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Sulfur cycling is known to control the speciation and bioavailability of copper in the environment via inorganic sulfur oxidation and reduction. However, it remains unclear how the mineralization of organic sulfur and associated microbial processes affect Cu transformations. This study discovered a neglected mechanism that mediates Cu mobility and speciation via cysteine mineralization in a paddy soil. We provide evidence for a pathway of sulfide production from cysteine via indigenous soil microorganisms. The produced sulfide promotes the formation of copper sulfide nanoparticles, constituting an alternative copper sulfide formation mechanism that bypasses sulfate reduction. A bacterium isolated from the soil, named Bacillus sp. TR1, played a role in forming cell-associated copper sulfide nanoparticles. A metagenomics approach was applied to detect genes related to cysteine mineralization (dcyD, CTH, CBS, and sseA) and the associated microbes in the soil. The sseA gene was most abundant, and the microorganisms involved in cysteine mineralization were taxonomically diverse, including members of phyla Proteobacteria, Firmicutes, and Thaumarchaeota. Geobacter, Sulfuriferula, Nitrososphaera, Noviherbaspirillum, and Clostridium were the dominant genera with potential to metabolize cysteine to form copper sulfide nanoparticles. Our study not only provides initial molecular-level insights into the abundance, diversity, and metabolism of cysteine-mineralizing microorganisms but also highlights their important ecological functions in metal and sulfur biogeochemical cycles.

Direct discharge of chromium-containing waste water and improper disposal of waste residues in industrial sites may lead to the vertical migration of metals into aquifers, posing serious threat to soil-groundwater system. The heterogeneity in soil profile further aggravates the complexity and unpredictability of this transport process. However, topsoil was the main focus of most studies. Herein, the vertical transport and transformation of Cr in soils at different depths in three industrial sites (i.e., Shijiazhuang, Zhuzhou, and Guangzhou) were investigated to delineate Cr transport and retention characteristics under complex conditions. Regional and vertical differences in soil properties led to the specificity in Cr migration behaviors among these three sites. Correlation analysis showed that soil pH (r = −0.909, p < 0.05) and Fe content (r = 0.949, p < 0.01) were the major controlling factors of Cr(VI) migration and transformation in aquifers. Furthermore, the soil of Zhuzhou site showed the maximum adsorption capacity for Cr(VI) (0.225 mol/kg), and the strongest reduction ability of Cr(VI) was observed in the Guangzhou soil. Results of model-based long-term forecast indicated that the Cr(III) concentration in the liquid phase of Guangzhou subsoil could reach 0.08 mol/m3 within 20 years. Heavier rainfall condition exacerbated the contamination due to an increased pollutant flux and enhanced convection. Specially, Cr was fixed in the topsoil of Zhuzhou site with the formation of PbCrO4 and presented least vertical migration risk. The conclusions above can provide scientific theoretical guidance for heavy metal pollution prevention and control in industrial contaminated regions.

Machine learning (ML) algorithms are being increasingly used in Earth and Environmental modeling studies owing to the ever-increasing availability of diverse data sets and computational resources as well as advancement in ML algorithms. Despite advances in their predictive accuracy, the usefulness of ML algorithms for inference remains elusive. In this study, we employ two popular ML algorithms, artificial neural networks and random forest, to analyze a large data set of flood events across Germany with the goals to analyze their predictive accuracy and their usability to provide insights to hydrologic system functioning. The results of the ML algorithms are contrasted against a parametric approach based on multiple linear regression. For analysis, we employ a model-agnostic framework named Permuted Feature Importance to derive the influence of models' predictors. This allows us to compare the results of different algorithms for the first time in the context of hydrology. Our main findings are that (1) the ML models achieve higher prediction accuracy than linear regression, (2) the results reflect basic hydrological principles, but (3) further inference is hindered by the heterogeneity of results across algorithms. Thus, we conclude that the problem of equifinality as known from classical hydrological modeling also exists for ML and severely hampers its potential for inference. To account for the observed problems, we propose that when employing ML for inference, this should be made by using multiple algorithms and multiple methods, of which the latter should be embedded in a cross-validation routine., Zweitver��ffentlichungen der Universit��t Potsdam : Mathematisch-Naturwissenschaftliche Reihe; 1193

