Characterization of Ambroxol and Its Hydrochloride Salt Crystals by Bromine K-Edge X-Ray Absorption Near-Edge Structure Spectroscopy and X-Ray Crystal Structure Analysis.

Polymorphic crystals of ambroxol, forms I and II, and form A ambroxol hydrochloride crystals were characterized with bromine K-edge X-ray absorption near-edge structure (XANES) spectroscopy and single-crystal X-ray structure analysis. The XANES spectra had unique shapes depending on the crystal forms. Refined single-crystal structures revealed different interatomic interactions around bromine atoms, such as C-H…Br and N-H…Br hydrogen bonds, Br…O halogen bonds, and N-H…π interactions. Differences in these weak interactions could affect the electronic states of the bromines, resulting in differences in the XANES spectra. The results demonstrated that weak non-conventional interatomic interactions could alter the shape of XANES spectra. Hence, the spectra could be used for evaluating polymorphs of active pharmaceutical ingredients.

Spatiotemporal connectivity maps abnormal communication pathways in major depressive disorder underlying gamma oscillations.

Auditory steady-state response underlying gamma oscillations (gamma-ASSR) have been explored in patients with major depressive disorder (MDD), while ignoring the spatiotemporal dynamic characteristics. This study aims to construct dynamic directed brain networks to explore the disruption of spatiotemporal dynamics underlying gamma-ASSR in MDD. This study recruited 29 MDD patients and 30 healthy controls for a 40 Hz auditory steady-state evoked experiment. The propagation of gamma-ASSR was divided into early, middle, and late time interval. Partial directed coherence was applied to construct dynamic directed brain networks based on graph theory. The results showed that MDD patients had lower global efficiency and out-strength in temporal, parietal, and occipital regions over three time intervals. Additionally, distinct disrupted connectivity patterns occurred in different time intervals with abnormalities in the early and middle gamma-ASSR in left parietal regions cascading forward to produce dysfunction of frontal brain regions necessary to support gamma oscillations. Furthermore, the early and middle local efficiency of frontal regions were negatively correlated with symptom severity. These findings highlight patterns of hypofunction in the generation and maintenance of gamma-band oscillations across parietal-to-frontal regions in MDD patients, which provides novel insights into the neuropathological mechanism underlying gamma oscillations associated with aberrant brain network dynamics of MDD.

Associations between metabolic disorders and sleep disturbance in patients with schizophrenia.

BACKGROUND: Sleep disturbance plays a crucial role in mental illness and metabolic dysregulation. However, the clinical correlates of metabolic disorders (MD, only meeting 1 or 2 metabolic syndrome standards) and its relationship to sleep disturbance in patients with schizophrenia are uncertain. The study was to illuminate the association between MD and sleep disturbance in patients with schizophrenia. METHODS: One hundred and sixty-four patients with schizophrenia (157 drug-naive and 7 drug-free) were classified into 2 groups: MD and non-MD. The Pittsburgh Sleep Quality Index (PSQI) and the Positive and Negative Symptom Scale (PANSS) were employed to assess sleep quality and clinical symptoms. Weight, height, waistline, blood pressure, fasting glucose, and lipid metabolic levels were recorded. RESULTS: Sleep disturbance was more pronounced in the MD group compared to the non-MD group, including subjective sleep quality (z = -4.074, p = 0.000), sleep latency (z = -3.867, p = 0.000), sleep duration (z = -2.471, p = 0.013) and total scores (z = -3.074, p = 0.002). After controlling for confounding factors including age, sex, body mass index, smoking, marital status, and duration of illness, binary logistics regression showed that subjective sleep quality (p = 0.034) and sleep latency (p = 0.034) were significant independent predictors of MD. Further, partial correlation analysis showed that sleep latency (r = -0.200, p = 0.011) was significantly negatively correlated with HDLC. CONCLUSION: Our study suggests a high rate of MD in patients with schizophrenia, most of who were drug-naive, in a Chinese population. Longer sleep latency is associated with MD in schizophrenia patients, suggesting an important role of sleep disturbance in the development of MD in patients with schizophrenia. Interventions to improve sleep quality may prevent MD in patients with schizophrenia at an early stage.

Hypofunction of directed brain network within alpha frequency band in depressive patients: a graph-theoretic analysis.

