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Marine low clouds strongly cool the planet. How this cooling effect will respond to climate change is a leading source of uncertainty in climate sensitivity, the planetary warming resulting from CO2 doubling. Here, we observationally constrain this low cloud feedback at a near-global scale. Satellite observations are used to estimate the sensitivity of low clouds to interannual meteorological perturbations. Combined with model predictions of meteorological changes under greenhouse warming, this permits quantification of spatially resolved cloud feedbacks. We predict positive feedbacks from midlatitude low clouds and eastern ocean stratocumulus, nearly unchanged trade cumulus and a near-global marine low cloud feedback of 0.19 ± 0.12 W m−2 K−1 (90% confidence). These constraints imply a moderate climate sensitivity (~3 K). Despite improved midlatitude cloud feedback simulation by several current-generation climate models, their erroneously positive trade cumulus feedbacks produce unrealistically high climate sensitivities. Conversely, models simulating erroneously weak low cloud feedbacks produce unrealistically low climate sensitivities. Marine low clouds cool the planet, but their response to warming is uncertain and dominates the spread in model-based climate sensitivities. Observational constraints suggest smaller cloud feedbacks than previously reported and imply a more moderate climate sensitivity.

Over the tropical Atlantic during boreal spring, average interhemispheric differences in sea-surface temperature (SST) coincide with a coherent pattern of interannual climate variability often referred to as the Atlantic Meridional Mode. This includes anomalous SST and sea-level pressure roughly anti-symmetric about the equator, as well as cross-equatorial near-surface winds directed toward the warmer hemisphere. Within subtropical marine boundary layer cloud regions in both hemispheres, enhanced cloudiness associated with this variability is co-located with cool SST, a strong temperature inversion, and cold horizontal surface temperature advection, while reduced cloudiness is associated with the opposite meteorological conditions. This is indicative a positive cloud feedback that reinforces the underlying SST anomalies. The simulation of this feedback varies widely among models participating in phase 5 of the Coupled Model Intercomparison Project. Models that fail to simulate this feedback substantially underestimate the amplitudes of typical tropical Atlantic interhemispheric variability in cloudiness off of the equator, SST, and atmospheric circulation. Models that correctly reproduce a positive cloud feedback generally produce higher and more realistic amplitudes of variability, but with substantial scatter. Marine boundary layer clouds therefore appear to be a key element of springtime coupled atmosphere–ocean variability over the tropical Atlantic. A markedly more successful simulation of this variability in climate models may be obtained by better representing boundary layer cloud processes.

Climate modes of variability over the Atlantic and Pacific may be amplified by a positive feedback between sea-surface temperature (SST) and marine boundary layer clouds. However, it is well known that climate models poorly simulate this feedback. Does this deficiency contribute to model-to-model differences in the representation of climate modes of variability? Over both the North Atlantic and Pacific, typical summertime interannual to interdecadal SST variability exhibits horseshoe-like patterns of co-located anomalies of shortwave cloud radiative effect (CRE), low-level cloud fraction, SST, and estimated inversion strength over the subtropics and midlatitudes that are consistent with a positive cloud feedback. During winter over the midlatitudes, this feedback appears to be diminished. Models participating in the Coupled Model Intercomparison Project phase 5 that simulate a weak feedback between subtropical SST and shortwave CRE produce smaller and less realistic amplitudes of summertime SST and CRE variability over the northern oceans compared to models with a stronger feedback. The change in SST amplitude per unit change in CRE amplitude among the models and observations may be understood as the temperature response of the ocean mixed layer to a unit change in radiative flux over the course of a season. These results highlight the importance of boundary layer clouds in interannual to interdecadal atmosphere–ocean variability over the northern oceans during summer. The results also suggest that deficiencies in the simulation of these clouds in coupled climate models contribute to underestimation in their simulation of summer-to-summer SST variability.

Extracellular vesicles (EVs) mediate the intercellular transfer of RNAs, which alter gene expression in target cells. EV heterogeneity has limited progress towards defining their physiological functions and utility as disease-specific biomarkers. CD63 and MHC1 are widely used as markers to purify EVs. CD47 is also present on EVs and alters their effects on target cells, suggesting that specific surface markers define functionally distinct EVs. This hypothesis was addressed by comparing Jurkat T cell EVs captured using CD47, CD63, and MHC1 antibodies. These EV subsets have similar sizes but divergent RNA contents. Apart from differences in numbers of nonannotated transcripts, CD63+, MHC1+, and CD47+ EVs have similar overall contents of most noncoding RNA classes, but the relative enrichment of specific RNAs differs. The enrichment of micro-RNAs is highly divergent, and some including miR320a are selectively concentrated in CD47+ EVs. Small nucleolar RNAs including SNORD116@ and SNHG10 are also selectively enriched in CD47+ EVs, whereas no small nuclear RNAs are enriched in CD47+ EVs. Conversely, MHC1+ EVs are selectively enriched in a subset of tRNAs including TRE-CTC and TRR-CCG. This heterogeneity in RNA composition suggests multiple sorting mechanisms that direct specific RNAs into subsets of EVs that express specific surface markers.

