Building social capital through breastfeeding peer support: Insights from an evaluation of a voluntary breastfeeding peer support service in North-West England

Background: Peer support is reported to be a key method to help build social capital in communities. To date there are no studies that describe how this can be achieved through a breastfeeding peer support service. In this paper we present findings from an evaluation of a voluntary model of breastfeeding peer support in North-West England to describe how the service was operationalized and embedded into the community. This study was undertaken from May, 2012 to May, 2013. Methods: Interviews (group or individual) were held with 87 participants: 24 breastfeeding women, 13 peer supporters and 50 health and community professionals. The data contained within 23 monthly monitoring reports (January, 2011 to February 2013) compiled by the voluntary peer support service were also extracted and analysed. Results: Thematic analysis was undertaken using social capital concepts as a theoretical lens. Key findings were identified to resonate with ’bonding’, ‘bridging’ and ‘linking’ forms of social capital. These insights illuminate how the peer support service facilitates ‘bonds’ with its members, and within and between women who access the service; how the service ‘bridges’ with individuals from different interests and backgrounds, and how ‘links’ were forged with those in authority to gain access and reach to women and to promote a breastfeeding culture. Some of the tensions highlighted within the social capital literature were also identified. Conclusions: Horizontal and vertical relationships forged between the peer support service and community members enabled peer support to be embedded into care pathways, helped to promote positive attitudes to breastfeeding and to disseminate knowledge and maximise reach for breastfeeding support across the community. Further effort to engage with those of different ethnic backgrounds and to resolve tensions between peer supporters and health professionals is warranted

Genome-wide linkage analysis of 972 bipolar pedigrees using single-nucleotide polymorphisms.

Because of the high costs associated with ascertainment of families, most linkage studies of Bipolar I disorder (BPI) have used relatively small samples. Moreover, the genetic information content reported in most studies has been less than 0.6. Although microsatellite markers spaced every 10 cM typically extract most of the genetic information content for larger multiplex families, they can be less informative for smaller pedigrees especially for affected sib pair kindreds. For these reasons we collaborated to pool family resources and carried out higher density genotyping. Approximately 1100 pedigrees of European ancestry were initially selected for study and were genotyped by the Center for Inherited Disease Research using the Illumina Linkage Panel 12 set of 6090 single-nucleotide polymorphisms. Of the ~1100 families, 972 were informative for further analyses, and mean information content was 0.86 after pruning for linkage disequilibrium. The 972 kindreds include 2284 cases of BPI disorder, 498 individuals with bipolar II disorder (BPII) and 702 subjects with recurrent major depression. Three affection status models (ASMs) were considered: ASM1 (BPI and schizoaffective disorder, BP cases (SABP) only), ASM2 (ASM1 cases plus BPII) and ASM3 (ASM2 cases plus recurrent major depression). Both parametric and non-parametric linkage methods were carried out. The strongest findings occurred at 6q21 (non-parametric pairs LOD 3.4 for rs1046943 at 119 cM) and 9q21 (non-parametric pairs logarithm of odds (LOD) 3.4 for rs722642 at 78 cM) using only BPI and schizoaffective (SA), BP cases. Both results met genome-wide significant criteria, although neither was significant after correction for multiple analyses. We also inspected parametric scores for the larger multiplex families to identify possible rare susceptibility loci. In this analysis, we observed 59 parametric LODs of 2 or greater, many of which are likely to be close to maximum possible scores. Although some linkage findings may be false positives, the results could help prioritize the search for rare variants using whole exome or genome sequencing

The development of radioactive sample surrogates for training and exercises

The development of radioactive sample surrogates for training and exercises Source term information is required for to reconstruct a device used in a dispersed radiological dispersal device. Simulating a radioactive environment to train and exercise sampling and sample characterization methods with suitable sample materials is a continued challenge. The Idaho National Laboratory has developed and permitted a Radioactive Response Training Range (RRTR), an 800 acre test range that is approved for open air dispersal of activated KBr, for training first responders in the entry and exit from radioactively contaminated areas, and testing protocols for environmental sampling and field characterization. Members from the Department of Defense, Law Enforcement, and the Department of Energy participated in the first contamination exercise that was conducted at the RRTR in the July 2011. The range was contaminated using a short lived radioactive Br-82 isotope (activated KBr). Soil samples contaminated with KBr (dispersed as a solution) and glass particles containing activated potassium bromide that emulated dispersed radioactive materials (such as ceramic-based sealed source materials) were collected to assess environmental sampling and characterization techniques. This presentation summarizes the performance of a radioactive materials surrogate for use as a training aide for nuclear forensics

