Methane Production from Solid Potatoes by a Procedure Simulating a Bench-Scale Sequencing Batch Reactor Anaerobic Process

In this study, an experimental setup for the evaluation of a two-stage anaerobic digestion has been developed: a laboratory-scale apparatus was assembled employing solid potatoes as energy crops. Two coupled 5-litre batch-fed stirred reactors, one for the hydrolytic-acidogenic step and one for the acetogenic-methanogenic step, kept at mesophilic temperature (308.1 K), were adopted. Evaluated in the first acidogenic reactor was the influence of fermentative yeast (Saccharomyces cerevisiae) on the degree of hydrolysation and on the acidification rate of the vegetable substrate. All runs were performed without the addition of chemicals. Samples of hydrolysed substrate were sent to the second methanogenic bioreactor, fed with an industrial anaerobic sludge and selected lyophilized anaerobic bacteria, in order to evaluate the methane yield of the produced biogas and the specific methanogenic activity (SMA). The whole procedure was repeated simulating an anaerobic sequencing batch reactor (ASBR) process

The Relationship of Stress, Cognitive Appraisal and Dating Violence

The purpose of the present study was to test a specific path model. It was hypothesized that the relationship between the impact (amount and valence) of stress and an outcome (expressing violence toward a partner) would be mediated by an individual's cognitive appraisal of stressful events. Multiple regression procedures were used to test the model. Standardized beta coefficients indicated the strength of the relationships among the variables. Significant findings indicated that the strength of specific relationships among the ten variables (impact of events, three types of primary appraisal, four types of secondary appraisal and the expression of threats and acts of physical violence toward a partner) differed depending upon subject sex and whether the impact of the events was perceived as positive or negative

Biovalorization of Brewery Waste by Applying Anaerobic Digestion

In the food industry, the brewing sector holds a strategic economic position: in the year 2013, the beer production of the EU-28 was equal to 383,553,000 hL. The brewing process includes chemical and biochemical reactions and solid-liquid separations, involving the generation of various residues and by-products, among which the major two fractions are brewer’s spent grain (BSG), and exhausted brewery yeast (BY). Although until today their main use has been for animal feed, in recent years, several studies have investigated the application of anaerobic digestion in order to revalue the brewery wastes. In this work, specific methane production (SMP) and first-order solubilisation (disintegration+ hydrolysis) rates (ksol) for BSG and BY were evaluated. Biomethanation tests were performed in 5-L fed-batch stirred reactors at several substrate/inoculum ratios. The obtained SMP ranged from 0.255 L CH4 g–1 COD for exhausted brewery yeast to 0.284 L CH4 g–1 COD for brewer’s spent grain. The estimated ksol values ranged from 0.224 d–1 for BSG to 0.659 d–1 for BY

MRI-based radiomics for prognosis of pediatric diffuse intrinsic pontine glioma: an international study.

Background: Diffuse intrinsic pontine gliomas (DIPGs) are lethal pediatric brain tumors. Presently, MRI is the mainstay of disease diagnosis and surveillance. We identify clinically significant computational features from MRI and create a prognostic machine learning model. Methods: We isolated tumor volumes of T1-post-contrast (T1) and T2-weighted (T2) MRIs from 177 treatment-naïve DIPG patients from an international cohort for model training and testing. The Quantitative Image Feature Pipeline and PyRadiomics was used for feature extraction. Ten-fold cross-validation of least absolute shrinkage and selection operator Cox regression selected optimal features to predict overall survival in the training dataset and tested in the independent testing dataset. We analyzed model performance using clinical variables (age at diagnosis and sex) only, radiomics only, and radiomics plus clinical variables. Results: All selected features were intensity and texture-based on the wavelet-filtered images (3 T1 gray-level co-occurrence matrix (GLCM) texture features, T2 GLCM texture feature, and T2 first-order mean). This multivariable Cox model demonstrated a concordance of 0.68 (95% CI: 0.61-0.74) in the training dataset, significantly outperforming the clinical-only model (C = 0.57 [95% CI: 0.49-0.64]). Adding clinical features to radiomics slightly improved performance (C = 0.70 [95% CI: 0.64-0.77]). The combined radiomics and clinical model was validated in the independent testing dataset (C = 0.59 [95% CI: 0.51-0.67], Noether's test P = .02). Conclusions: In this international study, we demonstrate the use of radiomic signatures to create a machine learning model for DIPG prognostication. Standardized, quantitative approaches that objectively measure DIPG changes, including computational MRI evaluation, could offer new approaches to assessing tumor phenotype and serve a future role for optimizing clinical trial eligibility and tumor surveillance

Radiomic signatures of posterior fossa ependymoma: Molecular subgroups and risk profiles

BACKGROUND: The risk profile for posterior fossa ependymoma (EP) depends on surgical and molecular status [Group A (PFA) versus Group B (PFB)]. While subtotal tumor resection is known to confer worse prognosis, MRI-based EP risk-profiling is unexplored. We aimed to apply machine learning strategies to link MRI-based biomarkers of high-risk EP and also to distinguish PFA from PFB. METHODS: We extracted 1800 quantitative features from presurgical T2-weighted (T2-MRI) and gadolinium-enhanced T1-weighted (T1-MRI) imaging of 157 EP patients. We implemented nested cross-validation to identify features for risk score calculations and apply a Cox model for survival analysis. We conducted additional feature selection for PFA versus PFB and examined performance across three candidate classifiers. RESULTS: For all EP patients with GTR, we identified four T2-MRI-based features and stratified patients into high- and low-risk groups, with 5-year overall survival rates of 62% and 100%, respectively (p < 0.0001). Among presumed PFA patients with GTR, four T1-MRI and five T2-MRI features predicted divergence of high- and low-risk groups, with 5-year overall survival rates of 62.7% and 96.7%, respectively (p = 0.002). T1-MRI-based features showed the best performance distinguishing PFA from PFB with an AUC of 0.86. CONCLUSIONS: We present machine learning strategies to identify MRI phenotypes that distinguish PFA from PFB, as well as high- and low-risk PFA. We also describe quantitative image predictors of aggressive EP tumors that might assist risk-profiling after surgery. Future studies could examine translating radiomics as an adjunct to EP risk assessment when considering therapy strategies or trial candidacy

