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In recent years, marine, freshwater and terrestrial pollution with microplastics has been discussed extensively, whereas atmospheric microplastic transport has been largely overlooked. Here, we present global simulations of atmospheric transport of microplastic particles produced by road traffic (TWPs – tire wear particles and BWPs – brake wear particles), a major source that can be quantified relatively well. We find a high transport efficiencies of these particles to remote regions. About 34% of the emitted coarse TWPs and 30% of the emitted coarse BWPs (100 kt yr−1 and 40 kt yr−1 respectively) were deposited in the World Ocean. These amounts are of similar magnitude as the total estimated direct and riverine transport of TWPs and fibres to the ocean (64 kt yr−1). We suggest that the Arctic may be a particularly sensitive receptor region, where the light-absorbing properties of TWPs and BWPs may also cause accelerated warming and melting of the cryosphere.

This Opinion article discusses progress and challenges in using patient-derived xenograft (PDX) models in cancer precision medicine. It is primarily co-authored by members of the EurOPDX Consortium and as such highlights the merits of shared PDX resources. Patient-derived xenografts (PDXs) have emerged as an important platform to elucidate new treatments and biomarkers in oncology. PDX models are used to address clinically relevant questions, including the contribution of tumour heterogeneity to therapeutic responsiveness, the patterns of cancer evolutionary dynamics during tumour progression and under drug pressure, and the mechanisms of resistance to treatment. The ability of PDX models to predict clinical outcomes is being improved through mouse humanization strategies and the implementation of co-clinical trials, within which patients and PDXs reciprocally inform therapeutic decisions. This Opinion article discusses aspects of PDX modelling that are relevant to these questions and highlights the merits of shared PDX resources to advance cancer medicine from the perspective of EurOPDX, an international initiative devoted to PDX-based research.

On 11 March 2011, an earthquake occurred about 130 km off the Pacific coast of Japan's main island Honshu, followed by a large tsunami. The resulting loss of electric power at the Fukushima Dai-ichi nuclear power plant developed into a disaster causing massive release of radioactivity into the atmosphere. In this study, we determine the emissions into the atmosphere of two isotopes, the noble gas xenon-133 (133Xe) and the aerosol-bound caesium-137 (137Cs), which have very different release characteristics as well as behavior in the atmosphere. To determine radionuclide emissions as a function of height and time until 20 April, we made a first guess of release rates based on fuel inventories and documented accident events at the site. This first guess was subsequently improved by inverse modeling, which combined it with the results of an atmospheric transport model, FLEXPART, and measurement data from several dozen stations in Japan, North America and other regions. We used both atmospheric activity concentration measurements as well as, for 137Cs, measurements of bulk deposition. Regarding 133Xe, we find a total release of 15.3 (uncertainty range 12.2–18.3) EBq, which is more than twice as high as the total release from Chernobyl and likely the largest radioactive noble gas release in history. The entire noble gas inventory of reactor units 1–3 was set free into the atmosphere between 11 and 15 March 2011. In fact, our release estimate is higher than the entire estimated 133Xe inventory of the Fukushima Dai-ichi nuclear power plant, which we explain with the decay of iodine-133 (half-life of 20.8 h) into 133Xe. There is strong evidence that the 133Xe release started before the first active venting was made, possibly indicating structural damage to reactor components and/or leaks due to overpressure which would have allowed early release of noble gases. For 137Cs, the inversion results give a total emission of 36.6 (20.1–53.1) PBq, or about 43% of the estimated Chernobyl emission. Our results indicate that 137Cs emissions peaked on 14–15 March but were generally high from 12 until 19 March, when they suddenly dropped by orders of magnitude at the time when spraying of water on the spent-fuel pool of unit 4 started. This indicates that emissions may not have originated only from the damaged reactor cores, but also from the spent-fuel pool of unit 4. This would also confirm that the spraying was an effective countermeasure. We explore the main dispersion and deposition patterns of the radioactive cloud, both regionally for Japan as well as for the entire Northern Hemisphere. While at first sight it seemed fortunate that westerly winds prevailed most of the time during the accident, a different picture emerges from our detailed analysis. Exactly during and following the period of the strongest 137Cs emissions on 14 and 15 March as well as after another period with strong emissions on 19 March, the radioactive plume was advected over Eastern Honshu Island, where precipitation deposited a large fraction of 137Cs on land surfaces. Radioactive clouds reached North America on 15 March and Europe on 22 March. By middle of April, 133Xe was fairly uniformly distributed in the middle latitudes of the entire Northern Hemisphere and was for the first time also measured in the Southern Hemisphere (Darwin station, Australia). In general, simulated and observed concentrations of 133Xe and 137Cs both at Japanese as well as at remote sites were in good quantitative agreement. Altogether, we estimate that 6.4 PBq of 137Cs, or 18% of the total fallout until 20 April, were deposited over Japanese land areas, while most of the rest fell over the North Pacific Ocean. Only 0.7 PBq, or 1.9% of the total fallout were deposited on land areas other than Japan.

