Simple Summary Gliobastoma is one of the deadliest tumors overall, yet the most common malignant brain tumor. The new World Health Organization Classification of Brain Tumors brought changes in how we look at this type of malignancy. Now we know that glioblastoma is rather a spectrum of similar tumors, but with some distinct characteristics that include molecular footprint, response to therapy and with that overall survival, among others. We hypothesised that by employing phosphorous magnetic resonance we will be able to show differences in cellular energy metabolism in these various subtypes of glioblastoma. For example, we found indices of faster cell reproduction and tumor growth in MGMT-methylated and EGFR-amplified tumors. These tumors also could have reduced energetic state or tissue oxygenation due to the increased necrosis. Tumors with EGFR-amplification could have increased apoptotic activity regardless of their MGMT status. Our study indicated various differences in energetic metabolism in tumors with different molecular characteristics, which could potentially be important in future therapeutic strategies. Abstract The World Health Organisation’s (WHO) classification of brain tumors requires consideration of both histological appearance and molecular characteristics. Possible differences in brain energy metabolism could be important in designing future therapeutic strategies. Forty-three patients with primary, isocitrate dehydrogenase 1 (IDH1) wild type glioblastomas (GBMs) were included in this study. Pre-operative standard MRI was obtained with additional phosphorous magnetic resonance spectroscopy (31-P-MRS) imaging. Following microsurgical resection of the tumors, biopsy specimens underwent neuropathological diagnostics including standard molecular diagnosis. The spectroscopy results were correlated with epidermal growth factor (EGFR) and O6-Methylguanine-DNA methyltransferase (MGMT) status. EGFR amplified tumors had significantly lower phosphocreatine (PCr) to adenosine triphosphate (ATP)-PCr/ATP and PCr to inorganic phosphate (Pi)-PCr/Pi ratios, and higher Pi/ATP and phosphomonoesters (PME) to phosphodiesters (PDE)-PME/PDE ratio than those without the amplification. Patients with MGMT-methylated tumors had significantly higher cerebral magnesium (Mg) values and PME/PDE ratio, while their PCr/ATP and PCr/Pi ratios were lower than in patients without the methylation. In survival analysis, not-EGFR-amplified, MGMT-methylated GBMs showed the longest survival. This group had lower PCr/Pi ratio when compared to MGMT-methylated, EGFR-amplified group. PCr/Pi ratio was lower also when compared to the MGMT-unmethylated, EGFR not-amplified group, while PCr/ATP ratio was lower than all other examined groups. Differences in energy metabolism in various molecular subtypes of wild-type-GBMs could be important information in future precision medicine approach.

