Pain-related and psychological factors mediate the effect of personality on health-related quality of life. A study in breast cancer survivors with persistent pain.

Introduction: Personality characteristics affect the long-term well-being and health-related quality of life (HrQoL) of breast cancer (BC) survivors. Persistent pain significantly affects psychosocial well-being and HrQoL in this patient group. We studied the effects of temperament and character via pain-related and psychological factors on dimensions of HrQoL in BC survivors.

Temperament and character dimensions differ in chronic post-surgical neuropathic pain and cold pressure pain.

Objectives: Psychobiological temperament and cognitive-evaluative character link to coping with chronic pain. The aim was to study possible independent role of temperament and character dimensions both in chronic and experimental pain in chronic post-surgical pain patients. This is a substudy of a previously published larger cohort of patients with intercostobrachial nerve injury after breast cancer surgery.

Static mechanical allodynia in post-surgical neuropathic pain after breast cancer treatments.

Objectives Static mechanical allodynia (SMA), i. e., pain caused by normally non-painful static pressure, is a prevalent manifestation of neuropathic pain (NP).

Psychological resilience associates with pain experience in women treated for breast cancer.

Background and aims Psychological resilience refers to successful adaptation or a positive outcome in the context of significant life adversity, such as chronic pain. On the other hand, anxiety closely associates with pain. The aim of this study was to explore how anxiety and psychological resilience together associate with persistent and experimental pain.

Douleur Neuropathique 4 (DN4) stratifies possible and definite neuropathic pain after surgical peripheral nerve lesion.

Background: Douleur Neuropathique 4 (DN4) is a screening questionnaire to help identify neuropathic pain (NP) in clinical practice and research. We tested the accuracy of the DN4 questionnaire in stratifying possible NP (pNP) and definite NP (dNP) in patients operated for breast cancer.

Methods: We studied 163 patients from a longitudinal cohort of breast cancer operated patients 4-9 years after surgery.

What makes surgical nerve injury painful? A 4-year to 9-year follow-up of patients with intercostobrachial nerve resection in women treated for breast cancer.

Nerve injury during breast cancer surgery can cause neuropathic pain (NP). It is not known why some, but not all, patients develop chronic postsurgical neuropathic pain (CPSNP) after the same nerve injury. In this study, we examined 251 breast cancer survivors with surgeon-verified intercostobrachial nerve resection to identify factors that associate with CPSNP.

Changes in global gene expression of Vibrio parahaemolyticus induced by cold- and heat-stress.

Background: Vibrio (V.) parahaemolyticus causes seafood-borne gastro-intestinal bacterial infections in humans worldwide. It is widely found in marine environments and is isolated frequently from seawater, estuarine waters, sediments and raw or insufficiently cooked seafood.

Gene expression profiles of Vibrio parahaemolyticus in viable but non-culturable state.

Viable but non-culturable (VBNC) state is referred to as a dormant state of non-sporulating bacteria enhancing the survival in adverse environments. To our knowledge, only few studies have been conducted on whole genomic expression of Vibrio parahaemolyticus VBNC state. Since a degradation of nucleic acids in V.

Metabolic engineering of Acinetobacter baylyi ADP1 for improved growth on gluconate and glucose.

A high growth rate in bacterial cultures is usually achieved by optimizing growth conditions, but metabolism of the bacterium limits the maximal growth rate attainable on the carbon source used. This limitation can be circumvented by engineering the metabolism of the bacterium. Acinetobacter baylyi has become a model organism for studies of bacterial metabolism and metabolic engineering due to its wide substrate spectrum and easy-to-engineer genome.

Bioprocess data mining using regularized regression and random forests.

Background: In bioprocess development, the needs of data analysis include (1) getting overview to existing data sets, (2) identifying primary control parameters, (3) determining a useful control direction, and (4) planning future experiments. In particular, the integration of multiple data sets causes that these needs cannot be properly addressed by regression models that assume linear input-output relationship or unimodality of the response function. Regularized regression and random forests, on the other hand, have several properties that may appear important in this context.

Heat stress adaptation induces cross-protection against lethal acid stress conditions in Arcobacter butzleri but not in Campylobacter jejuni.

The ability of many bacteria to adapt to stressful conditions may later protect them against the same type of stress (specific adaptive response) or different types of stresses (multiple adaptive response, also termed cross-protection). Arcobacter butzleri and Campylobacter jejuni are close phylogenetic relatives that occur in many foods of animal origin and have been linked with human illness (mainly diarrhoea). In the present study, sublethal stress adaptation temperatures (48 °C and 10 °C) and mild and lethal acid conditions (pH 5.

Improved triacylglycerol production in Acinetobacter baylyi ADP1 by metabolic engineering.

Background: Triacylglycerols are used in various purposes including food applications, cosmetics, oleochemicals and biofuels. Currently the main sources for triacylglycerol are vegetable oils, and microbial triacylglycerol has been suggested as an alternative for these. Due to the low production rates and yields of microbial processes, the role of metabolic engineering has become more significant.

Storage of environmental samples for guaranteeing nucleic acid yields for molecular microbiological studies.

The purpose of this study is to evaluate whether sample preservation can affect the yield of nucleic acid extracts from environmental samples. Storage of microbial samples was studied using three sediment types of varying carbon contents (10-57% carbon of dry weight). Four different storage solutions were tested at three temperatures.

Reconstruction and validation of RefRec: a global model for the yeast molecular interaction network.

Molecular interaction networks establish all cell biological processes. The networks are under intensive research that is facilitated by new high-throughput measurement techniques for the detection, quantification, and characterization of molecules and their physical interactions. For the common model organism yeast Saccharomyces cerevisiae, public databases store a significant part of the accumulated information and, on the way to better understanding of the cellular processes, there is a need to integrate this information into a consistent reconstruction of the molecular interaction network.

Computational methods for estimation of cell cycle phase distributions of yeast cells.

Two computational methods for estimating the cell cycle phase distribution of a budding yeast (Saccharomyces cerevisiae) cell population are presented. The first one is a nonparametric method that is based on the analysis of DNA content in the individual cells of the population. The DNA content is measured with a fluorescence-activated cell sorter (FACS).

Critical networks exhibit maximal information diversity in structure-dynamics relationships.

Network structure strongly constrains the range of dynamic behaviors available to a complex system. These system dynamics can be classified based on their response to perturbations over time into two distinct regimes, ordered or chaotic, separated by a critical phase transition. Numerous studies have shown that the most complex dynamics arise near the critical regime.

RMBNToolbox: random models for biochemical networks.

Background: There is an increasing interest to model biochemical and cell biological networks, as well as to the computational analysis of these models. The development of analysis methodologies and related software is rapid in the field. However, the number of available models is still relatively small and the model sizes remain limited.

Simulation of microarray data with realistic characteristics.

Background: Microarray technologies have become common tools in biological research. As a result, a need for effective computational methods for data analysis has emerged. Numerous different algorithms have been proposed for analyzing the data.

Simulation tools for biochemical networks: evaluation of performance and usability.

Motivation: Simulation of dynamic biochemical systems is receiving considerable attention due to increasing availability of experimental data of complex cellular functions. Numerous simulation tools have been developed for numerical simulation of the behavior of a system described in mathematical form. However, there exist only a few evaluation studies of these tools.