Owing to their ability to maintain a thermodynamically stable fold at extremely high temperatures, thermophilic proteins (TTPs) play a critical role in basic research and a variety of applications in the food industry. As a result, the development of computation models for rapidly and accurately identifying novel TTPs from a large number of uncharacterized protein sequences is desirable. In spite of existing computational models that have already been developed for characterizing thermophilic proteins, their performance and interpretability remain unsatisfactory. We present a novel sequence-based thermophilic protein predictor, termed SCMTPP, for improving model predictability and interpretability. First, an up-to-date and high-quality dataset consisting of 1853 TPPs and 3233 non-TPPs was compiled from published literature. Second, the SCMTPP predictor was created by combining the scoring card method (SCM) with estimated propensity scores of g-gap dipeptides. Benchmarking experiments revealed that SCMTPP had a cross-validation accuracy of 0.883, which was comparable to that of a support vector machine-based predictor (0.906-0.910) and 2-17% higher than that of commonly used machine learning models. Furthermore, SCMTPP outperformed the state-of-the-art approach (ThermoPred) on the independent test dataset, with accuracy and MCC of 0.865 and 0.731, respectively. Finally, the SCMTPP-derived propensity scores were used to elucidate the critical physicochemical properties for protein thermostability enhancement. In terms of interpretability and generalizability, comparative results showed that SCMTPP was effective for identifying and characterizing TPPs. We had implemented the proposed predictor as a user-friendly online web server at http://pmlabstack.pythonanywhere.com/SCMTPP in order to allow easy access to the model. SCMTPP is expected to be a powerful tool for facilitating community-wide efforts to identify TPPs on a large scale and guiding experimental characterization of TPPs.
A novel bacterial strain of acetic acid bacteria capable of producing riboflavin was isolated from the soil sample collected in Wuhan, China. The isolated strain was identified as Gluconobacter oxydans FBFS97 based on several phenotype characteristics, biochemicals tests, and 16S rRNA gene sequence conducted. Furthermore, the complete genome sequencing of the isolated strain has showed that it contains a complete operon for the biosynthesis of riboflavin. In order to obtain the maximum concentration of riboflavin production, Gluconobacter oxydans FBFS97 was optimized in shake flask cultures through response surface methodology employing Plackett-Burman design (PBD), and Central composite design (CCD). The results of the pre-experiments displayed that fructose and tryptone were found to be the most suitable sources of carbon and nitrogen for riboflavin production. Then, PBD was conducted for initial screening of eleven minerals (FeSO4, FeCl3, KH2PO4, K2HPO4, MgSO4, ZnSO4, NaCl, CaCl2, KCl, ZnCl2, and AlCl3.6H2O) for their significances on riboflavin production by Gluconobacter oxydans strain FBFS97. The most significant variables affecting on riboflavin production are K2HPO4 and CaCl2, the interaction affects and levels of these variables were optimized by CCD. After optimization of the medium compositions for riboflavin production were determined as follows: fructose 25 g/L, tryptone 12.5 g/L, K2HPO4 9 g/L, and CaCl2 0.06 g/L with maximum riboflavin production 23.24 mg/L.
The current investigation aims to examine heat transfer as well as entropy generation analysis of Powell-Eyring nanofluid moving over a linearly expandable non-uniform medium. The nanofluid is investigated in terms of heat transport properties subjected to a convectively heated slippery surface. The effect of a magnetic field, porous medium, radiative flux, nanoparticle shapes, viscous dissipative flow, heat source, and Joule heating are also included in this analysis. The modeled equations regarding flow phenomenon are presented in the form of partial-differential equations (PDEs). Keller-box technique is utilized to detect the numerical solutions of modeled equations transformed into ordinary-differential equations (ODEs) via suitable similarity conversions. Two different nanofluids, Copper-methanol (Cu-MeOH) as well as Graphene oxide-methanol (GO-MeOH) have been taken for our study. Substantial results in terms of sundry variables against heat, frictional force, Nusselt number, and entropy production are elaborate graphically. This work's noteworthy conclusion is that the thermal conductivity in Powell-Eyring phenomena steadily increases in contrast to classical liquid. The system's entropy escalates in the case of volume fraction of nanoparticles, material parameters, and thermal radiation. The shape factor is more significant and it has a very clear effect on entropy rate in the case of GO-MeOH nanofluid than Cu-MeOH nanofluid.
