Natural product is an excellent candidate for alternative medicine for disease management. The bulb of E. bulbosa is one of the notable Iridaceae family with a variety therapeutic potential that is widely cultivated in Southeast Asia. The bulb has been used traditionally among the Dayak community as a folk medicine to treat several diseases like diabetes, breast cancer, nasal congestion, and fertility problems. The bulb is exceptionally rich in phytochemicals like phenolic and flavonoid derivatives, naphthalene, anthraquinone, and naphthoquinone. The electronic database was searched using various keywords, i.e., E. bulbosa, E. americana, E. palmifolia, E. platifolia, and others due to the interchangeably used scientific names of different countries. Scientific investigations revealed that various pharmacological activities were recorded from the bulb of E. bulbosa including anti-cancer, anti-diabetic, anti-bacterial, anti-fungi, anti-viral, anti-inflammatory, dermatological problems, anti-oxidant, and anti-fertility. The potential application of the bulb in the food industry and in animal nutrition was also discussed to demonstrate its great versatility. This is a compact study and is the first study to review the extensive pharmacological activities of the E. bulbosa bulb and its potential applications. The development of innovative food and pharma products from the bulb of E. bulbosa is of great interest.
This article proposes a novel data selection technique called the mixed peak-over-threshold-block-maxima (POT-BM) approach for modeling unhealthy air pollution events. The POT technique is employed to obtain a group of blocks containing data points satisfying extreme-event criteria that are greater than a particular threshold u. The selected groups are defined as POT blocks. In parallel with that, a declustering technique is used to overcome the problem of dependency behaviors that occurs among adjacent POT blocks. Finally, the BM concept is integrated to determine the maximum data points for each POT block. Results show that the extreme data points determined by the mixed POT-BM approach satisfy the independent properties of extreme events, with satisfactory fitted model precision results. Overall, this study concludes that the mixed POT-BM approach provides a balanced tradeoff between bias and variance in the statistical modeling of extreme-value events. A case study was conducted by modeling an extreme event based on unhealthy air pollution events with a threshold u > 100 in Klang, Malaysia.
For almost a half-decade, the unique autocorrelation properties of Golay complementary pairs (GCP) have added a significant value to the key performance of conventional time-domain multiplexed fiber Bragg grating sensors (TDM-FBGs). However, the employment of the unipolar form of Golay coded TDM-FBG has suffered from several performance flaws, such as limited improvement of the signal-to-noise ratio (SNIR), noisy backgrounds, and distorted signals. Therefore, we propose and experimentally implement several digital filtering techniques to mitigate such limitations. Moving averages (MA), Savitzky-Golay (SG), and moving median (MM) filters were deployed to process the signals from two low reflectance FBG sensors located after around 16 km of fiber. The first part of the experiment discussed the sole deployment of Golay codes from 4 bits to 256 bits in the TDM-FBG sensor. As a result, the total SNIR of around 8.8 dB was experimentally confirmed for the longest 256-bit code. Furthermore, the individual deployment of MA, MM, and SG filters within the mentioned decoded sequences secured a further significant increase in SNIR of around 4, 3.5, and 3 dB, respectively. Thus, the deployment of the filtering technique alone resulted in at least four times faster measurement time (equivalent to 3 dB SNIR). Overall, the experimental analysis confirmed that MM outperformed the other two techniques in better signal shape, fastest signal transition time, comparable SNIR, and capability to maintain high spatial resolution.
The objective of this study was to explore the effects of dietary acid load (DAL) and IGF1 and IL6 gene polymorphisms and their potential diet-gene interactions on metabolic traits. A total of 211 community-dwelling postmenopausal women were recruited. DAL was estimated using potential renal acid load (PRAL). Blood was drawn for biochemical parameters and DNA was extracted and Agena® MassARRAY was used for genotyping analysis to identify the signalling of IGF1 (rs35767 and rs7136446) and IL6 (rs1800796) polymorphisms. Interactions between diet and genetic polymorphisms were assessed using regression analysis. The result showed that DAL was positively associated with fasting blood glucose (FBG) (β = 0.147, p < 0.05) and there was significant interaction effect between DAL and IL6 with systolic blood pressure (SBP) (β = 0.19, p = 0.041). In conclusion, these findings did not support the interaction effects between DAL and IGF1 and IL6 single nucleotide polymorphisms (rs35767, rs7136446, and rs1800796) on metabolic traits, except for SBP. Besides, higher DAL was associated with higher FBG, allowing us to postulate that high DAL is a potential risk factor for diabetes.
