A Comparison of PKD2L1-Expressing Cerebrospinal Fluid Contacting Neurons in Spinal Cords of Rodents, Carnivores, and Primates.

Cerebrospinal fluid contacting neurons (CSF-cNs) are a specific type of neurons located around the ventricles in the brain and the central canal in the spinal cord and have been demonstrated to be intrinsic sensory neurons in the central nervous system. One of the important channels responsible for the sensory function is the polycystic kidney disease 2-like 1 (PKD2L1) channel. Most of the studies concerning the distribution and function of the PKD2L1-expressing CSF-cNs in the spinal cord have previously been performed in non-mammalian vertebrates. In the present study immunohistochemistry was performed to determine the distribution of PKD2L1-immunoreactive (IR) CSF-cNs in the spinal cords of four mammalian species: mouse, rat, cat, and macaque monkey. Here, we found that PKD2L1-expressing CSF-cNs were present at all levels of the spinal cord in these animal species. Although the distribution pattern was similar across these species, differences existed. Mice and rats presented a clear PKD2L1-IR cell body labeling, whereas in cats and macaques the PKD2L1-IR cell bodies were more weakly labeled. Ectopic PKD2L1-IR neurons away from the ependymal layer were observed in all the animal species although the abundance and the detailed locations varied. The apical dendritic protrusions with ciliated fibers were clearly seen in the lumen of the central canal in all the animal species, but the sizes of protrusion bulbs were different among the species. PKD2L1-IR cell bodies/dendrites were co-expressed with doublecortin, MAP2 (microtubule-associated protein 2), and aromatic L-amino acid decarboxylase, but not with NeuN (neuronal nuclear protein), indicating their immature properties and ability to synthesize monoamine transmitters. In addition, in situ hybridization performed in rats revealed PKD2L1 mRNA expression in the cells around the central canal. Our results indicate that the intrinsic sensory neurons are conserved across non-mammalian and mammalian vertebrates. The similar morphology of the dendritic bulbs with ciliated fibers (probably representing stereocilia and kinocilia) protruding into the central canal across different animal species supports the notion that PKD2L1 is a chemo- and mechanical sensory channel that responds to mechanical stimulations and maintains homeostasis of the spinal cord. However, the differences of PKD2L1 distribution and expression between the species suggest that PKD2L1-expressing neurons may receive and process sensory signals differently in different animal species.

The Development of Hindlimb Postural Asymmetry Induced by Focal Traumatic Brain Injury Is Not Related to Serotonin 2A/C Receptor Expression in the Spinal Cord.

Brain injury and stroke are leading causes of adult disability. Motor deficits are common problems, and their underlying pathological mechanisms remain poorly understood. The serotoninergic system is implicated in both functional recovery from and the occurrence of spasticity after injuries to the central nervous system. This study, which was conducted on rats, investigated the development of limb postural changes and their relationship to the expression of serotonin (5-HT) 2A and 2C receptors in the spinal cord in the 4 weeks after focal traumatic brain injury (TBI) to the right hindlimb sensorimotor cortex. The limb motor deficits were assessed by measuring gait pattern changes during walking and hindlimb postural asymmetry at different time intervals (3−28 days) after surgery. The expressions of the 5-HT2A and 2C receptors in the lumbar spinal cord were investigated using immunohistochemistry. The results showed that all the rats with TBI, independently of the duration of the interval, displayed postural asymmetry with flexion on the contralateral (left) side (>2 mm), while the sham-operated rats showed no apparent postural asymmetry. The TBI rats also had longer stride lengths during walking in both their hindlimbs and their forelimbs compared with the sham rats. For both the TBI and the sham rats, the hind-paw placement angles were larger on the contralateral side in some of the groups. Compared to the sham-operated rats, the 5-HT2A and 2C receptor expression did not significantly change on either side of the lumbar spinal cords of the TBI rats in any of the groups. These results suggest that focal TBI can induce motor deficits lasting a relatively long time, and that these deficits are not related to the expression of the 5-HT2A and 2C receptors in the spinal cord.

Comparison of Phytochemical Profiles of Wild and Cultivated American Ginseng Using Metabolomics by Ultra-High Performance Liquid Chromatography-High-Resolution Mass Spectrometry.