Arctic haze is a seasonal phenomenon with high concentrations of accumulation-mode aerosols occurring in the Arctic in winter and early spring. Chemistry transport models and climate chemistry models struggle to reproduce this phenomenon, and this has recently prompted changes in aerosol removal schemes to remedy the modeling problems. In this paper, we show that shortcomings in current emission data sets are at least as important. We perform a 3 yr model simulation of black carbon (BC) with the Lagrangian particle dispersion model FLEXPART. The model is driven with a new emission data set (\"ECLIPSE emissions\") which includes emissions from gas flaring. While gas flaring is estimated to contribute less than 3% of global BC emissions in this data set, flaring dominates the estimated BC emissions in the Arctic (north of 66° N). Putting these emissions into our model, we find that flaring contributes 42% to the annual mean BC surface concentrations in the Arctic. In March, flaring even accounts for 52% of all Arctic BC near the surface. Most of the flaring BC remains close to the surface in the Arctic, so that the flaring contribution to BC in the middle and upper troposphere is small. Another important factor determining simulated BC concentrations is the seasonal variation of BC emissions from residential combustion (often also called domestic combustion, which is used synonymously in this paper). We have calculated daily residential combustion emissions using the heating degree day (HDD) concept based on ambient air temperature and compare results from model simulations using emissions with daily, monthly and annual time resolution. In January, the Arctic-mean surface concentrations of BC due to residential combustion emissions are 150% higher when using daily emissions than when using annually constant emissions. While there are concentration reductions in summer, they are smaller than the winter increases, leading to a systematic increase of annual mean Arctic BC surface concentrations due to residential combustion by 68% when using daily emissions. A large part (93%) of this systematic increase can be captured also when using monthly emissions; the increase is compensated by a decreased BC burden at lower latitudes. In a comparison with BC measurements at six Arctic stations, we find that using daily-varying residential combustion emissions and introducing gas flaring emissions leads to large improvements of the simulated Arctic BC, both in terms of mean concentration levels and simulated seasonality. Case studies based on BC and carbon monoxide (CO) measurements from the Zeppelin observatory appear to confirm flaring as an important BC source that can produce pollution plumes in the Arctic with a high BC / CO enhancement ratio, as expected for this source type. BC measurements taken during a research ship cruise in the White, Barents and Kara seas north of the region with strong flaring emissions reveal very high concentrations of the order of 200–400 ng m−3. The model underestimates these concentrations substantially, which indicates that the flaring emissions (and probably also other emissions in northern Siberia) are rather under- than overestimated in our emission data set. Our results suggest that it may not be \"vertical transport that is too strong or scavenging rates that are too low\" and \"opposite biases in these processes\" in the Arctic and elsewhere in current aerosol models, as suggested in a recent review article (Bond et al., Bounding the role of black carbon in the climate system: a scientific assessment, J. Geophys. Res., 2013), but missing emission sources and lacking time resolution of the emission data that are causing opposite model biases in simulated BC concentrations in the Arctic and in the mid-latitudes.

