Three new limonoids, chisomicines A-C (1-3), have been isolated from the bark of Chisocheton ceramicus. Their structures were determined by 2D NMR, CD spectroscopic methods, and X-ray analysis. Chisomicine A (1) exhibited NO production inhibitory activity in J774.1 cells stimulated by LPS dose-dependently at high cell viability.
Resveratrol, a natural stilbene found in grapes and wines exhibits a wide range of pharmacological properties. Resveratrol is also known as a good chemopreventive agent for inhibiting carcinogenesis processes that target kinases, cyclooxygenases, ribonucleotide reductase and DNA polymerases. A total of 19 analogues with an amide moiety were synthesized and the cytotoxic effects of the analogues on a series of human cancer cell lines are reported. Three compounds 6d, 6i and 6n showed potent cytotoxicity against prostate cancer DU-145 (IC50=16.68 µM), colon cancer HT-29 (IC50=7.51 µM) and breast cancer MCF-7 (IC50=21.24 µM), respectively, which are comparable with vinblastine. The resveratrol analogues were synthesized using the Heck method.
A phytochemical investigation of the methanolic extract of the bark of Endiandra kingiana led to the isolation of seven new tetracyclic endiandric acid analogues, kingianic acids A-G (1-7), together with endiandric acid M (8), tsangibeilin B (9) and endiandric acid (10). Their structures were determined by 1D- and 2D-NMR analysis in combination with HRMS experiments. The structure of compounds 9 and 10 were confirmed by single-crystal X-ray diffraction analysis. These compounds were screened for Bcl-xL and Mcl-1 binding affinities and cytotoxic activity on various cancer cell lines. Compound 5 showed moderate cytotoxic activity against human colorectal adeno-carcinoma (HT-29) and lung adenocarcinoma epithelial (A549) cell lines, with IC50 values in the range 15-17 µM, and compounds 3, 6 and 9 exhibited weak binding affinity for the anti-apoptotic protein Mcl-1.
Two new indole alkaloids, neolamarckines A and B (1, 2) were isolated from the leaves of Neolamarckia cadamba (Rubiaceae). Structural elucidation of 1 and 2 was performed by combination of 2D-NMR and circular dichroism (CD) spectra, and chemical correlations. Neolamarckine A (1) showed inhibition of inducible nitric oxide synthase (iNOS) dose dependently.
Eleven compounds:goniomicin A (1), goniomicin B (2), goniomicin C (3), goniomicin D (4), tapisoidin (5), goniothalamin (6), 9-deoxygoniopypyrone (7), pterodondiol (8), liriodenine (9), benzamide (10) and cinnamic acid (11), were isolated from the stem bark of Goniothalamus tapisoides. All compounds were identified by spectroscopic analysis and, for known compounds, by comparison with published data. Goniothalamin (6) exhibited mild cytotoxic activity towards a colon cancer cell line (HT-29), with an IC(50)value of 64.17 ± 5.60 µM. Goniomicin B (2) give the highest antioxidant activity in the DPPH assay among all compounds tested, with an IC(50) of 0.207 µM.
Centratherum anthelminticum (L.) Kuntze (scientific synonyms: Vernonia anthelmintica; black cumin) is one of the ingredients of an Ayurvedic preparation, called "Kayakalp", commonly applied to treat skin disorders in India and Southeast Asia. Despite its well known anti-inflammatory property on skin diseases, the anti-cancer effect of C. anthelminticum seeds on skin cancer is less documented. The present study aims to investigate the anti-cancer effect of Centratherum anthelminticum (L.) seeds chloroform fraction (CACF) on human melanoma cells and to elucidate the molecular mechanism involved.
Centratherum anthelminticum (L.) seeds (CA) is a well known medicinal herb in Indian sub-continent. We recently reported anti-oxidant property of chloroform fraction of Centratherum anthelminticum (L.) seeds (CACF) by inhibiting tumor necrosis factor-α (TNF-α)-induced growth of human breast cancer cells. However, the active compounds in CACF have not been investigated previously.
Pseuduvarines A (1) and B (2), two new dioxoaporphine alkaloids with an amino moiety, were isolated from the stem bark of Pseuduvaria rugosa and their structures were elucidated by combination of 2D-NMR spectroscopic analysis. Pseuduvarines A (1) and B (2) showed cytotoxicity against MCF7, HepG2, and HL-60 (1: IC₅₀, 0.9, 21.7, and >50.0 µM, respectively, 2: IC₅₀ >50.0, 15.7, and 12.4 µM, respectively).