American ginseng (Panax quinquefolius L.) has been recognized as a valuable herb medicine, and ginsenosides are the most important components responsible for the health-beneficial effects. This study investigated the secondary metabolites responsible for the differentiation of wild and cultivated American ginsengs with ultrahigh-performance liquid chromatography-high resolution mass spectrometry (UHPLC-HRMS)-based metabolomic approach. An in-house ginsenoside library was developed to facilitate data processing and metabolite identification. Data visualization methods, such as heatmaps and volcano plots, were utilized to extract discriminated ion features. The results suggested that the ginsenoside profiles of wild and cultivated ginsengs were significantly different. The octillol (OT)-type ginsenosides were present in greater abundance and diversity in wild American ginsengs; however, a wider distribution of the protopanaxadiol (PPD)-and oleanolic acid (OA)-type ginsenosides were found in cultivated American ginseng. Based on the tentative identification and semi-quantification, the amounts of five ginsenosides (i.e., notoginsenoside H, glucoginsenoside Rf, notoginsenoside R1, pseudoginsenoside RT2, and ginsenoside Rc) were 2.3-54.5 fold greater in wild ginseng in comparison to those in their cultivated counterparts, and the content of six ginsenosides (chicusetsusaponin IVa, malonylginsenoside Rd, pseudoginsenoside Rc1, malonylfloralginsenoside Rd6, Ginsenoside Rd, and malonylginsenoside Rb1) was 2.6-14.4 fold greater in cultivated ginseng compared to wild ginseng. The results suggested that the in-house metabolite library can significantly reduce the complexity of the data processing for ginseng samples, and UHPLC-HRMS is effective and robust for identifying characteristic components (marker compounds) for distinguishing wild and cultivated American ginseng.

Unilateral brain injury to pregnant rats induces asymmetric neurological deficits in the offspring.

Effects of environmental factors may be transmitted to the following generation, and cause neuropsychiatric disorders including depression, anxiety, and posttraumatic stress disorder in the offspring. Enhanced synaptic plasticity induced by environmental enrichment may be also transmitted. We here test the hypothesis that the effects of brain injury in pregnant animals may produce neurological deficits in the offspring. Unilateral brain injury (UBI) by ablation of the hindlimb sensorimotor cortex in pregnant rats resulted in the development of hindlimb postural asymmetry (HL-PA), and impairment of balance and coordination in beam walking test in the offspring. The offspring of rats with the left UBI exhibited HL-PA before and after spinal cord transection with the contralesional (i.e., right) hindlimb flexion. The right UBI caused the offspring to develop HL-PA that however was cryptic and not-lateralized; it was evident only after spinalization, and was characterized by similar occurrence of the ipsi- and contralesional hindlimb flexion. The HL-PA persisted after spinalization suggesting that the asymmetry was encoded in lumbar spinal neurocircuits that control hindlimb muscles. Balance and coordination were affected by the right UBI but not the left UBI. Thus, the effects of a unilateral brain lesion in pregnant animals may be intergenerationally transmitted, and this process may depend on the side of brain injury. The results suggest the existence of left-right side-specific mechanisms that mediate transmission of the lateralized effects of brain trauma from mother to fetus.

Rapid and Sensitive Identification and Discrimination of Bound/Unbound Ligands on Colloidal Nanocrystals via Direct Analysis in Real-Time Mass Spectrometry.

Direct analysis in real-time mass spectrometry (DART-MS) has been applied to the characterization of colloidal nanocrystal surface ligands. The nanocrystals (NCs) in colloidal suspension were purified and deposited onto a solid substrate, and the solvent was allowed to evaporate. Ligand desorption was thermally stimulated using a temperature ramp from 30 °C up to 530 °C, and the desorbed ligands were introduced into a DART-MS instrument where metastable He atoms provide energy for ionization and fragmentation through the reaction with ambient vapors including O2 and H2O. The method allows the identification of ligand species with various functional groups, even in complex, mixed-ligand samples. Bound and unbound molecules can be distinguished based on the desorption temperature. In ideal cases, the desorption profile for a given molecule can be analyzed according to methods adapted from thermal desorption spectroscopy (TDS) to estimate desorption activation energy for NC-bound ligands. Results are presented and discussed for different nanocrystal and ligand types. The method is a promising complement to the range of existing tools for NC ligand analysis.

