Use of heparin to rescue immunosuppressive monocyte reprogramming by glioblastoma-derived extracellular vesicles.

OBJECTIVE: The profound immunosuppression found in glioblastoma (GBM) patients is a critical barrier to effective immunotherapy. Multiple mechanisms of tumor-mediated immune suppression exist, and the induction of immunosuppressive monocytes such as myeloid-derived suppressor cells (MDSCs) is increasingly appreciated as a key part of this pathology. GBM-derived extracellular vesicles (EVs) can induce the formation of MDSCs. The authors sought to identify the molecular consequences of these interactions in myeloid cells in order to identify potential targets that could pharmacologically disrupt GBM EV-monocyte interaction as a means to ameliorate tumor-mediated immune suppression. Heparin-sulfate proteoglycans (HSPGs) are a general mechanism by which EVs come into association with their target cells, and soluble heparin has been shown to interfere with EV-HSPG interactions. The authors sought to assess the efficacy of heparin treatment for mitigating the effects of GBM EVs on the formation of MDSCs. METHODS: GBM EVs were collected from patient-derived cell line cultures via staged ultracentrifugation and cocultured with monocytes collected from apheresis cones from healthy blood donors. RNA was isolated from EV-conditioned and unconditioned monocytes after 72 hours of coculture, and RNA-sequencing analysis performed. For the heparin treatment studies, soluble heparin was added at the time of EV-monocyte coculture and flow cytometry analysis was performed 72 hours later. After the initial EV-monocyte coculture period, donor-matched T-cell coculture studies were performed by adding fluorescently labeled and stimulated T cells for 5 days of coculture. RESULTS: Transcriptomic analysis of GBM EV-treated monocytes demonstrated downregulation of several important immunological and metabolic pathways, with upregulation of the pathways associated with synthesis of cholesterol and HSPG. Heparin treatment inhibited association between GBM EVs and monocytes in a dose-dependent fashion, which resulted in a concomitant reduction in MDSC formation (p < 0.01). The authors further demonstrated that reduced MDSC formation resulted in a partial rescue of immune suppression, as measured by effects on activated donor-matched T cells (p < 0.05). CONCLUSIONS: The authors demonstrated that GBM EVs induce broad but reproducible reprogramming in monocytes, with enrichment of pathways that may portend an immunosuppressive phenotype. The authors further demonstrated that GBM EV-monocyte interactions are potentially druggable targets for overcoming tumor-mediated immune suppression, with heparin inhibition of EV-monocyte interactions demonstrating proof of principle.

Current trends and outcomes of non-elective neurosurgical care in Central Europe during the second year of the COVID-19 pandemic.

Reflecting the first wave COVID-19 pandemic in Central Europe (i.e. March 16th-April 15th, 2020) the neurosurgical community witnessed a general diminution in the incidence of emergency neurosurgical cases, which was impelled by a reduced number of traumatic brain injuries (TBI), spine conditions, and chronic subdural hematomas (CSDH). This appeared to be associated with restrictions imposed on mobility within countries but also to possible delayed patient introduction and interdisciplinary medical counseling. In response to one year of COVID-19 experience, also mapping the third wave of COVID-19 in 2021 (i.e. March 16 to April 15, 2021), we aimed to reevaluate the current prevalence and outcomes for emergency non-elective neurosurgical cases in COVID-19-negative patients across Austria and the Czech Republic. The primary analysis was focused on incidence and 30-day mortality in emergency neurosurgical cases compared to four preceding years (2017-2020). A total of 5077 neurosurgical emergency cases were reviewed. The year 2021 compared to the years 2017-2019 was not significantly related to any increased odds of 30 day mortality in Austria or in the Czech Republic. Recently, there was a significant propensity toward increased incidence rates of emergency non-elective neurosurgical cases during the third COVID-19 pandemic wave in Austria, driven by their lower incidence during the first COVID-19 wave in 2020. Selected neurosurgical conditions commonly associated with traumatic etiologies including TBI, and CSDH roughly reverted to similar incidence rates from the previous non-COVID-19 years. Further resisting the major deleterious effects of the continuing COVID-19 pandemic, it is edifying to notice that the neurosurgical community´s demeanor to the recent third pandemic culmination keeps the very high standards of non-elective neurosurgical care alongside with low periprocedural morbidity. This also reflects the current state of health care quality in the Czech Republic and Austria.