Emerging sets of single-cell sequencing data makes it appealing to apply existing tumor phylogeny reconstruction methods to analyze associated intratumor heterogeneity. Unfortunately, tumor phylogeny inference is an NP-hard problem and existing principled methods typically fail to scale up to handle thousands of cells and mutations observed in emerging single-cell data sets. Even though there are greedy heuristics to build hierarchical clustering of cells and mutations, they suffer from well-documented issues in accuracy. Additionally even when “optimal” solutions are feasible, existing approaches only provide a single “most likely” tree to depict the evolutionary processes that may result in an observed collection of cells and mutations. To make matters worse, the vast majority of single-cell sequencing data sets are transcriptomic and as a result, suffer from considerable variation in coverage across mutational loci. In this paper, we introduce Trisicell, a computational toolkit for scalable tumor phylogeny reconstruction and validation from single-cell genomic, exomic or transcriptomic sequencing data. Trisicell has three components: (i) Trisicell-DnC, a new tumor phylogeny reconstruction method from genotype matrices derived from single-cell data, (ii) Trisicell-ConT a new algorithm for constructing the consensus for two or more tumor phylogenies - which may be built through the use of different data types on the same set of cells, or built through the use of different methods on the same data, and (iii) Trisicell-PF, a new partition function method for assessing the likelihood of any user-defined subtree/set of cells to be seeded by a given set of mutations in the phylogeny. Collectively, these tools provide means of identifying and validating robust portions of a tumor phylogeny, offering the ability to focus on the most important (sub)clones and the genomic alterations that seed the associated clonal expansion. We applied Trisicell to a panel of clonal sublines derived from single-cells of a parental mouse melanoma model on which we performed both whole exome and whole transcriptome sequencing. The tumor phylogenies of the clonal sublines built on exomic and transcriptomic mutations by Trisicell-DnC, were shown by Trisicell-ConT to be highly similar and the subtrees comprised of phenotypically similar clonal sublines were shown to be strongly associated by Trisicell-PF to their seeding mutations. In addition, we applied Trisicell to single-cell whole transcriptome sequencing data from a tumor derived from the same parental melanoma cell line, which was subjected to anti-CTLA-4 immunotherapy. The phylogenies generated from both studies featured distinct subtrees, strongly associated with phenotypes including cell differentiation status, tumor growth and therapeutic response. These results suggest that Trisicell can be used for scalable tumor phylogeny reconstruction and validation through both single-cell and clonal-subline sequencing data, which may reveal strong phenotypic associations. In particular, they suggest that the developmental status and phenotypic intratumoral heterogeneity of melanoma originates from observable subclonal variation. Citation Format: Farid Rashidi Mehrabadi, Salem Malikic, Kerrie L. Marie, Eva Perez-Guijarro, Erfan Sadeqi Azer, Howard H. Yang, Can Kizilkale, Charli Gruen, Huaitian Liu, Christina Marcelus, Aydin Buluc, Funda Ergun, Maxwell P. Lee, Glenn Merlino, Chi-Ping Day, S. Cenk Sahinalp. Trisicell: Scalable Tumor Phylogeny Reconstruction and Validation Reveals Developmental Origin and Therapeutic Impact of Intratumoral Heterogeneity [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2021; 2021 Apr 10-15 and May 17-21. Philadelphia (PA): AACR; Cancer Res 2021;81(13_Suppl):Abstract nr LB019.

Introduction: Graph theory has been applied to study the pathophysiology of multiple sclerosis (MS) since it provides global and focal measures of brain network properties that are affected by MS. Typically, the connection strength and, consequently, the network properties are computed by counting the number of streamlines (NOS) connecting couples of gray matter regions. However, recent studies have shown that this method is not quantitative. Methods: We evaluated diffusion-based microstructural measures extracted from three different models to assess the network properties in a group of 66 MS patients and 64 healthy subjects. Besides, we assessed their correlation with patients' disability and with a biological measure of neuroaxonal damage. Results: Graph metrics extracted from connectomes weighted by intra-axonal microstructural components were the most sensitive to MS pathology and the most related to clinical disability. In contrast, measures of network segregation extracted from the connectomes weighted by maps describing extracellular diffusivity were the most related to serum concentration of neurofilament light chain. Network properties assessed with NOS were neither sensitive to MS pathology nor correlated with clinical and pathological measures of disease impact in MS patients. Conclusion: Using tractometry-derived graph measures in MS patients, we identified a set of metrics based on microstructural components that are highly sensitive to the disease and that provide sensitive correlates of clinical and biological deterioration in MS patients. Impact statement Graph theory has been widely used to study the alterations in the structural connectivity of multiple sclerosis (MS) patients. Usually, brain graphs used for the extraction of network metrics are created by counting the number of streamlines connecting gray matter regions, however, this method is not quantitative. In this study, we used tractometry to average the values of diffusion-based microstructural maps along the reconstructed streamlines. Our results show that network metrics extracted from the connectomes weighted on microstructural maps provide sensitive information to MS pathology, which correlate with clinical and biological measures of disease impact.

