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|---|---|---|
Spatial integration in the dendrites. In these simulations on the Z+ PC model, type II BPRs were elicited by 500 Hz—10 spikes pf bursts in dendritic sectors I and II and SC synapses were activated by 130 Hz—three spikes trains in the same sectors. The number of active pf synapse was either 50 or 100. (A) The raster plots and PSTH show model responses when sectors I and II are activate alone or together. (B) The histograms show the amplitude of PSTH peak and the depth and duration of the pause in the different cases.
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study
| 100.0 |
When activation in sector I preceded sector II, or vice versa, the bursts were initially fused together but then separated generating characteristic response profiles (Figure 11). When sector II preceded sector I, the unified burst initially decreased and then approached the level of the burst in sector II before separating into two individual bursts. For longer delays, the second burst was reduced along the time course of the BPR pause and finally recovered to sector I burst amplitude. When sector I preceded sector II, the responses behaved similarly. Starting from a reduced conjoint burst, the burst amplitude increased toward that of the burst in sector I. For longer delays, the second burst was reduced along the time course of the BPR pause and finally recovered to sector II burst amplitude.
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study
| 100.0 |
Temporal integration in the dendrites. In these simulations on the Z+ PC model, type II BPRs were elicited by 500 Hz—10 spikes bursts to 100 pfs in dendritic sectors I and II and SC synapses were activated by 130 Hz—three spikes trains in the same sectors. Following activation of one sector, the other was delayed by 10–200 ms. (A) The raster plots and PSTH show model responses when sectors II precedes sector I (left) or when sectors I precedes sector II (right). (B) The plots show the amplitude of PSTH peaks in the different cases. The levels of isolated sector I and II responses are indicated by dashed lines.
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study
| 100.0 |
The present simulations allowed to investigate the foundations of PC responsiveness to synaptic bursts in a way that would not be possible with experiments only. Using the model, we could predetermine the composition of synaptic input patterns and analyze the neuron response mechanisms by independently monitoring several parameters (like membrane potential, ionic currents and calcium concentration) over multiple dendritic compartments. In response to pf and SC inputs, the PC model generated BPRs based on voltage-dependent activation of the dendritic Ca-KCa channel system. BPRs could reliably represent complex granular and molecular layer input patterns and depended on the specific sector of the dendritic tree that was stimulated, on the ionic channel complement, and on the excitatory/inhibitory synaptic pattern. These simulations suggest therefore that PCs exploit their intrinsic electroresponsiveness and the input pattern topography on the dendrites in order to generate a flexible BPR code (Herzfeld et al., 2015) to be relayed to DCN neurons.
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study
| 100.0 |
This investigation was made possible by the use of an advanced model of the PC (Masoli et al., 2015), which was developed from earlier ones (De Schutter and Bower, 1994a,b; Rapp et al., 1994; Roth and Häusser, 2001; Steuber et al., 2007; Masoli et al., 2015) by including novel electrophysiological features and was validated against a large set of recent experimental data. The model was implemented with ionotropic synapses coming from granule cells (both aa and parallel fibers) and SCs. Additional synaptic mechanisms that may affect the response to specific input patterns (e.g., see Barbour et al., 1994; Takahashi et al., 1995; Tabata et al., 2005; Blot and Barbour, 2014) remain to be assessed.
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study
| 100.0 |
The pf synaptic transmission was calibrated to match responses evoked by random input patterns (Dittman et al., 2000), ensuring that pf synapses could precisely reproduce the temporal dynamics of short-term synaptic plasticity. The aa were made identical to pf synapses but were located on distal rather than proximal dendrites. A potentiation of the aa (Sims and Hartell, 2005, 2006; Walter et al., 2009) was required to counterbalance the longer electronic distance (L = 1.4 vs. L = 0.4) from soma (Roth and Häusser, 2001), thus ensuring the reported functional equivalence of aa and pf synapses (Walter et al., 2009).
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study
| 100.0 |
The bursts in type I and type II PC responses (De Zeeuw et al., 2011) was similar, in agreement with the fact that inhibition arrives after the burst is terminated (typically 5–10 ms later, Ramakrishnan et al., 2016). Therefore, the granule cell output patterns could directly reflect onto the PC burst, supporting experimental observations (Cao et al., 2012; Herzfeld et al., 2015).
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study
| 100.0 |
In the Z+ PC model, the pause was largely determined by intrinsic membrane properties and was accentuated by molecular layer interneuron inhibition, while in the Z− PC model, the pause was much more strictly dependent on SC inhibition. It is therefore possible that PCs in Z+ and Z− zones undergo different control schemes through the inhibitory interneuron network of the molecular layer.
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study
| 100.0 |
In response to random synapse stimulation, the burst: (i) started precisely in coincidence with the arrival of synaptic inputs; (ii) had a duration faithfully reproducing that of synaptic inputs; (iii) had a frequency proportional to input intensity; but (iv) was poorly sensitive to input frequency. Moreover, (iv) the burst and pause length co-varied generating a linear relationship with the input burst length. Therefore, the timing and duration of granule cell discharge and the number of discharging granule cells would be the most critical parameters controlling the burst (Arleo et al., 2010; Galliano et al., 2013).
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study
| 100.0 |
Burst and pause precision could be fine-tuned on the millisecond time-scale by pf release probability but much less so by receptor conductance, suggesting a specific role for presynaptic forms of plasticity at the pf-PC synapse in tuning transmission precision (Hansel et al., 2001; Gao et al., 2012).
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study
| 100.0 |
The BPR demonstrated a remarkable sensitivity to synapse location that caused the modulation of pause length. Therefore, the geometrical arrangement of input patterns could be important to shape BPR (Bower, 2010; Abrams and Zhang, 2011; Wilms and Häusser, 2015; Valera et al., 2016), e.g., by differentiating responses to aa and pf synapses (Bower, 2002) or by exploiting prewired connections from granule cell clusters (Valera et al., 2016).
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study
| 100.0 |
Different dendritic sectors could interfere one with each other in determining complex BPR combinations and sequences (Santamaria and Bower, 2005). The interference was determined by the generation of non-linear supra-threshold events driven by Ca spikes. Threshold crossing depended on a minimal number of active synapses and was enhanced by the high input conductance of terminal regions. As an important consequence, this would make the aa superior to pf synapses for generating dendritic Ca spikes and in controlling dendritic response patterns (Bower, 2002).
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study
| 100.0 |
These observations suggest that BPRs represents a flexible coding strategy accounting for the timing, duration and intensity of input granule cell spike patterns and that can be modulated by the spatiotemporal distribution of the input, by its intensity, by synaptic plasticity and by inhibitory interneuron activity.
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study
| 99.9 |
Model simulations also helped hypothesizing how PC dendrites process incoming synaptic inputs through BPRs. Dendritic Ca channels, primed by pf or aa EPSPs, would generate a depolarizing current flowing through the dendrites and activate a spike burst in the AIS. The corresponding raise in [Ca]i would activate KCa channels causing a protracted hyperpolarization, interrupting pacemaking and generating the pause. The whole process turned out to be very sensitive to the location of synaptic inputs on the dendrites. Actually, EPSPs amplitude was larger at longer electrotonic distances and this enhanced the threshold crossing for generating local Ca spikes, that could then spread around invading neighboring dendritic regions. Thus, the combined effect of dendritic structure and voltage-dependent ionic channels generated non-linear interactions sculpting the spatio-temporal profile of local [Ca]i and BPRs. It is tempting to speculate that this would eventually extend the plastic and computational properties of PCs beyond the linear perceptron hypothesized previously (Brunel et al., 2004).
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study
| 100.0 |
A peculiarity of the PC dendrites is the enrichment in Ca channels (Llinás and Sugimori, 1980a,b), which include both HVA (Cav2.1) and multiple LVA (Cav3.1, Cav3.2, Cav3.3) subtypes (Ly et al., 2016). While Cav2.1 (the classical PC P-type channel) was known to regulate KCa1.1 (BK) channel activation and therefore the fast action potential AHP, the role of LVA channels remained uncertain. The present simulations show that LVA Ca channels (including at least cav3.1 and Cav3.3) are critical for BPR, since they are activated during the burst and then play a local but key role in activating the KCa2.2 (SK2) and KCa3.1 (SK4) channels, thereby regulating the pause. The relevant role of LVA calcium channels in EPSP generation by input bursts has recently been reported experimentally (Ly et al., 2016).