The 'Back-to-nature' concept has currently been adopted intensively in various industries, especially the pharmaceutical industry. In the past few decades, the overuse of synthetic chemicals has caused severe damage to the environment and ecosystem. One class of natural materials developed to substitute artificial chemicals in the pharmaceutical industries is the natural polymers, including cellulose and its derivatives. The development of nanocelluloses as nanocarriers in drug delivery systems has reached an advanced stage. Cellulose nanofiber (CNF), nanocrystal cellulose (NCC), and bacterial nanocellulose (BC) are the most common nanocellulose used as nanocarriers in drug delivery systems. Modification and functionalization using various processes and chemicals have been carried out to increase the adsorption and drug delivery performance of nanocellulose. Nanocellulose may be attached to the drug by physical interaction or chemical functionalization for covalent drug binding. Current development of nanocarrier formulations such as surfactant nanocellulose, ultra-lightweight porous materials, hydrogel, polyelectrolytes, and inorganic hybridizations has advanced to enable the construction of stimuli-responsive and specific recognition characteristics. Thus, an opportunity has emerged to develop a new generation of nanocellulose-based carriers that can modulate the drug conveyance for diverse drug characteristics. This review provides insights into selecting appropriate nanocellulose-based hybrid materials and the available modification routes to achieve satisfactory carrier performance and briefly discusses the essential criteria to achieve high-quality nanocellulose.
In this review, the unique properties of intrinsically conducting polymer (ICP) in biomedical engineering fields are summarized. Polythiophene and its valuable derivatives are known as potent materials that can broadly be applied in biosensors, DNA, and gene delivery applications. Moreover, this material plays a basic role in curing and promoting anti-HIV drugs. Some of the thiophene's derivatives were chosen for different experiments and investigations to study their behavior and effects while binding with different materials and establishing new compounds. Many methods were considered for electrode coating and the conversion of thiophene to different monomers to improve their functions and to use them for a new generation of novel medical usages. It is believed that polythiophenes and their derivatives can be used in the future as a substitute for many old-fashioned ways of creating chemical biosensors polymeric materials and also drugs with lower side effects yet having a more effective response. It can be noted that syncing biochemistry with biomedical engineering will lead to a new generation of science, especially one that involves high-efficiency polymers. Therefore, since polythiophene can be customized with many derivatives, some of the novel combinations are covered in this review.
The bacterial leaf blight (BLB) caused by Xanthomonas oryzae pv. oryzae (Xoo) is one of the most serious rice diseases, causing huge yield losses worldwide. Several technologies and approaches have been opted to reduce the damage; however, these have had limited success. Recently, scientists have been focusing their efforts on developing efficient and environmentally friendly nanobactericides for controlling bacterial diseases in rice fields. In the present study, a scanning electron microscope (SEM), transmission electron microscope (TEM), and a confocal laser scanning microscope (CLSM) were utilized to investigate the mode of actions of ginger EOs on the cell structure of Xoo. The ginger EOs caused the cells to grow abnormally, resulting in an irregular form with hollow layers, whereas the dimethylsulfoxide (DMSO) treatment showed a typical rod shape for the Xoo cell. Ginger EOs restricted the growth and production of biofilms by reducing the number of biofilms generated as indicated by CLSM. Due to the instability, poor solubility, and durability of ginger EOs, a nanoemulsions approach was used, and a glasshouse trial was performed to assess their efficacy on BLB disease control. The in vitro antibacterial activity of the developed nanobactericides was promising at different concentration (50-125 µL/mL) tested. The efficacy was concentration-dependent. There was significant antibacterial activity recorded at higher concentrations. A glasshouse trial revealed that developed nanobactericides managed to suppress BLB disease severity effectively. Treatment at a concentration of 125 μL/mL was the best based on the suppression of disease severity index, AUDPC value, disease reduction (DR), and protection index (PI). Furthermore, findings on plant growth, physiological features, and yield parameters were significantly enhanced compared to the positive control treatment. In conclusion, the results indicated that ginger essential oils loaded-nanoemulsions are a promising alternative to synthetic antibiotics in suppressing Xoo growth, regulating the BLB disease, and enhancing rice yield under a glasshouse trial.
