Cumulative mutagenesis of the basic residues in the 201-218 region of insulin-like growth factor (IGF)-binding protein-5 results in progressive loss of both IGF-I binding and inhibition of IGF-I biological action

We have reported previously that mutation of two conserved nonbasic amino acids (G203 and Q209) within the highly basic 201–218 region in the C-terminal domain of IGF-binding protein-5 (IGFBP-5) decreases binding to IGFs. This study reveals that cumulative mutagenesis of the 10 basic residues in this region, to create the C-Term series of mutants, ultimately results in a 15-fold decrease in the affinity for IGF-I and a major loss in heparin binding. We examined the ability of mutants to inhibit IGF-mediated survival of MCF-7 cells and were able to demonstrate that this depended not only upon the affinity for IGF-I, but also the kinetics of this interaction, because IGFBP-5 mutants with similar affinity constants (KD) values, but with different association (Ka) and dissociation (Kd) rate values, had markedly different inhibitory properties. In contrast, the affinity for IGF-I provided no predictive value in terms of the ability of these mutants to enhance IGF action when bound to the substratum. Instead, these C-Term mutants appeared to enhance the actions of IGF-I by a combination of increased dissociation of IGF-IGFBP complexes from the substratum, together with dissociation of IGF-I from IGFBP-5 bound to the substratum. These effects of the IGFBPs were dependent upon binding to IGF-I, because a non-IGF binding mutant (N-Term) was unable to inhibit or enhance the actions of IGF-I. These results emphasize the importance of the kinetics of association/dissociation in determining the enhancing or inhibiting effects of IGFBP-5 and demonstrate the ability to generate an IGFBP-5 mutant with exclusively IGF-enhancing activity

Comammox Nitrospira Clade B is the most abundant complete ammonia oxidizer in a dairy pasture soil and inhibited by dicyandiamide and high ammonium concentrations

The recent discovery of comammox Nitrospira, a complete ammonia oxidizer, capable of completing the nitrification on their own has presented tremendous challenges to our understanding of the nitrification process. There are two divergent clades of comammox Nitrospira, Clade A and B. However, their population abundance, community structure and role in ammonia and nitrite oxidation are poorly understood. We conducted a 94-day microcosm study using a grazed dairy pasture soil amended with urea fertilizers, synthetic cow urine, and the nitrification inhibitor, dicyandiamide (DCD), to investigate the growth and community structure of comammox Nitrospira spp. We discovered that comammox Nitrospira Clade B was two orders of magnitude more abundant than Clade A in this fertile dairy pasture soil and the most abundant subcluster was a distinctive phylogenetic uncultured subcluster Clade B2. We found that comammox Nitrospira Clade B might not play a major role in nitrite oxidation compared to the role of canonical Nitrospira nitrite-oxidizers, however, comammox Nitrospira Clade B is active in nitrification and the growth of comammox Nitrospira Clade B was inhibited by a high ammonium concentration (700 kg synthetic urine-N ha¯¹) and the nitrification inhibitor DCD. We concluded that comammox Nitrospira Clade B: (1) was the most abundant comammox in the dairy pasture soil; (2) had a low tolerance to ammonium and can be inhibited by DCD; and (3) was not the dominant nitrite-oxidizer in the soil. This is the first study discovering a new subcluster of comammox Nitrospira Clade B2 from an agricultural soil

Electrocardiogram Monitoring Wearable Devices and Artificial-Intelligence-Enabled Diagnostic Capabilities: A Review

Worldwide, population aging and unhealthy lifestyles have increased the incidence of high-risk health conditions such as cardiovascular diseases, sleep apnea, and other conditions. Recently, to facilitate early identification and diagnosis, efforts have been made in the research and development of new wearable devices to make them smaller, more comfortable, more accurate, and increasingly compatible with artificial intelligence technologies. These efforts can pave the way to the longer and continuous health monitoring of different biosignals, including the real-time detection of diseases, thus providing more timely and accurate predictions of health events that can drastically improve the healthcare management of patients. Most recent reviews focus on a specific category of disease, the use of artificial intelligence in 12-lead electrocardiograms, or on wearable technology. However, we present recent advances in the use of electrocardiogram signals acquired with wearable devices or from publicly available databases and the analysis of such signals with artificial intelligence methods to detect and predict diseases. As expected, most of the available research focuses on heart diseases, sleep apnea, and other emerging areas, such as mental stress. From a methodological point of view, although traditional statistical methods and machine learning are still widely used, we observe an increasing use of more advanced deep learning methods, specifically architectures that can handle the complexity of biosignal data. These deep learning methods typically include convolutional and recurrent neural networks. Moreover, when proposing new artificial intelligence methods, we observe that the prevalent choice is to use publicly available databases rather than collecting new data

Physical-Biological Coupling in Southern Lake Michigan: Influence of Episodic Sediment Resuspension on Phytoplankton

