Microneedling with a Novel, n-3-PUFA-Rich Formulation Accelerates Inflammation Resolution to Improve Skin Recovery Outcomes in Adults with Healthy Skin.

INTRODUCTION: Microneedling is a cosmetic procedure that leverages the skin's natural ability to heal in order to promote collagen formation and skin rejuvenation. To provide improved results, the technique can be combined with topical formulations. A new formulation of multiple actives, including omega-3 (n-3) polyunsaturated fatty acids (PUFAs), was designed to accelerate the resolution of inflammation and wound healing following micro-injury treatments, while enhancing the visible appearance of procedure results, including erythema, luminosity and skin texture. METHODS: In this randomised, controlled, split-face study, we examined 32 healthy female participants aged 30-70 years for 4 weeks following microneedling treatment with a novel multiple-active-ingredient formulation or conventional microneedling protocol with a hyaluronic acid control serum. Changes in skin condition were assessed by blinded clinical photography and expert evaluation. Measurements were collected at baseline, 1 h, 1 day, 7 days and 28 days post treatment. RESULTS: Significantly greater improvements in expert-assessed erythema, luminosity and skin texture were reported following application of the novel multiple-active-ingredient formulation than the hyaluronic acid control serum. This was confirmed by representative VISIA®-CR imaging. CONCLUSION: These data provide new evidence for the role of a novel multiple-active-ingredient formulation for improving skin outcomes up to 28 days following microneedling in adults with healthy skin when compared with a hyaluronic acid serum. The n-3 PUFA content of this formulation may drive accelerated inflammation resolution and wound healing alongside the complementary action of the other active ingredients, leading to the observed improvements in erythema, luminosity and skin texture.

Urinary glyphosate and AMPA levels in a cross-sectional study of postmenopausal women: Associations with organic eating behavior and dietary intake.

Animal and epidemiologic studies suggest that there may be adverse health effects from exposure to glyphosate, the most highly used pesticide in the world, and its metabolite aminomethylphosphonic acid (AMPA). Meanwhile, consumption of organic foods (presumably grown free of chemical pesticides) has increased in recent years. However, there have been limited biomonitoring studies assessing the levels of human glyphosate and AMPA exposure in the United States. We examined urinary levels of glyphosate and AMPA in the context of organic eating behavior in a cohort of healthy postmenopausal women residing in Southern California and evaluated associations with demographics, dietary intake, and other lifestyle factors. 338 women provided two first-morning urine samples and at least one paired 24-h dietary recall reporting the previous day's dietary intake. Urinary glyphosate and AMPA were measured using LC-MS/MS. Participants reported on demographic and lifestyle factors via questionnaires. Potential associations were examined between these factors and urinary glyphosate and AMPA concentrations. Glyphosate was detected in 89.9% of urine samples and AMPA in 67.2%. 37.9% of study participants reported often or always eating organic food, 30.2% sometimes, and 32.0% seldom or never. Frequency of organic food consumption was associated with several demographic and lifestyle factors. Frequent organic eaters had significantly lower urinary glyphosate and AMPA levels, but not after adjustment for covariates. Grain consumption was significantly associated with higher urinary glyphosate levels, even among women who reported often or always eating organic grains. Soy protein and alcohol consumption as well as high frequency of eating fast food were associated with higher urinary AMPA levels. In conclusion, in the largest study to date examining paired dietary recall data and measurements of first-void urinary glyphosate and AMPA, the vast majority of subjects sampled had detectable levels, and significant dietary sources in the American diet were identified.

Reassessing the Abundance of miRNAs in the Human Pancreas and Rodent Cell Lines and Its Implication.

miRNAs are critical for pancreas development and function. However, we found that there are discrepancies regarding pancreatic miRNA abundance in published datasets. To obtain a more relevant profile that is closer to the true profile, we profiled small RNAs from human islets cells, acini, and four rodent pancreatic cell lines routinely used in diabetes and pancreatic research using a bias reduction protocol for small RNA sequencing. In contrast to the previous notion that miR-375-3p is the most abundant pancreatic miRNA, we found that miR-148a-3p and miR-7-5p were also abundant in islets. In silico studies using predicted and validated targets of these three miRNAs revealed that they may work cooperatively in endocrine and exocrine cells. Our results also suggest, compared to the most-studied miR-375, that both miR-148a-3p and miR-7-5p may play more critical roles in the human pancreas. Moreover, according to in silico-predicted targets, we found that miR-375-3p had a much broader target spectrum by targeting the coding sequence and the 5' untranslated region, rather than the conventional 3' untranslated region, suggesting additional unexplored roles of miR-375-3p beyond the pancreas. Our study provides a valuable new resource for studying miRNAs in pancreata.