Background In 2006, the Bowel Cancer Screening Programme (BCSP) in England began offering biennial faecal occult blood testing (FOBt) at ages 60–69 years. Although FOBt is aimed at detecting colorectal neoplasms, other conditions can affect the result. In a large UK prospective study, we examined associations, both before and after screening, between FOBt positivity and 10 conditions that are often associated with gastrointestinal bleeding. Methods By electronically linking BCSP and Million Women Study records, we identified 604 495 women without previous colorectal cancer who participated in their first routine FOBt screening between 2006 and 2012. Regression models, using linked national hospital admission records, yielded adjusted relative risks (RRs) in FOBt-positive versus FOBt-negative women for colorectal cancer, adenoma, diverticular disease, inflammatory bowel disease, haemorrhoids, upper gastrointestinal cancer, oesophagitis, peptic ulcer, anaemia and other haematological disorders. Results RRs in FOBt-positive versus FOBt-negative women were 201.3 (95% CI 173.8–233.2) for colorectal cancer and 197.9 (95% CI 180.6–216.8) for adenoma within 12 months after screening and 3.49 (95% CI 2.31–5.26) and 4.88 (95% CI 3.80–6.26), respectively, 12–24 months after screening; P

Faecal occult blood (FOB) ‐ based screening programmes for colorectal cancer detect about half of all cancers. Little is known about individual health behavioural characteristics which may be associated with screen‐detected and interval cancers. Electronic linkage between the UK National Health Service Bowel Cancer Screening Programme (BCSP) in England, cancer registration and other national health records, and a large on‐going UK cohort, the Million Women Study, provided data on 628,976 women screened using a guaiac‐FOB test (gFOBt) between 2006 and 2012. Relative risks (RRs) and 95% confidence intervals (CIs) were estimated by logistic and Cox regression for associations between individual lifestyle factors and risk of colorectal tumours. Among screened women, 766 were diagnosed with screen‐detected colorectal cancer registered within 2 years after a positive gFOBt result, and 749 with interval colorectal cancers registered within 2 years after a negative gFOBt result. Current smoking was significantly associated with risk of interval cancer (RR 1.64, 95%CI 1.35–1.99) but not with risk of screen‐detected cancer (RR 1.03, 0.84–1.28), and was the only factor of eight examined to show a significant difference in risk between interval and screen‐detected cancers (p for difference, 0.003). Compared to screen‐detected cancers, interval cancers tended to be sited in the proximal colon or rectum, to be of non‐adenocarcinoma morphology, and to be of higher stage.

The Australian National Bowel Cancer Screening Program (NBCSP) will fully roll‐out 2‐yearly screening using the immunochemical Faecal Occult Blood Testing (iFOBT) in people aged 50 to 74 years by 2020. In this study, we aimed to estimate the comparative health benefits, harms, and cost‐effectiveness of screening with iFOBT, versus other potential alternative or adjunctive technologies. A comprehensive validated microsimulation model, Policy1‐Bowel, was used to simulate a total of 13 screening approaches involving use of iFOBT, colonoscopy, sigmoidoscopy, computed tomographic colonography (CTC), faecal DNA (fDNA) and plasma DNA (pDNA), in people aged 50 to 74 years. All strategies were evaluated in three scenarios: (i) perfect adherence, (ii) high (but imperfect) adherence, and (iii) low adherence. When assuming perfect adherence, the most effective strategies involved using iFOBT (annually, or biennially with/without adjunct sigmoidoscopy either at 50, or at 54, 64 and 74 years for individuals with negative iFOBT), or colonoscopy (10‐yearly, or once‐off at 50 years combined with biennial iFOBT). Colorectal cancer incidence (mortality) reductions for these strategies were 51–67(74–80)% in comparison with no screening; 2‐yearly iFOBT screening (i.e. the NBCSP) would be associated with reductions of 51(74)%. Only 2‐yearly iFOBT screening was found to be cost‐effective in all scenarios in context of an indicative willingness‐to‐pay threshold of A$50,000/life‐year saved (LYS); this strategy was associated with an incremental cost‐effectiveness ratio of A$2,984/LYS–A$5,981/LYS (depending on adherence). The fully rolled‐out NBCSP is highly cost‐effective, and is also one of the most effective approaches for bowel cancer screening in Australia.