The world is currently facing an ongoing coronavirus disease 2019 (COVID-19) pandemic. The disease is a highly contagious respiratory disease which is caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Current control measures used by many countries include social distancing, wearing face masks, frequent hand washing, self-isolation, and vaccination. The current commercially available vaccines are injectable vaccines, although a few intranasal vaccines are in trial stages. The reported side effects of COVID-19 vaccines, perceptions towards the safety of the vaccines, and frequent mutation of the virus may lead to poor herd immunity. In veterinary medicine, attaining herd immunity is one of the main considerations in disease control, and herd immunity depends on the use of efficacious vaccines and the vaccination coverage in a population. Hence, many aerosol or intranasal vaccines have been developed to control veterinary respiratory diseases such as Newcastle disease, rinderpest, infectious bronchitis, and haemorrhagic septicaemia. Different vaccine technologies could be employed to improve vaccination coverage, including the usage of an intranasal live recombinant vaccine or live mutant vaccine. This paper discusses the potential use of intranasal vaccination strategies against human COVID-19, based on a veterinary intranasal vaccine strategy.
Rickettsia raoultii is one of the causative agents of tick-borne lymphadenopathy in humans. This bacterium was previously isolated and propagated in tick cell lines; however, the growth characteristics have not been investigated. Here, we present the replication kinetics of R. raoultii in cell lines derived from different tick genera (BME/CTVM23, RSE/PILS35, and IDE8). Tick cell cultures were infected in duplicate with cryopreserved R. raoultii prepared from homologous cell lines. By 12-14 days post infection, 100% of the cells were infected, as visualized in Giemsa-stained cytocentrifuge smears. R. raoultii growth curves, determined by rickettsiae-specific gltA qPCR, exhibited lag, exponential, stationary and death phases. Exponential phases of 4-12 days and generation times of 0.9-2.6 days were observed. R. raoultii in BME/CTVM23 and RSE/PILS35 cultures showed, respectively, 39.5- and 37.1-fold increases compared to the inoculum. In contrast, multiplication of R. raoultii in the IDE8 cultures was 110.1-fold greater than the inoculum with a 7-day stationary phase. These findings suggest variation in the growth kinetics of R. raoultii in the different tick cell lines tested, amongst which IDE8 cells could tolerate the highest levels of R. raoultii replication. Further studies of R. raoultii are needed for a better understanding of its persistence within tick populations.
Fungi, especially edible mushrooms, are considered as high-quality food with nutritive and functional values. They are of considerable interest and have been used in the synthesis of nutraceutical supplements due to their medicinal properties and economic significance. Specific fungal groups, including predominantly filamentous endophytic fungi from Ascomycete phylum and several Basidiomycetes, produce secondary metabolites (SMs) with bioactive properties that are involved in the antimicrobial and antioxidant activities. These beneficial fungi, while high in protein and important fat contents, are also a great source of several minerals and vitamins, in particular B vitamins that play important roles in carbohydrate and fat metabolism and the maintenance of the nervous system. This review article will summarize and discuss the abilities of fungi to produce antioxidant, anticancer, antiobesity, and antidiabetic molecules while also reviewing the evidence from the last decade on the importance of research in fungi related products with direct and indirect impact on human health.
Neuropathic pain is a chronic pain condition persisting past the presence of any noxious stimulus or inflammation. Zerumbone, of the Zingiber zerumbet ginger plant, has exhibited anti-allodynic and antihyperalgesic effects in a neuropathic pain animal model, amongst other pharmacological properties. This study was conducted to further elucidate the mechanisms underlying zerumbone's antineuropathic actions. Research on therapeutic agents involving cannabinoid (CB) and peroxisome proliferator-activated receptors (PPARs) is rising. These receptor systems have shown importance in causing a synergistic effect in suppressing nociceptive processing. Behavioural responses were assessed using the von Frey filament test (mechanical allodynia) and Hargreaves plantar test (thermal hyperalgesia), in chronic constriction injury (CCI) neuropathic pain mice. Antagonists SR141716 (CB1 receptor), SR144528 (CB2 receptor), GW6471 (PPARα receptor) and GW9662 (PPARγ receptor) were pre-administered before the zerumbone treatment. Our findings indicated the involvement of CB1, PPARα and PPARγ in zerumbone's action against mechanical allodynia, whereas only CB1 and PPARα were involved against thermal hyperalgesia. Molecular docking studies also suggest that zerumbone has a comparable and favourable binding affinity against the respective agonist on the CB and PPAR receptors studied. This finding will contribute to advance our knowledge on zerumbone and its significance in treating neuropathic pain.
