Tubal damage, infertility and tubal ectopic pregnancy : chlamydia trachomatis and other microbial aetiologies

Infertility is a worldwide health problem with one in six couples suffering from this condition and with a major economic burden on the global healthcare industry. Estimates of the current global infertility rate suggest that 15% of couples are infertile (Zegers-Hochschild et al 2009) defined as: (1) failure to conceive after 12 months of unprotected sexual intercourse (i.e. infertility); (2) repeated implantation failure following ART cycles; or (3) recurrent miscarriage without difficulty conceiving (natural conceptions). Tubal factor infertility is among the leading causes of female factor infertility accounting for 7-9.8% of all female factor infertilities. Tubal disease directly causes from 36% to 85% of all cases of female factor infertility in developed and developing nations respectively and is associated with polymicrobial aetiologies. One of the leading global causes of tubal factor infertility is thought to be symptomatic (and asymptomatic in up to 70% cases) infection of the female reproductive tract with the sexually transmitted pathogen, Chlamydia trachomatis. Infection-related damage to the Fallopian tubes caused by Chlamydia accounts for more than 70% of cases of infertility in women from developing nations such as sub-Saharan Africa (Sharma et al 2009). Bacterial vaginosis, a condition associated with increased transmission of sexually transmitted infections including those caused by Neisseria gonorrhoeae and Mycoplasma genitalium is present in two thirds of women with pelvic inflammatory disease (PID). This review will focus on (1) the polymicrobial aetiologies of tubal factor infertility and (2) studies involved in screening for, and treatment and control of, Chlamydial infection to prevent PID and the associated sequelae of Fallopian tube inflammation that may lead to infertility and ectopic pregnancy.

Learning from episodes of degradation and recovery in variable Australian rangelands

Land-change science emphasizes the intimate linkages between the human and environmental components of land management systems. Recent theoretical developments in drylands identify a small set of key principles that can guide the understanding of these linkages. Using these principles, a detailed study of seven major degradation episodes over the past century in Australian grazed rangelands was reanalyzed to show a common set of events: (i) good climatic and economic conditions for a period, leading to local and regional social responses of increasing stocking rates, setting the preconditions for rapid environmental collapse, followed by (ii) a major drought coupled with a fall in the market making destocking financially unattractive, further exacerbating the pressure on the environment; then (iii) permanent or temporary declines in grazing productivity, depending on follow-up seasons coupled again with market and social conditions. The analysis supports recent theoretical developments but shows that the establishment of environmental knowledge that is strictly local may be insufficient on its own for sustainable management. Learning systems based in a wider community are needed that combine local knowledge, formal research, and institutional support. It also illustrates how natural variability in the state of both ecological and social systems can interact to precipitate nonequilibrial change in each other, so that planning cannot be based only on average conditions. Indeed, it is this variability in both environment and social subsystems that hinders the local learning required to prevent collapse.

Frequency response function based structural damage detection using artificial neural networks

Damage detection in structures has become increasingly important in recent years. While a number of damage detection and localization methods have been proposed, few attempts have been made to explore the structure damage with frequency response functions (FRFs). This paper illustrates the damage identification and condition assessment of a beam structure using a new frequency response functions (FRFs) based damage index and Artificial Neural Networks (ANNs). In practice, usage of all available FRF data as an input to artificial neural networks makes the training and convergence impossible. Therefore one of the data reduction techniques Principal Component Analysis (PCA) is introduced in the algorithm. In the proposed procedure, a large set of FRFs are divided into sub-sets in order to find the damage indices for different frequency points of different damage scenarios. The basic idea of this method is to establish features of damaged structure using FRFs from different measurement points of different sub-sets of intact structure. Then using these features, damage indices of different damage cases of the structure are identified after reconstructing of available FRF data using PCA. The obtained damage indices corresponding to different damage locations and severities are introduced as input variable to developed artificial neural networks. Finally, the effectiveness of the proposed method is illustrated and validated by using the finite element modal of a beam structure. The illustrated results show that the PCA based damage index is suitable and effective for structural damage detection and condition assessment of building structures.

Subjective and Objective Indicators of Recovery in Severe Mental Illness: a Cross-Sectional Study

Background: This study aimed to determine whether subjective dimensions of recovery such as empowerment are associated with self-report of more objective indicators such as level of participation in the community and income from employment. A secondary aim was to investigate the extent to which diagnosis or other consumer characteristics mediated any relationship between these variables. Methods: The Community Integration Measure, the Empowerment Scale, the Recovery Assessment Scale, and the Camberwell Assessment of Needs Short Appraisal Schedule were administered to a convenience sample of 161 consumers with severe mental illness. Results: The majority of participants had a primary diagnosis of schizophreniform, anxiety/depression or bipolar affective disorder. The Empowerment Scale was quite strongly correlated with the Recovery Assessment Scale and the Community Integration Measure. Participants with a diagnosis of bipolar affective disorder had signifi cantly higher recovery and empowerment scores than participants with schizophrenia or depression. Both empowerment and recovery scores were significantly higher for people engaged in paid employment than for those receiving social security benefits. Conclusions: The measurement of subjective dimensions of recovery such as empowerment has validity in evaluation of global recovery for people with severe mental illness. A diagnosis of bipolar disorder is associated with higher scores on subjective and objective indicators of recovery.

Recovery-based practice: do we know what we mean or mean what we know?

The concept of recovery is now widely promoted as the guiding principle for the provision of mental health services in Australia and overseas. While there is increasing pressure on service providers to ensure that services are recovery oriented, the way in which recovery-based practice is operationalized at the coalface presents a number of challenges. These are discussed in the context of five key questions that address (i) the appropriateness of recovery as a focus for service delivery, (ii) the distinction between recovery as a process and an outcome, (iii) the assessment of recovery initiatives, (iv) the alignment of recovery with current service delivery models, and (v) the risks associated with recovery-based practice. It is argued that these questions provide a framework for a debate that must extend beyond patients and providers of mental health services to the broader public, whose attitudes will ultimately determine the possibilities and limits of recovery-oriented practice.