The capability to accurately yet efficiently represent atmospheric nanoparticle growth by biogenic and anthropogenic secondary organics is a challenge for current atmospheric large-scale models. It is, however, crucial to predict nanoparticle growth accurately in order to reliably estimate the atmospheric cloud condensation nuclei (CCN) concentrations. In this work we introduce a simple semi-empirical parameterization for sub-20 nm particle growth that distributes secondary organics to the nanoparticles according to their size and is therefore able to reproduce particle growth observed in the atmosphere. The parameterization includes particle growth by sulfuric acid, secondary organics from monoterpene oxidation (SORGMT) and an additional condensable vapor of non-monoterpene organics ("background"). The performance of the proposed parameterization was investigated using ambient data on particle growth rates in three diameter ranges (1.5–3 nm, 3–7 nm and 7–20 nm). The growth rate data were acquired from particle/air ion number size distribution measurements at six continental sites over Europe. The longest time series of 7 yr (2003–2009) was obtained from a boreal forest site in Hyytiälä, Finland, while about one year of data (2008–2009) was used for the other stations. The extensive ambient measurements made it possible to test how well the parameterization captures the seasonal cycle observed in sub-20 nm particle growth and to determine the weighing factors for distributing the SORGMT for different sized particles as well as the background mass flux (concentration). Besides the monoterpene oxidation products, background organics with a concentration comparable to SORGMT, around 6 × 107 cm−3 (consistent with an additional global SOA yield of 100 Tg yr−1) was needed to reproduce the observed nanoparticle growth. Simulations with global models suggest that the "background" could be linked to secondary biogenic organics that are formed in the presence of anthropogenic pollution.

Precise regulation of cell cycle events by the Cdk-control network is essential for cell proliferation and the perpetuation of life. The unidirectionality of cell cycle progression is governed by several critical irreversible transitions: the G1-to-S transition, the G2-to-M transition, and the M-to-G1 transition. Recent experimental and theoretical evidence has pulled into question the consensus view that irreversible protein degradation causes the irreversibility of those transitions. A new view has started to emerge, which explains the irreversibility of cell cycle transitions as a consequence of systems-level feedback rather than of proteolysis.This thesis applies mathematical modelling approaches to test this proposal for the Mto- G1 transition, which consists of two consecutive irreversible substeps: the metaphase-to-anaphase transition, and mitotic exit. The main objectives of the present work were: (i) to develop deterministic models to identify the essential molecular feedback loops and to examine their roles in the irreversibility of the M-to-G1 transition; (ii) to present a straightforward and reliable workflow to translate deterministic models of reaction networks into stochastic models; (iii) to explore the effects of noise on the cell cycle transitions using stochastic models, and to compare the deterministic and the stochastic approaches.In the first part of this thesis, I constructed a simplified deterministic model of the metaphase-to-anaphase transition, which is mainly regulated by the spindle assembly checkpoint (the SAC). Based on the essential feedback loops causing the bistability of the transition, this deterministic model provides explanations for three open questions regarding the SAC: Why is the SAC not reactivated when the kinetochore tension decreases to zero at anaphase onset? How can a single unattached kinetochore keep the SAC active? How is the synchronized and abrupt destruction of cohesin triggered?This deterministic model was then translated into a stochastic model of the SAC by treating the kinetochore microtubule attachment at prometaphase as a noisy process. The stochastic model was analyzed and simulation results were compared to the experimental data, with the aim of explaining the mitotic timing regulation by the SAC. Our model works remarkably well in qualitatively explaining experimental key findings and also makes testable predictions for different cell lines with very different number of chromosomes. The noise generated from the chemical interactions was found to only perturb the transit timing of the mitotic events, but not their ultimate outcomes: all cells eventually undergo anaphase, however, the time required to satisfy the SAC differs between cells due to stochastic effects.In the second part of the thesis, stochastic models of mitotic exit were created for two model organisms, budding yeast and mammalian cells. I analyzed the role of noise in mitotic exit at both the single-cell and the population level. Stochastic time series simulations of the models are able to explain the phenomenon of reversible mitotic exit, which is observed under specific experimental conditions in both model organisms. In spite of the fact that the detailed molecular networks of mitotic exit are very different in budding yeast and mammalian cells, their dynamic properties are similar. Importantly, bistability of the transitions is successfully captured also in the stochastic models.This work strongly supports the hypothesis that uni-directional cell cycle progression is a consequence of systems-level feedback in the cell cycle control system. Systems-level feedback creates alternative steady states, which allows cells to accomplish irreversible transitions, such as the M-to-G1 transition studied here. We demonstrate that stochastic models can serve as powerful tools to capture and study the heterogeneity of dynamical features among individual cells. In this way, stochastic simulations not only complement the deterministic approach, but also help to obtain a better understanding of mechanistic aspects. We argue that the effects of noise and the potential needs for stochastic simulations should not be overlooked in studying dynamic features of biological systems.

