Plant cell packs: a scalable platform for recombinant protein production and metabolic engineering

Industrial plant biotechnology applications include the production of sustainable fuels, complex metabolites and recombinant proteins, but process development can be impaired by a lack of reliable and scalable screening methods. Here, we describe a rapid and versatile expression system which involves the infusion of Agrobacterium tumefaciens into three‐dimensional, porous plant cell aggregates deprived of cultivation medium, which we have termed plant cell packs (PCPs). This approach is compatible with different plant species such as Nicotiana tabacum BY2, Nicotiana benthamiana or Daucus carota and 10‐times more effective than transient expression in liquid plant cell culture. We found that the expression of several proteins was similar in PCPs and intact plants, for example, 47 and 55 mg/kg for antibody 2G12 expressed in BY2 PCPs and N. tabacum plants respectively. Additionally, the expression of specific enzymes can either increase the content of natural plant metabolites or be used to synthesize novel small molecules in the PCPs. The PCP method is currently scalable from a microtiter plate format suitable for high‐throughput screening to 150‐mL columns suitable for initial product preparation. It therefore combined the speed of transient expression in plants with the throughput of microbial screening systems. Plant cell packs therefore provide a convenient new platform for synthetic biology approaches, metabolic engineering and conventional recombinant protein expression techniques that require the multiplex analysis of several dozen up to hundreds of constructs for efficient product and process development

Nonequilibrium control of thermal and mechanical changes in a levitated system

Fluctuation theorems are fundamental extensions of the second law of thermodynamics for small nonequilibrium systems. While work and heat are equally important forms of energy exchange, fluctuation relations have not been experimentally assessed for the generic situation of simultaneous mechanical and thermal changes. Thermal driving is indeed generally slow and more difficult to realize than mechanical driving. We here use feedback cooling techniques to implement fast and controlled temperature variations of an underdamped levitated microparticle that are one order of magnitude faster than the equilibration time. Combining mechanical and thermal control, we verify the validity of a fluctuation theorem that accounts for both contributions, well beyond the range of linear response theory. Our system allows the investigation of general far-from-equilibrium processes in microscopic systems that involve fast mechanical and thermal changes at the same time

Measurement of single nanoparticle anisotropy by laser induced optical alignment and Rayleigh scattering for determining particle morphology

We demonstrate the measurement of nanoparticle anisotropy by angularly resolved Rayleigh scattering of single optical levitated particles that are oriented in space via the trapping light in vacuum. This technique is applied to a range of particle geometries from perfect spherical nanodroplets to octahedral nanocrystals. We show that this method can resolve shape differences down to a few nanometers and be applied in both low-damping environments, as demonstrated here, and in traditional overdamped fluids used in optical tweezers

Predictive Value of HAS-BLED Score Regarding Bleeding Events and Graft Survival following Renal Transplantation

