Aza-Prilezhaev Aziridination-Enabled Multidimensional Analysis of Isomeric Lipids via High-Resolution U-Shaped Mobility Analyzer-Mass Spectrometry.

Unsaturated lipids constitute a significant portion of the lipidome, serving as players of multifaceted functions involving cellular signaling, membrane structure, and bioenergetics. While derivatization-assisted liquid chromatography tandem mass spectrometry (LC-MS/MS) remains the gold standard technique in lipidome, it mainly faces challenges in efficiently labeling the carbon-carbon double bond (C═C) and differentiating isomeric lipids in full dimension. This presents a need for new orthogonal methodologies. Herein, a metal- and additive-free aza-Prilezhaev aziridination (APA)-enabled ion mobility mass spectrometric method is developed for probing multiple levels of unsaturated lipid isomerization with high sensitivity. Both unsaturated polar and nonpolar lipids can be efficiently labeled in the form of N-H aziridine without significant side reactions. The signal intensity can be increased by up to 3 orders of magnitude, achieving the nM detection limit. Abundant site-specific fragmentation ions indicate C═C location and sn-position in MS/MS spectra. Better yet, a stable monoaziridination product is dominant, simplifying the spectrum for lipids with multiple double bonds. Coupled with a U-shaped mobility analyzer, identification of geometric isomers and separation of different lipid classes can be achieved. Additionally, a unique pseudo MS3 mode with UMA-QTOF MS boosts the sensitivity for generating diagnostic fragments. Overall, the current method provides a comprehensive solution for deep-profiling lipidomics, which is valuable for lipid marker discovery in disease monitoring and diagnosis.

Heterosynaptic plasticity of the visuo-auditory projection requires cholecystokinin released from entorhinal cortex afferents.

The entorhinal cortex is involved in establishing enduring visuo-auditory associative memory in the neocortex. Here we explored the mechanisms underlying this synaptic plasticity related to projections from the visual and entorhinal cortices to the auditory cortex in mice using optogenetics of dual pathways. High-frequency laser stimulation (HFS laser) of the visuo-auditory projection did not induce long-term potentiation. However, after pairing with sound stimulus, the visuo-auditory inputs were potentiated following either infusion of cholecystokinin (CCK) or HFS laser of the entorhino-auditory CCK-expressing projection. Combining retrograde tracing and RNAscope in situ hybridization, we show that Cck expression is higher in entorhinal cortex neurons projecting to the auditory cortex than in those originating from the visual cortex. In the presence of CCK, potentiation in the neocortex occurred when the presynaptic input arrived 200 ms before postsynaptic firing, even after just five trials of pairing. Behaviorally, inactivation of the CCK+ projection from the entorhinal cortex to the auditory cortex blocked the formation of visuo-auditory associative memory. Our results indicate that neocortical visuo-auditory association is formed through heterosynaptic plasticity, which depends on release of CCK in the neocortex mostly from entorhinal afferents.

Intramolecular Ring-Chain Equilibrium Elimination Strategy for Pinpointing C═C Positional and Geometric Isomers of N-Alkylpyridinium Unsaturated Fatty Acid Derivatives via Ion Mobility-Mass Spectrometry.

Free unsaturated fatty acids (UFA) are key intermediates of lipid metabolism and participate in many metabolic pathways with specific biological functions. Although various fragmentation-based methods for pinpointing C═C locations in UFA were developed, the current mass spectrometry methods are difficult to simultaneously differentiate geometric isomers and positional isomers in trace samples due to low ionization efficiency, low conversion, and low resolution. Herein, an intramolecular ring-chain equilibrium elimination strategy via 4-plex stable isotope labeling dual derivatization-assisted ion mobility-mass spectrometry was developed, thereby one-pot specifically labeling C═C and carboxyl groups among the trace and unstable UFA with high sensitivity, high efficiency, and good substrate generality. It achieved fast separation of both C═C positional and geometric isomers with high resolution, which benefited from eliminating the intramolecular ring-chain equilibrium by suppressing the formation of salt bridges between free carboxyl groups and pyridine cations. 4-plex stable isotope labeling reagents showed similar reactivity, enabling high-throughput quantitative analysis of omics. This method was successfully applied for accurate and rapid identification of the UFA composition in olive oil extract. These results suggest that the developed method provides new insight for rapid characterization of UFA C═C positional and geometric isomers in complex samples to explore disease biomarkers and food quality control indicators.

