Psychosocial adjustment in newly diagnosed prostate cancer

Objective: To examine the psychological and social adjustment of men with early or advanced stage prostate cancer and to compare them with a matched group of cancer-free community volunteers. Methods: A longitudinal observational study in which 367 men recently diagnosed with early (n =211) or advanced stage (n = 156), prostate cancer were compared to 169 cancer-free men from the community, of similar age and residential area, using self-report measures of psychosocial adjustment. Results: On the mental health subscales of the Short-Form 36-item Health Survey, men with advanced disease had lower vitality and social functioning than the other two groups, and lower mental health scores than the comparison group. Both patient groups had lower role-emotional scores than the comparison group. With regard to the Brief Symptom Inventory, the advanced disease group had higher somatization scores, and lower interpersonal sensitivity and paranoid ideation scores than the early stage group and the community comparison group. In terms of psychiatric morbidity, there were higher rates of anxiety disorders but not depressive disorders in both patient groups although overall diagnosis rates were low. No differences were found in terms of couple or family functioning. Conclusions: There is impairment in psychosocial function in men with prostate cancer, particularly those with advanced disease, but no increase in the rate of formal psychiatric disorder or adverse effects on the couples and families. This suggests directions for psychosocial interventions with these patient group

Polariton Condensation and Lasing

The similarities and differences between polariton condensation in microcavities and standard lasing in a semiconductor cavity structure are reviewed. The recent experiments on "photon condensation" are also reviewed.Comment: 23 pages, 6 figures; Based on the book chapter in Exciton Polaritons in Microcavities, (Springer Series in Solid State Sciences vol. 172), V. Timofeev and D. Sanvitto, eds., (Springer, 2012

Exponentially more precise quantum simulation of fermions in the configuration interaction representation

We present a quantum algorithm for the simulation of molecular systems that is asymptotically more efficient than all previous algorithms in the literature in terms of the main problem parameters. As in Babbush et al (2016 New Journal of Physics 18, 033032), we employ a recently developed technique for simulating Hamiltonian evolution using a truncated Taylor series to obtain logarithmic scaling with the inverse of the desired precision. The algorithm of this paper involves simulation under an oracle for the sparse, first-quantized representation of the molecular Hamiltonian known as the configuration interaction (CI) matrix. We construct and query the CI matrix oracle to allow for on-the-fly computation of molecular integrals in a way that is exponentially more efficient than classical numerical methods. Whereas second-quantized representations of the wavefunction require qubits, where N is the number of single-particle spin-orbitals, the CI matrix representation requires qubits, where is the number of electrons in the molecule of interest. We show that the gate count of our algorithm scales at most as

Key reaction components affect the kinetics and performance robustness of cell-free protein synthesis reactions

This is the final version. Available on open access from Elsevier via the DOI in this recordData statement: All data are available both in Source Data files associated with this publication, and at https://doi.org/10.25405/data.ncl.17041931Cell-free protein synthesis (CFPS) reactions have grown in popularity with particular interest in applications such as gene construct prototyping, biosensor technologies and the production of proteins with novel chemistry. Work has frequently focussed on optimising CFPS protocols for improving protein yield, reducing cost, or developing streamlined production protocols. Here we describe a statistical Design of Experiments analysis of 20 components of a popular CFPS reaction buffer. We simultaneously identify factors and factor interactions that impact on protein yield, rate of reaction, lag time and reaction longevity. This systematic experimental approach enables the creation of a statistical model capturing multiple behaviours of CFPS reactions in response to components and their interactions. We show that a novel reaction buffer outperforms the reference reaction by 400% and importantly reduces failures in CFPS across batches of cell lysates, strains of E. coli, and in the synthesis of different proteins. Detailed and quantitative understanding of how reaction components affect kinetic responses and robustness is imperative for future deployment of cell-free technologies.Engineering and Physical Sciences Research Council (EPSRC

CRISPR-Cas9 screens in human cells and primary neurons identify modifiers of C9ORF72 dipeptide-repeat-protein toxicity.