Objective: Due to the high prevalence and incidence of cardio- and cerebrovascular diseases among dialysis-dependent patients with end-stage renal disease (ERSD) scheduled for kidney transplantation (KT), the use of antiplatelet therapy (APT) and/or anticoagulant drugs in this patient population is common. However, these patients share a high risk of complications, either due to thromboembolic or bleeding events, which makes adequate peri- and post-transplant anticoagulation management challenging. Predictive clinical models, such as the HAS-BLED score developed for predicting major bleeding events in patients under anticoagulation therapy, could be helpful tools for the optimization of antithrombotic management and could reduce peri- and postoperative morbidity and mortality. Methods: Data from 204 patients undergoing kidney transplantation (KT) between 2011 and 2018 at the University Hospital Leipzig were retrospectively analyzed. Patients were stratified and categorized postoperatively into the prophylaxis group (group A)—patients without pretransplant anticoagulation/antiplatelet therapy and receiving postoperative heparin in prophylactic doses—and into the (sub)therapeutic group (group B)—patients with postoperative continued use of pretransplant antithrombotic medication used (sub)therapeutically. The primary outcome was the incidence of postoperative bleeding events, which was evaluated for a possible association with the use of antithrombotic therapy. Secondary analyses were conducted for the associations of other potential risk factors, specifically the HAS-BLED score, with allograft outcome. Univariate and multivariate logistic regression as well as a Cox proportional hazard model were used to identify risk factors for long-term allograft function, outcome and survival. The calibration and prognostic accuracy of the risk models were evaluated using the Hosmer–Lemshow test (HLT) and the area under the receiver operating characteristic curve (AUC) model. Results: In total, 94 of 204 (47%) patients received (sub)therapeutic antithrombotic therapy after transplantation and 108 (53%) patients received prophylactic antithrombotic therapy. A total of 61 (29%) patients showed signs of postoperative bleeding. The incidence (p < 0.01) and timepoint of bleeding (p < 0.01) varied significantly between the different antithrombotic treatment groups. After applying multivariate analyses, pre-existing cardiovascular disease (CVD) (OR 2.89 (95% CI: 1.02–8.21); p = 0.04), procedure-specific complications (blood loss (OR 1.03 (95% CI: 1.0–1.05); p = 0.014), Clavien–Dindo classification > grade II (OR 1.03 (95% CI: 1.0–1.05); p = 0.018)), HAS-BLED score (OR 1.49 (95% CI: 1.08–2.07); p = 0.018), vit K antagonists (VKA) (OR 5.89 (95% CI: 1.10–31.28); p = 0.037), the combination of APT and therapeutic heparin (OR 5.44 (95% CI: 1.33–22.31); p = 0.018) as well as postoperative therapeutic heparin (OR 3.37 (95% CI: 1.37–8.26); p < 0.01) were independently associated with an increased risk for bleeding. The intraoperative use of heparin, prior antiplatelet therapy and APT in combination with prophylactic heparin was not associated with increased bleeding risk. Higher recipient body mass index (BMI) (OR 0.32 per 10 kg/m2 increase in BMI (95% CI: 0.12–0.91); p = 0.023) as well as living donor KT (OR 0.43 (95% CI: 0.18–0.94); p = 0.036) were associated with a decreased risk for bleeding. Regarding bleeding events and graft failure, the HAS-BLED risk model demonstrated good calibration (bleeding and graft failure: HLT: chi-square: 4.572, p = 0.802, versus chi-square: 6.52, p = 0.18, respectively) and moderate predictive performance (bleeding AUC: 0.72 (0.63–0.79); graft failure: AUC: 0.7 (0.6–0.78)). Conclusions: In our current study, we could demonstrate the HAS-BLED risk score as a helpful tool with acceptable predictive accuracy regarding bleeding events and graft failure following KT. The intensified monitoring and precise stratification/assessment of bleeding risk factors may be helpful in identifying patients at higher risks of bleeding, improved individualized anticoagulation decisions and choices of antithrombotic therapy in order to optimize outcome after kidney transplantatio

Подбор оборудования для эксплуатации скважин в условиях активного выноса песка на нефтяных месторождениях Западной Сибири

Цель работы – анализ известных представлений по проблеме пескопроявления в процессе эксплуатации скважин; анализ технологических и технических решений для борьбы с пескопроявлением. В результате даны рекомендации по использованию того или иного оборудования для получения наилучшего эффекта. Область применения: скважины, характеризующиеся высоким количеством песчаных частиц в извлекаемом флюиде, а также скважины, вскрывающие слабосцементированные песчаные породы.The purpose of the work is the analysis of well-known ideas on the problem of sand occurrence during the operation of wells; analysis of technologies and technical solutions for sand control. For the best effect. Scope: wells characterized by a high content of sand particles in the recovered fluid, as well as wells revealing weakly cemented sand formations

Deep learning for detection of radiographic sacroiliitis: achieving expert-level performance

