The early detection of poststroke dementia (PSD) is important for medical practitioners to customize patient treatment programs based on cognitive consequences and disease severity progression. The aim is to diagnose and detect brain degenerative disorders as early as possible to help stroke survivors obtain early treatment benefits before significant mental impairment occurs. Neuropsychological assessments are widely used to assess cognitive decline following a stroke diagnosis. This study reviews the function of the available neuropsychological assessments in the early detection of PSD, particularly vascular dementia (VaD). The review starts from cognitive impairment and dementia prevalence, followed by PSD types and the cognitive spectrum. Finally, the most usable neuropsychological assessments to detect VaD were identified. This study was performed through a PubMed and ScienceDirect database search spanning the last 10 years with the following keywords: "post-stroke"; "dementia"; "neuro-psychological"; and "assessments". This study focuses on assessing VaD patients on the basis of their stroke risk factors and cognitive function within the first 3 months after stroke onset. The search strategy yielded 535 articles. After application of inclusion and exclusion criteria, only five articles were considered. A manual search was performed and yielded 14 articles. Twelve articles were included in the study design and seven articles were associated with early dementia detection. This review may provide a means to identify the role of neuropsychological assessments as early PSD detection tests.
This research proposes an exploratory study of a simple, accurate, and computationally efficient movement classification technique for prosthetic hand application. Surface myoelectric signals were acquired from the four muscles, namely, flexor carpi ulnaris, extensor carpi radialis, biceps brachii, and triceps brachii, of four normal-limb subjects. The signals were segmented, and the features were extracted with a new combined time-domain feature extraction method. Fuzzy C-means clustering method and scatter plot were used to evaluate the performance of the proposed multi-feature versus Hudgins' multi-feature. The movements were classified with a hybrid Adaptive Resonance Theory-based neural network. Comparative results indicate that the proposed hybrid classifier not only has good classification accuracy (89.09%) but also a significantly improved computation time.
Surface electromyography (SEMG) signals can provide important information for prosthetic hand control application. In this study, time domain (TD) features were used in extracting information from the SEMG signal in determining hand motions and stages of contraction (start, middle and end). Data were collected from ten healthy subjects. Two muscles, which are flexor carpi ulnaris (FCU) and extensor carpi radialis (ECR) were assessed during three hand motions of wrist flexion (WF), wrist extension (WE) and co-contraction (CC). The SEMG signals were first segmented into 132.5 ms windows, full wave rectified and filtered with a 6 Hz low pass Butterworth filter. Five TD features of mean absolute value, variance, root mean square, integrated absolute value and waveform length were used for feature extraction and subsequently patterns were determined. It is concluded that the TD features that were used are able to differentiate hand motions. However, for the stages of contraction determination, although there were patterns observed, it is determined that the stages could not be properly be differentiated due to the variability of signal strengths between subjects.
In this work, we report on the isolation of a phenol-degrading Rhodococcus sp. with a high tolerance towards phenol. The isolate was identified as Rhodococcus sp. strain AQ5NOL 2, based on 16S rDNA analysis. The strain degraded phenol using the meta pathway, a trait shared by many phenol-degraders. In addition to phenol biodegradation, the strain was also capable of degrading diesel. Strain AQ5NOL 2 exhibited a broad optimum temperature for growth on phenol at between 20 °C and 35 °C. The best nitrogen sources were ammonium sulphate, glycine or phenylalanine, followed by proline, nitrate, leucine, and alanine (in decreasing efficiency). Strain AQ5NOL 2 showed a high tolerance and degradation capacity of phenol, for it was able to register growth in the presence of 2000 mg l(-1) phenol. The growth of this strain on phenol as sole carbon and energy source were modeled using Haldane kinetics with a maximal specific growth rate (μ(max)) of 0.1102 hr(-1), a half-saturation constant (K(s) ) of 99.03 mg l(-1) or 1.05 mmol l(-1), and a substrate inhibition constant (K(i)) of 354 mg l(-1) or 3.76 mmol l(-1). Aside from phenol, the strain could utilize diesel, 2,4-dinitrophenol and ρ-cresol as carbon sources for growth. Strain AQ5NOL 2 exhibited inhibition of phenol degradation by Zn(2+), Cu(2+), Cr(6+), Ag(+) and Hg(2+) at 1 mg l(-1).