Although epigenetic modifications have been intensely investigated over the last decade due to their role in crop adaptation to rapid climate change, it is unclear which epigenetic changes are heritable and therefore transmitted to their progeny. The identification of epigenetic marks that are transmitted to the next generations is of primary importance for their use in breeding and for the development of new cultivars with a broad-spectrum of tolerance/resistance to abiotic and biotic stresses. In this review, we discuss general aspects of plant responses to environmental stresses and provide an overview of recent findings on the role of transgenerational epigenetic modifications in crops. In addition, we take the opportunity to describe the aims of EPI-CATCH, an international COST action consortium composed by researchers from 28 countries. The aim of this COST action launched in 2020 is: (1) to define standardized pipelines and methods used in the study of epigenetic mechanisms in plants, (2) update, share, and exchange findings in epigenetic responses to environmental stresses in plants, (3) develop new concepts and frontiers in plant epigenetics and epigenomics, (4) enhance dissemination, communication, and transfer of knowledge in plant epigenetics and epigenomics.

BACKGROUND: Avelumab, a monoclonal antibody targeting PD-L1, is currently approved in the USA in combination with axitinib for the first-line treatment of patients with aRCC. This analysis evaluated the relationship between potential covariates, including avelumab exposure, and the efficacy endpoints progression-free survival (PFS; by blinded independent central review per Response Evaluation Criteria in Solid Tumors [RECIST] criteria) and objective response (OR; per RECIST) in patients with aRCC. METHODS: Exposure metrics for all patients in JAVELIN Renal 101 who received avelumab 10 mg/kg every 2 weeks (Q2W) in combination with axitinib were derived from a population pharmacokinetic model (N=434). E-R analysis for PFS was conducted using parametric time-to-event (TTE) methodology. The hazard distribution was tested using exponential, Weibull, log-normal, and log-logistic distributions. E-R analysis for OR was performed using generalized binomial logistic regression. For OR, the full model included the influence of all potential covariates, while the final model retained statistically significant covariates after stepwise backwards elimination (α=0.15). For PFS, covariates were included in the full model based on forward addition (α=0.05), and the final model was determined using backward elimination (α=0.01). Model evaluation included TTE-visual predictive checks, the likelihood ratio test, the Hosmer-Lemeshow test, and receiver operating characteristic curves. RESULTS: The best fit to the PFS data was the log-normal distribution. Avelumab exposure (cycle 1 day 15 trough concentration) was associated with probability of longer PFS in both univariate and multivariate regression models. In addition, the favorable-risk group, according to baseline Heng criteria, was associated with probability of longer PFS relative to patients with intermediate prognosis using Heng criteria. Similarly, increasing avelumab exposure was associated with a higher probability of achieving OR. However, several factors have confounded the interpretation of the causal relationship between exposure and PFS or OR, including the imbalance of Heng prognostic criteria across exposure quartiles, correlation among covariates, and that data were from a single-dose regimen. No relationship was found between incidence of ADA or baseline PD-L1 status and the efficacy endpoints PFS or OR. CONCLUSION: The E-R analyses were considered exploratory and no definite conclusions could be made on the impact of exposure on PFS or OR, as other variables confounded interpretation of the relationship. Overall, the exposure from avelumab 10 mg/kg IV Q2W in combination with axitinib was associated with a manageable and tolerable safety profile and demonstrated superior efficacy compared with sunitinib in terms of PFS in treatment-naive patients with aRCC. Citation Format: Carlo Bello, Satjit Brar, Joanna C. Masters, Akash Khandelwal, Ana M. Novakovic, Ana Ruiz-Garcia, Jennifer Hibma. Exposure-response (E-R) analysis of efficacy for avelumab in combination with axitinib in patients with advanced renal cell carcinoma (aRCC) in JAVELIN Renal 101 [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2021; 2021 Apr 10-15 and May 17-21. Philadelphia (PA): AACR; Cancer Res 2021;81(13_Suppl):Abstract nr 1364.

