Wavelet-based ULF wave diagnosis of substorm expansion phase onset

Using a discrete wavelet transform with a Meyer wavelet basis, we present a new quantitative algorithm for determining the onset time of Pi1 and Pi2 ULF waves in the nightside ionosphere with ∼20- to 40-s resolution at substorm expansion phase onset. We validate the algorithm by comparing both the ULF wave onset time and location to the optical onset determined by the Imager for Magnetopause-to-Aurora Global Exploration (IMAGE)–Far Ultraviolet Imager (FUV) instrument. In each of the six events analyzed, five substorm onsets and one pseudobreakup, the ULF onset is observed prior to the global optical onset observed by IMAGE at a station closely conjugate to the optical onset. The observed ULF onset times expand both latitudinally and longitudinally away from an epicenter of ULF wave power in the ionosphere. We further discuss the utility of the algorithm for diagnosing pseudobreakups and the relationship of the ULF onset epicenter to the meridians of elements of the substorm current wedge. The importance of the technique for establishing the causal sequence of events at substorm onset, especially in support of the multisatellite Time History of Events and Macroscale Interactions During Substorms (THEMIS) mission, is also described.

'Doctor, Doctor...' entrepreneurial diagnosis and market making

Doctor-patient jokes are universally popular because of the information asymmetries within the diagnostic relationship. We contend that entrepreneurial diagnosis is present in markets where consumers are unable to diagnose their own problems and, instead, may rely on the entrepreneur to diagnose them. Entrepreneurial diagnosis is a cognitive skill possessed by the entrepreneur. It is an identifiable subset of entrepreneurial judgment and can be modeled – which we attempt to do. In order to overcome the information asymmetries and exploit opportunities, we suggest that entrepreneurs must invest in market making innovations (as distinct from product innovations) such as trustworthy reputations. The diagnostic entrepreneur described in this paper represents a creative response to difficult diagnostic problems and helps to explain the success of many firms whose products are not particularly innovative but which are perceived as offering high standards of service. These firms are trusted not only for their truthfulness about the quality of their product, but for their honesty, confidentiality and understanding in helping customers identify the most appropriate product to their needs.

Abnormal functional activation and maturation of fronto-striato-temporal and cerebellar regions during sustained attention in autism spectrum disorder

Objective Sustained attention problems are common in people with autism spectrum disorder (ASD) and may have significant implications for the diagnosis and management of ASD and associated comorbidities. Furthermore, ASD has been associated with atypical structural brain development. The authors used functional MRI to investigate the functional brain maturation of attention between childhood and adulthood in people with ASD. Method Using a parametrically modulated sustained attention/vigilance task, the authors examined brain activation and its linear correlation with age between childhood and adulthood in 46 healthy male adolescents and adults (ages 11–35 years) with ASD and 44 age- and IQ-matched typically developing comparison subjects. Results Relative to the comparison group, the ASD group had significantly poorer task performance and significantly lower activation in inferior prefrontal cortical, medial prefrontal cortical, striato-thalamic, and lateral cerebellar regions. A conjunction analysis of this analysis with group differences in brain-age correlations showed that the comparison group, but not the ASD group, had significantly progressively increased activation with age in these regions between childhood and adulthood, suggesting abnormal functional brain maturation in ASD. Several regions that showed both abnormal activation and functional maturation were associated with poorer task performance and clinical measures of ASD and inattention. Conclusions The results provide first evidence that abnormalities in sustained attention networks in individuals with ASD are associated with underlying abnormalities in the functional brain maturation of these networks between late childhood and adulthood.

Cognitive-behavior therapy for low self-esteem: a case example

Low self-esteem is a common, disabling, and distressing problem that has been shown to be involved in the etiology and maintenance of range of Axis I disorders. Hence, it is a priority to develop effective treatments for low self-esteem. A cognitive-behavioral conceptualization of low self-esteem has been proposed and a cognitive-behavioral treatment (CBT) program described (Fennell, 1997, 1999). As yet there has been no systematic evaluation of this treatment with routine clinical populations. The current case report describes the assessment, formulation, and treatment of a patient with low self-esteem, depression, and anxiety symptoms. At the end of treatment (12 sessions over 6 months), and at 1-year follow-up, the treatment showed large effect sizes on measures of depression, anxiety, and self-esteem. The patient no longer met diagnostic criteria for any psychiatric disorder, and showed reliable and clinically significant change on all measures. As far as we are aware, there are no other published case studies of CBT for low self-esteem that report pre- and posttreatment evaluations, or follow-up data. Hence, this case provides an initial contribution to the evidence base for the efficacy of CBT for low self-esteem. However, further research is needed to confirm the efficacy of CBT for low self-esteem and to compare its efficacy and effectiveness to alternative treatments, including diagnosis-specific CBT protocols.