Hexanucleotide-repeat expansions in the C9ORF72 gene are the most common cause of amyotrophic lateral sclerosis and frontotemporal dementia (c9ALS/FTD). The nucleotide-repeat expansions are translated into dipeptide-repeat (DPR) proteins, which are aggregation prone and may contribute to neurodegeneration. We used the CRISPR-Cas9 system to perform genome-wide gene-knockout screens for suppressors and enhancers of C9ORF72 DPR toxicity in human cells. We validated hits by performing secondary CRISPR-Cas9 screens in primary mouse neurons. We uncovered potent modifiers of DPR toxicity whose gene products function in nucleocytoplasmic transport, the endoplasmic reticulum (ER), proteasome, RNA-processing pathways, and chromatin modification. One modifier, TMX2, modulated the ER-stress signature elicited by C9ORF72 DPRs in neurons and improved survival of human induced motor neurons from patients with C9ORF72 ALS. Together, our results demonstrate the promise of CRISPR-Cas9 screens in defining mechanisms of neurodegenerative diseases

MAGE-A cancer/testis antigens inhibit MDM2 ubiquitylation function and promote increased levels of MDM4

Melanoma antigen A (MAGE-A) proteins comprise a structurally and biochemically similar sub-family of Cancer/Testis antigens that are expressed in many cancer types and are thought to contribute actively to malignancy. MAGE-A proteins are established regulators of certain cancer-associated transcription factors, including p53, and are activators of several RING finger-dependent ubiquitin E3 ligases. Here, we show that MAGE-A2 associates with MDM2, a ubiquitin E3 ligase that mediates ubiquitylation of more than 20 substrates including mainly p53, MDM2 itself, and MDM4, a potent p53 inhibitor and MDM2 partner that is structurally related to MDM2. We find that MAGE-A2 interacts with MDM2 via the N-terminal p53-binding pocket and the RING finger domain of MDM2 that is required for homo/hetero-dimerization and for E2 ligase interaction. Consistent with these data, we show that MAGE-A2 is a potent inhibitor of the E3 ubiquitin ligase activity of MDM2, yet it does not have any significant effect on p53 turnover mediated by MDM2. Strikingly, however, increased MAGE-A2 expression leads to reduced ubiquitylation and increased levels of MDM4. Similarly, silencing of endogenous MAGE-A expression diminishes MDM4 levels in a manner that can be rescued by the proteasomal inhibitor, bortezomid, and permits increased MDM2/MDM4 association. These data suggest that MAGE-A proteins can: (i) uncouple the ubiquitin ligase and degradation functions of MDM2; (ii) act as potent inhibitors of E3 ligase function; and (iii) regulate the turnover of MDM4. We also find an association between the presence of MAGE-A and increased MDM4 levels in primary breast cancer, suggesting that MAGE-A-dependent control of MDM4 levels has relevance to cancer clinically

Determinants of a healthy lifestyle and use of preventive screening in Canada

BACKGROUND: This study explores the associations between individual characteristics such as income and education with health behaviours and utilization of preventive screening. METHODS: Data from the Canadian National Population Health Survey (NPHS) 1998–9 were used. Independent variables were income, education, age, sex, marital status, body mass index, urban/rural residence and access to a regular physician. Dependent variables included smoking, excessive alcohol use, physical activity, blood pressure checks, mammography in past year and Pap smear in past 3 years. Logistic regression models were developed for each dependent variable. RESULTS: 13,756 persons 20 years of age and older completed the health portion of the NPHS. In general, higher levels of income were associated with healthier behaviours, as were higher levels of education, although there were exceptions to both. The results for age and gender also varied depending on the outcome. The presence of a regular medical doctor was associated with increased rates of all preventive screening and reduced rates of smoking. CONCLUSION: These results expand upon previous data suggesting that socioeconomic disparities in healthy behaviours and health promotion continue to exist despite equal access to medical screening within the Canadian healthcare context. Knowledge, resources and the presence of a regular medical doctor are important factors associated with identified differences

Survival Analysis Part I: Basic concepts and first analyses

Survival analysis is a collection of statistical procedures for data analysis where the outcome variable of interest is time until an event occurs. Because of censoring - the nonobservation of the event of interest after a period of follow-up - a proportion of the survival times of interest will often be unknown. It is assumed that those patients who are censored have the same survival prospects as those who continue to be followed, that is, the censoring is uninformative. Survival data are generally described and modelled in terms of two related functions, the survivor function and the hazard function. The survivor function represents the probability that an individual survives from the time of origin to some time beyond time t. It directly describes the survival experience of a study cohort, and is usually estimated by the KM method. The logrank test may be used to test for differences between survival curves for groups, such as treatment arms. The hazard function gives the instantaneous potential of having an event at a time, given survival up to that time. It is used primarily as a diagnostic tool or for specifying a mathematical model for survival analysis. In comparing treatments or prognostic groups in terms of survival, it is often necessary to adjust for patient-related factors that could potentially affect the survival time of a patient. Failure to adjust for confounders may result in spurious effects. Multivariate survival analysis, a form of multiple regression, provides a way of doing this adjustment, and is the subject the next paper in this series