Metastatic breast carcinoma mimicking a sebaceous gland neoplasm: a case report

<p>Abstract</p> <p>Introduction</p> <p>Breast cancer is common in women and its metastases involve the skin in approximately one quarter of patients. Accordingly, metastatic breast cancer shown to be cutaneous through histology must be distinguished from a wide variety of other neoplasms as well as the diverse morphologic variants of breast cancer itself.</p> <p>Case presentation</p> <p>We report the case of a 61-year-old Caucasian woman with cutaneous metastases of a bilateral ductal breast carcinoma that in histopathological examination mimicked an adnexal neoplasm with sebaceous differentiation.</p> <p>Conclusion</p> <p>Against the background of metastatic breast carcinoma, dermatopathological considerations of sebaceous differentiation of skin lesions are presented and discussed focusing on the rare differential diagnosis of sebaceous carcinoma of the breast.</p

A RAC/CDC-42–Independent GIT/PIX/PAK Signaling Pathway Mediates Cell Migration in C. elegans

P21 activated kinase (PAK), PAK interacting exchange factor (PIX), and G protein coupled receptor kinase interactor (GIT) compose a highly conserved signaling module controlling cell migrations, immune system signaling, and the formation of the mammalian nervous system. Traditionally, this signaling module is thought to facilitate the function of RAC and CDC-42 GTPases by allowing for the recruitment of a GTPase effector (PAK), a GTPase activator (PIX), and a scaffolding protein (GIT) as a regulated signaling unit to specific subcellular locations. Instead, we report here that this signaling module functions independently of RAC/CDC-42 GTPases in vivo to control the cell shape and migration of the distal tip cells (DTCs) during morphogenesis of the Caenorhabditis elegans gonad. In addition, this RAC/CDC-42–independent PAK pathway functions in parallel to a classical GTPase/PAK pathway to control the guidance aspect of DTC migration. Among the C. elegans PAKs, only PAK-1 functions in the GIT/PIX/PAK pathway independently of RAC/CDC42 GTPases, while both PAK-1 and MAX-2 are redundantly utilized in the GTPase/PAK pathway. Both RAC/CDC42–dependent and –independent PAK pathways function with the integrin receptors, suggesting that signaling through integrins can control the morphology, movement, and guidance of DTC through discrete pathways. Collectively, our results define a new signaling capacity for the GIT/PIX/PAK module that is likely to be conserved in vertebrates and demonstrate that PAK family members, which are redundantly utilized as GTPase effectors, can act non-redundantly in pathways independent of these GTPases

Is Ankyrin a genetic risk factor for psychiatric phenotypes?

Background Genome wide association studies reported two single nucleotide polymorphisms in ANK3 (rs9804190 and rs10994336) as independent genetic risk factors for bipolar disorder. Another SNP in ANK3 (rs10761482) was associated with schizophrenia in a large European sample. Within the debate on common susceptibility genes for schizophrenia and bipolar disorder, we tried to investigate common findings by analyzing association of ANK3 with schizophrenia, bipolar disorder and unipolar depression. Methods We genotyped three single nucleotide polymorphisms (SNPs) in ANK3 (rs9804190, rs10994336, and rs10761482) in a case-control sample of German descent including 920 patients with schizophrenia, 400 with bipolar affective disorder, 220 patients with unipolar depression according to ICD 10 and 480 healthy controls. Sample was further differentiated according to Leonhard's classification featuring disease entities with specific combination of bipolar and psychotic syndromes. Results We found no association of rs9804190 and rs10994336 with bipolar disorder, unipolar depression or schizophrenia. In contrast to previous findings rs10761482 was associated with bipolar disorder (p = 0.015) but not with schizophrenia or unipolar depression. We observed no association with disease entities according to Leonhard's classification. Conclusion Our results support a specific genetic contribution of ANK3 to bipolar disorder though we failed to replicate findings for schizophrenia. We cannot confirm ANK3 as a common risk factor for different diseases

