Voxel-wise analysis: A powerful tool to predict radio-induced toxicity and potentially perform personalised planning in radiotherapy.

Dose - volume histograms have been historically used to study the relationship between the planned radiation dose and healthy tissue damage. However, this approach considers neither spatial information nor heterogenous radiosensitivity within organs at risk, depending on the tissue. Recently, voxel-wise analyses have emerged in the literature as powerful tools to fully exploit three-dimensional information from the planned dose distribution. They allow to identify anatomical subregions of one or several organs in which the irradiation dose is associated with a given toxicity. These methods rely on an accurate anatomical alignment, usually obtained by means of a non-rigid registration. Once the different anatomies are spatially normalised, correlations between the three-dimensional dose and a given toxicity can be explored voxel-wise. Parametric or non-parametric statistical tests can be performed on every voxel to identify the voxels in which the dose is significantly different between patients presenting or not toxicity. Several anatomical subregions associated with genitourinary, gastrointestinal, cardiac, pulmonary or haematological toxicity have already been identified in the literature for prostate, head and neck or thorax irradiation. Voxel-wise analysis appears therefore first particularly interesting to increase toxicity prediction capability by identifying specific subregions in the organs at risk whose irradiation is highly predictive of specific toxicity. The second interest is potentially to decrease the radio-induced toxicity by limiting the dose in the predictive subregions, while not decreasing the dose in the target volume. Limitations of the approach have been pointed out.

A high-performance method of deep learning for prostate MR-only radiotherapy planning using an optimized Pix2Pix architecture.

PURPOSE: The first aim was to generate and compare synthetic-CT (sCT) images using a conditional generative adversarial network (cGAN) method (Pix2Pix) for MRI-only prostate radiotherapy planning by testing several generators, loss functions, and hyper-parameters. The second aim was to compare the optimized Pix2Pix model with five other architectures (bulk-density, atlas-based, patch-based, U-Net, and GAN). METHODS: For 39 patients treated by VMAT for prostate cancer, T2-weighted MRI images were acquired in addition to CT images for treatment planning. sCT images were generated using the Pix2Pix model. The generator, loss function, and hyper-parameters were tuned to improve sCT image generation (in terms of imaging endpoints). The final evaluation was performed by 3-fold cross-validation. This method was compared to five other methods using the following imaging endpoints: the mean absolute error (MAE) and mean error (ME) between sCT and reference CT images (rCT) of the whole pelvis, bones, prostate, bladder, and rectum. For dose planning analysis, the dose-volume histogram metric differences and 3D gamma analysis (local, 1 %/1 mm) were calculated using the sCT and reference CT images. RESULTS: Compared with the other architectures, Pix2Pix with Perceptual loss function and generator ResNet 9 blocks showed the lowest MAE (29.5, 107.7, 16.0, 13.4, and 49.1 HU for the whole pelvis, bones, prostate, bladder, and rectum, respectively) and the highest gamma passing rates (99.4 %, using the 1 %/1mm and 10 % dose threshold criterion). Concerning the DVH points, the mean errors were -0.2% for the planning target volume V95%, 0.1 % for the rectum V70Gy, and -0.1 % for the bladder V50Gy. CONCLUSION: The sCT images generated from MRI data with the Pix2Pix architecture had the lowest image errors and similar dose uncertainties (in term of gamma pass-rate and dose-volume histogram metric differences) than other deep learning methods.

Headspace control and antimicrobials: Inhibition strategies to prevent the growth of Alicyclobacillus acidoterrestris in orange juice.

Alicyclobacillus acidoterrestris can cause spoilage in orange juice that leads to consumer rejection. Six different orange juices were physiochemically characterized (pH, total soluble solids, titratable acidity, total polyphenols and vitamin C). A bottle for each sampling point per juice was filled (headspace: 40% volume) and inoculated with 102 -103 CFU per ml of A. acidoterrestris ATCC® 49025™ (heat shocked before inoculation: 75°C, 20 min). Samples were stored for 21 days at 45 ± 1°C and plate counted periodically on acidified YSG agar (pH 3·7) incubated at 45 ± 1°C for 3 days. The effect of headspace (6% versus 40% volume) on A. acidoterrestris growth was also evaluated. The effect of nisin (0·006, 0·003, 0·0015, and 0·00075%), sodium benzoate (0·1%), potassium sorbate (0·1%) and a mix of benzoate and sorbate (0·05% each) on A. acidoterrestris was additionally addressed. Alicyclobacillus acidoterrestris reached up to 107 CFU per ml in five of the six juices in less than 1 week. Headspace significantly impacted (P < 0·05) A. acidoterrestris maximum population, which reached the critical value of 5 log CFU per ml at 40% headspace. All preservatives, regardless of concentration, showed a bacteriostatic effect during 22 days of storage with no significant differences amongst treatments (P > 0·05).

