Long-term Changing Research Articles

Abstract 2360: Gene expression profile induced by pregnancy in the breast of premenopausal women

Abstract We previously reported that having completed a full term pregnancy (FTP) confers specific gene expression patterns in the breast of healthy postmenopausal women [Belitskaya-Levy, I. et al. 2011, Peri, S. et al. 2012 and Russo, J. 2012]. In the present work, we report on gene expression differences in the breast of parous versus nulliparous healthy premenopausal women. Using Affymetrix Human Genome U133 Plus 2.0 microarrays, we analyzed the gene expression profile of breast tissue from 30 nulliparous (NP) and 79 parous (P) premenopausal volunteers between the ages of 30 and 47 years who were free of breast pathology. Because of the known short-term increase in breast cancer risk preceding the long-term protective effect of FTP, we also examined gene expression differences in P vs. NP women as a function of time since last FTP. Through multiple regression analysis, controlling for confounders, we found 416 probesets differentially expressed (fold-change ≥ 1.2 and false discovery rate < 10%) comparing all P vs. all NP, and/or, P women whose last FTP was less than 5 years before biopsy vs. all NP women. Among these, 352 probesets, representing 238 genes, were up-regulated, while 64 probesets, representing 48 genes, were down-regulated in parous compared to nulliparous breast. Of interest is that among the up-regulated genes, we observed three expression patterns: 1) transient: genes up-regulated after FTP but whose expression levels rapidly returned to nulliparous levels. These genes were mainly related to immune response (CCL5, CD48, IL7R); 2) long-term changing: genes up-regulated following FTP, whose expression levels decreased with increasing time since last FTP but did not return to nulliparous levels. These genes included genes related to immune response (CD38, CXCL10) and development (DKK3, LAMA2); 3) long-term constant: genes that remained up-regulated in parous compared to nulliparous breast, independent of time since last FTP. These genes were mainly involved in developmental processes (BHLHE22, FZD8, KRT5), cell differentiation (RASGRP1, DSC3) and chromatin remodeling (NAP1L2). This study shows that a FTP induces long-term expression changes in genes related to the processes of development, cell differentiation and chromatin remodeling as we also found in the parous postmenopausal breast. Additionally, the transiently activated genes related to immune response during the first five years after FTP may play a role in the short-term increase of breast cancer risk following FTP. A better understanding of the molecular effects of parity on the breast may help the development of novel strategies for preventing breast cancer. (This work was supported by Avon Foundation for Women Breast Cancer Research Program grant 02-2010-117 and by NIH core grant CA06927 to Fox Chase Cancer Center). Citation Format: Julia Santucci-Pereira, Anne Zeleniuch-Jacquotte, Yelena Afanasyeva, Hua Zhong, Eric A. Ross, Michael Slifker, Suraj Peri, Ricardo López de Cicco, Yubo Zhai, Irma H. Russo, Theresa Nguyen, Fathima Sheriff, Alan A. Arslan, Pal Bordas, Per Lenner, Janet Åhman, Anna-Stina L. Eriksson, Robert Johansson, Göran Hallmans, Paolo Toniolo, Jose Russo. Gene expression profile induced by pregnancy in the breast of premenopausal women. [abstract]. In: Proceedings of the 105th Annual Meeting of the American Association for Cancer Research; 2014 Apr 5-9; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2014;74(19 Suppl):Abstract nr 2360. doi:10.1158/1538-7445.AM2014-2360

Calculate excess mortality during heatwaves using Hilbert-Huang transform algorithm

