A multitude of chronic diseases are not yet classified as being stochastic or deterministic. The purpose of this work was to provide an adaptative software tool which enables detection of thresholds for the cause-consequence relationships with a maximum degree of confidence given the available statistics. This tool is meant to be tested on radioactivity datasets, for which the thresholds exist and are well-known, then to be applied to other datasets on radio-activity and microplastics (environment), antibiotics (pharmacological factors), and nitrites (food industry). The main algorithm for this supporting program for health research was built as an unitary procedure for all situations, additional covariance analysis on multi-factor cases will be performed, together with a scheme which explicates the importance of transfer factors for the data recorded on various substances (e. g. water-fish-human transfer for radio- activity and microplastics). The key elements are the non-biased datasets available and the algorithms for conditional probability calculations and potential thresholds determination. One very important action to take is separating the accurate and verifiable data from the plethora of biased information from the repositories.
Lead aprons are essential for personal protective equipment used in laboratory environments to protect workers from harmful radiation exposure. A lead apron contains materials meant to attenuate radiation by scattering and absorption during safety involving diagnostic and therapeutic radiation procedures. However, ensuring consistent lead apron usage presents challenges because many facilities rely on manual observation and self-reporting methods especially in busy environments where continuous monitoring is difficult to maintain. Manual monitoring often fails to provide coverage and documentation. Therefore, the convolutional neural network method is used to detect lead apron and provide efficient monitoring systems that help to ensure with radiation protection. This research uses a convolutional neural network model approach designed for small dataset scenarios. Lead apron detection involves binary classification with two categories such as with apron and without apron scenarios. The dataset comprises 295 grayscale images processed at 150 x 150 pixel resolution and annotated for binary classification. From the test result, the model achieved performance with a precision value of 97 %, recall value of 97 %, and F1-score value of 97 %. The model achieving good 95.7 % for lead apron detection and precision score 98.5 % for without apron detection scenarios.
DRHBc Mass Table Collaboration, Peng Guo, Xiaojie Cao
et al.
The mass table in the deformed relativistic Hartree-Bogoliubov theory in continuum (DRHBc) with the PC-PK1 density functional has been established for even-$Z$ nuclei with $8\le Z\le120$, extended from the previous work for even-even nuclei [Zhang $\it{et.~al.}$ (DRHBc Mass Table Collaboration), At. Data Nucl. Data Tables 144, 101488 (2022)]. The calculated binding energies, two-nucleon and one-neutron separation energies, root-mean-square (rms) radii of neutron, proton, matter, and charge distributions, quadrupole deformations, and neutron and proton Fermi surfaces are tabulated and compared with available experimental data. A total of 4829 even-$Z$ nuclei are predicted to be bound, with an rms deviation of 1.477 MeV from the 1244 mass data. Good agreement with the available experimental odd-even mass differences, $α$ decay energies, and charge radii is also achieved. The description accuracy for nuclear masses and nucleon separation energies as well as the prediction for drip lines is compared with the results obtained from other relativistic and nonrelativistic density functional. The comparison shows that the DRHBc theory with PC-PK1 provides an excellent microscopic description for the masses of even-$Z$ nuclei. The systematics of the nucleon separation energies, odd-even mass differences, pairing energies, two-nucleon gaps, $α$ decay energies, rms radii, quadrupole deformations, potential energy curves, neutron density distributions, and neutron mean-field potentials are discussed.
