The proliferative capacity and continuous survival of cells are highly dependent on telomerase expression and the maintenance of telomere length. For this reason, elevated expression of telomerase has been identified in virtually all cancers, including leukemias; however, it should be noted that expression of telomerase is sometimes observed later in malignant development. This time point of activation is highly dependent on the type of leukemia and its causative factors. Many recent studies in this field have contributed to the elucidation of the mechanisms by which the various forms of leukemias increase telomerase activity. These include the dysregulation of telomerase reverse transcriptase (TERT) at various levels which include transcriptional, post-transcriptional, and post-translational stages. The pathways and biological molecules involved in these processes are also being deciphered with the advent of enabling technologies such as next-generation sequencing (NGS), ribonucleic acid sequencing (RNA-Seq), liquid chromatography-mass spectrometry (LCMS/MS), and many others. It has also been established that TERT possess diagnostic value as most adult cells do not express high levels of telomerase. Indeed, studies have shown that prognosis is not favorable in patients who have leukemias expressing high levels of telomerase. Recent research has indicated that targeting of this gene is able to control the survival of malignant cells and therefore offers a potential treatment for TERT-dependent leukemias. Here we review the mechanisms of hTERT regulation and deliberate their association in malignant states of leukemic cells. Further, we also cover the clinical implications of this gene including its use in diagnostic, prognostic, and therapeutic discoveries.
Polyhydroxyalkanoates (PHA) are biodegradable polymers that are considered able to replace synthetic plastic because their biochemical characteristics are in some cases the same as other biodegradable polymers. However, due to the disadvantages of costly and non-renewable carbon sources, the production of PHA has been lower in the industrial sector against conventional plastics. At the same time, first-generation sugar-based cultivated feedstocks as substrates for PHA production threatens food security and considerably require other resources such as land and energy. Therefore, attempts have been made in pursuit of suitable sustainable and affordable sources of carbon to reduce production costs. Thus, in this review, we highlight utilising waste lignocellulosic feedstocks (LF) as a renewable and inexpensive carbon source to produce PHA. These waste feedstocks, second-generation plant lignocellulosic biomass, such as maize stoves, dedicated energy crops, rice straws, wood chips, are commonly available renewable biomass sources with a steady supply of about 150 billion tonnes per year of global yield. The generation of PHA from lignocellulose is still in its infancy, hence more screening of lignocellulosic materials and improvements in downstream processing and substrate pre-treatment are needed in the future to further advance the biopolymer sector.
Neurodegenerative diseases (NDs) extend the global health burden. Consumption of alcohol as well as maternal exposure to ethanol can damage several neuronal functions and cause cognition and behavioral abnormalities. Ethanol induces oxidative stress that is linked to the development of NDs. Treatment options for NDs are yet scarce, and natural product-based treatments could facilitate ND management since plants possess plenty of bioactive metabolites, including flavonoids, which typically demonstrate antioxidant and anti-inflammatory properties. Hypericum oblongifolium is an important traditional medicinal plant used for hepatitis, gastric ulcer, external wounds, and other gastrointestinal disorders. However, it also possesses multiple bioactive compounds and antioxidant properties, but the evaluation of isolated pure compounds for neuroprotective efficacy has not been done yet. Therefore, in the current study, we aim to isolate and characterize the bioactive flavonoid folecitin and evaluate its neuroprotective activity against ethanol-induced oxidative-stress-mediated neurodegeneration in the hippocampus of postnatal day 7 (PND-7) rat pups. A single dose of ethanol (5 g/kg body weight) was intraperitoneally administered after the birth of rat pups on PND-7. This caused oxidative stress accompanied by the activation of phosphorylated-c-Jun N-terminal kinase (p-JNK), nod-like receptor family pyrin domain containing 3 (NLRP3), apoptosis-associated speck-like protein (ASC), and cysteine-aspartic acid protease-1 (caspase-1) proteins to form a complex called the NLRP3-inflammasome, which converts pro-interleukin 1 beta (IL-1B) to activate IL-1B and induce widespread neuroinflammation and neurodegeneration. In contrast, co-administration of folecitin (30 mg/kg body weight) reduced ethanol-induced oxidative stress, inhibited p-JNK, and deactivated the NLRP3-inflammasome complex. Furthermore, folecitin administration reduced neuroinflammatory and neurodegenerative protein markers, including decreased caspase-3, BCL-2-associated X protein (BAX), B cell CLL/lymphoma 2 (BCL-2), and poly (ADP-ribose) polymerase-1 (PARP-1) expression in the immature rat brain. These findings conclude that folecitin is a flavone compound, and it might be a novel, natural and safe agent to curb oxidative stress and its downstream harmful effects, including inflammasome activation, neuroinflammation, and neurodegeneration. Further evaluation in a dose-dependent manner would be worth it in order to find a suitable dose regimen for NDs.