In the present study, the construction of arrays on silicon for naked-eye detection of DNA dengue was demonstrated. The array was created by exposing a polyethylene glycol (PEG) silane monolayer to 254 nm ultraviolet (UV) light through a photomask. Formation of the PEG silane monolayer and photomodifed surface properties was thoroughly characterized by using atomic force microscopy (AFM), X-ray photoelectron spectroscopy (XPS), and contact angle measurements. The results of XPS confirmed that irradiation of ultraviolet (UV) light generates an aldehyde functional group that offers conjugation sites of amino DNA probe for detection of a specific dengue virus target DNA. Employing a gold enhancement process after inducing the electrostatic interaction between positively charged gold nanoparticles and the negatively charged target DNA hybridized to the DNA capture probe allowed to visualize the array with naked eye. The developed arrays demonstrated excellent performance in diagnosis of dengue with a detection limit as low as 10 pM. The selectivity of DNA arrays was also examined using a single base mismatch and noncomplementary target DNA.
Despite established country's tobacco control law, cigarette smoking by the young people and the magnitude of nicotine dependence among the students is alarming in Bangladesh. This study was aimed to determine the prevalence of smoking and factors influencing it among the secondary school students. A two-stage cluster sampling was used for selection of schools with probability proportional to enrollment size followed by stratified random sampling of government and private schools. The 70-item questionnaire included 'core GYTS' (Global Youth Tobacco Survey) and other additional questions were used to collect relevant information. Analysis showed that the prevalence of smoking was 12.3% among boys and 4.5% among girls, respectively. The mean age at initiation of smoking was 10.8 years with standard deviation of 2.7 years. Logistic regression analysis revealed that boys are 2.282 times likely to smoked than girls and it was 1.786 times higher among the students aged 16 years and above than their younger counterparts. Smoking by teachers appeared to be the strong predictor for students smoking behaviour (OR 2.206, 95% CI: 1.576, 3.088) followed by peer influence (OR 1.988, 95% CI: 1.178, 3.356). Effective smoking prevention program should to be taken to reduce smoking behaviour. The school curricula had less impact in preventing smoking except teacher's smoking behaviour.
Inflammation and oxidative stress are believed to contribute to the pathology of several chronic diseases including hypercholesterolemia (elevated levels of cholesterol in blood) and atherosclerosis. HMG-CoA reductase inhibitors of plant origin are needed as synthetic drugs, such as statins, which are known to cause adverse effects on the liver and muscles. Amaranthus viridis (A. viridis) has been used from ancient times for its supposedly medically beneficial properties. In the current study, different parts of A. viridis (leaf, stem, and seed) were evaluated for potential anti-HMG-CoA reductase, antioxidant, and anti-inflammatory activities. The putative HMG-CoA reductase inhibitory activity of A. viridis extracts at different concentrations was determined spectrophotometrically by NADPH oxidation, using HMG-CoA as substrate. A. viridis leaf extract revealed the highest HMG-CoA reductase inhibitory effect at about 71%, with noncompetitive inhibition in Lineweaver-Burk plot analysis. The leaf extract showed good inhibition of hydroperoxides, 2,2-diphenyl-1-picrylhydrazyl (DPPH), nitric oxide (NO), and ferric ion radicals in various concentrations. A. viridis leaf extract was proven to be an effective inhibitor of hyaluronidase, lipoxygenase, and xanthine oxidase enzymes. The experimental data suggest that A. viridis leaf extract is a source of potent antioxidant and anti-inflammatory agent and may modulate cholesterol metabolism by inhibition of HMG-CoA reductase.
