Variability in the analysis of a single neuroimaging dataset by many teams.

Data analysis workflows in many scientific domains have become increasingly complex and flexible. Here we assess the effect of this flexibility on the results of functional magnetic resonance imaging by asking 70 independent teams to analyse the same dataset, testing the same 9 ex-ante hypotheses1. The flexibility of analytical approaches is exemplified by the fact that no two teams chose identical workflows to analyse the data. This flexibility resulted in sizeable variation in the results of hypothesis tests, even for teams whose statistical maps were highly correlated at intermediate stages of the analysis pipeline. Variation in reported results was related to several aspects of analysis methodology. Notably, a meta-analytical approach that aggregated information across teams yielded a significant consensus in activated regions. Furthermore, prediction markets of researchers in the field revealed an overestimation of the likelihood of significant findings, even by researchers with direct knowledge of the dataset2-5. Our findings show that analytical flexibility can have substantial effects on scientific conclusions, and identify factors that may be related to variability in the analysis of functional magnetic resonance imaging. The results emphasize the importance of validating and sharing complex analysis workflows, and demonstrate the need for performing and reporting multiple analyses of the same data. Potential approaches that could be used to mitigate issues related to analytical variability are discussed.

The significance and limited influence of cerebrovascular reactivity on age and sex effects in task- and resting-state brain activity.

Functional MRI measures the blood-oxygen-level dependent signals, which provide an indirect measure of neural activity mediated by neurovascular responses. Cerebrovascular reactivity affects both task-induced and resting-state blood-oxygen-level dependent activity and may confound inter-individual effects, such as those related to aging and biological sex. We examined a large dataset containing breath-holding, checkerboard, and resting-state tasks. We used the breath-holding task to measure cerebrovascular reactivity, used the checkerboard task to obtain task-based activations, and quantified resting-state activity with amplitude of low-frequency fluctuations and regional homogeneity. We hypothesized that cerebrovascular reactivity would be correlated with blood-oxygen-level dependent measures and that accounting for these correlations would result in better estimates of age and sex effects. We found that cerebrovascular reactivity was correlated with checkerboard task activations in the visual cortex and with amplitude of low-frequency fluctuations and regional homogeneity in widespread fronto-parietal regions, as well as regions with large vessels. We also found significant age and sex effects in cerebrovascular reactivity, some of which overlapped with those observed in amplitude of low-frequency fluctuations and regional homogeneity. However, correcting for the effects of cerebrovascular reactivity had very limited influence on the estimates of age and sex. Our results highlight the limitations of accounting for cerebrovascular reactivity with the current breath-holding task.

Network-wise analysis of movie-specific information in dynamic functional connectivity using COBE.

Movie watching during functional magnetic resonance imaging has emerged as a promising tool to measure the complex behavior of the brain in response to a stimulus similar to real-life situations. It has been observed that presenting a movie (sequence of events) as a stimulus will lead to a unique time course of dynamic functional connectivity related to movie stimuli that can be compared across the participants. We assume that the observed dynamic functional connectivity across subjects can be divided into following 2 components: (i) specific to a movie stimulus (depicting group-level behavior in functional connectivity) and (ii) individual-specific behavior (not necessarily common across the subjects). In this work, using the dynamic time warping distance measure, we have shown the extent of similarity between the temporal sequences of functional connectivity while the underlying movie stimuli were same and different. Further, the temporal sequence of functional connectivity patterns related to a movie is enhanced by suppressing the subject-specific components of dynamic functional connectivity using common and orthogonal basis extraction. Quantitative analysis using the F-ratio measure reveals significant differences in dynamic functional connectivity within the somatomotor network and default mode network, as well as between the occipital network and somatomotor networks.

Cerebrovascular reactivity increases across development in multiple networks as revealed by a breath-holding task: A longitudinal fMRI study.