Numerous studies have shown that dispositional mindfulness is positively associated with many mental abilities related to sports performance, including psychological skills and mental toughness. The purpose of this study was to explore the relationship between dispositional mindfulness, psychological skills, and mental toughness among different types of athletes. For this cross-sectional study, 101 college athletes were recruited. Their dispositional mindfulness, psychological skills, and mental toughness were measured by the Mindfulness Attention Awareness Scale (MAAS), Athletic Psychological Skills Inventory (APSI), and Traits of Mental Toughness Inventory for Sports Scale (TMTIS). Pearson's correlation was used to calculate how dispositional mindfulness is associated with psychological skills and mental toughness. The results revealed that dispositional mindfulness is positively associated with comprehensive APSI (r = 0.21-0.36, p < 0.05), TMTIS overall (r = 0.27, p < 0.01), positive effort (r = 0.26, p = 0.01), and pressure (r = 0.30, p < 0.01). These findings suggest a positive linkage between mindfulness and the two examined psychological characteristics related to sports performance. Other approaches to increase mindfulness may be considered in the future.
The COVID-19 pandemic, as well as the more general global increase in viral diseases, has led researchers to look to the plant kingdom as a potential source for antiviral compounds. Since ancient times, herbal medicines have been extensively applied in the treatment and prevention of various infectious diseases in different traditional systems. The purpose of this review is to highlight the potential antiviral activity of plant compounds as effective and reliable agents against viral infections, especially by viruses from the coronavirus group. Various antiviral mechanisms shown by crude plant extracts and plant-derived bioactive compounds are discussed. The understanding of the action mechanisms of complex plant extract and isolated plant-derived compounds will help pave the way towards the combat of this life-threatening disease. Further, molecular docking studies, in silico analyses of extracted compounds, and future prospects are included. The in vitro production of antiviral chemical compounds from plants using molecular pharming is also considered. Notably, hairy root cultures represent a promising and sustainable way to obtain a range of biologically active compounds that may be applied in the development of novel antiviral agents.
Electrospinning technology, which was previously known as a scientific interdisciplinary research approach, is now ready to move towards a practice-based interdisciplinary approach in a variety of fields, progressively. Electrospun nanofiber-applied products are made directly from a nonwoven fabric-based membranes prepared from polymeric liquids involving the application of sufficiently high voltages during electrospinning. Today, electrospun nanofiber-based materials are of remarkable interest across multiple fields of applications, such as in electronics, sensors, functional garments, sound proofing, filters, wound dressing and scaffolds. This article presents such a review for summarizing the current progress on the manufacturing scalability of electrospun nanofibers and the commercialization of electrospun nanofiber products by dedicated companies globally. Despite the clear potential and limitless possibilities for electrospun nanofiber applications, the uptake of electrospinning by the industry is still limited due to the challenges in the manufacturing and turning of electrospun nanofibers into physical products. The recent developments in the field of electrospinning, such as the prominent nonwoven technology, personal views and the potential path forward for the growth of commercially applied products based on electrospun nanofibers, are also highlighted.