A phytochemical study on the bark of Neisosperma oppositifolia (Apocynaceae) yielded two new beta-carboline indole alkaloids, oppositinines A (1) and B (2), together with five known alkaloids, isoreserpiline, isocarapanaubine, vobasine, 10-methoxydihydrocorynantheol-N-oxide, and ochropposinine oxindole. Structural elucidation of 1 and 2 was performed using 2D NMR methods. Oppositinines A (1) and B (2) showed potent vasorelaxant effects on the rat aorta.
The rhizomes of Zingiber spectabile yielded a new dimeric flavonol glycoside for which the name kaempferol-3-O-(4″-O-acetyl)-α-L-rhamnopyranoside-(I-6,II-8)-kaempferol-3-O-(4″-O-acetyl)-α-L-rhamnopyranoside; spectaflavoside A (1) was proposed, along with kaempferol and its four acetylrhamnosides (2-6), demethoxycurcumin (7) and curcumin (8). The structure of spectaflavoside A was elucidated by spectroscopic methods including, 1D and 2D NMR techniques. This is the first report on the occurrence of a dimeric flavonol glycoside in the Zingiberaceae and the second in nature. Spectaflavoside A was found to be a potent iron chelating agent.
Cognitive impairment and memory dysfunction following stroke diagnosis are common symptoms that significantly affect the survivors' quality of life. Stroke patients have a high potential to develop dementia within the first year of stroke onset. Currently, efforts are being exerted to assess stroke effects on the brain, particularly in the early stages. Numerous neuropsychological assessments are being used to evaluate and differentiate cognitive impairment and dementia following stroke. This article focuses on the role of available neuropsychological assessments in detection of dementia and memory loss after stroke. This review starts with stroke types and risk factors associated with dementia development, followed by a brief description of stroke diagnosis criteria and the effects of stroke on the brain that lead to cognitive impairment and end with memory loss. This review aims to combine available neuropsychological assessments to develop a post-stroke memory assessment (PSMA) scheme based on the most recognized and available studies. The proposed PSMA is expected to assess different types of memory functionalities that are related to different parts of the brain according to stroke location. An optimal therapeutic program that would help stroke patients enjoy additional years with higher quality of life is presented.
In addition to classic motor signs and symptoms, individuals with Parkinson's disease (PD) are characterized by emotional deficits. Ongoing brain activity can be recorded by electroencephalograph (EEG) to discover the links between emotional states and brain activity. This study utilized machine-learning algorithms to categorize emotional states in PD patients compared with healthy controls (HC) using EEG. Twenty non-demented PD patients and 20 healthy age-, gender-, and education level-matched controls viewed happiness, sadness, fear, anger, surprise, and disgust emotional stimuli while fourteen-channel EEG was being recorded. Multimodal stimulus (combination of audio and visual) was used to evoke the emotions. To classify the EEG-based emotional states and visualize the changes of emotional states over time, this paper compares four kinds of EEG features for emotional state classification and proposes an approach to track the trajectory of emotion changes with manifold learning. From the experimental results using our EEG data set, we found that (a) bispectrum feature is superior to other three kinds of features, namely power spectrum, wavelet packet and nonlinear dynamical analysis; (b) higher frequency bands (alpha, beta and gamma) play a more important role in emotion activities than lower frequency bands (delta and theta) in both groups and; (c) the trajectory of emotion changes can be visualized by reducing subject-independent features with manifold learning. This provides a promising way of implementing visualization of patient's emotional state in real time and leads to a practical system for noninvasive assessment of the emotional impairments associated with neurological disorders.
Parkinson's disease (PD) is not only characterized by its prominent motor symptoms but also associated with disturbances in cognitive and emotional functioning. The objective of the present study was to investigate the influence of emotion processing on inter-hemispheric electroencephalography (EEG) coherence in PD. Multimodal emotional stimuli (happiness, sadness, fear, anger, surprise, and disgust) were presented to 20 PD patients and 30 age-, education level-, and gender-matched healthy controls (HC) while EEG was recorded. Inter-hemispheric coherence was computed from seven homologous EEG electrode pairs (AF3-AF4, F7-F8, F3-F4, FC5-FC6, T7-T8, P7-P8, and O1-O2) for delta, theta, alpha, beta, and gamma frequency bands. In addition, subjective ratings were obtained for a representative of emotional stimuli. Interhemispherically, PD patients showed significantly lower coherence in theta, alpha, beta, and gamma frequency bands than HC during emotion processing. No significant changes were found in the delta frequency band coherence. We also found that PD patients were more impaired in recognizing negative emotions (sadness, fear, anger, and disgust) than relatively positive emotions (happiness and surprise). Behaviorally, PD patients did not show impairment in emotion recognition as measured by subjective ratings. These findings suggest that PD patients may have an impairment of inter-hemispheric functional connectivity (i.e., a decline in cortical connectivity) during emotion processing. This study may increase the awareness of EEG emotional response studies in clinical practice to uncover potential neurophysiologic abnormalities.