Functional magnetic resonance imaging (fMRI) has been widely used to understand the neurodevelopmental changes that occur in cognition and behavior across childhood. The blood-oxygen-level-dependent (BOLD) signal obtained from fMRI is understood to be comprised of both neuronal and vascular information. However, it is unclear whether the vascular response is altered across age in studies investigating development in children. Since the breath-hold (BH) task is commonly used to understand cerebrovascular reactivity (CVR) in fMRI studies, it can be used to account for developmental differences in vascular response. This study examines how the cerebrovascular response changes over age in a longitudinal children's BH data set from the Nathan Kline Institute (NKI) Rockland Sample (aged 6-18 years old at enrollment). A general linear model approach was applied to derive CVR from BH data. To model both the longitudinal and cross-sectional effects of age on BH response, we used mixed-effects modeling with the following terms: linear, quadratic, logarithmic, and quadratic-logarithmic, to find the best-fitting model. We observed increased BH BOLD signals in multiple networks across age, in which linear and logarithmic mixed-effects models provided the best fit with the lowest Akaike information criterion scores. This shows that the cerebrovascular response increases across development in a brain network-specific manner. Therefore, fMRI studies investigating the developmental period should account for cerebrovascular changes that occur with age.

PEI, a new transfection method, augments the inhibitory effect of RBM5 on prostate cancer.

PEI is a cationic polymer, serving as a non-viral transfection carrier grounded in nanotechnology that enhances transfection efficiency via the proton sponge effect. RBM5 is an RNA-binding protein that can inhibit tumor development. This study involved the transfection of RBM5 in prostate cancer cells with PEI, Lipo2000, and their combination. Transwell and wound healing assays were used to observe invasion and migration of prostate cancer cells and flow cytometry was used to observe the apoptosis. Detect the expression of invasion and migration-related protein MMP9 through western blotting experiment. An activity detection kit was used to detect the activity of apoptotic protein caspase-3. We found that there was no significant difference in transfection efficiency when PEI and Lipo2000 were used alone but it significantly improved when they are combined. RBM5 reduced invasion, migration, and proliferation of prostate cancer and enhanced apoptosis. MMP9 expression was reduced, and the activity of caspase-3 was increased. PEI transfection could improve the inhibition of RBM5 on tumors more than Lipo2000. The inhibitory effect is more obvious when the two are used together. RBM5 transfected with PEI can amplify its inhibitory effect on prostate cancer, and this effect is more evident when combined with Lipo2000.

Reduced Volume Expansion of Micron-Sized SiOx via Closed-Nanopore Structure Constructed by Mg-Induced Elemental Segregation.

The inherently huge volume expansion during Li uptake has hindered the use of Si-based anodes in high-energy lithium-ion batteries. While some pore-forming and nano-architecting strategies show promises to effectively buffer the volume change, other parameters essential for practical electrode fabrication, such as compaction density, are often compromised. Here we propose a new in situ Mg doping strategy to form closed-nanopore structure into a micron-sized SiOx particle at a high bulk density. The doped Mg atoms promote the segregation of O, so that high-density magnesium silicates form to generate closed nanopores. By altering the mass content of Mg dopant, the average radii (ranged from 5.4 to 9.7 nm) and porosities (ranged from 1.4 % to 15.9 %) of the closed pores are precisely adjustable, which accounts for volume expansion of SiOx from 77.8 % to 22.2 % at the minimum. Benefited from the small volume variation, the Mg-doped micron-SiOx anode demonstrates improved Li storage performance towards realization of a 700-(dis)charge-cycle, 11-Ah-pouch-type cell at a capacity retention of >80 %. This work offers insights into reasonable design of the internal structure of micron-sized SiOx and other materials that undergo conversion or alloying reactions with drastic volume change, to enable high-energy batteries with stable electrochemistry.

[Research progress on chemical constituents and pharmacological effects of Ajania plants].

