Hydrocarbon pollution is widespread around the globe and, even in the remoteness of Antarctica, the impacts of hydrocarbons from anthropogenic sources are still apparent. Antarctica's chronically cold temperatures and other extreme environmental conditions reduce the rates of biological processes, including the biodegradation of pollutants. However, the native Antarctic microbial diversity provides a reservoir of cold-adapted microorganisms, some of which have the potential for biodegradation. This study evaluated the diesel hydrocarbon-degrading ability of a psychrotolerant marine bacterial consortium obtained from the coast of the north-west Antarctic Peninsula. The consortium's growth conditions were optimised using one-factor-at-a-time (OFAT) and statistical response surface methodology (RSM), which identified optimal growth conditions of pH 8.0, 10 °C, 25 ppt NaCl and 1.5 g/L NH4NO3. The predicted model was highly significant and confirmed that the parameters' salinity, temperature, nitrogen concentration and initial diesel concentration significantly influenced diesel biodegradation. Using the optimised values generated by RSM, a mass reduction of 12.23 mg/mL from the initial 30.518 mg/mL (4% (w/v)) concentration of diesel was achieved within a 6 d incubation period. This study provides further evidence for the presence of native hydrocarbon-degrading bacteria in non-contaminated Antarctic seawater.
Although the application of sub-sensory mechanical noise to the soles of the feet has been shown to enhance balance, there has been no study on how the bandwidth of the noise affects balance. Here, we report a single-blind randomized controlled study on the effects of a narrow and wide bandwidth mechanical noise on healthy young subjects' sway during quiet standing on firm and compliant surfaces. For the firm surface, there was no improvement in balance for both bandwidths-this may be because the young subjects could already balance near-optimally or optimally on the surface by themselves. For the compliant surface, balance improved with the introduction of wide but not narrow bandwidth noise, and balance is improved for wide compared to narrow bandwidth noise. This could be explained using a simple model, which suggests that adding noise to a sub-threshold pressure stimulus results in markedly different frequency of nerve impulse transmitted to the brain for the narrow and wide bandwidth noise-the frequency is negligible for the former but significantly higher for the latter. Our results suggest that if a person's standing balance is not optimal (for example, due to aging), it could be improved by applying a wide bandwidth noise to the feet.
Antarctica is a relatively pristine continent that attracts scientists and tourists alike. However, the risk of environmental pollution in Antarctica is increasing with the increase in the number of visitors. Recently, there has been a surge in interest regarding diesel, heavy metals and microplastics pollution. Contamination from these pollutants poses risks to the environment and the health of organisms inhabiting the continent. Penguins are one of the most prominent and widely distributed animals in Antarctica and are at major risk due to pollution. Even on a small scale, the impacts of pollution toward penguin populations are extensive. This review discusses the background of penguins in Antarctica, the anthropogenic pollution and cases, as well as the impacts of diesel, heavy metals and microplastics toxicities on penguins. The trends of the literature for the emerging risks of these pollutants are also reviewed through a bibliometric approach and network mapping analysis. A sum of 27 articles are analyzed on the effects of varying pollutants on penguins in Antarctica from 2000 to 2020 using the VOSviewer bibliometric software, Microsoft Excel and Tableau Public. Research articles collected from the Scopus database are evaluated for the most applicable research themes according to the bibliometric indicators (articles, geography distribution, annual production, integrated subject areas, key source journals and keyword or term interactions). Although bibliometric studies on the present research theme are not frequent, our results are sub-optimal due to the small number of search query matches from the Scopus database. As a result, our findings offer only a fragmentary comprehension of the topics in question. Nevertheless, this review provides valuable inputs regarding prospective research avenues for researchers to pursue in the future.
Petroleum pollution is a major concern in Antarctica due to the persistent nature of its hydrocarbon components coupled with the region's extreme environmental conditions, which means that bioremediation approaches are largely inapplicable at present. The current study assessed the ability of the psychrotolerant phenol-degrader, Rhodococcus sp. strain AQ5-07, to assimilate diesel fuel as the sole carbon source. Factors expected to influence the efficiency of diesel degradation, including the initial hydrocarbon concentration, nitrogen source concentration and type, temperature, pH and salinity were studied. Strain AQ5-07 displayed optimal cell growth and biodegradation activity at 1% v/v initial diesel concentration, 1 g/L NH4Cl concentration, pH 7 and 1% NaCl during one-factor-at-a-time (OFAT) analyses. Strain AQ5-07 was psychrotolerant based on its optimum growth temperature being near 20 °C. In conventionally optimised media, strain AQ5-07 showed total petroleum hydrocarbons (TPH) mineralisation of 75.83%. However, the optimised condition for TPH mineralisation predicted through statistical response surface methodology (RSM) enhanced the reduction to 90.39% within a 2 days incubation. Our preliminary data support strain AQ5-07 being a potential candidate for real-field soil bioremediation by specifically adopting sludge-phase bioreactor system in chronically cold environments such as Antarctica. The study also confirmed the utility of RSM in medium optimisation.
