Fabrication of Electrochemical-DNA Biosensors for the Reagentless Detection of Nucleic Acids, Proteins and Small Molecules

As medicine is currently practiced, doctors send specimens to a central laboratory for testing and thus must wait hours or days to receive the results. Many patients would be better served by rapid, bedside tests. To this end our laboratory and others have developed a versatile, reagentless biosensor platform that supports the quantitative, reagentless, electrochemical detection of nucleic acids (DNA, RNA), proteins (including antibodies) and small molecules analytes directly in unprocessed clinical and environmental samples. In this video, we demonstrate the preparation and use of several biosensors in this "E-DNA" class. In particular, we fabricate and demonstrate sensors for the detection of a target DNA sequence in a polymerase chain reaction mixture, an HIV-specific antibody and the drug cocaine. The preparation procedure requires only three hours of hands-on effort followed by an overnight incubation, and their use requires only minutes

CheapStat: An Open-Source, “Do-It-Yourself” Potentiostat for Analytical and Educational Applications

Although potentiostats are the foundation of modern electrochemical research, they have seen relatively little application in resource poor settings, such as undergraduate laboratory courses and the developing world. One reason for the low penetration of potentiostats is their cost, as even the least expensive commercially available laboratory potentiostats sell for more than one thousand dollars. An inexpensive electrochemical workstation could thus prove useful in educational labs, and increase access to electrochemistry-based analytical techniques for food, drug and environmental monitoring. With these motivations in mind, we describe here the CheapStat, an inexpensive (<$80), open-source (software and hardware), hand-held potentiostat that can be constructed by anyone who is proficient at assembling circuits. This device supports a number of potential waveforms necessary to perform cyclic, square wave, linear sweep and anodic stripping voltammetry. As we demonstrate, it is suitable for a wide range of applications ranging from food- and drug-quality testing to environmental monitoring, rapid DNA detection, and educational exercises. The device's schematics, parts lists, circuit board layout files, sample experiments, and detailed assembly instructions are available in the supporting information and are released under an open hardware license

Racial variation in baseline characteristics and wait times among patients undergoing bariatric surgery

BACKGROUND: Although bariatric surgery is the most effective treatment for obesity and weight-related comorbid diseases, utilization rates are disproportionately low among non-white patients. We sought to understand if variation in baseline characteristics or access to care exists between white and non-white patients. METHODS: Using a statewide bariatric-specific data registry, we evaluated all patients who underwent bariatric surgery between 2006 and 2020 and completed a preoperative baseline questionnaire, which included a question about self-identification of race. Patient characteristics, co-morbidities, and time from initial preoperative clinic evaluation to date of surgery were compared among racial groups. RESULTS: A total of 73,141 patients met inclusion criteria with 18,741 (25.5%) self-identified as non-white. These included Black/African American (n = 11,904), Hispanic (n = 3448), Asian (n = 121), Native Hawaiian/Pacific Islander (n = 41), Middle Eastern (n = 164), Multiple (n = 2047) and other (n = 608). Non-white males were the least represented group, accounting for only 4% of all bariatric cases performed. Non-white patients were more likely to be younger (43.0 years vs. 46.6 years, p \u3c 0.0001), disabled (16% vs. 11.4%, p \u3c 0.0001) and have Medicaid (8.4% vs. 3.8%, p \u3c 0.0001) when compared to white patients, despite having higher rates of college education (78.0% vs. 76.6, p \u3c 0.0001). In addition, median time from initial evaluation to surgery was also longer among non-white patients (157 days vs. 127 days, p \u3c 0.0001), despite having higher rates of patients with a body mass index above 50 kg/m(2) (39.0% vs. 33.2%, p \u3c 0.0001). CONCLUSIONS: Non-white patients undergoing bariatric surgery represent an extremely diverse group of patients with more socioeconomic disadvantages and longer wait times when compared to white patients despite presenting with higher rates of severe obesity. Current guidelines and referral patterns for bariatric surgery may not be equitable and need further examination when considering the management of obesity within diverse populations to reduce disparities in care-of which non-white males are particularly at risk