Snakebite envenomation is a neglected tropical disease of high mortality and morbidity largely due to insufficient supply of effective and affordable antivenoms. Snake antivenoms are mostly effective against the venoms used in their production. It is thus crucial that effective and affordable antivenom(s) with wide para-specificity, capable of neutralizing the venoms of a large number of snakes, be produced. Here we studied the pan-specific antiserum prepared previously by a novel immunization strategy involving the exposure of horses to a 'diverse toxin repertoire' consisting of 12 neurotoxic Asian snake toxin fractions/ venoms from six species. This antiserum was previously shown to exhibit wide para-specificity by neutralizing 11 homologous and 16 heterologous venoms from Asia and Africa. We now show that the antiserum can neutralize 9 out of 10 additional neurotoxic venoms. Altogether, 36 snake venoms belonging to 10 genera from 4 continents were neutralized by the antiserum. Toxin profiles previously generated using proteomic techniques of these 36 venoms identified α-neurotoxins, β-neurotoxins, and cytotoxins as predominant toxins presumably neutralized by the antiserum. The bases for the wide para-specificity of the antiserum are discussed. These findings indicate that it is feasible to generate antivenoms of wide para-specificity against elapid neurotoxic venoms from different regions in the world and raises the possibility of a universal neurotoxic antivenom. This should reduce the mortality resulting from neurotoxic snakebite envenomation.
Plant phenolics are being increasingly consumed globally with limited scientific and clinical evidence pertaining to safety and efficacy. The oil palm fruit contains a cocktail of phenolics, and palm oil production results in high volumes of aqueous by-products enriched in phenolics and bioactives. Several lines of evidence from in vitro and in vivo animal studies confirmed that the aqueous extract enriched in phenolics and other bioactives collectively known as oil palm phenolics (OPP) is safe and has potent bioactivity. A phase one clinical trial was conducted to evaluate the safety and effects of OPP in healthy volunteers. In this single-blind trial, 25 healthy human volunteers were supplemented with 450 mg gallic acid equivalent (GAE)/day of OPP or control treatments for a 60-day period. Fasting blood and urine samples were collected at days 1, 30 and 60. Medical examination was performed during these trial interventions. All clinical biochemistry profiles observed throughout the control and OPP treatment period were in the normal range with no major adverse effect (AE) or serious adverse effect (SAE) observed. Additionally, OPP supplementation resulted in improvement of total cholesterol and LDL-C levels, compared to the control treatment. The outcomes support our previous observations that OPP is safe and may have a protective role in reducing cholesterol levels.
Mirror-induced behaviour has been described as a cognitive ability of an animal to self-direct their image in front of the mirror. Most animals when exposed to a mirror responded with a social interactive behaviour such as aggressiveness, exploratory and repetitive behaviour. The objective of this study is to determine the mirror-induced self-directed behaviour on wildlife at the Royal Belum Rainforest, Malaysia. Wildlife species at the Royal Belum Rainforest were identified using a camera traps from pre-determined natural saltlick locations. Acrylic mirrors with steel frame were placed facing the two saltlicks (Sira Batu and Sira Tanah) and the camera traps with motion-detecting infrared sensor were placed at strategically hidden spot. The behavioural data of the animal response to the mirror were analysed using an ethogram procedure. Results showed that barking deer was the species showing the highest interaction in front of the mirror. Elephants displayed self-directed response through inspecting behaviour via usage of their trunk and legs while interacting to the mirror. Interestingly, the Malayan tapir showed startled behaviour during their interaction with the mirror. However, the absence of interactive behaviour of the Malayan tiger signalled a likelihood of a decreased social response behaviour. These results suggested that the ability to self-directed in front of the mirror is most likely related to the new approach to study the neural mechanism and its level of stimulus response in wildlife. In conclusion, research on mirror-induced self-directed behaviour in wildlife will have profound implications in understanding the cognitive ability of wildlife as an effort to enhance the management strategies and conservation.