Copeptin Reflect Left Ventricular Systolic Function at Early Stage of Acute Myocardial Infarction in a Pig Model.

Introduction: Measurement of biomarkers early after acute myocardial infarction (AMI) might provide a cost-effective and widely available tool to assess infarct severity, myocardial dysfunction, and clinical outcomes. We aimed to induce AMI in miniature pigs, measure the levels of serum biomarkers and global LV function dynamically and explore the release kinetics and optimal sampling time points of copeptin and its correlation with global LV function. Methods: We induced AMI in the experimental group using a closed-chest model. Left ventricular (LV) function was detected by dual-source computed tomography (DSCT) and serum copeptin was determined by ELISA. Results: The serum copeptin levels were increased at 1 hour, peaked at 3 hours, gradually decreased after 6 hours, and returned to baseline 3 days after AMI. At 3 to 6 hours, the copeptin cutoff of 16.97 to 17.44 pmol/l had 100% sensitivity and 100% specificity (P ⩽ .001) for AMI. Serum copeptin levels at 3 hours and 3 days were negatively correlated with the 3-hours LVEF (P ⩽ .001), respectively. Conclusion: Serum copeptin levels change in time, and measurements at 3 to 6 hours after AMI had the highest predictive value.

A Novel CCK Receptor GPR173 Mediates Potentiation of GABAergic Inhibition.

Cholecystokinin (CCK) enables excitatory circuit long-term potentiation (LTP). Here, we investigated its involvement in the enhancement of inhibitory synapses. Activation of GABA neurons suppressed neuronal responses in the neocortex to a forthcoming auditory stimulus in mice of both sexes. High-frequency laser stimulation (HFLS) of GABAergic neurons potentiated this suppression. HFLS of CCK interneurons could induce the LTP of their inhibition toward pyramidal neurons. This potentiation was abolished in CCK knock-out mice but intact in mice with both CCK1R and 2R knockout of both sexes. Next, we combined bioinformatics analysis, multiple unbiased cell-based assays, and histology examinations to identify a novel CCK receptor, GPR173. We propose GPR173 as CCK3R, which mediates the relationship between cortical CCK interneuron signaling and inhibitory LTP in the mice of either sex. Thus, GPR173 might represent a promising therapeutic target for brain disorders related to excitation and inhibition imbalance in the cortex.SIGNIFICANCE STATEMENT CCK, the most abundant and widely distributed neuropeptide in the CNS, colocalizes with many neurotransmitters and modulators. GABA is one of the important inhibitory neurotransmitters, and much evidence shows that CCK may be involved in modulating GABA signaling in many brain areas. However, the role of CCK-GABA neurons in the cortical microcircuits is still unclear. We identified a novel CCK receptor, GPR173, localized in the CCK-GABA synapses and mediated the enhancement of the GABA inhibition effect, which might represent a promising therapeutic target for brain disorders related to excitation and inhibition imbalance in the cortex.

Efficient determination of enantiomeric ratios of α-hydroxy/amino acids from fermented milks via ion mobility-mass spectrometry.

Chiral analysis of food components can provide important information for food quality, bioactivity and safety. Determination of enantiomeric ratios in food is a tedious task, due to the poor resolution and insufficient sensitivity for simultaneous discrimination and quantification of trace amounts of d-form metabolites. Herein, a high-throughput, high-sensitive and high-resolution method was developed for simultaneously determining enantiomeric ratios of multiple chiral α-hydroxy/amino acids (HA/AAs) from fermented milks in one-run by [d0]/[d5]-estradiol-3-benzoate-17ß-chloroformate labeling-assisted ion mobility - mass spectrometry. Results revealed extensive variation in chiral HA/AA profiles among 15 fermented milks. A total of 14 D-HA/AAs were identified. d-Lactic acid and d-alanine appeared as the most discriminatory in fermented milks with live lactic acid bacteria (LAB). Results suggested that glycolysis, casein hydrolysis and enantioisomerization of HA/AAs were most likely affected by various starter culture LAB. It may contribute to entail a valuable step forward in food quality control and discovering functional-related chiral biomarkers.