Deficits in the ability to process emotions characterize several neuropsychiatric disorders and are traits of Parkinson's disease (PD), and there is need for a method of quantifying emotion, which is currently performed by clinical diagnosis. Electroencephalogram (EEG) signals, being an activity of central nervous system (CNS), can reflect the underlying true emotional state of a person. This study applied machine-learning algorithms to categorize EEG emotional states in PD patients that would classify six basic emotions (happiness and sadness, fear, anger, surprise and disgust) in comparison with healthy controls (HC). Emotional EEG data were recorded from 20 PD patients and 20 healthy age-, education level- and sex-matched controls using multimodal (audio-visual) stimuli. The use of nonlinear features motivated by the higher-order spectra (HOS) has been reported to be a promising approach to classify the emotional states. In this work, we made the comparative study of the performance of k-nearest neighbor (kNN) and support vector machine (SVM) classifiers using the features derived from HOS and from the power spectrum. Analysis of variance (ANOVA) showed that power spectrum and HOS based features were statistically significant among the six emotional states (p < 0.0001). Classification results shows that using the selected HOS based features instead of power spectrum based features provided comparatively better accuracy for all the six classes with an overall accuracy of 70.10% ± 2.83% and 77.29% ± 1.73% for PD patients and HC in beta (13-30 Hz) band using SVM classifier. Besides, PD patients achieved less accuracy in the processing of negative emotions (sadness, fear, anger and disgust) than in processing of positive emotions (happiness, surprise) compared with HC. These results demonstrate the effectiveness of applying machine learning techniques to the classification of emotional states in PD patients in a user independent manner using EEG signals. The accuracy of the system can be improved by investigating the other HOS based features. This study might lead to a practical system for noninvasive assessment of the emotional impairments associated with neurological disorders.
While Parkinson's disease (PD) has traditionally been described as a movement disorder, there is growing evidence of disruption in emotion information processing associated with the disease. The aim of this study was to investigate whether there are specific electroencephalographic (EEG) characteristics that discriminate PD patients and normal controls during emotion information processing.
Madhupur forest area, Tangail is one of early human settlements in Bangladesh. Having abode in the vicinity of the forest, a strong ethnobotanical practice has prevailed in this area since ancient time. Due to the rapid deforestation during the last few decades, many plants have already disappeared or are facing extinction. Thus we attempted to document the medicinal plant use of Madhupur forest area with a view to preserve the ethnobotanical knowledge and in order to protect the biodiversity of this area.
Although an emotional deficit is a common finding in Parkinson's disease (PD), its neurobiological mechanism on emotion recognition is still unknown. This study examined the emotion processing deficits in PD patients using electroencephalogram (EEG) signals in response to multimodal stimuli.
A study on the leaves of Aglaia exima led to the isolation of one new and seven known compounds: six triterpenoids and two steroids. Their structures were elucidated and analyzed mainly by using spectroscopic methods; 1D and 2D NMR, mass spectrometry, UV spectrometry and X-ray. All the triterpenoids and steroids were measured in vitro for their cytotoxic activities against eight cancer cell lines; lung (A549), prostate (DU-145), skin (SK-MEL-5), pancreatic (BxPC-3), liver (Hep G2), colon (HT-29), breast (MCF-7) and (MDA-MB-231). The new cycloartane triterpenoid, 24(E)-cycloart-24-ene-26-ol-3-one 1, showed potent cytotoxic activity against colon (HT-29) cancer cell line (IC(50) 11.5μM).
Lipoxygenase (LOX)-inhibiting compounds from the leaves of Chisocheton polyandrus Merr. were isolated in this study using a bioactivity-guided fractionation technique. Two dammarane triterpenoids, dammara-20,24-dien-3-one (1) (IC(50)=0.69±0.07 μM) and 24-hydroxydammara-20,25-dien-3-one (2) (IC(50)=1.11±0.38 μM), were isolated and identified based on the soybean LOX assay. Dammara-20,24-dien-3-one (1) exhibited dual inhibition of both human 5-LOX (IC(50)=24.27±2.92 μM) and cyclooxygenase-2 (COX-2) (IC(50)=3.17±0.90 μM), whereas 24-hydroxydammara-20,25-dien-3-one (2) did not exhibit any significant inhibitory effects. This report is the first to detail the inhibition of LOX and COX by both C. polyandrus and its isolated compounds.
The leaves of the Phoebe scortechinii (Gamb.) Kochummen Comb. Nov. (Lauraceae), afforded one new proaporphine-tryptamine dimer; (-)-phoebescortechiniine (1), along with two known ones; phoebegrandine A and phoebegrandine B. The proaporphine, tetrahydropronuciferine (2), was isolated for the first time as a natural product. The alkaloids were elucidated primarily by means of high field NMR and HRMS.