Emotions are fundamental for human beings and play an important role in human cognition. Emotion is commonly associated with logical decision making, perception, human interaction, and to a certain extent, human intelligence itself. With the growing interest of the research community towards establishing some meaningful "emotional" interactions between humans and computers, the need for reliable and deployable solutions for the identification of human emotional states is required. Recent developments in using electroencephalography (EEG) for emotion recognition have garnered strong interest from the research community as the latest developments in consumer-grade wearable EEG solutions can provide a cheap, portable, and simple solution for identifying emotions. Since the last comprehensive review was conducted back from the years 2009 to 2016, this paper will update on the current progress of emotion recognition using EEG signals from 2016 to 2019. The focus on this state-of-the-art review focuses on the elements of emotion stimuli type and presentation approach, study size, EEG hardware, machine learning classifiers, and classification approach. From this state-of-the-art review, we suggest several future research opportunities including proposing a different approach in presenting the stimuli in the form of virtual reality (VR). To this end, an additional section devoted specifically to reviewing only VR studies within this research domain is presented as the motivation for this proposed new approach using VR as the stimuli presentation device. This review paper is intended to be useful for the research community working on emotion recognition using EEG signals as well as for those who are venturing into this field of research.
Kosakonia radicincitans (formerly known as Enterobacter radicincitans), an endophytic bacterium was isolated from the symptomatic tissues of bacterial wilt diseased banana (Musa spp.) plant in Malaysia. The total genome size of K. radicincitans UMEnt01/12 is 5 783 769 bp with 5463 coding sequences (CDS), 75 tRNAs, and 9 rRNAs. The annotated draft genome of the K. radicincitans UMEnt01/12 strain might shed light on its role as a bacterial wilt-associated bacterium.
Microbial-based fertilizer has been widely used as a healthier and better alternative to agrochemical products. However, the effects of biofertilizers on the rhizospheric microbiota has rarely been investigated. Thus, the aim of this study was to investigate the effects of symbiotic fungus Trichoderma asperellum SL2-based inoculant on the soil bacterial population through next generation sequencing using a metabarcoding approach. The treatment plots were treated with T. asperellum SL2 spore suspension, while the control plots were treated with sterilized distilled water. The results showed similar bacterial microbiome profiles in the soil of control and T. asperellum SL2-treated plots. In conclusion, the application of the T. asperellum SL2 inoculant had not exerted a negative impact towards the bacterial population as similar observation was reflected in control plots. Nonetheless, future research should be conducted to investigate the effects of repeated application of T. asperellum SL2 over a longer period on the rice microbiota communities.
Arboviruses are a significant threat to global public health, with outbreaks occurring worldwide. Toll-like receptors (TLRs) play a crucial role in the innate immune response against these viruses by recognizing pathogen-associated molecular patterns and initiating an inflammatory response. Significantly, TLRs commonly implicated in the immune response against viral infections include TLR2, TLR4, TLR6, TLR3, TLR7, and TLR8; limiting or allowing them to replicate and spread within the host. Modulating TLRs has emerged as a promising approach to combat arbovirus infections. This review summarizes recent advances in TLR modulation as a therapeutic target in arbovirus infections. Studies have shown that the activation of TLRs can enhance the immune response against arbovirus infections, leading to increased viral clearance and protection against disease. Conversely, inhibition of TLRs can reduce the excessive inflammation and tissue damage associated with arbovirus infection. Modulating TLRs represents a potential therapeutic strategy to combat arbovirus infections.
In this paper, the electrical, dielectric, Raman and small angle X-ray scattering (SAXS) structure behavior of disposed transformer oil in the presence of multi-walled carbon nanotube (MWCNT) were systematically tested to verify their versatility for preparing better alternative transformer oil in future. MWCNT nanofluids are prepared using a two-step method with concentrations ranging from 0.00 to 0.02 g/L. The test results reveal that 0.005 g/L concentration possesses the most optimum performance based on the electrical (AC breakdown and lightning impulse) and dielectric (permittivity, dissipation factor and resistivity) behavior. According to the trend of AC breakdown strength and lightning impulse pattern, there were 212.58% and 40.01% enhancement indicated for 0.005 g/L concentration compared to the disposed transformer oil. The presence of MWCNT also yielding to the decrement of dissipation factor, increased on permittivity and resistivity behavior of disposed transformer oil which reflected to the performance of electrical properties. Furthermore, it is found that these features correlated to the structural properties as systematically verify by Raman and SAXS analysis study.
Antibody-based treatment was first used in 1891 for the treatment of diphtheria. Since then, monoclonal antibodies (mAbs) have been developed to treat many diseases such as cancer and act as vaccines. However, murine-derived therapeutic mAbs were found to be highly immunogenic, and caused anti-drug antibodies (ADAs) reaction, reducing their efficacy and causing severe infusion reactions. Fully human, humanised, and chimeric antibodies were then introduced for better therapeutic efficacy. With the introduction of immune response associated with mAbs immunogenicity. This review explores the immunogenicity of mAbs, its mechanism, contributing factors, and its impact on therapeutic efficacy. It also discusses immunogenicity assessment for preclinical studies and strategies for minimising immunogenicity for effective therapeutic treatment in various diseases. Finally, predicting immunogenicity in drug development is essential for selecting top drug candidates. A lot of methods can be implemented by the researchers and developers to reduce the development of ADAs while simultaneously minimising the immunogenicity reaction of mAbs.