Collapse of a semiflexible polymer in poor solvent

We investigate the dynamics and the pathways of the collapse of a single, semiflexible polymer in a poor solvent via 3-D Brownian Dynamics simulations. Earlier work indicates that the condensation of semiflexible polymers generically proceeds via a cascade through metastable racquet-shaped, long-lived intermediates towards the stable torus state. We investigate the rate of decay of uncollapsed states, analyze the preferential pathways of condensation, and describe likelihood and lifespan of the different metastable states. The simulation are performed with a bead-stiff spring model with excluded volume interaction and exponentially decaying attractive potential. The semiflexible chain collapse is studied as functions of the three relevant length scales of the phenomenon, i.e., the total chain length $L$, the persistence length $L_p$ and the condensation length $L_0 = \sqrt{k_B T L_p/u_0}$, where $u_0$ is a measure of the attractive potential per unit length. Two dimensionless ratios, $L/L_p$ and $L_0/L_p$, suffice to describe the decay rate of uncollapsed states, which appears to scale as $(L/L_p)^{1/3} (L_0/L_p)$. The condensation sequence is described in terms of the time series of the well separated energy levels associated with each metastable collapsed state. The collapsed states are described quantitatively through the spatial correlation of tangent vectors along the chain. We also compare the results obtained with a locally inextensible bead-rod chain and with a phantom bead-spring model. Finally, we show preliminary results on the effects of steady shear flow on the kinetics of collapse.Comment: 9 pages, 8 figure

On the magnetic stability at the surface in strongly correlated electron systems

The stability of ferromagnetism at the surface at finite temperatures is investigated within the strongly correlated Hubbard model on a semi-infinite lattice. Due to the reduced surface coordination number the effective Coulomb correlation is enhanced at the surface compared to the bulk. Therefore, within the well-known Stoner-picture of band ferromagnetism one would expect the magnetic stability at the surface to be enhanced as well. However, by taking electron correlations into account well beyond the Hartree-Fock (Stoner) level we find the opposite behavior: As a function of temperature the magnetization of the surface layer decreases faster than in the bulk. By varying the hopping integral within the surface layer this behavior becomes even more pronounced. A reduced hopping integral at the surface tends to destabilize surface ferromagnetism whereas the magnetic stability gets enhanced by an increased hopping integral. This behavior represents a pure correlation effect and can be understood in terms of general arguments which are based on exact results in the limit of strong Coulomb interaction.Comment: 6 pages, RevTeX, 4 eps figures, accepted (Phys. Rev. B), for related work and info see http://orion.physik.hu-berlin.d

Understanding the barriers to integrating maternal and mental health at primary health care in Vietnam

The prevalence of common perinatal mental disorders in Vietnam ranges from 16.9% to 39.9%, and substantial treatment gaps have been identified at all levels. This paper explores constraints to the integration of maternal and mental health services at the primary healthcare level and the implications for the health system’s responsiveness to the needs and expectations of pregnant women with mental health conditions in Vietnam. As part of the RESPONSE project, a three-phased realist evaluation study, we present Phase One findings which employed systematic and scoping literature reviews, and qualitative data collection (focus groups and interviews) with key health system actors, in Bac Giang province, Vietnam, to understand the barriers to maternal mental healthcare provision, utilisation, and integration strategies. A four-level framing of the barriers to integrating perinatal mental health services in Vietnam was used in reporting findings, which comprised individual, socio-cultural, organisational, and structural levels. At the socio-cultural and structural levels, these barriers included: cultural beliefs about the holistic notion of physical and mental health, stigma towards mental health, biomedical approach to healthcare services, absence of comprehensive mental health policy, and a lack of mental health workforce. At the organisational level, there was absence of clinical guidelines on the integration of mental health in routine antenatal visits, a shortage of staff, and poor health facilities. Finally, at the provider level, a lack of knowledge and training on mental health was identified. The integration of mental health into routine antenatal visits at the primary care level has the potential help to reduce stigma towards mental health and improve health system responsiveness by providing services closer to the local level, offering prompt attention, better choice of services, and better communication while ensuring privacy and confidentiality of services. This can improve the demand for mental health services and help reduce the delay of care-seeking