Deep learning methods to generate synthetic CT from MRI in radiotherapy: A literature review.

PURPOSE: In radiotherapy, MRI is used for target volume and organs-at-risk delineation for its superior soft-tissue contrast as compared to CT imaging. However, MRI does not provide the electron density of tissue necessary for dose calculation. Several methods of synthetic-CT (sCT) generation from MRI data have been developed for radiotherapy dose calculation. This work reviewed deep learning (DL) sCT generation methods and their associated image and dose evaluation, in the context of MRI-based dose calculation. METHODS: We searched the PubMed and ScienceDirect electronic databases from January 2010 to March 2021. For each paper, several items were screened and compiled in figures and tables. RESULTS: This review included 57 studies. The DL methods were either generator-only based (45% of the reviewed studies), or generative adversarial network (GAN) architecture and its variants (55% of the reviewed studies). The brain and pelvis were the most commonly investigated anatomical localizations (39% and 28% of the reviewed studies, respectively), and more rarely, the head-and-neck (H&N) (15%), abdomen (10%), liver (5%) or breast (3%). All the studies performed an image evaluation of sCTs with a diversity of metrics, with only 36 studies performing dosimetric evaluations of sCT. CONCLUSIONS: The median mean absolute errors were around 76 HU for the brain and H&N sCTs and 40 HU for the pelvis sCTs. For the brain, the mean dose difference between the sCT and the reference CT was <2%. For the H&N and pelvis, the mean dose difference was below 1% in most of the studies. Recent GAN architectures have advantages compared to generator-only, but no superiority was found in term of image or dose sCT uncertainties. Key challenges of DL-based sCT generation methods from MRI in radiotherapy is the management of movement for abdominal and thoracic localizations, the standardization of sCT evaluation, and the investigation of multicenter impacts.

Implication of heat shock proteins in rotavirus entry into Reh cells.

The mechanisms of rotavirus entry into the target cell are described as a multi-step event in which the virions are bound to sialic acid (SA), followed by interaction with heat shock cognate protein 70 (Hsc70), some integrins and protein disulfide isomerase (PDI). However, the cell surface receptor molecules facilitating the entry of tumor cell-adapted rotavirus are not completely characterized. Using infection blocking assays with antibodies to some heat shock proteins (HSPs) and also some inhibitors of these cellular proteins, we were able to identify the cell surface Hsp90, Hsp70, Hsc70, Hsp60, Hsp40, PDI and integrin ß3 as receptors of tumor cell-adapted rotavirus in Reh cells. Furthermore, the results also indicated that these rotavirus receptors are associated with lipid microdomains (rafts). Our findings provide evidence that rotavirus tropism for these human acute lymphocytic leukemia cells is explained by the relatively high expression of some HSPs in rafts. The results shown here encourage further research aim at evaluating the potential use of rotaviruses as an oncolytic agent for the treatment of some cancers. Keywords: heat shock proteins; rotavirus; cell receptor; cancer; oncolytic virus.

Thiol/disulfide exchange occurs in rotavirus structural proteins during contact with intestinal villus cell surface.

