ResearchPad - bioengineering-and-biotechnology https://www.researchpad.co Default RSS Feed en-us © 2020 Newgen KnowledgeWorks <![CDATA[Targeting Acidic Diseased Tissues by pH-Triggered Membrane-Associated Peptide Folding]]> https://www.researchpad.co/article/elastic_article_7494 The advantages of targeted therapy have motivated many efforts to find distinguishing features between the molecular cell surface landscapes of diseased and normal cells. Typically, the features have been proteins, lipids or carbohydrates, but other approaches are emerging. In this discussion, we examine the use of cell surface acidity as a feature that can be exploited by using pH-sensitive peptide folding to target agents to diseased cell surfaces or cytoplasms.

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<![CDATA[State-of-Art Bio-Assay Systems and Electrochemical Approaches for Nanotoxicity Assessment]]> https://www.researchpad.co/article/elastic_article_7452 Innovations in the field of nanotechnology, material science and engineering has rendered fruitful utilities in energy, environment and healthcare. Particularly, emergence of surface engineered nanomaterials offered novel varieties in the daily consumables and healthcare products including therapeutics and diagnostics. However, the nanotoxicity and bioactivity of the nanomaterials upon interaction with biological system has raised critical concerns to individual as well as to the environment. Several biological models including plant and animal sources have been identified to study the toxicity of novel nanomaterials, correlating the physio-chemical properties. Biological interaction of nanomaterials and its mediated physiological functions are studied using conventional cell/molecular biological assays to understand the expression levels of genetic information specific to intra/extra cellular enzymes, cell viability, proliferation and function. However, modern research still demands advanced bioassay methods to screen the acute and chronic effects of nanomaterials at the real-time. In this regard, bioelectrochemical techniques, with the recent advancements in the microelectronics, proved to be capable of providing non-invasive measurement of the nanotoxicity effects (in vivo and in vitro) both at single cellular and multicellular levels. This review attempted to provide a detailed information on the recent advancements made in development of bioassay models and systems for assessing the nanotoxicology. With a short background information on engineered nanomaterials and physiochemical properties specific to consumer application, present review highlights the multiple bioassay models evolved for toxicological studies. Emphasize on multiple mechanisms involved in the cell toxicity and electrochemical probing of the biological interactions, revealing the cytotoxicity were also provided. Limitations in the existing electrochemical techniques and opportunities for the future research focusing the advancement in single molecular and whole cell bioassay has been discussed.

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<![CDATA[Bioprinting Cell- and Spheroid-Laden Protein-Engineered Hydrogels as Tissue-on-Chip Platforms]]> https://www.researchpad.co/article/elastic_article_7430 Human tissues, both in health and disease, are exquisitely organized into complex three-dimensional architectures that inform tissue function. In biomedical research, specifically in drug discovery and personalized medicine, novel human-based three-dimensional (3D) models are needed to provide information with higher predictive value compared to state-of-the-art two-dimensional (2D) preclinical models. However, current in vitro models remain inadequate to recapitulate the complex and heterogenous architectures that underlie biology. Therefore, it would be beneficial to develop novel models that could capture both the 3D heterogeneity of tissue (e.g., through 3D bioprinting) and integrate vascularization that is necessary for tissue viability (e.g., through culture in tissue-on-chips). In this proof-of-concept study, we use elastin-like protein (ELP) engineered hydrogels as bioinks for constructing such tissue models, which can be directly dispensed onto endothelialized on-chip platforms. We show that this bioprinting process is compatible with both single cell suspensions of neural progenitor cells (NPCs) and spheroid aggregates of breast cancer cells. After bioprinting, both cell types remain viable in incubation for up to 14 days. These results demonstrate a first step toward combining ELP engineered hydrogels with 3D bioprinting technologies and on-chip platforms comprising vascular-like channels for establishing functional tissue models.