Lung cancers are ranked third among the cancer incidence in France in the year 2020, with adenocarcinomas being the commonest sub-type out of ~85% of non-small cell lung carcinomas. The constant evolution of molecular genotyping, which is used for the management of lung adenocarcinomas, has led to the current focus on tumor suppressor genes, specifically the loss of function mutation in the SMARCA4 gene. SMARCA4-deficient adenocarcinomas are preponderant in younger aged male smokers with a predominant solid morphology. The importance of identifying SMARCA4-deficient adenocarcinomas has gained interest for lung cancer management due to its aggressive behavior at diagnosis with vascular invasion and metastasis to the pleura seen upon presentation in most cases. These patients have poor clinical outcome with short overall survival rates, regardless of the stage of disease. The detection of SMARCA4 deficiency is possible in most pathology labs with the advent of sensitive and specific immunohistochemical antibodies. The gene mutations can be detected together with other established lung cancer molecular markers based on the current next generation sequencing panels. Sequencing will also allow the identification of associated gene mutations, notably KRAS, KEAP1, and STK11, which have an impact on the overall survival and progression-free survival of the patients. Predictive data on the treatment with anti-PD-L1 are currently uncertain in this high tumor mutational burden cancer, which warrants more groundwork. Identification of target drugs is also still in pre-clinical testing. Thus, it is paramount to identify the SMARCA4-deficient adenocarcinoma, as it carries worse repercussions on patient survival, despite having an exceptionally low prevalence. Herein, we discuss the pathophysiology of SMARCA4, the clinicopathological consequences, and different detection methods, highlighting the perspectives and challenges in the assessment of SMARCA4 deficiency for the management of non-small cell lung cancer patients. This is imperative, as the contemporary shift on identifying biomarkers associated with tumor suppressor genes such as SMARCA4 are trending; hence, awareness of pathologists and clinicians is needed for the SMARCA4-dNSCLC entity with close follow-up on new management strategies to overcome the poor possibilities of survival in such patients.
Biofilms comprising aggregates of microorganisms or multicellular communities have been a major issue as they cause resistance against antimicrobial agents and biofouling. To date, numerous biofilm-forming microorganisms have been identified, which have been shown to result in major effects including biofouling and biofilm-related infections. Quorum sensing (which describes the cell communication within biofilms) plays a vital role in the regulation of biofilm formation and its virulence. As such, elucidating the various mechanisms responsible for biofilm resistance (including quorum sensing) will assist in developing strategies to inhibit and control the formation of biofilms in nature. Employing biological control measures (such as the use of bioactive compounds) in targeting biofilms is of great interest since they naturally possess antimicrobial activity among other favorable attributes and can also possibly act as potent antibiofilm agents. As an effort to re-establish the current notion and understanding of biofilms, the present review discuss the stages involved in biofilm formation, the factors contributing to its development, the effects of biofilms in various industries, and the use of various bioactive compounds and their strategies in biofilm inhibition.