The enzyme 3-hydroxy-3-methyl-glutaryl-coenzyme A (HMG-CoA) reductase is the key enzyme of the mevalonate pathway that produces cholesterol. Inhibition of HMG-CoA reductase reduces cholesterol biosynthesis in the liver. Synthetic drugs, statins, are commonly used for the treatment of hypercholesterolemia. Due to the side effects of statins, natural HMG-CoA reductase inhibitors of plant origin are needed. In this study, 25 medicinal plant methanol extracts were screened for anti-HMG-CoA reductase activity. Basella alba leaf extract showed the highest inhibitory effect at about 74%. Thus, B. alba was examined in order to investigate its phytochemical components. Gas chromatography with tandem mass spectrometry and reversed phase high-performance liquid chromatography analysis revealed the presence of phenol 2,6-bis(1,1-dimethylethyl), 1-heptatriacotanol, oleic acid, eicosyl ester, naringin, apigenin, luteolin, ascorbic acid, and α-tocopherol, which have been reported to possess antihypercholesterolemic effects. Further investigation of in vivo models should be performed in order to confirm its potential as an alternative treatment for hypercholesterolemia and related cardiovascular diseases.
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.
Crude extract of ChE from the liver of Puntius javanicus was purified using procainamide-sepharyl 6B. S-Butyrylthiocholine iodide (BTC) was selected as the specific synthetic substrate for this assay with the highest maximal velocity and lowest biomolecular constant at 53.49 µmole/min/mg and 0.23 mM, respectively, with catalytic efficiency ratio of 0.23. The optimum parameter was obtained at pH 7.5 and optimal temperature in the range of 25 to 30°C. The effect of different storage condition was assessed where ChE activity was significantly decreased after 9 days of storage at room temperature. However, ChE activity showed no significant difference when stored at 4.0, 0, and -25°C for 15 days. Screening of heavy metals shows that chromium, copper, and mercury strongly inhibited P. javanicus ChE by lowering the activity below 50%, while several pairwise combination of metal ions exhibited synergistic inhibiting effects on the enzyme which is greater than single exposure especially chromium, copper, and mercury. The results showed that P. javanicus ChE has the potential to be used as a biosensor for the detection of metal ions.
The early detection and classification of dementia are important clinical support tasks for medical practitioners in customizing patient treatment programs to better manage the development and progression of these diseases. Efforts are being made to diagnose these neurodegenerative disorders in the early stages. Indeed, early diagnosis helps patients to obtain the maximum treatment benefit before significant mental decline occurs. The use of electroencephalogram as a tool for the detection of changes in brain activities and clinical diagnosis is becoming increasingly popular for its capabilities in quantifying changes in brain degeneration in dementia. This paper reviews the role of electroencephalogram as a biomarker based on signal processing to detect dementia in early stages and classify its severity. The review starts with a discussion of dementia types and cognitive spectrum followed by the presentation of the effective preprocessing denoising to eliminate possible artifacts. It continues with a description of feature extraction by using linear and nonlinear techniques, and it ends with a brief explanation of vast variety of separation techniques to classify EEG signals. This paper also provides an idea from the most popular studies that may help in diagnosing dementia in early stages and classifying through electroencephalogram signal processing and analysis.
Atherosclerosis is the process of hardening and narrowing the arteries. Atherosclerosis is generally associated with cardiovascular diseases such as strokes, heart attacks, and peripheral vascular diseases. Since the usage of the synthetic drug, statins, leads to various side effects, the plants flavonoids with antiartherosclerotic activity gained much attention and were proven to reduce the risk of atherosclerosis in vitro and in vivo based on different animal models. The flavonoids compounds also exhibit lipid lowering effects and anti-inflammatory and antiatherogenic properties. The future development of flavonoids-based drugs is believed to provide significant effects on atherosclerosis and its related diseases. This paper discusses the antiatherosclerotic effects of selected plant flavonoids such as quercetin, kaempferol, myricetin, rutin, naringenin, catechin, fisetin, and gossypetin.
Hypercholesterolemia is the major risk factor that leads to atherosclerosis. Nowadays, alternative treatment using medicinal plants gained much attention since the usage of statins leads to adverse health effects, especially liver and muscle toxicity. This study was designed to investigate the hypocholesterolemic and antiatherosclerotic effects of Basella alba (B. alba) using hypercholesterolemia-induced rabbits. Twenty New Zealand white rabbits were divided into 5 groups and fed with varying diets: normal diet, 2% high cholesterol diet (HCD), 2% HCD + 10 mg/kg simvastatin, 2% HCD + 100 mg/kg B. alba extract, and 2% HCD + 200 mg/kg B. alba extract, respectively. The treatment with B. alba extract significantly lowered the levels of total cholesterol, LDL, and triglycerides and increased HDL and antioxidant enzymes (SOD and GPx) levels. The elevated levels of liver enzymes (AST and ALT) and creatine kinase were noted in hypercholesterolemic and statin treated groups indicating liver and muscle injuries. Treatment with B. alba extract also significantly suppressed the aortic plaque formation and reduced the intima: media ratio as observed in simvastatin-treated group. This is the first in vivo study on B. alba that suggests its potential as an alternative therapeutic agent for hypercholesterolemia and atherosclerosis.