Getah virus (GETV), a mosquito-borne alphavirus, is an emerging animal pathogen causing outbreaks among racehorses and pigs. Early detection of the GETV infection is essential for timely implementation of disease prevention and control interventions. Thus, a rapid and accurate nucleic acid detection method for GETV is highly needed. Here, two TaqMan minor groove binding (MGB) probe-based quantitative reverse transcription-polymerase chain reaction (qRT-PCR) assays were developed. The qRT-PCR primers and TaqMan MGB probe were designed based on the conserved region of nsP1 and nsP2 genes of 23 GETV genome sequences retrieved from GenBank. Only the qRT-PCR assay using nsP2-specific primers and probe detected all two Malaysia GETV strains (MM2021 and B254) without cross-reacting with other closely related arboviruses. The qRT-PCR assay detected as few as 10 copies of GETV RNA, but its detection limit at the 95% probability level was 63.25 GETV genome copies (probit analysis, P ≤ 0.05). Further validation of the qRT-PCR assay using 16 spiked simulated clinical specimens showed 100% for both sensitivity and specificity. In conclusion, the qRT-PCR assay developed in this study is useful for rapid, sensitive and specific detection and quantification of GETV.
To study the antimicrobial effects of quaternary ammonium silane (QAS) exposure on Streptococcus mutans and Lactobacillus acidophilus bacterial biofilms at different concentrations. Streptococcus mutans and Lactobacillus acidophilus biofilms were cultured on dentine disks, and incubated for bacterial adhesion for 3-days. Disks were treated with disinfectant (experimental QAS or control) and returned to culture for four days. Small-molecule drug discovery-suite was used to analyze QAS/Sortase-A active site. Cleavage of a synthetic fluorescent peptide substrate, was used to analyze inhibition of Sortase-A. Raman spectroscopy was performed and biofilms stained for confocal laser scanning microscopy (CLSM). Dentine disks that contained treated dual-species biofilms were examined using scanning electron microscopy (SEM). Analysis of DAPI within biofilms was performed using CLSM. Fatty acids in bacterial membranes were assessed with succinic-dehydrogenase assay along with time-kill assay. Sortase-A protein underwent conformational change due to QAS molecule during simulation, showing fluctuating alpha and beta strands. Spectroscopy revealed low carbohydrate intensities in 1% and 2% QAS. SEM images demonstrated absence of bacterial colonies after treatment. DAPI staining decreased with 1% QAS (p
Irritable bowel syndrome (IBS) is frequently linked with coexisting mental illnesses. Our previous study discovered that 32.1% of IBS patients had subthreshold depression (SD), placing them at higher risk of developing major depression. Gut microbiota modulation through psychobiotics was found to influence depression via the gut-brain axis. However, the efficacy of lessening depression among IBS patients remains ambiguous. The study's aim was to investigate the roles of cultured milk drinks containing 109 cfu Lactobacillus acidophilus LA-5 and Lactobacillus paracasei L. CASEI-01 on depression and related variables among IBS participants with SD. A total of 110 IBS participants with normal mood (NM) and SD, were randomly assigned to one of four intervention groups: IBS-NM with placebo, IBS-NM with probiotic, IBS-SD with placebo, and IBS-SD with probiotic. Each participant was required to consume two bottles of cultured milk every day for a duration of 12 weeks. The following outcomes were assessed: depression risk, quality of life, the severity of IBS, and hormonal changes. The depression scores were significantly reduced in IBS-SD with probiotic and placebo from baseline (p
Postbiotic RS5, produced by Lactiplantibacillus plantarum RS5, has been identified as a promising alternative feed supplement for various livestock. This study aimed to lower the production cost by enhancing the antimicrobial activity of the postbiotic RS5 by improving the culture density of L. plantarum RS5 and reducing the cost of growth medium. A combination of conventional and statistical-based approaches (Fractional Factorial Design and Central Composite Design of Response Surface Methodology) was employed to develop a refined medium for the enhancement of the antimicrobial activity of postbiotic RS5. A refined medium containing 20 g/L of glucose, 27.84 g/L of yeast extract, 5.75 g/L of sodium acetate, 1.12 g/L of Tween 80 and 0.05 g/L of manganese sulphate enhanced the antimicrobial activity of postbiotic RS5 by 108%. The cost of the production medium was reduced by 85% as compared to the commercially available de Man, Rogosa and Sharpe medium that is typically used for Lactobacillus cultivation. Hence, the refined medium has made the postbiotic RS5 more feasible and cost-effective to be adopted as a feed supplement for various livestock industries.