A Benchmark Dataset of Endoscopic Images and Novel Deep Learning Method to Detect Intestinal Metaplasia and Gastritis Atrophy.

Endoscopy has been routinely used to diagnose stomach diseases including intestinal metaplasia (IM) and gastritis atrophy (GA). Such routine examination usually demands highly skilled radiologists to focus on a single patient with substantial time, causing the following two key challenges: 1) the dependency on the radiologist's experience leading to inconsistent diagnosis results across different radiologists; 2) limited examination efficiency due to the demanding time and energy consumption to the radiologist. This paper proposes to address these two issues in endoscopy using novel machine learning method in three-folds. Firstly, we build a novel and relatively big endoscopy dataset of 21,420 images from the widely used White Light Imaging (WLI) endoscopy and more recent Linked Color Imaging (LCI) endoscopy, which were annotated by experienced radiologists and validated with biopsy results, presenting a benchmark dataset. Secondly, we propose a novel machine learning model inspired by the human visual system, named as local attention grouping, to effectively extract key visual features, which is further improved by learning from multiple randomly selected regional images via ensemble learning. Such a method avoids the significant problem in the deep learning methods that decrease the resolution of original images to reduce the size of input samples, which would remove smaller lesions in endoscopy images. Finally, we propose a dual transfer learning strategy to train the model with co-distributed features between WLI and LCI images to further improve the performance. The experiment results, measured by accuracy, specificity, sensitivity, positive detection rate and negative detection rate, on IM are 99.18 %, 98.90 %, 99.45 %, 99.45 %, 98.91 %, respectively, and on GA are 97.12 %, 95.34 %, 98.90 %, 98.86 %, 95.50 %, respectively, achieving state of the art performance that outperforms current mainstream deep learning models.

A Fully Deep Learning Paradigm for Pneumoconiosis Staging on Chest Radiographs.

Pneumoconiosis staging has been a very challenging task, both for certified radiologists and computer-aided detection algorithms. Although deep learning has shown proven advantages in the detection of pneumoconiosis, it remains challenging in pneumoconiosis staging due to the stage ambiguity of pneumoconiosis and noisy samples caused by misdiagnosis when they are used in training deep learning models. In this article, we propose a fully deep learning pneumoconiosis staging paradigm that comprises a segmentation procedure and a staging procedure. The segmentation procedure extracts lung fields in chest radiographs through an Asymmetric Encoder-Decoder Network (AED-Net) that can mitigate the domain shift between multiple datasets. The staging procedure classifies the lung fields into four stages through our proposed deep log-normal label distribution learning and focal staging loss. The two cascaded procedures can effectively solve the problem of model overfitting caused by stage ambiguity and noisy labels of pneumoconiosis. Besides, we collect a clinical chest radiograph dataset of pneumoconiosis from the certified radiologist's diagnostic reports. The experimental results on this novel pneumoconiosis dataset confirm that the proposed deep pneumoconiosis staging paradigm achieves an Accuracy of 90.4%, a Precision of 84.8%, a Sensitivity of 78.4%, a Specificity of 95.6%, an F1-score of 80.9% and an Area Under the Curve (AUC) of 96%. In particular, we achieve 68.4% Precision, 76.5% Sensitivity, 95% Specificity, 72.2% F1-score and 89% AUC on the early pneumoconiosis 'stage-1'.

The anterior cingulate cortex directly enhances auditory cortical responses in air-puffing-facilitated flight behavior.

For survival, animals encode prominent events in complex environments, which modulates their defense behavior. Here, we design a paradigm that assesses how a mild aversive cue (i.e., mild air puff) interacts with sound-evoked flight behavior in mice. We find that air puffing facilitates sound-evoked flight behavior by enhancing the auditory responses of auditory cortical neurons. We then find that the anterior part of the anterior cingulate cortex (ACC) encodes the valence of air puffing and modulates the auditory cortex through anatomical examination, physiological recordings, and optogenetic/chemogenetic manipulations. Activating ACC projections to the auditory cortex simulates the facilitating effect of air puffing, whereas inhibiting the ACC or its projections to the auditory cortex neutralizes this facilitating effect. These findings show that the ACC regulates sound-evoked flight behavior by potentiating neuronal responses in the auditory cortex.

RF Signal-Based UAV Detection and Mode Classification: A Joint Feature Engineering Generator and Multi-Channel Deep Neural Network Approach.