Unilateral traumatic brain injury of the left and right hemisphere produces the left hindlimb response in rats.

Traumatic brain injury and stroke result in hemiplegia, hemiparesis, and asymmetry in posture. The effects are mostly contralateral; however, ipsilesional deficits may also develop. We here examined whether ablation brain injury and controlled cortical impact (CCI), a rat model of clinical focal traumatic brain injury, both centered over the left or right sensorimotor cortex, induced hindlimb postural asymmetry (HL-PA) with contralesional or ipsilesional limb flexion. The contralesional hindlimb was flexed after left or right side ablation injury. In contrast, both the left and right CCI unexpectedly produced HL-PA with flexion on left side. The flexion persisted after complete spinal cord transection suggesting that CCI triggered neuroplastic processes in lumbar neural circuits enabling asymmetric muscle contraction. Left limb flexion was exhibited under pentobarbital anesthesia. However, under ketamine anesthesia, the body of the left and right CCI rats bent laterally in the coronal plane to the ipsilesional side suggesting that the left and right injury engaged mirror-symmetrical motor pathways. Thus, the effects of the left and right CCI on HL-PA were not mirror-symmetrical in contrast to those of the ablation brain injury, and to the left and right CCI produced body bending. Ipsilateral effects of the left CCI on HL-PA may be mediated by a lateralized motor pathway that is not affected by the left ablation injury. Alternatively, the left-side-specific neurohormonal mechanism that signals from injured brain to spinal cord may be activated by both the left and right CCI but not by ablation injury.

Forensic Fiber Analysis by Thermal Desorption/Pyrolysis-Direct Analysis in Real Time-Mass Spectrometry.

The thermal desorption/pyrolysis-direct analysis in real time-mass spectrometry (TD/Py-DART-MS) method was developed for the analysis of fibers in this study. The fiber samples were pyrolyzed with a temperature gradient and the pyrolysis products were determined by DART-MS. The pyrogram from the TD/Py-DART-MS fiber analysis was found to be associated with the physical properties such as the melting points. At the same time, the TD/Py-DART-MS allows the analyst to obtain the chemical information such as polymeric backbone structures and dyes on the fiber. The pyrolysis profiles of common polymeric fibers in textile materials such as cotton, cellulose triacetate (CT), poly(caprolactam) (nylon-6), poly(hexamethylene adipamide) (nylon-6/6), poly(acrylonitrile) (PAN), poly(ethylene terephthalate) (PET), poly(butylene terephthalate) (PBT), poly(propylene) (PP), and polytrimethylene terephthalate (PTT) and their respective characteristic mass spectra were reported in this study. The fibers from 40 commercial textile samples were analyzed by the TD/Py-DART-MS method, and the statistical methods including principal component analysis (PCA) and Pearson product moment correlation (PPMC) were applied to classify and associate the fibers based on their mass spectral data. The strong correlation between the reference fiber mass spectral profiles and tested fiber mass spectral profiles was observed by using the PPMC method, and the identification accuracy was 97.5%. When combined, the mass spectral and pyrogram data, the types of fibers including the blended fibers were identified effectively. The TD/Py-DART-MS method also demonstrated the promising capability for the identification of dyes on fibers. Overall, the TD/Py-DART-MS method requires small sample size and minimal sample preparation but offers reproducible and multidimensional information for the fiber evidence rapidly (i.e., ∼6.7 min). Since the proposed method is simple to perform and the data are easy to interpret, this approach may significantly contribute to the fiber identification and comparison procedures in forensic settings with high sample throughput potential.

The classification of Cannabis hemp cultivars by thermal desorption direct analysis in real time mass spectrometry (TD-DART-MS) with chemometrics.

