Discovery of novel SOS1 inhibitors using machine learning.

Overactivation of the rat sarcoma virus (RAS) signaling is responsible for 30% of all human malignancies. Son of sevenless 1 (SOS1), a crucial node in the RAS signaling pathway, could modulate RAS activation, offering a promising therapeutic strategy for RAS-driven cancers. Applying machine learning (ML)-based virtual screening (VS) on small-molecule databases, we selected a random forest (RF) regressor for its robustness and performance. Screening was performed with the L-series and EGFR-related datasets, and was extended to the Chinese National Compound Library (CNCL) with more than 1.4 million compounds. In addition to a series of documented SOS1-related molecules, we uncovered nine compounds that have an unexplored chemical framework and displayed inhibitory activity, with the most potent achieving more than 50% inhibition rate in the KRAS G12C/SOS1 PPI assay and an IC50 value in the proximity of 20 µg mL-1. Compared with the manner that known inhibitory agents bind to the target, hit compounds represented by CL01545365 occupy a unique pocket in molecular docking. An in silico drug-likeness assessment suggested that the compound has moderately favorable drug-like properties and pharmacokinetic characteristics. Altogether, our findings strongly support that, characterized by the distinctive binding modes, the recognition of novel skeletons from the carboxylic acid series could be candidates for developing promising SOS1 inhibitors.

Biosensor in smart food traceability system for food safety and security.

The burden of food contamination and food wastage has significantly contributed to the increased prevalence of foodborne disease and food insecurity all over the world. Due to this, there is an urgent need to develop a smarter food traceability system. Recent advancements in biosensors that are easy-to-use, rapid yet selective, sensitive, and cost-effective have shown great promise to meet the critical demand for onsite and immediate diagnosis and treatment of food safety and quality control (i.e. point-of-care technology). This review article focuses on the recent development of different biosensors for food safety and quality monitoring. In general, the application of biosensors in agriculture (i.e. pre-harvest stage) for early detection and routine control of plant infections or stress is discussed. Afterward, a more detailed advancement of biosensors in the past five years within the food supply chain (i.e. post-harvest stage) to detect different types of food contaminants and smart food packaging is highlighted. A section that discusses perspectives for the development of biosensors in the future is also mentioned.

A Smartphone-Based sEMG Signal Analysis System for Human Action Recognition.

In lower-limb rehabilitation, human action recognition (HAR) technology can be introduced to analyze the surface electromyography (sEMG) signal generated by movements, which can provide an objective and accurate evaluation of the patient's action. To balance the long cycle required for rehabilitation and the inconvenient factors brought by wearing sEMG devices, a portable sEMG signal acquisition device was developed that can be used under daily scenarios. Additionally, a mobile application was developed to meet the demand for real-time monitoring and analysis of sEMG signals. This application can monitor data in real time and has functions such as plotting, filtering, storage, and action capture and recognition. To build the dataset required for the recognition model, six lower-limb motions were developed for rehabilitation (kick, toe off, heel off, toe off and heel up, step back and kick, and full gait). The sEMG segment and action label were combined for training a convolutional neural network (CNN) to achieve high-precision recognition performance for human lower-limb actions (with a maximum accuracy of 97.96% and recognition accuracy for all actions reaching over 97%). The results show that the smartphone-based sEMG analysis system proposed in this paper can provide reliable information for the clinical evaluation of lower-limb rehabilitation.

Prospects of microalgae in nutraceuticals production with nanotechnology applications.

Nutraceutical supplements provide health benefits, such as fulfilling the lack of nutrients in the human body or being utilized to treat or cure certain diseases. As the world population is growing, certain countries are experiencing food crisis challenges, causing natural foods are not sustainable to be used for nutraceutical production because it will require large-scale of food supply to produce enriched nutraceutics. The high demand for abundant nutritional compounds has made microalgae a reliable source as they can synthesize high-value molecules through photosynthetic activities. However, some microalgae species are limited in growth and unable to accumulate a significant amount of biomass due to several factors related to environmental conditions. Therefore, adding nanoparticles (NPs) as a photocatalyst is considered to enhance the yield rate of microalgae in an energy-saving and economical way. This review focuses on the composition of microalgal biomass for nutraceutical production, the health perspectives of nutritional compounds on humans, and the application of nanotechnology on microalgae for improved production and harvesting. The results obtained show that microalgal-based compounds indeed have better nutrients content than natural foods. However, nanotechnology must be further comprehended to make them non-hazardous and sustainable.