Biogas upgraded to biomethane can provide a renewable gaseous transport fuel and is one of the proposed solutions in meeting the renewable energy supply in transport targets set under the EU Renewable Energy Directive. The upgrading process for biogas involves the removal of CO2. Amine scrubbing is one traditional method of upgrading that is applied due to its low methane slippage and its capability to provide a high purity renewable methane product. However, new technologies such as power to gas (P2G) can also upgrade biogas through biological methanation by combining the CO2 in biogas with H2 to produce renewable methane. The H2 for P2G can be produced through electrolysis of renewable electricity. Through simulation software – SuperPro Designer, the economics of different pathways for upgrading biogas from a grass silage and slurry fed digester are analysed and compared in this paper. Three scenarios were investigated: biogas upgrading through amine scrubbing (scenario 1); biogas upgrading through amine scrubbing with CO2 directed to ex-situ biological methanation (scenario 2) and biogas upgrading through ex-situ biological methanation only (scenario 3). The results show that at a net present value of zero, the minimum selling price (MSP) per m3 of renewable methane for scenario 1, 2 and 3 is €0.76; €1.50 and €1.43, respectively (with an electricity price to produce H2 of €0.10/kWh and a grass silage production cost of €27/t). The electricity price has a significant effect on the cost of renewable methane in both scenarios 2 and 3. The MSP reduces to €1.09 and €1.00 per m3 of renewable methane, respectively for scenarios 2 and 3, if the electricity price is reduced to €0.05/kWh. Since the renewable methane MSP from scenario 2 is higher than scenario 3, it is suggested that direct biogas injection to the methanation reactor is financially more attractive than capturing CO2 from biogas and feeding it to the methanation step. The MSP of renewable methane from both scenarios 2 and 3 are significantly higher than that of scenario 1. However, when considering climate change mitigation, balancing of the electricity network and storage of surplus electricity, utilising P2G can offset some of these costs. The cost of H2 is a significant factor in determining the cost of renewable methane.
The gut microbiome is extremely important for maintaining homeostasis with host intestinal epithelial, neuronal, and immune cells and this host-microbe interaction is critical during times of stress or disease. Environmental, nutritional, and cognitive stress are just a few factors known to influence the gut microbiota and are thought to induce microbial dysbiosis. Research on this bidirectional relationship as it pertains to health and disease is extensive and rapidly expanding in both in vivo and in vitro/ex vivo models. However, far less work has been devoted to studying effects of host-microbe interactions on acute stressors and performance, the underlying mechanisms, and the modulatory effects of different stressors on both the host and the microbiome. Additionally, the use of in vitro/ex vivo models to study the gut microbiome and human performance has not been researched extensively nor reviewed. Therefore, this review aims to examine current evidence concerning the current status of in vitro and ex vivo host models, the impact of acute stressors on gut physiology/microbiota as well as potential impacts on human performance and how we can parlay this information for DoD relevance as well as the broader scientific community. Models reviewed include widely utilized intestinal cell models from human and animal models that have been applied in the past for stress or microbiology research as well as ex vivo organ/tissue culture models and new innovative models including organ-on-a-chip and co-culture models.
Silvia Costa is a journalist and a centre-left politician, she was elected in 2009 at the European Parliament within the SD coalition and from 2020 is the Government Commissioner for the preservation and re-purposing of the ex-prison complex on the island of Santo Stefano. The Ventotene-Santo Stefano project, which has just been dedicated to former EU Parliament President David Sassoli, seeks to preserve material and memorial legacies of two sites of confinement where the very idea of European Union was conceived.
Natural killer (NK) cells are a promising tool for the use in adoptive immunotherapy, since they efficiently recognize and kill tumor cells. In this context, ex vivo cultivation is an attractive option to increase NK cells in numbers and to improve their antitumor potential prior to clinical applications. Consequently, various strategies to generate NK cells for adoptive immunotherapy have been developed. Here, we give an overview of different NK cell cultivation approaches and their impact on shaping the NK cell antitumor activity. So far, the cytokines interleukin (IL)-2, IL-12, IL-15, IL-18, and IL-21 are used to culture and expand NK cells. The selection of the respective cytokine combination is an important factor that directly affects NK cell maturation, proliferation, survival, distribution of NK cell subpopulations, activation, and function in terms of cytokine production and cytotoxic potential. Importantly, cytokines can upregulate the expression of certain activating receptors on NK cells, thereby increasing their responsiveness against tumor cells that express the corresponding ligands. Apart from using cytokines, cocultivation with autologous accessory non-NK cells or addition of growth-inactivated feeder cells are approaches for NK cell cultivation with pronounced effects on NK cell activation and expansion. Furthermore, ex vivo cultivation was reported to prime NK cells for the killing of tumor cells that were previously resistant to NK cell attack. In general, NK cells become frequently dysfunctional in cancer patients, for instance, by downregulation of NK cell activating receptors, disabling them in their antitumor response. In such scenario, ex vivo cultivation can be helpful to arm NK cells with enhanced antitumor properties to overcome immunosuppression. In this review, we summarize the current knowledge on NK cell modulation by different ex vivo cultivation strategies focused on increasing NK cytotoxicity for clinical application in malignant diseases. Moreover, we critically discuss the technical and regulatory aspects and challenges underlying NK cell based therapeutic approaches in the clinics.