With the proliferation of Unmanned Aerial Vehicles (UAVs) to provide diverse critical services, such as surveillance, disaster management, and medicine delivery, the accurate detection of these small devices and the efficient classification of their flight modes are of paramount importance to guarantee their safe operation in our sky. Among the existing approaches, Radio Frequency (RF) based methods are less affected by complex environmental factors. The similarities between UAV RF signals and the diversity of frequency components make accurate detection and classification a particularly difficult task. To bridge this gap, we propose a joint Feature Engineering Generator (FEG) and Multi-Channel Deep Neural Network (MC-DNN) approach. Specifically, in FEG, data truncation and normalization separate different frequency components, the moving average filter reduces the outliers in the RF signal, and the concatenation fully exploits the details of the dataset. In addition, the multi-channel input in MC-DNN separates multiple frequency components and reduces the interference between them. A novel dataset that contains ten categories of RF signals from three types of UAVs is used to verify the effectiveness. Experiments show that the proposed method outperforms the state-of-the-art UAV detection and classification approaches in terms of 98.4% and F1 score of 98.3%.

Rapid Discrimination of Citrus reticulata 'Chachi' by Electrospray Ionization-Ion Mobility-High-Resolution Mass Spectrometry.

A common idea is that some dishonest businessmen often disguise Citrus reticulata Blanco varieties as Citrus reticulata 'Chachi', which places consumers at risk of economic losses. In this work, we combined high-resolution ion mobility (U-shaped mobility analyzer) with high-resolution mass spectrometry to rapidly distinguish Citrus reticulata 'Chachi' from other Citrus species. The samples were analyzed directly through simple extraction and the analytes were separated in one second. It only took about 1 min to perform a cycle of sample analysis and data acquisition. The results showed that polymethoxylated flavones and their isomers were separated easily by the ion mobility analyzer and preliminarily identified according to the accurate mass. Moreover, the collision cross-section values of all analytes, which could be used as auxiliary parameters to characterize and identify the compounds in the samples, were measured. Twenty-four samples were grouped as two clusters by multivariate analysis, which meant that Citrus reticulata 'Chachi' could be effectively differentiated. It was confirmed that the developed method had the potential to rapidly separate polymethoxylated flavones and distinguish between Citrus reticulata 'Chachi' and other Citrus reticulata Blanco varieties.

Powerful Steroid-Based Chiral Selector for High-Throughput Enantiomeric Separation of α-Amino Acids Utilizing Ion Mobility-Mass Spectrometry.

Stereospecific recognition of amino acids (AAs) plays a crucial role in chiral biomarker-based diagnosis and prognosis. Separation of AA enantiomers is a long and tedious task due to the requirement of AA derivatization prior to the chromatographic or electrophoretic steps which are also time-consuming. Here, a mass-tagged chiral selector named [d0]/[d5]-estradiol-3-benzoate-17ß-chloroformate ([d0]/[d5]-17ß-EBC) with high reactivity and good enantiomeric resolution in regard to AAs was developed. After a quick and easy chemical derivatization step of AAs using 17ß-EBC as the single chiral selector before ion mobility-mass spectrometry analysis, good enantiomer separation was achieved for 19 chiral proteinogenic AAs in a single analytical run (∼2 s). A linear calibration curve of enantiomeric excess was also established using [d0]/[d5]-17ß-EBC. It was demonstrated to be capable of determining enantiomeric ratios down to 0.5% in the nanomolar range. 17ß-EBC was successfully applied to investigate the absolute configuration of AAs among peptide drugs and detect trace levels of d-AAs in complex biological samples. These results indicated that [d0]/[d5]-17ß-EBC may contribute to entail a valuable step forward in peptide drug quality control and discovering chiral disease biomarkers.

Photocross-Linkable Hole Transport Materials for Inkjet-Printed High-Efficient Quantum Dot Light-Emitting Diodes.