In a previous study, we isolated Leifsonia sp. strain SIU, a new bacterium from agricultured soil. The bacterium was tested for its ability to degrade caffeine. The isolate was encapsulated in gellan gum and its ability to degrade caffeine was compared with the free cells. The optimal caffeine degradation was attained at a gellan gum concentration of 0.75% (w/v), a bead size of 4 mm diameter, and 250 beads per 100 mL of medium. At a caffeine concentration of 0.1 g/L, immobilised cells of the strain SIU degraded caffeine within 9 h, which is faster when compared to the case of free cells, in which it took 12 h to degrade. The immobilised cells degraded caffeine completely within 39 and 78 h at 0.5 and 1.0 g/L, while the free cells took 72 and 148 h at 0.5 and 1.0 g/L, respectively. At higher caffeine concentrations, immobilised cells exhibited a higher caffeine degradation rate. At concentrations of 1.5 and 2.0 g/L, caffeine-degrading activities of both immobilised and free cells were inhibited. The immobilised cells showed no loss in caffeine-degrading activity after being used repeatedly for nine 24-h cycles. The effect of heavy metals on immobilised cells was also tested. This study showed an increase in caffeine degradation efficiency when the cells were encapsulated in gellan gum.
We performed a comparative study to select the efficient mother wavelet (MWT) basis functions that optimally represent the signal characteristics of the electrical activity of the human brain during a working memory (WM) task recorded through electro-encephalography (EEG). Nineteen EEG electrodes were placed on the scalp following the 10-20 system. These electrodes were then grouped into five recording regions corresponding to the scalp area of the cerebral cortex. Sixty-second WM task data were recorded from ten control subjects. Forty-five MWT basis functions from orthogonal families were investigated. These functions included Daubechies (db1-db20), Symlets (sym1-sym20), and Coiflets (coif1-coif5). Using ANOVA, we determined the MWT basis functions with the most significant differences in the ability of the five scalp regions to maximize their cross-correlation with the EEG signals. The best results were obtained using "sym9" across the five scalp regions. Therefore, the most compatible MWT with the EEG signals should be selected to achieve wavelet denoising, decomposition, reconstruction, and sub-band feature extraction. This study provides a reference of the selection of efficient MWT basis functions.
A molybdenum-reducing bacterium from Antarctica has been isolated. The bacterium converts sodium molybdate or Mo⁶⁺ to molybdenum blue (Mo-blue). Electron donors such as glucose, sucrose, fructose, and lactose supported molybdate reduction. Ammonium sulphate was the best nitrogen source for molybdate reduction. Optimal conditions for molybdate reduction were between 30 and 50 mM molybdate, between 15 and 20°C, and initial pH between 6.5 and 7.5. The Mo-blue produced had a unique absorption spectrum with a peak maximum at 865 nm and a shoulder at 710 nm. Respiratory inhibitors such as antimycin A, sodium azide, potassium cyanide, and rotenone failed to inhibit the reducing activity. The Mo-reducing enzyme was partially purified using ion exchange and gel filtration chromatography. The partially purified enzyme showed optimal pH and temperature for activity at 6.0 and 20°C, respectively. Metal ions such as cadmium, chromium, copper, silver, lead, and mercury caused more than 95% inhibition of the molybdenum-reducing activity at 0.1 mM. The isolate was tentatively identified as Pseudomonas sp. strain DRY1 based on partial 16s rDNA molecular phylogenetic assessment and the Biolog microbial identification system. The characteristics of this strain would make it very useful in bioremediation works in the polar and temperate countries.