The herbicide glyphosate is often used to control weeds in agricultural lands. However, despite its ability to effectively kill weeds at low cost, health problems are still reported due to its toxicity level. The removal of glyphosate from the environment is usually done by microbiological process since chemical process of degradation is ineffective due to the presence of highly stable bonds. Therefore, finding glyphosate-degrading microorganisms in the soil of interest is crucial to remediate this glyphosate.Burkholderia vietnamiensisstrain AQ5-12 was found to have glyphosate-degrading ability. Optimisation of biodegradation condition was carried out utilising one factor at a time (OFAT) and response surface methodology (RSM). Five parameters including carbon and nitrogen source, pH, temperature and glyphosate concentration were optimised. Based on OFAT result, glyphosate degradation was observed to be optimum at fructose concentration of 6, 0.5 g/L ammonia sulphate, pH 6.5, temperature of 32 °C and glyphosate concentration at 100 ppm. Meanwhile, RSM resulted in a better degradation with 92.32% of 100 ppm glyphosate compared to OFAT. The bacterium was seen to tolerate up to 500 ppm glyphosate while increasing concentration results in reduced degradation and bacterial growth rate.
Suitable extraction technique and the least cost while reducing the environmental impact is the primary concern in timber transportation planning in undulate topography. Two types of extraction machines with unique characteristics to be applied in timber harvest area in Malaysia is combined for timber harvesting with the aim each machine will extract timber suitable to their ability. A Bees Algorithm (BA) was proposed to find an optimum TTP for timber extraction, forest road, and landing locations with grid cell-sized 10 m × 10 m and attributed with fixed and variable costs. The result shows the log fisher (1351 timbers) as a preferable extraction technique with total cost of RM 86,551.73 than the crawler tractor (206 timbers); the timber extraction route is 2630 m for the log fisher and 9860 m for the crawler tractor with total cost of RM 10,453.03. The model finds a suitable timber extraction technique and estimates the extraction costs. Further studies are required to compare the BA with other optimization methods for better results.
An Antarctic soil bacterial consortium (reference BS14) was confirmed to biodegrade canola oil, and kinetic studies on this biodegradation were carried out. The purpose of this study was to examine the ability of BS14 to produce biosurfactants during the biodegradation of canola oil. Secondary mathematical equations were chosen for kinetic analyses (Monod, Haldane, Teissier-Edwards, Aiba and Yano models). At the same time, biosurfactant production was confirmed through a preliminary screening test and further optimised using response surface methodology (RSM). Mathematical modelling demonstrated that the best-fitting model was the Haldane model for both waste (WCO) and pure canola oil (PCO) degradation. Kinetic parameters including the maximum degradation rate (μmax) and maximum concentration of substrate tolerated (Sm) were obtained. For WCO degradation these were 0.365 min-1 and 0.308%, respectively, while for PCO they were 0.307 min-1 and 0.591%, respectively. The results of all preliminary screenings for biosurfactants were positive. BS14 was able to produce biosurfactant concentrations of up to 13.44 and 14.06 mg/mL in the presence of WCO and PCO, respectively, after optimisation. The optimum values for each factor were determined using a three-dimensional contour plot generated in a central composite design, where a combination of 0.06% salinity, pH 7.30 and 1.55% initial substrate concentration led to the highest biosurfactant production when using WCO. Using PCO, the highest biosurfactant yield was obtained at 0.13% salinity, pH 7.30 and 1.25% initial substrate concentration. This study could help inform the development of large-scale bioremediation applications, not only for the degradation of canola oil but also of other hydrocarbons in the Antarctic by utilising the biosurfactants produced by BS14.