Immunosuppression in Glioblastoma: Current Understanding and Therapeutic Implications.

Glioblastoma (GBM) is the most common primary brain tumor in adults an carries and carries a terrible prognosis. The current regiment of surgical resection, radiation, and chemotherapy has remained largely unchanged in recent years as new therapeutic approaches have struggled to demonstrate benefit. One of the most challenging hurdles to overcome in developing novel treatments is the profound immune suppression found in many GBM patients. This limits the utility of all manner of immunotherapeutic agents, which have revolutionized the treatment of a number of cancers in recent years, but have failed to show similar benefit in GBM therapy. Understanding the mechanisms of tumor-mediated immune suppression in GBM is critical to the development of effective novel therapies, and reversal of this effect may prove key to effective immunotherapy for GBM. In this review, we discuss the current understanding of tumor-mediated immune suppression in GBM in both the local tumor microenvironment and systemically. We also discuss the effects of current GBM therapy on the immune system. We specifically explore some of the downstream effectors of tumor-driven immune suppression, particularly myeloid-derived suppressor cells (MDSCs) and other immunosuppressive monocytes, and the manner by which GBM induces their formation, with particular attention to the role of GBM-derived extracellular vesicles (EVs). Lastly, we briefly review the current state of immunotherapy for GBM and discuss additional hurdles to overcome identification and implementation of effective therapeutic strategies.

Perforating Arteries of the Lemniscal Trigone: A Microsurgical Neuroanatomic Description.

Background: The perforating arteries in the dorsolateral zone of the midbrain play a crucial role in the functions of the brain stem. Their damage due to herniation, pathological lesions, or surgery, favored by the narrow tentorial incisura, can lead to hemorrhages or ischemia and subsequently to severe consequences for the patient. Objective: In literature, not much attention has been directed to the perforating arteries in the lemniscus; in fact, no reports on the perforators of this anatomical region are available. The present study aims to a detailed analysis of the microanatomy and the clinical implications of these perforators, in relation to the parent vessels. We focused on the small vessels that penetrate the midbrain's dorsolateral surface, known as lemniscal trigone, to understand better their microanatomy and their functional importance in the clinical practice during the microsurgical approach to this area. Methods: Eighty-seven alcohol-fixed cadaveric hemispheres (44 brains) without any pathological lesions provided the material for studying the perforating vessels and their origin around the dorsolateral midbrain using an operating microscope (OPMI 1 FC, Zeiss). Measurements of the perforators' distances, in relation to the parent vessels, were taken using a digital caliper. Results: An origin from the SCA could be found in 70.11% (61) and from the PCA in 27.58% (24) of the hemispheres. In one hemisphere, an origin from the posterior choroidal artery was found (4.54%). No perforating branches were discovered in 8.04% of specimens (7). Conclusion: The perforating arteries of the lemniscal trigone stem not only from the superior cerebellar artery (SCA), as described in the few studies available in literature, but also from the posterior cerebral artery (PCA). Therefore, special attention should be paid during surgery to spare those vessels and associated perforators. A comprehensive understanding of the lemniscal trigone's perforating arteries is vital to avoid infarction of the brainstem when treating midbrain tumors or vascular malformations.

Corrigendum: Perforating Arteries of the Lemniscal Trigone: A Microsurgical Neuroanatomic Description.

[This corrects the article DOI: 10.3389/fnana.2021.675313.].

ACValidator: A novel assembly-based approach for in silico verification of circular RNAs.

