Common community‐acquired infections and subsequent risk of multiple myeloma: A population‐based study

The role of bacteria and viruses as aetiological agents in the pathogenesis of cancer has been well established for several sites, including a number of haematological malignancies. Less clear is the impact of such exposures on the subsequent development of multiple myeloma (MM). Using the population‐based U.S. Surveillance Epidemiology and End Results‐Medicare dataset, 15,318 elderly MM and 200,000 controls were identified to investigate the impact of 14 common community‐acquired infections and risk of MM. Odds ratios (ORs) and associated 95% confidence intervals (CIs) were adjusted for sex, age and calendar year of selection. The 13‐month period prior to diagnosis/selection was excluded. Risk of MM was increased by 5–39% following Medicare claims for eight of the investigated infections. Positive associations were observed for several infections including bronchitis (adjusted OR 1.14, 95% CI 1.09–1.18), sinusitis (OR 1.15, 95% CI 1.10–1.20) pneumonia (OR 1.27, 95% CI 1.21–1.33), herpes zoster (OR 1.39, 95% CI 1.29–1.49) and cystitis (OR 1.09, 95% CI 1.05–1.14). Each of these infections remained significantly elevated following the exclusion of more than 6 years of claims data. Exposure to infectious antigens may therefore play a role in the development of MM. Alternatively, the observed associations may be a manifestation of an underlying immune disturbance present several years prior to MM diagnosis and thereby part of the natural history of disease progression.     

Simplified protein design biased for prebiotic amino acids yields a foldable,halophilic protein

A compendium of different types of abiotic chemical syntheses identifies a consensus set of 10 “prebiotic” α-amino acids. Before the emergence of biosynthetic pathways, this set is the most plausible resource for protein formation (i.e., proteogenesis) within the overall process of abiogenesis. An essential unsolved question regarding this prebiotic set is whether it defines a “foldable set”—that is, does it contain sufficient chemical information to permit cooperatively folding polypeptides? If so, what (if any) characteristic properties might such polypeptides exhibit? To investigate these questions, two “primitive” versions of an extant protein fold (the β-trefoil) were produced by top-down symmetric deconstruction, resulting in a reduced alphabet size of 12 or 13 amino acids and a percentage of prebiotic amino acids approaching 80%. These proteins show a substantial acidification of pI and require high salt concentrations for cooperative folding. The results suggest that the prebiotic amino acids do comprise a foldable set within the halophile environment.     

From the Cover: Warm early Mars surface enabled by high-altitude water ice clouds

Despite receiving just 30% of the Earth’s present-day insolation, Mars had water lakes and rivers early in the planet’s history, due to an unknown warming mechanism. A possible explanation for the >10²-y-long lake-forming climates is warming by water ice clouds. However, this suggested cloud greenhouse explanation has proved difficult to replicate and has been argued to require unrealistically optically thick clouds at high altitudes. Here, we use a global climate model (GCM) to show that a cloud greenhouse can warm a Mars-like planet to global average annual-mean temperature (T¯) ∼265 K, which is warm enough for low-latitude lakes, and stay warm for centuries or longer, but only if the planet has spatially patchy surface water sources. Warm, stable climates involve surface ice (and low clouds) only at locations much colder than the average surface temperature. At locations horizontally distant from these surface cold traps, clouds are found only at high altitudes, which maximizes warming. Radiatively significant clouds persist because ice particles sublimate as they fall, moistening the subcloud layer so that modest updrafts can sustain relatively large amounts of cloud. The resulting climates are arid (area-averaged surface relative humidity ∼25%). In a warm, arid climate, lakes could be fed by groundwater upwelling, or by melting of ice following a cold-to-warm transition. Our results are consistent with the warm and arid climate favored by interpretation of geologic data, and support the cloud greenhouse hypothesis.