Efficient approach based on the photochemistry of benzophenone has been developed for the cross-linking of the polymer hole-transporting layer (HTL). The cross-linked poly[(9,9-dioctylfluorenyl-2,7-diyl)-alt-(4,4'-(N-(4-butylphenyl) (TFB) thin films showed high solvent stability, smooth surface morphology, and improved charge-carrier mobility. The solution-processed red, green, and blue (RGB) quantum dot light-emitting diodes (QLEDs) based on the cross-linked HTLs showed much better performances than the corresponding devices based on the pristine TFB HTLs. The spin-coated red QLEDs based on the cross-linked HTLs showed the maximum current efficiency (CE), the maximum power efficiency (PE), and the peak external quantum efficiency (EQE) of 32.3 cd A-1, 42.3 lm W-1, and 21.4%, respectively. The inkjet-printed red QLEDs with the cross-linked HTLs exhibited the CE, PE, and EQE of 26.5 cd A-1, 37.8 lm W-1, and 18.1%, respectively. The high-performance HTLs were obtained by significantly reducing the amount of cross-linking agents.

Wire Desorption Combined with Electrospray Ionization Mass Spectrometry: Direct Analysis of Small Organic and Large Biological Compounds.

A novel atmospheric pressure ionization mass spectrometry based on wire desorption and electrospray ionization (WD-ESI) for direct analysis was developed to characterize chemical compounds with different polarities and thermal stabilities at atmospheric pressure. This technique is a variant of the thermal desorption electrospray ion source developed by Shiea et al. One large improvement is that the heating speed (>500 °C/s) of the thermal desorption in this work is extremely fast, using a self-heating metal wire, with which sample solution can splash from the surface to form small droplets and thus the analytes can be protected from thermal decomposition. With this feature, we have successfully achieved soft ionization of highly polar organic and biological compounds such as aflatoxin, small peptides, and even large proteins from complex matrices. The simple structure and self-cleaning capability of the WD-ESI source make it ideal for on-site screening in various applications such as food safety and biodrug testing, especially when coupled with a transportable mass spectrometer.

U-Shaped Mobility Analyzer: A Compact and High-Resolution Counter-Flow Ion Mobility Spectrometer.

In recent years, there has been a rapid increase in the use of counter-flow-type ion mobility spectrometers (IMS) due to their improved resolution and functionality. In this study, we developed a new type of counter-flow ion mobility device named the U-shaped mobility analyzer (UMA) for coupling with a mass spectrometer, where the analyte ions could travel along a gas flow in the first channel of the UMA device and then against a gas flow in the second channel of the device. Hence, a mobility band-pass filter was formed by setting different electric fields in the two channels, which enables high-resolution mobility selection of analyte ions. A resolution of ca. 180 was achieved for singly charged small organic molecules, and a resolution of up to ca. 370 was achieved for multiply charged +15 myoglobin. It was thus demonstrated that this filtering function can greatly enhance the dynamic range of an IMS-MS instrument, particularly favoring targeted analysis in complex matrices. Alternatively, the analyte ions could be operated in a so-called trap-scan mode in which ions were trapped first in one of the channels and released sequentially for mobility analysis with an even higher resolution (ca. 210 for singly charged small organic molecules and ca. 590 for +15 myoglobin). Overall, this new UMA device would enable many new applications in omics studies with its high resolution and dynamic range, especially when using the filter-scan mode for scrutinizing analytes with very low concentrations under high chemical backgrounds.

Visuoauditory Associative Memory Established with Cholecystokinin Under Anesthesia Is Retrieved in Behavioral Contexts.

Plastic change in neuronal connectivity is the foundation of memory encoding. It is not clear whether the changes during anesthesia can alter subsequent behavior. Here, we demonstrated that in male rodents under anesthesia, a visual stimulus (VS) was associated with electrical stimulation of the auditory cortex or natural auditory stimulus in the presence of cholecystokinin (CCK), which guided the animals' behavior in a two-choice auditory task. Auditory neurons became responsive to the VS after the pairings. Moreover, high-frequency stimulation of axon terminals of entorhinal CCK neurons in the auditory cortex enabled LTP of the visual response in the auditory cortex. Such pairing during anesthesia also generated VS-induced freezing in an auditory fear conditioning task. Finally, we verified that direct inputs from the entorhinal CCK neurons and the visual cortex enabled the above neural plasticity in the auditory cortex. Our findings suggest that CCK-enabled visuoauditory association during anesthesia can be translated to the subsequent behavior action.SIGNIFICANCE STATEMENT Our study provides strong evidence for the hypothesis that cholecystokinin plays an essential role in the formation of cross-modal associative memory. Moreover, we demonstrated that an entorhinal-neocortical circuit underlies such neural plasticity, which will be helpful to understand the mechanisms of memory formation and retrieval in the brain.