Circular RNAs (circRNAs) are evolutionarily conserved RNA species that are formed when exons "back-splice" to each other. Current computational algorithms to detect these back-splicing junctions produce divergent results, and hence there is a need for a method to distinguish true-positive circRNAs. To this end, we developed Assembly based CircRNA Validator (ACValidator) for in silico verification of circRNAs. ACValidator extracts reads from a user-defined window on either side of a circRNA junction and assembles them to generate contigs. These contigs are aligned against the circRNA sequence to find contigs spanning the back-spliced junction. When evaluated on simulated datasets, ACValidator achieved over ∼80% sensitivity on datasets with an average of 10 circRNA-supporting reads and with read lengths of at least 100 bp. In experimental datasets, ACValidator produced higher verification percentages for samples treated with ribonuclease R compared to nontreated samples. Our workflow is applicable to non-polyA-selected RNAseq datasets and can also be used as a candidate selection strategy for prioritizing experimental validations. All workflow scripts are freely accessible on our GitHub page https://github.com/tgen/ACValidator along with detailed instructions to set up and run ACValidator.

Stochastic yield catastrophes and robustness in self-assembly.

A guiding principle in self-assembly is that, for high production yield, nucleation of structures must be significantly slower than their growth. However, details of the mechanism that impedes nucleation are broadly considered irrelevant. Here, we analyze self-assembly into finite-sized target structures employing mathematical modeling. We investigate two key scenarios to delay nucleation: (i) by introducing a slow activation step for the assembling constituents and, (ii) by decreasing the dimerization rate. These scenarios have widely different characteristics. While the dimerization scenario exhibits robust behavior, the activation scenario is highly sensitive to demographic fluctuations. These demographic fluctuations ultimately disfavor growth compared to nucleation and can suppress yield completely. The occurrence of this stochastic yield catastrophe does not depend on model details but is generic as soon as number fluctuations between constituents are taken into account. On a broader perspective, our results reveal that stochasticity is an important limiting factor for self-assembly and that the specific implementation of the nucleation process plays a significant role in determining the yield.

The self-assembly of a large biological molecule from small building blocks is like finishing a puzzle of magnetic pieces by shaking the box. Even though each piece of the puzzle is attracted to its correct neighbours, the limited control makes it very hard to finish the puzzle in a short amount of time. The problem becomes even more difficult if several copies of the same puzzle are assembled in one box. If several puzzles start at the same time, the different parts might steal pieces from each other, making it impossible to successfully complete any of the puzzles. This is called a depletion trap. If the box is only shaken and there is no real control over individual pieces, these traps occur at random. Overcoming these random depletion traps is an important challenge when assembling nanostructures and other artificial molecules designed by humans without wasting many, potentially expensive, components. Previous studies have shown that when multiple copies of the same structure are assembled simultaneously, slowing the rate of initiation increases the yield of correctly-made structures. This prevents new structures from stealing pieces from existing structures before they are fully completed. Now, Gartner, Graf, Wilke et al. have used a mathematical model to show that changing the way initiation is delayed leads to different yields. This was especially true for small systems where fluctuations in the availability of the different pieces strongly enhanced the initiation of new structures. In these cases, the self-assembly process terminated undesirably with many incomplete structures. Nanostructures have various applications ranging from drug delivery to robotics. These findings suggest that in order to efficiently assemble biological molecules, the concentrations of the different building blocks need to be tightly controlled. A question for further research is to investigate strategies that reduce fluctuations in the availability of the building blocks to develop more efficient assembly protocols.

Topological Phase Transition in Coupled Rock-Paper-Scissors Cycles.

A hallmark of topological phases is the occurrence of topologically protected modes at the system's boundary. Here, we find topological phases in the antisymmetric Lotka-Volterra equation (ALVE). The ALVE is a nonlinear dynamical system and describes, for example, the evolutionary dynamics of a rock-paper-scissors cycle. On a one-dimensional chain of rock-paper-scissor cycles, topological phases become manifest as robust polarization states. At the transition point between left and right polarization, solitary waves are observed. This topological phase transition lies in symmetry class D within the "tenfold way" classification as also realized by 1D topological superconductors.