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study
| 100.0 |
It should be noted that, when simulating intrinsic electroresponsiveness with somatic recordings, LVA Ca channels and KCa channels proved either noncritical or subcritical (Masoli et al., 2015). Therefore, in light of the present simulations, the tuning procedures of maximum ionic conductances in neuronal models should be targeted toward features addressing synaptic response pattern (Marasco et al., 2013) rather than just responses generated by somatic current injection (Druckmann et al., 2007, 2008; Masoli et al., 2015, 2017). Since some of these channels are located in the spines (specifically Cav3.1), a future assessment of the impact of spines in the PC model is warranted.
|
study
| 99.94 |
In aggregate, these simulations showed that BPRs could fully exploit dendritic ionic channels (Llinás and Sugimori, 1980a,b) to generate voltage-dependent responses. However, this mechanism did not compromise the linearity of BPR input-output relationships supporting the predictions that PC may work as a linear perceptron (Brunel et al., 2004) and a perfect integrator (Phoka et al., 2010). Simulations supported the concept that BPRs represent a fundamental operating mode of PCs (Walter and Khodakhah, 2006, 2009; Chen et al., 2016). First, BPRs could discriminate among different input patterns coming from the mossy fibers and expanded/recoded in the granular and molecular layer (Marr, 1969). Second, BPRs sensitivity on the millisecond scale would allow PCs to operate as precise temporal devices (Eccles, 1973). Third, BPRs could discriminate among synaptic locations, generating an exquisite sensitivity to the topography of input patterns (Migliore et al., 2008). Finally, BPRs could generate complex combinations and sequences (Santamaria and Bower, 2005). By expressing these properties, BPRs would effectively integrate the spatio-temporal activity patterns generated in the cerebellar cortex into salient engrams, a prediction warranted experimental testing through electrophysiological, imaging and optogenetic recordings.
|
study
| 99.94 |
Glioblastoma is the most aggressive and the most common type of brain malignant tumors in adults with an average survival of 12 months after diagnosis. This poor prognosis is due to the fast growth and highly infiltrative feature of glioma cells, which are able to migrate from the main tumor mass and invade the normal brain parenchyma [1–4]. Preoperative imaging does not always clearly define the edge of the tumor because of this infiltration, and the presence of a positive margin after surgery contributes to frequent recurrence rates . In this study a new contrast agent consisting of a fluorescently labeled Affibody molecule that binds to the epidermal growth factor receptor (EGFR) was examined for uptake in orthotopic glioma tumors to assess the contrast available to guide surgery.
|
study
| 99.94 |
Several recent studies have demonstrated the use of intraoperative fluorescent imaging as a tool to overcome some limitations of conventional white light surgery, to enhance the visual contrast between tumor and normal tissue [6–10]. Oral administration of 5-ALA induces PpIX fluorescence in high grade glioblastoma tumors, which can be imaged during fluorescent-guided surgery (FGS). This has been adopted clinically in several countries, following success reported in both preclinical and clinical trials. However, the observed PpIX accumulation is thought to be partially due to the blood brain barrier breakdown, allowing the ALA to leak through, which can be less pronounced in the tumor edges [11, 12]. In comparison, exogenous protein targeting has allowed identification of several biomarkers which are overexpressed in many types of cancer such as the cell surface receptors EGFR and VEGFR [13–17] which have been studied as targets for therapeutic drug delivery [18–20] and diagnostic imaging [21–23]. Rosenthal and collaborators (2015) described the results of the first-in-human clinical trial using cetuximab conjugated to IRDye® 800CW to guide the surgery of head and neck squamous cell carcinoma and the fluorescence was correlated to EGFR expression of the tumor. The tumor-to-background contrast was dose-dependent, although there was evidence of receptor saturation at higher dose. However, because of the long biological half-life of antibodies, the tumor-to-normal contrast increases over time .
|
review
| 99.9 |
In this study, fluorescently labeled affibody molecules (Affibody, Solna, Sweden) targeting EGFR have been developed for human use. Affibody molecules are small proteins (derived from a 58 amino acids long Z-domain scaffold) . The EGRF-binding affibody molecules were engineered with a maleimide linker for site-specific cysteine conjugation with a fluorescent dye such that fluorophore labeling does not interfere with the binding domain site for a receptor, thereby maintaining binding affinity. These molecules have high affinity (approximately K d ~ 2.8 nM) and demonstrate localization in glioma tumors [13, 26]. Due to their small size, affibody molecules present fast clearance from the blood and reasonable diffusion through tissue, which are the desirable features for a high-contrast surgical imaging agent .
|
study
| 100.0 |
In a study performed by Lee and colleagues, the tumor accumulation of an anti-HER2 affibody conjugated to Alexa Fluor® 750 was evaluated. The results showed its potential as a probe for in vivo imaging of HER2-positive breast cancer . In a previous study, Sexton et al. showed that the accumulation of an anti-EGFR affibody, conjugated to IRDye® 800CW, was higher in rodent glioma tumors than the anti-EGFR antibody cetuximab conjugated to IRDye® 680RD. The anti-EGFR affibody molecule was present in the tumor periphery whereas the anti-EGFR antibody was primarily localized in the central portion of the tumor . In the present study, the tumor uptake of pre-GMP ABY-029 was evaluated for the contrast in tumor-to-normal brain, as a function of time and administered dose.
|
study
| 100.0 |
Anti-EGFR affibody molecules were manufactured under contract from Affibody AB (Solna, Sweden); IRDye® 800CW maleimide was specially produced by LI-COR Biosciences (Lincoln, Nebraska). The anti-EGFR affibody molecules labeled with IRDye® 800CW have been developed by Bachem and named pre-GMP ABY-029.
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other
| 99.9 |
The human glioblastoma cell line U251 was obtained from Dr. Mark Israel (Norris Cotton Cancer Center, Dartmouth-Hitchcock Medical Center, Lebanon, NH, USA) and cultured in DMEM supplemented with 10 % fetal bovine serum and 100 IU/ml penicillin-streptomycin. The cells were subcultivated at 80–90 % of confluence.
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other
| 90.3 |
Forty-eight female nude rats (6–8-week old) were used. The U251 cell line was chosen due to its clinically relevant level of EGFR expression. The animals were anesthetized using isoflurane (2 % and 1 l/min oxygen) and an incision was made in the scalp, with the brain accessed by a 1-mm rotary drill to create a burr hole. Guided using a stereotaxic frame (Stoelting Co, Wood Dale, IL, USA), the 1 × 106 cells in 5 μl phosphate-buffered saline (PBS) were injected at a 3-mm depth into the left cerebral hemisphere of the rats, 3 mm posterior to the bregma, using a Hamilton syringe (Hamilton Company, Reno, NV). The cells were injected over a 5-min period, and the needle slowly retracted from the brain. Bone wax (Ethicon, Inc., Piscataway, NJ, USA) was used to close the hole in the skull and the incision in the scalp closed, using 5–0 sterile non-absorbable suture material (Ethicon, Inc., Piscataway, NJ, USA).
|
study
| 99.94 |
Contrast-enhanced magnetic resonance imaging was used to monitor tumor growth in the brain. In these studies, the rats were anesthetized with isoflurane and maintained at a surgical anesthesia plane through the procedure. A Phillips Achieva 3.0T X-series MRI with a modified rodent coil (Philips Research Europe, Hamburg, Germany) was used . T1- and T2-weighted turbo-spin echo images were acquired prior to intravenous administration of 0.1 mmol of gadolinium Gd-DTPA (Magnevist®) and the post-contrast T1W image sequence was collected 10 min following gadolinium injection. The T2W image sequence was collected during the contrast uptake. The MRI images were processed and analyzed using NIRFAST Software (Version 1.12) [28, 29].
|
study
| 100.0 |
Two weeks post-tumor cell inoculation, the rats received a non-fluorescent diet (Purified Mouse Diet, MP Biomedicals, LLC, Illkirch, France) to reduce auto-fluorescence from chlorophyll contained in regular chow. Three to 4 weeks post-tumor inoculation, rats were randomly divided into 10 experimental groups to either receive different doses of ABY-029 (24.5, 49.0, or 122.5 μg/kg) at different time points (1–48 h) or PBS (control group). The lowest dose, 24.5 μg/kg, corresponds to the human equivalent microdose for a protein molecule, defined by the FDA as ≤30 nanomoles (Guidance for Industry, Investigators, and Reviewers-Exploratory IND Studies, 2006). After the predetermined time, the animals were euthanized by cervical dislocation; the brain was removed and sectioned into 2-mm thick slices. Three U251 inoculated rats and two sham rats, for each group, were used.
|
study
| 100.0 |
Fluorescence images from the sequential brain sections were acquired by scanning the 2-mm thick slices on the Odyssey Infrared Imaging System (LI-COR Biosciences) using the 800-nm channel, at 21-μm lateral spatial resolution. Eight to ten slices from each rat were examined in a single scan, and completed within minutes of brain removal.
|
study
| 99.94 |
For fluorescence image contrast analysis, the relative difference between the fluorescence intensity in the tumor and normal brain tissue was calculated according to the equation:\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$ \mathrm{Contrast}=\frac{\left({F}_{\mathrm{T}}-{F}_{\mathrm{N}}\right)}{\left({F}_{\mathrm{N}}-{F}_{\mathrm{B}}\right)} $$\end{document}Contrast=FT−FNFN−FB
|
study
| 99.94 |
where F is the region of interest (ROI) fluorescence from tumor (F T) and contralateral normal (F N) brain quantified in ImageJ® software (NIH, Bethesda, MD), and background being outside the brain region (F B). The ROI of both tumor region and contralateral normal brain was guided by custom delineation based upon the fluorescence images and confirmed with the hematoxylin and eosin images.