Directed brain networks may provide new insights into exploring physiological mechanism and neuromarkers for depression. This study aims to investigate the abnormalities of directed brain networks in depressive patients. We constructed the directed brain network based on resting electroencephalogram for 19 depressive patients and 20 healthy controls with eyes closed and eyes open. The weighted directed brain connectivity was measured by partial directed coherence for α, ß, γ frequency band. Furthermore, topological parameters (clustering coefficient, characteristic path length, and et al.) were computed based on graph theory. The correlation between network metrics and clinical symptom was also examined. Depressive patients had a significantly weaker value of partial directed coherence at alpha frequency band in eyes-closed state. Clustering coefficient and characteristic path length were significantly lower in depressive patients (both p < .01). More importantly, in depressive patients, disruption of directed connectivity was noted in left-to-left (p < .05), right-to-left (p < .01) hemispheres and frontal-to-central (p < .01), parietal-to-central (p < .05), occipital-to-central (p < .05) regions. Furthermore, connectivity in LL and RL hemispheres was negatively correlated with depression scale scores (both p < .05). Depressive patients showed a more randomized network structure, disturbed directed interaction of left-to-left, right-to-left hemispheric information and between different cerebral regions. Specifically, left-to-left, right-to-left hemispheric connectivity was negatively correlated with the severity of depression. Our analysis may serve as a potential neuromarker of depression.

Direct detection of the crystal form of an active pharmaceutical ingredient in tablets by X-ray absorption fine structure spectroscopy.

Different crystal forms of active pharmaceutical ingredients (APIs) may display variations in physicochemical properties. During the drug development process, the definitive purpose is to maintain homogeneous quality in a single crystalline form. Hence, it is important to evaluate and understand the properties of each crystal form of APIs in pharmaceutics. In this study, forms 0, Ⅰ, Ⅱ, III of bromhexine hydrochloride, and form S of bromhexine were characterized by the commonly used methods X-ray powder diffraction, thermogravimetry-differential thermal analysis, and single crystal structure X-ray diffraction. Additionally, X-ray absorption fine structure spectroscopy (XAFS), a seldom used method in the pharmaceutics discipline was also applied to explore the chemical environment of bromine atoms in forms 0, Ⅰ, Ⅱ and S as well as chloride ions in forms 0 to Ⅱ. The XAFS spectra of each form were different from each of the other forms which indicated the chemical environment around target elements in the crystal polymorphs were distinct. Then, we measured the commercial bromhexine hydrochloride tablets with XAFS measurement and found that XAFS could distinguish the crystal form in the tablets. Hence, we demonstrated that XAFS measurements would be applicable as one of the methods for the direct detection of APIs in the tablets.

Alterations in Patients With First-Episode Depression in the Eyes-Open and Eyes-Closed Conditions: A Resting-State EEG Study.

Altered resting-state EEG activity has been repeatedly reported in major depressive disorder (MDD), but no robust biomarkers have been identified until now. The poor consistency of EEG alterations may be due to inconsistent resting conditions; that is, the eyes-open (EO) and eyes-closed (EC) conditions. Here, we explored the effect of the EO and EC conditions on EEG biomarkers for discriminating MDD subjects and healthy control (HC) subjects. EEG data were recorded from 30 first-episode MDD and 26 HC subjects during an 8-min resting-state session. The features were extracted using spectral power, Lempel-Ziv complexity, and detrended fluctuation analysis. Significant features were further selected via the sequential backward feature selection algorithm. Support vector machine (SVM), logistic regression, and linear discriminate analysis were used to determine a better resting condition to provide more reliable estimates for identifying MDD. Compared with the HC group, we found that the MDD group exhibited widespread increased ß and γ powers ( ) in both conditions. In the EO condition, the MDD group showed increased complexity and scaling exponents in the α band relative to HC subjects ( ). The best classification performance of the combined feature sets was found in the EO condition, with the leave-one-out classification accuracy of 89.29%, sensitivity of 90.00%, and specificity of 88.46% using SVM with the linear kernel classifier when the threshold was set to 0.7, followed by the ß and γ spectral features with an average accuracy of 83.93%. Overall, EO and EC conditions indeed affected the between-group variance, and the EO condition is suggested as the more separable resting condition to identify depression. Specially, the ß and γ powers are suggested as potential biomarkers for first-episode MDD.