In sports, fatigue management is vital as adequate rest builds strength and enhances performance, whereas inadequate rest exposes the body to prolonged fatigue (PF) or also known as overtraining. This paper presents PF identification and classification based on surface electromyography (EMG) signals. An experiment was performed on twenty participants to investigate the behaviour of surface EMG during the inception of PF. PF symptoms were induced in accord with a five-day Bruce Protocol treadmill test on four lower extremity muscles: the biceps femoris (BF), rectus femoris (RF), vastus medialis (VM), and vastus lateralis (VL). The results demonstrate that the experiment successfully induces soreness, unexplained lethargy, and performance decrement and also indicate that the progression of PF can be observed based on changes in frequency features (ΔF med and ΔF mean) and time features (ΔRMS and ΔMAV) of surface EMG. This study also demonstrates the ability of wavelet index features in PF identification. Using a naïve Bayes (NB) classifier exhibits the highest accuracy based on time and frequency features with 98% in distinguishing PF on RF, 94% on BF, 9% on VL, and 97% on VM. Thus, this study has positively indicated that surface EMG can be used in identifying the inception of PF. The implication of the findings is significant in sports to prevent a greater risk of PF.
With the progressive increase in human activities in the Antarctic region, the possibility of domestic oil spillage also increases. Developing means for the removal of oils, such as canola oil, from the environment and waste "grey" water using biological approaches is therefore desirable, since the thermal process of oil degradation is expensive and ineffective. Thus, in this study an indigenous cold-adapted Antarctic soil bacterium, Rhodococcus erythropolis strain AQ5-07, was screened for biosurfactant production ability using the multiple approaches of blood haemolysis, surface tension, emulsification index, oil spreading, drop collapse and "MATH" assay for cellular hydrophobicity. The growth kinetics of the bacterium containing different canola oil concentration was studied. The strain showed β-haemolysis on blood agar with a high emulsification index and low surface tension value of 91.5% and 25.14 mN/m, respectively. Of the models tested, the Haldane model provided the best description of the growth kinetics, although several models were similar in performance. Parameters obtained from the modelling were the maximum specific growth rate (qmax), concentration of substrate at the half maximum specific growth rate, Ks% (v/v) and the inhibition constant Ki% (v/v), with values of 0.142 h-1, 7.743% (v/v) and 0.399% (v/v), respectively. These biological coefficients are useful in predicting growth conditions for batch studies, and also relevant to "in field" bioremediation strategies where the concentration of oil might need to be diluted to non-toxic levels prior to remediation. Biosurfactants can also have application in enhanced oil recovery (EOR) under different environmental conditions.
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.
Hydrocarbons can cause pollution to Antarctic terrestrial and aquatic ecosystems, both through accidental release and the discharge of waste cooking oil in grey water. Such pollutants can persist for long periods in cold environments. The native microbial community may play a role in their biodegradation. In this study, using mixed native Antarctic bacterial communities, several environmental factors influencing biodegradation of waste canola oil (WCO) and pure canola oil (PCO) were optimised using established one-factor-at-a-time (OFAT) and response surface methodology (RSM) approaches. The factors include salinity, pH, type of nitrogen and concentration, temperature, yeast extract and initial substrate concentration in OFAT and only the significant factors proceeded for the statistical optimisation through RSM. High concentration of substrate targeted for degradation activity through RSM compared to OFAT method. As for the result, all factors were significant in PBD, while only 4 factors were significant in biodegradation of PCO (pH, nitrogen concentration, yeast extract and initial substrate concentration). Using OFAT, the most effective microbial community examined was able to degrade 94.42% and 86.83% (from an initial concentration of 0.5% (v/v)) of WCO and PCO, respectively, within 7 days. Using RSM, 94.99% and 79.77% degradation of WCO and PCO was achieved in 6 days. The significant interaction for the RSM in biodegradation activity between temperature and WCO concentration in WCO media were exhibited. Meanwhile, in biodegradation of PCO the significant factors were between (1) pH and PCO concentration, (2) nitrogen concentration and yeast extract, (3) nitrogen concentration and PCO concentration. The models for the RSM were validated for both WCO and PCO media and it showed no significant difference between experimental and predicted values. The efficiency of canola oil biodegradation achieved in this study provides support for the development of practical strategies for efficient bioremediation in the Antarctic environment.
