Comparative assessment of amphibious hearing in pinnipeds

Auditory sensitivity in pinnipeds is influenced by the need to balance efficient sound detection in two vastly different physical environments. Previous comparisons between aerial and underwater hearing capabilities have considered media-dependent differences relative to auditory anatomy, acoustic communication, ecology, and amphibious life history. New data for several species, including recently published audiograms and previously unreported measurements obtained in quiet conditions, necessitate a re-evaluation of amphibious hearing in pinnipeds. Several findings related to underwater hearing are consistent with earlier assessments, including an expanded frequency range of best hearing in true seals that spans at least six octaves. The most notable new results indicate markedly better aerial sensitivity in two seals (Phoca vitulina and Mirounga angustirostris) and one sea lion (Zalophus californianus), likely attributable to improved ambient noise control in test enclosures. An updated comparative analysis alters conventional views and demonstrates that these amphibious pinnipeds have not necessarily sacrificed aerial hearing capabilities in favor of enhanced underwater sound reception. Despite possessing underwater hearing that is nearly as sensitive as fully aquatic cetaceans and sirenians, many seals and sea lions have retained acute aerial hearing capabilities rivaling those of terrestrial carnivores.     

Synthesis and biological evaluation of gem-diamine 1-N-iminosugars related to L-iduronic acid as inhibitors of heparan sulfate 2-O-sulfotransferase

A variety of gem-diamine 1-N-iminosugars related to L-iduronic acid were synthesized and evaluated as inhibitors of heparan sulfate uronyl 2-O-sulfotransferase using an in vitro enzyme assay. Two iminosugars containing guanidino groups acted as potent in vitro inhibitors of the enzyme.     

Bias Assessment of General Chemistry Analytes using Commutable Samples

Harmonisation of reference intervals for routine general chemistry analytes has been a goal for many years. Analytical bias may prevent this harmonisation. To determine if analytical bias is present when comparing methods, the use of commutable samples, or samples that have the same properties as the clinical samples routinely analysed, should be used as reference samples to eliminate the possibility of matrix effect. The use of commutable samples has improved the identification of unacceptable analytical performance in the Netherlands and Spain. The International Federation of Clinical Chemistry and Laboratory Medicine (IFCC) has undertaken a pilot study using commutable samples in an attempt to determine not only country specific reference intervals but to make them comparable between countries. Australia and New Zealand, through the Australasian Association of Clinical Biochemists (AACB), have also undertaken an assessment of analytical bias using commutable samples and determined that of the 27 general chemistry analytes studied, 19 showed sufficiently small between method biases as to not prevent harmonisation of reference intervals. Application of evidence based approaches including the determination of analytical bias using commutable material is necessary when seeking to harmonise reference intervals.     

Identification of Novel Cytotoxic Peptide KENPVLSLVNGMF from Marine Sponge <Emphasis Type="Italic">Xestospongia testudinaria</Emphasis>, with Characterization of Stability in Human Serum

Resistance and side effects are common problems for anticancer drugs used in chemotherapy. Thus, continued research to discover novel and specific anticancer drugs is obligatory. Marine sponges hold great promise as a source of potent cytotoxic peptides with future applications in cancer treatments. This study aimed to purify and identify cytotoxic peptides from the protein hydrolysates of the giant barrel sponge Xestospongia testudinaria, guided by a cytotoxicity assay based on the human cervical cancer cell line (HeLa). Comparison among trypsin, chymotrypsin, papain and alcalase hydrolysates of X. testudinaria revealed papain hydrolysate (PH) to be the most active. PH was purified consecutively by membrane ultrafiltration, gel filtration chromatography, and reversed-phase high performance liquid chromatography (RP-HPLC). Following liquid chromatography-tandem mass spectrometric analysis, two peptides were identified from the most cytotoxic RP-HPLC fraction: KENPVLSLVNGMF and LLATIPKVGVFSILV. Between the two, only the synthetic peptide KENPVLSLVNGMF showed cytotoxicity toward HeLa cells in a dose-dependent manner. KENPVLSLVNGMF (EC₅₀ 0.67 mM) was 3.8-fold more cytotoxic compared with anticancer drug 5-fluorouracil (EC₅₀ 2.56 mM). Furthermore, KENPVLSLVNGMF show only marginal 5% cytotoxicity to Hek293, a non-cancerous, human embryonic kidney cell line, when tested at 0.67 mM. The half-life of the peptide was 3.2?±?0.5 h in human serum in vitro, as revealed by RP-HPLC analyses. These results suggest that KENPVLSLVNGMF identified from X. testudinaria papain hydrolysate has potential applications as peptide lead in future development of potent and specific anticancer drugs.     

