Skin‐like devices for advanced healthcare

[...]their cumbersome equipment, ergonomic discomfort, and episodic treatment hinder mobile, comfortable, real-time, and long-term monitoring. [...]the insufficient, inconvenient, and inaccurate medical services of the conventional healthcare system inevitably cause overloaded patient populations, skyrocketing expenditures, and medical burdens, especially for the still-ongoing COVID-19. Compared to routine healthcare models, skin-like devices cannot only reduce the cost of clinical interventions but also monitor a variety of physiological conditions in a real-time, comfortable, and long-term transformative manner. [...]skin-like devices for health management have more advantages than traditional healthcare and are considered essential for efficient health maintenance and disease treatment. In addition to phototherapy, electrotherapy, thermotherapy and drug delivery approaches, E et al. introduced three new electromagnetic therapeutics to treat cancer cells that are quite different from normal cells in volume, water content, and differentiation.

Peptidomic analysis of mycobacterial secreted proteins enables species identification

Pulmonary disease arising from slow‐growing mycobacterial infections has emerged as an increasingly prevalent clinical concern over the past two to three decades. Proteins belonging to the family of ESAT‐6 secretion (Esx) systems play critical roles in the virulence of most pathogenic mycobacterial species and are associated with drug resistance. However, no clinical applications can detect and discriminate the expression of species‐specific variants of these proteins in clinical samples, such as early growth cultures, for rapid diagnosis of specific mycobacterial infections, which may require distinct interventions. Conventional immunoassay approaches are not suitable for this purpose due to the significant degree of conservation of Esx proteins among species. Herein we describe the development of a novel immunoprecipitation‐coupled mass spectrometry assay that can distinguish Esx proteins that are expressed by slow‐growing mycobacterial species commonly detected in clinical isolates. This approach uses custom antibodies raised against single semi‐conserved peptide regions in M. tuberculosis (Mtb) EsxB and EsxN to capture corresponding peptides from protein orthologs of mycobacteria associated with human respiratory infections, including Mtb, M. avium, M. intracellulare, M. kansasii, M. gordonae, and M. marinum, to detect these species in standard clinical cultures at the first sign mycobacterial growth to allow rapid disease diagnosis.

A review of pooled‐sample strategy: Does complexity lead to better performance?

The outbreak of coronavirus disease 2019 (COVID‐19, caused by SARS‐Cov‐2) is a big challenge for global health systems and the economy. Rapid and accurate tests are crucial at early stages of this pandemic. Reverse transcription‐quantitative real‐time polymerase chain reaction is the current gold standard method for detection of SARS‐Cov‐2. It is impractical and costly to test individuals in large‐scale population screens, especially in low‐ and middle‐income countries due to their shortage of nucleic acid testing reagents and skilled staff. Accordingly, sample pooling, such as for blood screening for syphilis, is now widely applied to COVID‐19. In this paper, we survey and review several different pooled‐sample testing strategies, based on their group size, prevalence, testing number, and sensitivity, and we discuss their efficiency in terms of reducing cost and saving time while ensuring sensitivity.

Microclimate control to increase productivity and nutritional quality of leafy vegetables in a cost-effective manner

Food security is one of the key global challenges in this century. In Singapore, our research team has been using novel aeroponic technology to produce fresh vegetables since 1997. Aeroponic systems allow for year-round production of not only tropical, but also sub-tropical and temperate fresh vegetables, by simply cooling the roots suspended in aeroponic systems while the aerial parts grow under tropical ambient environments. It has also been used to investigate the impacts of root-zone CO2 on vegetables by enriching root-zone CO2 while their aerial portions were subjected to constant atmospheric CO2. To compensate for the lack of available land, Singapore also needs to develop a farming system that can increase productivity per unit land area by many-fold. Over the past 10 years, my research team has established a commercially viable LED integrated vertical aeroponic farming system to grow different leafy vegetables under different LED spectra, intensities, and durations in the tropical greenhouse. The results demonstrate that it is possible to increase shoot production and rate of shoot production of leafy vegetables by increasing light intensity and extending the photoperiod under effective LED lighting. Furthermore, temperate vegetable crops such as lettuce were able to acclimate to high light intensity under supplementary LED lights to natural sunlight in the greenhouse. Supplementary LED lightings promote both leaf initiation and expansion with increased photo synthetic pigments, higher Cyt b6f and Rubisco protein contents on a per area basis and thus improve photosynthetic capacity and enhance productivity. Plants sense and respond to changes in their immediate environments (microclimate), manipulating the root zone temperature (RZT) and water supply will impact not only their growth and development but also their nutritional quality. Our on-going research aims to investigate if the nutritional quality of leafy vegetables could be improved under suboptimal RZT and mild water deficit through deficit irrigation. If substantial energy and water savings in urban farming can be achieved without substantial yield penalty but with higher nutritional quality, the amount of water and energy saved can bring substantial benefits to society.