In Antarctica, human activities have been reported to be the major cause of the accumulation of heavy metal contaminants. A comprehensive bibliometric analysis of publications on heavy metal contamination in Antarctica from year 2000 to 2020 was performed to obtain an overview of the current landscape in this line of research. A total of 106 documents were obtained from Scopus, the largest citation database. Extracted data were analysed, and VOSviewer software was used to visualise trends. The result showed an increase in publications and citations in the past 20 years indicating the rising interest on heavy metal contamination in the Antarctic region. Based on the analysis of keywords, the publications largely discuss various types of heavy metals found in the Antarctic water and sediment. The analysis on subject areas detects multiple disciplines involved, wherein the environmental science was well-represented. The top countries and authors producing the most publication in this field were from Australia, China, Brazil and Chile. Numerous efforts have been exercised to investigate heavy metal pollution and its mitigation approaches in the region in the past decades. This paper not only is relevant for scholars to understand the development status and trends in this field but also offers clear insights on the future direction of Antarctic heavy metal contamination and remediation research.
Oil spill incidents are hazardous and have prolonged damage to the marine environment. Management and spill clean-up procedures are practical and rapid, with several shortcomings. Coco peat (CP) and coco fibre (CF) are refined from coconut waste, and their abundance makes them desirable for diesel spillage treatment. Using a filter-based system, the selectivity of coco peat sorbent was tested using CP, CF and peat-fibre mix (CPM). CP exhibited maximal diesel sorption capacity with minimal seawater uptake, thus being selected for further optimisation analysis. The heat treatment considerably improved the sorption capacity and efficiency of diesel absorbed by CP, as supported by FTIR and VPSEM-EDX analysis. Conventional one-factor-at-a-time (OFAT) examined the performance of diesel sorption by CP under varying parameters, namely temperature, time of heating, packing density and diesel concentration. The significant factors were statistically evaluated using response surface methodology (RSM) via Plackett-Burman design (PB) and central composite design (CCD). Three significant (p < 0.05) factors (time, packing density and diesel concentration) were identified by PB and further analysed for interactions among the parameters. CCD predicted efficiency of diesel absorbed at 59.92% (71.90 mL) (initial diesel concentration of 30% v/v) and the experimental model validated the design with 59.17% (71.00 mL) diesel sorbed at the optimised conditions of 14.1 min of heating (200 °C) with packing density of 0.08 g/cm3 and 30% (v/v) of diesel concentration. The performance of CP in RSM (59.17%) was better than that in OFAT (58.33%). The discoveries imply that natural sorbent materials such as CP in oil spill clean-up operations can be advantageous and environmentally feasible. This study also demonstrated the diesel-filter system as a pilot study for the prospective up-scale application of oil spills.
In response to the rising number of COVID-19-related deaths among older adults in Malaysia, observation concerning COVID-19-related mortality among older adults is of urgent public health importance. This study presents a review of the COVID-19-related death cases among older adults in Malaysia. Clinical and social demographic data of death cases officially released by the Ministry of Health Malaysia were reviewed. As of 12 June 2020, 81 older adult death cases were identified and included in this study. The mean age of the death cases was 71.88 years old. Even though 79% of these cases were male, gender was not likely to be associated with mortality. A substantial difference between the prevalence of diabetes among death cases and the nationwide population indicated that diabetes was more likely to be associated with mortality. Most of the studied deaths were individuals with pre-existing medical conditions, predominantly diabetes and hypertension, and those aged 70 years old or above. The mean time from hospitalisation to death was 11.83 days. Extra focus should be given to older adults in the prevention and control of COVID-19.
Electromyography (EMG)-based control is the core of prostheses, orthoses, and other rehabilitation devices in recent research. Nonetheless, EMG is difficult to use as a control signal given the complex nature of the signal. To overcome this problem, the researchers employed a pattern recognition technique. EMG pattern recognition mainly involves four stages: signal detection, preprocessing feature extraction, dimensionality reduction, and classification. In particular, the success of any pattern recognition technique depends on the feature extraction stage. In this study, a modified time-domain features set and logarithmic transferred time-domain features (LTD) were evaluated and compared with other traditional time-domain features set (TTD). Three classifiers were employed to assess the two feature sets, namely linear discriminant analysis (LDA), k nearest neighborhood, and Naïve Bayes. Results indicated the superiority of the new time-domain feature set LTD, on conventional time-domain features TTD with the average classification accuracy of 97.23 %. In addition, the LDA classifier outperformed the other two classifiers considered in this study.