Polarised Quark Distributions in the Nucleon from Semi-Inclusive Spin Asymmetries

We present a measurement of semi-inclusive spin asymmetries for positively and negatively charged hadrons from deep inelastic scattering of polarised muons on polarised protons and deuterons in the range $0.003$1 GeV$^2$. Compared to our previous publication on this subject, with the new data the statistical errors have been reduced by nearly a factor of two. From these asymmetries and our inclusive spin asymmetries we determine the polarised quark distributions of valence quarks and non-strange sea quarks at $Q^2$=10 GeV$^2$. The polarised $u$ valence quark distribution, $\Delta u_v(x)$, is positive and the polarisation increases with $x$. The polarised $d$ valence quark distribution, $\Delta d_v(x)$, is negative and the non-strange sea distribution, $\Delta \bar q(x)$, is consistent with zero over the measured range of $x$. We find for the first moments $\int_0^1 \Delta u_v(x) dx = 0.77 \pm 0.10 \pm 0.08$, $\int_0^1 \Delta d_v(x) dx = -0.52 \pm 0.14 \pm 0.09$ and $\int_0^1 \Delta \bar q(x) dx= 0.01 \pm 0.04 \pm 0.03$, where we assumed $\Delta \bar u(x) = \Delta \bar d(x)$. We also determine for the first time the second moments of the valence distributions $\int_0^1 x \Delta q_v(x) dx$.Comment: 17 page

Numerical Modelling Of The V-J Combinations Of The T Cell Receptor TRA/TRD Locus

T-Cell antigen Receptor (TR) repertoire is generated through rearrangements of V and J genes encoding α and β chains. The quantification and frequency for every V-J combination during ontogeny and development of the immune system remain to be precisely established. We have addressed this issue by building a model able to account for Vα-Jα gene rearrangements during thymus development of mice. So we developed a numerical model on the whole TRA/TRD locus, based on experimental data, to estimate how Vα and Jα genes become accessible to rearrangements. The progressive opening of the locus to V-J gene recombinations is modeled through windows of accessibility of different sizes and with different speeds of progression. Furthermore, the possibility of successive secondary V-J rearrangements was included in the modelling. The model points out some unbalanced V-J associations resulting from a preferential access to gene rearrangements and from a non-uniform partition of the accessibility of the J genes, depending on their location in the locus. The model shows that 3 to 4 successive rearrangements are sufficient to explain the use of all the V and J genes of the locus. Finally, the model provides information on both the kinetics of rearrangements and frequencies of each V-J associations. The model accounts for the essential features of the observed rearrangements on the TRA/TRD locus and may provide a reference for the repertoire of the V-J combinatorial diversity

Evolvable Neuronal Paths: A Novel Basis for Information and Search in the Brain

We propose a previously unrecognized kind of informational entity in the brain that is capable of acting as the basis for unlimited hereditary variation in neuronal networks. This unit is a path of activity through a network of neurons, analogous to a path taken through a hidden Markov model. To prove in principle the capabilities of this new kind of informational substrate, we show how a population of paths can be used as the hereditary material for a neuronally implemented genetic algorithm, (the swiss-army knife of black-box optimization techniques) which we have proposed elsewhere could operate at somatic timescales in the brain. We compare this to the same genetic algorithm that uses a standard ‘genetic’ informational substrate, i.e. non-overlapping discrete genotypes, on a range of optimization problems. A path evolution algorithm (PEA) is defined as any algorithm that implements natural selection of paths in a network substrate. A PEA is a previously unrecognized type of natural selection that is well suited for implementation by biological neuronal networks with structural plasticity. The important similarities and differences between a standard genetic algorithm and a PEA are considered. Whilst most experiments are conducted on an abstract network model, at the conclusion of the paper a slightly more realistic neuronal implementation of a PEA is outlined based on Izhikevich spiking neurons. Finally, experimental predictions are made for the identification of such informational paths in the brain