MeSH terms: Anti-Bacterial Agents/pharmacology; Biofilms*; Quorum Sensing*
In this study, a novel application of neurocomputing technique is presented for solving nonlinear heat transfer and natural convection porous fin problems arising in almost all areas of engineering and technology, especially in mechanical engineering. The mathematical models of the problems are exploited by the intelligent strength of Euler polynomials based Euler neural networks (ENN's), optimized with a generalized normal distribution optimization (GNDO) algorithm and Interior point algorithm (IPA). In this scheme, ENN's based differential equation models are constructed in an unsupervised manner, in which the neurons are trained by GNDO as an effective global search technique and IPA, which enhances the local search convergence. Moreover, a temperature distribution of heat transfer and natural convection porous fin are investigated by using an ENN-GNDO-IPA algorithm under the influence of variations in specific heat, thermal conductivity, internal heat generation, and heat transfer rate, respectively. A large number of executions are performed on the proposed technique for different cases to determine the reliability and effectiveness through various performance indicators including Nash-Sutcliffe efficiency (NSE), error in Nash-Sutcliffe efficiency (ENSE), mean absolute error (MAE), and Thiel's inequality coefficient (TIC). Extensive graphical and statistical analysis shows the dominance of the proposed algorithm with state-of-the-art algorithms and numerical solver RK-4.
Breast cancer has been reported to have the highest survival rate among various cancers. However, breast cancer survivors face several challenges following breast cancer treatment including breast cancer-related lymphedema (BCRL), sexual dysfunction, and psychological distress. This study aimed to investigate the potential risk factors of BCRL in long term breast cancer survivors. A total of 160 female breast cancer subjects were recruited on a voluntary basis and arm lymphedema was assessed through self-reporting of diagnosis, arm circumference measurement, and ultrasound examination. A total of 33/160 or 20.5% of the women developed BCRL with significantly higher scores for upper extremity disability (37.14 ± 18.90 vs. 20.08 ± 15.29, p < 0.001) and a lower score for quality of life (103.91 ± 21.80 vs. 115.49 ± 16.80, p = 0.009) as compared to non-lymphedema cases. Univariate analysis revealed that multiple surgeries (OR = 5.70, 95% CI: 1.21-26.8, p < 0.001), axillary lymph nodes excision (>10) (OR = 2.83, 95% CI: 0.94-8.11, p = 0.047), being overweight (≥25 kg/m2) (OR = 2.57, 95% CI: 1.04 - 6.38, p = 0.036), received fewer post-surgery rehabilitation treatment (OR = 2.37, 95% CI: 1.05-5.39, p = 0.036) and hypertension (OR = 2.38, 95% CI: 1.01-5.62, p = 0.043) were associated with an increased risk of BCRL. Meanwhile, multivariate analysis showed that multiple surgeries remained significant and elevated the likelihood of BCRL (OR = 5.83, 95% CI: 1.14-29.78, p = 0.034). Arm swelling was more prominent in the forearm area demonstrated by the highest difference of arm circumference measurement when compared to the upper arm (2.07 ± 2.48 vs. 1.34 ± 1.91 cm, p < 0.001). The total of skinfold thickness of the affected forearm was also significantly higher than the unaffected arms (p < 0.05) as evidenced by the ultrasound examination. The continuous search for risk factors in specific populations may facilitate the development of a standardized method to reduce the occurrence of BCRL and provide better management for breast cancer patients.
Automated artificial intelligence (AI) systems enable the integration of different types of data from various sources for clinical decision-making. The aim of this study is to propose a pipeline to develop a fully automated clinician-friendly AI-enabled database platform for breast cancer survival prediction. A case study of breast cancer survival cohort from the University Malaya Medical Centre was used to develop and evaluate the pipeline. A relational database and a fully automated system were developed by integrating the database with analytical modules (machine learning, automated scoring for quality of life, and interactive visualization). The developed pipeline, iSurvive has helped in enhancing data management as well as to visualize important prognostic variables and survival rates. The embedded automated scoring module demonstrated quality of life of patients whereas the interactive visualizations could be used by clinicians to facilitate communication with patients. The pipeline proposed in this study is a one-stop center to manage data, to automate analytics using machine learning, to automate scoring and to produce explainable interactive visuals to enhance clinician-patient communication along the survivorship period to modify behaviours that relate to prognosis. The pipeline proposed can be modelled on any disease not limited to breast cancer.