|
study
| 97.4 |
Following analysis of the fluorescence in the brain sections, the samples were fixed overnight in 4 % neutral buffered formaldehyde. Research Pathology Services at the Geisel School of Medicine at Dartmouth College prepared the following histopathology and immunohistochemistry tissue sections. Formalin-fixed tissues were dehydrated using crescent concentrations (70–100 %) of alcohol (Fisher Scientific, USA), cleared with xylene (Cat # X3P-1GAL, Fisher Scientific, USA) and embedded in paraffin (Cat # 7052, Sakura Finetek, Torrance, CA, USA). The brain sections were cut to 4-μm thickness and stained with hematoxylin and eosin (H&E) and for total EGFR using an anti-EGFR primary antibody (EP38Y) (Cat # ab52894; Abcam Inc., Cambridge, MA, USA) (immunohistochemistry).
|
study
| 99.9 |
Statistical analysis was performed using OriginPro® 8 software (OriginLab, Wellesley Hills, MA, USA). Student’s paired t test was performed to determine statistical significance of the difference in signal between the tumor regions and corresponding contralateral brain or animals undergoing sham surgery. Statistics assessment was also used to determine the difference between different doses and time points. Linear regression was used to compare the size of the tumor and contralateral normal brain fluorescence. This information was reported as a Pearson correlation coefficient (r). Results were considered statistically significant at a P < 0.05.
|
study
| 100.0 |
Pre-GMP ABY029 uptake was evaluated using an infrared imaging system and the level of fluorescence from rat ex vivo brain slices was acquired at different time points post-injection. Figure 1 presents the 1:1 correlation of whole brain fluorescence and H&E histologic staining. This co-registration demonstrates a high correlation between tumor presence and fluorescence.Fig. 1.Multiple plane co-registration of brain tumor morphology (a, d) and ABY-029 fluorescence (b, c) in a series of brain slices from the same rat. The tumor regions are fairly obvious in the H&E, and are circled in the lower left H&E images, which correlate well with the fluorescence areas. Each row from columns a and b or c and d correspond to the same slice of the brain
|
study
| 100.0 |
Multiple plane co-registration of brain tumor morphology (a, d) and ABY-029 fluorescence (b, c) in a series of brain slices from the same rat. The tumor regions are fairly obvious in the H&E, and are circled in the lower left H&E images, which correlate well with the fluorescence areas. Each row from columns a and b or c and d correspond to the same slice of the brain
|
other
| 82.4 |
There was high fluorescence heterogeneity, within and around the tumors (Fig. 2a). Histograms of the tumor fluorescence, shown in Fig. 2b, demonstrate the regular presence of two regions of intensity. The regions of high ABY-029 fluorescence intensity were often well correlated to the regions of high EGFR expression, as illustrated by ex vivo staining using anti-EGFR antibodies in Fig. 2d. The EGFR-specific staining confirms the localization patterns expected; however, it is important to note that low level ABY-029 fluorescence is still visible in the regions with lower EGFR-specific staining with antibodies.Fig. 2. a The distribution of ABY-029 fluorescence in the tumor region immediately after tissue removal. b The heterogeneity of fluorescence signal distribution for each corresponding slice. c The H&E-stained tissue. d The EGFR-stained tissue. This information illustrates the true EGFR expression patterns.
|
study
| 100.0 |
a The distribution of ABY-029 fluorescence in the tumor region immediately after tissue removal. b The heterogeneity of fluorescence signal distribution for each corresponding slice. c The H&E-stained tissue. d The EGFR-stained tissue. This information illustrates the true EGFR expression patterns.
|
other
| 74.7 |
Another feature evaluated in this study was the ability of ABY-029 to recognize positive margins in which migratory cells are presented (Fig. 3). Tumor cells cannot only migrate through blood vessels to infiltrate the normal brain, but also can be derived from the main tumor mass and migrate in surrounding brain tissue as seen by ABY-029 fluorescence in Fig. 3a.Fig. 3.These images represent the presence of fluorescent (EGFR) tumor cells at the margin of the primary tumor mass. a Ex vivo fluorescence analysis. b H&E staining (×0.6 magnification). c H&E staining (×10 magnification) and visualization of tumor cells migrating into normal brain tissue. The last row corresponds to sham surgery and, therefore, serves as a control brain tissue.
|
study
| 100.0 |
These images represent the presence of fluorescent (EGFR) tumor cells at the margin of the primary tumor mass. a Ex vivo fluorescence analysis. b H&E staining (×0.6 magnification). c H&E staining (×10 magnification) and visualization of tumor cells migrating into normal brain tissue. The last row corresponds to sham surgery and, therefore, serves as a control brain tissue.
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other
| 78.44 |
The effect of dose escalation and temporal analysis of the fluorescence is demonstrated in Fig. 4. The peak of fluorescence in tumors is observed at early times (1–4 h) in a dose-dependent manner and there is significant fluorescence in the glioma tumors for several hours after injection. Moreover, fluorescence in the tumor regions was significantly higher than in the contralateral normal brain, or in the brains of rats that received a sham surgery.Fig. 4.Normalized fluorescent signals are shown for all tumor and normal tissues slices analyzed, at all three dose levels (24.5, 49, 122.5 μg/kg), and at varying times following injection (1 h up to 24 h or 48 h). *P < 0.05, Student’s t test.
|
study
| 100.0 |
Figure 5a, b presents the fluorescence signal intensity from contralateral normal brain as a function of the tumor area detected by the lowest and highest dose of the pre-GMP ABY-029. There are no statistically significant fluorescence trends for tumor size in the 1× microdose group; however, there is a significance when the dose is elevated fivefold.Fig. 5.Fluorescence from the contralateral normal brain as a function of the observed tumor size for a microdose (24.5 μg/kg) and b five times the microdose (122.5 μg/kg); 1 h (closed symbols) and 24 h (open symbols) post-injection. The lines correspond significant trends observed from linear regression. c T1 (left) and T2 (right) MRI of a U251 tumor-bearing rat post-gadolinium injection. The tumor (T) can be seen as a focal region in the T1, with peri-tumor edema (E) in the T2 image.
|
study
| 100.0 |
Fluorescence from the contralateral normal brain as a function of the observed tumor size for a microdose (24.5 μg/kg) and b five times the microdose (122.5 μg/kg); 1 h (closed symbols) and 24 h (open symbols) post-injection. The lines correspond significant trends observed from linear regression. c T1 (left) and T2 (right) MRI of a U251 tumor-bearing rat post-gadolinium injection. The tumor (T) can be seen as a focal region in the T1, with peri-tumor edema (E) in the T2 image.
|
study
| 100.0 |
The success of a fluorescence-guided brain surgery is highly dependent of the tumor-to-normal brain fluorescence contrast, and the results are presented in Fig. 6. The contrast relative to the normal brain is dependent on the dose given and the time of data acquisition after dose administration. In our study, the contrast varied from 7 to 16 in the first 4 h. After 24 h, in the microdose level, the contrast is reduced by a factor of 3 to 2.7 resulting in a very low fluorescence intensity. However, with higher administered ABY-029 doses (two or five the microdose level), the contrast level decreased only slightly over time.Fig. 6.The tumor-to-normal brain contrast values are expressed as mean values ± standard error of mean using the ratio of data from Fig. 4 for each injection concentration and time point studied.
|
study
| 100.0 |
Several published studies have tested the concept of a receptor-binding molecule, conjugated to a near-infrared fluorescent probe that is able to be localized in the margin of tumor and normal tissue. The goal of this and similar research is to increase the tumor-to-background contrast ratio as a means of improving the tumor delineation during surgical resection, and to determine if injection at the microdose level was a reasonable administration concentration to achieve this. In 2011, van Dam and colleagues studied the use of folate conjugated to fluorescein isothiocyanate (FITC) to target the folate receptor α (FR-α) overexpressed in ovarian cancer. This receptor-targeting fluorescent probe demonstrated a promising approach for detection of the receptor positive human tumors compared to the conventional visual inspection during standard surgery . In neurosurgery, substantial efforts have been made with the metabolic marker protoporphyrin IX produced by mitochondrial heme synthesis [31–34], and indocyanine green perfusion imaging [35–37] to delineate the tumor borders during brain surgery. Based on this basic research, dedicated surgical microscope systems are now commercially available for fluorescence image acquisition in either the red (600–750 nm) or near-infrared (800+ nm) wavelength bands .
|
review
| 99.8 |
In this study, the tumor uptake of ABY-029 was examined as a function of its administered dose and time after injection. The co-localization of the tumor microenvironment and Affibody-fluorescent probe signal was observed through bulk analysis (Figs. 1, 2, and 3). However, the distribution of the fluorescence signal in the tumor was also documented to be highly heterogeneous (Fig. 2). This results from cellular heterogeneity and differentiation level of the glioma cells , and/or the spatial and temporal heterogeneity of the blood supply, leading to high delivery variability from the enhanced permeability and retention effect [40, 41]. The absence of fluorescence usually was observed in the tumor interior and it could be either correlated with necrotic areas (Fig. 2c inset), in which vascular supply is often inadequate or insufficient, or lower interstitial pressure present in peripheral areas of the tumor that allows leakage of macromolecules . Perhaps most importantly, the EGFR overexpression was documented by ex vivo staining with an independent antibody, and the presence of hot spots staining of ABY-029 appeared to be well correlated to the EGFR density (Fig. 2d inset).