A Nanogrid (NG) model is described as a power distribution system that integrates Hybrid Renewable Energy Sources (HRESs) and Energy Storage Systems (ESSs) into the primary grid. However, this process is affected by several factors, like load variability, market pricing, and the intermittent nature of Wind Turbines (WTs) and Photovoltaic (PV) systems. Hence, other researchers in the past have used a few optimization-based processes to improve the development of Energy Management Systems (EMSs) and ESSs, which further enhanced the operational performance of NGs. It was seen that EMS acts as the distributed energy source in the NG setup and assists in power generation, usage, dissemination, and differential pricing. Hence this study employed the MATLAB Simulink software for modelling the grid-connected NG that included HRES; such as wind and PV; in addition to 3 Battery Storage Devices (BSDs) to design an effective EMS for the NG system and decrease its overall costs. For this purpose, a Rule-Based EMS (RB-EMS) that employs State Flow (SF) to guarantee a safe and reliable operating power flow to the NG has been developed. In addition to that, a Genetic Algorithm (GA)-based optimization system and Simulated Annealing optimization Algorithm (SAA) were proposed to determine an economical solution for decreasing the cost of the NG system depending on its operational constraints. Lastly, comparison about the cost between RB-EMS, GA and SAA has been presented. According to the simulation results, the proposed GA displayed an economical performance since it could achieve a 40% cost saving whereas the SAA system showed a 19.3% cost saving compared to the RB-EMS. It can be concluded from the findings that the GA-based optimization technique was very cost-effective displays many important features, like rapid convergence, simple design, and very few controlling factors.
Ruthenium(II) polypyridyl complexes can intercalate DNA with high affinity and prevent cell proliferation; however, the direct impact of ruthenium-based intercalation on cellular DNA replication remains unknown. Here we show the multi-intercalator [Ru(dppz)2(PIP)](2+) (dppz = dipyridophenazine, PIP = 2-(phenyl)imidazo[4,5-f][1,10]phenanthroline) immediately stalls replication fork progression in HeLa human cervical cancer cells. In response to this replication blockade, the DNA damage response (DDR) cell signalling network is activated, with checkpoint kinase 1 (Chk1) activation indicating prolonged replication-associated DNA damage, and cell proliferation is inhibited by G1-S cell-cycle arrest. Co-incubation with a Chk1 inhibitor achieves synergistic apoptosis in cancer cells, with a significant increase in phospho(Ser139) histone H2AX (γ-H2AX) levels and foci indicating increased conversion of stalled replication forks to double-strand breaks (DSBs). Normal human epithelial cells remain unaffected by this concurrent treatment. Furthermore, pre-treatment of HeLa cells with [Ru(dppz)2(PIP)](2+) before external beam ionising radiation results in a supra-additive decrease in cell survival accompanied by increased γ-H2AX expression, indicating the compound functions as a radiosensitizer. Together, these results indicate ruthenium-based intercalation can block replication fork progression and demonstrate how these DNA-binding agents may be combined with DDR inhibitors or ionising radiation to achieve more efficient cancer cell killing.
The emergence and spread of antimicrobial resistance have been of serious concern to human health and the management of bacterial infectious diseases. Effective treatment of these diseases requires the development of novel therapeutics, preferably free of side effects. In this regard, natural products are frequently conceived to be potential alternative sources for novel antibacterial compounds. Herein, we have evaluated the antibacterial activity of the epicarp extracts of the Malaysian cultivar of yellow rambutan fruit (Nephelium lappaceum L.) against six pathogens namely, Bacillus subtilis, methicillin-resistant Staphylococcus aureus (MRSA), Streptococcus pyogenes, Pseudomonas aeruginosa, Klebsiella pneumoniae and Salmonella enterica. Among a series of solvent extracts, fractions of ethyl acetate and acetone have revealed significant activity towards all tested strains. Chemical profiling of these fractions, via HPLC, LC-MS and GC-MS, has generated a library of potentially bioactive compounds. Downstream virtual screening, pharmacological prediction, and receptor-ligand molecular dynamics simulation have eventually unveiled novel potential antibacterial compounds, which can be extracted for medicinal use. We report compounds like catechin, eplerenone and oritin-4-beta-ol to be computationally inhibiting the ATP-binding domain of the chaperone, DnaK of P. aeruginosa and MRSA. Thus, our work follows the objective to propose new antimicrobials capable of perforating the barrier of resistance posed by both the gram positives and the negatives.
