Use of Bayesian MUNE to show differing rate of loss of motor units in subgroups of ALS

Objectives To evaluate differences among patients with different clinical features of ALS, we used our Bayesian method of motor unit number estimation (MUNE). Methods We performed serial MUNE studies on 42 subjects who fulfilled the diagnostic criteria for ALS during the course of their illness. Subjects were classified into three subgroups according to whether they had typical ALS (with upper and lower motor neurone signs) or had predominantly upper motor neurone weakness with only minor LMN signs, or predominantly lower motor neurone weakness with only minor UMN signs. In all subjects we calculated the half life of MUs, defined as the expected time for the number of MUs to halve, in one or more of the abductor digiti minimi (ADM), abductor pollicis brevis (APB) and extensor digitorum brevis (EDB) muscles. Results The mean half life of MUs was less in subjects who had typical ALS with both upper and lower motor neurone signs than in those with predominantly upper motor neurone weakness or predominantly lower motor neurone weakness. In 18 subjects we analysed the estimated size of the MUs and demonstrated the appearance of large MUs in subjects with upper or lower motor neurone predominant weakness. We found that the appearance of large MUs was correlated with the half life of MUs. Conclusions Patients with different clinical features of ALS have different rates of loss and different sizes of MUs. Significance: These findings could indicate differences in disease pathogenesis.

Latent class analysis reveals distinct subgroups of patients based on symptom occurrence and demographic and clinical characteristics

Context Cancer patients experience a broad range of physical and psychological symptoms as a result of their disease and its treatment. On average, these patients report ten unrelieved and co-occurring symptoms. Objectives To determine if subgroups of oncology outpatients receiving active treatment (n=582) could be identified based on their distinct experience with thirteen commonly occurring symptoms; to determine whether these subgroups differed on select demographic, and clinical characteristics; and to determine if these subgroups differed on quality of life (QOL) outcomes. Methods Demographic, clinical, and symptom data from one Australian and two U.S. studies were combined. Latent class analysis (LCA) was used to identify patient subgroups with distinct symptom experiences based on self-report data on symptom occurrence using the Memorial Symptom Assessment Scale (MSAS). Results Four distinct latent classes were identified (i.e., All Low (28.0%), Moderate Physical and Lower Psych (26.3%), Moderate Physical and Higher Psych (25.4%), All High (20.3%)). Age, gender, education, cancer diagnosis, and presence of metastatic disease differentiated among the latent classes. Patients in the All High class had the worst QOL scores. Conclusion Findings from this study confirm the large amount of interindividual variability in the symptom experience of oncology patients. The identification of demographic and clinical characteristics that place patients are risk for a higher symptom burden can be used to guide more aggressive and individualized symptom management interventions.

Nucleocapsid gene variability reveals two subgroups of Lettuce necrotic yellows virus

The complete nucleocapsid (N) genes of eight Australian isolates of Lettuce necrotic yellows virus (LNYV) were amplified by reverse transcription PCR, cloned and sequenced. Phylogenetic analyses of these sequences revealed two distinct subgroups of LNYV isolates. Nucleotide sequences within each subgroup were more than 96% identical but heterogeneity between groups was about 20% at the nucleotide sequence level. However, less than 4% heterogeneity was noted at the amino acid level, indicating mostly third nucleotide position changes and a strong conservation for N protein function. There was no obvious geographical or temporal separation of the subgroups in Australia.

Concordance of genetic risk across migraine subgroups: Impact on current and future genetic association studies

BACKGROUND There has been intensive debate whether migraine with aura (MA) and migraine without aura (MO) should be considered distinct subtypes or part of the same disease spectrum. There is also discussion to what extent migraine cases collected in specialised headache clinics differ from cases from population cohorts, and how female cases differ from male cases with respect to their migraine. To assess the genetic overlap between these migraine subgroups, we examined genome-wide association (GWA) results from analysis of 23,285 migraine cases and 95,425 population-matched controls. METHODS Detailed heterogeneity analysis of single-nucleotide polymorphism (SNP) effects (odds ratios) between migraine subgroups was performed for the 12 independent SNP loci significantly associated (p < 5 x 10(-8); thus surpassing the threshold for genome-wide significance) with migraine susceptibility. Overall genetic overlap was assessed using SNP effect concordance analysis (SECA) at over 23,000 independent SNPs. RESULTS: Significant heterogeneity of SNP effects (p het < 1.4 x 10(-3)) was observed between the MA and MO subgroups (for SNP rs9349379), and between the clinic- and population-based subgroups (for SNPs rs10915437, rs6790925 and rs6478241). However, for all 12 SNPs the risk-increasing allele was the same, and SECA found the majority of genome-wide SNP effects to be in the same direction across the subgroups. CONCLUSIONS Any differences in common genetic risk across these subgroups are outweighed by the similarities. Meta-analysis of additional migraine GWA datasets, regardless of their major subgroup composition, will identify new susceptibility loci for migraine.

On an embedding property of generalized Carter subgroups

If E and F are saturated formations, we say that E is strongly contained in F if for any solvable group G with E-subgroup, E, and F-subgroup, F, some conjugate of E is contained in F. In this paper, we investigate the problem of finding the formations which strongly contain a fixed saturated formation E.