Since the start of the COVID-19 pandemic at the end of 2019, more than 170 million patients have been infected with the virus that has resulted in more than 3.8 million deaths all over the world. This disease is easily spreadable from one person to another even with minimal contact, even more for the latest mutations that are more deadly than its predecessor. Hence, COVID-19 needs to be diagnosed as early as possible to minimize the risk of spreading among the community. However, the laboratory results on the approved diagnosis method by the World Health Organization, the reverse transcription-polymerase chain reaction test, takes around a day to be processed, where a longer period is observed in the developing countries. Therefore, a fast screening method that is based on existing facilities should be developed to complement this diagnosis test, so that a suspected patient can be isolated in a quarantine center. In line with this motivation, deep learning techniques were explored to provide an automated COVID-19 screening system based on X-ray imaging. This imaging modality is chosen because of its low-cost procedures that are widely available even in many small clinics. A new convolutional neural network (CNN) model is proposed instead of utilizing pre-trained networks of the existing models. The proposed network, Residual-Shuffle-Net, comprises four stacks of the residual-shuffle unit followed by a spatial pyramid pooling (SPP) unit. The architecture of the residual-shuffle unit follows an hourglass design with reduced convolution filter size in the middle layer, where a shuffle operation is performed right after the split branches have been concatenated back. Shuffle operation forces the network to learn multiple sets of features relationship across various channels instead of a set of global features. The SPP unit, which is placed at the end of the network, allows the model to learn multi-scale features that are crucial to distinguish between the COVID-19 and other types of pneumonia cases. The proposed network is benchmarked with 12 other state-of-the-art CNN models that have been designed and tuned specially for COVID-19 detection. The experimental results show that the Residual-Shuffle-Net produced the best performance in terms of accuracy and specificity metrics with 0.97390 and 0.98695, respectively. The model is also considered as a lightweight model with slightly more than 2 million parameters, which makes it suitable for mobile-based applications. For future work, an attention mechanism can be integrated to target certain regions of interest in the X-ray images that are deemed to be more informative for COVID-19 diagnosis.
Seaweeds are an important ingredient of functional foods recommended for daily food, due to their unique compositions and nutritional value. Padina tetrastromatica is a brown edible seaweed that is commonly found along the coastal regions of Peninsular Malaysia and consumed as food by some coastal communities. This study investigates the nutritional and antihyperglycaemic potential of P. tetrastromatica extracts, which is generally accepted as an important functional food. In our methodology, we induced diabetes intraperitoneally in experimental animals with a dose of 65 mg kg-1 body weight of streptozotocin. Oral treatment with 200 and 400 mg kg-1 of P. tetrastromatica ethanolic and ethyl acetate extracts were initiated, respectively, to experimental rats once daily for 18 days. Metformin was used as the positive control. Biochemical estimations and histopathological analysis were included in this study. Treatment with P. tetrastromatica extracts significantly lowered the plasma glucose levels in Streptozotocin-induced diabetic rats. In addition, P. tetrastromatica extract treatment also showed a significant reduction in serum alanine transaminase levels. However, no significant changes were observed in serum aspartate transaminase levels. The ethyl acetate extract of P. tetrastromatica at 400 mg kg-1 dose shows some nephroprotective effect, which is observed from the significant increase in the plasma albumin levels. Histopathological evaluation revealed no marked morphological changes in tissues of the isolated organs of the ethyl acetate extract-treated group, revealing the safe nature of P. tetrastromatica.
Early diagnosis is still as crucial as the initial stage of the COVID-19 pandemic. As RT-PCR sometimes is not feasible in developing nations or rural areas, health professionals may use a rapid antigen test (RAT) to lessen the load of diagnosis. However, the efficacy of RAT is yet to be investigated thoroughly. Hence, we tried to evaluate the overall performance of RAT in SARS-CoV-2 diagnosis. Based on our PROSPERO registered protocol (CRD42021231432), we searched online databases (i.e., PubMed, Google Scholar, Scopus, and Web of Science) and analysed overall pooled specificity and sensitivity of RAT along with study quality, publication bias, heterogeneity and more. The overall pooled specificity and sensitivity of RAT were detected as 99.4% (95% CI: 99.1-99.8; I2 = 90%) and 68.4% (95% CI: 60.8-75.9; I2 = 98%), respectively. In subgroup analyses, nasopharyngeal specimens and symptomatic patient's samples were more sensitive in RAT, while cycle threshold (Ct) values were found to have an inverse relationship with sensitivity. In the European and American populations, RAT showed better performance. Although the sensitivity of RAT is yet to be improved, it could still be an alternative in places with poor laboratory set up. Nevertheless, the negative samples of RAT can be re-tested using RT-PCR to reduce false negative results.