DIAGNOSIS OF COVID-19 BASED ON ARTIFICIAL INTELLIGENCE MODELS AND PHYSIOLOGICAL SENSORS: REVIEW: APPLICATIONS, BASIS, AND COMMUNICATIONS

Covid-19 invaded the world very quickly and caused the loss of many lives;maximum emergency was activated all over the world due to its rapid spread. Consequently, it became a huge burden on emergency and intensive care units due to the large number of infected individuals and the inability of the medical staff to deal with patients according to the degree of severity. Covid-19 can be diagnosed based on the artificial intelligence (AI) model. Based on AI, the CT images of the patient’s chest can be analyzed to identify the patient case whether it is normal or he/she has Covid-19. The possibility of employing physiological sensors such as heart rate, temperature, respiratory rate, and SpO2 sensors in diagnosing Covid-19 was investigated. In this paper, several articles which used intelligent techniques and vital signs for diagnosing Covid-19 have been reviewed, classified, and compared. The combination of AI and physiological sensors reading, called AI-PSR, can help the clinician in making the decisions and predicting the occurrence of respiratory failure in Covid-19 patients. The physiological parameters of the Covid-19 patients can be transmitted wirelessly based on a specific wireless technology such as Wi-Fi and Bluetooth to the clinician to avoid direct contact between the patient and the clinician or nursing staff. The outcome of the AI-PSR model leads to the probability of recording and linking data with what will happen later, to avoid respiratory failure, and to help the patient with one of the mechanical ventilation devices.

CONFIDENCE LEVEL OF A MOTION FEEDBACK SYSTEM FOR ANALYZING EXERCISE TRAINING EFFICACY: APPLICATIONS, BASIS, AND COMMUNICATIONS

The increase in aged population is a global trend. Inculcating healthy behaviors such as regular exercises in the elderly has a significant impact on the financial and medical burden globally. Moreover, air pollution and the outbreak of the coronavirus disease 19 (COVID-19) pose a serious threat to public health. In order to improve the health conditions of the population, this study developed a motion feedback system named MoveV that can be used for several indoor training exercises. This system provides instant motion feedback by synchronizing exercise training videos on the website using a motion analysis algorithm that is applicable on smartphones, and a cloud database platform is used to record health behaviors. Feature extraction is performed based on force intensity, motion velocity, and exercise direction. The resultant accuracy of the motion feedback system was tested by a motion science expert and presented as the confidence level. For perfect movement, a confidence level of up to 90.5% was achieved, indicating that the MoveV system was able to record users’ exercise frequency and distinguish whether the user was performing well in the exercise movements. The proposed system is convenient and does not incur additional expenditure by purchasing any new device. Furthermore, it provides visual and voice feedback, companionship, and exercise motivation to the users, all of which are important factors when using online exercise platforms.

Lipid coating technology: A potential solution to address the problem of sticky containers and vanishing drugs

Pharmaceutical drugs and vaccines require the use of material containers for protection, storage, and transportation. Glass and plastic materials are widely used for packaging, and a longstanding challenge in the field is the nonspecific adsorption of pharmaceutical drugs to container walls – the so‐called “sticky containers, vanishing drugs” problem – that effectively reduces the active drug concentration and can cause drug denaturation. This challenge has been frequently discussed in the case of the anticancer drug, paclitaxel, and the ongoing coronavirus disease 2019 (COVID‐19) pandemic has brought renewed attention to this material science challenge in light of the need to scale up COVID‐19 vaccine production and to secure sufficient quantities of packaging containers. To reduce nonspecific adsorption on inner container walls, various strategies based on siliconization and thin polymer films have been explored, while it would be advantageous to develop mass‐manufacturable, natural material solutions, especially ones involving pharmaceutical grade excipients. Inspired by how lipid nanoparticles have revolutionized the vaccine field, in this perspective, we discuss the prospects for developing lipid bilayer coatings to prevent nonspecific adsorption of pharmaceutical drugs and vaccines and how recent advances in lipid bilayer coating fabrication technologies are poised to accelerate progress in the field. We critically discuss recent examples of how lipid bilayer coatings can prevent nonspecific sticking of proteins and vaccines to relevant material surfaces and examine future translational prospects.

Numerical Analysis of Blood Flow through COVID-19 Infected Arteries

Computational Fluid Dynamics has become relevant in the study of hemodynamics, where clinical results are challenging to obtain. This paper discusses a 2-Dimensional transient blood flow analysis through an arterial bifurcation for patients infected with the Coronavirus. The geometry considered is an arterial bifurcation with main stem diameter 3 mm and two outlets. The left outlet (smaller) has a diameter of 1.5 mm and the right outlet (larger), 2 mm. The length of the main stem, left branch and right branch are fixed at 35 mm, 20 mm and 25 mm respectively. Viscosity change that occurs in the blood leads to different parametrical changes in blood flow. The blood flow towards the smaller branch is significantly affected by the changed blood viscosity. Extended regions of high pressure and increased velocity towards the larger outlet are obtained. The Time Averaged Wall Shear Stress (TAWSS) for the corona affected artery is found to be 10.4114 Pa at a 90° angle of bifurcation as compared to 2.45002 Pa of the normal artery. For varying angles of bifurcation, an angle of 75° was found to have a maximum Time Averaged Wall Shear Stress of 2.46076 Pa and 10.42542 Pa for normal and corona affected artery, respectively.

