distinguished between HER2-low-positive and HER2-zero patients with AUCs of 0.855 and 0.750, respectively. Cox regression analysis showed that the prediction score obtained using the DLR model (HR, 0.175; p = 0.024) and lesion size (HR, 1.043; p = 0.009) were significant, independent predictors of DFS. CONCLUSIONS: We successfully constructed a DLR model based on MRI to noninvasively evaluate the HER2 status and further revealed prospects for predicting the DFS of patients with HER2-low-positive status. CLINICAL RELEVANCE STATEMENT: The MRI-based DLR model could noninvasively identify HER2-low-positive status, which is considered a novel prognostic predictor and therapeutic target. KEY POINTS: • The DLR model effectively distinguished the HER2 status of breast cancer patients, especially the HER2-low-positive status. • The DLR model was better than the traditional radiomics model or DSFR model in distinguishing HER2 expression. • The prediction score obtained using the model and lesion size were significant independent predictors of DFS.

Bacteroides fragilis ubiquitin homologue drives intraspecies bacterial competition in the gut microbiome.

Interbacterial antagonism and associated defensive strategies are both essential during bacterial competition. The human gut symbiont Bacteroides fragilis secretes a ubiquitin homologue (BfUbb) that is toxic to a subset of B. fragilis strains in vitro. In the present study, we demonstrate that BfUbb lyses certain B. fragilis strains by non-covalently binding and inactivating an essential peptidyl-prolyl isomerase (PPIase). BfUbb-sensitivity profiling of B. fragilis strains revealed a key tyrosine residue (Tyr119) in the PPIase and strains that encode a glutamic acid residue at Tyr119 are resistant to BfUbb. Crystal structural analysis and functional studies of BfUbb and the BfUbb-PPIase complex uncover a unique disulfide bond at the carboxy terminus of BfUbb to mediate the interaction with Tyr119 of the PPIase. In vitro coculture assays and mouse studies show that BfUbb confers a competitive advantage for encoding strains and this is further supported by human gut metagenome analyses. Our findings reveal a previously undescribed mechanism of bacterial intraspecies competition.

Proguanil and chlorhexidine augment the antibacterial activities of clarithromycin and rifampicin against Acinetobacter baumannii.

The emergence of Acinetobacter baumannii infections as a significant healthcare concern in hospital settings, coupled with their association with poorer clinical outcomes, has prompted extensive investigation into novel therapeutic agents and innovative treatment strategies. Proguanil and chlorhexidine, both categorized as biguanide compounds, have displayed clinical efficacy as antimalarial and topical antibacterial agents, respectively. In this study, we conducted an investigation to assess the effectiveness of combining proguanil and chlorhexidine with clarithromycin or rifampicin against both laboratory strains and clinical isolates of A. baumannii. The combination therapy demonstrated rapid bactericidal activity against planktonic multidrug-resistant A. baumannii, exhibiting efficacy in eradicating mature biofilms and impeding the development of antibiotic resistance in vitro. Additionally, when administered in conjunction with clarithromycin or rifampicin, proguanil enhanced the survival rate of mice afflicted with intraperitoneal A. baumannii infections, and chlorhexidine expedited wound healing in mice with skin infections. These findings are likely attributable to the disruption of A. baumannii cell membrane integrity by proguanil and chlorhexidine, resulting in heightened membrane permeability and enhanced intracellular accumulation of clarithromycin and rifampicin. Overall, this study underscores the potential of employing proguanil and chlorhexidine in combination with specific antibiotics to effectively combat A. baumannii infections and improve treatment outcomes in clinically challenging scenarios.

Determination of alectinib and its active metabolite in plasma by pipette-tip solid-phase extraction using porous polydopamine graphene oxide adsorbent coupled with high-performance liquid chromatography-ultraviolet detection.

Alectinib is known as an effective targeted drug, which has excellent therapeutic effect on non-small cell lung cancer and can significantly prolong the survival of patients. Therapeutic drug monitoring is necessary due to the photo-instability of alectinib and the individual differences in patients. In this work, a porous polydopamine graphene oxide composite (PDAG) was prepared by a simple surface modification method. A PDAG-based pipette-tip solid-phase extraction (PT-SPE) coupled with HPLC-UV detection was proposed for the separation and detection of alectinib and its active metabolite M4 in plasma. The method was methodologically validated and showed good linearity in the range of 50-5000 ng mL-1 (R2 > 0.9995). The limit of detection (LOD) was 4.8 ng mL-1 and 3.9 ng mL-1 for alectinib and M4, respectively, and the limit of quantitation (LOQ) was 16.1 ng mL-1 and 13.1 ng mL-1, respectively. The intra-day and inter-day precision expressed by coefficient of variation was less than 4.8 %. The recovery of this method ranged from 84.9 % to 103.5 % with a standard deviation of less than 4.3 %. In conclusion, the established method is accurate, stable and inexpensive, and can be used to monitor the levels of alectinib and M4 in plasma, which provide technical and data support for exploring optimal individualized remedial dosing regimens.

KBStyle: Fast Style Transfer Using a 200 KB Network With Symmetric Knowledge Distillation.

Convolutional Neural Networks (CNNs) have achieved remarkable progress in arbitrary artistic style transfer. However, the model size of existing state-of-the-art (SOTA) style transfer algorithms is immense, leading to enormous computational costs and memory demand. It makes real-time and high resolution hard for GPUs with limited memory and limits the application on mobile devices. This paper proposes a novel arbitrary artistic style transfer algorithm, KBStyle, whose model size is only 200 KB. Firstly, we design a style transfer network where the style encoder, content encoder, and corresponding decoder are custom designed to guarantee low computational cost and high shape retention. Besides, the weighted style loss function is presented to improve the performance of style migration. Then, we propose a novel knowledge distillation method (Symmetric Knowledge Distillation, SKD) for encoder-decoder-based style transfer models, which redefines the knowledge and symmetrically compresses the encoder and decoder. With the SKD, the proposed style transfer network is further compressed by 14 times to achieve the KBStyle. Experimental results demonstrate that the proposed SKD method achieves comparable results with other SOTA knowledge distillation algorithms for style transfer. Besides, the proposed KBStyle achieves high-quality stylized images. And the inference time of the KBStyle on an Nvidia TITAN RTX GPU is only 20 ms when the resolutions of the content image and style image are both 2k-resolution ( 2048×1080 ). Moreover, the 200 KB model size of KBStyle is much smaller than the SOTA models and facilitates style transfer on mobile devices.