Ajania belonging to the subtribe Artemisiinae of Anthemideae(Asteraceae) is a genus of semi-shrubs closely related to Chrysanthemum. There are 24 species of Ajania in northwestern China, most of which are folk herbal medicines with strong stress tolerance. Modern medical studies have demonstrated that the chemical constituents of Ajania mainly include terpenoids, flavonoids, phenylpropanoids, alkynes, and essential oils. These compounds endow the plants with antimicrobial, anti-inflammatory, antitumor, antimalarial, antioxidant, and insecticide effects. In this study, we reviewed the research progress in the chemical constituents and pharmacological activities of Ajania, aiming to provide reference for the further research and development of Ajania.

Insights into Anion-Solvent Interactions to Boost Stable Operation of Ether-Based Electrolytes in Pure-SiOx ||LiNi0.8 Mn0.1 Co0.1 O2 Full Cells.

Ether solvents with superior reductive stability promise excellent interphasial stability with high-capacity anodes while the limited oxidative resistance hinders their high-voltage operation. Extending the intrinsic electrochemical stability of ether-based electrolytes to construct stable-cycling high-energy-density lithium-ion batteries is challenging but rewarding. Herein, the anion-solvent interactions were concerned as the key point to optimize the anodic stability of the ether-based electrolytes and an optimized interphase was realized on both pure-SiOx anodes and LiNi0.8 Mn0.1 Co0.1 O2 cathodes. Specifically, the small-anion-size LiNO3 and tetrahydrofuran with high dipole moment to dielectric constant ratio realized strengthened anion-solvent interactions, which enhance the oxidative stability of the electrolyte. The designed ether-based electrolyte enabled a stable cycling performance over 500 cycles in pure-SiOx ||LiNi0.8 Mn0.1 Co0.1 O2 full cell, demonstrating its superior practical prospects. This work provides new insight into the design of new electrolytes for emerging high-energy density lithium-ion batteries through the regulation of interactions between species in electrolytes.

Principal component analysis reveals multiple consistent responses to naturalistic stimuli in children and adults.

Functional MRI (fMRI) study of naturalistic conditions, for example, movie watching, usually focuses on shared responses across subjects. However, individual differences have been attracting increasing attention in search of group differences or associations with behavioral outcomes. Individual differences are typically studied by directly modeling the pair-wise intersubject correlation matrix or projecting the relations onto a single dimension. We contend that it is critical to examine whether there are one or more consistent responses underlying the whole sample, because multiple components, if exist, may undermine the intersubject relations using the previous methods. We propose to use principal component analysis (PCA) to examine the heterogeneity of brain responses across subjects and project the individual variability into higher dimensions. By analyzing an fMRI dataset of children and adults watching a cartoon movie, we showed evidence of two consistent responses in the supramarginal gyrus and other regions. While the first components in many regions represented a response pattern mostly in older children and adults, the second components mainly represented the younger children. The second components in the supramarginal network resembled a delayed version of the first PCs for 4 s (2 TR), indicating slower responses in the younger children than the older children and adults. The analyses highlight the importance of identifying multiple consistent responses in responses to naturalistic stimuli. This PCA-based approach could be complementary to the commonly used intersubject correlation to analyze movie-watching data.

Estimations of the weather effects on brain functions using functional MRI: A cautionary note.

The influences of environmental factors such as weather on the human brain are still largely unknown. A few neuroimaging studies have demonstrated seasonal effects, but were limited by their cross-sectional design or sample sizes. Most importantly, the stability of the MRI scanner has not been taken into account, which may also be affected by environments. In the current study, we analyzed longitudinal resting-state functional MRI (fMRI) data from eight individuals, where they were scanned over months to years. We applied machine learning regression to use different resting-state parameters, including the amplitude of low-frequency fluctuations (ALFF), regional homogeneity (ReHo), and functional connectivity matrix, to predict different weather and environmental parameters. For careful control, the raw EPI and the anatomical images were also used for predictions. We first found that daylight length and air temperatures could be reliably predicted with cross-validation using the resting-state parameters. However, similar prediction accuracies could also be achieved by using one frame of EPI image, and even higher accuracies could be achieved by using the segmented or raw anatomical images. Finally, the signals outside of the brain in the anatomical images and signals in phantom scans could also achieve higher prediction accuracies, suggesting that the predictability may be due to the baseline signals of the MRI scanner. After all, we did not identify detectable influences of weather on brain functions other than the influences on the baseline signals of MRI scanners. The results highlight the difficulty of studying long-term effects using MRI.