Bacteria with the ability to tolerate, remove, and/or degrade several xenobiotics simultaneously are urgently needed for remediation of polluted sites. A previously isolated bacterium with sodium dodecyl sulfate- (SDS-) degrading capacity was found to be able to reduce molybdenum to the nontoxic molybdenum blue. The optimal pH, carbon source, molybdate concentration, and temperature supporting molybdate reduction were pH 7.0, glucose at 1.5% (w/v), between 25 and 30 mM, and 25°C, respectively. The optimum phosphate concentration for molybdate reduction was 5 mM. The Mo-blue produced exhibits an absorption spectrum with a maximum peak at 865 nm and a shoulder at 700 nm. None of the respiratory inhibitors tested showed any inhibition to the molybdenum-reducing activity suggesting that the electron transport system of this bacterium is not the site of molybdenum reduction. Chromium, cadmium, silver, copper, mercury, and lead caused approximately 77, 65, 77, 89, 80, and 80% inhibition of the molybdenum-reducing activity, respectively. Ferrous and stannous ions markedly increased the activity of molybdenum-reducing activity in this bacterium. The maximum tolerable concentration of SDS as a cocontaminant was 3 g/L. The characteristics of this bacterium make it a suitable candidate for molybdenum bioremediation of sites cocontaminated with detergent pollutant.
Although nanoparticle-enhanced biosensors have been extensively researched, few studies have systematically characterized the roles of nanoparticles in enhancing biosensor functionality. This paper describes a successful new method in which DNA binds directly to iron oxide nanoparticles for use in an optical biosensor. A wide variety of nanoparticles with different properties have found broad application in biosensors because their small physical size presents unique chemical, physical, and electronic properties that are different from those of bulk materials. Of all nanoparticles, magnetic nanoparticles are proving to be a versatile tool, an excellent case in point being in DNA bioassays, where magnetic nanoparticles are often used for optimization of the hybridization and separation of target DNA. A critical step in the successful construction of a DNA biosensor is the efficient attachment of biomolecules to the surface of magnetic nanoparticles. To date, most methods of synthesizing these nanoparticles have led to the formation of hydrophobic particles that require additional surface modifications. As a result, the surface to volume ratio decreases and nonspecific bindings may occur so that the sensitivity and efficiency of the device deteriorates. A new method of large-scale synthesis of iron oxide (Fe3O4) nanoparticles which results in the magnetite particles being in aqueous phase, was employed in this study. Small modifications were applied to design an optical DNA nanosensor based on sandwich hybridization. Characterization of the synthesized particles was carried out using a variety of techniques and CdSe/ZnS core-shell quantum dots were used as the reporter markers in a spectrofluorophotometer. We showed conclusively that DNA binds to the surface of ironoxide nanoparticles without further surface modifications and that these magnetic nanoparticles can be efficiently utilized as biomolecule carriers in biosensing devices.
A locally isolated Acinetobacter sp. Strain AQ5NOL 1 was encapsulated in gellan gum and its ability to degrade phenol was compared with the free cells. Optimal phenol degradation was achieved at gellan gum concentration of 0.75% (w/v), bead size of 3 mm diameter (estimated surface area of 28.26 mm(2)) and bead number of 300 per 100 ml medium. At phenol concentration of 100 mg l(-1), both free and immobilized bacteria exhibited similar rates of phenol degradation but at higher phenol concentrations, the immobilized bacteria exhibited a higher rate of degradation of phenol. The immobilized cells completely degrade phenol within 108, 216 and 240 h at 1,100, 1,500 and 1,900 mg l(-1) phenol, respectively, whereas free cells took 240 h to completely degrade phenol at 1,100 mg l(-1). However, the free cells were unable to completely degrade phenol at higher concentrations. Overall, the rates of phenol degradation by both immobilized and free bacteria decreased gradually as the phenol concentration was increased. The immobilized cells showed no loss in phenol degrading activity after being used repeatedly for 45 cycles of 18 h cycle. However, phenol degrading activity of the immobilized bacteria experienced 10 and 38% losses after the 46 and 47th cycles, respectively. The study has shown an increased efficiency of phenol degradation when the cells are encapsulated in gellan gum.