The purpose of this study was to determine the level of gross motor skills in ASD children during the COVID-19 Pandemic. Participants in this study were ASD children with a total of 25 children aged 8-12 years (M = 10.02;SD 1.27), who were selected by random sampling technique. This research instrument is the Test of Gross Motor Development-2 (TGMD-2). Data analysis in this study is descriptive analysis. The results of gross motor skills show that 20 ASD children are in the average standard score of 4-5 (gross motor question = 70-79) in the low assessment category (80.00%) and 5 ASD children are in the average standard score of 1-3 (gross motor question = <70) is included in the very low assessment category (20.00%). Therefore, the majority of the total gross motoric data for ASD children are in the low category, namely 20 children or 80.00%. This research is not without limitations in its implementation. This research contributes to the implementation of future research, namely the need for treatment to optimize Gross Motor skills in Children with Autism Spectrum Disorder during the COVID-19 Pandemic. The urgency for proper and measurable treatment and the limitations of this study are important things to pay attention to for further research. © 2021 by authors, all rights reserved.

Background: The objective of this study was to evaluate the efficacy of modified clinoptilolite (Minazel Plus®, MZ) as a mycotoxin adsorbent for preventing the negative the effects of ochratoxin A (OTA) on performance, pathohistological changes, and OTA residue in the eggs of laying hens. Methods: Forty eight (n = 48) laying hens (27 weeks old) were equally divided into six groups and depending on the type of addition were allocated to the following experimental treatments for 7 weeks: E-I group-1 mg/kg OTA; E-II group 0.25 mg/kg OTA; E-III group 1 mg/kg OTA + 0.2% of MZ; E-IV group 0.25 mg/kg OTA + 0.2% of MZ; MZ group supplemented with 0.2% of the adsorbent; and control (K, without feed additive). Results: Overall, the addition of 0.2% MZ to laying hen feed mitigated the harmful effects of OTA on target organs and reduced the presence of OTA residue in eggs. The groups that received 0.2% of MZ achieved better production results in terms of body weight, number of eggs, and feed consumption, compared to the other treatments. Conclusions: The current findings confirm the efficacy of MZ in preventing performance losses in laying hens exposed to OTA, as well as for improving the welfare and health of food producing animals.

Objectives: Food supplements and medicines which are not on the list of prohibited substances of the World Anti-Doping Agency are included in the group of permitted pharmacological agents for athlete’s recovery. The aim of this study was to describe qualitatively and quantitatively food supplements (FS) and over-the-counter drugs use among athletes in the last six month. Methods: This was a cross sectional study. Data on food supplements and the over-the-counter drugs, usage were collected during 2018 by self-administered, anonymous questionnaire. Results: A total of 112 athletes completed the survey. A total of 51.8% (n = 58) athletes reported the use of food supplements. The use of medical supplements was reported by 50.0% (n = 56) of athletes, 26.8% (n = 30) reported using ergogenic supplements, 1.8% (n = 2) using of sports food and 4.5% (n = 5) using other supplements. The use of over-the-counter drugs was reported by 35.7% (n = 40) of athletes. The over-the-counter analgesic drugs were used by 95% (n = 38) of over-the-counter drug users. Concomitant administration two or more over-the-counter drugs was reported by 40% (n = 16) athletes. Doctors and coaches had no advisory role in the use of food supplements or over-the-counter drugs.

This work is motivated by growing evidence that the standard Cyclic Prefix (CP) length, adopted in the Long Term Evolution (LTE) physical layer (PHY) specifications, is oversized in propagation environments ranging from indoor to typical urban. Although this ostensibly seems to be addressed by 5G New Radio (NR) numerology, its scalable CP length reduction is proportionally tracked by the OFDM symbol length, which preserves the relative CP overhead of LTE. Furthermore, some simple means to optimize fixed or introduce adaptive CP length arose from either simulations or models taking into account only the bit-oriented PHY transmission performance. On the contrary, in the novel crosslayer analytical model proposed here, the closed-form expression for the optimal CP length is derived such as to minimize the effective average codeblock length, by also considering the error recovery retransmissions through the layers above PHY—the Medium Access Control (MAC) and the Radio Link Control (RLC), in particular. It turns out that, for given protective coding, the optimal CP length is determined by the appropriate rms delay spread of the channel power delay profile part remaining outside the CP span. The optimal CP length values are found to be significantly lower than the corresponding industry-standard ones, which unveils the potential for improving the net throughput.