398.6ºC at 760mmHg
HS Code Reference
Personal Projective Equipment
For Reference Standard and R&D, Not for Human Use Directly.
provides coniferyl ferulate(CAS#:53369-00-9) MSDS, density, melting point, boiling point, structure, formula, molecular weight etc. Articles of coniferyl ferulate are included as well.>> amp version: coniferyl ferulate
The goal of this protocol is to study mitochondria within intraepidermal nerve fibers. Therefore, 3D imaging and analysis techniques were developed to isolate nerve-specific mitochondria and evaluate disease-induced alterations of mitochondria in the distal tip of sensory nerves. The protocol combines fluorescence immunohistochemistry, confocal microscopy and 3D image analysis techniques to visualize and quantify nerve-specific mitochondria. Detailed parameters are defined throughout the procedures in order to provide a concrete example of how to use these techniques to isolate nerve-specific mitochondria. Antibodies were used to label nerve and mitochondrial signals within tissue sections of skin punch biopsies, which was followed by indirect immunofluorescence to visualize nerves and mitochondria with a green and red fluorescent signal respectively. Z-series images were acquired with confocal microscopy and 3D analysis software was used to process and analyze the signals. It is not necessary to follow the exact parameters described within, but it is important to be consistent with the ones chosen throughout the staining, acquisition and analysis steps. The strength of this protocol is that it is applicable to a wide variety of circumstances where one fluorescent signal is used to isolate other signals that would otherwise be impossible to study alone.
Neurobiology, Issue 127, mitochondria, intraepidermal nerve fibers, human skin biopsy, three-dimensional imaging and analysis, small fiber neuropathy
Three-dimensional Imaging and Analysis of Mitochondria within Human Intraepidermal Nerve Fibers
Hussein S. Hamid, 1 John M. Hayes, 2 Eva L. Feldman, 2 and Stephen I. Lentz 3
Unexpected weight loss is a symptom of serious disease in primary care, for example between 1 in 200 and 1 in 30 patients with unexpected weight loss go on to develop cancer. However, it remains unclear how and when general practitioners (GPs) should investigate unexpected weight loss. Without clarification, GPs may wait too long before referring (choosing to watch and wait and potentially missing a diagnosis) or not long enough (overburdening hospital services and exposing patients to the risks of investigation). The overall aim of this study is to provide the evidence necessary to allow GPs to more effectively manage patients with unexpected weight loss.
A retrospective cohort analysis of UK Clinical Practice Research Datalink (CPRD) data to: (1) describe how often in UK primary care the symptom of reported weight loss is coded, when weight is measured, and how GPs respond to a patient attending with unexpected weight loss; (2) identify the predictive value of recorded weight loss for cancer and serious disease in primary care, using cumulative incidence plots to compare outcomes between subgroups and Cox regression to explore and adjust for covariates. Preliminary work in CPRD estimates that weight loss as a symptom is recorded for approximately 148,000 eligible patients > 18 years and is distributed evenly across decades of age, providing adequate statistical power and precision in relation to cancer overall and common cancers individually. Further stratification by cancer stage will be attempted but may not be possible as not all practices within CPRD are eligible for cancer registry linkage, and staging information is often incomplete. The feasibility of using multiple imputation to address missing covariate values will be explored.
This will be the largest reported retrospective cohort of primary care patients with weight measurements and unexpected weight loss codes used to understand the association between weight measurement, unexpected weight loss, and serious disease including cancer. Our findings will directly inform international guidelines for the management of unexpected weight loss in primary care populations.
Weight loss, Early detection of cancer, Serious disease, Primary care, Cohort study
Weight loss as a predictor of cancer and serious disease in primary care: an ISAC-approved CPRD protocol for a retrospective cohort study using routinely collected primary care data from the UK
B. D. Nicholson,corresponding author1 P. Aveyard,1 F. D. R. Hobbs,1 M. Smith,1 A. Fuller,1 R. Perera,1 W. Hamilton,2 S. Stevens,1 and C. R. Bankhead1
Reports that aging slows down in space prompted this investigation of anti-aging effects in humans by analyzing astronauts’ heart rate variability (HRV). Ambulatory 48-hour electrocardiograms from 7 astronauts (42.1 ± 6.8 years; 6 men) 20.6 ± 2.7 days (ISS01) and 138.6 ± 21.8 days (ISS02) after launch were divided into 24-hour spans of relative lower or higher magnetic disturbance, based on geomagnetic measures in Tromso, Norway. Magnetic disturbances were significantly higher on disturbed than on quiet days (ISS01: 72.01 ± 33.82 versus 33.96 ± 17.90 nT, P = 0.0307; ISS02: 71.06 ± 51.52 versus 32.53 ± 27.27 nT, P = 0.0308). SDNNIDX was increased on disturbed days (by 5.5% during ISS01, P = 0.0110), as were other HRV indices during ISS02 (SDANN, 12.5%, P = 0.0243; Triangular Index, 8.4%, P = 0.0469; and TF-component, 17.2%, P = 0.0054), suggesting the action of an anti-aging or longevity effect. The effect on TF was stronger during light (12:00-17:00) than during darkness (0:00-05:00) (P = 0.0268). The brain default mode network (DMN) was activated, gauged by increases in the LF-band (9.7%, P = 0.0730) and MF1-band (9.9%, P = 0.0281). Magnetic changes in the magnetosphere can affect and enhance HRV indices in space, involving an anti-aging or longevity effect, probably in association with the brain DMN, in a light-dependent manner and/or with help from the circadian clock.
Subject terms: Quality of life, Ageing
Anti-aging effects of long-term space missions, estimated by heart rate variability
Kuniaki Otsuka,corresponding author1,2 Germaine Cornelissen,2 Yutaka Kubo,3 Koichi Shibata,3 Koh Mizuno,4,5 Hiroshi Ohshima,5 Satoshi Furukawa,5 and Chiaki Mukai5