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<![CDATA[Extension of Genetic Marker List Using Unnatural Amino Acid System: An Efficient Genomic Modification Strategy in <i>Escherichia coli</i>]]> https://www.researchpad.co/article/elastic_article_7429 Genetic manipulations including chromosome engineering are essential techniques used to restructure cell metabolism. Lambda/Red (λ/Red)-mediated recombination is the most commonly applied approach for chromosomal modulation in Escherichia coli. However, the efficiency of this method is significantly hampered by the laborious removal of the selectable markers. To overcome the problem, the integration helper plasmid was constructed, pSBC1a-CtR, which contains Red recombinase, Cre recombinase, and exogenous orthogonal aminoacyl-transfer RNA (tRNA) synthetase/tRNA pairs, allows an unnatural amino acid (UAA) to be genetically encoded at the defined site of the antibiotic resistance gene-encoded protein. When UAAs are not in the culture medium, there was no expression in the antibiotic resistance gene-encoded protein. Accordingly, the next procedure of antibiotic gene excising is not needed. To verify this method, poxB gene was knocked out successfully. Furthermore, sequential deletion of three target genes (galR, ptsG, and pgi) was able to generate neurosporene-producing strain marked by high growth rate. Thus, the site-specific incorporation UAA mutagenesis system were used to control and expand the use of conditional selectable marker, and the technique is used to facilitate a rapid continuous genome editing in Escherichia coli.

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<![CDATA[Simulative Minimization of Mass Transfer Limitations Within Hydrogel-Based 3D-Printed Enzyme Carriers]]> https://www.researchpad.co/article/elastic_article_7421 In biotechnology, immobilization of functional reactants is often done as a surface immobilization on small particles. Examples are chromatography columns and fixed-bed reactors. However, the available surface for immobilization is directly linked to particle diameter and bed porosity for these systems, leading to high backpressure for small particle sizes. When larger molecules, such as enzymes are immobilized, physical entrapment within porous materials like hydrogels is an alternative. An emerging technique for the production of geometrically structured, three-dimensional and scalable hollow bodies is 3D-printing. Different bioprinting methods are available to produce structures of the desired size, resolution and solids content. However, in case of entrapped enzymes mass transfer limitations often determine the achievable reactivities. With increasing complexity of the system, for example a fixed-bed reactor, 3D-simulation is indispensable to understand the local reaction conditions to be able to highlight the optimization potential. Based on experimental data, this manuscript shows the application of the dimensionless numbers effectiveness factor and Thiele modulus for the design of a 3D-printed flow-through reactor. Within the reactor, enzymes are physically entrapped in 3D-printed hydrogel lattices. The local reaction rate of the enzymes is directly dependent on the provided substrate amount at the site of reaction which is limited by the diffusion properties of the hydrogel matrix and the diffusion distance. All three parameters can be summed up by one key figure, the Thiele modulus, which, in short, quantifies mass transfer limitations of a catalytic system. Depending on the rate of the enzymatic reaction in correlation to the diffusional transport, mass transfer limitations will shift the optimum of the system, favoring slow enzyme kinetics and small diffusion distances. Comparison with the enzymatic reaction rate in solution yields the effectiveness factor of the system. As a result, the optimization potential of varying the 3D-printed geometries or the reaction rate within the experimentally available design space can be estimated.

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<![CDATA[Review on Bioenergy Storage Systems for Preserving and Improving Feedstock Value]]> https://www.researchpad.co/article/elastic_article_7417 Long-term storage is a necessary unit operation in the biomass feedstock logistics supply chain, enabling biorefineries to run year-round despite daily, monthly, and seasonal variations in feedstock availability. At a minimum, effective storage approaches must preserve biomass. Uncontrolled loss of biomass due to microbial degradation is common when storage conditions are not optimized. This can lead to physical and mechanical challenges with biomass handling, size reduction, preprocessing, and ultimately conversion. This review summarizes the unit operations of dry and wet storage and how they may contribute to preserving or even improving feedstock value for biorefineries.

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<![CDATA[The Joint Analysis of Multi-Omics Data Revealed the Methylation-Expression Regulations in Atrial Fibrillation]]> https://www.researchpad.co/article/N3550cfca-c0af-459c-8893-c96f0a99e93d

Atrial fibrillation (AF) is one of the most prevalent heart rhythm disorder. The causes of AF include age, male sex, diabetes, hypertension, valve disease, and systolic/diastolic dysfunction. But on molecular level, its mechanisms are largely unknown. In this study, we collected 10 patients with persistent atrial fibrillation, 10 patients with paroxymal atrial fibrillation and 10 healthy individuals and did Methylation EPICBead Chip and RNA sequencing. By analyzing the methylation and gene expression data using machine learning based feature selection method Boruta, we identified the key genes that were strongly associated with AF and found their interconnections. The results suggested that the methylation of KIF15 may regulate the expression of PSMC3, TINAG, and NUDT6. The identified AF associated methylation-expression regulations may help understand the molecular mechanisms of AF from a multi-omics perspective.