Protein disulfide isomerase (PDI) is an enzyme that catalyzes disulfide bond reduction or formation and rearrangements of disulfide bridges, and also functions as a chaperone. During entry of some of the viruses PDI participates in thiol-disulfide exchange. Previous reports show that rotavirus entry is interfered by impermeant thiol/disulfide exchange inhibitors and antibodies against PDI. Our objective was to assess the interaction between PDI and triple-layered particles (TLPs) from rotavirus strains ECwt and RRV and from a human rotavirus isolate (HI) during the early steps of virus entry in a system of isolated small intestinal villi. Purified soluble PDI was incubated with either isolated intestinal villi or cell membrane-enriched fractions in the presence or absence of thiol/disulfide inhibitors such as bacitracin, DTNB or N- ethylmaleimide followed by the assessment of the PDI interactions with TLPs and rotavirus structural proteins in terms of their redox state changes. Soluble and membrane-bound PDI was found to interact with TLPs from all the rotaviruses assayed and also with the isolated structural proteins represented by the recombinant rVP5* (a tryptic cleavage product of VP4), rVP6 and the native VP7. PDI interaction with TLPs and rotavirus structural proteins was decreased by the presence of thiol/disulfide exchange inhibitors. Interactions of cell membrane-enriched fractions with TLPs produced rearrangements in the disulfide bridges of rotavirus structural proteins. We conclude that PDI interacts with rotavirus virions through redox reactions that could facilitate the rotavirus entry into the host cell. Keywords: cell surface PDI; thiol-disulfide exchange; rotavirus TLPs; virus entry; bacitracin; DTNB.

Head-and-Neck MRI-only radiotherapy treatment planning: From acquisition in treatment position to pseudo-CT generation.

PURPOSE: In context of head-and-neck radiotherapy, this study aims to compare MR image quality according to diagnostic (DIAG) and radiotherapy (RT) setups; and to optimise an MRI-protocol (including 3D T1 and T2-weighted sequences) for dose-planning (based on pseudo-CT generation). MATERIALS AND METHODS: To compare DIAG and RT setups, signal-to-noise-ratio (SNR) and percentage-image-uniformity (PIU) were computed on T1 images of phantoms and volunteers. Influence of the sample conductivity on SNR was quantified using homemade phantoms. To obtain reliable T1 and T2 images for RT-planning, an experimental design was performed on volunteers by using SNR, contrast-to-noise-ratio (CNR) and mean-opinion-score (MOS). Further, pseudo-CTs were generated from 8 patients T2 images with a state-of-art deep-learning method. These pseudo-CTs were evaluated by mean-absolute-error (MAE) and mean-error (ME). RESULTS: SNR was higher for DIAG-setup compared to RT-setup (SNR-ratio=1.3). A clear influence of the conductivity on SNR was observed. PIU was higher for DIAG-setup (38.8%) compared to RT-setup (33.5%). Regarding the protocol optimisation, SNR, CNR, and MOS were 20.6, 6.16, and 3.91 for the optimal T1 sequence. For the optimal T2 sequence, SNR, CNR and MOS were 25.6, 44.46 and 4.0. In the whole head-and-neck area, the mean MAE and ME of the pseudo-CTs were 82.8 and -3.9 HU. CONCLUSION: We quantified the image quality decrease induces by using an RT-setup for head-and-neck radiotherapy. To compensate this decrease, an MRI protocol was optimised by using an experimental design. This protocol of 15minutes provides accurate images which could be used for MRI-dose-planning in clinical practice.

Voxel-based identification of local recurrence sub-regions from pre-treatment PET/CT for locally advanced head and neck cancers.

BACKGROUND: Overall, 40% of patients with a locally advanced head and neck cancer (LAHNC) treated by chemoradiotherapy (CRT) present local recurrence within 2 years after the treatment. The aims of this study were to characterize voxel-wise the sub-regions where tumor recurrence appear and to predict their location from pre-treatment 18F-fluorodeoxyglucose (FDG) positron emission tomography (PET) images. MATERIALS AND METHODS: Twenty-six patients with local failure after treatment were included in this study. Local recurrence volume was identified by co-registering pre-treatment and recurrent PET/CT images using a customized rigid registration algorithm. A large set of voxel-wise features were extracted from pre-treatment PET to train a random forest model allowing to predict local recurrence at the voxel level. RESULTS: Out of 26 expert-assessed registrations, 15 provided enough accuracy to identify recurrence volumes and were included for further analysis. Recurrence volume represented on average 23% of the initial tumor volume. The MTV with a threshold of 50% of SUVmax plus a 3D margin of 10 mm covered on average 89.8% of the recurrence and 96.9% of the initial tumor. SUV and MTV alone were not sufficient to identify the area of recurrence. Using a random forest model, 15 parameters, combining radiomics and spatial location, were identified, allowing to predict the recurrence sub-regions with a median area under the receiver operating curve of 0.71 (range 0.14-0.91). CONCLUSION: As opposed to regional comparisons which do not bring enough evidence for accurate prediction of recurrence volume, a voxel-wise analysis of FDG-uptake features suggested a potential to predict recurrence with enough accuracy to consider tailoring CRT by dose escalation within likely radioresistant regions.