The neuroprotective potential of Orthosiphon stamineus leaf proteins (OSLPs) has never been evaluated in SH-SY5Y cells challenged by hydrogen peroxide (H2O2). This work thus aims to elucidate OSLP neuroprotective potential in alleviating H2O2 stress. OSLPs at varying concentrations were evaluated for cytotoxicity (24 and 48 h) and neuroprotective potential in H2O2-induced SH-SY5Y cells (24 h). The protective mechanism of H2O2-induced SH-SY5Y cells was also explored via mass-spectrometry-based label-free quantitative proteomics (LFQ) and bioinformatics. OSLPs (25, 50, 125, 250, 500, and 1000 µg/mL; 24 and 48 h) were found to be safe. Pre-treatments with OSLP doses (250, 500, and 1000 µg/mL, 24 h) significantly increased the survival of SH-SY5Y cells in a concentration-dependent manner and improved cell architecture-pyramidal-shaped cells, reduced clumping and shrinkage, with apparent neurite formations. OSLP pre-treatment (1000 µg/mL, 24 h) lowered the expressions of two major heat shock proteins, HSPA8 (heat shock protein family A (Hsp70) member 8) and HSP90AA1 (heat shock protein 90), which promote cellular stress signaling under stress conditions. OSLP is, therefore, suggested to be anti-inflammatory by modulating the "signaling of interleukin-4 and interleukin-13" pathway as the predominant mechanism in addition to regulating the "attenuation phase" and "HSP90 chaperone cycle for steroid hormone receptors" pathways to counteract heat shock protein (HSP)-induced damage under stress conditions.
Successful cyber-attacks are caused by the exploitation of some vulnerabilities in the software and/or hardware that exist in systems deployed in premises or the cloud. Although hundreds of vulnerabilities are discovered every year, only a small fraction of them actually become exploited, thereby there exists a severe class imbalance between the number of exploited and non-exploited vulnerabilities. The open source national vulnerability database, the largest repository to index and maintain all known vulnerabilities, assigns a unique identifier to each vulnerability. Each registered vulnerability also gets a severity score based on the impact it might inflict upon if compromised. Recent research works showed that the cvss score is not the only factor to select a vulnerability for exploitation, and other attributes in the national vulnerability database can be effectively utilized as predictive feature to predict the most exploitable vulnerabilities. Since cybersecurity management is highly resource savvy, organizations such as cloud systems will benefit when the most likely exploitable vulnerabilities that exist in their system software or hardware can be predicted with as much accuracy and reliability as possible, to best utilize the available resources to fix those first. Various existing research works have developed vulnerability exploitation prediction models by addressing the existing class imbalance based on algorithmic and artificial data resampling techniques but still suffer greatly from the overfitting problem to the major class rendering them practically unreliable. In this research, we have designed a novel cost function feature to address the existing class imbalance. We also have utilized the available large text corpus in the extracted dataset to develop a custom-trained word vector that can better capture the context of the local text data for utilization as an embedded layer in neural networks. Our developed vulnerability exploitation prediction models powered by a novel cost function and custom-trained word vector have achieved very high overall performance metrics for accuracy, precision, recall, F1-Score and AUC score with values of 0.92, 0.89, 0.98, 0.94 and 0.97, respectively, thereby outperforming any existing models while successfully overcoming the existing overfitting problem for class imbalance.
Networking is crucial for smart city projects nowadays, as it offers an environment where people and things are connected. This paper presents a chronology of factors on the development of smart cities, including IoT technologies as network infrastructure. Increasing IoT nodes leads to increasing data flow, which is a potential source of failure for IoT networks. The biggest challenge of IoT networks is that the IoT may have insufficient memory to handle all transaction data within the IoT network. We aim in this paper to propose a potential compression method for reducing IoT network data traffic. Therefore, we investigate various lossless compression algorithms, such as entropy or dictionary-based algorithms, and general compression methods to determine which algorithm or method adheres to the IoT specifications. Furthermore, this study conducts compression experiments using entropy (Huffman, Adaptive Huffman) and Dictionary (LZ77, LZ78) as well as five different types of datasets of the IoT data traffic. Though the above algorithms can alleviate the IoT data traffic, adaptive Huffman gave the best compression algorithm. Therefore, in this paper, we aim to propose a conceptual compression method for IoT data traffic by improving an adaptive Huffman based on deep learning concepts using weights, pruning, and pooling in the neural network. The proposed algorithm is believed to obtain a better compression ratio. Additionally, in this paper, we also discuss the challenges of applying the proposed algorithm to IoT data compression due to the limitations of IoT memory and IoT processor, which later it can be implemented in IoT networks.
