WETLANDS AND AGRICULTURE

SUMMARY

Emphasis is given to the importance of wetlands and the need for a rational and multi-use approach to their development. Their occurence in the landscape is explained and a brief account is given of characteristic soils and other related features.

Wetlands are widely distributed in certain landscapes and generally have high agricultural potential, especially for the production of cultivated pastures. A large proportion of the vleis in Natal have already been developed.

Important principles and procedures to be considered in planning wetland development are presented. The urgent need to develop a wetland strategy, initiate appropriate research, apply effective legislation and identify wetlands in need of total protection is stressed.     

Aspergillus antigen induces robust Th2 cytokine production,inflammation, airway hyperreactivity and fibrosis in the absence of MCP-1 or CCR2

BackgroundAsthma is characterized by type 2 T-helper cell (Th2) inflammation, goblet cell hyperplasia, airway hyperreactivity, and airway fibrosis. Monocyte chemoattractant protein-1 (MCP-1 or CCL2) and its receptor, CCR2, have been shown to play important roles in the development of Th2 inflammation. CCR2-deficient mice have been found to have altered inflammatory and physiologic responses in some models of experimental allergic asthma, but the role of CCR2 in contributing to inflammation and airway hyperreactivity appears to vary considerably between models. Furthermore, MCP-1-deficient mice have not previously been studied in models of experimental allergic asthma.MethodsTo test whether MCP-1 and CCR2 are each required for the development of experimental allergic asthma, we applied an Aspergillus antigen-induced model of Th2 cytokine-driven allergic asthma associated with airway fibrosis to mice deficient in either MCP-1 or CCR2. Previous studies with live Aspergillus conidia instilled into the lung revealed that MCP-1 and CCR2 play a role in anti-fungal responses; in contrast, we used a non-viable Aspergillus antigen preparation known to induce a robust eosinophilic inflammatory response.ResultsWe found that wild-type C57BL/6 mice developed eosinophilic airway inflammation, goblet cell hyperplasia, airway hyperreactivity, elevations in serum IgE, and airway fibrosis in response to airway challenge with Aspergillus antigen. Surprisingly, mice deficient in either MCP-1 or CCR2 had responses to Aspergillus antigen similar to those seen in wild-type mice, including production of Th2 cytokines.ConclusionWe conclude that robust Th2-mediated lung pathology can occur even in the complete absence of MCP-1 or CCR2.     

The antiepileptic potential of Vateria indica Linn in experimental animal models: Effect on brain GABA levels and molecular mechanisms

BackgroundEpilepsy is a neurodegenerative condition characterized by uncontrollable convulsions caused by a misalignment of the central nervous system's inhibitory and excitatory branches. Vateria indica is a medicinal herb with anti-inflammatory, anthelmintic, antiulcer, antitumor, and anticancer properties.ObjectivesTo investigate the antiepileptic activity of Vateria indica using maximal electrical shock (MES), pentylenetetrazole (PTZ), and isoniazid (INH) induced experimental animal models.MethodologyVateria indica bark was subjected to Soxhlet extraction using ethanol and quantitative and qualitative analysis was performed. The antiepileptic activity of Vateria indica bark extract (VIE) was investigated using different animal models in mice. GABA levels in the brain and antioxidant capacity in vitro were estimated.ResultsTreatment of mice with VIE significantly reversed the MES-induced convulsions, which was reflected by the decrease in the duration (sec) of all the phases of MES-induced convulsions, with an increment in the GABA levels. In the PTZ and INH models, pretreatment with VIE delayed the latency to clonic convulsions (p 0.001), reduced the intensity and duration of clonic convulsions, and reduced the mortality rate in the treatment groups in a dose-dependent manner. VIE intervention dose-dependently restored brain GABA levels. VIE also exhibited significant in-vitro antioxidant activity.ConclusionOverall, the findings imply that Vateria indica has substantial antiepileptic activities, mediated by positive GABAergic neurotransmission and antioxidant capabilities. To summarize, Vateria indica may provide adequate protection against epileptic seizures, suggesting that it could be used to treat petitmal and grandmal epilepsy. We plan to provide pure lead compounds derived from Vateria indica in the future in order to better understand the role it could play in the development of natural anticonvulsant drugs.     