Electrocaloric (EC) materials show promise in eco-friendly solid-state refrigeration and integrable on-chip thermal management. While direct measurement of EC thin-films still remains challenging, a generic theoretical framework for quantifying the cooling properties of rich EC materials including normal-, relaxor-, organic- and anti-ferroelectrics is imperative for exploiting new flexible and room-temperature cooling alternatives. Here, we present a versatile theory that combines Master equation with Maxwell relations and analytically relates the macroscopic cooling responses in EC materials with the intrinsic diffuseness of phase transitions and correlation characteristics. Under increased electric fields, both EC entropy and adiabatic temperature changes increase quadratically initially, followed by further linear growth and eventual gradual saturation. The upper bound of entropy change (∆Smax) is limited by distinct correlation volumes (V cr ) and transition diffuseness. The linearity between V cr and the transition diffuseness is emphasized, while ∆Smax = 300 kJ/(K.m3) is obtained for Pb0.8Ba0.2ZrO3. The ∆Smax in antiferroelectric Pb0.95Zr0.05TiO3, Pb0.8Ba0.2ZrO3 and polymeric ferroelectrics scales proportionally with V cr-2.2, owing to the one-dimensional structural constraint on lattice-scale depolarization dynamics; whereas ∆Smax in relaxor and normal ferroelectrics scales as ∆Smax ~ V cr-0.37, which tallies with a dipolar interaction exponent of 2/3 in EC materials and the well-proven fractional dimensionality of 2.5 for ferroelectric domain walls.
This scientific report investigates the heat transfer analysis in mixed convection flow of Maxwell fluid over an oscillating vertical plate with constant wall temperature. The problem is modelled in terms of coupled partial differential equations with initial and boundary conditions. Some suitable non-dimensional variables are introduced in order to transform the governing problem into dimensionless form. The resulting problem is solved via Laplace transform method and exact solutions for velocity, shear stress and temperature are obtained. These solutions are greatly influenced with the variation of embedded parameters which include the Prandtl number and Grashof number for various times. In the absence of free convection, the corresponding solutions representing the mechanical part of velocity reduced to the well known solutions in the literature. The total velocity is presented as a sum of both cosine and sine velocities. The unsteady velocity in each case is arranged in the form of transient and post transient parts. It is found that the post transient parts are independent of time. The solutions corresponding to Newtonian fluids are recovered as a special case and comparison between Newtonian fluid and Maxwell fluid is shown graphically.
Due to tamper-resistant sensor nodes and wireless media, Industrial Wireless Sensor Networks (WSNs) are susceptible to various security threats that severely affect industrial/business applications. The survival of sensor networks is highly dependent on the flourishing collaboration of sensor nodes. Trust management schemes seem to be realistic and promising techniques to improve security as well as cooperation (dependability) among sensor nodes by estimating the trust level (score) of individual sensor nodes. This research paper presents a well-organized and motivating secure, dependable trust assessment (SDTS) scheme for industrial WSNs to cope with unexpected behavior such as an on-off attack, bad-mouthing attack, garnished attack, etc., by employing robust trust evaluation components based on success ratio and node misbehaviour. SDTS incorporates an interesting trust evaluation function in which the trust range can be adjusted in accordance with the application requirement. SDTS include direct communication trust, indirect communication trust, data trust, and misbehavior-based trust to defend the multiple internal attacks. SDTS works according to the behavior of nodes, i.e., whether the sensor nodes are interacting frequently or not. Moreover, abnormal attenuation and dynamic slide lengths are incorporated in the proposed model (SDTS) to deal with various natural calamities and internal attacks. SDTS is compared against three recent state-of-the-art methods and found efficient in terms of ease of trust assessment, false-positive rate (2.5%), false-negative rate (2%), attack detection rate (90%), detection accuracy (91%), average energy consumption (0.40 J), and throughput (108 Kbps) under the load of 500 sensor nodes with 50% malicious nodes. Investigational results exhibit the potency of the proposed scheme.
Community structure is an important feature of a complex network, where detection of the community structure can shed some light on the properties of such a complex network. Amongst the proposed community detection methods, the label propagation algorithm (LPA) emerges as an effective detection method due to its time efficiency. Despite this advantage in computational time, the performance of LPA is affected by randomness in the algorithm. A modified LPA, called CLPA-GNR, was proposed recently and it succeeded in handling the randomness issues in the LPA. However, it did not remove the tendency for trivial detection in networks with a weak community structure. In this paper, an improved CLPA-GNR is therefore proposed. In the new algorithm, the unassigned and assigned nodes are updated synchronously while the assigned nodes are updated asynchronously. A similarity score, based on the Sørensen-Dice index, is implemented to detect the initial communities and for breaking ties during the propagation process. Constraints are utilised during the label propagation and community merging processes. The performance of the proposed algorithm is evaluated on various benchmark and real-world networks. We find that it is able to avoid trivial detection while showing substantial improvement in the quality of detection.