Multi T1-weighted contrast MRI with fluid and white matter suppression at 1.5 T.

INTRODUCTION: The fluid and white matter suppression sequence (FLAWS) provides two T1-weighted co-registered datasets: a white matter (WM) suppressed contrast (FLAWS1) and a cerebrospinal fluid (CSF) suppressed contrast (FLAWS2). FLAWS has the potential to improve the contrast of the subcortical brain regions that are important for Deep Brain Stimulation surgery planning. However, to date FLAWS has not been optimized for 1.5 T. In this study, the FLAWS sequence was optimized for use at 1.5 T. In addition, the contrast-enhancement properties of FLAWS image combinations were investigated using two voxel-wise FLAWS combined images: the division (FLAWS-div) and the high contrast (FLAWS-hc) image. METHODS: FLAWS sequence parameters were optimized for 1.5 T imaging using an approach based on the use of a profit function under constraints for brain tissue signal and contrast maximization. MR experiments were performed on eleven healthy volunteers (age 18-30). Contrast (CN) and contrast to noise ratio (CNR) between brain tissues were measured in each volunteer. Furthermore, a qualitative assessment was performed to ensure that the separation between the internal globus pallidus (GPi) and the external globus pallidus (GPe) is identifiable in FLAWS1. RESULTS: The optimized set of sequence parameters for FLAWS at 1.5 T provided contrasts similar to those obtained in a previous study at 3 T. The separation between the GPi and the GPe was clearly identified in FLAWS1. The CN of FLAWS-hc was higher than that of FLAWS1 and FLAWS2, but was not different from the CN of FLAWS-div. The CNR of FLAWS-hc was higher than that of FLAWS-div. CONCLUSION: Both qualitative and quantitative assessments validated the optimization of the FLAWS sequence at 1.5 T. Quantitative assessments also showed that FLAWS-hc provides an enhanced contrast compared to FLAWS1 and FLAWS2, with a higher CNR than FLAWS-div.

4D in vivo quantification of ankle joint space width using dynamic MRI.

Spatio-temporal evolution of joint space width (JSW) during motion is of great importance to help with making early treatment plans for degenerative joint diseases like osteoarthritis (OA). These diseases can affect people of all ages leading to an acceleration of joint degeneration and to limitations in the activities of daily living. However, only a few studies have attempted to quantify the JSW from moving joints. In this paper, we present a generic pipeline to accurately determine the changes of the JSW during the joint motion cycle. The key idea is to combine spatial information of static MRI with temporal information of low-resolution (LR) dynamic MRI sequences via an intensity-based registration framework, leading to a high-resolution (HR) temporal reconstruction of the joint. This allows the temporal JSW to be measured in the HR domain using an Eulerian approach for solving partial differential equations (PDEs) inside a deforming inter-bone area where the HR reconstructed bone segmentations are considered as temporal Dirichlet boundaries. The proposed approach has been applied and evaluated on in vivo MRI data of five healthy children to non-invasively quantify the spatio-temporal evolution of the JSW of the ankle (tibiotalar joint) during the entire dorsi-plantar flexion motion cycle. Promising results were obtained, showing that this pipeline can be useful to perform large-scale studies containing subjects with OA for different joints like ankle and knee.

PET-based prognostic survival model after radiotherapy for head and neck cancer.