Multiple recurrent somatic mutations have recently been identified in association with myeloproliferative neoplasms (MPN). This meta-analysis aims to assess the pooled prevalence of TET2 gene mutations among patients with MPN. Six databases (PubMed, Scopus, ScienceDirect, Google Scholar, Web of Science and Embase) were searched for relevant studies from inception till September 2020, without language restrictions. The eligibility criteria included BCR-ABL-negative MPN adults with TET2 gene mutations. A random-effects model was used to estimate the pooled prevalence with 95% confidence intervals (CIs). Subgroup analyses explored results among different continents and countries, WHO diagnostic criteria, screening methods and types of MF. Quality assessment was undertaken using the Joanna Briggs Institute critical appraisal tool. The study was registered with PROSPERO (CRD42020212223). Thirty-five studies were included (n = 5121, 47.1% female). Overall, the pooled prevalence of TET2 gene mutations in MPN patients was 15.5% (95% CI: 12.1-19.0%, I2 = 94%). Regional differences explained a substantial amount of heterogeneity. The prevalence of TET2 gene mutations among the three subtypes PV, ET and MF were 16.8%, 9.8% and 15.7%, respectively. The quality of the included studies was determined to be moderate-high among 83% of the included studies. Among patients with BCR-ABL-negative MPN, the overall prevalence of TET2 gene mutations was 15.5%.
Together, 316L steel, magnesium-alloy, Ni-Ti, titanium-alloy, and cobalt-alloy are commonly employed biomaterials for biomedical applications due to their excellent mechanical characteristics and resistance to corrosion, even though at times they can be incompatible with the body. This is attributed to their poor biofunction, whereby they tend to release contaminants from their attenuated surfaces. Coating of the surface is therefore required to mitigate the release of contaminants. The coating of biomaterials can be achieved through either physical or chemical deposition techniques. However, a newly developed manufacturing process, known as powder mixed-electro discharge machining (PM-EDM), is enabling these biomaterials to be concurrently machined and coated. Thermoelectrical processes allow the migration and removal of the materials from the machined surface caused by melting and chemical reactions during the machining. Hydroxyapatite powder (HAp), yielding Ca, P, and O, is widely used to form biocompatible coatings. The HAp added-EDM process has been reported to significantly improve the coating properties, corrosion, and wear resistance, and biofunctions of biomaterials. This article extensively explores the current development of bio-coatings and the wear and corrosion characteristics of biomaterials through the HAp mixed-EDM process, including the importance of these for biomaterial performance. This review presents a comparative analysis of machined surface properties using the existing deposition methods and the EDM technique employing HAp. The dominance of the process factors over the performance is discussed thoroughly. This study also discusses challenges and areas for future research.
Cellulose and chitosan with remarkable biocompatibility and sophisticated physiochemical characteristics can be a new dawn to the advanced drug nano-carriers in cancer treatment. This study aims to synthesize layer-by-layer bionanocomposites from chitosan and rice straw cellulose encapsulated 5-Fluorouracil (CS-CF/5FU BNCs) using the ionic gelation method and the sodium tripolyphosphate (TPP) cross-linker. Data from X-ray and Fourier-transform infrared spectroscopy showed successful preparation of CS-CF/5FU BNCs. Based on images of scanning electron microscopy, 48.73 ± 1.52 nm was estimated for an average size of the bionanocomposites as spherical chitosan nanoparticles mostly coated rod-shaped cellulose reinforcement. 5-Fluorouracil indicated an increase in thermal stability after its encapsulation in the bionanocomposites. The drug encapsulation efficiency was found to be 86 ± 2.75%. CS-CF/5FU BNCs triggered higher drug release in a media simulating the colorectal fluid with pH 7.4 (76.82 ± 1.29%) than the gastric fluid with pH 1.2 (42.37 ± 0.43%). In in vitro cytotoxicity assays, cellulose fibers, chitosan nanoparticles and the bionanocomposites indicated biocompatibility towards CCD112 normal cells. Most promisingly, CS-CF/5FU BNCs at 250 µg/mL concentration eliminated 56.42 ± 0.41% of HCT116 cancer cells and only 8.16 ± 2.11% of CCD112 normal cells. Therefore, this study demonstrates that CS-CF/5FU BNCs can be considered as an eco-friendly and innovative nanodrug candidate for potential colorectal cancer treatment.