社会资本进入公立医院政策演进分析

目的 对我国公立医院利用社会资本的有关政策进行阐述和分析。方法 基于国内公立医院发展现况,通过个案调查、访谈、文献查阅等形式,对公立医院的融资过程进行政策分析。结果 公立医院对社会资本引入的尝试,已形成了一些具有若干特点的融资模式,如银行贷款、融资租赁、慈善捐赠等。结论 我国公立医院为实现可持续发展,多渠道引入社会资本已经成为必然的发展趋势。但从整体上讲,还未形成满足各种社会资本状况的政策体系。     

CLODRONATE LIPOSOMES: PERSPECTIVES IN RESEARCH AND THERAPEUTICS

ABSTRACT

Liposomes encapsulating the bisphosphonate clodronate can be used for the transient suppression of macrophage functions. Given the important role of macrophages in various disorders, the application of clodronate liposomes has been studied in several models of rheumatoid arthritis, neurological disorders such as experimental allergic encephalomyelitis and spinal cord injury, autoantibody mediated disorders such as immune thrombocytopenic purpura (ITP) and for the improvement of the efficacy of gene transfer and drug targeting.     

PTBP3 promotes tumorigenesis of glioblastoma by stabilizing Twist1

ObjectiveGlioblastoma (GBM) is the most common malignancy tumor of central nervous system. PTBP3 was closely associated with the development of tumor. However, the function and molecular mechanism of PTBP3 in GBM is little known.MethodsqPCR and immunoblotting were used to detect PTBP3 expression levels in glioma tissues and cells. CCK8, Edu, flow cytometry, wound healing, and transwell assays were used to examined the function of PTBP3 in GBM. qPCR, Immunoblotting, and ubiquitination assays were performed to identify the mechanism of PTBP3.ResultsWe found that PTBP3 was upregulated in GBM, and high expression of PTBP3 correlated with the poor survival of GBM patients. PTBP3 knockdown reduced proliferation, invasion, and migration of GBM. Conversely, overexpressing PTBP3 has an opposite effect. Moreover, PTBP3 had an effect on the EMT of GBM. More importantly, we found that PTBP3 stabilized Twist1 by decreasing its ubiquitination and degradation. Furthermore, orthotopic xenograft models were used to demonstrate the PTBP3 on the development of GBM in vivo.ConclusionThis study proved that PTBP3 promoted tumorigenesis of GBM by stabilizing Twist1, which provided a new therapeutic target for GBM.     

Synthesis and SAR development of novel P2X7 receptor antagonists for the treatment of pain: part 2

Novel P2X₇ antagonists were developed using a purine scaffold. These compounds were potent and selective at the P2X₇ receptor in human and rodent as well as efficacious in rodent pain models. Compound 15a was identified to have oral potency in several pain models in rodent similar to naproxen, gabapentin and pregabalin. Structure–activity relationship (SAR) development and results of pain models are presented.     

Secondary hip dysplasia increases risk for early coxarthritis after Legg-Calve-Perthes disease. A study of 255 hips

Abstract

The biomechanical parameters of the hip joint articular surface were analysed in 141 adult hips after Legg-Calve Perthes Disease, and 114 contralateral unaffected hips (controls), by using HIPSTRESS mathematical models. Geometrical parameters, assessed from anteroposterior and axial radiograms, were used as input to models for resultant hip force and contact hip stress. Results confirm previous indications that head enlargement after the Legg-Calve-Perthes Disease compensates the values of hip stress. Furthermore, it was found that an increased risk for coxarthritis development after the disease is secondary to concomitant hip dysplasia, with considerable and statistically significantly lower centre-edge angle and unfavourable distribution of stress.     