|
study
| 100.0 |
Glioma cells are highly infiltrative i.e., they have the ability to migrate from the main tumor mass to the normal tissue surrounding the margins of the tumor. The accurate anatomical delineation of the tumor boundaries during surgery is challenging, and it is extremely important for the clinical success in the surgery. In this study, ABY-029 fluorescence was seen in tumor cells at the margin of main tumor mass (Fig. 3).
|
study
| 100.0 |
One point to be considered is the fact that EGFR is also highly expressed in some normal tissues, such as the liver, skin, and submaxillary salivary gland. Therefore, the bioavailability of ABY-029 could be reduced as a consequence of off-target EGFR binding of the NIR probe. The results from dose escalation showed a dose-dependent ABY-029 tumor uptake (Fig. 4), which can be related to saturation of EGFR in the liver . Moreover, the fluorescence from the tumor was higher than the contralateral normal brain or brain from the rats that received sham surgery. This was true even 48 h post-injection. Thus, these results show that there is high in vivo specificity for ABY-029 uptake by tumor cells.
|
study
| 100.0 |
An interesting result observed in this study was the increase in the contralateral normal brain fluorescence as a function of tumor area for the animals that received 5-fold larger dose than the initial dose (Fig. 5b), which could be correlated to the transport, likely due to edema, leading to nearly 10-fold higher uptake in the tumor, and approximately a 2-fold increase in tumor to normal tissue contrast. Curiously, at the lower injected dose of 24.5 μg/kg, the increase in normal brain uptake with tumor size was not as apparent, but this could have been due to the lower leakage rates into the tissue from lower concentration. In the cases of larger tumors, the ABY-029 uptake in the background normal brain presented in the extracellular matrix by the cerebrospinal fluid to intact areas of the brain, as seen in Fig. 5c. Similar results have been documented with PpIX fluorescence imaging near glioma tumors . More importantly, though, this increased background from edema-based perfusion to normal brain did not significantly decrease the tumor˗-to-normal contrast (Fig. 6), and a high contrast could be seen even after 24 h post-injection, which is important to cover all possible times for surgical use.
|
study
| 100.0 |
ABY-029 can be used in intraoperative fluorescent-guided surgery of glioma in order to improve detection of the tumor-to-normal tissue boundary and decrease the residual tumor cells surrounding the tumor margin, which is the key to improved prognosis of following resection of glioblastoma. The value of increasing the injected dose above a microdose appears clear, providing significant 2-fold increase in contrast and also a longer term increase extending out to 24 h. However, it is possible to see contrast in glioma tumors with injected doses as low as a standard FDA microdose level. GMP production of ABY-029 is in progress, and toxicological studies have been completed to confirm the safety of the molecular-targeted fluorescent probe for future clinical trial .
|
study
| 97.8 |
Friedreich’s ataxia (FRDA) is the most common autosomal recessive form of ataxia that affects approximately 1 in 50,000 Caucasians. FRDA is caused by autosomal recessive GAA trinucleotide expansion in the first intron of the FXN gene on the proximal long arm of chromosome 9, which interferes with frataxin transcription. Moreover 1–3% of the patients are heterozygosus for the GAA expansions on one allele and a point mutation or deletion on the other allele of FXN. Typical age at onset occurs around or even before puberty, although showing a very large variability even between siblings. Progressive gait ataxia, dysmetria, dysdiadocokinesia, muscular weakness, sensory loss, areflexia are typical clinical features of the disease. In addition to neurodegenerative symptoms, there is a multiple systemic involvement that includes cardiomyopathy, scoliosis, diabetes mellitus, foot deformities, abnormalities of eye movements. FRDA patients are wheelchair bound by a disease duration of 15.5 years (range 3–44) with a shortened life expectancy .
|
review
| 99.9 |
One of the challenges for therapeutic clinical trials in FRDA is the development of outcome measures, which should have good reliability, validity, reproducibility and sensitivity to change. Nowadays, more than in the past, the longitudinal studies of FRDA disease are important to analyze disease progression and to improve the accuracy of prognosis but mostly to prove the adequacy and the sensitivity to change of the outcome measures. An accurate knowledge of the disease natural history is in fact a critical assumption upon which a clinical trial has to be designed.
|
review
| 88.7 |
The Scale for the Assessment and Rating of Ataxia (SARA) for functional assessments has been recognized as the most sensitive scale in a longitudinal analysis of FRDA patients in comparison with ICARS and FARS. SARA has been considered the best choice for its high construct validity, its good effect size and for its compact structure. Sensitivity to longitudinal change of SARA was evaluated in adult FRDA subjects by Marelli and coll. Furthermore, although there are no validated scales for childhood, SARA is reliably applicable to children beyond the age of 10 years and proved to be more suitable for long-term quantitative ataxia assessment from child- to adulthood in comparison to ICARS and BARS. However, the complexity of the neurological phenotype of FRDA due to the intricate interplay between cerebellar degeneration, somatosensory loss and muscle atrophy leads to explore the specific functional and gait changes over time more deeply and with the use of sensitive and objective measures.
|
review
| 92.5 |
Moreover, as well-known in the literature[10–13], the high intra-subject variability of all gait measures is the peculiar and distinctive aspect of ataxic gait that needs an accurate and exhaustive evaluation. However, in FRDA only a few studies have investigated the walking pattern by means of an objective gait analysis. These studies reported a good relationship between gait parameters and the clinical status of disease [12–16].
|
study
| 94.5 |
Unfortunately, these studies have focused only on spatiotemporal parameters (e.g. velocity, step length, single-double support %, etc.) of the gait or in the adult population of FRDA. Other studies compared gait parameters among ataxic patients with the heterogeneous etiology of ataxia. Furthermore, only few prospective natural history studies are reported in the literature and all the studies have used simply functional rating scales to describe the progression rate of impairment and disability in FRDA[18–20].
|
review
| 99.9 |
To the best of our knowledge, no longitudinal study on FRDA patients employing gait analysis has been described so far, although this methodology of functional evaluation of gait progression proved to be a useful tool in longitudinal studies both on normal children during growth and on affected children with Cerebral Palsy.
|
study
| 99.94 |
In the present longitudinal study, we report changes in a one-year time frame of the gait analysis and SARA in a cohort of children and adolescents affected by FRDA. The goal of this study was threefold: First, to investigate analytically the FRDA gait pattern, through an accurate measurement of kinematic and kinetic data in comparison with healthy controls. Second, to assess the spectrum of changes over 12 months in the individual measures and the correlation between clinical and objective assessment. Third, to identify among the redundant indices of gait analysis which parameters better reflect the core gait pattern of FRDA in terms of sensitivity to change in a longitudinal evaluation and in relation to the functional disease status. Our hypothesis is that functional outcomes measures integrated by instrumental evaluation may increase their sensitivity, reliability and suitability for the follow-up of the disease progression and for the application in clinical trials and in rehabilitative programs.
|
study
| 99.94 |
Eleven genetically confirmed FRDA patients (age range 6.9–17.8; mean±SD 13.4±3 years; 8 females) were enrolled in this study. Patients were age-matched with 13 typically developing children and adolescents (age range 5.5–14;mean±SD10.3±3; 7females). Table 1 shows the clinical and functional characteristics of our cohort. Nine participants were able to walk independently, 2 patients needed mild walking aids (cans). All the patients were taking idebenone (10 mg/kg/day) for more than 6 months at the time of the study[23–26]. All the patients were able to complete the entire protocol in an outpatient setting. No patient had visual impairment except for slight abnormalities of eye movements (fixation instability, square wave jerks).
|
study
| 99.94 |
Ten patients were evaluated again after a one-year follow-up (mean 15.2 months): two of them lost ambulation during the period between the two sessions. One patient dropped out of the follow-up. Therefore, at the follow-up ten patients were evaluated with the SARA scale, and eight of them were able to execute the gait analysis.
|
clinical case
| 99.6 |
Standardized gait analysis was conducted by eight-camera motion capture system (Vicon MX, UK) and two force plates (AMTI, Or6). The sampling rates was set at 200 Hz for motion capture system and at 2 kHz using the two force plates (AMTI, or-6, US). The two force plates were hidden in the middle portion of a 10 meters walkway. Assessments were video recorded to assist clinical interpretation of data. After some familiarization trials, when the patients had reached their own self-selected barefoot speed, a specific starting position was selected in order to achieve the whole foot landing on the force plate avoiding any further verbal instructions. 33 markers were located on anatomical landmarks of the subjects as indicated by the Plug-in-Gait protocol in order to reconstruct a full body kinematic and kinetic model. Fifteen body segments were modelled. Kinematic and kinetic temporal series were normalized to the stride duration. Walking velocity and step length were normalized to leg length. Kinetic data were normalized to subject’s weight.