Our main results are restricted to formations, E, such that E = {G|G/F(G) ϵT}, where T is a non-empty formation of solvable groups, and F(G) is the Fitting subgroup of G. If T consists only of the identity, then E=N, the class of nilpotent groups, and for any solvable group, G, the N-subgroups of G are the Carter subgroups of G.

We give a characterization of strong containment which depends only on the formations E, and F. From this characterization, we prove:

If T is a non-empty formation of solvable groups, E = {G|G/F(G) ϵT}, and E is strongly contained in F, then

(1) there is a formation V such that F = {G|G/F(G) ϵV}.

(2) If for each prime p, we assume that T does not contain the class, S_p’, of all solvable p’-groups, then either E = F, or F contains all solvable groups.

This solves the problem for the Carter subgroups.

We prove the following result to show that the hypothesis of (2) is not redundant:

If R = {G|G/F(G) ϵS_r’}, then there are infinitely many formations which strongly contain R.

Estimating the magnitude of trastuzumab effects within patient subgroups in the HERA trial.

BACKGROUND: Trastuzumab (Herceptin(R)) improves disease-free survival (DFS) and overall survival for patients with human epidermal growth factor receptor 2 (HER2)-positive early breast cancer. We aimed to assess the magnitude of its clinical benefit for subpopulations defined by nodal and steroid hormone receptor status using data from the Herceptin Adjuvant (HERA) study. PATIENTS AND METHODS: HERA is an international multicenter randomized trial comparing 1 or 2 years of trastuzumab treatment with observation after standard chemotherapy in women with HER2-positive breast cancer. In total, 1703 women randomized to 1-year trastuzumab and 1698 women randomized to observation were included in these analyses. Median follow-up was 23.5 months. The primary endpoint was DFS. RESULTS: The overall hazard ratio (HR) for trastuzumab versus observation was 0.64 [95% confidence interval (CI) 0.54-0.76; P < 0.0001], ranging from 0.46 to 0.82 for subgroups. Estimated improvement in 3-year DFS in subgroups ranged from +11.3% to +0.6%. Patients with the best prognosis (those with node-negative disease and tumors 1.1-2.0 cm) had benefit similar to the overall cohort (HR 0.53, 95% CI 0.26-1.07; 3-year DFS improvement +4.6%, 95% CI -4.0% to 13.2%). CONCLUSIONS: Adjuvant trastuzumab therapy reduces the risk of relapse similarly across subgroups defined by nodal status and steroid hormone receptor status, even those at relatively low risk for relapse.

On maximal subgroups of the multiplicative group of a division algebra

This note studies the question whether a multiplicative group of a division ring has a maximal subgroup. It is published in J. Algebra. This is a reputable journal in the subject algebra. Most of submitted papers from 5* schools in RAE was in this journal.

Microarray-based classifiers and prognosis models identify subgroups with distinct clinical outcomes and high risk of AML transformation of myelodysplastic syndrome

The diagnosis of myelodysplastic syndrome (MDS) currently relies primarily on the morphologic assessment of the patient's bone marrow and peripheral blood cells. Moreover, prognostic scoring systems rely on observer-dependent assessments of blast percentage and dysplasia. Gene expression profiling could enhance current diagnostic and prognostic systems by providing a set of standardized, objective gene signatures. Within the Microarray Innovations in LEukemia study, a diagnostic classification model was investigated to distinguish the distinct subclasses of pediatric and adult leukemia, as well as MDS. Overall, the accuracy of the diagnostic classification model for subtyping leukemia was approximately 93%, but this was not reflected for the MDS samples giving only approximately 50% accuracy. Discordant samples of MDS were classified either into acute myeloid leukemia (AML) or

Synovial membrane immunohistology in early untreated juvenile idiopathic arthritis: differences between clinical subgroups

Abstract: Objective Juvenile idiopathic arthritis (JIA) consists of a heterogeneous group of inflammatory disorders, within which there are a number of clinical subgroups. Diagnosis and assignment to a particular subgroup can be problematical and more concise methods of subgroup classification are required. This study of the synovial membrane characterises the immunohistochemical features in early untreated, newly diagnosed JIA and compares findings with disease subgroup at 2 years.

Methods: 42 patients with newly diagnosed untreated JIA underwent synovial biopsy before the administration of steroids or disease-modifying antirheumatic drugs. Patients were classified as either polyarticular, persistent oligoarticular or extended-to-be oligoarticular. The location and semiquantitative analysis of T-cell subsets, B cells, macrophages and blood vessels were determined using immunohistochemistry.

Results: Synovial hyperplasia varied significantly between the three groups
(p<0.0001). There was a significant difference in the CD3 T-cell population between the three groups (p=0.004) and between the extended-to-be and persistent group (p=0.032). CD4 expression was significantly higher in the poly and extended-to-be oligo groups (p=0.002), again the extended-to-be group had more CD4 T cells than the persistent group (p=0.008). B-cell infiltrates were more marked in the polyarticular group and were significantly higher in the extended-to-be group compared with the persistent group (p=0.005). Vascularisation was more pronounced in the polyarticular and extended-to-be oligoarticular groups, the extended-to-be group had significantly more vascularisation than the persistent group (p=0.0002).

Conclusions: There are significant differences in the histomorphometric features of synovial tissue between patient subgroups. Immunohistological examination of synovial membrane biopsies may provide further insight into early disease processes in JIA.