Bayesian Structural Equation Modeling (SEM-Bayesian) was applied across different research areas to model the correlation between manifest and latent variables. The primary purpose of this study is to introduce a new framework of complexity to adolescent obesity modeling based on adolescent lifestyle through the application of SEM-Bayesian. The introduced model was designed based on the relationships among several factors: household socioeconomic status, healthy food intake, unhealthy food intake, lifestyle, body mass index (BMI) and body fat. One of the main contributions of this study is from considering both BMI and body fat as dependent variables. To demonstrate the reliability of the model, especially in terms of its fitting and accuracy, real-time data were extracted and analyzed across 881 adolescents from secondary schools in Tehran, Iran. The output of this study may be helpful for researchers who are interested in adolescent obesity modeling based on the lifestyle and household socioeconomic status of adolescents.
Aedes aegypti is a significant vector for many tropical and subtropical flavivirus diseases. Only the female mosquito transmits pathogens, while the male plays a vital role in mating and species continuity. This study explored the total proteomes of females and males based on the physiological and genetic differences of female and male mosquitoes. Protein extracts from mosquitoes were analysed using LC-ESI-MS/MS for protein identification, protein interaction network analysis, functional ontology enrichment, and differential protein abundance analyses. Protein identification revealed 422 and 682 proteins exclusive to males and females, respectively, with 608 common proteins found in both sexes. The most significant PPIs (<1.0 × 10-16) were for common proteins, followed by proteins exclusive to females (<1.0 × 10-16) and males (1.58 × 10-12). Significant functional enrichments were observed in the biological process, molecular function, and cellular component for the male and female proteins. The abundance of the proteins differed, with one protein showing an increase (elongation factor 1 α, EF1α) and two showing reductions (actin family) in females versus males. Overall, the study verified the total proteomes differences between male and female Ae. aegypti based on protein identification and interactions, functional ontologies, and differentially abundant proteins. Some of the identified proteins merit further investigation to elucidate their roles in blocking viral transmission.
This paper presents the effect of the micro-sized particles on the storage modulus and durability characteristics of magnetorheological elastomers (MREs). The initial phase of the investigation is to determine any associations among the microparticles' weight percent fraction (wt%), structure arrangement, and the storage modulus of MRE samples. In order to carry out this, both isotropic and anisotropic types of MRE samples consisting of the silicone rubber matrix and 50, 60, 70, 75, and 80 wt% microparticles of carbonyl iron fractions are prepared. It is identified from the magneto-rheometer that the increase in storage modulus and decrease in linear viscoelastic region limit are observed in varying consistency depending on wt% and particle arrangement. The consistency of this dependency feature is highlighted by superimposing all of the graphs plotted to create the proposed the samples' behavior model. In response to increasing magnetic stimulation, a sample of 70 wt% microparticles with an isotropic arrangement is found to be significant and stable. The experimentally defined fraction is then used for the durability test as the second phase of the investigation. During this phase, the durability evaluation is subjected to stress relaxation for an extended period of time. After undergoing durability testing, storage modulus performance is decreased by 0.7-13% at various magnetic stimulation levels. This result directly indicates that the storage modulus characteristics of different forms of MRE are sensitive to the different iron particle fractions' and microparticles' alignment. Therefore, important treatments to alter the storage modulus can be undertaken before the practical implementation to accommodate any desired performance of MRE itself and MRE application systems.