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<![CDATA[Microbial Community Redundancy and Resilience Underpins High-Rate Anaerobic Treatment of Dairy-Processing Wastewater at Ambient Temperatures]]> https://www.researchpad.co/article/N0f288abc-5d2c-40b1-b30b-62a7c98e3f92

High-rate anaerobic digestion (AD) is a reliable, efficient process to treat wastewaters and is often operated at temperatures exceeding 30°C, involving energy consumption of biogas in temperate regions, where wastewaters are often discharged at variable temperatures generally below 20°C. High-rate ambient temperature AD, without temperature control, is an economically attractive alternative that has been proven to be feasible at laboratory-scale. In this study, an ambient temperature pilot scale anaerobic reactor (2 m3) was employed to treat real dairy wastewater in situ at a milk processing plant, at organic loading rates of 1.3 ± 0.6 to 10.6 ± 3.7 kg COD/m3/day and hydraulic retention times (HRT) ranging from 36 to 6 h. Consistent high levels of COD removal efficiencies, ranging from 50 to 70% for total COD removal and 70 to 84% for soluble COD removal, were achieved during the trial. Within the reactor biomass, stable active archaeal populations were observed, consisting mainly of Methanothrix (previously Methanosaeta) species, which represented up to 47% of the relative abundant active species in the reactor. The decrease in HRT, combined with increases in the loading rate had a clear effect on shaping the structure and composition of the bacterial fraction of the microbial community, however, without affecting reactor performance. On the other hand, perturbances in influent pH had a strong impact, especially when pH went higher than 8.5, inducing shifts in the microbial community composition and, in some cases, affecting negatively the performance of the reactor in terms of COD removal and biogas methane content. For example, the main pH shock led to a drop in the methane content to 15%, COD removals decreased to 0%, while the archaeal population decreased to ~11% both at DNA and cDNA levels. Functional redundancy in the microbial community underpinned stable reactor performance and rapid reactor recovery after perturbations.

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<![CDATA[A Novel Synthetic Model of the Glucose-Insulin System for Patient-Wise Inference of Physiological Parameters From Small-Size OGTT Data]]> https://www.researchpad.co/article/N8ed61570-afdb-4e56-be39-61b850ced829

Existing mathematical models for the glucose-insulin (G-I) dynamics often involve variables that are not susceptible to direct measurement. Standard clinical tests for measuring G-I levels for diagnosing potential diseases are simple and relatively cheap, but seldom give enough information to allow the identification of model parameters within the range in which they have a biological meaning, thus generating a gap between mathematical modeling and any possible physiological explanation or clinical interpretation. In the present work, we present a synthetic mathematical model to represent the G-I dynamics in an Oral Glucose Tolerance Test (OGTT), which involves for the first time for OGTT-related models, Delay Differential Equations. Our model can represent the radically different behaviors observed in a studied cohort of 407 normoglycemic patients (the largest analyzed so far in parameter fitting experiments), all masked under the current threshold-based normality criteria. We also propose a novel approach to solve the parameter fitting inverse problem, involving the clustering of different G-I profiles, a simulation-based exploration of the feasible set, and the construction of an information function which reshapes it, based on the clinical records, experimental uncertainties, and physiological criteria. This method allowed an individual-wise recognition of the parameters of our model using small size OGTT data (5 measurements) directly, without modifying the routine procedures or requiring particular clinical setups. Therefore, our methodology can be easily applied to gain parametric insights to complement the existing tools for the diagnosis of G-I dysregulations. We tested the parameter stability and sensitivity for individual subjects, and an empirical relationship between such indexes and curve shapes was spotted. Since different G-I profiles, under the light of our model, are related to different physiological mechanisms, the present method offers a tool for personally-oriented diagnosis and treatment and to better define new health criteria.

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<![CDATA[Development, Validation and Comparison of Artificial Neural Network Models and Logistic Regression Models Predicting Survival of Unresectable Pancreatic Cancer]]> https://www.researchpad.co/article/N19720d82-c604-4c5b-bd15-c57b82fc491d

Background: Prediction models for the overall survival of pancreatic cancer remain unsatisfactory. We aimed to explore artificial neural networks (ANNs) modeling to predict the survival of unresectable pancreatic cancer patients.