Background: Radiographs of the sacroiliac joints are commonly used for the diagnosis and classification of axial spondyloarthritis. The aim of this study was to develop and validate an artificial neural network for the detection of definite radiographic sacroiliitis as a manifestation of axial spondyloarthritis (axSpA). Methods: Conventional radiographs of the sacroiliac joints obtained in two independent studies of patients with axSpA were used. The first cohort comprised 1553 radiographs and was split into training (n = 1324) and validation (n = 229) sets. The second cohort comprised 458 radiographs and was used as an independent test dataset. All radiographs were assessed in a central reading session, and the final decision on the presence or absence of definite radiographic sacroiliitis was used as a reference. The performance of the neural network was evaluated by calculating areas under the receiver operating characteristic curves (AUCs) as well as sensitivity and specificity. Cohen's kappa and the absolute agreement were used to assess the agreement between the neural network and the human readers. Results: The neural network achieved an excellent performance in the detection of definite radiographic sacroiliitis with an AUC of 0.97 and 0.94 for the validation and test datasets, respectively. Sensitivity and specificity for the cut-off weighting both measurements equally were 88% and 95% for the validation and 92% and 81% for the test set. The Cohen's kappa between the neural network and the reference judgements were 0.79 and 0.72 for the validation and test sets with an absolute agreement of 90% and 88%, respectively. Conclusion: Deep artificial neural networks enable the accurate detection of definite radiographic sacroiliitis relevant for the diagnosis and classification of axSpA

Understanding the uncertainty in global forest carbon turnover

The length of time that carbon remains in forest biomass is one of the largest uncertainties in the global carbon cycle, with both recent historical baselines and future responses to environmental change poorly constrained by available observations. In the absence of large-scale observations, models used for global assessments tend to fall back on simplified assumptions of the turnover rates of biomass and soil carbon pools. In this study, the biomass carbon turnover times calculated by an ensemble of contemporary terrestrial biosphere models (TBMs) are analysed to assess their current capability to accurately estimate biomass carbon turnover times in forests and how these times are anticipated to change in the future. Modelled baseline 1985-2014 global average forest biomass turnover times vary from 12.2 to 23.5 years between TBMs. TBM differences in phenological processes, which control allocation to, and turnover rate of, leaves and fine roots, are as important as tree mortality with regard to explaining the variation in total turnover among TBMs. The different governing mechanisms exhibited by each TBM result in a wide range of plausible turnover time projections for the end of the century. Based on these simulations, it is not possible to draw robust conclusions regarding likely future changes in turnover time, and thus biomass change, for different regions. Both spatial and temporal uncertainty in turnover time are strongly linked to model assumptions concerning plant functional type distributions and their controls. Thirteen model-based hypotheses of controls on turnover time are identified, along with recommendations for pragmatic steps to test them using existing and novel observations. Efforts to resolve uncertainty in turnover time, and thus its impacts on the future evolution of biomass carbon stocks across the world\u27s forests, will need to address both mortality and establishment components of forest demography, as well as allocation of carbon to woody versus non-woody biomass growth

Literatur-Rundschau

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Migraine aura: retracting particle-like waves in weakly susceptible cortex

Cortical spreading depression (SD) has been suggested to underlie migraine aura. Despite a precise match in speed, the spatio-temporal patterns of SD and aura symptoms on the cortical surface ordinarily differ in aspects of size and shape. We show that this mismatch is reconciled by utilizing that both pattern types bifurcate from an instability point of generic reaction-diffusion models. To classify these spatio-temporal pattern we suggest a susceptibility scale having the value [sigma]=1 at the instability point. We predict that human cortex is only weakly susceptible to SD ([sigma]&#x3c;1), and support this prediction by directly matching visual aura symptoms with anatomical landmarks using fMRI retinotopic mapping. We discuss the increased dynamical repertoire of cortical tissue close to [sigma]=1, in particular, the resulting implications on migraine pharmacology that is hitherto tested in the regime ([sigma]&#x3e;&#x3e;1), and potentially silent aura occurring below a second bifurcation point at [sigma]=0 on the susceptible scale