PURPOSE: The aims of this multicentre retrospective study of locally advanced head and neck cancer (LAHNC) treated with definitive radiotherapy were to (1) identify positron emission tomography (PET)-18F-fluorodeoxyglucose (18F-FDG) parameters correlated with overall survival (OS) in a training cohort, (2) compute a prognostic model, and (3) externally validate this model in an independent cohort. MATERIALS AND METHODS: A total of 237 consecutive LAHNC patients divided into training (n = 127) and validation cohorts (n = 110) were retrospectively analysed. The following PET parameters were analysed: SUVMax, metabolic tumour volume (MTV), total lesion glycolysis (TLG), and SUVMean for the primary tumour and lymph nodes using a relative SUVMax threshold or an absolute SUV threshold. Cox analyses were performed on OS in the training cohort. The c-index was used to identify the highly prognostic parameters. A prognostic model was subsequently identified, and a nomogram was generated. The model was externally tested in the validation cohort. RESULTS: In univariate analysis, the significant PET parameters for the primary tumour included MTV (relative thresholds from 6 to 83% and absolute thresholds from 1.5 to 6.5) and TLG (relative thresholds from 1 to 82% and absolute thresholds from 0.5 to 4.5). For the lymph nodes, the significant parameters included MTV and TLG regardless of the threshold value. In multivariate analysis, tumour site, p16 status, MTV35% of the primary tumour, and MTV44% of the lymph nodes were independent predictors of OS. Based on these four parameters, a prognostic model was identified with a c-index of 0.72. The corresponding nomogram was generated. This prognostic model was externally validated, achieving a c-index of 0.66. CONCLUSIONS: A prognostic model of OS based on primary tumour and lymph node MTV, tumour site, and p16 status was proposed and validated. The corresponding nomogram may be used to tailor individualized treatment.

Activation of aryl hydrocarbon receptor regulates the LPS/IFNγ-induced inflammatory response by inducing ubiquitin-proteosomal and lysosomal degradation of RelA/p65.

Several studies have identified the aryl hydrocarbon receptor (AhR) as a negative regulator of the innate and adaptive immune responses. However, the molecular mechanisms by which this transcription factor exerts such modulatory effects are not well understood. Interaction between AhR and RelA/p65 has previously been reported. RelA/p65 is the major NFκB subunit that plays a critical role in immune responses to infection. The aim of the present study was to determine whether the activation of AhR disrupted RelA/p65 signaling in mouse peritoneal macrophages by decreasing its half-life. The data demonstrate that the activation of AhR by TCDD and ß-naphthoflavone (ß-NF) decreased protein levels of the pro-inflammatory cytokines TNF-α, IL-6 and IL-12 after macrophage activation with LPS/IFNγ. In an AhR-dependent manner, TCDD treatment induces RelA/p65 ubiquitination and proteosomal degradation, an effect dependent on AhR transcriptional activity. Activation of AhR also induced lysosome-like membrane structure formation in mouse peritoneal macrophages and RelA/p65 lysosome-dependent degradation. In conclusion, these results demonstrate that AhR activation promotes RelA/p65 protein degradation through the ubiquitin proteasome system, as well as through the lysosomes, resulting in decreased pro-inflammatory cytokine levels in mouse peritoneal macrophages.

[External beam radiotherapy cone beam-computed tomography-based dose calculation]. / Calcul de dose de radiothérapie à partir de tomographies coniques : état de l'art.

In external beam radiotherapy, the dose planning is currently based on computed tomography (CT) images. A relation between Hounsfield numbers and electron densities (or mass densities) is necessary for dose calculation taking heterogeneities into account. In image-guided radiotherapy process, the cone beam CT is classically used for tissue visualization and registration. Cone beam CT for dose calculation is also attractive in dose reporting/monitoring perspectives and particularly in a context of dose-guided adaptive radiotherapy. The accuracy of cone beam CT-based dose calculation is limited by image characteristics such as quality, Hounsfield numbers consistency and restrictive sizes of volume acquisition. The analysis of the literature identifies three kinds of strategies for cone beam CT-based dose calculation: establishment of Hounsfield numbers versus densities curves, density override to regions of interest, and deformable registration between CT and cone beam CT images. Literature results show that discrepancies between the reference CT-based dose calculation and the cone beam CT-based dose calculation are often lower than 3%, regardless of the method. However, they can also reach 10% with unsuitable method. Even if the accuracy of the cone beam CT-based dose calculation is independent of the method, some strategies are promising but need improvements in the automating process for a routine implementation.