Cannabis has been cultivated as a source of food, fiber, and medicine globally, so the classification of Cannabis cultivars based on their chemical fingerprints is important to standardize and control the quality of Cannabis, ensure that patients receive a full and consistent spectrum of therapeutic benefits, and promote the further implementation of Cannabis-based products in clinical uses. In this study, a high-throughput analytical method, thermal desorption direct analysis in real time mass spectrometry (TD-DART-MS), was employed to classify various Cannabis hemp cultivars with multivariate analysis. Cannabis plant materials from four cultivars were analyzed directly by TD-DART-MS without solvent extraction. The total run time was 15 min including 8 min for data acquisition and 7 min for cooling down the thermal stage. Data preprocessing strategy such as data transformation was evaluated on the TD-DART-MS data set and cubic root transform has shown significant improvement to the classification. TD-DART-MS data was then processed by principal component analysis (PCA) and the results were compared with those from liquid chromatography-mass spectrometry (LC-MS) data. The samples were clustered based on cultivars by PCA, and the validation samples collected 2 months later were also grouped together with the original samples by cultivars after mean-centering the data sets. Partial least squares discriminant analysis (PLS-DA) models were constructed with the TD-DART-MS data sets and a 99.3 ± 0.3% classification accuracy was obtained from 100 independent bootstrapped Latin partition evaluations. Our results indicate that TD-DART-MS may be used as a screening tool for the classification of Cannabis cultivars. Graphical abstract.

Simultaneous Determination and Analysis of Major Ginsenosides in Wild American Ginseng Grown in Tennessee.

Ginsenosides are the major constituent that is responsible for the health effects of American ginseng. The ginsenoside profile of wild American ginseng is ultimately the result of germplasm, climate, geography, vegetation species, water, and soil conditions. This is the first report to address the ginsenoside profile of wild American ginseng grown in Tennessee (TN), the third leading state for production of wild American ginseng. In the present study, ten major ginsenosides in wild American ginseng roots grown in TN, including Rb1, Rb2, Rb3, Rc, Rd, Re, Rf, Rg1, Rg2, and Rg3, were determined simultaneously. The chemotypic differences among TN wild ginseng, cultivated American ginseng, and Asian ginseng were assessed based on the widely used markers of ginsenoside profiling, including the top three ginsenosides, ratios of PPD/PPT, Rg1/Rb1, Rg1/Re, and Rb2/Rc. Our findings showed marked variation in ginsenoside profile for TN wild ginseng populations. Nevertheless, TN wild ginseng has significant higher ginsenoside content and more ginsenoside diversity than the cultivated ginseng. The total ginsenoside content in TN wild ginseng, as well as ginsenosides Rg1 and Re, increases with the age of the roots. Marked chemotypic differences between TN wild ginseng and cultivated American ginseng were observed based on the chemotypic markers. Surprisingly, we found that TN wild ginseng is close to Asian ginseng with regard to these characteristics in chemical composition. This study verified an accessible method to scientifically elucidate the difference in chemical constituents to distinguish wild from the cultivated American ginseng. This work is critical for the ecological and biological assessments of wild American ginseng so as to facilitate long-term sustainability of the wild population.

Development of a Comprehensive Flavonoid Analysis Computational Tool for Ultrahigh-Performance Liquid Chromatography-Diode Array Detection-High-Resolution Accurate Mass-Mass Spectrometry Data.

Liquid chromatography and mass spectrometry methods, especially ultrahigh-performance liquid chromatography coupled with diode array detection and high-resolution accurate-mass multistage mass spectrometry (UHPLC-DAD-HRAM/MSn), have become the tool-of-the-trade for profiling flavonoids in foods. However, manually processing acquired UHPLC-DAD-HRAM/MSn data for flavonoid analysis is very challenging and highly expertise-dependent due to the complexities of the chemical structures of the flavonoids and the food matrixes. A computational expert data analysis program, FlavonQ-2.0v, has been developed to facilitate this process. The program first uses UV-vis spectra for an initial stepwise classification of flavonoids into classes and then identifies individual flavonoids in each class based on their mass spectra. Step-wise identification of flavonoid classes is based on a UV-vis spectral library compiled from 146 flavonoid reference standards and a novel chemometric model that uses stepwise strategy and projected distance resolution (PDR) method. Further identification of the flavonoids in each class is based on an in-house database that contains 5686 flavonoids analyzed in-house or previously reported in the literature. Quantitation is based on the UV-vis spectra. The stepwise classification strategy to identify classes significantly improved the performance of the program and resulted in more accurate and reliable classification results. The program was validated by analyzing data from a variety of samples, including mixed flavonoid standards, blueberry, mizuna, purple mustard, red cabbage, and red mustard green. Accuracies of identification for all samples were above 88%. FlavonQ-2.0v greatly facilitates the identification and quantitation of flavonoids from UHPLC-HRAM-MSn data. It saves time and resources and allows less experienced people to analyze the data.