Functional electrical stimulation (FES) device has been widely used by spinal cord injury (SCI) patients in their rehab exercises to restore motor function to their paralysed muscles. The major challenge of muscle contraction induced by FES is early muscle fatigue due to the open-loop stimulation strategy. To reduce the early muscle fatigue phenomenon, a closed-loop FES system is proposed to track the angle of the limb's movement and provide an accurate amount of charge according to the desired reference angle. Among the existing feedback controllers, fuzzy logic controller (FLC) has been found to exhibit good control performance in handling complex non-linear systems without developing any complex mathematical model. Recently, there has been considerable interest in the implementation of FLC in hardware embedded systems. Therefore, in this paper, a digital fuzzy feedback controller (FFC) embedded in a field-programmable gate array (FPGA) board was proposed. The digital FFC mainly consists of an analog-to-digital converter (ADC) Data Acquisition and FLC sub-modules. The FFC was designed to monitor and control the progress of knee extension movement by regulating the stimulus pulse width duration to meet the target angle. The knee is expected to extend to a maximum reference angle setting (70°, 40° or 30°) from its normal position of 0° once the stimulus charge is applied to the muscle by the FES device. Initially, the FLC was modelled using MATLAB Simulink. Then, the FLC was hardcoded into digital logic using hardware description language (HDL) Verilog codes. Thereafter, the performance of the digital FLC was tested with a knee extension model using the HDL co-simulation technique in MATLAB Simulink. Finally, for real-time verification, the designed digital FFC was downloaded to the Intel FPGA (DE2-115) board. The digital FFC utilized only 4% of the total FPGA (Cyclone IV E) logic elements (LEs) and required 238 µs to regulate stimulus pulse width data, including 3 µs for the FLC computation. The high processing speed of the digital FFC enables the stimulus pulse width duration to be updated every stimulation cycle. Furthermore, the implemented digital FFC has demonstrated good control performance in accurately controlling the stimulus pulse width duration to reach the desired reference angle with very small overshoot (1.4°) and steady-state error (0.4°). These promising results are very useful for a real-world closed-loop FES application.
The MXenes are a novel family of 2-D materials with promising biomedical activity, however, their anticancer potential is still largely unexplored. In this study, a comparative cytotoxicity investigation of Ti3C2 MXenes with polypropylene glycol (PPG), and polyethylene glycol (PEG) surface-modified 2-D Ti3C2 MXene flakes has been conducted towards normal and cancerous human cell lines. The wet chemical etching method was used to synthesize MXene followed by a simple chemical mixing method for surface modification of Ti3C2 MXene with PPG and PEG molecules. SEM and XRD analyses were performed to examine surface morphology and elemental composition, respectively. FTIR and UV-vis spectroscopy were used to confirm surface modification and light absorption, respectively. The cell lines used to study the cytotoxicity of MXene and surface-modified MXenes in this study were normal (HaCaT and MCF-10A) and cancerous (MCF-7 and A375) cells. These cell lines were also used as controls (without exposure to study material and irradiation) to measure their baseline cell viability under the same lab environment. The surface-modified MXenes exhibited a sharp reduction in cell viability towards both normal (HaCaT and MCF-10A) and cancerous (MCF-7 and A375) cells but cytotoxicity was more pronounced towards cancerous cell lines. This may be due to the difference in cell metabolism and the occurrence of high pre-existing levels of reactive oxygen species (ROS) within cancerous cells. The highest toxicity towards both normal and cancerous cell lines was observed with PEGylated MXenes followed by PPGylated and bare MXenes. The normal cell's viability was barely above 70% threshold with 250 mg/L PEGylated MXene concentration whereas PPGylated and bare MXene were less toxic towards normal cells, even at 500 mg/L concentration. Moreover, the toxicity was found to be directly related to the type of cell lines. In general, the HaCaT cell line exhibited the lowest toxicity while toxicity was highest in the case of the A375 cell line. The photothermal studies revealed high photo response for PEGylated MXene followed by PPGylated and bare MXenes. However, the PPGylated MXene's lower cytotoxicity towards normal cells while comparable toxicity towards malignant cells as compared to PEGylated MXenes makes the former a relatively safe and effective anticancer agent.