Methods: Thirty-two clinical parameters were collected from 221 unresectable pancreatic cancer patients, and their prognostic ability was evaluated using univariate and multivariate logistic regression. ANN and logistic regression (LR) models were developed on a training group (168 patients), and the area under the ROC curve (AUC) was used for comparison of the ANN and LR models. The models were further tested on the testing group (53 patients), and k-statistics were used for accuracy comparison.

Results: We built three ANN models, based on 3, 7, and 32 basic features, to predict 8 month survival. All 3 ANN models showed better performance, with AUCs significantly higher than those from the respective LR models (0.811 vs. 0.680, 0.844 vs. 0.722, 0.921 vs. 0.849, all p < 0.05). The ability of the ANN models to discriminate 8 month survival with higher accuracy than the respective LR models was further confirmed in 53 consecutive patients.

Conclusion: We developed ANN models predicting the 8 month survival of unresectable pancreatic cancer patients. These models may help to optimize personalized patient management.

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<![CDATA[Development of a Novel Biosensor-Driven Mutation and Selection System via in situ Growth of Corynebacterium crenatum for the Production of L-Arginine]]> https://www.researchpad.co/article/N05d5801b-8b68-4f22-a617-501d66a939a2

The high yield mutants require a high-throughput screening method to obtain them quickly. Here, we developed an L-arginine biosensor (ARG-Select) to obtain increased L-arginine producers among a large number of mutant strains. This biosensor was constructed by ArgR protein and argC promoter, and could provide the strain with the output of bacterial growth via the reporter gene sacB; strains with high L-arginine production could survive in 10% sucrose screening. To extend the screening limitation of 10% sucrose, the sensitivity of ArgR protein to L-arginine was decreased. Corynebacterium crenatum SYPA5-5 and its systems pathway engineered strain Cc6 were chosen as the original strains. This biosensor was employed, and L-arginine hyperproducing mutants were screened. Finally, the HArg1 and DArg36 mutants of C. crenatum SYPA5-5 and Cc6 could produce 56.7 and 95.5 g L–1 of L-arginine, respectively, which represent increases of 35.0 and 13.5%. These results demonstrate that the transcription factor-based biosensor could be applied in high yield strains selection as an effective high-throughput screening method.

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<![CDATA[Thrombogenic and Inflammatory Reactions to Biomaterials in Medical Devices]]> https://www.researchpad.co/article/Nb9eb8112-3323-4e0c-9df9-4847732622ad

Blood-contacting medical devices of different biomaterials are often used to treat various cardiovascular diseases. Thrombus formation is a common cause of failure of cardiovascular devices. Currently, there are no clinically available biomaterials that can totally inhibit thrombosis under the more challenging environments (e.g., low flow in the venous system). Although some biomaterials reduce protein adsorption or cell adhesion, the issue of biomaterial associated with thrombosis and inflammation still exists. To better understand how to develop more thrombosis-resistant medical devices, it is essential to understand the biology and mechano-transduction of thrombus nucleation and progression. In this review, we will compare the mechanisms of thrombus development and progression in the arterial and venous systems. We will address various aspects of thrombosis, starting with biology of thrombosis, mathematical modeling to integrate the mechanism of thrombosis, and thrombus formation on medical devices. Prevention of these problems requires a multifaceted approach that involves more effective and safer thrombolytic agents but more importantly the development of novel thrombosis-resistant biomaterials mimicking the biological characteristics of the endothelium and extracellular matrix tissues that also ameliorate the development and the progression of chronic inflammation as part of the processes associated with the detrimental generation of late thrombosis and neo-atherosclerosis. Until such developments occur, engineers and clinicians must work together to develop devices that require minimal anticoagulants and thrombolytics to mitigate thrombosis and inflammation without causing serious bleeding side effects.