A Bayesian approach for structure learning in oscillating regulatory networks

Oscillations lie at the core of many biological processes, from the cell cycle, to circadian oscillations and developmental processes. Time-keeping mechanisms are essential to enable organisms to adapt to varying conditions in environmental cycles, from day/night to seasonal. Transcriptional regulatory networks are one of the mechanisms behind these biological oscillations. However, while identifying cyclically expressed genes from time series measurements is relatively easy, determining the structure of the interaction network underpinning the oscillation is a far more challenging problem. Here, we explicitly leverage the oscillatory nature of the transcriptional signals and present a method for reconstructing network interactions tailored to this special but important class of genetic circuits. Our method is based on projecting the signal onto a set of oscillatory basis functions using a Discrete Fourier Transform. We build a Bayesian Hierarchical model within a frequency domain linear model in order to enforce sparsity and incorporate prior knowledge about the network structure. Experiments on real and simulated data show that the method can lead to substantial improvements over competing approaches if the oscillatory assumption is met, and remains competitive also in cases it is not

The Epidemiology of Acute Organ System Dysfunction From Severe Sepsis Outside of the Intensive Care Unit

BACKGROUND: Severe sepsis is a common, costly, and complex problem, the epidemiology of which has only been well studied in the intensive care unit (ICU). However, nearly half of all patients with severe sepsis are cared for outside the ICU. OBJECTIVE: To determine rates of infection and organ sys- tem dysfunction in patients with severe sepsis admitted to non-ICU services. DESIGN: Retrospective cohort study. SETTING: A large, tertiary, academic medical center in the United States. PATIENTS: Adult patients initially admitted to non-ICU medical services from 2009 through 2010. MEASUREMENTS: All International Classification of Dis- eases, 9th Revision, Clinical Modification diagnosis codes were screened for severe sepsis. Three hospitalists reviewed a sample of medical records evaluating the char- acteristics of severe sepsis. The International Consensus Conference (ICC) for sepsis defines severe sepsis as an infection leading to acute organ dysfunction.1,2 Severe sepsis afflicts over 1 million patients each year in Medicare alone, and is substantially more common among older Americans than acute myocardial infarction.3–5 Recently, the Agency for Healthcare Research and Quality identified severe sepsis as the single most expensive cause of hospitalization in the United States.6 The incidence of severe sepsis continues to rise.4,5 Severe sepsis is often mischaracterized as a diagno- sis cared for primarily in the intensive care unit (ICU). Yet, studies indicate that only 32% to 50% of patients with severe sepsis require ICU care, leaving *Address for correspondence and reprint requests: Jeffrey M. Rohde, MD, Department of Internal Medicine, University of Michigan Medical School, 3119 Taubman Center, 1500 E. Medical Center Dr., Ann Arbor, MI 48109-5376; Telephone: 734-647-1599; Fax: 734-233-9343; E-mail: [email protected] Additional Supporting Information may be found in the online version of this article. Received: July 15, 2012; Revised: December 16, 2012; Accepted: December 26, 2012 2013SocietyofHospitalMedicine DOI10.1002/jhm.2012 Published online in Wiley Online Library (Wileyonlinelibrary.com). RESULTS: Of 23,288 hospitalizations, 14% screened posi- tive for severe sepsis. A sample of 111 cases was manually reviewed, identifying 64 cases of severe sepsis. The mean age of patients with severe sepsis was 63 years, and 39% were immunosuppressed prior to presentation. The most common site of infection was the urinary tract (41%). The most common organ system dysfunctions were cardiovas- cular (hypotension) and renal dysfunction occurring in 66% and 64% of patients, respectively. An increase in the num- ber of organ systems affected was associated with an increase in mortality and eventual ICU utilization. Severe sepsis was documented by the treating clinicians in 47% of cases. CONCLUSIONS: Severe sepsis was commonly found and poorly documented on the wards at our medical center. The epidemiology and organ dysfunctions among patients with severe sepsis appear to be different from previously described ICU severe sepsis populations.This work was supported in part by the US National Insti- tutes of Health–K08, HL091249 (TJI) and the University of Michigan Specialist–Hospitalist Allied Research Program (SHARP). This work was also supported in part by VA Ann Arbor Healthcare System, Geriatric Research Education and Clinical Center (GRECC).Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/102728/1/Rohde 13 JHM epi acute organ dysfxn sepsis outside ICU.pdf11