Meta-analysis of three-stressor combinations on population-level fitness reveal substantial higher-order interactions.

Although natural populations are typically subjected to multiple stressors, most past research has focused on single-stressor and two-stressor interactions, with little attention paid to higher-order interactions among three or more stressors. However, higher-order interactions increasingly appear to be widespread. Consequently, we used a recently introduced and improved framework to re-analyze higher-order ecological interactions. We conducted a literature review of the last 100 years (1920-2020) and reanalyzed 142 ecological three-stressor interactions on species' populations from 38 published papers; the vast majority of these studies were from the past 10 years. We found that 95.8 % (n = 136) of the three-stressor combinations had either not been categorized before or resulted in different interactions than previously reported. We also found substantial levels of emergent properties-interactions that are not due to strong pairwise interactions within the combination but rather uniquely due to all three stressors being combined. Calculating net interactions-the overall accounting for all possible interactions within a combination including the emergent and all pairwise interactions-we found that the most prevalent interaction type is antagonism, corresponding to a smaller than expected effect based on single stressor effects. In contrast, for emergent interactions, the most prevalent interaction type is synergistic, resulting in a larger than expected effect based on single stressor effects. Additionally, we found that hidden suppressive interactions-where a pairwise interaction is suppressed by a third stressor-are found in the majority of combinations (74 %). Collectively, understanding multiple stressor interactions through applying an appropriate framework is crucial for answering fundamental questions in ecology and has implications for conservation biology and population management. Crucially, identifying emergent properties can reveal hidden suppressive interactions that could be particularly important for the ecological management of at-risk populations.

Cardio PyMEA: A user-friendly, open-source Python application for cardiomyocyte microelectrode array analysis.

Open source analytical software for the analysis of electrophysiological cardiomyocyte data offers a variety of new functionalities to complement closed-source, proprietary tools. Here, we present the Cardio PyMEA application, a free, modifiable, and open source program for the analysis of microelectrode array (MEA) data obtained from cardiomyocyte cultures. Major software capabilities include: beat detection; pacemaker origin estimation; beat amplitude and interval; local activation time, upstroke velocity, and conduction velocity; analysis of cardiomyocyte property-distance relationships; and robust power law analysis of pacemaker spatiotemporal instability. Cardio PyMEA was written entirely in Python 3 to provide an accessible, integrated workflow that possesses a user-friendly graphical user interface (GUI) written in PyQt5 to allow for performant, cross-platform utilization. This application makes use of object-oriented programming (OOP) principles to facilitate the relatively straightforward incorporation of custom functionalities, e.g. power law analysis, that suit the needs of the user. Cardio PyMEA is available as an open source application under the terms of the GNU General Public License (GPL). The source code for Cardio PyMEA can be downloaded from Github at the following repository: https://github.com/csdunhamUC/cardio_pymea.

Pacemaker translocations and power laws in 2D stem cell-derived cardiomyocyte cultures.

Power laws are of interest to several scientific disciplines because they can provide important information about the underlying dynamics (e.g. scale invariance and self-similarity) of a given system. Because power laws are of increasing interest to the cardiac sciences as potential indicators of cardiac dysfunction, it is essential that rigorous, standardized analytical methods are employed in the evaluation of power laws. This study compares the methods currently used in the fields of condensed matter physics, geoscience, neuroscience, and cardiology in order to provide a robust analytical framework for evaluating power laws in stem cell-derived cardiomyocyte cultures. One potential power law-obeying phenomenon observed in these cultures is pacemaker translocations, or the spatial and temporal instability of the pacemaker region, in a 2D cell culture. Power law analysis of translocation data was performed using increasingly rigorous methods in order to illustrate how differences in analytical robustness can result in misleading power law interpretations. Non-robust methods concluded that pacemaker translocations adhere to a power law while robust methods convincingly demonstrated that they obey a doubly truncated power law. The results of this study highlight the importance of employing comprehensive methods during power law analysis of cardiomyocyte cultures.

Characterization of dental anatomy and gingival biotype in Asian populations.

Gingival and dental characteristics are risk factors for periodontal problems. With short or fused roots, a decreased periodontium results in some attachment loss, compromising periodontal stability. Similarly, with an increased incidence of thin gingival biotype, inflammatory and traumatic insults may result in gingival recession. Anecdotally, Asian dentitions have been described as having short roots with "thin gingiva". This cross-sectional study will utilize clinical data and radiographic interpretation to ascertain whether this clinical impression is valid.