Characterization of whole-brain task-modulated functional connectivity in response to nociceptive pain: A multisensory comparison study.

Previous functional magnetic resonance imaging (fMRI) studies have shown that brain responses to nociceptive pain, non-nociceptive somatosensory, visual, and auditory stimuli are extremely similar. Actually, perception of external sensory stimulation requires complex interactions among distributed cortical and subcortical brain regions. However, the interactions among these regions elicited by nociceptive pain remain unclear, which limits our understanding of mechanisms of pain from a brain network perspective. Task fMRI data were collected with a random sequence of intermixed stimuli of four sensory modalities in 80 healthy subjects. Whole-brain psychophysiological interaction analysis was performed to identify task-modulated functional connectivity (FC) patterns for each modality. Task-modulated FC strength and graph-theoretical-based network properties were compared among the four modalities. Lastly, we performed across-sensory-modality prediction analysis based on the whole-brain task-modulated FC patterns to confirm the specific relationship between brain patterns and sensory modalities. For each sensory modality, task-modulated FC patterns were distributed over widespread brain regions beyond those typically activated or deactivated during the stimulation. As compared with the other three sensory modalities, nociceptive stimulation exhibited significantly different patterns (more widespread and stronger FC within the cingulo-opercular network, between cingulo-opercular and sensorimotor networks, between cingulo-opercular and emotional networks, and between default mode and emotional networks) and global property (smaller modularity). Further, a cross-sensory-modality prediction analysis found that task-modulated FC patterns could predict sensory modality at the subject level successfully. Collectively, these results demonstrated that the whole-brain task-modulated FC is preferentially modulated by pain, thus providing new insights into the neural mechanisms of pain processing.

Frequency-specific coactivation patterns in resting-state and their alterations in schizophrenia: An fMRI study.

The resting-state human brain is a dynamic system that shows frequency-dependent characteristics. Recent studies demonstrate that coactivation pattern (CAP) analysis can identify recurring brain states with similar coactivation configurations. However, it is unclear whether and how CAPs depend on the frequency bands. The current study investigated the spatial and temporal characteristics of CAPs in the four frequency sub-bands from slow-5 (0.01-0.027 Hz), slow-4 (0.027-0.073 Hz), slow-3 (0.073-0.198 Hz), to slow-2 (0.198-0.25 Hz), in addition to the typical low-frequency range (0.01-0.08 Hz). In the healthy subjects, six CAP states were obtained at each frequency band in line with our prior study. Similar spatial patterns with the typical range were observed in slow-5, 4, and 3, but not in slow-2. While the frequency increased, all CAP states displayed shorter persistence, which caused more between-state transitions. Specifically, from slow-5 to slow-4, the coactivation not only changed significantly in distributed cortical networks, but also increased in the basal ganglia as well as the amygdala. Schizophrenia patients showed significant alteration in the persistence of CAPs of slow-5. Using leave-one-pair-out, hold-out and resampling validations, the highest classification accuracy (84%) was achieved by slow-4 among different frequency bands. In conclusion, our findings provide novel information about spatial and temporal characteristics of CAP states at different frequency bands, which contributes to a better understanding of the frequency aspect of biomarkers for schizophrenia and other disorders.

The differential association between local neurotransmitter levels and whole-brain resting-state functional connectivity in two distinct cingulate cortex subregions.