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<![CDATA[The Scrapie Prevalence in a Goat Herd Is Underestimated by Using a Rapid Diagnostic Test]]> https://www.researchpad.co/article/N6ff1b713-e668-470f-988e-28d898a96a58

Current European surveillance regulations for scrapie, a naturally occurring transmissible spongiform encephalopathy (TSE) or prion disease in sheep and goats, require testing of fallen stock or healthy slaughter animals, and outline measures in the case of confirmation of disease. An outbreak of classical scrapie in a herd with 2500 goats led to the culling of the whole herd, providing the opportunity to examine a subset of goats, take samples, and examine them for the presence of disease-associated prion protein (PrPSc) to provide further information on scrapie test sensitivity, pathology, and association with prion protein genotype. Goats were examined clinically prior to cull, and the brains examined post mortem by Bio-Rad ELISA, a rapid screening test used for active surveillance in sheep and goats, and two confirmatory tests, Western blot and immunohistochemistry. Furthermore, up to 10 lymphoid tissues were examined by immunohistochemistry. Of 151 goats examined, three (2.0%) tested positive for scrapie by ELISA on brain, confirmed by confirmatory tests, and a further five (3.3%) were negative by ELISA but positive by at least one of the confirmatory tests. Only two of these, both positive by ELISA, displayed evident signs of scrapie. In addition, 10 (6.6%) goats, which also included two clinical suspects, were negative on brain examination but had detectable PrPSc in lymphoid tissue. PrPSc was detected most frequently in the medial retropharyngeal lymph node (LN; 94.4% of all 18 cases) and palatine tonsil (88.9%). Abnormal behavior and circling or loss of balance when blindfolded were the best clinical discriminators for scrapie status. None of the goats that carried a single allele in the prion protein gene associated with increased resistance to scrapie (Q211, K222, S146) were scrapie-positive, and the percentage of goats with these alleles was greater than expected from previous surveys. Significantly more goats that were scrapie-positive were isoleucine homozygous at codon 142 (II142). The results indicate that the sensitivity of the applied screening test is poor in goats compared to the confirmatory tests as gold standard, particularly for asymptomatic animals. Sensitivity of surveillance could be improved by testing retropharyngeal LN or palatine tonsil in addition to brain.

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<![CDATA[Development of a Canine Rigid Body Musculoskeletal Computer Model to Evaluate Gait]]> https://www.researchpad.co/article/Nae1d9a81-5066-4511-90ef-0a6c3829b21c

Background

Kinematic and kinetic analysis have been used to gain an understanding of canine movement and joint loading during gait. By non-invasively predicting muscle activation patterns and forces during gait, musculoskeletal models can further our understanding of normal variability and muscle activation patterns and force profiles characteristic of gait.

Methods

Pelvic limb kinematics and kinetics were measured for a 2 year old healthy female Dachshund (5.4 kg) during gait using 3-D motion capture and force platforms. A computed tomography scan was conducted to acquire pelvis and pelvic limb morphology. Using the OpenSim modeling platform, a bilateral pelvic limb subject-specific rigid body musculoskeletal computer model was developed. This model predicted muscle activation patterns, muscle forces, and angular kinematics and joint moments during walking.

Results

Gait kinematics determined from motion capture matched those predicted by the model, verifying model accuracy. Primary muscles involved in generating joint moments during stance and swing were predicted by the model: at mid-stance the adductor magnus et brevis (peak activation 53.2%, peak force 64.7 N) extended the hip, and stifle flexor muscles (biceps femoris tibial and calcaneal portions) flexed the stifle. Countering vertical ground reaction forces, the iliopsoas (peak activation 37.9%, peak force 68.7 N) stabilized the hip in mid-stance, while the biceps femoris patellar portion stabilized the stifle in mid-stance and the plantar flexors (gastrocnemius and flexor digitorum muscles) stabilized the tarsal joint during early stance. Transitioning to swing, the iliopsoas, rectus femoris and tensor fascia lata flexed the hip, while in late swing the adductor magnus et brevis impeded further flexion as biceps femoris tibial and calcaneal portions stabilized the stifle for ground contact.

Conclusion

The musculoskeletal computer model accurately replicated experimental canine angular kinematics associated with gait and was used to predict muscle activation patterns and forces. Thus, musculoskeletal modeling allows for quantification of measures such as muscle forces that are difficult or impossible to measure in vivo.