[MRI-based radiotherapy planning]. / Planification à partir d'imagerie par résonance magnétique en radiothérapie.

MRI-based radiotherapy planning is a topical subject due to the introduction of a new generation of treatment machines combining a linear accelerator and a MRI. One of the issues for introducing MRI in this task is the lack of information to provide tissue density information required for dose calculation. To cope with this issue, two strategies may be distinguished from the literature. Either a synthetic CT scan is generated from the MRI to plan the dose, or a dose is generated from the MRI based on physical underpinnings. Within the first group, three approaches appear: bulk density mapping assign a homogeneous density to different volumes of interest manually defined on a patient MRI; machine learning-based approaches model local relationship between CT and MRI image intensities from multiple data, then applying the model to a new MRI; atlas-based approaches use a co-registered training data set (CT-MRI) which are registered to a new MRI to create a pseudo CT from spatial correspondences in a final fusion step. Within the second group, physics-based approaches aim at computing the dose directly from the hydrogen contained within the tissues, quantified by MRI. Excepting the physics approach, all these methods generate a synthetic CT called "pseudo CT", on which radiotherapy planning will be finally realized. This literature review shows that atlas- and machine learning-based approaches appear more accurate dosimetrically. Bulk density approaches are not appropriate for bone localization. The fastest methods are machine learning and the slowest are atlas-based approaches. The less automatized are bulk density assignation methods. The physical approaches appear very promising methods. Finally, the validation of these methods is crucial for a clinical practice, in particular in the perspective of adaptive radiotherapy delivered by a linear accelerator combined with an MRI scanner.

Uncoupling Protein Overexpression in Metabolic Disease and the Risk of Uncontrolled Cell Proliferation and Tumorigenesis.

In metabolic diseases such as obesity, metabolic syndrome and type II diabetes, the over-expression of uncoupling proteins (UCPs) in a response to increased reactive oxygen species (ROS) generation by mitochondrial respiratory complexes, and to the excess of free fatty acid (FFA) supply from adipose tissue, may protect cells from oxidative stress, lipotoxicity and in turn from death. UCPs by reducing superoxide anion and H2O2 generation trigger several signals to cell for their adaptation to the lipotoxic microenvironment. In mitochondria, a decrease of cytochrome c (cyt c) and proapoptotic protein release promotes cell survival and proliferation. The altered lipid metabolism also affects cardiolipin susceptibility to the peroxidation, a process involved in the dissociation of cyt c from mitochondrial inner membrane and its release, a key step of apoptosis. Therefore, UCPs by attenuating ROS generation and lipotoxicity may downregulate programmed cell death, a well-known physiological process controlling cell proliferation contributing to uncontrolled cell proliferation and tumorigenesis. In addition, tumor cells over-expressed UCPs, by inhibiting ROS generation acquire resistance to death during pharmacological treatment with oxidative stress drug inducers. Therefore, the aim of this review is to discuss recent findings regarding the role that UCPs play in cell survival by protecting against ROS generation and maintaining bioenergetic metabolism homeostasis to promote cell proliferation.

[Adaptive radiotherapy in routine use? State of the art: The medical physicist's point of view]. / Radiothérapie adaptative en routine ? État de l'art : point de vue du physicien médical.

The development of both image-guided and intensity-modulated radiotherapy has underlined the question of treatment adaptation to anatomical and/or biological changes occurring during radiotherapy course and modifying delivered dose to the patient. Adaptive radiotherapy has been introduced when several plans are used to treat a patient during radiotherapy. Adaptation may be performed online, offline or in a hybrid way. New images of the patient are needed for adaptive radiotherapy to perform many processes: image registration, segmentation and evaluation of cumulative dose. Deformable image registration methods are generally used to image registration and contours propagation. Fraction and cumulative dose evaluations use deformable image registration methods or more complex methods based on Monte-Carlo calculation. These methods have uncertainties and have to be evaluated. However, evaluation and validation tools are still being developed. The physicist's mission is to ensure that every new technology, such as adaptive radiotherapy, is deployed with highest safety, by technical validation and by implementing a specific quality assurance program. Adaptive radiotherapy implementation still raises many questions, so its potential clinical application requires great caution and should be carefully explored in prospective clinical trials.