MSAll strategy for comprehensive quantitative analysis of PEGylated-doxorubicin, PEG and doxorubicin by LC-high resolution q-q-TOF mass spectrometry coupled with all window acquisition of all fragment ion spectra.

The covalent attachment of polyethylene glycol (PEG) to therapeutic compounds (known as PEGylation) is one of the most promising techniques to improve the biological efficacy of small molecular weight drugs. After administration, PEGylated prodrugs can be metabolized into pharmacologically active compounds so that PEGylated drug, free drug and released PEG are present simultaneously in the body. Understanding the pharmacokinetic behavior of these three compounds is needed to guide the development of pegylated theranostic agents. However, PEGs are polydisperse molecules with a wide range of molecular weights, so that the simultaneous quantitation of PEGs and PEGylated molecules in biological matrices is very challenging. This article reports the application of a data-independent acquisition method (MSAll) based on liquid chromatography electrospray ionization quadrupole time-of-flight mass spectrometry (LC-q-q-TOF-MS) in the positive ion mode to the simultaneous determination of methoxyPEG2000-doxorubicin (mPEG2K-Dox) and its breakdown products in rat blood. Using the MSAll technique, precursor ions of all molecules are generated in q1, fragmented to product ions in q2 (collision cell), and subjected to TOF separation before precursor and product ions are recorded using low and high collision energies (CE) respectively in different experiments for a single sample injection. In this study, dissociation in q2 generated a series of high resolution PEG-related product ions at m/z 89.0611, 133.0869, 177.1102, 221.1366, 265.1622, 309.1878, and 353.2108 corresponding to fragments containing various numbers of ethylene oxide subunits, Dox-related product ions at m/z 321.0838 and 361.0785, and an mPEG2K-Dox specific product ion at m/z 365.0735. Detection of mPEGs and mPEG2K-Dox was based on high resolution extracted ions of mPEG and the specific compound. The method was successfully applied to a pharmacokinetic study of doxorubicin, mPEG2K (methylated polyethylene glycol 2K), and mPEG2K-doxorubicin in rats after a single intravenous injection of mPEG2K-doxorubicin. To the best of our knowledge, this is the first assay that simultaneously determines mPEG, Dox, and mPEG2K-Dox in a biological matrix. We believe the MSAll technique as applied in this study can be potentially extended to the determination of other PEGylated small molecules or polymeric compounds.

Feruloyl dopamine-O-hexosides are efficient marker compounds as orthogonal validation for authentication of black cohosh (Actaea racemosa)-an UHPLC-HRAM-MS chemometrics study.

Due to the complexity and variation of the chemical constituents in authentic black cohosh (Actaea racemosa) and its potential adulterant species, an accurate and feasible method for black cohosh authentication is not easy. A high-resolution accurate mass (HRAM) LC-MS fingerprinting method combined with chemometric approach was employed to discover new marker compounds. Seven hydroxycinnamic acid amide (HCAA) glycosides are proposed as potential marker compounds for differentiation of black cohosh from related species, including two Asian species (A. foetida, A. dahurica) and two American species (A. pachypoda, A. podocarpa). These markers were putatively identified by comparing their mass spectral fragmentation behavior with those of their authentic aglycone compounds and phytochemistry reports. Two isomers of feruloyl methyldopamine 4-O-hexoside ([M + H]+ 506) and one feruloyl tyramine 4-O-hexoside ([M + H]+ 476) contributed significantly to the separation of Asian species in principle component analysis (PCA) score plot. The efficacy of the models built on four reasonable combinations of these markers in differentiating black cohosh and its adulterants were evaluated and validated by partial least-square discriminant analysis (PLS-DA). Two models based on these reduced dataset achieved 100% accuracy based on the current sample collection, including the model that used only three feruloyl dopamine-O-hexoside isomers ([M + H]+ 492) and one feruloyl dopamine-O-dihexoside ([M + H-hexosyl]+ at m/z 492). Graphical abstract Hydroxycinnamic acid amide glycosides are proposed as potential marker compounds for authentication of black cohosh.