|
study
| 100.0 |
The following list of variables was selected to detect the main gait strategies adopted by the patients and compared with a cohort of age-matched healthy subjects. In particular, we considered: walking velocity, step and stride length, stride time, step width, single support (SS) and double support (DS) percentage, lateral displacement of the centre of mass (COM), hip angle at initial contact (Hc), hip maximum extension (H1), hip maximum flexion (H2), hip abduction in stance (Habdc and Habd1) and in swing (Habd2), knee angle at initial contact (Kc), knee flexion during load response (K1), knee extension in late stance (K2), knee flexion during swing (K3), ankle angle at initial contact (Ac), plantar flexion during load response (A1), dorsal flexion in late stance (A2), plantar flexion in early swing (A3), dorsal flexion in swing (A4), peaks of foot intra-rotation and extra-rotation (Foot-Int, Foot-Ext), maximum and minimum hip moments (HMmax, HMmin) and knee moments during stance (KMmax, KMmin), maximum ankle dorsal moment in stance (AM), hip (HP1, HP2, HP3), knee (KP1, KP2), and ankle (APmax, APmin) maximum power generation and absorption during stance (see Fig 1).
|
study
| 100.0 |
The figure shows the time series of the variables examined in the paper. In the horizontal axis is represented the time normalized respect to the duration of the gait cycle (from the hell contact to the floor to the ipsilateral succeeding hell contact). The arrows indicate the peak values here studied. The black line represents the mean values of the baseline of the patient with FRDA, while the gray band represents the standard deviation of the control group. In the first row are represented in degree the flexion and extension rotation of the hip, the knee and the ankle, from left to right respectively. In the second and third rows are represented joints moment and power, respectively, normalized respect to body wheight. In the four row is represented the hip ab-adduction and the angle of the internal end external rotation of the foot.
|
study
| 100.0 |
The t-Student’s test with Bonferroni correction was applied to identify statistical significance between patients with FRDA and controls. The values of step length, stride length and step width have been normalized for participant’s height. Repeated measures t-Student’s tests were executed to verify statistical differences between the baseline and the follow-up values of the patients. T-Student’s tests were similarly applied to evaluate statistical differences on the standard deviations between FRDA and controls and for the patients between baseline and follow-up. The differences between standard deviations were assumed as an index of variability in the motor pattern. Correlational analyses were also executed among the variables of the study: demographic, genetic, clinical variables and gait analysis parameters. Statistical analyses were conducted using the software IBM-SPSS 20.
|
study
| 100.0 |
By comparing the gait parameters of FRDA and control group, we found significant differences for several indexes, as reported in Table 2. Bonferroni correction for multiple comparisons were applied and α = 0.0013 has been assumed as threshold for significance (α = 0.05 divided by 37 comparisons). The patients showed a significant reduction of walking velocity (0.9 vs. 1.2 m/s, FRDA vs. controls: t(81) = -6.6, p <.0013) with a shorter step (0.36 vs 0.41 m: t(103) = -7, p <.0013) and stride length (0.71 vs 0.82 m: t(107) = -7.8, p <.0013) and an increase of the stride time (1.3 vs 1 s: t(130) = -8.8, p <.0013). The maximal lateral displacement of the COM were double than controls (77.8 vs 34 cm: t(34) = 5, p <.0013), and the % of double support was increased (24.8 vs 17.7: t(66) = 4.5, p <.0013).
|
study
| 100.0 |
hip angle at initial contact (Hc), hip maximum extension (H1), hip maximum flexion (H2), knee angle at initial contact (Kc), knee flexion during load response (K1), knee extension in late stance (K2), knee flexion during swing (K3), ankle angle at initial contact (Ac), plantar flexion during load response (A1), dorsal flexion in late stance (A2), plantar flexion in early swing (A3), dorsal flexion in swing (A4), maximum ankle dorsal moment in stance (AM), ankle maximum power generation and absorption during stance (APmax, APmin), peaks of foot intra-rotation and extra-rotation (Foot-Int, Foot-Ext), maximum and minimum hip moments (HMmax, HMmin), maximum and minimum knee moments during stance (KMmax, KMmin), hip maximum power generation and absorption during stance (HP1, HP2, HP3), maximum power generation and absorption during stance (KP1, KP2), hip abduction in stance at initial contact (Habdc), in middle stance (Habd1) and in swing (Habd2), single support duration in percentage SS(%) and double support duration in percentage DS(%). See also Fig 1.
|
other
| 90.06 |
As far as the kinematic parameters were concerned, we observed a significant different behavioral pattern of the ankle and knee, in particular we found that Ac, A1, and A2 were significantly reduced in FRDA in the mean values (all p values <.0013, see Table 2), meaning increased plantar flexion. Also K1, K2 were reduced, whereas K3 was increased (all p <.0013) in FRDA in comparison to the healthy subjects. The analysis of kinetics showed significant differences in the moment AM, KMmax, KMmin and HMmax (all p <.0013) and in the power of AP max (p <.0013) and HP1 (p <.0013).
|
study
| 100.0 |
We also conducted the analysis of the differences between the standard deviations calculated for the patients with FRDA and controls in order to evaluate the previously described increase of gait variability in patients with FRDA. The results in Table 2 showed increasing variability in FRDA vs Controls in the maximum ankle plantar flexion during stance (A2; t(22) = 3.9, p <.0013), and in single support percentage (SS; t(22) = 8.5, p <.0013).
|
study
| 100.0 |
Since the presence of multiple comparisons, Bonferroni correction were also applied and the threshold for significance has been assumed as α = 0.0013. Among all the significant parameters, only K1 (t(7) = 6.5, p<.0013) and K2 (t(7) = 8.4, p <.0013) were confirmed as statistically changed during the time of the follow-up. The differences at the SARA scale did not reach the corrected threshold for significance.
|
study
| 100.0 |
For completeness of information longitudinal analysis without multiple comparison correction are also reported. The results demonstrated worsening of SARA scores: Total score (from 12.6 to 15.9; t(9) = -4.2, p <.01); Gait (from 3 to 3.7; t(9) = -2.7, p <.05); Stance (from 2.7 to 3.1; t(9) = -2.4, p <.05); and Sitting (from 0.7 to 1.3; t(9) = -3.7, p <.01). Analysis of kinematic data showed an increase of the knee shift towards extension during stance, as evidenced by the variation of Kc (from 14.4 to 8.2; t(7) = 4.2, p <.01), K1 (from 21.2 to 11.4; t(7) = 6.5, p <.001) and K2 (from 6.8 to -0.5; t(7) = 8.4, p <.001). Moreover, the ankle showed similar behavior with a shift towards the plantar flexion evidenced by the variation of Ac (from -3.9 to -8.6; t(7) = 2.4, p <.05), A1 (from -4.9 to -8.7; t(7) = 3.4, p <.05) and A2 (from 12.7 to 10.1; t(7) = 3.4, p <.05). In Fig 2 we illustrate this above mentioned statistical difference of gait pattern with a graphical representation of the co-variation plots of hip, knee and ankle angles. This graph shows clearly this difference of intra-limb coordination in comparison with controls, which became even more evident after one year follow-up (see S1 Fig for a 3D rotation of the hip-knee-ankle plot).
|
study
| 100.0 |
The figure depicts the angles of hip, knee and ankle during the gait cycle on 3D plot, that is, the angle values on vertical axes of Fig 1 for hip, knee and ankle was bring back, respectively on x, y and z axes, in this figure. This figure represents the lower limb joint co-variation during the gait cycle. Solid line represents the mean values of controls, dotted line the baseline of FRDA, and dashed line the FRDA follow-up. Dark gray arrows indicate the foot landing, that is, the gait cycle start. White arrows indicate the beginning of the swing phase. The large light gray arrow represents the gait pattern progressive deterioration towards ankle and knee extension moving from the dotted to the dashed curves in patients with FRDA (see S1 Fig for a 3D animation of the graph).
|
study
| 100.0 |
Kinetic data analysis evidenced decreased knee maximum extensor moment during early stance KMmax (from 0.38 to 0.12; t(7) = 3.1, p <.05) and increased maximum flexor moment in late stance KMmin (from -0.3 to -0.5; t(7) = 3.3, p <.05). The hip power generation in pre-swing phase HP3 (from 1.5 to 1.1; t(7) = 3.3, p <.05) decreased as well.
|
study
| 100.0 |
Because of the great deal of variables in the correlation analysis and for sake of clarity, the full correlation matrix is reported in S1 Table. To sum up, we found a significant inverse correlation between velocity, percentage of the single support and SARA total score and all SARA-subscales (i.e. gait, stance, sitting, finger chase, nose to finger, heel-shin, all p values <.05). The stride time correlated directly and step and stride length correlated inversely with SARA total score and all the sub-scales (all p <.05). No correlation between GAA repeat size, disease duration and spatiotemporal parameters (walking velocity, step and stride length, stride time, step width, single support and double support %) were found. Conversely, we found a good correlation between the peaks of knee (Kc e K1) and GAA longer size and with disease duration (all p <.05). COM lateral displacement was negatively correlated to Habdc, Hp1, HMmax (all p <.05). SARA total score was inversely correlated with H2, Kc-2, Ac- A2 (all p <.05).