Eukaryotic cells utilize macroautophagy (hereafter autophagy) to recycle cellular materials during nutrient stress. Target of rapamycin (Tor) is a central regulator of this process, acting by post-translational mechanisms, phosphorylating preformed autophagy-related (Atg) proteins to repress autophagy during log-phase growth. We recently reported an additional role for post-transcriptional regulation of autophagy, whereby the mRNA decapping protein, Dcp2, undergoes Tor-dependent phosphorylation, resulting in increased ATG mRNA decapping and degradation under nutrient-rich, repressing conditions. Dephosphorylation of Dcp2 during starvation is associated with dissociation of the decapping-ATG mRNA complex, with resultant stabilization of, and accumulation of, ATG transcripts, leading to induction of autophagy. Regulation of mRNA degradation occurs in concert with known mRNA synthetic inductive mechanisms to potentiate overall transcriptional regulation. This mRNA degradative pathway thus constitutes a type of transcriptional ‘futile cycle’ where under nutrient-rich conditions transcript is constantly being generated and degraded. As nutrient levels decline, steady state mRNA levels are increased by both inhibition of degradation as well as increased de novo synthesis. A role for this regulatory process in fungal virulence was further demonstrated by showing that overexpression of the Dcp2-associated mRNA-binding protein Vad1 in the AIDS-associated pathogen Cryptococcus neoformans results in constitutive repression of autophagy even under starvation conditions as well as attenuated virulence in a mouse model. In summary, Tor-dependent post-transcriptional regulation of autophagy plays a key role in the facilitation of microbial pathogenesis.

The melting process of a spherical nanoparticle is analysed using a mathematical model derived from continuum theory. The standard model for macro-scale melting is modified to include melting point depression using the Gibbs–Thomson equation. The key difference between the current and previous work in the melting of nanoparticles is that the difference in densities between the solid and liquid phases is accounted for. This modifies the energy balance at the phase change interface to include a kinetic energy term, which then changes the form of the equation, and it also requires an advection term in the heat equation for the liquid phase. Approximate analytical and numerical solutions are presented for the melting of particles in the range 10–100 nm. It is shown that when the density difference is included in the model, melting is significantly slower than when density is assumed constant throughout the process. This is attributed to the flowing liquid providing a sink term, namely kinetic energy, in the energy balance. The difference in results is greatest for small particles; however, it is concluded that the varying density model will never reduce to the constant density model resulting in a difference of around 15 % even at the macro-scale.

In this paper, we study the melting of a spherical nanoparticle. The model differs from previous ones in that a number of features have been incorporated to match experimental observations. These include the size dependence of the latent heat and a cooling condition at the boundary (as opposed to the fixed temperature condition used in previous studies). Melt temperature variation and density change are also included. The density variation drives the flow of the outer fluid layer. The latent heat variation is modelled by a new relation, which matches experimental data better than previous models. A novel form of Stefan condition is used to determine the position of the melt front. This condition takes into account the latent heat variation, the energy required to create new surface and the kinetic energy of the displaced fluid layer. Results show that melting times can be significantly faster than predicted by previous theoretical models; for smaller particles, this can be around a factor 3. This is primarily due to the latent heat variation. The previously used fixed temperature boundary condition had two opposing effects on melt times: the implied infinite heat transfer led to faster melting but also artificially magnified the effect of kinetic energy, which slowed down the process. We conclude that any future models of nanoparticle melting must be based on the new Stefan condition and account for latent heat variation.

A mathematical model is developed to describe the melting of nanowires. The first section of the paper deals with a standard theoretical situation, where the wire melts due to a fixed boundary temperature. This analysis allows us to compare with existing results for the phase change of nanospheres. The equivalent solidification problem is also examined. This shows that solidification is a faster process than melting; this is because the energy transfer occurs primarily through the solid rather than the liquid which is a poorer conductor of heat. This effect competes with the energy required to create new solid surface which acts to slow down the process, but overall conduction dominates. In the second section, we consider a more physically realistic boundary condition, where the phase change occurs due to a heat flux from surrounding material. This removes the singularity in initial melt velocity predicted in previous models of nanoparticle melting. It is shown that even with the highest possible flux the melting time is significantly slower than with a fixed boundary temperature condition.