Optimal patient stratification is of utmost importance in the era of personalized medicine. Prediction of individual treatment responses by functional ex vivo assays requires model systems derived from viable tumor samples, which should closely resemble in vivo tumor characteristics and microenvironment. This review discusses a broad spectrum of model systems, ranging from classic 2D monolayer culture techniques to more experimental ‘cancer-on-chip’ procedures. We mainly focus on organotypic tumor slices that take tumor heterogeneity and tumor–stromal interactions into account. These 3D model systems can be exploited for patient selection as well as for fundamental research. Selection of the right model system for each specific research endeavor is crucial and requires careful balancing of the pros and cons of each technology.
The Convention on Biological Diversity's target of halting extinctions by 2020 is less than a handful of years away. Captive, or ex situ, management has long been cited as having a potential role to play in the recovery of species, although this remains the subject of debate. IUCN's Species Survival Commission (IUCN SSC) produced guidelines to assist in identifying when ex situ management may contribute to species recovery in 2002. Since then, there have been considerable developments in a range of areas that may influence the design of such programs (e.g., understanding of constraints on breeding programs, development of new techniques and approaches, and strategic planning approaches to species conservation). IUCN SSC has therefore revised its guidance and proposes a five‐step process: (1) compile a status review; (2) define the role(s) that ex situ management might play; (3) determine the precise nature of the ex situ population in order to meet identified role(s); (4) define resources and expertise, and appraise the feasibility and risks; and (5) make a decision that is informed based on the above analysis and transparent. These guidelines offer an objective process for considering the role of ex situ management in species conservation.
Summary Ex vivo gene therapy based on CD34+ hematopoietic stem cells (HSCs) has shown promising results in clinical trials, but genetic engineering to high levels and in large scale remains challenging. We devised a sorting strategy that captures more than 90% of HSC activity in less than 10% of mobilized peripheral blood (mPB) CD34+ cells, and modeled a transplantation protocol based on highly purified, genetically engineered HSCs co-infused with uncultured progenitor cells. Prostaglandin E2 stimulation allowed near-complete transduction of HSCs with lentiviral vectors during a culture time of less than 38 hr, mitigating the negative impact of standard culture on progenitor cell function. Exploiting the pyrimidoindole derivative UM171, we show that transduced mPB CD34+CD38− cells with repopulating potential could be expanded ex vivo. Implementing these findings in clinical gene therapy protocols will improve the efficacy, safety, and sustainability of gene therapy and generate new opportunities in the field of gene editing.
PurposeA large proportion of the environmental impacts of a technology is determined by decisions made at the early development stages. Therefore, effective approaches to grasp the potential environmental performance of a technology early in development are needed. This paper reflects on the usefulness of ex ante application of LCA using a case study on the appraisal of the potential environmental impacts of a lab-scale novel process for bioleaching of e-waste for metal recovery.MethodsThe LCA framework was applied at an early stage to the novel bioleaching process to embed it in a life cycle context, linking it to upstream and downstream flows. Then, a short-term future scaled-up scenario was defined using a proxy technology and estimated data. Environmental hotspots of this scenario were identified, and its environmental impacts were compared with those of a current industrial pyrometallurgical technique, involving an integrated smelter refinery.Results and discussionLCA displays potential environmental hotspots related to energy and material inputs for the bioleaching process and solvents for copper recovery, despite uncertainties. Comparison with an existing integrated smelter refinery technology returned an inferior environmental performance. These results could not be considered accurate given the early-stage application, yet they served as valuable preliminary information. The uncertainties also prompted further enquiry about the chosen product system boundary, the role of the emerging technology and the comparability of the technologies.ConclusionsThe ex ante application of life cycle assessment on an emerging technology brings a systematic rigour and discipline to an ambiguous situation at the start of technological development. Applying the LCA framework broadens the scope of the research, introducing a systems approach and long-term view. Environmental aspects and alternative perspectives on the novel technology are also brought into the research domain. The approach creates new knowledge on the novel technology’s potential development, and developmental challenges are given definition at an early stage.The LCA outcomes should not be regarded as a final result but have a signalling purpose as a contribution to technological development. Though imprecise with much conjecture involved, such an approach gives a valid mock-up of a plausible future providing useful provisional insights to be built upon. Applying ex ante LCA and an exploratory scenario to an emerging technology is of great service as a developmental design tool and can be further refined in later development stages.