Evaluation of in vitro human skin models for studying effects of external stressors and stimuli and developing treatment modalities

Skin is exposed to a variety of potential stressors and stimulators that may impact homeostasis, healing, tumor development, inflammation, and irritation. As such it is important to understand the impact that these stimuli have on skin health and function, and to develop therapeutic interventions. Animal experiments have been the gold standard for testing the safety and efficacy of therapeutics and observing disease pathology for centuries. However, complex ethics, costs, time consumption, and interspecies variation limit the transferability of results to humans and reduce their repeatability and reliability. Furthermore, traditional 2D cell studies are not representative of human tissue. Skin tissue is a dynamic environment, and when cells are isolated in unphysiologically stiff, static petri dishes their behavior, and phenotypic expression is altered. Increasingly complex in vitro models of human skin, including organoids, 3D bioprinting, and skin‐on‐a‐chip platforms, present the opportunity to gain insight into how stressors affect tissue at a cellular level in a controlled and repeatable environment. This insight can be leveraged to further understand pathological skin conditions and better formulate and validate drugs and therapeutics. Here, we will discuss the application of in vitro skin modeling to investigating the effects of mechanical, electromagnetic, and chemical stressors on skin.

AUTOMATED SEGMENTATION OF COVID-19 REGIONS FROM LUNG CT IMAGES USING WATERSHED ALGORITHM AND CLASSIFICATION USING MACHINE LEARNING CLASSIFIERS: APPLICATIONS, BASIS, AND COMMUNICATIONS

The COVID-19 pandemic originated in Wuhan, China in December 2019 and has since affected over 200 countries worldwide. The highly contagious Coronavirus primarily affects the respiratory system, causing pulmonary inflammation that can be visualized through medical imaging such as CT and X-rays. Conventional testing methods include PCR and antibody tests. Shortage of test kits in hospitals as well as time taken for results to be received can be compensated through medical imaging. Therefore, there is a need for an automated system, which is accurate and robust in detection of Covid-19 from medical radiographs for clinical practice. The objectives of our study are as follows: (i) To segment the lung CT images using a hybrid watershed and fuzzy c-means algorithm. (2) To extract various textural features using the GLCM algorithm. (iii) To implement machine learning classifiers for classification of COVID and non-COVID image classes. Our dataset consisting of 60 chest CT images of COVID-19 and non-COVID-19 patients was pre-processed and segmented using a hybrid watershed and fuzzy c-means algorithm. Then, textural features were extracted from the segmented ROI using the GLCM algorithm. Finally, the images were classified into COVID and non-COVID classes using three machine learning classifiers namely Naïve Bayes, SVM and K-star. Naïve Bayes classifier achieved the highest accuracy of 95%, while SVM achieved 93% accuracy. The ROC curves were also obtained, with AUC of 0.98. Thus, our proposed system has shown promising results in the classification of lung CT images into the two classes namely COVID and non-COVID.

Advances in nanoparticle‐based lateral flow immunoassay for point‐of‐care testing

As a representative technology for point‐of‐care testing (POCT), lateral flow immunoassay (LFIA) has been broadly used to detect analytes in many fields. However, its clinical application is severely limited by the unsatisfactory sensitivity, which makes it difficult to obtain accurate results when detecting biomarkers of trace levels, especially in complex matrices. Nanoparticles have been introduced into LFIA for years and become an indispensable part, acting not only as carriers that load and enrich biomolecules, such as antibodies and dyes, but also a miniature platform applied for creative design and construction of nanoprobes. Due to the unique properties at the nanoscale, including the mimetic enzyme activity, the characteristic plasma resonance spectrum and so on, nanomaterials exhibit great potential in the development of novel LFIA and high‐sensitivity detection.

Longevity of vaccine protection: Immunological mechanism, assessment methods, and improving strategy

Vaccination represents one of the most important achievements in modern medicine. During the era of COVID‐19 pandemic, the successful vaccination for SARS‐COV‐2 is the major hope to bring the society back to normal. However, although vaccines, such as for smallpox and poliomyelitis, can trigger life‐long protection in individuals and help to generate the herd immunity resulting in the eradication of pathogens, other vaccines, with seasonal influenza vaccine as a case in point, are unable to induce sustained immunity so that repeated vaccination is required. As most vaccines were developed empirically, the immunological mechanism underlying the longevity of vaccine‐induced protection remains only partially understood. In this review, we first describe vaccine‐induced humoral immune response in which long‐lived plasma cells and memory B cells are produced. We then summarise methods using immunological correlates of protection to assess the longevity of vaccine efficacy and provide the evidence and knowledge for the duration of protection by current vaccines. Last, we discuss rationale and strategies to improve the duration of vaccine protection by targeting vaccine immunogenicity, antibody affinity, avidity and prime‐boost scheme.