Mars is cold today, but early Mars was warm enough for lakes (e.g., ref. 1) that were habitable (2). These early (4 to <3 Ga) warm climates cannot be explained by basic models of the early Mars greenhouse effect (involving only CO₂ and H₂O vapor) because these predict climates that are too cold (3, 4). Hypotheses for solving this problem have difficulty in explaining the geologic evidence for >10²-y-long lake-forming climates that persisted as late as <3 Ga (e.g., refs. 2, 4, and 5 and references therein). One hypothesis for reconciling models with data are greenhouse warming by H₂–CO₂ collision-induced absorption (e.g., refs. 6–8). Here, we demonstrate that a different mechanism can explain warm paleoclimates. Recently, warm (T¯ ∼265 K, where T¯ = annual mean temperature) early Mars climates were found in one three-dimensional (3D) global climate model (GCM) simulation of the greenhouse effect of high-altitude water ice clouds (9). However, Urata and Toon (9) did not check for steady-state mass balance for surface H₂O reservoirs, and the high clouds produced by this model require an imposed cloud lifetime, adjusted to be longer than that of Earth clouds by a factor of 10². This and other choices have been described as “not physically reasonable” by subsequent work (10), and other studies also reached similar pessimistic conclusions about the potential of water ice clouds to explain warm paleoclimates (3, 11). For example, Wordsworth et al. (12) found in their model that even if cloud precipitation was (unrealistically) disabled, cloud radiative effects gave only a 1- to 2-y-long rise in surface temperature, too brief to explain geologic data. High clouds are needed for strong cloud warming because high clouds are cold relative to the surface, and the greenhouse-warming potential of clouds increases when the temperature difference between the cloud-forming altitudes and the surface increases (e.g., refs. 10 and 11). In one-dimensional (1D) models, strong H₂O ice-cloud warming occurs if—and only if—radiatively significant clouds are located at high altitudes (11). Nevertheless, 1D calculations have consistently shown the potential of a tiny quantity of water (just ∼0.01 kg/m² H₂O in the form of cloud ice) to raise planet temperature by ∼50 K (10, 11). For comparison, Mars today has an average of ∼3 × 10⁴ kg/m² of surface H₂O ice and ∼0.01 kg/m² atmospheric H₂O vapor. This motivates new 3D simulations in order to understand the discrepant results from earlier studies and test the cloud greenhouse hypothesis. Here, we present cloud greenhouse simulations run from geologically reasonable initial conditions, with physically based cloud microphysics, and run for long enough for the atmosphere to reach equilibrium with surface water reservoirs.To test the cloud greenhouse hypothesis, we use the MarsWRF GCM (13, 14), modified to include radiatively active water ice clouds. MarsWRF is the Martian implementation of the Planet Weather Research and Forecasting (PlanetWRF) GCM (15), itself derived from the terrestrial Weather Research and Forecasting (WRF) model (16, 17). For early Mars, with static cloud locations, we find maximum warming when cloud optical depth is of order unity and clouds are high (∼30 km altitude) (SI Appendix, Fig. S2). These 3D results with static clouds are consistent with the 1D results of refs. 10 and 11 (SI Appendix). In the remainder of this paper, we use a dynamic water cycle (dynamic clouds), including sedimentation of individual cloud particles, rapid snow-out above an autoconversion threshold, and exchange with surface water ice (Methods). We assume that relative humidity is buffered to ≲1 by rapid condensation of cloud particles; although air parcels can reach saturation at any temperature in our model, condensation occurs at ≳190 K in our output, consistent with our assumption that supersaturation is minor. Individual cloud particles undergo Stokes settling (gas viscosity 10⁻⁵ Pa s) at a rate set by their modal sizes, with a Cunningham slip correction. Our model has two types of particles: cloud particles that do not fall very fast and snow that does fall fast because the particles are much larger. Cloud particles can be converted to form fast-settling snow if the cloud-particle number density exceeds a threshold. This threshold represents the dependence of cloud-particle coalescence on cloud-particle number density. Specifically, in order to conservatively represent the cloud-depleting effect of mass transfer from slow-settling (cm/s) cloud particles to fast-settling snow (autoconversion), we increase the settling velocity to a fast value (1 m/s) when cloud-particle density exceeds a conservatively low threshold (3 × 10⁻⁵ kg/kg). In other words, the conversion of cloud ice to snow does not occur until the number density of cloud particles reaches a certain magnitude. Falling particles either reach the ground as snow or reevaporate when they descend into dry air. Consistent with output from another GCM (11), we find that snow descending into unsaturated air at >30 km will evaporate well before reaching the ground.     

Treatment outcomes and incidence of brain metastases in pulmonary large cell neuroendocrine carcinoma

Introduction

Large cell neuroendocrine carcinoma (LCNEC) is a rare type of high-grade pulmonary neuroendocrine tumor. The study objective is to investigate its survival outcomes, incidence of brain metastases, and patterns of recurrence.