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<![CDATA[Construction and Analysis of Human Diseases and Metabolites Network]]> https://www.researchpad.co/article/N455829b2-d0b1-4ee3-a21a-2219868856f3 The relationship between aberrant metabolism and the initiation and progression of diseases has gained considerable attention in recent years. To gain insights into the global relationship between diseases and metabolites, here we constructed a human diseases-metabolites network (HDMN). Through analyses based on network biology, the metabolites associated with the same disorder tend to participate in the same metabolic pathway or cascade. In addition, the shortest distance between disease-related metabolites was shorter than that of all metabolites in the Kyoto Encyclopedia of Genes and Genomes (KEGG) metabolic network. Both disease and metabolite nodes in the HDMN displayed slight clustering phenomenon, resulting in functional modules. Furthermore, a significant positive correlation was observed between the degree of metabolites and the proportion of disease-related metabolites in the KEGG metabolic network. We also found that the average degree of disease metabolites is larger than that of all metabolites. Depicting a comprehensive characteristic of HDMN could provide great insights into understanding the global relationship between disease and metabolites. ]]> <![CDATA[A Video-Based Framework for Automatic 3D Localization of Multiple Basketball Players: A Combinatorial Optimization Approach]]> https://www.researchpad.co/article/N3af1e98f-579d-492d-a2d1-aa2daa564e14 Sports complexity must be investigated at competitions; therefore, non-invasive methods are essential. In this context, computer vision, image processing, and machine learning techniques can be useful in designing a non-invasive system for data acquisition that identifies players’ positions in official basketball matches. Here, we propose and evaluate a novel video-based framework to perform automatic 3D localization of multiple basketball players. The introduced framework comprises two parts. The first stage is player detection, which aims to identify players’ heads at the camera image level. This stage is based on background segmentation and on classification performed by an artificial neural network. The second stage is related to 3D reconstruction of the player positions from the images provided by the different cameras used in the acquisition. This task is tackled by formulating a constrained combinatorial optimization problem that minimizes the re-projection error while maximizing the number of detections in the formulated 3D localization problem. ]]> <![CDATA[Development of a Continuous Pulsed Electric Field (PEF) Vortex-Flow Chamber for Improved Treatment Homogeneity Based on Hydrodynamic Optimization]]> https://www.researchpad.co/article/Ne6987b53-2bac-4ee9-8f7b-9253abf246b1 Pulsed electric fields (PEF) treatment is an effective process for preservation of liquid products in food and biotechnology at reduced temperatures, by causing electroporation. It may contribute to increase retention of heat-labile constituents with similar or enhanced levels of microbial inactivation, compared to thermal processes. However, especially continuous PEF treatments suffer from inhomogeneous treatment conditions. Typically, electric field intensities are highest at the inner wall of the chamber, where the flow velocity of the treated product is lowest. Therefore, inhomogeneities of the electric field within the treatment chamber and associated inhomogeneous temperature fields emerge. For this reason, a specific treatment chamber was designed to obtain more homogeneous flow properties inside the treatment chamber and to reduce local temperature peaks, therefore increasing treatment homogeneity. This was accomplished by a divided inlet into the chamber, consequently generating a swirling flow (vortex). The influence of inlet angles on treatment homogeneity was studied (final values: radial angle α = 61°; axial angle β = 98°), using computational fluid dynamics (CFD). For the final design, the vorticity, i.e., the intensity of the fluid rotation, was the lowest of the investigated values in the first treatment zone (1002.55 1/s), but could be maintained for the longest distance, therefore providing an increased mixing and most homogeneous treatment conditions. The new design was experimentally compared to a conventional co-linear setup, taking into account inactivation efficacy of Microbacterium lacticum as well as retention of heat-sensitive alkaline phosphatase (ALP). Results showed an increase in M. lacticum inactivation (maximum Δlog of 1.8 at pH 7 and 1.1 at pH 4) by the vortex configuration and more homogeneous treatment conditions, as visible by the simulated temperature fields. Therefore, the new setup can contribute to optimize PEF treatment conditions and to further extend PEF applications to currently challenging products. ]]> <![CDATA[Development of Multifunctional Biopolymeric Auto-Fluorescent Micro- and Nanogels as a Platform for Biomedical Applications]]> https://www.researchpad.co/article/N0448042e-856c-4ba7-afee-aba084ef7d40 The emerging field of theranostics for advanced healthcare has raised the demand for effective and safe delivery systems consisting of therapeutics and diagnostics agents in a single monarchy. This requires the development of multi-functional bio-polymeric systems for efficient image-guided therapeutics. This study reports the development of size-controlled (micro-to-nano) auto-fluorescent biopolymeric hydrogel particles of chitosan and hydroxyethyl cellulose (HEC) synthesized using water-in-oil emulsion polymerization technique. Sustainable resource linseed oil-based polyol is introduced as an element of hydrophobicity with an aim to facilitate their ability to traverse the blood-brain barrier (BBB). These nanogels are demonstrated to have salient features such as biocompatibility, stability, high cellular uptake by a variety of host cells, and ability to transmigrate across an in vitro BBB model. Interestingly, these unique nanogel particles exhibited auto-fluorescence at a wide range of wavelengths 450–780 nm on excitation at 405 nm whereas excitation at 710 nm gives emission at 810 nm. In conclusion, this study proposes the developed bio-polymeric fluorescent micro- and nano- gels as a potential theranostic tool for central nervous system (CNS) drug delivery and image-guided therapy. ]]> <![CDATA[The Synergistic Action of Electro-Fenton and White-Rot Fungi in the Degradation of Lignin]]> https://www.researchpad.co/article/Ne5933b7a-727b-4160-94a1-b46015bf85ff