Risks and Benefits of Glioblastoma Resection in Older Adults: A Retrospective Austrian Multicenter Study.

OBJECTIVE: To assess the prognostic profile, clinical outcome, treatment-associated morbidity, and treatment burden of elderly patients with glioblastoma (GBM) undergoing microsurgical tumor resection as part of contemporary treatment algorithms. METHODS: We retrospectively identified patients with GBM ≥65 years of age who were treated by resection at 2 neuro-oncology centers. Survival was assessed by Kaplan-Meier analyses; log-rank tests identified prognostic factors. RESULTS: The study population included 160 patients (mean age, 73.1 ± 5.1 years), and the median contrast-enhancing tumor volume was 31.0 cm3. Biomarker analyses revealed O(6)-methylguanine-DNA methyltransferase-promoter methylation in 62.7% and wild-type isocitrate dehydrogenase in 97.5% of tumors. The median extent of resection (EOR) was 92.3%, surgical complications were noted in 10.0% of patients, and the median postoperative hospitalization period was 8 days. Most patients (60.0%) received adjuvant radio-/chemotherapy. The overall treatment-associated morbidity was 30.6%. The median progression-free and overall survival were 5.4 months (95% confidence interval [CI], 4.6-6.4 months) and 10.0 months (95% CI, 7.9-11.7 months). The strongest predictors for favorable outcome were patient age ≤73.0 years (P = 0.0083), preoperative Karnofsky Performance Status Scale score ≥80% (P = 0.0179), postoperative modified Rankin Scale score ≤1 (P < 0.0001), adjuvant treatment (P < 0.0001), and no treatment-associated morbidity (P = 0.0478). Increased EOR did not correlate with survival (P = 0.5046), but correlated significantly with treatment-associated morbidity (P = 0.0031). CONCLUSIONS: Clinical outcome for elderly patients with GBM remains limited. Nonetheless, the observed treatment-associated morbidity and treatment burden were moderate in the patients, and patient age and performance status remained the strongest predictors for survival. The risks and benefits of tumor resection in the age of biomarker-adjusted treatment concepts require further prospective evaluation.

Identification of Circular RNAs using RNA Sequencing.

Circular RNAs (circRNAs) are a class of non-coding RNAs involved in functions including micro-RNA (miRNA) regulation, mediation of protein-protein interactions, and regulation of parental gene transcription. In classical next generation RNA sequencing (RNA-seq), circRNAs are typically overlooked as a result of poly-A selection during construction of mRNA libraries, or are found at very low abundance, and are therefore difficult to isolate and detect. Here, a circRNA library construction protocol was optimized by comparing library preparation kits, pre-treatment options and various total RNA input amounts. Two commercially available whole transcriptome library preparation kits, with and without RNase R pre-treatment, and using variable amounts of total RNA input (1 to 4 µg), were tested. Lastly, multiple tissue types; including liver, lung, lymph node, and pancreas; as well as multiple brain regions; including the cerebellum, inferior parietal lobe, middle temporal gyrus, occipital cortex, and superior frontal gyrus; were compared to evaluate circRNA abundance across tissue types. Analysis of the generated RNA-seq data using six different circRNA detection tools (find_circ, CIRI, Mapsplice, KNIFE, DCC, and CIRCexplorer) revealed that a stranded total RNA library preparation kit with RNase R pre-treatment and 4 µg RNA input is the optimal method for identifying the highest relative number of circRNAs. Consistent with previous findings, the highest enrichment of circRNAs was observed in brain tissues compared to other tissue types.

Circular RNA expression and regulatory network prediction in posterior cingulate astrocytes in elderly subjects.

