The Importance of Hydration in Wound Healing: Reinvigorating the clinical perspective

Balancing skin hydration levels is important as any disruption in skin integrity will result in disturbance of the dermal water balance. The discovery that a moist wound healing environment actively supports the healing response when compared to a dry environment highlights the importance of water and good hydration levels for optimal wound healing. The benefits of “wet” or “hyper-hydrated” wound healing appears to offer benefits that are similar to those offered by moist wound healing over wounds healing in a dry environment. This suggests that the presence of free water itself during wound healing may not be detrimental to healing but that any adverse effects of wound fluid on tissues is more likely related to the biological components contained within chronic wound exudate (e.g. elevated protease levels). Appropriate dressings applied to wounds must be able to absorb not only the exudate but also retain this excess fluid together with its protease solutes while concurrently preventing desiccation. This is particularly important in the case of chronic wounds where peri-wound skin barrier properties are compromised and there is increased permeation across the injured skin barrier. This review discusses the importance of appropriate levels of hydration in skin with a particular focus on the need for optimal hydration levels for effective healing

Homocysteine levels in pediatric renal transplant recipients.

Transplant Proc. 2003 May;35(3):1093-5. Homocysteine levels in pediatric renal transplant recipients. Mota C, Fonseca I, Santos MJ, Costa T, Faria MS, Henriques AC, Sarmento AM, Pereira E, Pereira M. Department of Paediatric Nephrology, Maria Pia Children's Hospital, R. da Boavista, 827, 4050-111, Porto, Portugal. [email protected] PMID: 12947872 [PubMed - indexed for MEDLIN

Bioassays against pinewood nematode: assessment of a suitable dilution agent and screening for bioactive essential oils

Acetone was investigated and found to be an appropriate alternative to Triton X-100 as a solvent of essential oils in bioassays aimed to investigate their effects on pinewood nematode (Bursaphelenchus xylophilus) mortality. Therefore it was used as dilution agent to screen the effectiveness of fifty two essential oils against this pest. Thirteen essential oils were highly effective, resulting in more than 90% pinewood nematode mortality at 2 mg/mL, with six of them resulting in 100% mortality. LC100 values ranged between 0.50 mg/mL and 0.83 mg/mL for the essential oils of Origanum vulgare and Satureja montana, respectively. Essential oils were submitted to gas chromatography and gas chromatography-mass spectrometry analysis and their chemical composition established. Data from essential oils with 100% mortality at 2 mg/mL and other essential oils previously found to have LC100 ≤ 2 mg/mL was combined, their chemical profiles investigated by correspondences analysis plus automatic classification

Time series forecasting with the WARIMAX-GARCH method

It is well-known that causal forecasting methods that include appropriately chosen Exogenous Variables (EVs) very often present improved forecasting performances over univariate methods. However, in practice, EVs are usually difficult to obtain and in many cases are not available at all. In this paper, a new causal forecasting approach, called Wavelet Auto-Regressive Integrated Moving Average with eXogenous variables and Generalized Auto-Regressive Conditional Heteroscedasticity (WARIMAX-GARCH) method, is proposed to improve predictive performance and accuracy but also to address, at least in part, the problem of unavailable EVs. Basically, the WARIMAX-GARCH method obtains Wavelet “EVs” (WEVs) from Auto-Regressive Integrated Moving Average with eXogenous variables and Generalized Auto-Regressive Conditional Heteroscedasticity (ARIMAX-GARCH) models applied to Wavelet Components (WCs) that are initially determined from the underlying time series. The WEVs are, in fact, treated by the WARIMAX-GARCH method as if they were conventional EVs. Similarly to GARCH and ARIMA-GARCH models, the WARIMAX-GARCH method is suitable for time series exhibiting non-linear characteristics such as conditional variance that depends on past values of observed data. However, unlike those, it can explicitly model frequency domain patterns in the series to help improve predictive performance. An application to a daily time series of dam displacement in Brazil shows the WARIMAX-GARCH method to remarkably outperform the ARIMA-GARCH method, as well as the (multi-layer perceptron) Artificial Neural Network (ANN) and its wavelet version referred to as Wavelet Artificial Neural Network (WANN) as in [1], on statistical measures for both in-sample and out-of-sample forecasting

Wound healing and hyper-hydration - a counter intuitive model

Winters seminal work in the 1960s relating to providing an optimal level of moisture to aid wound healing (granulation and re-epithelialisation) has been the single most effective advance in wound care over many decades. As such the development of advanced wound dressings that manage the fluidic wound environment have provided significant benefits in terms of healing to both patient and clinician. Although moist wound healing provides the guiding management principle confusion may arise between what is deemed to be an adequate level of tissue hydration and the risk of developing maceration. In addition, the counter-intuitive model ‘hyper-hydration’ of tissue appears to frustrate the moist wound healing approach and advocate a course of intervention whereby tissue is hydrated beyond what is a normally acceptable therapeutic level. This paper discusses tissue hydration, the cause and effect of maceration and distinguishes these from hyper-hydration of tissue. The rationale is to provide the clinician with a knowledge base that allows optimisation of treatment and outcomes and explains the reasoning behind wound healing using hyper-hydration

The pattern of growth hormone secretion during the menstrual cycle in normal and depressed women

Objective Major depression is associated to altered hypothalamic pituitary function. Stress is linked to elevated cortisol as well as menstrual cycle disturbance; however, there is no known relationship between depression and menstrual cycle disruption. The aim of this study was to investigate changes of growth hormone (GH) secretion during the menstrual cycle in normal and depressed women. Design Case-control study. Patients and methods Nineteen women affected with depression and 24 normal controls were included. The two groups had comparable body mass index (BMI), and age (29·4 ±9·8 vs. 28·6 ± 9·7 years). Nine depressed and 10 controls were studied in the follicular phase, while 10 depressed and 14 controls were studied in the luteal phase of the cycle. GH was sampled every 10 min for 24 h, and the data were analysed by the cluster pulse detection method. Results There was no difference in 24-h mean GH concentrations between depressed and control subjects (P =0·93), even after accounting for menstrual cycle phase (P = 0·38). GH pulse frequency was higher during the follicular phase of the cycle (P =0·032), and nocturnal GH was higher in the follicular phase of the cycle (P =0·05, and after adjusting for 24-h GH, P= 0·0138) regardless of whether thesubjects were depressed or healthy. Conclusions In studies of GH secretion in women with or without depression, it is necessary to control for the phase of menstrual cycle.NIMH MH 50030 NICHD K12HD01438Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/49486/2/KasaVubuYoung.pd