BackgroundHeatwaves could cause the population excess death numbers to be ranged from tens to thousands within a couple of weeks in a local area. An excess mortality due to a special event (e.g., a heatwave or an epidemic outbreak) is estimated by subtracting the mortality figure under ‘normal’ conditions from the historical daily mortality records. The calculation of the excess mortality is a scientific challenge because of the stochastic temporal pattern of the daily mortality data which is characterised by (a) the long-term changing mean levels (i.e., non-stationarity); (b) the non-linear temperature-mortality association. The Hilbert-Huang Transform (HHT) algorithm is a novel method originally developed for analysing the non-linear and non-stationary time series data in the field of signal processing, however, it has not been applied in public health research. This paper aimed to demonstrate the applicability and strength of the HHT algorithm in analysing health data.MethodsSpecial R functions were developed to implement the HHT algorithm to decompose the daily mortality time series into trend and non-trend components in terms of the underlying physical mechanism. The excess mortality is calculated directly from the resulting non-trend component series.ResultsThe Brisbane (Queensland, Australia) and the Chicago (United States) daily mortality time series data were utilized for calculating the excess mortality associated with heatwaves. The HHT algorithm estimated 62 excess deaths related to the February 2004 Brisbane heatwave. To calculate the excess mortality associated with the July 1995 Chicago heatwave, the HHT algorithm needed to handle the mode mixing issue. The HHT algorithm estimated 510 excess deaths for the 1995 Chicago heatwave event. To exemplify potential applications, the HHT decomposition results were used as the input data for a subsequent regression analysis, using the Brisbane data, to investigate the association between excess mortality and different risk factors.ConclusionsThe HHT algorithm is a novel and powerful analytical tool in time series data analysis. It has a real potential to have a wide range of applications in public health research because of its ability to decompose a nonlinear and non-stationary time series into trend and non-trend components consistently and efficiently.

Interleukin-10 Inhibits Bone Resorption: A Potential Therapeutic Strategy in Periodontitis and Other Bone Loss Diseases

Periodontitis and other bone loss diseases, decreasing bone volume and strength, have a significant impact on millions of people with the risk of tooth loss and bone fracture. The integrity and strength of bone are maintained through the balance between bone resorption and bone formation by osteoclasts and osteoblasts, respectively, so the loss of bone results from the disruption of such balance due to increased resorption or/and decreased formation of bone. The goal of therapies for diseases of bone loss is to reduce bone loss, improve bone formation, and then keep healthy bone density. Current therapies have mostly relied on long-term medication, exercise, anti-inflammatory therapies, and changing of the life style. However there are some limitations for some patients in the effective treatments for bone loss diseases because of the complexity of bone loss. Interleukin-10 (IL-10) is a potent anti-inflammatory cytokine, and recent studies have indicated that IL-10 can contribute to the maintenance of bone mass through inhibition of osteoclastic bone resorption and regulation of osteoblastic bone formation. This paper will provide a brief overview of the role of IL-10 in bone loss diseases and discuss the possibility of IL-10 adoption in therapy of bone loss diseases therapy.

Management of dentoalveolar fracture with multiple avulsions: A case report with three years follow-up

Traumatic dental injuries are common in children and adolescents are may cause dramatic episodes. Avulsion management associated with dentoalveolar fracture may pose significant difficulty to the clinician. Acute dental treatment is an important requisite after such injuries. Immediate management and continuous follow-up is necessary especially with ever long-term changing treatment protocols. Herein we describe a 10 year-old-boy, referred to our hospital for multiple teeth avulsions, extrusions including molar which is very rare and dentoalveolar fracture as he met with an accident while playing. Timely treatment was done with cap splint appliance. Patient is doing well with three years of follow-up. We highlight the significance of storage media for carrying the avulsed teeth, and cap splint for stabilization of complicated dentoalveolar fracture which resulted in excellent treatment and a long-time prognosis

YIELDSTAT – A spatial yield model for agricultural crops

The YIELDSTAT model for crop yields, an advanced hybrid of traditional non-linear regression approaches and expert knowledge databases, was developed to predict the spatial distribution of yields for a range of arable crops (winter wheat, winter barley, winter rye, winter triticale, spring barley, oats, potato, sugar beet, winter oil-seed rape, silage maize, clover, clover/grass mix, lucerne, lucerne/grass mix, fodder grass) and two grassland types (intensive, extensive) in eastern Germany across different scales up to the regional scale. YIELDSTAT accounts for a wide range of yield-influencing factors derived from weather, soil, relief and management data, as well as for the long-term changing atmospheric CO2 concentration and for the trend owing to progress in breeding and agro-technology. YIELDSTAT regression modules were derived from several hundred farm data sets from 1975 to 1990 and tested against recent yield observations from the Federal State of Thuringia, Germany. The model test was performed at three different spatial scales. YIELDSTAT successfully reproduced the observed data at all three scales, with a normalised mean bias error of 3.02% across all crops and scales. Model testing also revealed a number of weaknesses in the model, identifying yield-reducing factors that had not been considered previously. All in all, the model proved fitness-for-purpose for simulating spatial yields, also under assumed future climate conditions.