BACKGROUND: Circular RNAs (circRNAs) are a novel class of endogenous, non-coding RNAs that form covalently closed continuous loops and that are both highly conserved and abundant in the mammalian brain. A role for circRNAs in sponging microRNAs (miRNAs) has been proposed, but the circRNA-miRNA-mRNA interaction networks in human brain cells have not been defined. Therefore, we identified circRNAs in RNA sequencing data previously generated from astrocytes microdissected from the posterior cingulate (PC) of Alzheimer's disease (AD) patients (N = 10) and healthy elderly controls (N = 10) using four circRNA prediction algorithms - CIRI, CIRCexplorer, find_circ and KNIFE. RESULTS: Overall, utilizing these four tools, we identified a union of 4438 unique circRNAs across all samples, of which 70.3% were derived from exonic regions. Notably, the widely reported CDR1as circRNA was detected in all samples across both groups by find_circ. Given the putative miRNA regulatory function of circRNAs, we identified potential miRNA targets of circRNAs, and further, delineated circRNA-miRNA-mRNA networks using in silico methods. Pathway analysis of the genes regulated by these miRNAs identified significantly enriched immune response pathways, which is consistent with the known function of astrocytes as immune sensors in the brain. CONCLUSIONS: In this study, we performed circRNA detection on cell-specific transcriptomic data and identified potential circRNA-miRNA-mRNA regulatory networks in PC astrocytes. Given the known function of astrocytes in cerebral innate immunity and our identification of significantly enriched immune response pathways, the circRNAs we identified may be associated with such key functions. While we did not detect recurrent differentially expressed circRNAs in the context of healthy controls or AD, we report for the first time circRNAs and their potential regulatory impact in a cell-specific and region-specific manner in aged subjects. These predicted regulatory network and pathway analyses may help provide new insights into transcriptional regulation in the brain.

Molecular mechanism for cavitation in water under tension.

Despite its relevance in biology and engineering, the molecular mechanism driving cavitation in water remains unknown. Using computer simulations, we investigate the structure and dynamics of vapor bubbles emerging from metastable water at negative pressures. We find that in the early stages of cavitation, bubbles are irregularly shaped and become more spherical as they grow. Nevertheless, the free energy of bubble formation can be perfectly reproduced in the framework of classical nucleation theory (CNT) if the curvature dependence of the surface tension is taken into account. Comparison of the observed bubble dynamics to the predictions of the macroscopic Rayleigh-Plesset (RP) equation, augmented with thermal fluctuations, demonstrates that the growth of nanoscale bubbles is governed by viscous forces. Combining the dynamical prefactor determined from the RP equation with CNT based on the Kramers formalism yields an analytical expression for the cavitation rate that reproduces the simulation results very well over a wide range of pressures. Furthermore, our theoretical predictions are in excellent agreement with cavitation rates obtained from inclusion experiments. This suggests that homogeneous nucleation is observed in inclusions, whereas only heterogeneous nucleation on impurities or defects occurs in other experiments.

The Consequences of Hypomorphic RPE65 for Rod and Cone Photoreceptors.

RPE65 is essential for both rod- and cone-mediated vision. So far, more than 120 disease-associated mutations have been identified in the human RPE65 gene. Differential clinical manifestations suggested that some patients suffer from null mutations while others retain residual RPE65 activity and some useful vision. To understand the mechanism of retinal degeneration or dysfunction caused by such hypomorphic RPE65 alleles, we generated an Rpe65 (R91W) knock-in mouse (R91W) that expresses a mutant RPE65 protein with reduced function. Data obtained suggested that the R91W mouse is highly suitable to study the impact of RPE65 insufficiency on rod pathophysiology. To study the impact on cones, we combined the R91W with the Nrl (-/-) mouse that develops an all-cone retina. Here we summarize the consequences of hypomorphic RPE65 function (reduced 11-cis-retinal synthesis) for rod and cone pathophysiology.

Detecting vapour bubbles in simulations of metastable water.