Tracking transcription factor complexes on DNA using total internal reflectance fluorescence protein binding microarrays

We have developed a high-throughput protein binding microarray (PBM) assay to systematically investigate transcription regulatory protein complexes binding to DNA with varied specificity and affinity. Our approach is based on the novel coupling of total internal reflectance fluorescence (TIRF) spectroscopy, swellable hydrogel double-stranded DNA microarrays and dye-labeled regulatory proteins, making it possible to determine both equilibrium binding specificities and kinetic rates for multiple protein:DNA interactions in a single experiment. DNA specificities and affinities for the general transcription factors TBP, TFIIA and IIB determined by TIRF–PBM are similar to those determined by traditional methods, while simultaneous measurement of the factors in binary and ternary protein complexes reveals preferred binding combinations. TIRF–PBM provides a novel and extendible platform for multi-protein transcription factor investigation

Genetic assessment of age-associated Alzheimer disease risk: Development and validation of a polygenic hazard score

Background Identifying individuals at risk for developing Alzheimer disease (AD) is of utmost importance. Although genetic studies have identified AD-associated SNPs in APOE and other genes, genetic information has not been integrated into an epidemiological framework for risk prediction. Methods and findings Using genotype data from 17,008 AD cases and 37,154 controls from the International Genomics of Alzheimer’s Project (IGAP Stage 1), we identified AD-associated SNPs (at p < 10−5 ). We then integrated these AD-associated SNPs into a Cox proportional hazard model using genotype data from a subset of 6,409 AD patients and 9,386 older controls from Phase 1 of the Alzheimer’s Disease Genetics Consortium (ADGC), providing a polygenic hazard score (PHS) for each participant. By combining population-based incidence rates and the genotype-derived PHS for each individual, we derived estimates of instantaneous risk for developing AD, based on genotype and age, and tested replication in multiple independent cohorts (ADGC Phase 2, National Institute on Aging Alzheimer’s Disease Center [NIA ADC], and Alzheimer’s Disease Neuroimaging Initiative [ADNI], total n = 20,680). Within the ADGC Phase 1 cohort, individuals in the highest PHS quartile developed AD at a considerably lower age and had the highest yearly AD incidence rate. Among APOE ε3/3 individuals, the PHS modified expected age of AD onset by more than 10 y between the lowest and highest deciles (hazard ratio 3.34, 95% CI 2.62–4.24, p = 1.0 × 10−22). In independent cohorts, the PHS strongly predicted empirical age of AD onset (ADGC Phase 2, r = 0.90, p = 1.1 × 10−26) and longitudinal progression from normal aging to AD (NIA ADC, Cochran–Armitage trend test, p = 1.5 × 10−10), and was associated with neuropathology (NIA ADC, Braak stage of neurofibrillary tangles, p = 3.9 × 10−6 , and Consortium to Establish a Registry for Alzheimer’s Disease score for neuritic plaques, p = 6.8 × 10−6 ) and in vivo markers of AD neurodegeneration (ADNI, volume loss within the entorhinal cortex, p = 6.3 × 10−6 , and hippocampus, p = 7.9 × 10−5 ). Additional prospective validation of these results in non-US, non-white, and prospective community-based cohorts is necessary before clinical use. Conclusions We have developed a PHS for quantifying individual differences in age-specific genetic risk for AD. Within the cohorts studied here, polygenic architecture plays an important role in modifying AD risk beyond APOE. With thorough validation, quantification of inherited genetic variation may prove useful for stratifying AD risk and as an enrichment strategy in therapeutic trials