An electrochemical method for detecting the presence of zinc (Zn2+) ions in drinking water was developed using functionalized multi-walled carbon nanotubes (f-MWCNTs) and chitosan (CS). Numerous cylinder-shaped graphene molecules make up f-MWCNTs, which have a high mechanical and electrical conductivity. CS benefits from nanomaterials include biocompatibility, biodegradability, and low toxicity, which are excellent in capacity absorption of metal ions. Dangerous levels of metal ions such as zinc are currently present in drinking water as a result of human and natural activity. Zinc toxicity is associated with a variety of disorders, including Alzheimer's, Parkinson's, diabetes, and cancer. This study incorporated f-MWCNTs and CS with Prussian blue (PB) immobilised on a gold electrode (AuE). Several parameters, including as buffers, pH, scan rate, redox indicator, accumulation time, and volume, were optimised using the cyclic voltammetry (CV) method. According to the CV method, the optimal parameters were phosphate buffered saline (0.1 M, pH 2), 5 mM Prussian blue, 200 mVs-1 scan rate, and 5 s accumulation time. Under ideal circumstances, the differential pulse voltammetry (DPV) method was used to determine the Zn2+ ions concentration range of 0.2-7.0 ppm. The limit of detection (LOD) was 2.60 × 10-7 mol L-1 with a correlation coefficient of R2 = 0.9777. The recovery rate of the developed sensor (f-MWCNTs/CS/PB/AuE) ranged from 95.78 to 98.96%. The developed sensor showed a variety of advantages for detecting Zn2+ in drinking water, including a quick setup process, quick detection, high sensitivity, and mobility. This study developed the essential sensor for monitoring Zn2+ levels in drinking water in the future.
Identifying effective drug targets, with little or no side effects, remains an ever challenging task. A potential pitfall of failing to uncover the correct drug targets, due to side effect of pleiotropic genes, might lead the potential drugs to be illicit and withdrawn. Simplifying disease complexity, for the investigation of the mechanistic aspects and identification of effective drug targets, have been done through several approaches of protein interactome analysis. Of these, centrality measures have always gained importance in identifying candidate drug targets. Here, we put forward an integrated method of analysing a complex network of cancer and depict the importance of k-core, functional connectivity and centrality (KFC) for identifying effective drug targets. Essentially, we have extracted the proteins involved in the pathways leading to cancer from the pathway databases which enlist real experimental datasets. The interactions between these proteins were mapped to build an interactome. Integrative analyses of the interactome enabled us to unearth plausible reasons for drugs being rendered withdrawn, thereby giving future scope to pharmaceutical industries to potentially avoid them (e.g. ESR1, HDAC2, F2, PLG, PPARA, RXRA, etc). Based upon our KFC criteria, we have shortlisted ten proteins (GRB2, FYN, PIK3R1, CBL, JAK2, LCK, LYN, SYK, JAK1 and SOCS3) as effective candidates for drug development.
The objective of this work is to prepare a cost-effective, low reagent consumption and high performance polytetrafluoroethylene (PTFE) vessel that is capable to work in domestic microwave for digesting food and environmental samples. The designed vessel has a relatively thicker wall compared to that of commercial vessels. In this design, eight vessels are placed in an acrylonitrile butadiene styrene (ABS) holder to keep them safe and stable. This vessel needs only 2.0 mL of HNO3 and 1.0 mL H2O2 to digest 100 mg of biological sample. The performance of this design is then evaluated with an ICP-MS instrument in the analysis of the several NIST standard reference material of milk 1849a, rice flour 1568b, spinach leave 1570a and Peach Leaves 1547 in a domestic microwave oven with inverter technology. Outstanding agreement to (SRM) values are observed by using the suggested power to time microwave program, which simulates the reflux action occurring in this closed vessel. Taking into account the high cost of commercial microwave vessels and the volume of chemicals needed for various experiments (8-10 mL), this simple vessel is cost effective and suitable for digesting food and environmental samples.