Genetic variation on the Y chromosome has not been convincingly implicated in prostate cancer risk. To comprehensively analyze the role of inherited Y chromosome variation in prostate cancer risk in individuals of European ancestry, we genotyped 34 binary Y chromosome markers in 3,995 prostate cancer cases and 3,815 control subjects drawn from four studies. In this set, we identified nominally significant association between a rare haplogroup, E1b1b1c, and prostate cancer in stage I (P = 0.012, OR = 0.51; 95% confidence interval 0.30–0.87). Population substructure of E1b1b1c carriers suggested Ashkenazi Jewish ancestry, prompting a replication phase in individuals of both European and Ashkenazi Jewish ancestry. The association was not significant for prostate cancer overall in studies of either Ashkenazi Jewish (1,686 cases and 1,597 control subjects) or European (686 cases and 734 control subjects) ancestry (Pmeta = 0.078), but a meta-analysis of stage I and II studies revealed a nominally significant association with prostate cancer risk (Pmeta = 0.010, OR = 0.77; 95% confidence interval 0.62–0.94). Comparing haplogroup frequencies between studies, we noted strong similarities between those conducted in the US and France, in which the majority of men carried R1 haplogroups, resembling Northwestern European populations. On the other hand, Finns had a remarkably different haplogroup distribution with a preponderance of N1c and I1 haplogroups. In summary, our results suggest that inherited Y chromosome variation plays a limited role in prostate cancer etiology in European populations but warrant follow-up in additional large and well characterized studies of multiple ethnic backgrounds. Electronic supplementary material The online version of this article (doi:10.1007/s00439-012-1139-5) contains supplementary material, which is available to authorized users.

The presence of pancreatic cancer (PC) in melanoma-prone families has been consistently associated with an increased frequency of CDKN2A mutations, the major high-risk susceptibility gene identified for melanoma. However, the precise relationship between CDKN2A, melanoma and PC remains unknown. We evaluated a recently identified PC susceptibility gene PALB2 using both sequencing and tagging to determine whether PALB2 might explain part of the relationship between CDKN2A, melanoma, and PC. No disease-related mutations were identified from sequencing PALB2 in multiple pancreatic cancer patients or other mutation carrier relatives of PC patients from the eight melanoma-prone families with CDKN2A mutations and PC. In addition, no significant associations were observed between 11 PALB2 tagging SNPs and melanoma risk in 23 melanoma-prone families with CDKN2A mutations or the subset of 11 families with PC or PC-related CDKN2A mutations. The results suggested that PALB2 does not explain the relationship between CDKN2A, melanoma, and pancreatic cancer in these melanoma-prone families.

Large glacial–interglacial fluctuations occurred during the late Palaeozoic. Geochemical and fossil data show these cycles were marked by coincident shifts in the carbon cycle and terrestrial biosphere.

A model is developed for the unsteady laminar flow of athin fluid film over a substrate with roughness of the same order as the film height. The limits of large and small surface resistance and small surface-roughness are investigated and it is shown that at leading order the classical parabolic form for the velocity profile is retrieved in all cases. Empirical expressions for the depth-averaged velocity and the ratio of the average to maximum velocities are investigated and shown to agree with the present theory under certain conditions. The method is verified by comparison with experiments for steady uni-directional flow over a surface of known roughness.

Despite recent advances in the therapeutic management of asthma, the prevalence, morbidity and mortality of this chronic disease continue to increase in most countries. The financial burden associated with asthma has received increasing scrutiny in the medical literature over the past two decades. In 1990, a study in the US demonstrated that all chronic disease conditions accounted for $US425 billion in medical care costs. These chronic conditions accounted for 96% of home care visits, 80% of hospital days, 69% of hospital admissions, 66% of doctor and 55% of emergency department visits, and 55% of pharmacy prescriptions. This has led to an increased demand for improved outpatient management of asthma, and patients are now monitoring their asthma and gathering data in the ambulatory setting. Self-monitoring tools for patients with diabetes mellitus and hypertension have grown in recent years, but technological advances for self-monitoring of patients with asthma have been slow over the past several decades. This article reviewed the literature on self-monitoring tools currently available for improving outcomes in the patient with asthma. These tools currently consist of written treatment plans, peak flow meters and metered-dose inhaler monitoring devices. Patient education and training in self-management involving self-monitoring of either symptoms or peak expiratory flow, in conjunction with education and a written treatment plan, appears to improve health outcomes for both children and adults with asthma. Education allowing patients with asthma or their caregivers to intervene and adjust medications under the guidance of a written treatment plan appears to be more effective than other forms of asthma self-management.

We used cDNA microarrays to assess gene expression profiles in 60 human cancer cell lines used in a drug discovery screen by the National Cancer Institute. Using these data, we linked bioinformatics and chemoinformatics by correlating gene expression and drug activity patterns in the NCI60 lines. Clustering the cell lines on the basis of gene expression yielded relationships very different from those obtained by clustering the cell lines on the basis of their response to drugs. Gene-drug relationships for the clinical agents 5-fluorouracil and L-asparaginase exemplify how variations in the transcript levels of particular genes relate to mechanisms of drug sensitivity and resistance. This is the first study to integrate large databases on gene expression and molecular pharmacology.

