22q11.2 deletion syndrome (22q11.2 DS) is the most common microdeletion syndrome and is underdiagnosed in diverse populations. This syndrome has a variable phenotype and affects multiple systems, making early recognition imperative. In this study, individuals from diverse populations with 22q11.2 DS were evaluated clinically and by facial analysis technology. Clinical information from 106 individuals and images from 101 were collected from individuals with 22q11.2 DS from 11 countries; average age was 11.7 and 47% were male. Individuals were grouped into categories of African descent (African), Asian, and Latin American. We found that the phenotype of 22q11.2 DS varied across population groups. Only two findings, congenital heart disease and learning problems, were found in greater than 50% of participants. When comparing the clinical features of 22q11.2 DS in each population, the proportion of individuals within each clinical category was statistically different except for learning problems and ear anomalies (P<0.05). However, when Africans were removed from analysis, six additional clinical features were found to be independent of ethnicity (P≥0.05). Using facial analysis technology, we compared 156 Caucasians, Africans, Asians, and Latin American individuals with 22q11.2 DS with 156 age and gender matched controls and found that sensitivity and specificity were greater than 96% for all populations. In summary, we present the varied findings from global populations with 22q11.2 DS and demonstrate how facial analysis technology can assist clinicians in making accurate 22q11.2 DS diagnoses. This work will assist in earlier detection and in increasing recognition of 22q11.2 DS throughout the world.

Noonan syndrome (NS) is a common genetic syndrome associated with gain of function variants in genes in the Ras/MAPK pathway. The phenotype of NS has been well characterized in populations of European descent with less attention given to other groups. In this study, individuals from diverse populations with Noonan syndrome were evaluated clinically and by facial analysis technology. Clinical data and images from 125 individuals with NS were obtained from 20 countries with an average age of 8 years and female composition of 46%. Individuals were grouped into categories of African descent (African), Asian, Latin American and additional/other. Across these different population groups, NS was phenotypically similar with only 2 of 21 clinical elements showing a statistically significant difference. The most common clinical characteristics found in all population groups included widely spaced eyes and low-set ears in 80% or greater of participants, short stature in more than 70%, and pulmonary stenosis in roughly half of study individuals. Using facial analysis technology, we compared 161 Caucasian, African, Asian, and Latin American individuals with NS with 161 gender and age matched controls and found that sensitivity was equal to or greater than 94% for all groups, and specificity was equal to or greater than 90%. In summary, we present consistent clinical findings from global populations with NS and additionally demonstrate how facial analysis technology can support clinicians in making accurate NS diagnoses. This work will assist in earlier detection and in increasing recognition of NS throughout the world.

Rapid and precise analytical tools are essential for monitoring food safety and screening of any undesirable contaminants, allergens, or pathogens, which may cause significant health risks upon consumption. Substantial developments in analytical techniques have empowered the analyses and quantitation of these contaminants. However, conventional techniques are limited by delayed analysis times, expensive and laborious sample preparation, and the necessity for highly-trained workers. Therefore, prompt advances in electrochemical biosensors have supported significant gains in quantitative detection and screening of food contaminants and showed incredible potential as a means of defying such limitations. Apart from indicating high specificity towards the target analytes, these biosensors have also addressed the challenge of food industry by providing high analytical accuracy within complex food matrices. Here, we discuss some of the recent advances in this area and analyze the role and contributions made by electrochemical biosensors in the food industry. This article also reviews the key challenges we believe biosensors need to overcome to become the industry standard.

Food and environmental monitoring is one of the most important aspects of dealing with recent threats to human well-being and ecosystems. In this framework, electrochemical aptamer-based sensors are resilient due to their ability to resolve food and environmental contamination. An aptamer-based sensor is a compact analytical device combining an aptamer as the bio-sensing element integrated on the transducer surface. Aptamers display many advantages as biorecognition elements in sensor development when compared to affinity-based (antibodies) sensors. Aptasensors are small, chemically unchanging, and inexpensive. Moreover, they offer extraordinary elasticity and expediency in the design of their assemblies, which has led to innovative sensors that show tremendous sensitivity and selectivity. This review will emphasize recent food and environmental safeguarding using aptasensors; there are good prospects for their performance as a supplement to classical techniques.

Williams-Beuren syndrome (WBS) is a common microdeletion syndrome characterized by a 1.5Mb deletion in 7q11.23. The phenotype of WBS has been well described in populations of European descent with not as much attention given to other ethnicities. In this study, individuals with WBS from diverse populations were assessed clinically and by facial analysis technology. Clinical data and images from 137 individuals with WBS were found in 19 countries with an average age of 11 years and female gender of 45%. The most common clinical phenotype elements were periorbital fullness and intellectual disability which were present in greater than 90% of our cohort. Additionally, 75% or greater of all individuals with WBS had malar flattening, long philtrum, wide mouth, and small jaw. Using facial analysis technology, we compared 286 Asian, African, Caucasian, and Latin American individuals with WBS with 286 gender and age matched controls and found that the accuracy to discriminate between WBS and controls was 0.90 when the entire cohort was evaluated concurrently. The test accuracy of the facial recognition technology increased significantly when the cohort was analyzed by specific ethnic population (P-value < 0.001 for all comparisons), with accuracies for Caucasian, African, Asian, and Latin American groups of 0.92, 0.96, 0.92, and 0.93, respectively. In summary, we present consistent clinical findings from global populations with WBS and demonstrate how facial analysis technology can support clinicians in making accurate WBS diagnoses.