Nurturing diversity and inclusion in AI in Biomedicine through a virtual summer program for high school students

Artificial Intelligence (AI) has the power to improve our lives through a wide variety of applications, many of which fall into the healthcare space; however, a lack of diversity is contributing to limitations in how broadly AI can help people. The UCSF AI4ALL program was established in 2019 to address this issue by targeting high school students from underrepresented backgrounds in AI, giving them a chance to learn about AI with a focus on biomedicine, and promoting diversity and inclusion. In 2020, the UCSF AI4ALL three-week program was held entirely online due to the COVID-19 pandemic. Thus, students participated virtually to gain experience with AI, interact with diverse role models in AI, and learn about advancing health through AI. Specifically, they attended lectures in coding and AI, received an in-depth research experience through hands-on projects exploring COVID-19, and engaged in mentoring and personal development sessions with faculty, researchers, industry professionals, and undergraduate and graduate students, many of whom were women and from underrepresented racial and ethnic backgrounds. At the conclusion of the program, the students presented the results of their research projects at the final symposium. Comparison of pre- and post-program survey responses from students demonstrated that after the program, significantly more students were familiar with how to work with data and to evaluate and apply machine learning algorithms. There were also nominally significant increases in the students’ knowing people in AI from historically underrepresented groups, feeling confident in discussing AI, and being aware of careers in AI. We found that we were able to engage young students in AI via our online training program and nurture greater diversity in AI. This work can guide AI training programs aspiring to engage and educate students entirely online, and motivate people in AI to strive towards increasing diversity and inclusion in this field.     

Uncertainty in source partitioning using stable isotopes

Stable isotope analyses are often used to quantify the contribution of multiple sources to a mixture, such as proportions of food sources in an animal's diet, or C₃ and C₄ plant inputs to soil organic carbon. Linear mixing models can be used to partition two sources with a single isotopic signature (e.g., '¹³C) or three sources with a second isotopic signature (e.g., '¹⁵N). Although variability of source and mixture signatures is often reported, confidence interval calculations for source proportions typically use only the mixture variability. We provide examples showing that omission of source variability can lead to underestimation of the variability of source proportion estimates. For both two- and three-source mixing models, we present formulas for calculating variances, standard errors (SE), and confidence intervals for source proportion estimates that account for the observed variability in the isotopic signatures for the sources as well as the mixture. We then performed sensitivity analyses to assess the relative importance of: (1) the isotopic signature difference between the sources, (2) isotopic signature standard deviations (SD) in the source and mixture populations, (3) sample size, (4) analytical SD, and (5) the evenness of the source proportions, for determining the variability (SE) of source proportion estimates. The proportion SEs varied inversely with the signature difference between sources, so doubling the source difference from 2‰ to 4‰ reduced the SEs by half. Source and mixture signature SDs had a substantial linear effect on source proportion SEs. However, the population variability of the sources and the mixture are fixed and the sampling error component can be changed only by increasing sample size. Source proportion SEs varied inversely with the square root of sample size, so an increase from 1 to 4 samples per population cut the SE in half. Analytical SD had little effect over the range examined since it was generally substantially smaller than the population SDs. Proportion SEs were minimized when sources were evenly divided, but increased only slightly as the proportions varied. The variance formulas provided will enable quantification of the precision of source proportion estimates. Graphs are provided to allow rapid assessment of possible combinations of source differences and source and mixture population SDs that will allow source proportion estimates with desired precision. In addition, an Excel spreadsheet to perform the calculations for the source proportions and their variances, SEs, and 95% confidence intervals for the two-source and three-source mixing models can be accessed at http://www.epa.gov/wed/pages/models.htm.     

Genistein improves neuropathology and corrects behaviour in a mouse model of neurodegenerative metabolic disease

Background

Neurodegenerative metabolic disorders such as mucopolysaccharidosis IIIB (MPSIIIB or Sanfilippo disease) accumulate undegraded substrates in the brain and are often unresponsive to enzyme replacement treatments due to the impermeability of the blood brain barrier to enzyme. MPSIIIB is characterised by behavioural difficulties, cognitive and later motor decline, with death in the second decade of life. Most of these neurodegenerative lysosomal storage diseases lack effective treatments. We recently described significant reductions of accumulated heparan sulphate substrate in liver of a mouse model of MPSIIIB using the tyrosine kinase inhibitor genistein.

Methodology/Principal Findings

We report here that high doses of genistein aglycone, given continuously over a 9 month period to MPSIIIB mice, significantly reduce lysosomal storage, heparan sulphate substrate and neuroinflammation in the cerebral cortex and hippocampus, resulting in correction of the behavioural defects observed. Improvements in synaptic vesicle protein expression and secondary storage in the cerebral cortex were also observed.

Conclusions/Significance

Genistein may prove useful as a substrate reduction agent to delay clinical onset of MPSIIIB and, due to its multimodal action, may provide a treatment adjunct for several other neurodegenerative metabolic diseases.