The influence of episodic, sediment resuspension on phytoplankton abundance/volume and composition, the photosynthetic maximum rate (P B max ) and efficiency (α B ), and chlorophyll-specific growth (μ Chl ) was evaluated during the spring isothermal period in southern Lake Michigan (Laurentian Great Lakes, USA). Resuspension altered the nutrient and light climate of nearshore waters; light attenuation (K d ) and phosphorus concentrations corresponded (p ≤ 0.0001 and p ≤ 0.001, respectively) with concentrations of suspended particulate matter (SPM). Phytoplankton cell volume and diatom cell abundance and volume were not associated with SPM concentrations (p > 0.05). Diatom composition displayed spatial dissimilarities corresponding with resuspension (p ≤ 0.001); small centric diatoms exhibiting meroplanktonic life histories and pennate diatoms considered benthic in origin were most abundant within SPM-impacted, nearshore waters whereas taxa typically comprising assemblages in optically-clear, offshore waters and the basin-wide, spring bloom were not. Values of P B max and α B corresponded (p ≤ 0.0001) with both K d coefficients and SPM concentrations, potentially reflecting increased light harvesting/utilization within impacted assemblages. However, integral production was inversely associated with K d coefficients and SPM concentrations (p < 0.0001) and photosynthesis was light-limited (or nearly so) for most assemblages. Although μ Chl values corresponded with K d coefficients (p ≤ 0.05), values were quite low (x ± S.E., 0.10 ± 0.004 d -1 ) throughout the study. Most likely, distinct rate processes between SPM- and non-impacted assemblages reflected short-term compositional (and corresponding physiological) variations due to infusion of meroplankton and/or tributary-derived phytoplankton. Overall, resuspension appears to have little, if any, long-term impact upon the structure and function of the lake’s phytoplankton.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/41735/1/10452_2004_Article_5149255.pd

Understanding the meaning of medications for patients: The medication experience

Objective: To understand and describe the meaning of medications for patients. Methods: A metasynthesis of three different, yet complementary qualitative research studies, was conducted by two researchers. The first study was a phenomenological study of patients’ medication experiences that used unstructured interviews. The second study was an ethnographic study of pharmaceutical care practice, which included participant observation, in-depth interviews and focus groups with patients of pharmaceutical care. The third was a phenomenological study of the chronic illness experience of medically uninsured individuals in the United States and included an explicit aim to understand the medication experience within that context. The two researchers who conducted these three qualitative studies that examined the medication experience performed the meta-synthesis. The process began with the researchers reviewing the themes of the medication experience for each study. The researchers then aggregated the themes to identify the overlapping and similar themes of the medication experience and which themes are sub-themes within another theme versus a unique theme of the medication experience. The researchers then used the analytic technique, “free imaginative variation” to determine the essential, structural themes of the medication experience. Results: The meaning of medications for patients was captured as four themes of the medication experience: a meaningful encounter; bodily effects; unremitting nature; and exerting control. The medication experience is an individual’s subjective experience of taking a medication in his daily life. It begins as an encounter with a medication. It is an encounter that is given meaning before it occurs. The experience may include positive or negative bodily effects. The unremitting nature of a chronic medication often causes an individual to question the need for the medication. Subsequently, the individual may exert control by altering the way he takes the medication and often in part because of the gained expertise with the medication in his own body. Conclusion: The medication experience is a practice concept that serves to understand patients’ experiences and to understand an individual patient’s medication experience and medication-taking behaviors in order to meet his or her medication-related needs

Benthic algal response to N and P enrichment along a pH gradient

Nutrient enrichment and its effect on benthic algal growth, community composition, and average cell size was assessed across two sites of differing pH within a single habitat. Nutrients were added using in situ substrata, which released either N, P, or no additional nutrients (controls) at each site for 21 days. Upon collection, chlorophyll and biovolume standing stocks of the attached algal microflora were measured. Chlorophyll concentration was different among all treatments, accumulating greatest on P, followed by N, and the least on C substrata (P < 0.001) and was highest at site-2 (P < 0.001), while total algal biovolume was highest on P compared to both N and C substrata (P < 0.05) and did not vary between sites. Increased growth on P substrata was due to the enhanced biovolume of filamentous green algae, although the affected taxa varied between sites. Biovolume to cell density ratios (as a measure of average cell size) were highest on P substrata over both N-enriched and control substrata (P < 0.05) and this pattern was similar between sites. Progression towards a community composed of larger cells following P enrichment observed along this pH gradient, seems to be related to the dominance of larger celled filamentous green algae. Thus, nutrients exhibited greater control on benthic algal growth than did changes in hydrogen ion concentration.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/42877/1/10750_2004_Article_BF00007599.pd

T1 mapping in cardiac MRI

Quantitative myocardial and blood T1 have recently achieved clinical utility in numerous pathologies, as they provide non-invasive tissue characterization with the potential to replace invasive biopsy. Native T1 time (no contrast agent), changes with myocardial extracellular water (edema, focal or diffuse fibrosis), fat, iron, and amyloid protein content. After contrast, the extracellular volume fraction (ECV) estimates the size of the extracellular space and identifies interstitial disease. Spatially resolved quantification of these biomarkers (so-called T1 mapping and ECV mapping) are steadily becoming diagnostic and prognostically useful tests for several heart muscle diseases, influencing clinical decision-making with a pending second consensus statement due mid-2017. This review outlines the physics involved in estimating T1 times and summarizes the disease-specific clinical and research impacts of T1 and ECV to date. We conclude by highlighting some of the remaining challenges such as their community-wide delivery, quality control, and standardization for clinical practice