The investigation of cavitation in metastable liquids with molecular simulations requires an appropriate definition of the volume of the vapour bubble forming within the metastable liquid phase. Commonly used approaches for bubble detection exhibit two significant flaws: first, when applied to water they often identify the voids within the hydrogen bond network as bubbles thus masking the signature of emerging bubbles and, second, they lack thermodynamic consistency. Here, we present two grid-based methods, the M-method and the V-method, to detect bubbles in metastable water specifically designed to address these shortcomings. The M-method incorporates information about neighbouring grid cells to distinguish between liquid- and vapour-like cells, which allows for a very sensitive detection of small bubbles and high spatial resolution of the detected bubbles. The V-method is calibrated such that its estimates for the bubble volume correspond to the average change in system volume and are thus thermodynamically consistent. Both methods are computationally inexpensive such that they can be used in molecular dynamics and Monte Carlo simulations of cavitation. We illustrate them by computing the free energy barrier and the size of the critical bubble for cavitation in water at negative pressure.

Proton Ordering of Cubic Ice Ic: Spectroscopy and Computer Simulations.

Several proton-disordered crystalline ice structures are known to proton order at sufficiently low temperatures, provided that the right preparation procedure is used. For cubic ice, ice Ic, however, no proton ordering has been observed so far. Here, we subject ice Ic to an experimental protocol similar to that used to proton order hexagonal ice. In situ FT-IR spectroscopy carried out during this procedure reveals that the librational band of the spectrum narrows and acquires a structure that is observed neither in proton-disordered ice Ic nor in ice XI, the proton-ordered variant of hexagonal ice. On the basis of vibrational spectra computed for ice Ic and four of its proton-ordered variants using classical molecular dynamics and ab initio simulations, we conclude that the features of our experimental spectra are due to partial proton ordering, providing the first evidence of proton ordering in cubic ice. We further find that the proton-ordered structure with the lowest energy is ferroelectric, while the structure with the second lowest energy is weakly ferroelectric. Both structures fit the experimental spectral similarly well such that no unique assignment of proton order is possible based on our results.

Neural networks for local structure detection in polymorphic systems.

The accurate identification and classification of local ordered and disordered structures is an important task in atomistic computer simulations. Here, we demonstrate that properly trained artificial neural networks can be used for this purpose. Based on a neural network approach recently developed for the calculation of energies and forces, the proposed method recognizes local atomic arrangements from a set of symmetry functions that characterize the environment around a given atom. The algorithm is simple and flexible and it does not rely on the definition of a reference frame. Using the Lennard-Jones system as well as liquid water and ice as illustrative examples, we show that the neural networks developed here detect amorphous and crystalline structures with high accuracy even in the case of complex atomic arrangements, for which conventional structure detection approaches are unreliable.

Mass spectrometry-based metabolomics of single yeast cells.

Single-cell level measurements are necessary to characterize the intrinsic biological variability in a population of cells. In this study, we demonstrate that, with the microarrays for mass spectrometry platform, we are able to observe this variability. We monitor environmentally (2-deoxy-D-glucose) and genetically (ΔPFK2) perturbed Saccharomyces cerevisiae cells at the single-cell, few-cell, and population levels. Correlation plots between metabolites from the glycolytic pathway, as well as with the observed ATP/ADP ratio as a measure of cellular energy charge, give biological insight that is not accessible from population-level metabolomic data.

Optimum protocol for fast-switching free-energy calculations.

Free-energy differences computed from fast-switching simulations or measurements according to the Jarzynski equation are independent of the particular protocol specifying how the control parameter is changed in time. In contrast, the average work carried out on the system as well the accuracy of the resulting free energy strongly depend on the protocol. Recently, Schmiedl and Seifert [Phys. Rev. Lett. 98, 108301 (2007)] found that protocols that minimize the average work for a given duration of the switching process have discrete steps at the beginning and the end. Here we determine numerically the protocols that minimize the statistical error in the free energy estimate and find that such minimum error protocols have similar discrete jumps. Our analysis shows that the reduction in computational effort achieved by the use of steplike protocols can be considerable. Such large savings of computing time, however, typically occur for parameter ranges in which an application of the Jarzynski equation is impractical due to large statistical errors arising from the exponential work average.