Frontiers in analytical science最新文献

{"title":"Novel Clinimetric Toolset to Quantify the Stability of Blood Pressure and Its Application to Evaluate Cardiovascular Function After Spinal Cord Injury","authors":"Samineh Mesbah, Bonnie E. Legg Ditterline, Siqi Wang, Samuel Wu, J. Weir, J. Wecht, G. Forrest, S. Harkema, B. Ugiliweneza","doi":"10.3389/frans.2021.701891","DOIUrl":"https://doi.org/10.3389/frans.2021.701891","url":null,"abstract":"Profound dysfunction of the cardiovascular system occurs after spinal cord injury (SCI), which is a leading cause of mortality in this population. Most individuals with chronic SCI experience transient episodes of hypotensive and hypertensive blood pressure in response to daily life activities. There are currently limited tools available to evaluate the stability of blood pressure with respect to a reference range. The aim of this study was to develop a clinimetric toolset for accurately quantifying stability of the blood pressure measurements and taking into consideration the complex dynamics of blood pressure variability among individuals with SCI. The proposed toolset is based on distribution of the blood pressure data points within and outside of the clinically recommended range. This toolset consists of six outcome measures including 1) total deviation of the 90% of the blood pressure data points from the center of the target range (115 mmHg); 2) The area under the cumulative distribution curve starting from the percentage of blood pressure measurements within the range, and the percentage of values within symmetrically expanded boundary ranges, above and below the target range; 3) the slope of the cumulative distribution curve that is calculated by fitting an exponential cumulative distribution function and the natural logarithm of its rate parameter; 4) its x- and 5) y-axis intercepts; and 6) the fitting error. These outcome measures were validated using blood pressure measurements recorded during cardiovascular perturbation tests and prolonged monitoring period from individuals with chronic SCI and non-injured controls. The statistical analysis based on the effect size and intra-class correlation coefficient, demonstrated that the proposed outcome measures fulfill reliability, responsiveness and discrimination criteria. The novel methodology proposed in this study is reliable and effective for evaluating the stability of continuous blood pressure in individuals with chronic spinal cord injury.","PeriodicalId":73063,"journal":{"name":"Frontiers in analytical science","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-08-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48151402","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Grand Challenges in Analytical Science","authors":"Huan‐Tsung Chang","doi":"10.3389/frans.2021.725070","DOIUrl":"https://doi.org/10.3389/frans.2021.725070","url":null,"abstract":"Analytical science is related to the development and application of techniques for detection of analytes, characterization of composites, analysis of samples, and monitoring of chemical and biochemical systems. It has played significant roles in the studies of physical, life, material, environmental, food, medical, and sustainability sciences. In the recent years, we have witnessed various techniques for single-cell analysis, screening of circulating tumor cells, viral diagnostics, detection of radioactive substances and explosive compounds, screening and identification of abused drugs, tracking contaminants and chemicals to ensure water quality and food safety, the study of omics, and characterization of synthetic polymers and nanomaterials. For example, various analytical technique, such as reverse transcription polymerase chain reaction (RT-qPCR), loopmediated amplification (LAMP), and clustered regularly interspaced short palindromic repeats (CRISPR) assays have been applied for sensitive and specific detection of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) that causes COVID-19 disease (Huang et al., 2020; Wang et al., 2021). LAMP is attractive because there is no need for temperature cycling and it provides extremely high sensitivity (down to fM) with fluorescent, electrochemical or electroluminescent signal transduction. To minimize the threat of pandemics, vaccines against pathogens such as Zika virus and SARS-CoV-2 have been developed. For quality control and safety of vaccines, many analytical techniques such as sampling, purification, high performance liquid chromatography (HPLC), and gene expression profiling are needed. To meet the requirement of various studies and needs of society, analytical techniques must be in general sensitive, selective, fast, accurate, and simple. The instruments must be cost effective, easy in operation and maintenance, compact (portable ideally), suitable for the analysis of various samples, and available to provide wide dynamic ranges for quantitation of analytes. Analytical techniques are chosen mainly based on the purpose of the study, equipment available, properties of the analyte, and nature of the sample. For example, optical techniques provide high temporal and spatial resolution are commonly applied for cell tracking. To improve reproducibility, efficiency, and accuracy of the cell studies, the sequential cell images are then subjected to computational object tracking to track cells events over time and to obtain signals from each object. When in-vivo monitoring of drug function is the aim, nonconstructive optical techniques allowing deep penetration from the surface is usually carried out. In this case, materials can absorb light and generate optical signals like fluorescence in the infrared (IR) or near IR (NIR) region are suitable. For environmental analysis and forensics, portable and low-cost on-field analytical instruments are ideal. To provide high specificity and sensitivity","PeriodicalId":73063,"journal":{"name":"Frontiers in analytical science","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-07-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41681798","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Grand Challenges and Perspectives in Biomedical Analysis and Diagnostics","authors":"Q. Cheng","doi":"10.3389/frans.2021.700386","DOIUrl":"https://doi.org/10.3389/frans.2021.700386","url":null,"abstract":"The importance of analytical sciences and biosensing to medical diagnosis has been well recognized by those involved in the field; the recent global pandemic due to severe acute respiratory syndrome-associated coronavirus 2 (SARS-CoV-2) has further elevated the topic to paramount worldwide prominence and urgency (Lippi et al., 2020). While the pandemic may be contained in the near future due to the heroic efforts of medical staff and biotechnologists around the world, the research interest in analytical sciences toward more efficient medical diagnosis will undoubtedly remain for the foreseeable future. Aside from innovative schemes that offer new angles for detection and quantification, evaluations and reevaluations of the state and efficacy of analytical sensing are also required when applied to medical samples. For a broader conversation of the directions of research, it is important to assess the state-of-the-art and significant trends across the field. There have been exciting technical developments in recent years that push forward the accuracy and sensitivity of techniques, expand the scope of analyses beyond simple biomarkers, and improve the accessibility and applicability of analytical methods. In addition, clinical data of increasing depth and complexity are gathered at an extraordinary pace in recent years due to “Big Data” movement in healthcare. Therefore, one of the most prominent trends in analytical science appears to be the application of artificial intelligence and machine learning models to correlate sensed or imaged markers from patients to diagnosis (Rajkomar et al., 2019). Recent examples include an artificial intelligence system that outperformed doctors by 11% in diagnosing breast cancers (McKinney et al., 2020), and a study of machine learning models that used imaging biomarkers and predictive models for rapid diagnosis of COVID-19 (Wynants et al., 2020). This dense, complex approach toward information accumulation also requires a scale-up in the sophistication of models by which the information is treated so that relevant outcomes and knowledge can be obtained. Clearly, the need for technical advances in medical diagnosis is ever-present, and this is manifested in the current pandemic. Mature technologies such as PCR and immunoassays continue to provide reliable tests for the rapidly spreading disease, while in the meantime we have seen a wave of new approaches rolling out of unconventional sectors that are shaping the course of diagnostic development (mass spectrometry, 3D printing, and CRISPR-Cas12, to name a few). The challenges in this field also suggest a range of opportunities, which we aim to describe in this Article. In the interest of brevity, we will organize the discussion into analysis targets, technological developments, and data processing.","PeriodicalId":73063,"journal":{"name":"Frontiers in analytical science","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-06-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45781789","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}