An Integrated TCGA Pan-Cancer Clinical Data Resource to Drive High-Quality Survival Outcome Analytics

For a decade, The Cancer Genome Atlas (TCGA) program collected clinicopathologic annotation data along with multi-platform molecular profiles of more than 11,000 human tumors across 33 different cancer types. TCGA clinical data contain key features representing the democratized nature of the data collection process. To ensure proper use of this large clinical dataset associated with genomic features, we developed a standardized dataset named the TCGA Pan-Cancer Clinical Data Resource (TCGA-CDR), which includes four major clinical outcome endpoints. In addition to detailing major challenges and statistical limitations encountered during the effort of integrating the acquired clinical data, we present a summary that includes endpoint usage recommendations for each cancer type. These TCGA-CDR findings appear to be consistent with cancer genomics studies independent of the TCGA effort and provide opportunities for investigating cancer biology using clinical correlates at an unprecedented scale. Analysis of clinicopathologic annotations for over 11,000 cancer patients in the TCGA program leads to the generation of TCGA Clinical Data Resource, which provides recommendations of clinical outcome endpoint usage for 33 cancer types

Genetic algorithm in ab initio protein structure prediction using low resolution model : a review

Proteins are sequences of amino acids bound into a linear chain that adopt a specific folded three-dimensional (3D) shape. This specific folded shape enables proteins to perform specific tasks. The protein structure prediction (PSP) by ab initio or de novo approach is promising amongst various available computational methods and can help to unravel the important relationship between sequence and its corresponding structure. This article presents the ab initio protein structure prediction as a conformational search problem in low resolution model using genetic algorithm. As a review, the essence of twin removal, intelligence in coding, the development and application of domain specific heuristics garnered from the properties of the resulting model and the protein core formation concept discussed are all highly relevant in attempting to secure the best solution

Driver Fusions and Their Implications in the Development and Treatment of Human Cancers.

Gene fusions represent an important class of somatic alterations in cancer. We systematically investigated fusions in 9,624 tumors across 33 cancer types using multiple fusion calling tools. We identified a total of 25,664 fusions, with a 63% validation rate. Integration of gene expression, copy number, and fusion annotation data revealed that fusions involving oncogenes tend to exhibit increased expression, whereas fusions involving tumor suppressors have the opposite effect. For fusions involving kinases, we found 1,275 with an intact kinase domain, the proportion of which varied significantly across cancer types. Our study suggests that fusions drive the development of 16.5% of cancer cases and function as the sole driver in more than 1% of them. Finally, we identified druggable fusions involving genes such as TMPRSS2, RET, FGFR3, ALK, and ESR1 in 6.0% of cases, and we predicted immunogenic peptides, suggesting that fusions may provide leads for targeted drug and immune therapy

The Cancer Genome Atlas Comprehensive Molecular Characterization of Renal Cell Carcinoma

Renal cell carcinoma(RCC) is not a single disease, but several histologically defined cancers with different genetic drivers, clinical courses, and therapeutic responses. The current study evaluated 843 RCC from the three major histologic subtypes, including 488 clear cell RCC, 274 papillary RCC, and 81 chromophobe RCC. Comprehensive genomic and phenotypic analysis of the RCC subtypes reveals distinctive features of each subtype that provide the foundation for the development of subtype-specific therapeutic and management strategies for patients affected with these cancers. Somatic alteration of BAP1, PBRM1, and PTEN and altered metabolic pathways correlated with subtype-specific decreased survival, while CDKN2A alteration, increased DNA hypermethylation, and increases in the immune-related Th2 gene expression signature correlated with decreased survival within all major histologic subtypes. CIMP-RCC demonstrated an increased immune signature, and a uniform and distinct metabolic expression pattern identified a subset of metabolically divergent (MD) ChRCC that associated with extremely poor survival