Infectious diseases caused by viruses can elevate up to undesired pandemic conditions affecting the global population and normal life function. These in turn impact the established world economy, create jobless situations, physical, mental, emotional stress, and challenge the human survival. Therefore, timely detection, treatment, isolation and prevention of spreading the pandemic infectious diseases not beyond the originated town is critical to avoid global impairment of life (e.g., Corona virus disease - 2019, COVID-19). The objective of this review article is to emphasize the recent advancements in the electrochemical diagnostics of twelve life-threatening viruses namely - COVID-19, Middle east respiratory syndrome (MERS), Severe acute respiratory syndrome (SARS), Influenza, Hepatitis, Human immunodeficiency virus (HIV), Human papilloma virus (HPV), Zika virus, Herpes simplex virus, Chikungunya, Dengue, and Rotavirus. This review describes the design, principle, underlying rationale, receptor, and mechanistic aspects of sensor systems reported for such viruses. Electrochemical sensor systems which comprised either antibody or aptamers or direct/mediated electron transfer in the recognition matrix were explicitly segregated into separate sub-sections for critical comparison. This review emphasizes the current challenges involved in translating laboratory research to real-world device applications, future prospects and commercialization aspects of electrochemical diagnostic devices for virus detection. The background and overall progress provided in this review are expected to be insightful to the researchers in sensor field and facilitate the design and fabrication of electrochemical sensors for life-threatening viruses with broader applicability to any desired pathogens.

Aptamers are synthetic bio-receptors of deoxyribonucleic acid (DNA) or ribonucleic acid (RNA) origin selected by the systematic evolution of ligands (SELEX) process that bind a broad range of target analytes with high affinity and specificity. So far, electrochemical biosensors have come up as a simple and sensitive method to utilize aptamers as a bio-recognition element. Numerous aptamer based sensors have been developed for clinical diagnostics, food, and environmental monitoring and several other applications are under development. Aptasensors are capable of extending the limits of current analytical techniques in clinical diagnostics, food, and environmental sample analysis. However, the potential applications of aptamer based electrochemical biosensors are unlimited; current applications are observed in the areas of food toxins, clinical biomarkers, and pesticide detection. This review attempts to enumerate the most representative examples of research progress in aptamer based electrochemical biosensing principles that have been developed in recent years. Additionally, this account will discuss various current developments on aptamer-based sensors toward heavy metal detection, for various cardiac biomarkers, antibiotics detection, and also on how the aptamers can be deployed to couple with antibody-based assays as a hybrid sensing platform. Aptamers can be used in various applications, however, this account will focus on the recent advancements made toward food, environmental, and clinical diagnostic application. This review paper compares various electrochemical aptamer based sensor detection strategies that have been applied so far and used as a state of the art. As illustrated in the literature, aptamers have been utilized extensively for environmental, cancer biomarker, biomedical application, and antibiotic detection and thus have been extensively discussed in this article.

Mango (Mangifera indica L.) is known as the 'king of fruits' for its rich taste, flavor, color, production volume and diverse end usage. It belongs to plant family Anacardiaceae and has a small genome size of 439 Mb (2n = 40). Ancient literature indicates origin of cultivated mango in India. Although wild species of genus Mangifera are distributed throughout South and South-East Asia, recovery of Paleocene mango leaf fossils near Damalgiri, West Garo Hills, Meghalaya point to the origin of genus in peninsular India before joining of the Indian and Asian continental plates. India produces more than fifty percent of the world's mango and grows more than thousand varieties. Despite its huge economic significance genomic resources for mango are limited and genetics of useful horticultural traits are poorly understood. Here we present a brief account of our recent efforts to generate genomic resources for mango and its use in the analysis of genetic diversity and population structure of mango cultivars. Sequencing of leaf RNA from mango cultivars 'Neelam', 'Dashehari' and their hybrid 'Amrapali' revealed substantially higher level of heterozygosity in 'Amrapali' over its parents and helped develop genic simple sequence repeat (SSR) and single nucleotide polymorphism (SNP) markers. Sequencing of double digested restriction-site-associated genomic DNA (ddRAD) of 84 diverse mango cultivars identified 1.67 million high quality SNPs and two major sub-populations. We have assembled 323 Mb of the highly heterozygous 'Amrapali' genome using long sequence reads of PacBio single molecule real time (SMRT) sequencing chemistry and predicted 43,247 protein coding genes. We identified in the mango genome 122,332 SSR loci and developed 8,451 Type1 SSR and 835 HSSR markers for high level of polymorphism. Among the published genomes, mango showed highest similarity with sweet orange (Citrus sinensis). These genomic resources will fast track the mango varietal improvement for high productivity, disease resistance and superior end use quality.