Chiasma

Newspaper reporting on events at the Boston University School of Medicine in the 1960s

Generalized Rosenfeld scalings for tracer diffusivities in not-so-simple fluids: Mixtures and soft particles

Rosenfeld [Phys. Rev. A 15, 2545 (1977)] noticed that casting transport coefficients of simple monatomic, equilibrium fluids in specific dimensionless forms makes them approximately single-valued functions of excess entropy. This has predictive value because, while the transport coefficients of dense fluids are difficult to estimate from first principles, excess entropy can often be accurately predicted from liquid-state theory. Here, we use molecular simulations to investigate whether Rosenfeld's observation is a special case of a more general scaling law relating mobility of particles in mixtures to excess entropy. Specifically, we study tracer diffusivities, static structure, and thermodynamic properties of a variety of one- and two-component model fluid systems with either additive or non-additive interactions of the hard-sphere or Gaussian-core form. The results of the simulations demonstrate that the effects of mixture concentration and composition, particle-size asymmetry and additivity, and strength of the interparticle interactions in these fluids are consistent with an empirical scaling law relating the excess entropy to a new dimensionless (generalized Rosenfeld) form of tracer diffusivity, which we introduce here. The dimensionless form of the tracer diffusivity follows from knowledge of the intermolecular potential and the transport / thermodynamic behavior of fluids in the dilute limit. The generalized Rosenfeld scaling requires less information, and provides more accurate predictions, than either Enskog theory or scalings based on the pair-correlation contribution to the excess entropy. As we show, however, it also suffers from some limitations, especially for systems that exhibit significant decoupling of individual component tracer diffusivities.Comment: 15 pages, 10 figure

Self-assembly of artificial microtubules

Understanding the complex self-assembly of biomacromolecules is a major outstanding question. Microtubules are one example of a biopolymer that possesses characteristics quite distinct from standard synthetic polymers that are derived from its hierarchical structure. In order to understand how to design and build artificial polymers that possess features similar to those of microtubules, we have initially studied the self-assembly of model monomers into a tubule geometry. Our model monomer has a wedge shape with lateral and vertical binding sites that are designed to form tubules. We used molecular dynamics simulations to study the assembly process for a range of binding site interaction strengths. In addition to determining the optimal regime for obtaining tubules, we have calculated a diagram of the structures that form over a wide range of interaction strengths. Unexpectedly, we find that the helical tubules form, even though the monomer geometry is designed for nonhelical tubules. We present the detailed dynamics of the tubule self-assembly process and show that the interaction strengths must be in a limited range to allow rearrangement within clusters. We extended previous theoretical methods to treat our system and to calculate the boundaries between different structures in the diagram.Comment: 15 pages, 11 figure

Determining Frequent Patterns of Copy Number Alterations in Cancer

Cancer progression is often driven by an accumulation of genetic changes but also accompanied by increasing genomic instability. These processes lead to a complicated landscape of copy number alterations (CNAs) within individual tumors and great diversity across tumor samples. High resolution array-based comparative genomic hybridization (aCGH) is being used to profile CNAs of ever larger tumor collections, and better computational methods for processing these data sets and identifying potential driver CNAs are needed. Typical studies of aCGH data sets take a pipeline approach, starting with segmentation of profiles, calls of gains and losses, and finally determination of frequent CNAs across samples. A drawback of pipelines is that choices at each step may produce different results, and biases are propagated forward. We present a mathematically robust new method that exploits probe-level correlations in aCGH data to discover subsets of samples that display common CNAs. Our algorithm is related to recent work on maximum-margin clustering. It does not require pre-segmentation of the data and also provides grouping of recurrent CNAs into clusters. We tested our approach on a large cohort of glioblastoma aCGH samples from The Cancer Genome Atlas and recovered almost all CNAs reported in the initial study. We also found additional significant CNAs missed by the original analysis but supported by earlier studies, and we identified significant correlations between CNAs

Proteins of nucleotide and base excision repair pathways interact in mitochondria to protect from loss of subcutaneous fat, a hallmark of aging

