The Future Application of Organ-on-a-Chip Technologies as Proving Grounds for MicroBioRobots.

An evolving understanding of disease pathogenesis has compelled the development of new drug delivery approaches. Recently, bioinspired microrobots have gained traction as drug delivery systems. By leveraging the microscale phenomena found in physiological systems, these microrobots can be designed with greater maneuverability, which enables more precise, controlled drug release. Their function could be further improved by testing their efficacy in physiologically relevant model systems as part of their development. In parallel with the emergence of microscale robots, organ-on-a-chip technologies have become important in drug discovery and physiological modeling. These systems reproduce organ-level functions in microfluidic devices, and can also incorporate specific biological, chemical, and physical aspects of a disease. This review highlights recent developments in both microrobotics and organ-on-a-chip technologies and envisions their combined use for developing future drug delivery systems.

Engineering control circuits for molecular robots using synthetic biology.

The integration of molecular robots and synthetic biology allows for the creation of sophisticated behaviors at the molecular level. Similar to the synergy between bioelectronics and soft robotics, synthetic biology provides control circuitry for molecular robots. By encoding perception-action modules within synthetic circuits, molecular machines can advance beyond repeating tasks to the incorporation of complex behaviors. In particular, cell-free synthetic biology provides biomolecular circuitry independent of living cells. This research update reviews the current progress in using synthetic biology as perception-action control modules in robots from molecular robots to macroscale robots. Additionally, it highlights recent developments in molecular robotics and cell-free synthetic biology and suggests their combined use as a necessity for future molecular robot development.

Point-of-care testing in the early diagnosis of acute pesticide intoxication: The example of paraquat.

Acute pesticide intoxication is a common method of suicide globally. This article reviews current diagnostic methods and makes suggestions for future development. In the case of paraquat intoxication, it is characterized by multi-organ failure, causing substantial mortality and morbidity. Early diagnosis may save the life of a paraquat intoxication patient. Conventional paraquat intoxication diagnostic methods, such as symptom review and urine sodium dithionite assay, are time-consuming and impractical in resource-scarce areas where most intoxication cases occur. Several experimental and clinical studies have shown the potential of portable Surface Enhanced Raman Scattering (SERS), paper-based devices, and machine learning for paraquat intoxication diagnosis. Portable SERS and new SERS substrates maintain the sensitivity of SERS while being less costly and more convenient than conventional SERS. Paper-based devices provide the advantages of price and portability. Machine learning algorithms can be implemented as a mobile phone application and facilitate diagnosis in resource-limited areas. Although these methods have not yet met all features of an ideal diagnostic method, the combination and development of these methods offer much promise.

miRTarBase update 2018: a resource for experimentally validated microRNA-target interactions.

MicroRNAs (miRNAs) are small non-coding RNAs of ∼ 22 nucleotides that are involved in negative regulation of mRNA at the post-transcriptional level. Previously, we developed miRTarBase which provides information about experimentally validated miRNA-target interactions (MTIs). Here, we describe an updated database containing 422 517 curated MTIs from 4076 miRNAs and 23 054 target genes collected from over 8500 articles. The number of MTIs curated by strong evidence has increased ∼1.4-fold since the last update in 2016. In this updated version, target sites validated by reporter assay that are available in the literature can be downloaded. The target site sequence can extract new features for analysis via a machine learning approach which can help to evaluate the performance of miRNA-target prediction tools. Furthermore, different ways of browsing enhance user browsing specific MTIs. With these improvements, miRTarBase serves as more comprehensively annotated, experimentally validated miRNA-target interactions databases in the field of miRNA related research. miRTarBase is available at http://miRTarBase.mbc.nctu.edu.tw/.

Point-of-Care Devices Using Disease Biomarkers To Diagnose Neurodegenerative Disorders.

Neurodegenerative disorders such as Alzheimer's, Parkinson's, and Huntington's diseases are highly prevalent and immensely destructive to the health and well-being of individuals and their families across the globe. Neurodegenerative diseases are characterized by the gradual loss of neural tissue in the central nervous system. Clearly, early diagnosis of the onset of neurodegeneration is vital and beneficial. Current diagnostic methods rely heavily on symptoms or autopsy results, thus overlooking early diagnosis, the only opportunity for amelioration. However, appropriately selected and used biomarker diagnostics provide a solution. This article reviews the development and application of biomarker-related diagnostics for neurodegenerative disease with specific recommendations for point-of-care (POC) methodology. These advantageous approaches may offer a solution to existing obstacles and limitations to neurodegenerative disease treatment.

Detection of ovulation, a review of currently available methods.

The ability to identify the precise time of ovulation is important for women who want to plan conception or practice contraception. Here, we review the current literature on various methods for detecting ovulation including a review of point-of-care device technology. We incorporate an examination of methods to detect ovulation that have been developed and practiced for decades and analyze the indications and limitations of each-transvaginal ultrasonography, urinary luteinizing hormone detection, serum progesterone and urinary pregnanediol 3-glucuronide detection, urinary follicular stimulating hormone detection, basal body temperature monitoring, and cervical mucus and salivary ferning analysis. Some point-of-care ovulation detection devices have been developed and commercialized based on these methods, however previous research was limited by small sample size and an inconsistent standard reference to true ovulation.

Synthetic Biology-Based Point-of-Care Diagnostics for Infectious Disease.

Infectious diseases outpace all other causes of death in low-income countries, posing global health risks, laying stress on healthcare systems and societies, and taking an avoidable human toll. One solution to this crisis is early diagnosis of infectious disease, which represents a powerful way to optimize treatment, increase patient survival rate, and decrease healthcare costs. However, conventional early diagnosis methods take a long time to generate results, lack accuracy, and are known to seriously underperform with regard to fungal and viral infections. Synthetic biology offers a fast and highly accurate alternative to conventional infectious disease diagnosis. In this review, we outline obstacles to infectious disease diagnostics and discuss two emerging alternatives: synthetic viral diagnostic systems and biosensors. We argue that these synthetic biology-based approaches may overcome diagnostic obstacles in infectious disease and improve health outcomes.

miRTarBase 2016: updates to the experimentally validated miRNA-target interactions database.

MicroRNAs (miRNAs) are small non-coding RNAs of approximately 22 nucleotides, which negatively regulate the gene expression at the post-transcriptional level. This study describes an update of the miRTarBase (http://miRTarBase.mbc.nctu.edu.tw/) that provides information about experimentally validated miRNA-target interactions (MTIs). The latest update of the miRTarBase expanded it to identify systematically Argonaute-miRNA-RNA interactions from 138 crosslinking and immunoprecipitation sequencing (CLIP-seq) data sets that were generated by 21 independent studies. The database contains 4966 articles, 7439 strongly validated MTIs (using reporter assays or western blots) and 348 007 MTIs from CLIP-seq. The number of MTIs in the miRTarBase has increased around 7-fold since the 2014 miRTarBase update. The miRNA and gene expression profiles from The Cancer Genome Atlas (TCGA) are integrated to provide an effective overview of this exponential growth in the miRNA experimental data. These improvements make the miRTarBase one of the more comprehensively annotated, experimentally validated miRNA-target interactions databases and motivate additional miRNA research efforts.