Spinal cord injury enables aromatic L-amino acid decarboxylase cells to synthesize monoamines.

Serotonin (5-HT), an important modulator of both sensory and motor functions in the mammalian spinal cord, originates mainly in the raphe nuclei of the brainstem. However, following complete transection of the spinal cord, small amounts of 5-HT remain detectable below the lesion. It has been suggested, but not proven, that this residual 5-HT is produced by intraspinal 5-HT neurons. Here, we show by immunohistochemical techniques that cells containing the enzyme aromatic l-amino acid decarboxylase (AADC) occur not only near the central canal, as reported by others, but also in the intermediate zone and dorsal horn of the spinal gray matter. We show that, following complete transection of the rat spinal cord at S2 level, AADC cells distal to the lesion acquire the ability to produce 5-HT from its immediate precursor, 5-hydroxytryptophan. Our results indicate that this phenotypic change in spinal AADC cells is initiated by the loss of descending 5-HT projections due to spinal cord injury (SCI). By in vivo and in vitro electrophysiology, we show that 5-HT produced by AADC cells increases the excitability of spinal motoneurons. The phenotypic change in AADC cells appears to result from a loss of inhibition by descending 5-HT neurons and to be mediated by 5-HT1B receptors expressed by AADC cells. These findings indicate that AADC cells are a potential source of 5-HT at spinal levels below an SCI. The production of 5-HT by AADC cells, together with an upregulation of 5-HT2 receptors, offers a partial explanation of hyperreflexia below a chronic SCI.

FlavonQ: an automated data processing tool for profiling flavone and flavonol glycosides with ultra-high-performance liquid chromatography-diode array detection-high resolution accurate mass-mass spectrometry.

Profiling flavonoids in natural products poses a great challenge due to the diversity of flavonoids, the lack of commercially available standards, and the complexity of plant matrixes. The increasingly popular use of ultra-high-performance liquid chromatography-diode array detection-high resolution accurate mass-mass spectrometry (UHPLC-HRAM-MS) for the analysis of flavonoids has provided more definitive information but also vastly increased amounts of data. Thus, mining of the UHPLC-HRAM-MS data is a very daunting, labor-intensive, and expertise-dependent process. An automated data processing tool, FlavonQ, was developed that can transfer field-acquired expertise into data analysis and facilitate flavonoid research. FlavonQ is an "expert system" designed for automated data analysis of flavone and flavonol glycosides, two important subclasses of flavonoids. FlavonQ is capable of data format conversion, peak detection, flavone and flavonol glycoside peak extraction, flavone and flavonol glycoside identification, and production of quantitative results. An expert system was applied to the determination of flavone and flavonol glycosides in nine different plants with an average execution time of less than 1 min. The results obtained by FlavonQ were in good agreement with those determined conventionally by a flavonoid expert.

Application of chemometrics to resolve overlapping mass spectral peak clusters between trichloroethylene and its deuterated internal standard.

RATIONALE: Using one or two (2) H-atom-labeled analogs as internal standards (ISs) may cause a 'cross-contribution' problem (i.e., the overlap of ions from the IS and the analyte) especially for halogenated volatile organic compounds (VOCs). However, in this situation the overlapping peak clusters of the analyte and ISs can be resolved by multivariate chemometric methods such as classical least-squares (CLS) and inverse least-squares (ILS). METHODS: Trichloroethylene (TCE) and its internal standard, deuterated TCE (TCE-d), as model compounds, were analyzed using portable gas chromatography/mass spectrometry. CLS and ILS were applied to resolve overlapping TCE and TCE-d mass spectral signals and evaluated for the determination of TCE. CLS and ILS models were constructed and used to predict concentration ratios of TCE to TCE-d. Calibration samples were prepared by adding TCE at different concentrations and TCE-d at 300 ng mL(-1) as an IS. RESULTS: The calibration curve was linear over a range of 10-1000 ng mL(-1) with a coefficient of determination (R(2)) of 0.993. A validation data set collected 2 weeks later was used to further test the model robustness. Lower prediction errors and higher correlation coefficients were obtained from TCE/TCE-d ratios predicted by the CLS model. CONCLUSIONS: This paper describes the first application of CLS to deconvolute overlapping peaks between an analyte and its corresponding isotopic internal standard for quantification. The proposed method enables simple isotopic analogs of analytes (one H or C atom is isotopically labeled) to be used as internal standards for analytes with isotopic distributions. It has wide application because of the environmental impact and prevalence of halogenated VOCs, especially when analytes have isotopic distributions that overlap with an internal standard or when sophisticated isotopic analogs of the analytes with three or more (2)H- or/and (13)C-atoms are prohibitively expensive or even impossible.