Defects in the DNA repair mechanism nucleotide excision repair (NER) may lead to tumors in xeroderma pigmentosum (XP) or to premature aging with loss of subcutaneous fat in Cockayne syndrome (CS). Mutations of mitochondrial (mt)DNA play a role in aging, but a link between the NER-associated CS proteins and base excision repair (BER)-associated proteins in mitochondrial aging remains enigmatic. We show functional increase of CSA and CSB inside mt and complex formation with mtDNA, mt human 8-oxoguanine glycosylase (mtOGG)-1, and mt single-stranded DNA binding protein (mtSSBP)-1 upon oxidative stress. MtDNA mutations are highly increased in cells from CS patients and in subcutaneous fat of aged Csbm/m and Csa−/− mice. Thus, the NER-proteins CSA and CSB localize to mt and directly interact with BER-associated human mitochondrial 8-oxoguanine glycosylase-1 to protect from aging- and stress-induced mtDNA mutations and apoptosis-mediated loss of subcutaneous fat, a hallmark of aging found in animal models, human progeroid syndromes like CS and in normal human aging

Differences in COVID-19 Outcomes Among Patients With Type 1 Diabetes: First vs Later Surges

Background Outcomes of the novel coronavirus SARS-CoV-2 (COVID-19) have improved throughout the pandemic. However, whether outcomes of COVID-19 in the type 1 diabetes (T1D) population improved over time is unknown. Therefore, we aim to investigate differences in COVID-19 outcomes for patients with T1D in the US. Method We analyzed data collected via a registry of patients with T1D and COVID-19 from 56 sites between April 2020 and January 2021. First, we grouped cases into First Surge (04/09/2020 - 07/31/2020, n=188) and Late Surge (08/01/2020 - 01/31/2021, n=410). Then, we compared outcomes between both groups using descriptive statistics and logistic regression models. Results Adverse outcomes were more frequent during the first surge including Diabetic Ketoacidosis (32% versus 15%, p<0.001), severe hypoglycemia (4% versus 1%, p=0.04) and hospitalization (52% versus 22%, p<0.001). The First surge cases were older (28 +/- 18.8 years versus 18.8 +/- 11.1 years, p<0.001), had higher hemoglobin A1c (HbA1c) levels (Median (IQR): 9.3 (4.0) versus 8.4(2.8), <0.001) and use public insurance (n(%): 107 (57) versus 154 (38), p <0.001). There were five times increased odds of hospitalization for adults (OR 5.01 (2.11,12.63) in the first surge compared to the late surge. Conclusion COVID-19 cases among patients with T1D reported during the first surge had a higher proportion of adverse outcomes than those presented in a later surge

Gonadal Transcriptome Alterations in Response to Dietary Energy Intake: Sensing the Reproductive Environment

Reproductive capacity and nutritional input are tightly linked and animals' specific responses to alterations in their physical environment and food availability are crucial to ensuring sustainability of that species. We have assessed how alterations in dietary energy intake (both reductions and excess), as well as in food availability, via intermittent fasting (IF), affect the gonadal transcriptome of both male and female rats. Starting at four months of age, male and female rats were subjected to a 20% or 40% caloric restriction (CR) dietary regime, every other day feeding (IF) or a high fat-high glucose (HFG) diet for six months. The transcriptional activity of the gonadal response to these variations in dietary energy intake was assessed at the individual gene level as well as at the parametric functional level. At the individual gene level, the females showed a higher degree of coherency in gonadal gene alterations to CR than the males. The gonadal transcriptional and hormonal response to IF was also significantly different between the male and female rats. The number of genes significantly regulated by IF in male animals was almost 5 times greater than in the females. These IF males also showed the highest testosterone to estrogen ratio in their plasma. Our data show that at the level of gonadal gene responses, the male rats on the IF regime adapt to their environment in a manner that is expected to increase the probability of eventual fertilization of females that the males predict are likely to be sub-fertile due to their perception of a food deficient environment