Towards the computer-aided diagnosis of dementia based on the geometric and network connectivity of structural MRI data

We present an intuitive geometric approach for analysing the structure and fragility of T1-weighted structural MRI scans of human brains. Apart from computing characteristics like the surface area and volume of regions of the brain that consist of highly active voxels, we also employ Network Theory in order to test how close these regions are to breaking apart. This analysis is used in an attempt to automatically classify subjects into three categories: Alzheimer’s disease, mild cognitive impairment and healthy controls, for the CADDementia Challenge.

Preoperative predictors for postoperative problems in heart transplantation: psychiatric and psychosocial considerations

The psychiatric and psychosocial evaluation of the heart transplant candidate can identify particular predictors for postoperative problems. These factors, as identified during the comprehensive evaluation phase, provide an assessment of the candidate in context of the proposed transplantation protocol. Previous issues with compliance, substance abuse, and psychosis are clear indictors of postoperative problems. The prolonged waiting list time provides an additional period to evaluate and provide support to patients having a terminal disease who need a heart transplant, and are undergoing prolonged hospitalization. Following transplantation, the patient is faced with additional challenges of a new self-image, multiple concerns, anxiety, and depression. Ultimately, the success of the heart transplantation remains dependent upon the recipient's ability to cope psychologically and comply with the medication regimen. The limited resource of donor hearts and the high emotional and financial cost of heart transplantation lead to an exhaustive effort to select those patients who will benefit from the improved physical health the heart transplant confers.

Standardized evaluation of algorithms for computer-aided diagnosis of dementia based on structural MRI: The CADDementia challenge

Algorithms for computer-aided diagnosis of dementia based on structural MRI have demonstrated high performance in the literature, but are difficult to compare as different data sets and methodology were used for evaluation. In addition, it is unclear how the algorithms would perform on previously unseen data, and thus, how they would perform in clinical practice when there is no real opportunity to adapt the algorithm to the data at hand. To address these comparability, generalizability and clinical applicability issues, we organized a grand challenge that aimed to objectively compare algorithms based on a clinically representative multi-center data set. Using clinical practice as the starting point, the goal was to reproduce the clinical diagnosis. Therefore, we evaluated algorithms for multi-class classification of three diagnostic groups: patients with probable Alzheimer's disease, patients with mild cognitive impairment and healthy controls. The diagnosis based on clinical criteria was used as reference standard, as it was the best available reference despite its known limitations. For evaluation, a previously unseen test set was used consisting of 354 T1-weighted MRI scans with the diagnoses blinded. Fifteen research teams participated with a total of 29 algorithms. The algorithms were trained on a small training set (n = 30) and optionally on data from other sources (e.g., the Alzheimer's Disease Neuroimaging Initiative, the Australian Imaging Biomarkers and Lifestyle flagship study of aging). The best performing algorithm yielded an accuracy of 63.0% and an area under the receiver-operating-characteristic curve (AUC) of 78.8%. In general, the best performances were achieved using feature extraction based on voxel-based morphometry or a combination of features that included volume, cortical thickness, shape and intensity. The challenge is open for new submissions via the web-based framework: http://caddementia.grand-challenge.org.

Towards pain-free diagnosis of skin diseases through multiplexed microneedles: biomarker extraction and detection using a highly sensitive blotting method

Immunodiagnostic microneedles provide a novel way to extract protein biomarkers from the skin in a minimally invasive manner for analysis in vitro. The technology could overcome challenges in biomarker analysis specifically in solid tissue, which currently often involves invasive biopsies. This study describes the development of a multiplex immunodiagnostic device incorporating mechanisms to detect multiple antigens simultaneously, as well as internal assay controls for result validation. A novel detection method is also proposed. It enables signal detection specifically at microneedle tips and therefore may aid the construction of depth profiles of skin biomarkers. The detection method can be coupled with computerised densitometry for signal quantitation. The antigen specificity, sensitivity and functional stability of the device were assessed against a number of model biomarkers. Detection and analysis of endogenous antigens (interleukins 1α and 6) from the skin using the device was demonstrated. The results were verified using conventional enzyme-linked immunosorbent assays. The detection limit of the microneedle device, at ≤10 pg/mL, was at least comparable to conventional plate-based solid-phase enzyme immunoassays.

The case of pre-natal diagnosis

This chapter reconsiders critiques of pre-natal diagnosis in Disability Studies. Underlying assumptions about reproductive technologies are analysed to demonstrate that while many critiques of pre-natal diagnosis by Disability activists and theorists are concerned about children being the product of 'choice' through the selective effects of pre-natal diagnosis, the issue that reproductive technologies (such as IVF) themselves necessarily always already rely on 'choice' -- namely the choice for a 'biological' or 'own' child (different terms are used) -- is nowhere considered. The chapter considers several consequences of thinking through this issue and its implications.