Use of fuzzy chromatography mass spectrometric (FCMS) fingerprinting and chemometric analysis for differentiation of whole-grain and refined wheat (T. aestivum) flour.

A fuzzy chromatography mass spectrometric (FCMS) fingerprinting method combined with chemometric analysis has been established for rapid discrimination of whole-grain flour (WF) from refined wheat flour (RF). Bran, germ, endosperm, and WF from three local cultivars or purchased from a grocery store were studied. The state of refinement (whole vs. refined) of wheat flour was differentiated successfully by use of principal-components analysis (PCA) and soft independent modeling of class analogy (SIMCA), despite potential confounding introduced by wheat class (red vs. white; hard vs. soft) or resources (different brands). Twelve discriminatory variables were putatively identified. Among these, dihexoside, trihexoside, apigenin glycosides, and citric acid had the highest peak intensity for germ. Variable line plots indicated phospholipids were more abundant in endosperm. Samples of RF and WF from three cultivars (Hard Red, Hard White, and Soft White) were physically mixed to furnish 20, 40, 60, and 80 % WF of each cultivar. SIMCA was able to discriminate between 100 %, 80 %, 60 %, 40 %, and 20 % WF and 100 % RF. Partial least-squares (PLS) regression was used for prediction of RF-to-WF ratios in the mixed samples. When PLS models were used the relative prediction errors for RF-to-WF ratios were less than 6 %. Graphical Abstract Workflow of targeting discriminatory compounds by use of FCMS and chemometric analysis.

Spinal Cord Hemisection Facilitates Aromatic L-Amino Acid Decarboxylase Cells to Produce Serotonin in the Subchronic but Not the Chronic Phase.

Neuromodulators, such as serotonin (5-hydroxytryptamine, 5-HT) and noradrenalin, play an essential role in regulating the motor and sensory functions in the spinal cord. We have previously shown that in the rat spinal cord the activity of aromatic L-amino acid decarboxylase (AADC) cells to produce 5-HT from its precursor (5-hydroxytryptophan, 5-HTP) is dramatically increased following complete spinal cord transection. In this study, we investigated whether a partial loss of 5-HT innervation could similarly increase AADC activity. Adult rats with spinal cord hemisected at thoracic level (T11/T12) were used with a postoperation interval at 5 days or 60 days. Using immunohistochemistry, first, we observed a significant reduction in the density of 5-HT-immunoreactive fibers in the spinal cord below the lesion on the injured side for both groups. Second, we found that the AADC cells were similarly expressed on both injured and uninjured sides in both groups. Third, increased production of 5-HT in AADC cells following 5-HTP was seen in 5-day but not in 60-day postinjury group. These results suggest that plastic changes of the 5-HT system might happen primarily in the subchronic phase and for longer period its function could be compensated by plastic changes of other intrinsic and/or supraspinal modulation systems.

Comparison of three algorithms for the baseline correction of hyphenated data objects.