We examined the association between rsFC and local neurotransmitter levels in the pregenual anterior cingulate cortex (pgACC) and the anterior mid-cingulate cortex (aMCC) by varying rsFC-strengths at the whole-brain level. Our results showed region-dependent directionality of associations in the investigated ACC subdivisions.

RBM10 regulates alternative splicing of lncRNA Neat1 to inhibit the invasion and metastasis of NSCLC.

BACKGROUND: Non-small cell lung cancer (NSCLC) accounts for more than 85% of the total cases with lung cancer. NSCLC is characterized by easy metastasis, which often spreads to bones, brains and livers. RNA-binding motif protein 10 (RBM10) is an alternative splicing (AS) regulator frequently mutated in NSCLC. We found that there were multiple peak binding sites between RBM10 and long non-coding RNA nuclear enriched abundant transcript 1 (LncRNA Neat1) by crosslinking-immunprecipitation and high-throughput sequencing (Clip-Seq). LncRNA Neat1 plays an indispensable role in promoting cancer in a variety of tumors and produces two splicing variants: Neat1_1 and Neat1_2. This study aims to explore the mechanism of RBM10 and LncRNA Neat1 in invasion and metastasis of NSCLC. METHODS: Through histological and cytological experiments, we assessed the expression level of RBM10 protein expression. The interaction between RBM10 and Neat1 was evaluated via Clip-Seq and RNA immunoprecipitation assay. The effect of RBM10 on Neat1 and its splicing variants was identified by RT-qPCR. The effect of RBM10 and Neat1 on invasive and metastasis phenotypes of NSCLC was analyzed using transwell invasion assay and scratch test. Additionally, downstream signaling pathway of RBM10 were identified by immunofluorescence and western blot. RESULTS: RBM10 exhibited low levels of expression in NSCLC tissues and cells. RBM10 inhibited the invasion and metastasis of NSCLC and recruited Neat1 and Neat1_2. Overexpression of RBM10 simultaneously inhibited Neat1 and Neat1_2, and promoted the expression of Neat1_1. On the other hand, silencing RBM10 promoted Neat1 and Neat1_2, and inhibited the expression of Neat1_1. From this, we concluded that RBM10 regulated AS of Neat1, and the tumor-promoting effect of Neat1 was mainly attributed to Neat1_2. RBM10 had a negative correlation with Neat1_2. In addition, RBM10 upregulated the expression of PTEN and downregulated the phosphorylation of PI3K/AKT/mTOR through Neat1_2, which ultimately inhibited the invasion and metastasis of NSCLC. CONCLUSION: The RBM10 regulated AS of Neat1 to cause the imbalance of Neat1_1 and Neat1_2, and RBM10 suppressed the activation of the PTEN/PI3K/AKT/mTOR signal by downregulating Neat1_2, finally affected the invasion and metastasis of NSCLC.

Effect of Implantation and Fixation of Mirena in the Treatment of Adenomyosis and its Influence on Serum Inflammatory Factors.

This experiment was carried out to analyze the placement and fixation of Mirena in the treatment of adenomyosis (AM) and its influence on the level of serum inflammatory factors in patients. For this purpose, the subjects of this study were 100 AM patients hospitalized in our hospital from June 2019 to June 2021. They were divided into two groups according to the lottery method (n=50 for each group). The control group was treated with intramuscular triptorelin after the operation, and the observation group was treated with Mirena during the operation. Sex hormone indexes, VAS score, uterine volume, serum inflammatory indexes, the total incidence of adverse reactions, WHOQOL-BREF score and recurrence rate were compared between the two groups. Results showed that in the observation group after treatment E2VAS score and uterine volume were lower, serum IL-8 and TNF-A were lower, the whoqOL-BREf score was higher, and the recurrence rate (0) was lower than that in the control group (12.00%). The total incidence of adr in the observation group (4.00%) was lower than in the control group (8.00%). Then intraoperative placement of Mirena can effectively regulate sex hormone indexes of AM patients, reduce uterine volume, relieve dysmenorrhea symptoms, reduce the inflammatory response, improve quality of life, and reduce recurrence rate, without obvious adverse reactions.