Micro mechanism consideration is critical for gaining a thorough understanding of amorphous shear band behavior in magnetorheological (MR) solids, particularly those with viscoelastic matrices. Heretofore, the characteristics of shear bands in terms of formation, physical evolution, and response to stress distribution at the localized region have gone largely unnoticed and unexplored. Notwithstanding these limitations, atomic force microscopy (AFM) has been used to explore the nature of shear band deformation in MR materials during stress relaxation. Stress relaxation at a constant low strain of 0.01% and an oscillatory shear of defined test duration played a major role in the creation of the shear band. In this analysis, the localized area of the study defined shear bands as varying in size and dominantly deformed in the matrix with no evidence of inhibition by embedded carbonyl iron particles (CIPs). The association between the shear band and the adjacent zone was further studied using in-phase imaging of AFM tapping mode and demonstrated the presence of localized affected zone around the shear band. Taken together, the results provide important insights into the proposed shear band deformation zone (SBDZ). This study sheds a contemporary light on the contentious issue of amorphous shear band deformation behavior and makes several contributions to the current literature.
Several agro-waste materials have been utilized for sustainable engineering and environmental application over the past decades, showing different degrees of effectiveness. However, information concerning the wider use of palm oil clinker (POC) and its performance is still lacking. Therefore, as a solid waste byproduct produced in one of the oil palm processing stages, generating a huge quantity of waste mostly dumped into the landfill, the waste-to-resource potential of POC should be thoroughly discussed in a review. Thus, this paper provides a systematic review of the current research articles on the several advances made from 2005 to 2021 regarding palm oil clinker physical properties and performances, with a particular emphasis on their commitments to cost savings during environmental and engineering applications. The review begins by identifying the potential of POC application in conventional and geopolymer structural elements such as beams, slabs, and columns made of concrete, mortar, or paste for coarse aggregates, sand, and cement replacement. Aspects such as performance of POC in wastewater treatment processes, fine aggregate and cement replacement in asphaltic and bituminous mixtures during highway construction, a bio-filler in coatings for steel manufacturing processes, and a catalyst during energy generation are also discussed. This review further describes the effectiveness of POC in soil stabilization and the effect of POC pretreatment for performance enhancement. The present review can inspire researchers to find research gaps that will aid the sustainable use of agroindustry wastes. The fundamental knowledge contained in this review can also serve as a wake-up call for researchers that will motivate them to explore the high potential of utilizing POC for greater environmental benefits associated with less cost when compared with conventional materials.
Microbial fuel cell (MFC) would be a standalone solution for clean, sustainable energy and rural electrification. It can be used in addition to wastewater treatment for bioelectricity generation. Materials chosen for the membrane and electrodes are of low cost with suitable conducting ions and electrical properties. The prime objective of the present work is to enhance redox reactions by using novel and low-cost cathode catalysts synthesized from waste castor oil. Synthesized graphene has been used as an anode, castor oil-emitted carbon powder serves as a cathode, and clay material acts as a membrane. Three single-chambered MFC modules developed were used in the current study, and continuous readings were recorded. The maximum voltage achieved was 0.36 V for a 100 mL mixture of domestic wastewater and cow dung for an anodic chamber of 200 mL. The maximum power density obtained was 7280 mW/m2. In addition, a performance test was evaluated for another MFC with inoculums slurry, and a maximum voltage of 0.78 V and power density of 34.4093 mW/m2 with an anodic chamber of 50 mL was reported. The present study's findings show that such cathode catalysts can be a suitable option for practical applications of microbial fuel cells.
Filled hybrid composites are widely used in various structural applications where machining is critical. Hence, it is essential to understand the performance of the fibre composites' machining behaviour. As such, a new hybrid structural composite was fabricated with redmud as filler and sisal fibre as reinforcement in polyester matrix. The composite was then tested for its drilling performance. A comprehensive drilling experiment was conducted using Taguchi L27 orthogonal array. The effect of the drill tool point angle, the cutting speed, the feed rate on thrust force, delamination, and burr formation were analysed for producing quality holes. The significance of each parameter was analysed, and the experimental outcomes revealed some important findings in the context of the drilling behaviour of sisal fibre/polyester composites with redmud as a filler. Spindle speed contributed 39% in affecting the thrust force, while the feed rate had the maximum influence of ca. 38% in affecting delamination.