Endocannabinoid signaling in autism

Autism spectrum disorder (ASD) is a complex behavioral condition with onset during early childhood and a lifelong course in the vast majority of cases. To date, no behavioral, genetic, brain imaging, or electrophysiological test can specifically validate a clinical diagnosis of ASD. However, these medical procedures are often implemented in order to screen for syndromic forms of the disorder (i.e., autism comorbid with known medical conditions). In the last 25 years a good deal of information has been accumulated on the main components of the “endocannabinoid (eCB) system”, a rather complex ensemble of lipid signals (“endocannabinoids”), their target receptors, purported transporters, and metabolic enzymes. It has been clearly documented that eCB signaling plays a key role in many human health and disease conditions of the central nervous system, thus opening the avenue to the therapeutic exploitation of eCB-oriented drugs for the treatment of psychiatric, neurodegenerative, and neuroinflammatory disorders. Here we present a modern view of the eCB system, and alterations of its main components in human patients and animal models relevant to ASD. This review will thus provide a critical perspective necessary to explore the potential exploitation of distinct elements of eCB system as targets of innovative therapeutics against ASD.

The accuracy of HADS and GHQ-12 in detecting psychiatric morbidity in breast cancer patients

Objective: Psychological problems should be identified in breast cancer patients proactively if doctors and nurses are to help them cope with the challenges imposed by their illness. Screening is one possible way to identify emotional problems proactively. Self-report questionnaires can be useful alternatives to carrying out psychiatric interviews during screening, because interviewing a large number of patients can be impractical due to limited resources. Two such measures are the Hospital Anxiety and Depression Scale (HADS) and the General Health Questionnaire-12 (GHQ-12). Method: The present study aimed to compare the performance of the GHQ-12, and the HADS Unitary Scale and its subscales to that of the Schedule for Affective Disorders and Schizophrenia (SADS) in identifying patients with affective disorders, including DSM major depression and generalized anxiety disorder. The sample consisted of 296 female breast cancer patients who underwent surgery for breast cancer a year previously. Results: A small number of patients (11%) were identified as having DSM major depression or generalized anxiety disorder based on SADS score. The findings indicate that the optimal thresholds in detecting generalized anxiety disorder and DSM major depression with the HADS anxiety and depression subscales were ≥ 8 and ≥ 7, with 93.3% and 77.3% sensitivity, respectively, and 77.9% and 87.1% specificity, respectively. They also had a 21% and 36% positive predictive value, respectively. Using the HADS Unitary Scale the optimal threshold for detecting affective disorders was ≥ 12, with 88.9% sensitivity, 80.7% specificity, and a 35% positive predictive value. In detecting affective disorders, the optimal threshold on the GHQ-12 was ≥ 2, with 77.8% sensitivity and 70.2% specificity. This scale also had a 24% positive predictive value. In detecting generalized anxiety disorder and DSM major depression, the optimal thresholds on the GHQ-12 were ≥ 2 and ≥ 4 with 73.3% and 77.3% sensitivity, respectively, and 67.5% and 82% specificity, respectively. The scale also had 12% and 29% positive predictive values, respectively. Conclusion: The HADS Unitary Scale and its subscales were effective in identifying affective disorders. They can be used as screening measures in breast cancer patients. The GHQ-12 was less accurate in detecting affective disorders than the HADS, but it can also be used as a screening instrument to detect affective disorders, generalized anxiety disorder, and DSM major depression.

The perception of support received from breast care nurses by depressed patients following a diagnosis of breast cancer

INTRODUCTION Due to their specialist training, breast care nurses (BCNs) should be able to detect emotional distress and offer support to breast cancer patients. However, patients who are most distressed after diagnosis generally experience least support from care staff. To test whether BCNs overcome this potential barrier, we compared the support experienced by depressed and non-depressed patients from their BCNs and the other main professionals involved in their care: surgeons and ward nurses. PATIENTS AND METHODS Women with primary breast cancer (n = 355) 2–4 days after mastectomy or wide local excision, self-reported perceived professional support and current depression. Analysis of variance compared support ratings of depressed and non-depressed patients across staff types. RESULTS There was evidence of depression in 31 (9%) patients. Depressed patients recorded less surgeon and ward nurse support than those who were not depressed but the support received by patients from the BCN was high, whether or not patients were depressed. CONCLUSIONS BCNs were able to provide as much support to depressed patients as to non-depressed patients, whereas depressed patients felt less supported by surgeons and ward nurses than did non-depressed patients. Future research should examine the basis of BCNs' ability to overcome barriers to support in depressed patients. Our findings confirm the importance of maintaining the special role of the BCN.