Reproducible coactivation patterns of functional brain networks reveal the aberrant dynamic state transition in schizophrenia.

It is well documented that massive dynamic information is contained in the resting-state fMRI. Recent studies have identified recurring states dominated by similar coactivation patterns (CAPs) and revealed their temporal dynamics. However, the reproducibility and generalizability of the CAP analysis are unclear. To address this question, the effects of methodological pipelines on CAP are comprehensively evaluated in this study, including the preprocessing, network construction, cluster number and three independent cohorts. The CAP state dynamics are characterized by the fraction of time, persistence, counts, and transition probability. Results demonstrate six reliable CAP states and their dynamic characteristics are also reproducible. The state transition probability is found to be positively associated with the spatial similarity. Furthermore, the aberrant CAP states in schizophrenia have been investigated by using the reproducible method on three cohorts. Schizophrenia patients spend less time in CAP states that involve the fronto-parietal network, but more time in CAP states that involve the default mode and salience network. The aberrant dynamic characteristics of CAP states are correlated with the symptom severity. These results reveal the reproducibility and generalizability of the CAP analysis, which can provide novel insights into the neuropathological mechanism associated with aberrant brain network dynamics of schizophrenia.

Nomograms to Predict Overall and Cancer-Specific Survival in Gastric Signet-Ring Cell Carcinoma.

BACKGROUND: The objective of our study was to develop and validate nomograms to predict the overall survival (OS) and cancer-specific survival (CSS) of patients with signet-ring cell carcinoma (SRCC) of the stomach. METHODS: Data were collected from the Surveillance, Epidemiology, and End Results (SEER) database. A total of 1781 patients were randomly allocated to a training set (n = 1335) and a validation set (n = 446). Univariate and multivariate analyses were used to determine the prognostic effect of variables. Nomograms were developed to estimate OS and CSS and assessed using the concordance index (C-index), calibration curves, receiver operating characteristic (ROC), and decision curve analyses (DCA). DCA was utilized to compare the nomograms and the Tumor-Node-Metastasis (TNM) staging system. RESULTS: Age, race, tumor size, T, N, M stage, and use of surgery and/or radiotherapy were included in the nomograms. C-indexes for OS and CSS were 0.74 and 0.75 in the training set, respectively. C-indexes for OS and CSS were 0.76 and 0.76 in the validation set. Calibration plots and receiver operating characteristic (ROC) curves showed good predictive accuracy. According to the decision curve analyses (DCA), the new model was more useful than the TNM staging system. CONCLUSIONS: We developed nomograms to predict OS and CSS in patients with SRCC of the stomach. Nomograms may be a valuable clinical supplement of the conventional TNM staging system.

Diagnostic value of neutrophil CD64, procalcitonin, and interleukin-6 in sepsis: a meta-analysis.