Influence of Intra- and Extracellular Acidification on Free Radical Formation and Mitochondria Membrane Potential in Rat Brain Synaptosomes

Brain ischemia is accompanied by lowering of intra- and extracellular pH. Stroke often leads to irreversible damage of synaptic transmission by unknown mechanism. We investigated an influence of lowering of pH(i) and pH(o) on free radical formation in synaptosomes. Three models of acidosis were used: (1) pH(o) 6.0 corresponding to pH(i) decrease down to 6.04; (2) pH(o) 7.0 corresponding to the lowering of pH(i) down to 6.92: (3) 1mM amiloride corresponding to pH(i) decrease down to 6.65. We have shown that both types of extracellular acidification, but not intracellular acidification, increase 2',7'-dichlorodihydrofluorescein diacetate fluorescence that reflects free radical formation. These three treatments induce the rise of the dihydroethidium fluorescence that reports synthesis of superoxide anion. However, the impact of amiloride on superoxide anion synthesis was less than that induced by moderate extracellular acidification. Superoxide anion synthesis at pH(o) 7.0 was almost completely eliminated by mitochondrial uncoupler carbonyl cyanide 4-(trifluoromethoxy)phenylhydrazone. Furthermore, using fluorescent dyes JC-1 and rhodamine-123, we confirmed that pH(o) lowering, but not intracellular acidification, led to depolarization of intrasynaptosomal mitochondria. We have shown that pH(o) but not pH(i) lowering led to oxidative stress in neuronal presynaptic endings that might underlie the long-term irreversible changing in synaptic transmission.

Track Irregularity Time Series Analysis and Trend Forecasting

The combination of linear and nonlinear methods is widely used in the prediction of time series data. This paper analyzes track irregularity time series data by using gray incidence degree models and methods of data transformation, trying to find the connotative relationship between the time series data. In this paper, GM (1,1) is based on first‐order, single variable linear differential equations; after an adaptive improvement and error correction, it is used to predict the long‐term changing trend of track irregularity at a fixed measuring point; the stochastic linear AR, Kalman filtering model, and artificial neural network model are applied to predict the short‐term changing trend of track irregularity at unit section. Both long‐term and short‐term changes prove that the model is effective and can achieve the expected accuracy.

Carpal tunnel syndrome: long-term nerve conduction studies in 261 hands

To compare a long-term carpal tunnel syndrome (CTS) on nerve conduction studies (NCS) in hands treated non-surgically. We retrospectively selected 261 symptomatic CTS hands (166 patients), all of them confirmed by NCS. In all cases, at least 2 NCS were performed in an interval greater than 12 months. Cases with associated polyneuropathy were excluded. NCS parameters for CTS electrodiagnosis included a sensory conduction velocity (SCV) < or =46.6 m/s (wrist to index finger, 14 cm) and distal motor latency (DML) > or =4.25 ms (wrist to APB, 8 cm). 92.8% were women; mean age was 49 years (20-76); the mean interval between NCS was 47 months (12-150). In the first exam, the median sensory nerve action potential (SNAP) and the compound action muscular potential were absent in 9.8% and 1.9%, respectively. In the second/last exam, SCV worsened in 54.2%, remained unchanged in 11.6% and improved in 34.2%. SNAP amplitude worsened in 57.7%, remained unchanged in 13.1% and improved in 29.2%. DML worsened in 52.9%, remained unchanged in 7.6% and improved in 39.5%. Overall, NCS parameters worsened in 54.9%, improved in 34.3% and remained unchanged in 10.8%. Long-term changing in NCS of CTS hands apparently were not related to clinical symptomatology and could lead to some difficulty in clinical correlation and prognosis. Aging, male gender and absent SNAP were more related to NCS worsening, regardless the mean interval time between the NCS.

Synaptic plasticity: Keeping synapses under control

Recent studies have confirmed that a retrograde signal is produced at the neuromuscular junction that can adjust the efficacy of transmission to meet long-term changing needs. Genetic manipulations in Drosophila have begun to define the circumstances in which such signals are generated and how they act.