|
study
| 100.0 |
This study is a comprehensive analysis of the gait in a specific cohort of children and adolescents affected by FRDA, who were followed longitudinally for a period of 12 months. We analyzed the gait pattern in comparison with controls in terms of kinetic/kinematic characteristics and also in terms of variability of the measures. We analyzed the relationship between gait parameters and clinical and disease characteristics. Furthermore, we analyzed the spectrum of changes of all these parameters over a one-year follow-up.
|
study
| 100.0 |
It is known that several studies have focused on the description of the gait pattern of ataxic patients. The results of these previous studies were not always homogenous, ranging from deviations of spatiotemporal parameters and kinematic features to normal values in other reports. Some authors found gait alterations only in severe ataxia. Contrasting findings are maybe due to the heterogeneity of the populations examined in these studies. However, if we restrict the search to the studies focusing on gait analysis of FRDA population, we find a more consistent pattern.
|
review
| 99.75 |
In agreement with previous works, our cohort of patient affected by FRDA showed slower velocity, shorter and wider step, increased stride time, more pronounced lateral displacement (COM), increased extra-rotation of the angle of foot progression and increased double support duration than healthy subjects.
|
study
| 99.94 |
The reduced walking speed and the seeking of an increased base of support is a clear and well-known compensatory strategy to prevent the loss of balance. Indeed typical stumbling and unsteady ataxic gait reflects the poor ability to maintain balance in subjects affected by FRDA, but reflects the impairments of intra-limb coordination as well, as shown by Ilg and coll. Actually, FRDA pathophysiology is a mixed sensory and cerebellar ataxia resulting from spinocerebellar degeneration, peripheral sensory and optic neuropathy, cerebellar and vestibular pathology with a specific involvement of deep cerebellar nuclei (dentate, emboliform, globose and fastigial nucleus). The resulting walking pattern is the product of a complex interaction between cerebellar dysfunction and sensory loss, compromising balance control and multi-joint coordination.
|
review
| 99.1 |
The pattern of natural walking of our cohort of children and adolescent with FRDA in terms of kinematic and kinetic profiles showed a peculiar biomechanical strategy of gait characterized by a tendency to increase the ankle and knee extension during the stance phase. It seems that patients develop a compensation strategy characterized by knee joint stiffening in order to reduce the impairment in intra-limb coordination but also to compensate the disordered perception and peripheral neuropathy affecting the selective articulatory control. In other words, patients with FRDA lose the fine tuning of the knee joint, and as a consequence the lower limb is stabilized through knee hyper-extension during the stance phase. Longitudinal analysis showed a clear tendency to reiterate the use of such solution. The reduction of the control on intra-limb coordination could also be recognized from the increase of knee flexion in the swing phase that is followed by the increase of hip flexion. It is known, in fact, that the increase of knee flexion during swing produces the increase of hip flexion as a biomechanical consequence and not as a direct muscular control on the movement. The increase in knee flexion facilitates the foot clearance thus avoiding undesired falls.
|
study
| 100.0 |
The reduction of the sensibility and of the selective muscular control produces increased exploitation of the biomechanical properties. Indeed, as shown in the correlation analysis provided in the S1 Table, the mean peaks of the knee were strongly correlated with stride time and velocity, but also with the moment and power of the ankle. This means that the strategy adopted determined a well-defined biomechanical configuration characterized by increased plantar flexion of the ankle at the initial phase of the contact, increased extension of the knee, reduction of the stride time and consequently reduction of the speed, reduction of the extensor moment of the knee and reduction of ankle power.
|
study
| 100.0 |
The kinematic aspect of intralimb co-variation, clearly identifiable in Fig 2, was sensitive to change in the follow-up and able to measure the progression of the disease in our FRDA cohort. Moreover this biomechanical configuration appears consistently correlated with the status of the disease, as evaluated with the SARA scale.
|
study
| 100.0 |
We also analyzed the variability of the gait parameters, which is a feature that has been widely recognized as particularly characteristic of ataxia. The high gait variability of the patients with FRDA reflects both the deficit of balance control and the reduced a synergy of multi-joint movements. In our clinical cohort we found significant higher variability compared to controls in terms of standard deviations of ankle maximum dorsiflexion and duration of the single support phase, and a tendency to significance (significant differences only without Bonferroni correction) of some parameters such as lateral displacement of the COM, ankle joint excursion and foot progression angle. These measures are already reported as a safety strategy in order to control the balance and to prevent accidental falls. It is worthy to note that this feature influenced the possibility to exert any anticipatory or predictive strategy in gait control. The values of standard deviation were stable at the longitudinal analysis.
|
study
| 100.0 |
Taking into account the mean values of spatiotemporal parameters (velocity 0.9 m/sec, stride length 0.71 m, stride time 1.3 sec) and also the kinetic and kinematic features of our cohort, we argue that the patients were adopting a peculiar biomechanical safety strategy to prevent loss of balance and accidental falls. Consistently, we found a significant inverse correlation between velocity, percentage of the single support and SARA total score and all the analyzed SARA subscales (i.e. gait, stance, sitting, finger chase, nose to finger, heel-shin). The stride time correlated directly and step and stride length correlated inversely with SARA total score and all the subscales. This is partially in line with what was found in the study by Milne and coll. where the spatiotemporal gait parameters were highly correlated with clinical scales (FARS and 25FWT). In contrast with the already mentioned authors, we did not find any correlation between GAA repeat size, disease duration and spatiotemporal parameters. Conversely, we found a good correlation between peaks of knee (Kc e K1) and GAA longer size and with disease duration. COM lateral displacement was negatively correlated to Habd1, Hp1, HMmax. These data are consistent with the strategy of stabilizing the pelvis and the base of support in order to restrict the COM oscillation.
|
study
| 100.0 |
The t-Student’s test with Bonferroni correction highlighted the deterioration of the knee extension during the stance phase of the gait. As shown in Fig 2, the ankle-knee-hip covariation pattern of FRDA worsened between baseline and the follow-up evaluation. This feature anticipated the loss of the locomotor function in two patients. In this pediatric cohort of FRDA patients, the knee hyperextension was the only sensitive parameter for changes in one-year. However, at the follow-up, the patients with FRDA showed a clear clinical worsening, underlined also by the average changes of several parameters and SARA scores. These changes were significant applying the t-Student’s test without correction suggesting that in this particular case the Bonferroni correction could expose to the risk of false negative rejections (type II error). In fact, the analyses without correction showed a significant worsening of the SARA score (3.3± 2.5 mean SARA score variation points). Such SARA score annual variation is quite different from that reported in a previous study by Marelli and coll., where a mean SARA score variation of 1.36 ± 2.3 points/year was described. However, this could be mainly due to different reasons: The first is that our cohort was composed of patients with early disease onset and faster worsening. The second reason is that our sample size was small, particularly at the follow-up. Further studies with larger sample size and longer follow-up will verify if this peculiar aspect of ataxic gait can be a predictive feature of locomotor status: In particular able to discriminate between independent walker and who need assistive device.
|
study
| 99.94 |
In our study, we analyzed only the self-selected speed of walking and this may represent a limitation because previous studies have demonstrated that in cerebellar ataxia a higher variability occurred only during slow walking and not during medium and fast speed. However, the aim of our study was primarily to explore a possible common biomechanical characteristicof the gait in a specific cohort of ataxic patients. The selection of preferred walking mode is, in our experience, very representative of the skills and needs of daily living.
|
study
| 100.0 |
Although our study analyzed a limited sample size with a variable time of follow up, this is to our knowledge, the first work that reports a longitudinal natural history of gait in children and adolescent affected by FRDA using objective and exhaustive parameters of gait.
|
study
| 99.94 |
The mean peaks of ankle and knee joint during stance demonstrated: 1. to be correlated with SARA scores; 2. to be sensitive to discriminate between FRDA and controls (p<0.001); 3. the knee peak was the most sensitive parameter for longitudinal changes in our cohort (p<0.0013). The peculiar co-variation between ankle and knee could be explained both by the sensorial and control deficit, which is distinctive in FRDA patients. In the longitudinal analysis, the knee hyperextension proved to be more sensitive to change respect to the other gait parameters and to SARA scale as well. Moreover, despite the main spatial and temporal parameters of gait analysis significantly correlated with SARA scores, these parameters proved not to be sensitive enough in longitudinal observation.
|
study
| 100.0 |
Finally, our findings demonstrate that the selective and segmental analysis of kinetic/kinematic features of ataxic gait provides sensitive measures to detect specific longitudinal and functional alterations, more than the SARA scale. Moreover such kinetic/kinematic analysis is useful not only in monitoring the motor function, but also in defining the compensatory walking strategy and pointing out individualized rehabilitative programs. SARA scale, in comparison with the parameters of gait analysis, represents a practical tool with a good sensitivity to changes also.