A mechanistic damage model for ligaments

PurposeThe accuracy of biomechanical models is predicated on the realism by which they represent their biomechanical tissues. Unfortunately, most models use phenomenological ligament models that neglect the behaviour in the failure region. Therefore, the purpose of this investigation was to test whether a mechanistic model of ligamentous tissue portrays behaviour representative of actual ligament failure tests.ModelThe model tracks the time-evolution of a population of collagen fibres in a theoretical ligament. Each collagen fibre is treated as an independent linear cables with constant stiffness. Model equations were derived by assuming these fibres act as a continuum and applying a conservation law akin to Huxley’s muscle model. A breaking function models the rate of collagen fibre breakage at a given displacement, and was chosen to be a linear function for this preliminary analysis.MethodsThe model was fitted to experimental average curves for the cervical anterior longitudinal ligament. In addition, the model was cyclically loaded to test whether the tissue model behaves similarly.ResultsThe model agreed very well with experiment with an RMS error of 14.23 N and an R² of 0.995. Cyclic loading exhibited a reduction in force similar to experimental data.Discussion and conclusionThe proposed model showcases behaviour reminiscent of actual ligaments being strained to failure and undergoing cyclic load. Future work could incorporate viscous effects, or validate the model further by testing it in various loading conditions. Characterizing the breaking function more accurately would also lead to better results.     

Peer Support Workers in Health: A Qualitative Metasynthesis of Their Experiences

ObjectivePeer support models, where an individual has a specific illness or lifestyle experience and supports others experiencing similar challenges, have frequently been used in different fields of healthcare to successfully engage hard-to-reach groups. Despite recognition of their value, the impact of these roles on the peer has not been systematically assessed. By synthesising the qualitative literature we sought to review such an impact, providing a foundation for designing future clinical peer models.MethodsSystematic review and qualitative metasynthesis of studies found in Medline, CINAHL or Scopus documenting peer worker experiences.Results1,528 papers were found, with 34 meeting the criteria of this study. Findings were synthesised to reveal core constructs of reframing identity through reciprocal relations and the therapeutic use of self, enhancing responsibility.ConclusionsThe ability of the Peer Support Worker to actively engage with other marginalised or excluded individuals based on their unique insight into their own experience supports a therapeutic model of care based on appropriately sharing their story. Our findings have key implications for maximising the effectiveness of Peer Support Workers and in contributing their perspective to the development of a therapeutic model of care.     

Designing hybrid life cycle assessment models based on uncertainty and complexity

Purpose

Despite the wide use of LCA for environmental profiling, the approach for determining the system boundary within LCA models continues to be subjective and lacking in mathematical rigor. As a result, life cycle models are often developed in an ad hoc manner, and are difficult to compare. Significant environmental impacts may be inadvertently left out. Overcoming this shortcoming can help elicit greater confidence in life cycle models and their use for decision making.

Methods

This paper describes a framework for hybrid life cycle model generation by selecting activities based on their importance, parametric uncertainty, and contribution to network complexity. The importance of activities is determined by structural path analysis—which then guides the construction of life cycle models based on uncertainty and complexity indicators. Information about uncertainty is from the available life cycle inventory; complexity is quantified by cost or granularity. The life cycle model is developed in a hierarchical manner by adding the most important activities until error requirements are satisfied or network complexity exceeds user-specified constraints.

Results and Discussion

The framework is applied to an illustrative example for building a hybrid LCA model. Since this is a constructed example, the results can be compared with the actual impact, to validate the approach. This application demonstrates how the algorithm sequentially develops a life cycle model of acceptable uncertainty and network complexity. Challenges in applying this framework to practical problems are discussed.

Conclusion

The presented algorithm designs system boundaries between scales of hybrid LCA models, includes or omits activities from the system based on path analysis of environmental impact contribution at upstream network nodes, and provides model quality indicators that permit comparison between different LCA models.

     

Perspectives in the Modeling and Optimization of PHB Production by Pure and Mixed Cultures

ABSTRACT

Poly(β-hydroxybutyrate) or PHB is an important member of the family of polyhydroxyalkanoates with properties that make it potentially competitive with synthetic polymers. In addition, PHB is biodegradable. While the biochemistry of PHB synthesis by microorganisms is well known, improvement of large-scale productivity requires good fermentation modeling and optimization. The latter aspect is reviewed here.