A systolic array implementation of the one-shot decorrelating detector algorithm designed for Code-Division Multiple-Access (CDMA) spread spectrum communication systems used in mobile communications environments is developed. This detector has the advantage that it is near-far resistant, that is, it minimizes the interference effects that near-end users have on far-end users. However, its implementation requires the on-line inversion of the correlation matrix between the desired and interfering users. For this reason, a systolic computation approach is chosen to help solve the problem of fast on-the-fly matrix inversion. Performance of the proposed implementation is assessed via digital computer simulation. The implementation methodology presented here leads to a VLSI implementation structure.

The tumor suppressor gene p53 plays a major role in regulation of the mammalian cellular stress response, in part through the transcriptional activation of genes involved in cell cycle control, DNA repair, and apoptosis. Many factors contribute to control of the activation of p53, and the downstream response to its activation may also vary depending on the cellular environment or other modifying factors in the cell. The complexity of the p53 response makes this an ideal system for application of newly emerging rapid throughput analysis techniques and informatics analysis.

In this paper, we analyse the time-dependent heat equations over a finite domain to determine expressions for the thermal diffusivity and conductivity of a nanofluid (where a nanofluid is a fluid containing nanoparticles with average size below 100 nm). Due to the complexity of the standard mathematical analysis of this problem, we employ a well-known approximate solution technique known as the heat balance integral method. This allows us to derive simple analytical expressions for the thermal properties, which appear to depend primarily on the volume fraction and liquid properties. The model is shown to compare well with experimental data taken from the literature even up to relatively high concentrations and predicts significantly higher values than the Maxwell model for volume fractions approximately >1 %. The results suggest that the difficulty in reproducing the high values of conductivity observed experimentally may stem from the use of a static heat flow model applied over an infinite domain rather than applying a dynamic model over a finite domain.

In this paper the effects of changing the ion concentration in and around a sample of soft tissue are investigated. The triphasic theory developed by Laiet al. (1990,Biomechanics of Diarthrodial Joints, Vol. 1, Berlin, Springer-Verlag) is reduced to two coupled partial differential equations involving fluid ion concentration and tissue solid deformation. These equations are given in general form for Cartesian, cylindrical and spherical geometries. After solving the two equations quantities such as fluid velocity, fluid pressure, chemical potentials and chemical expansion stress may be easily calculated. In the Cartesian geometry comparison is made with the experimental and theoretical work of Myerset al. (1984,ASME J. biomech. Engng,106, 151–158). This dealt with changing the ion concentration of a salt shower on a strip of bovine articular cartilage. Results were obtained in both free swelling and isometric tension states, using an empirical formula to acount for ion induced deformation. The present theory predicts lower ion concentrations inside the tissue than this earlier work. A spherical sample of tissue subjected to a change in salt bath ion concentration is also considered. Numerical results are obtained for both hypertonic and hypotonic bathing solutions. Of particular interest is the finding that tissue may contract internally before reaching a final swollen equilibrium state or swell internally before finally contracting. By considering the relative magnitude, and also variation throughout the time course of terms in the governing equations, an even simpler system is deduced. As well as being linear the concentration equation in the new system is uncoupled. Results obtained from the linear system compare well with those from the spherical section. Thus, biological swelling situations may be modelled by a simple system of equations with the possibility, of approximate analytic solutions in certain cases.

For long rectangular rubber blocks with metal plates bonded to their upper and lower surfaces, approximate force-deflection relations are obtained for the problem of combined compression (or tension) and shear. The results obtained generalise that of Klingbeil and Shield for the case of pure compression alone, as well as incorporating the well known simple shear result. However, unlike the pure compression solution, horizontal and vertical force resultants on the free surfaces cannot both be set to zero, which is a well known characteristic of simple shearing. Here the strategy is adopted of equating to zero only the horizontal force resultants on the free surfaces so that the pure compression approximation of Klingbeil and Shield emerges in the event of zero shear. The force-deflection relations so obtained are illustrated graphically.

In this paper we discuss three examples where continuum theory may be applied to describe nanoscale phenomena: 1. Enhanced flow in carbon nanotubes (CNTs) – This model shows that the experimentally observed enhancement can be explained using standard flow equations but with a depletion layer between the liquid and solid interfaces. 2. Nanoparticle melting – Nanoparticles often exhibit a sharp increase in melting rate as the size decreases. A mathematical model will be presented which predicts this phenomena. 3. Nanofluids – Experimental results concerning the remarkable heat transfer characteristics of nanofluids are at times contradictory. We develop a model for the thermal conductivity of a nanofluid, which provides much higher predictions than the standard Maxwell model and a better match to data.