Portable Multi-Channel Electrochemical Device with Good Interaction and Wireless Connection for On-Site Testing.

It is very important to rapidly test the key indicators of water in the field to fully evaluate the quality of the regional water environment. However, a high-resolution measuring device that can generate small currents for low-concentration analytes in water samples is often bulky, complex to operate, and difficult for data sharing. This work introduces a portable multi-channel electrochemical device with a small volume, good interaction, and data-sharing capabilities called PMCED. The PMCED provides an easy-to-operate graphical interactive interface to conveniently set the parameters for cyclic voltammetry or a differential pulse method performed by the four electrode channels. At the same time, the device, with a current sensitivity of 100 nA V-1, was applied to the detection of water samples with high background current and achieved a high-resolution measurement at low current levels. The PMCED uses the Narrow Band Internet of Things (NB-IoT) to meet the needs for uploading data to the cloud in remote areas. The electrochemical signal preprocessing and chemometrics models run in the cloud, and the final results are visualized on a web page, providing a remote access channel for on-site testing results.

In situ quantitative assessment of food oral processing parameters: A review of feasible techniques and devices.

Oral processing is a combination of various actions, the detailed description of which has always been the subject of relevant research. By means of imaging technology and sensory evaluation, more knowledge of oral processing have been accumulated. Presently, the advances in sensory technology have added quantitative parameters to the qualitative description of oral processing, which also enriched the specifics of each action. Previous studies have shown that oral processing includes lip closure, dental occlusion, masticatory muscles activity, tongue movement, and swallowing, whose processing contains rich information such as the movement of organ and the intensity of organ contacts. "Quantification" was taken in this review as the basic feature of in situ detection information, the relevant parameters and feasible methods for the quantitative description of each activity was recorded in detail. In addition, basic problems and feasible optimization schemes of the existing in situ detection device are also proposed in the hope of promoting the development of in situ detection device thus providing available information for the description of oral processing.

Dynamic alpha-gamma phase-amplitude coupling signatures during sevoflurane-induced loss and recovery of consciousness.

Phase-amplitude coupling (PAC) plays an important role in anesthetic-induced unconsciousness. The delta-alpha PAC signature during anesthetic-induced unconsciousness is gradually becoming known; however, the frequency dependence and spatial characteristics of PAC are still unclear. Multi-channel electroencephalography (EEG) was performed during the loss and recovery phases of consciousness in patients undergoing general anesthesia using sevoflurane. First, a spectral analysis was used to investigate the power change of the different frequency bands in the EEG signals. Second, PAC comodulogram analysis was performed to confirm the frequencies of the PAC phase drivers. Finally, to investigate the spatial characteristics of PAC, a novel PAC network was constructed using within- and cross-lead PAC, and a K-means clustering algorithm was used to identify PAC network patterns. Our results show that, in addition to the delta-alpha PAC, unconsciousness induced by sevoflurane was accompanied by spatial non-uniform alpha-gamma PAC in the cortical network, and dynamic PAC patterns between the anterior and posterior brain were observed during the unconscious phase. The dynamic transition of PAC network patterns indicates that brain states under sevoflurane-induced unconsciousness emerge from the regulation of functional integration and segregation instantiated by delta-alpha and alpha-gamma PAC.

Application and Progress of Chemometrics in Voltammetric Biosensing.

The voltammetric electrochemical sensing method combined with biosensors and multi-sensor systems can quickly, accurately, and reliably analyze the concentration of the main analyte and the overall characteristics of complex samples. Simultaneously, the high-dimensional voltammogram contains the rich electrochemical features of the detected substances. Chemometric methods are important tools for mining valuable information from voltammetric data. Chemometrics can aid voltammetric biosensor calibration and multi-element detection in complex matrix conditions. This review introduces the voltammetric analysis techniques commonly used in the research of voltammetric biosensor and electronic tongues. Then, the research on optimizing voltammetric biosensor results using classical chemometrics is summarized. At the same time, the incorporation of machine learning and deep learning has brought new opportunities to further improve the detection performance of biosensors in complex samples. Finally, smartphones connected with miniaturized voltammetric biosensors and chemometric methods provide a high-quality portable analysis platform that shows great potential in point-of-care testing.