Direct auditory cortical input to the lateral periaqueductal gray controls sound-driven defensive behavior.

Threatening sounds can elicit a series of defensive behavioral reactions in animals for survival, but the underlying neural substrates are not fully understood. Here, we demonstrate a previously unexplored neural pathway in mice that projects directly from the auditory cortex (ACx) to the lateral periaqueductal gray (lPAG) and controls noise-evoked defensive behaviors. Electrophysiological recordings showed that the lPAG could be excited by a loud noise that induced an escape-like behavior. Trans-synaptic viral tracing showed that a great number of glutamatergic neurons, rather than GABAergic neurons, in the lPAG were directly innervated by those in layer V of the ACx. Activation of this pathway by optogenetic manipulations produced a behavior in mice that mimicked the noise-evoked escape, whereas inhibition of the pathway reduced this behavior. Therefore, our newly identified descending pathway is a novel neural substrate for noise-evoked escape and is involved in controlling the threat-related behavior.

Cholecystokinin release triggered by NMDA receptors produces LTP and sound-sound associative memory.

Memory is stored in neural networks via changes in synaptic strength mediated in part by NMDA receptor (NMDAR)-dependent long-term potentiation (LTP). Here we show that a cholecystokinin (CCK)-B receptor (CCKBR) antagonist blocks high-frequency stimulation-induced neocortical LTP, whereas local infusion of CCK induces LTP. CCK-/- mice lacked neocortical LTP and showed deficits in a cue-cue associative learning paradigm; and administration of CCK rescued associative learning deficits. High-frequency stimulation-induced neocortical LTP was completely blocked by either the NMDAR antagonist or the CCKBR antagonist, while application of either NMDA or CCK induced LTP after low-frequency stimulation. In the presence of CCK, LTP was still induced even after blockade of NMDARs. Local application of NMDA induced the release of CCK in the neocortex. These findings suggest that NMDARs control the release of CCK, which enables neocortical LTP and the formation of cue-cue associative memory.

A Non-canonical Reticular-Limbic Central Auditory Pathway via Medial Septum Contributes to Fear Conditioning.

In the mammalian brain, auditory information is known to be processed along a central ascending pathway leading to auditory cortex (AC). Whether there exist any major pathways beyond this canonical auditory neuraxis remains unclear. In awake mice, we found that auditory responses in entorhinal cortex (EC) cannot be explained by a previously proposed relay from AC based on response properties. By combining anatomical tracing and optogenetic/pharmacological manipulations, we discovered that EC received auditory input primarily from the medial septum (MS), rather than AC. A previously uncharacterized auditory pathway was then revealed: it branched from the cochlear nucleus, and via caudal pontine reticular nucleus, pontine central gray, and MS, reached EC. Neurons along this non-canonical auditory pathway responded selectively to high-intensity broadband noise, but not pure tones. Disruption of the pathway resulted in an impairment of specifically noise-cued fear conditioning. This reticular-limbic pathway may thus function in processing aversive acoustic signals.

Antitumor and immunomodulating activities of six Phellinus igniarius polysaccharides of different origins.

The aim of the current study was to compare the antitumor efficiency of Phellinus igniarius polysaccharides (PIP) from six different origins and preliminarily investigate its potential mechanisms. PIP was extracted using the microwave extraction method. The corresponding in vivo antitumor efficacy was assessed in Kunming mice bearing H22 tumors and Gansu PIP (GPIP) was identified to have a significantly higher antitumor efficacy compared with the control group (P<0.05), while no significant difference was observed following treatment with PIP from different origins (P>0.05). The spleen index of the GPIP group significantly increased compared with the saline and CTX groups (P<0.01). The in vitro MTT assay of GPIP on HepG2 cells indicated that GPIP had no direct cytotoxicity. The serum immune cytokines of interleukin-2, interleukin-12 and interferon-γ were assessed using the ELISA method. The concentration of all three serum cytokines significantly increased compared with saline and CTX groups (P<0.01) indicating that activating the immune system may be a potential antitumor mechanism. These results demonstrated that GPIP has great potential as a natural antitumor agent with immunomodulatory activity.