Calix[4]arene/polyurethane (C4PU) has been synthesized and characterized as an alternative adsorbent for the adsorption of methylene blue (MB) and malachite green (MG) dyes from the aqueous solution. C4PU was synthesized by reacting p-tert-butyl calix[4]arene with hexamethylene diisocyanate (HMDI) as the cross-linking agent. Different polymer ratios were synthesized, and C4PU-4 shows better adsorption than other ratios. The polymer was characterized by Fourier transform infrared spectroscopy (FTIR), thermogravimetric analysis (TGA), Brunauer-Emmett-Teller (BET) analysis, and point of zero charges (pHPZC). The isotherms and kinetics of the adsorption of MB and MG were studied under a range of experimental conditions, including pH, adsorbent dosage, initial dye concentration, and contact time. The adsorption was determined by the adsorption percentage of MB and MG dyes from the solution. The Langmuir isotherm model best describes the adsorption process for both dyes, and it follows a pseudo-second-order kinetic model, with the maximum adsorption capacity (qmax) of MB and MG, respectively, was found to be 1.991 mg·g-1 and 2.240 mg·g-1.
This study aims to investigate the influence of copper(II) ions as a cofactor on the electrochemical performance of a biocomposite consisting of a mini protein mimicking uricase (mp20) and zeolitic immidazolate framework-8 (ZIF-8) for the detection of uric acid. A central composite design (CCD) was utilized to optimize the independent investigation, including pH, deposition potential, and deposition time, while the current response resulting from the electrocatalytic oxidation of uric acid was used as the response. The statistical analysis of variance (ANOVA) showed a good correlation between the experimental and predicted data, with a residual standard error percentage (RSE%) of less than 2% for predicting optimal conditions. The synergistic effect of the nanoporous ZIF-8 host, Cu(II)-activated mp20, and reduced graphene oxide (rGO) layer resulted in a highly sensitive biosensor with a limit of detection (LOD) of 0.21 μM and a reproducibility of the response (RSD = 0.63%). The Cu(II)-activated mp20@ZIF-8/rGO/SPCE was highly selective in the presence of common interferents, and the fabricated layer exhibited remarkable stability with signal changes below 4.15% after 60 days. The biosensor's reliable performance was confirmed through real sample analyses of human serum and urine, with comparable recovery values to conventional HPLC.
In this paper, Response Surface Methodology with central composite design (RSM/CCD) was used to optimize a modified electrode for improved electron transfer rate and electrochemical performance. The modification was done on a screen-printed carbon electrode (SPCE) with reduced graphene oxide (ERGO)/calix [4] arene (ERGOC4-SPCE). The properties of the modified electrodes were analyzed via cyclic voltammetry, Raman spectroscopy, and Fourier-Transform Infrared (FT-IR) spectroscopy. Then, different variables were optimized, namely, the concentration of graphene oxide, GO (A), the number of scan cycles of graphene oxide (B), and the deposition time (C). The effect of the optimized variables on the reduction-oxidation peak current response of the potassium ferricyanide redox system was analyzed. By using statistical analysis, it shows a significant effect of the concentration of GO, the deposition time, and the number of scans cycles on the peak current response. The coefficient of determination (R2) value of 0.9987 produced indicated a good fit of the model with experimental finding.
Mini protein mimicking uricase (mp20) has shown significant potential as a replacement for natural enzymes in the development of uric acid biosensors. However, the design of mp20 has resulted to an inactive form of peptide, causing of loss their catalytic activity. Herein, this paper delineates the impact of various metal cofactors on the catalytic activity of mp20. The metal ion-binding site prediction and docking (MIB) web server was employed to identify the metal ion binding sites and their affinities towards mp20 residues. Among the tested metal ions, Cu2+ displayed the highest docking score, indicating its preference for interaction with Thr16 and Asp17 residues of mp20. To assess the catalytic activity of mp20 in the presence of metal ions, uric acid assays was monitored using a colorimetric method. The presence of Cu2+ in the assays promotes the activation of mp20, resulting in a color change based on quinoid production. Furthermore, the encapsulation of the mp20 within zeolitic imidazolate framework-8 (ZIF-8) notably improved the stability of the biomolecule. In comparison to the naked mp20, the encapsulated ZIFs biocomposite (mp20@ZIF-8) demonstrates superior stability, selectivity and sensitivity. ZIF's porous shells provides excellent protection, broad detection (3-100 μM) with a low limit (4.4 μM), and optimal function across pH (3.4-11.4) and temperature (20-100°C) ranges. Cost-effective and stable mp20@ZIF-8 surpasses native uricase, marking a significant biosensor technology breakthrough. This integration of metal cofactor optimization and robust encapsulation sets new standards for biosensing applications.
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.