|
study
| 100.0 |
Prostate cancer is the most common malignancy and the second most common cause of cancer death among men in the United States.1 Multiple molecular alterations have been identified in prostate cancer initiation, growth, invasion and metastasis. Further investigations are needed to understand the mechanisms of dysregulation and role in tumorigenesis of many of the dysregulated genes that are implicated in cancer. These studies will enhance the understanding of the disease process and help in developing new therapies. High-throughput gene expression profiling studies and transcriptome analyses have revealed tumor-specific gene signatures and multiple oncogenic drivers in cancers.2, 3, 4, 5, 6, 7, 8, 9, 10
|
review
| 99.9 |
Loss of tumor suppressor microRNAs (miRNAs or miR) is an established mechanism in cancer progression. Our analysis suggested that SUB1 homolog (Saccharomyces cerevisiae) (SUB1) is a target of miR-101. Our previous studies showed that genomic loci encoding miR-101 were deleted in aggressive prostate cancer leading to reduced miR-101 expression, resulting in overexpression of histone methyltransferase enhancer of zeste homolog 2 (EZH2).11 Apart from regulating EZH2, it has been shown that miR-101 can target other critical genes such as COX2 (cyclooxygenase-2), POMP (proteasome maturation protein), CERS6, STMN1, MCL-1 and ROCK2, among others.11, 12, 13, 14, 15, 16
|
study
| 100.0 |
In this study, we characterized SUB1 expression specifically in aggressive prostate cancer. Yeast SUB1 is biochemically identified as a stimulator of in vitro basal transcription that binds to single-strand DNA in the regions of transcription initiation.17, 18 SUB1 is a nuclear protein and is shown to have a role in various cellular processes.19, 20, 21, 22, 23, 24 It is substituted for replication protein A during transcription elongation.25 In addition to its role as transcriptional coactivator, SUB1 has been shown to repress promoter-driven transcription as well as nonspecific transcription in vitro.26, 27 Studies have reported that SUB1 interacts with distinct domains of activators such as VP16, GAL4, AP2, HIV-TAT, P53 and SMYD3 to modulate their functions.19, 22, 28, 29, 30, 31, 32 Previous studies indicated that the overexpression of SUB1 in a population of normal dermal multipotent fibroblasts resulted in the tumorigenic transformation of the cells, indicating its role in tumorigenesis. SUB1 has been recently found to show an upregulated level in different cancers. Expression of SUB1 was correlated with the levels of VEGF-C, VEGF-D and VEGFR-3 during the development of lymphangiogenesis and lymphatic metastasis in lung adenocarcinoma.33 SUB1 is also shown to have a role in non-small-cell lung cancer34 and astrocytoma.35 A recent study demonstrated that SUB1 has a role in SMYD3-mediated transactivation of growth/invasion-stimulatory genes in cancer cells.32
|
study
| 100.0 |
Here, we show increased SUB1 expression in prostate cancer cell lines and tissues. Through gene knockdown studies, we demonstrate that SUB1 has an important role in prostate cancer cell proliferation and invasion both in vitro and in vivo. We investigated the role of miR-101 in regulating SUB1 expression. Furthermore, our studies reveal that SUB1 can regulate several oncogenes including therapeutic targets such as PLK1, BUB1B and C-MYC by directly binding to their promoters. Finally, our studies indicate that SUB1-mediated oncogenic phenotype can be reversed by blocking PLK1 activity using PLK1 inhibitor.
|
study
| 100.0 |
Several studies have revealed that miRNAs are important regulators in cellular processes, such as cell proliferation, invasion and metastasis by repressing several oncogenes.11, 12, 13, 36, 37 To investigate the potential targets of miR-101, we used freely available web-based miR target prediction resources: TargetScan,38 miRanda39 and Diana-microT.40 We identified that miR-101 could potentially target SUB1. The binding site for miR-101 at 3′-UTR (untranslated region) of SUB1 is indicated (Figure 1a). MiR-101 is known to have tumor suppressor function by targeting several oncogenes including EZH2,11 proteasome assembly factor POMP,13 COX2,12 and others, therefore we sought to determine its role in SUB1 regulation. We treated prostate cancer cell line DU145 with precursor miRNA, miR-101 and tested some of the potential targets. We observed downregulation of QK1 and DDIT4 protein levels along with SUB1 (Figure 1b). Quantitative real-time PCR (qPCR) analyses also showed that miR-101 downregulates SUB1, DDIT4 and STC1 mRNA levels (Supplementary Figure S1). Here we show that miR-101 targets other known players in prostate cancer DDIT4, STC1 and QK1. To find the effect on SUB1 protein levels, we treated prostate cancer cells with precursor miRs, miR-101, -23a, -23b, -30a, -30b, -124 and -122 individually and measured SUB1 protein levels. As shown in Figure 1c, miR-101-treated cells showed significant reduction in SUB1 protein levels, whereas the control and other miR precursors did not alter SUB1 expression. Further, we measured the effect of miR-101 on cell growth using a colony growth assay using DU145, PC3 and LnCaP cells (Figure 1d). To determine whether miR-101 directly binds SUB1 3′-UTR and regulates it, HEK-293T cells were co-transfected with miR-101 and pMir-REPORT-SUB1 3′-UTR plasmids. MiR-101 showed substantial reduction in luciferase reporter activity compared with non-targeting (Non-T) control miR (Figure 1e). This effect is reversed by mutating miR-101 target site (Supplementary Figures S2a and b). These results indicate that SUB1 is a direct target of miR-101.
|
study
| 99.94 |
The expression profiling and transcriptome sequence analysis showed upregulation of SUB1 in metastatic prostate cancer (Figure 2a). Moreover, The Cancer Genome Atlas (TCGA) data show that SUB1 is overexpressed in metastatic prostate adenocarcinoma (Figure 2b). To validate this observation, we performed qPCR using RNA from multiple prostate cancer and benign tissues and confirmed increased expression of SUB1 in metastatic prostate cancer tissues relative to benign prostate samples (Figure 2c). Immunoblot analysis using SUB1-specific antibody (Figure 2d) indicated SUB1 protein overexpression. Similarly, elevated levels of SUB1 protein was observed in metastatic prostate cancer cell lines relative to benign cell lines (Figure 2e). Additionally, we investigated SUB1 protein expression in a large number of prostate cancer samples by immunohistochemical analysis, which showed weak or no reactivity in many benign tissues but stronger staining in aggressive prostate cancer tissue and metastatic prostate tumors (Figure 2f).
|
study
| 100.0 |
To determine the functional significance of SUB1 expression in prostate cancer, we perturbed SUB1 levels in prostate cells and investigated the effect of this modulation on cell proliferation, migration and invasion. We used both transient RNA interference and stable knockdown strategies targeting SUB1 in aggressive prostate cancer cell lines DU145 and PC3 and hormone-responsive LnCaP and VCaP cells. The efficiency of SUB1 knockdowns were confirmed by immunoblot (Figure 3a) and qPCR (Supplementary Figures S3a–g) analyses. We observed significant decrease in cell proliferation upon transient knockdown of SUB1 compared with control cells transfected with non-T small interfering RNAs (siRNAs) (Figure 3a). Next, we tested cell motility after stable SUB1 knockdown in prostate cancer cells using wound healing assay. The efficiency of SUB1 stable knockdowns were confirmed by immunoblot (Supplementary Figure S4a). SUB1 knockdown showed a wider wound area 24 h post wound generation relative to control cells, the delayed time to heal indicating an inability of SUB1 knockdown cells to migrate (Supplementary Figures S4b and c). Additionally, SUB1 knockdown in DU145 and PC3 reduced the invasive potential of these cells as assessed by Boyden chamber Matrigel invasion assay (Figure 3b). Further we tested for colony formation after transient knockdown of SUB1 and colonies were quantified (Figures 3c and d). Taken together, these observations demonstrate the involvement of SUB1 in the proliferation, migration, invasion and colony formation of prostate cancer cells in vitro.
|
study
| 100.0 |
To evaluate SUB1-mediated effects in prostate cancer progression, we performed gene expression analysis using RNA from SUB1 knockdown prostate cell lines. We identified multiple genes that were modulated upon SUB1 knockdown including PLK1, C-MYC, BUB1B and CDKN1B, among others (Figure 4a). PLK1 and C-MYC are known to have a role in cell proliferation, invasion and metastasis.41, 42 We validated the activation of CDKN1B and the downregulation of PLK1, C-MYC and BUB1B, both at the mRNA and protein levels upon SUB1 knockdowns (Supplementary Figures S5a–h, Figure 4b and Supplementary Figures S6a–c) and observed induction of these genes upon SUB1 overexpression in RWPE cells (Figure 4c). TCGA data show that PLK1 and BUB1B are overexpressed in metastatic prostate adenocarcinoma (Supplementary Figures S7a and b). Additionally, we validated both PLK1 mRNA and protein levels across benign, prostrate carcinoma and metastatic prostate cancer tissues by qPCR and immunoblot analysis, respectively (Supplementary Figures S7c and d), which confirmed the direct correlation between SUB1 and PLK1. Additionally, SUB1 and PLK1 mRNA levels are correlated in prostate cancer cell lines (Supplementary Figures S7e and f). Further, we generated stable SUB1-expressing RWPE cells using lentivirus (Supplementary Figure S8). Overexpression of SUB1 resulted in increased cell proliferation (Supplementary Figure S8 and Figure 4d) and invasion (Figure 4e). Furthermore, SUB1 overexpression elevated PLK1 and C-MYC expression, and reduced CDKN1B expression (Figure 4c and Supplementary Figure S6c), showing SUB1 dysregulation triggers alterations in critical oncogenes and tumor suppressors in prostate cancer. To verify the role of PLK1 in cell proliferation and invasion, we treated stable SUB1-overexpressing RWPE cells with PLK1 siRNA SMARTpool or PLK1 inhibitor (volasertib (BI6727)) and analyzed Myc-DDK-tagged SUB1 and PLK1 (Figure 4d inset). Both PLK1 knockdown and PLK1 inhibitor decreased cell proliferation (Figure 4d) and Matrigel invasion (Figure 4e). Thus, these consolidated observations underscore a downstream role for PLK1, C-MYC and CDKN1B in SUB1-mediated prostate cancer cell proliferation and invasion.