Current models are of two types: (i) mechanistic and (ii) cybernetic. The models may be unstructured or structured, and they have been applied to single cultures and co-cultures. However, neither class of models expresses adequately all the important features of large-scale non-ideal fermentations. Model-independent neural networks provide faithful representations of observations, but they can be difficult to design. So hybrid models, combining mechanistic, cybernetic and neural models, offer a useful compromise. All three kinds of basic models are discussed with applications and directions toward hybrid model development.     

REPRODUCTION AND LARVAL DEVELOPMENT OF LABEO UMBRATUS (PISCES,CYPRINIDAE) IN THE TYUME RIVER,EASTERN CAPE

SUMMARY

AN account is given of some aspects of the reproductive ecology and larval development of Lubeo umbrutus which is of great importance in the Eastern Cape due to its abundance in rivers and dams.

The sex ratio was found to be approximately 1:1 and females probably have a longer life span than males. Spawning takes place from October to January. Males become sexually mature at a length of 14 cm and females at a length of 20 cm. A spawning site is described. There is a curvilinear relationship between length and fecundity with the average fecundity increasing from 11 000 in fishes with a length of 20 cm to 48 000 in fishes with a length of 32 cm. Larval development from hatching to an age of 12 days is described.     

Characterization of the Burkholderia mallei tonB Mutant and Its Potential as a Backbone Strain for Vaccine Development

BackgroundIn this study, a Burkholderia mallei tonB mutant (TMM001) deficient in iron acquisition was constructed, characterized, and evaluated for its protective properties in acute inhalational infection models of murine glanders and melioidosis.Conclusions/SignificanceAlthough further work is needed to prevent chronic infection by TMM001 while maintaining immunogenicity, our attenuated strain demonstrates great potential as a backbone strain for future vaccine development against both glanders and melioidosis.     

AI applications to medical images: From machine learning to deep learning

PurposeArtificial intelligence (AI) models are playing an increasing role in biomedical research and healthcare services. This review focuses on challenges points to be clarified about how to develop AI applications as clinical decision support systems in the real-world context.MethodsA narrative review has been performed including a critical assessment of articles published between 1989 and 2021 that guided challenging sections.ResultsWe first illustrate the architectural characteristics of machine learning (ML)/radiomics and deep learning (DL) approaches. For ML/radiomics, the phases of feature selection and of training, validation, and testing are described. DL models are presented as multi-layered artificial/convolutional neural networks, allowing us to directly process images. The data curation section includes technical steps such as image labelling, image annotation (with segmentation as a crucial step in radiomics), data harmonization (enabling compensation for differences in imaging protocols that typically generate noise in non-AI imaging studies) and federated learning. Thereafter, we dedicate specific sections to: sample size calculation, considering multiple testing in AI approaches; procedures for data augmentation to work with limited and unbalanced datasets; and the interpretability of AI models (the so-called black box issue). Pros and cons for choosing ML versus DL to implement AI applications to medical imaging are finally presented in a synoptic way.ConclusionsBiomedicine and healthcare systems are one of the most important fields for AI applications and medical imaging is probably the most suitable and promising domain. Clarification of specific challenging points facilitates the development of such systems and their translation to clinical practice.     

Comparison of nutrient uptake between three‐dimensional simulation and an averaged root system model

Abstract

We present a new numerical approach describing nutrient uptake in three dimensions. Dynamic boundary conditions are considered at the individual root surfaces within a root system. As an example, we compare the three‐dimensional simulation results of phosphate uptake by a young maize root system to the corresponding effective solution. We show that the two solutions are similar concerning phosphate uptake and the size of the depletion zones. The presented approach makes it possible to verify simplifications that are made in the development of effective models. Furthermore, it is possible to extend existing models by including spatial heterogeneities that will increase our understanding of rhizosphere processes.     