Recent advances in the analytical strategies of microbial biosensor for detection of pollutants.

Microbial biosensor which integrates different types of microorganisms, such as bacteria, microalgae, fungi, and virus have become suitable technologies to address limitations of conventional analytical methods. The main applications of biosensors include the detection of environmental pollutants, pathogenic bacteria and compounds related to illness, and food quality. Each type of microorganisms possesses advantages and disadvantages with different mechanisms to detect the analytes of interest. Furthermore, there is an increasing trend in genetic modifications for the development of microbial biosensors due to potential for high-throughput analysis and portability. Many review articles have discussed the applications of microbial biosensor, but many of them focusing only about bacterial-based biosensor although other microbes also possess many advantages. Additionally, reviews on the applications of all microbes as biosensor especially viral and microbial fuel cell biosensors are also still limited. Therefore, this review summarizes all the current applications of bacterial-, microalgal-, fungal-, viral-based biosensor in regard to environmental, food, and medical-related applications. The underlying mechanism of each microbes to detect the analytes are also discussed. Additionally, microbial fuel cell biosensors which have great potential in the future are also discussed. Although many advantageous microbial-based biosensors have been discovered, other areas such as forensic detection, early detection of bacteria or virus species that can lead to pandemics, and others still need further investigation. With that said, microbial-based biosensors have promising potential for vast applications where the biosensing performance of various microorganisms are presented in this review along with future perspectives to resolve problems related on microbial biosensors.

A review on the diverse interactions between microalgae and nanomaterials: Growth variation, photosynthetic performance and toxicity.

Vast improvements in nanotechnology have led to the wide usage of nanomaterials (NMs) in daily products. This study reviews the interactions between NMs and microalgae in terms of impacts on growth and photosynthetic efficiency, and their toxicity on microalgae. All types of NMs such as carbon-based NMs (CNMs), metal oxide-based NMs (MONMs) and noble metal-based NMs (NMNMs) improve microalgal growth and photosynthetic efficiency at low concentration, typically ranging between 1 and 15 mg/L depending on the type of NMs, due to hormetic responses by microalgae. Higher concentrations of NMs have been found to reduce photosynthetic efficiency and subsequent growth inhibition of microalgae. MONMs-microalgae and NMNMs-microalgae interactions focus on membrane alteration, whereas carbon-based NMs-microalgae focus more on shading effect. The toxicity of each type of NMs on microalgae is in the order rGO > GO > MG > CNT for carbon-based NMs, ZnO > TiO2 > CuO > Fe2O3 for MONMs and Ag > Au > Pt for NMNMs. Incorporation of NMs in microalgae are seen to have promising future on producing higher microalgae yield with increased economic efficiency.

Prospects and environmental sustainability of phyconanotechnology: A review on algae-mediated metal nanoparticles synthesis and mechanism.

In recent years, researchers have proven that the employment of natural green components in the biogenesis of nanoparticles from microalgae species is one of the ways to delight the global environment issues. The application of nanotechnology with the exploitation of phycochemical produced from algae species is known as 'phyconanotechnology'. The use of biological compounds by microalgae as reducing agents for the synthesis of inorganic nanoparticles has shown promising results such as cost-effective and environmentally friendly. Different classifications of algae such as brown algae, red algae, green algae, and cyanobacteria are studied for the synthesis of different types of metal nanoparticles. It is also an important motive to acknowledge the mechanisms of the microalgae-mediated biosynthesis of nanoparticles via an intracellular pathway or extracellular pathway. Besides, microalgae species as biogenic sources preclude the use of conventional methods reagents, such as sodium borohydride (NaBH4) and N,N-dimethylformamide (DMF), which further consolidates their position as the best choice for sustainable (economically and environmentally) nanoparticle synthesis compared to the conventional nanoparticles synthesis pathway.

How far have we explored fungi to fight cancer?

The use of fungal cultures have been well documented in human history. Although its used in healthcare, like penicillin and statins, have saved countless of lives, but there is still no fungal products that are specifically indicated for cancers. Research into fungal-derived materials to curb cancers in the recent decades have made a considerable progress in terms of drug delivery vehicles, anticancer active ingredients and cancer immunotherapy. Various parts of the organisms have successfully been exploited to achieve specific tasks. Apart from the identification of novel anticancer compound from fungi, its native capsular structure can also be used as drug cargo to achieve higher oral bioavailability. This review summarises the anticancer potential of fungal-derived materials, highlighting the role of capsular polysaccharides, proteins, and other structures in variety of innovative utilities to fit the current pharmaceutical technology. Many bioactive compounds isolated from fungi have also been formulated into nanoparticles to achieve greater anticancer activity. The progress of fungal compounds and their analogues in clinical trials is also highlighted. In addition, the potential of various fungal species to be developed for anticancer immunotherapy are also discussed.