The ARGO-YBJ experiment is an air shower detector for gamma ray astronomy and cosmic ray studies with an energy threshold of ∼500 GeV. Working in “single particle mode”, i.e. counting the single particles hitting the detector at fixed time intervals, ARGO-YBJ can monitor cosmic ray and gamma ray transients at energies of a few GeV. The single particle counting rate is modulated by the atmospheric pressure and temperature, and is affected by the local radioactivity from soil and air. Among the radioactive elements, radon gas is of particular importance since its concentration in air can vary significantly, according to environmental conditions. In this paper we evaluate the contribution of the radon daughter gamma ray emitters to the single particle counting rate measured by ARGO-YBJ. According to our analysis, the radon gas contribution is roughly 1–2%, producing a counting rate modulation of the same order of magnitude of the atmospheric effects.

Background and purpose: Orthostatic hypotension has been observed when PDE 5 (cGMP-specific phosphodiesterase type 5) inhibitors are co-administered with α-adrenoceptor antagonists. Here we assessed the pharmacokinetic and haemodynamic interactions between udenafil and tamsulosin in rats, as both drugs are metabolized via rat hepatic cytochrome P450 3A1/2. Experimental approach: Interactions between the two drugs were evaluated in rats after simultaneous 1 or 15 min i.v. infusion or after p.o. administration of udenafil (30 mg·kg−1) and/or tamsulosin (1 mg·kg−1). In vitro metabolism of tamsulosin with udenafil was measured to obtain the inhibition constant (Ki) and [I]/Ki ratio of udenafil. Key results: The total area under the plasma concentration–time curve from time zero to time infinity (AUC)s (or AUC0–4h) of tamsulosin were significantly greater after 15 min of i.v. infusion or after oral administration with udenafil, compared with tamsulosin alone. The hepatic first-pass metabolism of tamsulosin was inhibited by udenafil, and the inhibition in vitro was in a non-competitive mode. The arterial systolic blood pressure was significantly lower at 5, 10 and 60 min after oral co-administration of the drugs. Conclusions and implications: The significantly greater AUC of tamsulosin after i.v. and p.o. administration of both drugs may be attributable to non-competitive inhibition of cytochrome P450 3A1/2-mediated hepatic tamsulosin metabolism by udenafil. The inhibition was also observed in human liver S9 fractions, suggesting that a reassessment of the oral dosage of tamsulosin is necessary when udenafil and tamsulosin are co-administered to patients with benign prostatic hyperplasia.

Allosensitized children listed with a requirement for a negative prospective crossmatch have high mortality. Previously we found that listing with the intent to accept the first suitable organ offer, regardless of the possibility of a positive crossmatch (TAKE strategy), results in a survival advantage from the time of listing as compared to awaiting transplantation across a negative crossmatch (WAIT). The cost-effectiveness of these strategies is unknown. We used Markov modeling to compare cost-effectiveness between these waitlist strategies for allosensitized children listed urgently for heart transplantation. We used registry data to estimate costs and waitlist/post-transplant outcomes. We assumed patients remained in hospital after listing, no positive crossmatches for WAIT, and a base-case probability of a positive crossmatch of 47% for TAKE. Accepting the first suitable organ offer cost less ($405,904 versus $534,035) and gained more quality-adjusted life years (3.71 versus 2.79). In sensitivity analyses, including substitution of waitlist data from children with unacceptable antigens specified during listing, TAKE remained cost-saving or cost-effective. Our findings suggest acceptance of the first suitable organ offer for urgently listed allosensitized pediatric heart transplant candidates is cost-effective and transplantation should not be denied because of allosensitization status alone.

The use of the free ion approach to quantify the toxic effects of Cd and Ni to the earthworms Lumbricus rubellus and Aporrectodea longa exposed in soils of different types was explored. Median lethal concentration (LC50) of Cd (expressed as the total concentration in soil) varied by approximately 11-fold and 28-fold for L. rubellus and A. longa, respectively. For Ni, these values were 50-fold and 38-fold, respectively. For the 2 earthworm species, no significant influence of cations (H