Recent advancements in toxicity prediction following prostate cancer radiotherapy.

In external beam radiotherapy for prostate cancer limiting toxicities for dose escalation are bladder and rectum toxicities. Normal tissue complication probability models aim at quantifying the risk of developping adverse events following radiotherapy. These models, originally proposed in the context of uniform irradiation, have evolved to implementations based on the state-of-the-art classification methods which are trained using empirical data. Recently, the use of image processing techniques combined with population analysis methods has led to a new generation of models to understand the risk of normal tissue complications following radiotherapy. This paper overviews those methods in the case of prostate cancer radiation therapy and propose some lines of future research.

Biochemical and biological analysis of Philodryas baroni (Baron's green racer; Dipsadidae) venom: relevance to the findings of human risk assessment.

Philodryas baroni--an attractively colored snake--has become readily available through the exotic pet trade. Most people consider this species harmless; however, it has already caused human envenomation. As little is known about the venom from this South American opisthoglyphous "colubrid" snake, herein, we studied its protein composition by sodium dodecyl sulfate-polyacrylamide gel electrophoresis (SDS-PAGE), as well as its effects on the hemostatic system. Both reducing and nonreducing SDS-PAGE analysis demonstrated that the venom exhibits greatest complexity in the range of 50-80 kDa. The venom displayed proteolytic activity toward azocollagen, with a specific activity of 75.5 U mg⁻¹, and rapidly hydrolyzed the Aα-chain of fibrinogen, exhibiting lower activity toward the Bß- and γ-chains. The venom from P. baroni showed no platelet proaggregating activity per se, but it inhibited collagen- and thrombin-induced platelet aggregation. Prominent hemorrhage developed in mouse skin after intradermal injection of the crude venom, and its minimum hemorrhagic dose was 13.9 µg. When injected intramuscularly into the gastrocnemius of mice, the venom induced local effects such as hemorrhage, myonecrosis, edema, and leucocyte infiltration. Due to its venom toxicity shown herein, P. baroni should be considered dangerous to humans and any medically significant bite should be promptly reviewed by a qualified health professional.

Magnetic nanoparticles: new players in antimicrobial peptide therapeutics.

Antimicrobial peptides are distributed in all forms of life presenting activity against bacteria, fungi, viruses, parasites and cancer. In spite of the tremendous potential of these molecules, very few of them have been successfully developed into therapeutics. The major problems associated with this new class of antimicrobials are molecule stability, toxicity in host cells and production cost. A novel strategy to overcome these obstacles is conjugation to nanomaterials. Magnetic nanoparticles have been widely studied in biomedicine due to their physicochemical properties. The conjugation of antimicrobial peptides to magnetic nanoparticles could combine the best properties of both, generating an improved antimicrobial nanoparticle. Here we provide an overview and discuss the potential application of magnetic nanoparticles conjugated to antimicrobial peptides in overcoming diseases.

Performance of innovative PU-foam and natural fiber-based composites for the biofiltration of a mixture of volatile organic compounds by a fungal biofilm.

The performance of perlite and two innovative carriers that consist of polyurethane (PU) chemically modified with starch; and polypropylene reinforced with agave fibers was evaluated in the biofiltration of a mixture of VOCs composed of hexane, toluene and methyl-ethyl-ketone. At a total organic loading rate of 145 gCm(-3)h(-1) the elimination capacities (ECs) obtained were 145, 24 and 96 gCm(-3)h(-1) for the biofilters packed with the PU, the reinforced polypropylene, and perlite, respectively. Specific maximum biodegradation rates of the mixture, in the biofilters, were 416 mgCg(protein)(-1) h(-1) for the PU and 63 mgCg(protein)(-1) h(-1) for perlite, which confirms the highest performance of the PU-composite. 18S rDNA analysis from the PU-biofilter revealed the presence of Fusarium solani in its sexual and asexual states, respectively. The modified PU carrier significantly reduced the start-up period of the biofilter and enhanced the EC of the VOCs. Thus, this study gives new alternatives in the field of packing materials synthesis, promoting the addition of easily biodegradable sources to enhance the performance of biofilters.