Key Points Several aspects of the design of phase I trials have evolved in the era of molecular targeted agents to enable better assessment of these novel therapies and maximize the efficiency of drug development Current phase I trial designs increasingly use new dose-escalation approaches and biomarker-driven patient selection, while expanding study objectives to include efficacy evaluation and pharmacokinetics/ pharmacodynamics (PK/PD), in addition to safety Preclinical evidence supporting a biological or pharmacological rationale and exploration of PK/PD interactions between drug partners are necessary for phase I trials of combination therapies that include targeted agents Changes to the regulatory approval process help to expedite drug development, particularly for novel agents with a well-established biological mechanism, a predictive biomarker, and clear evidence of efficacy in early trials Changes in the goals and conduct of phase I trials have resulted in a shift towards multi-institutional studies and centralized management, with a significant impact on the structure of phase I programmes Both the efficiency and rate of drug approval need to improve despite the limited acceptance of novel trial designs and difficulties associated with early phase biomarker integration The improved understanding of the molecular mechanisms that drive tumorigenesis has led to the development of molecularly targeted agents (MTAs) that inhibit specific proteins or pathways. However, the rate of drug approvals remains disappointingly low in oncology. The authors of this Review discuss several aspects of phase I trials that are evolving in the MTA era in order to adapt to the changing nature of cancer therapies and to expedite their clinical translation. Advances in our knowledge of the molecular pathogenesis of cancer have led to increased interest in molecularly targeted agents (MTAs), which target specific oncogenic drivers and are now a major focus of cancer drug development. MTAs differ from traditional cytotoxic agents in various aspects, including their toxicity profiles and the potential availability of predictive biomarkers of response. The landscape of phase I oncology trials is evolving to adapt to these novel therapies and to improve the efficiency of drug development. In this Review, we discuss new strategies used in phase I trial design, such as novel dose-escalation schemes to circumvent limitations of the classic 3 + 3 design and enable faster dose escalation and/or more-precise dose determinations using statistical modelling; improved selection of patients based on genetic or molecular biomarkers; pharmacokinetic and pharmacodynamic analyses; and the early evaluation of efficacy — in addition to safety. Indeed, new expedited approval pathways that can accelerate drug development require demonstration of efficacy in early phase trials. The application of molecular tumour profiling for matched therapy and the testing of drug combinations based on a strong biological rationale are also increasingly seen in phase I studies. Finally, the shift towards multi-institutional trials and centralized study management results in consequent implications for institutions and investigators. These issues are also highlighted herein.

Recent developments in pre-clinical screening tools, that more reliably predict the clinical effects and adverse events of candidate therapeutic agents, has ushered in a new era of drug development and screening. However, given the rapid pace with which these models have emerged, the individual merits of these translational research tools warrant careful evaluation in order to furnish clinical researchers with appropriate information to conduct pre-clinical screening in an accelerated and rational manner. This review assesses the predictive utility of both well-established and emerging pre-clinical methods in terms of their suitability as a screening platform for treatment response, ability to represent pharmacodynamic and pharmacokinetic drug properties, and lastly debates the translational limitations and benefits of these models. To this end, we will describe the current literature on cell culture, organoids, in vivo mouse models, and in silico computational approaches. Particular focus will be devoted to discussing gaps and unmet needs in the literature as well as current advancements and innovations achieved in the field, such as co-clinical trials and future avenues for refinement.

Black carbon (BC) aerosols from incomplete combustion of biomass and fossil fuel contribute to Arctic climate warming. Models—seeking to advise mitigation policy—are challenged in reproducing observations of seasonally varying BC concentrations in the Arctic air. Here we compare year-round observations of BC and its δ 13 C/Δ 14 C-diagnosed sources in Arctic Scandinavia, with tailored simulations from an atmospheric transport model. The model predictions for this European gateway to the Arctic are greatly improved when the emission inventory of anthropogenic sources is amended by satellite-derived estimates of BC emissions from fires. Both BC concentrations (R 2 =0.89, P <0.05) and source contributions (R 2 =0.77, P <0.05) are accurately mimicked and linked to predominantly European emissions. This improved model skill allows for more accurate assessment of sources and effects of BC in the Arctic, and a more credible scientific underpinning of policy efforts aimed at efficiently reducing BC emissions reaching the European Arctic. Black carbon (BC) contributes positively to the radiation budget, yet models are unable to correctly capture its seasonal variability in the Arctic. Here, the authors demonstrate improved model skill in simulating BC concentration and sources when including estimates of BC emissions from fires.