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| 100.0 |
Earlier studies suggest the importance of SUB1 in regulating transcription in vivo. For example, SUB1 enhances transcriptional activation by the activators GCN5 and HAP4 in yeast,43 and stimulates transcription in vitro with diverse kinds of activators, including SMYD3,32 VP16,24, 44 BRCA-145 and octomer transcription factor-1,46 possibly by facilitating assembly of the preinitiation complex. First, we compared motif occurrences within 500 bp upstream regions of downregulated genes and undifferentially expressed genes (when SUB1 is knocked down) using a computer program called CLOVER.47 Next, to validate the binding of SUB1 to PLK1, BUB1B and C-MYC promoters, we conducted chromatin immunoprecipitation (ChIP) assays using commercially available anti-SUB1 or -DDK antibodies in stable RWPE cells overexpressing lacz or Myc-DDK-tagged SUB1. As expected, SUB1 is enriched at PLK1, C-MYC and BUB1B promoter regions (Figures 5a–c). These data demonstrate that PLK1, C-MYC and BUB1B promoters are transcriptionally activated by SUB1 in prostate cancer.
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| 100.0 |
To demonstrate the role of SUB1 on tumor growth in vivo, we used a chick chorioallantoic membrane (CAM) assay and measured spontaneous metastasis, including local invasion, intravasation and metastasis to distant organs. CAM assay was performed as described previously,37, 48 using prostate cancer PC3-SUB1 knockdown cells. Depletion of SUB1 resulted in significantly reduced tumor weight compared with non-target short hairpin RNA (shRNA)-transfected control cells (Figure 6a). SUB1 knockdown in PC3 cells impaired their ability to invade the CAM basement membrane and resulted in a significantly decreased number of intravasated cells in the lower CAM compared with control cells (Figure 6b). Furthermore, there was attenuation of tumor metastasis in the SUB1 knockdown group compared with the control group (Figure 6c). Next, we examined SUB1-mediated tumorigenesis in a murine PC3 xenograft model using Non-T shRNA or two independent SUB1 stable knockdown PC3 cells. Both SUB1-shRNA 1 and 2 cells showed significantly reduced tumor growth and tumor weight in mice (Figures 6d and e) relative to control animals, demonstrating that SUB1 inhibition attenuates tumor growth (CAM assay and murine xenografts) and metastasis (CAM assay) in vivo. These observations show that SUB1 has a role in prostate tumor growth in vivo.
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| 100.0 |
In this study, we show that miR-101 regulates SUB1 expression and SUB1 has a role in prostate cancer growth. We and others have earlier shown that reduced expression of miR-101 leads to overexpression of oncogenic histone methyltransferase EZH2 in multiple tumors.11, 13, 36, 49 A genomic loss of miR-101 or epigenetic silencing leads to reduction in miR-101 expression in multiple cancers.50, 51 These observations suggest that attenuation of miR-101 expression is an important event in oncogenesis. Our investigations also demonstrate the role of SUB1 in prostate cancer cell proliferation and invasion.
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| 100.0 |
SUB1 protein has important roles in various cellular processes including transcription, replication, chromatin organization, cell cycle progression, DNA damage repair and apoptosis.20, 21, 34, 52 Earlier, it was shown that SUB1 is amplified and overexpressed in non-small-cell lung cancer cell lines,53 invasive intraductal papillary mucinous neoplasm of the pancreas54 and in carcinomatoses.55 Additionally, it has been shown that exogenous overexpression of SUB1 could induce the transformation of a population of normal dermal multipotent fibroblasts to acquire malignant characteristics of anchorage-independent growth in vitro and tumorigenicity in nude mice.56 Additionally, it was reported that SUB1 is upregulated in esophageal squamous cell carcinoma and its absence increased radiosensitivity of esophageal squamous cell carcinoma cells, and suppressed non-homologous end-joining activity via downregulation of XLF.52 Targeting coactivators and transcription factors through chemical inhibitors has been challenging.57, 58, 59, 60
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| 99.8 |
Although earlier studies showed the role of SUB1 in cancer, its mechanistic insight in oncogenesis is not fully understood. The present study shows an increased expression of SUB1 in prostate cancer. Moreover, it is involved in tumorigenesis through the activation of PLK1, BUB1B and C-MYC, and repression of CDKN1B during cancer progression. These proteins are involved in several cellular processes including cell proliferation, cell cycle and tumorigenesis.41, 42, 61, 62 The oncoprotein PLK1 is known to have a role in critical cell cycle events and acts in concert with cyclin-dependent kinase 1-cyclin B1 and Aurora kinases.63 Moreover, in cancer these kinases are often dysregulated, promoting uncontrolled cell proliferation and aberrant cell division.63, 64 The PLK family members have been associated with poor prognosis, which lead to enhanced interest as promising targets for anticancer drug development.65 In our study, we demonstrated that SUB1 positively regulated PLK1 expression at the transcriptional level. Furthermore, we investigated the potential role of SUB1-induced PLK1 in prostate cancer invasion by using PLK1-specific siRNA pool or inhibitor volasertib. The PLK1 inhibitor volasertib attenuated stable RWPE-SUB1 cells ability to proliferate as well as to invade through Matrigel in vitro. Moreover, it is currently the most clinically advanced inhibitor.66 Studies in various cancer cell lines (prostate, lung, colon, melanoma, hematopoietic malignancies and urothelial tumors) demonstrated that volasertib inhibits cell division leading to cell death.67, 68, 69, 70 Additionally, we also observed that SUB1 also regulates BUB1B.
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| 100.0 |
In summary, here we show that reduced miR-101 expression results in transcriptional coactivator SUB1 overexpression (Figure 6f). SUB1 triggers increased cell proliferation, invasion, metastasis and modulates expression of several including PLK1, BUB1B, C-MYC and CDKN1B. Finally, SUB1-mediated oncogenic event can be alleviated using PLK1 siRNA or inhibitor. This study shows SUB1 overexpression in aggressive prostate cancer and reveals therapeutic options to block SUB1-mediated oncogenesis.
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| 99.94 |
Prostate cancer cell lines DU145, PC3 and LnCaP were grown in RPMI-1640 (Life Technologies, Carlsbad, CA, USA), whereas VCaP was grown in Dulbecco's modified Eagle's medium with penicillin–streptomycin (100 U/ml) and 10% fetal bovine serum (Invitrogen, Carlsbad, CA, USA) in 5% CO2 cell culture incubator. The HEK293 (ATCC), RWPE-1 (henceforth referred as RWPE; ATCC, Manassas, VA, USA) cells were grown in their respective medium as specified by the suppliers. Lentiviruses were generated by the University of Michigan Vector Core (Ann Arbor, MI, USA). Prostate cancer cells were infected with lentiviruses expressing SUB1 shRNA or Non-T shRNA controls and stable cell lines were generated by selection with 1 μg/ml puromycin (Life Technologies).
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| 100.0 |
In this study, we used tissues from clinically localized prostate cancer patients who underwent radical prostatectomy. Samples were also obtained from androgen-independent metastatic prostate cancer patients from a rapid autopsy program through the University of Michigan Prostate SPORE Tissue Core as described previously.71, 72 The detailed clinical and pathological data are maintained in a secure relational database. The Institutional Review Board at the University of Michigan Medical School approved this study. Both radical prostatectomy series and the rapid autopsy program are part of the University of Michigan Prostate SPORE Tissue Core.
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| 100.0 |
The patients clinical data for prostate adenocarcinoma were downloaded using TCGA assembler.73 However, downloaded data comprised of only tumor pathologic and node pathologic information. Thus, based on tumor pathologic and node pathologic data as per 'https://cancerstaging.org/references-tools/quickreferences/Documents/ProstateSmall.pdf', samples were categorized into primary and metastatic tumor. Afterwards, level3 TCGA RNA-seq data (including raw_read_count and scaled_estimate for each sample) for all primary tumor, metastatic tumor and matched normal samples were downloaded using TCGA assembler. Transcript per million values for each gene was obtained by multiplying scaled_estimate by 1 000 000. Boxplot was generated using R (https://cran.r-project.org/).
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| 100.0 |
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