Smartphone-Based Electrochemical System for Biosensors and Biodetection.

With the advantages of high popularity, convenient operation, open-source operation systems, high resolution imaging, and excellent computing capabilities, smartphones have been widely used as the core of detection system for calculation, control, and real-time display. Hence, smartphones play an important role in electrochemical detection and optical detection. Smartphone-based electrochemical systems were combined with screen-printed electrode and interdigital electrodes for in situ detection. The electrodes were modified with biomaterials, chemical materials, and nanomaterials for biosensors and biodetection, such as 3-amino phenylboronic acid nanocomposites, graphene, gold nanoparticles, zinc oxide nanoparticles, carbon nanotubes, proteins, peptides, and antibodies. With the modified electrodes, the smartphone-based impedance system was used to detect acetone, bovine serum albumin, human serum albumin, and trinitrotoluene, while smartphone-based amperometric system was employed to monitor glucose, ascorbic acid, dopamine, uric acid, and levodopa. The smartphone-based electrochemical system for biosensors and biodetection has provided miniaturized and portable alternative for diagnosis, which is promising to find application in point-of-care testing (POCT).

Sonoproduction of nanobiomaterials - A critical review.

Ultrasound (US) demonstrates remarkable potential in synthesising nanomaterials, particularly nanobiomaterials targeted towards biomedical applications. This review briefly introduces existing top-down and bottom-up approaches for nanomaterials synthesis and their corresponding synthesis mechanisms, followed by the expounding of US-driven nanomaterials synthesis. Subsequently, the pros and cons of sono-nanotechnology and its advances in the synthesis of nanobiomaterials are drawn based on recent works. US-synthesised nanobiomaterials have improved properties and performance over conventional synthesis methods and most essentially eliminate the need for harsh and expensive chemicals. The sonoproduction of different classes and types of nanobiomaterials such as metal and superparamagnetic nanoparticles (NPs), lipid- and carbohydrate-based NPs, protein microspheres, microgels and other nanocomposites are broadly categorised based on the physical and/or chemical effects induced by US. This review ends on a good note and recognises US-driven synthesis as a pragmatic solution to satisfy the growing demand for nanobiomaterials, nonetheless some technical challenges are highlighted.

Recent Progress in Nanomaterials Modified Electrochemical Biosensors for the Detection of MicroRNA.

MicroRNAs (miRNAs) are important non-coding, single-stranded RNAs possessing crucial regulating roles in human body. Therefore, miRNAs have received extensive attention from various disciplines as the aberrant expression of miRNAs are tightly related to different types of diseases. Furthermore, the exceptional stability of miRNAs has presented them as biomarker with high specificity and sensitivity. However, small size, high sequence similarity, low abundance of miRNAs impose difficulty in their detection. Hence, it is of utmost importance to develop accurate and sensitive method for miRNA biosensing. Electrochemical biosensors have been demonstrated as promising solution for miRNA detection as they are highly sensitive, facile, and low-cost with ease of miniaturization. The incorporation of nanomaterials to electrochemical biosensor offers excellent prospects for converting biological recognition events to electronic signal for the development of biosensing platform with desired sensing properties due to their unique properties. This review introduces the signal amplification strategies employed in miRNA electrochemical biosensor and presents the feasibility of different strategies. The recent advances in nanomaterial-based electrochemical biosensor for the detection of miRNA were also discussed and summarized based on different types of miRNAs, opening new approaches in biological analysis and early disease diagnosis. Lastly, the challenges and future prospects are discussed.

Can algae contribute to the war with Covid-19?