White-rot fungus is a common lignin-degrading fungus. However, compared with those of microorganisms that biodegrade lignin alone, synergistic systems of electro-Fenton processes and white-rot fungi are superior because of their high efficiency, mild conditions, and environmental friendliness. To investigate the details of lignin degradation by a synergistic system comprising electro-Fenton processes and white-rot fungi, lignin degradation was studied at different voltages with three lignin-degrading fungi (Phanerochaete chrysosporium, Lentinula edodes, and Trametes versicolor). The lignin degradation efficiency (82∼89%) of the synergistic systems at 4 V was higher than that of a control at 96 h post inoculation. Furthermore, the H2O2 produced and phenolic lignin converted in the system can significantly enhance the efficiency of ligninolytic enzymes, so a considerably increased enzyme activity was obtained by the synergistic action of electro-Fenton processes and white-rot fungi. 13C NMR spectroscopy revealed that aromatic structure units (103–162 ppm) were effectively degraded by the three fungi. This study shows that the combination of electro-Fenton processes and white-rot fungi treatment significantly improved the lignin degradation efficiency, which established a promising strategy for lignin degradation and valorization.

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<![CDATA[Predicting Knee Joint Instability Using a Tibio-Femoral Statistical Shape Model]]> https://www.researchpad.co/article/Ncfa0bac3-6ba9-4eae-8689-54452b8ef41e

Statistical shape models (SSMs) are a well established computational technique to represent the morphological variability spread in a set of matching surfaces by means of compact descriptive quantities, traditionally called “modes of variation” (MoVs). SSMs of bony surfaces have been proposed in biomechanics and orthopedic clinics to investigate the relation between bone shape and joint biomechanics. In this work, an SSM of the tibio-femoral joint has been developed to elucidate the relation between MoVs and bone angular deformities causing knee instability. The SSM was built using 99 bony shapes (distal femur and proximal tibia surfaces obtained from segmented CT scans) of osteoarthritic patients. Hip-knee-ankle (HKA) angle, femoral varus-valgus (FVV) angle, internal-external femoral rotation (IER), tibial varus-valgus (TVV) angles, and tibial slope (TS) were available across the patient set. Discriminant analysis (DA) and logistic regression (LR) classifiers were adopted to underline specific MoVs accounting for knee instability. First, it was found that thirty-four MoVs were enough to describe 95% of the shape variability in the dataset. The most relevant MoVs were the one encoding the height of the femoral and tibial shafts (MoV #2) and the one representing variations of the axial section of the femoral shaft and its bending in the frontal plane (MoV #5). Second, using quadratic DA, the sensitivity results of the classification were very accurate, being all >0.85 (HKA: 0.96, FVV: 0.99, IER: 0.88, TVV: 1, TS: 0.87). The results of the LR classifier were mostly in agreement with DA, confirming statistical significance for MoV #2 (p = 0.02) in correspondence to IER and MoV #5 in correspondence to HKA (p = 0.0001), FVV (p = 0.001), and TS (p = 0.02). We can argue that the SSM successfully identified specific MoVs encoding ranges of alignment variability between distal femur and proximal tibia. This discloses the opportunity to use the SSM to predict potential misalignment in the knee for a new patient by processing the bone shapes, removing the need for measuring clinical landmarks as the rotation centers and mechanical axes.

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