Three novel two-way baseline correction algorithms, that is, orthogonal basis (OB), fuzzy optimal associative memory (FOAM), and polynomial fitting (PF), were evaluated with high performance liquid chromatography-mass spectrometry (HPLC-MS) and gas chromatography/mass spectrometry (GC/MS) data objects. Among these algorithms, both OB and FOAM are two-way baseline correction algorithms, which reconstruct the entire two-way backgrounds from blank data objects, while the PF algorithm is a pseudo-two-way method, which models each ion chromatogram baseline with a third-order polynomial. The performance of baseline correction methods was first evaluated with respect to the signal-to-noise ratios (SNRs) of 4 major peaks of the HPLC-MS total ion current (TIC) chromatograms of celery seed extracts. Then, the effect of baseline correction on pattern recognition was evaluated by using 42 two-way headspace (HS) solid phase microextraction (SPME) GC/MS data objects of 7 polychlorinated biphenyl (PCB) mixture standard solutions. Two types of classifiers, that is, a fuzzy rule-building expert system (FuRES) and partial least-squares-discriminant analysis (PLS-DA) were evaluated in parallel. Bootstrapped Latin partitions (BLPs) were used to give an unbiased and generalized evaluation of the classification accuracy. Results indicate that SNRs of major peaks of the TIC chromatogram representative of two-way HPLC-MS data objects are increased by baseline correction. In addition, higher prediction accuracies can be obtained by performing baseline correction on the entire GC/MS data set prior to pattern recognition. It is also found that proper data transformation is able to improve the performance of baseline correction. This report is the first of two-way baseline correction methods for hyphenated chromatography/mass spectrometry data objects. Both the orthogonal basis and FOAM baseline correction methods are novel in-house algorithms and proved to be generally effective for two-way baseline correction in the present study. Polynomial fitting is a conventional baseline correction method for one-way data objects and is applied to two-way data objects for the first time. It is applicable when blank data objects are unavailable.

Determination of Aroclor 1260 in soil samples by gas chromatography with mass spectrometry and solid-phase microextraction.

A novel fast screening method was developed for the determination of polychlorinated biphenyls that are constituents of the commercial mixture, Aroclor 1260, in soil matrices by gas chromatography with mass spectrometry combined with solid-phase microextraction. Nonequilibrium headspace solid-phase microextraction with a 100 µm polydimethylsiloxane fiber was used to extract polychlorinated biphenyls from 0.5 g of soil matrix. The use of 2 mL of saturated potassium dichromate in 6 M sulfuric acid solution improved the reproducibility of the extractions and the mass transfer of the polychlorinated biphenyls from the soil matrix to the microextraction fiber via the headspace. The extraction time was 30 min at 100°C. The percent recoveries, which were evaluated using an Aroclor 1260 standard and liquid injection, were within the range of 54.9-65.7%. Two-way extracted ion chromatogram data were used to construct calibration curves. The relative error was <±15% and the relative standard deviation was <15%, which are respective measures of the accuracy and precision. The method was validated with certified soil samples and the predicted concentrations for Aroclor 1260 agreed with the certified values. The method was demonstrated to be linear from 10 to 1000 ng/g for Aroclor 1260 in dry soil.

Interpretable medical image Visual Question Answering via multi-modal relationship graph learning.

Medical Visual Question Answering (VQA) is an important task in medical multi-modal Large Language Models (LLMs), aiming to answer clinically relevant questions regarding input medical images. This technique has the potential to improve the efficiency of medical professionals while relieving the burden on the public health system, particularly in resource-poor countries. However, existing medical VQA datasets are small and only contain simple questions (equivalent to classification tasks), which lack semantic reasoning and clinical knowledge. Our previous work proposed a clinical knowledge-driven image difference VQA benchmark using a rule-based approach (Hu et al., 2023). However, given the same breadth of information coverage, the rule-based approach shows an 85% error rate on extracted labels. We trained an LLM method to extract labels with 62% increased accuracy. We also comprehensively evaluated our labels with 2 clinical experts on 100 samples to help us fine-tune the LLM. Based on the trained LLM model, we proposed a large-scale medical VQA dataset, Medical-CXR-VQA, using LLMs focused on chest X-ray images. The questions involved detailed information, such as abnormalities, locations, levels, and types. Based on this dataset, we proposed a novel VQA method by constructing three different relationship graphs: spatial relationships, semantic relationships, and implicit relationship graphs on the image regions, questions, and semantic labels. We leveraged graph attention to learn the logical reasoning paths for different questions. These learned graph VQA reasoning paths can be further used for LLM prompt engineering and chain-of-thought, which are crucial for further fine-tuning and training multi-modal large language models. Moreover, we demonstrate that our approach has the qualities of evidence and faithfulness, which are crucial in the clinical field. The code and the dataset is available at https://github.com/Holipori/Medical-CXR-VQA.