The world at large is facing a new threat with the emergence of the Coronavirus Disease 2019 (COVID-19) pandemic. Though imperceptible by the naked eye, the medical, sociological and economical implications caused by this newly discovered virus have been and will continue to be a great impediment to our lives. This health threat has already caused over two million deaths worldwide in the span of a year and its mortality rate is projected to continue rising. In this review, the potential of algae in combating the spread of COVID-19 is investigated since algal compounds have been tested against viruses and algal anti-inflammatory compounds have the potential to treat the severe symptoms of COVID-19. The possible utilization of algae in producing value-added products such as serological test kits, vaccines, and supplements that would either mitigate or hinder the continued health risks caused by the virus is prominent. Many of the characteristics in algae can provide insights on the development of microalgae to fight against SARS-CoV-2 or other viruses and contribute in manufacturing various green and high-value products.

Battery-free, wireless, and flexible electrochemical patch for in situ analysis of sweat cortisol via near field communication.

Wearable and flexible biosensing devices have been widely developed for in situ detections. Cortisol is a vital biomarker which plays crucial regulatory role in numerous physiological processes of the human body. Here, a wireless, battery-free, and flexible integrated patch is developed for real-time on-body sweat cortisol detection. The patch integrated with all-printed flexible electrochemical immunosensor, which was used to detect cortisol through differential pulse voltammetry (DPV). The near field communication (NFC) module on the patch enables wireless power harvesting and data interaction with an NFC-enabled smartphone, which makes the patch get rid of rigid batteries and realize epidermal on-body testing. Multiple in situ detections on volunteers' sweat on the surface of skin showed that the flexible integrated patch could reflect the circadian rhythm of the body's sweat cortisol level changes in relaxed mood or under stress, which could be confirmed with the enzyme linked immunosorbent assay (ELISA) kit. In this way, the patch provides a rapid-detecting, convenient, and non-invasive sensing solution for in situ analysis of sweat cortisol, which can be applied for the personalized mental health management.

Salivary Cortisol Determination on Smartphone-Based Differential Pulse Voltammetry System.

Cortisol is commonly used as a significant biomarker of psychological or physical stress. With the accelerated pace of life, non-invasive cortisol detection at the point of care (POC) is in high demand for personal health monitoring. In this paper, an ultrasensitive immunosensor using gold nanoparticles/molybdenum disulfide/gold nanoparticles (AuNPs/MoS2/AuNPs) as transducer was explored for non-invasive salivary cortisol monitoring at POC with the miniaturized differential pulse voltammetry (DPV) system based on a smartphone. Covalent binding of cortisol antibody (CORT-Ab) onto the AuNPs/MoS2/AuNPs transducer was achieved through the self-assembled monolayer of specially designed polyethylene glycol (PEG, SH-PEG-COOH). Non-specific binding was avoided by passivating the surface with ethanolamine. The miniaturized portable DPV system was utilized for human salivary cortisol detection. A series current response of different cortisol concentrations decreased and exhibited a linear range of 0.5-200 nM, the detection limit of 0.11 nM, and high sensitivity of 30 µA M-1 with a regression coefficient of 0.9947. Cortisol was also distinguished successfully from the other substances in saliva. The recovery ratio of spiked human salivary cortisol and the variation of salivary cortisol level during one day indicated the practicability of the immunosensor based on the portable system. The results demonstrated the excellent performance of the smartphone-based immunosensor system and its great potential application for non-invasive human salivary cortisol detection at POC.

Fuzzy Evaluation Output of Taste Information for Liquor Using Electronic Tongue Based on Cloud Model.

As a taste bionic system, electronic tongues can be used to derive taste information for different types of food. On this basis, we have carried forward the work by making it, in addition to the ability of accurately distinguish samples, be more expressive by speaking evaluative language like human beings. Thus, this paper demonstrates the correlation between the qualitative digital output of the taste bionic system and the fuzzy evaluation language that conform to the human perception mode. First, through principal component analysis (PCA), backward cloud generator and forward cloud generator, two-dimensional cloud droplet groups of different flavor information were established by using liquor taste data collected by electronic tongue. Second, the frequency and order of the evaluation words for different flavor of liquor were obtained by counting and analyzing the data appeared in the artificial sensory evaluation experiment. According to the frequency and order of words, the cloud droplet range corresponding to each word was calculated in the cloud drop group. Finally, the fuzzy evaluations that originated from the eight groups of liquor data with different flavor were compared with the artificial sense, and the results indicated that the model developed in this work is capable of outputting fuzzy evaluation that is consistent with human perception rather than digital output. To sum up, this method enabled the electronic tongue system to generate an output, which conforms to human's descriptive language, making food detection technology a step closer to human perception.