BACKGROUND: The aim of the study was to conduct a meta-analysis to evaluate the accuracy of neutrophil CD64, procalcitonin (PCT), and interleukin-6 (IL-6) as markers for the diagnosis of sepsis in adult patients. METHODS: Various databases were searched to collect published studies on the diagnosis of sepsis in adult patients using neutrophil CD64, PCT, and IL-6 levels. Utilizing the Stata SE 15.0 software, forest plots and the area under the summary receiver operating characteristic curves were drawn. The pooled sensitivity, specificity, positive likelihood ratio, negative likelihood ratio, diagnostic odds ratio, and area under the curve (AUC) were calculated. RESULTS: Fifty-four articles were included in the study. The pooled sensitivity, specificity, and AUC of neutrophil CD64 for the diagnosis of sepsis were 0.88 (95% confidence interval [CI], 0.81-0.92), 0.88 (95% CI, 0.83-0.91), and 0.94 (95% CI, 0.91-0.96), respectively. The pooled sensitivity, specificity, and AUC of PCT for the diagnosis of sepsis were 0.82 (95% CI, 0.78-0.85), 0.78 (95% CI, 0.74-0.82), and 0.87 (95% CI, 0.83-0.89), respectively. Subgroup analysis showed that the AUC for PCT diagnosis of intensive care unit (ICU) sepsis was 0.86 (95% CI, 0.83-0.89) and the AUC for PCT diagnosis of non-ICU sepsis was 0.82 (95% CI, 0.78-0.85). The pooled sensitivity, specificity, and AUC of IL-6 for the diagnosis of sepsis were 0.72 (95% CI, 0.65-0.78), 0.70 (95% CI, 0.62-0.76), and 0.77 (95% CI, 0.73-0.80), respectively. CONCLUSIONS: Of the three biomarkers studied, neutrophil CD64 showed the highest diagnostic value for sepsis, followed by PCT, and IL-6. On the other hand, PCT showed a better diagnostic potential for the diagnosis of sepsis in patients with severe conditions compared with that in patients with non-severe conditions.

Enantioseparation on a new synthetic ß-cyclodextrin chemically bonded chiral stationary phase and molecular docking study.

A novel ß-cyclodextrin derivative chemically bonded chiral stationary phase (EDACD) was synthesized by the reaction of mono-6-ethylenediamine-ß-cyclodextrin with the active alkyl isocyanate, anchoring to silica gel. After the successful analysis and characterization using scanning electron microscopy, Fourier transform infrared spectra, solid-state nuclear magnetic resonance spectra, elemental analysis, and thermogravimetric analysis techniques, the enantioselective performance of the as-prepared EDACD column was evaluated by non-steroidal antiinflammatory drugs and flavonoids under the reversed-phase HPLC condition. The factors that affected enantioseparation including mobile phase compositions and buffers were investigated in more detail. As a result, EDACD showed a satisfactory enantioselectivity for the tested drugs. With the mobile phase of acetonitrile and 20-mM ammonium formate adjusted to pH 4.0 using formic acid (85:15, v/v) at the flow rate of 0.6 mL min-1, the enantiomers of ibuprofen, carprofen, naproxen, indoprofen, ketoprofen, eriocitrin, naringin, and narirutin were separated with the best resolutions of 1.53, 1.64, 3.72, 2.40, 0.50, 0.61, 0.58, and 0.52. To adjust the proportion of acetonitrile to 80% (by volume), the enantiomers of pranoprofen and flurbiprofen were completely resolved with the best resolutions of 1.60 and 1.59. Additionally, by the study of the molecular docking, hydrogen bonding and inclusion complexation were believed to play an important role in chiral recognition. As a new material, EDACD will have a wider application in the analysis of chiral compounds.

Fast Screening of Biomembrane-Permeable Compounds in Herbal Medicines Using Bubble-Generating Magnetic Liposomes Coupled with LC-MS.

A novel strategy based on the use of bionic membrane camouflaged magnetic particles and LC-MS was developed to quickly screen the biomembrane-permeable compounds in herbal medicines. The bionic membrane was constructed by bubble-generating magnetic liposomes loaded with NH4HCO3 (BMLs). The lipid bilayer structure of the liposomes enabled BMLs to capture biomembrane-permeable compounds from a herbal extract. The BMLs carrying the compounds were then separated from the extract by a magnetic field. Upon heat treatment, NH4HCO3 rapidly decomposed to form CO2 bubbles within the liposomal bilayer, and the captured compounds were released from BMLs and analyzed by LC-MS. Jinlingzi San (JLZS), which contains various natural ingredients, was chosen to assess the feasibility of the proposed method. As a result, nine potential permeable compounds captured by BMLs were identified for the first time. Moreover, an in vivo animal study found that most of the compounds screened out by the proposed method were absorbed into the blood. The study provides a powerful tool for rapid and simultaneous prediction of multiple biomembrane-permeable components.