The regeneration of the mucosal interface of the human intestine is critical in the host–gut microbiome crosstalk associated with gastrointestinal diseases. The biopsy-derived intestinal organoids provide genetic information of patients with physiological cytodifferentiation. However, the enclosed lumen and static culture condition substantially limit the utility of patient-derived organoids for microbiome-associated disease modeling. Here, we report a patient-specific three-dimensional (3D) physiodynamic mucosal interface-on-a-chip (PMI Chip) that provides a microphysiological intestinal milieu under defined biomechanics. The real-time imaging and computational simulation of the PMI Chip verified the recapitulation of non-linear luminal and microvascular flow that simulates the hydrodynamics in a living human gut. The multiaxial deformations in a convoluted microchannel not only induced dynamic cell strains but also enhanced particle mixing in the lumen microchannel. Under this physiodynamic condition, an organoid-derived epithelium obtained from the patients diagnosed with Crohn’s disease, ulcerative colitis, or colorectal cancer independently formed 3D epithelial layers with disease-specific differentiations. Moreover, co-culture with the human fecal microbiome in an anoxic–oxic interface resulted in the formation of stochastic microcolonies without a loss of epithelial barrier function. We envision that the patient-specific PMI Chip that conveys genetic, epigenetic, and environmental factors of individual patients will potentially demonstrate the pathophysiological dynamics and complex host–microbiome crosstalk to target a patient-specific disease modeling.

Background Triple-negative breast cancer (TNBC) remains an aggressive breast cancer subtype with limited treatment options. ENMD-2076 is a small-molecule inhibitor of Aurora and angiogenic kinases with proapoptotic and antiproliferative activity in preclinical models of TNBC. Methods This dual-institution, single-arm, two-stage, phase II clinical trial enrolled patients with locally advanced or metastatic TNBC previously treated with one to three prior lines of chemotherapy in the advanced setting. Patients were treated with ENMD-2076 250 mg orally once daily with continuous dosing in 4-week cycles until disease progression or unacceptable toxicity occurred. The primary endpoint was 6-month clinical benefit rate (CBR), and secondary endpoints included progression-free survival, pharmacokinetic profile, safety, and biologic correlates in archival and fresh serial tumor biopsies in a subset of patients. Results Forty-one patients were enrolled. The 6-month CBR was 16.7% (95% CI, 6–32.8%) and included two partial responses. The 4-month CBR was 27.8% (95% CI, 14–45.2%), and the average duration of benefit was 6.5 cycles. Common adverse events included hypertension, fatigue, diarrhea, and nausea. Treatment with ENMD-2076 resulted in a decrease in cellular proliferation and microvessel density and an increase in p53 and p73 expression, consistent with preclinical observations. Conclusions Single-agent ENMD-2076 treatment resulted in partial response or clinical benefit lasting more than 6 months in 16.7% of patients with pretreated, advanced, or metastatic TNBC. These results support the development of predictive biomarkers using archival and fresh tumor tissue, as well as consideration of mechanism-based combination strategies. Trial registration ClinicalTrials.gov, NCT01639248 . Registered on July 12, 2012.

Abstract Context Although the development of immune checkpoint inhibitors has transformed treatment strategies of several human malignancies, research models to study immunotherapy in adrenocortical carcinoma (ACC) are lacking. Objective To explore the effect of anti-PD1 immunotherapy on the alteration of the immune milieu in ACC in a newly generated preclinical model and correlate with the response of the matched patient. Design, Setting, and Intervention To characterize the CU-ACC2-M2B patient-derived xenograft in a humanized mouse model, evaluate the effect of a PD-1 inhibitor therapy, and compare it with the CU-ACC2 patient with metastatic disease. Results Characterization of the CU-ACC2-humanized cord blood-BALB/c-Rag2nullIl2rγnullSirpaNOD model confirmed ACC origin and match with the original human tumor. Treatment of the mice with pembrolizumab demonstrated significant tumor growth inhibition (60%) compared with controls, which correlated with increased tumor infiltrating lymphocyte activity, with an increase of human CD8+ T cells (P < 0.05), HLA-DR+ T cells (P < 0.05) as well as Granzyme B+ CD8+ T cells (<0.001). In parallel, treatment of the CU-ACC2 patient, who had progressive disease, demonstrated a partial response with 79% to 100% reduction in the size of target lesions, and no new sites of metastasis. Pretreatment analysis of the patient's metastatic liver lesion demonstrated abundant intratumoral CD8+ T cells by immunohistochemistry. Conclusions Our study reports the first humanized ACC patient-derived xenograft mouse model, which may be useful to define mechanisms and biomarkers of response and resistance to immune-based therapies, to ultimately provide more personalized care for patients with ACC.