Multiple-source models for electron beams of a medical linear accelerator using BEAMDP computer code

AimThe aim of this work was to develop multiple-source models for electron beams of the NEPTUN 10PC medical linear accelerator using the BEAMDP computer code.BackgroundOne of the most accurate techniques of radiotherapy dose calculation is the Monte Carlo (MC) simulation of radiation transport, which requires detailed information of the beam in the form of a phase-space file. The computing time required to simulate the beam data and obtain phase-space files from a clinical accelerator is significant. Calculation of dose distributions using multiple-source models is an alternative method to phase-space data as direct input to the dose calculation system.Materials and methodsMonte Carlo simulation of accelerator head was done in which a record was kept of the particle phase-space regarding the details of the particle history. Multiple-source models were built from the phase-space files of Monte Carlo simulations. These simplified beam models were used to generate Monte Carlo dose calculations and to compare those calculations with phase-space data for electron beams.ResultsComparison of the measured and calculated dose distributions using the phase-space files and multiple-source models for three electron beam energies showed that the measured and calculated values match well each other throughout the curves.ConclusionIt was found that dose distributions calculated using both the multiple-source models and the phase-space data agree within 1.3%, demonstrating that the models can be used for dosimetry research purposes and dose calculations in radiotherapy.     

Development and qualification of a representative scale-down model of automated Ficoll-based processing of a cell-based therapeutic according to quality by design principles

Background aimsThis article describes the development of a small-scale model for Ficoll-based cell separation as part of process development of an advanced therapy medicinal product and its qualification. Because of the complexity of biological products, their manufacturing process as well as characterization and control needs to be accurately understood. Likewise, scale-down models serve as an indispensable tool for process development, characterization, optimization and validation. This scale-down model represents a cell processor device widely used in advance therapies. This approach is inteded to optimise resources and to focus its use on process characterisation studies under the paradigm of the Quality by design. A scale-down model should reflect the large manufacturing scale. Consequently, this simplified system should offer a high degree of control over the process parameters to depict a robust model, even considering the process limitations. For this reason, a model should be developed and qualified for the intended purpose.MethodsProcess operating parameters were studied, and their resulting performance at full scale was used as a baseline to guide scale-down model development. Once the model was established, comparability runs were performed by establishing standard operating conditions with bone marrow samples. These analyses showed consistency between the bench and the large scale. Additionally, statistical analyses were employed to demonstrate equivalence.ResultsThe process performance indicators and assessed quality attributes were equivalent and fell into the acceptance ranges defined for the large-scale process.ConclusionsThis scale-down model is suitable for use in process characterization studies.     

Differential scanning calorimetry as a complementary diagnostic tool for the evaluation of biological samples

BackgroundDifferential scanning calorimetry (DSC) is a tool for measuring the thermal stability profiles of complex molecular interactions in biological fluids. DSC profiles (thermograms) of biofluids provide specific signatures which are being utilized as a new diagnostic approach for characterizing disease but the development of these approaches is still in its infancy.MethodsThis article evaluates several approaches for the analysis of thermograms which could increase the utility of DSC for clinical application. Thermograms were analyzed using localized thermogram features and principal components (PCs). The performance of these methods was evaluated alongside six models for the classification of a data set comprised of 300 systemic lupus erythematosus (SLE) patients and 300 control subjects obtained from the Lupus Family Registry and Repository (LFRR).ResultsClassification performance was substantially higher using the penalized algorithms relative to localized features/PCs alone. The models were grouped into two sets, the first having smoother solution vectors but lower classification accuracies than the second with seemingly noisier solution vectors.ConclusionsCoupling thermogram technology with modern classification algorithms provides a powerful diagnostic approach for analysis of biological samples. The solution vectors from the models may reflect important information from the thermogram profiles for discriminating between clinical groups.General significanceDSC thermograms show sensitivity to changes in the bulk plasma proteome that correlate with clinical status. To move this technology towards clinical application the development of new approaches is needed to extract discriminatory parameters from DSC profiles for the comparison and diagnostic classification of patients. This article is part of a Special Issue entitled Microcalorimetry in the BioSciences — Principles and Applications, edited by Fadi Bou-Abdallah.