Preclinical and clinical evaluation of German-sourced ONC201 for the treatment of H3K27M-mutant diffuse intrinsic pontine glioma

Background Diffuse intrinsic pontine glioma (DIPG) is a fatal childhood brainstem tumor for which radiation is the only treatment. Case studies report a clinical response to ONC201 for patients with H3K27M-mutant gliomas. Oncoceutics (ONC201) is only available in the United States and Japan; however, in Germany, DIPG patients can be prescribed and dispensed a locally produced compound-ONC201 German-sourced ONC201 (GsONC201). Pediatric oncologists face the dilemma of supporting the administration of GsONC201 as conjecture surrounds its authenticity. Therefore, we compared GsONC201 to original ONC201 manufactured by Oncoceutics Inc. Methods Authenticity of GsONC201 was determined by high-resolution mass spectrometry and nuclear magnetic resonance spectroscopy. Biological activity was shown via assessment of on-target effects, in vitro growth, proliferation, and apoptosis analysis. Patient-derived xenograft mouse models were used to assess plasma and brain tissue pharmacokinetics, pharmacodynamics, and overall survival (OS). The clinical experience of 28 H3K27M+ mutant DIPG patients who received GsONC201 (2017-2020) was analyzed. Results GsONC201 harbored the authentic structure, however, was formulated as a free base rather than the dihydrochloride salt used in clinical trials. GsONC201 in vitro and in vivo efficacy and drug bioavailability studies showed no difference compared to Oncoceutics ONC201. Patients treated with GsONC201 (n = 28) showed a median OS of 18 months (P = .0007). GsONC201 patients who underwent reirradiation showed a median OS of 22 months compared to 12 months for GsONC201 patients who did not (P = .012). Conclusions This study confirms the biological activity of GsONC201 and documents the OS of patients who received the drug; however, GsONC201 was never used as a monotherapy

Agile Co-Creation for Robots and Aging (ACCRA) Project

__Introduction__ Worldwide population is getting older. The older persons want to stay independent and wish to increase their engagement in social activities to tackle loneliness, depression, and isolation. Starting from these assumptions, we developed the ACCRA project (Agile Co-Creation for Robots and Aging) with the aim to enable the development of advanced ICT Robotics-based solutions for extending active and healthy aging in daily life by defining, developing and demonstrating an agile co-creation development process. __Methods__ ACCRA robotics solutions will be designed and developed to be tested in three different domains: mobility, daily life, socialization support in four countries (i.e., France, Netherlands, Italy, and Japan). The proposed approach identifies four different phases: (1) needs analysis, (2) agile co-creation, (3) experimentation, and (4) sustainability analysis. Currently, the first two phases were almost completed. For the needs phase, we have used the following recruitment criteria: (1) for mobility: age ≥ 60 years, the and presence of mobility issues assessed by Older Mobility Scale (EMS) with a score > 13; (2) for daily life: age ≥ 60 years, and the presence of difficulties engaging in housework assessed by Autonomie Gérontologie Groupes Iso-Ressources (AGGIR) with a GIR score ≥ 4; (3) for socialization support: age ≥ 60 years, and the absence or mild level of cognitive impairment assessed by Mini Mental State Examination (MMSE) with a score ≥ 24. __Results__ The needs analysis and first co-creation sessions focus attention on the experience of older in the four countries. Preliminary results showed how, in all the pilot sites, many expectations were raised from older, formal and informal caregivers about the application of the technology into their life. Minor concerns existed about privacy, real efficacy and modularity in a real-world environment. Overall, a good attitude was recorded towards the use of technologies to support life and promote independent living. Moreover, the older engaged in our studies showed a great interest to be actively involved in the developing phase of something built based on their needs. __Conclusions__ The availability of new solutions to increase independence and quality of life in a sustainable manner appears to be mandatory in the actual society considering the actual socio-economic situation over the industrial countries

PI3K/mTOR is a therapeutically targetable genetic dependency in diffuse intrinsic pontine glioma

Diffuse midline glioma (DMG), including tumors diagnosed in the brainstem (diffuse intrinsic pontine glioma; DIPG), are uniformly fatal brain tumors that lack effective treatment. Analysis of CRISPR/Cas9 loss-of-function gene deletion screens identified PIK3CA and MTOR as targetable molecular dependencies across patient derived models of DIPG, highlighting the therapeutic potential of the blood-brain barrier–penetrant PI3K/Akt/mTOR inhibitor, paxalisib. At the human-equivalent maximum tolerated dose, mice treated with paxalisib experienced systemic glucose feedback and increased insulin levels commensurate with patients using PI3K inhibitors. To exploit genetic dependence and overcome resistance while maintaining compliance and therapeutic benefit, we combined paxalisib with the antihyperglycemic drug metformin. Metformin restored glucose homeostasis and decreased phosphorylation of the insulin receptor in vivo, a common mechanism of PI3K-inhibitor resistance, extending survival of orthotopic models. DIPG models treated with paxalisib increased calcium-activated PKC signaling. The brain penetrant PKC inhibitor enzastaurin, in combination with paxalisib, synergistically extended the survival of multiple orthotopic patient-derived and immunocompetent syngeneic allograft models; benefits potentiated in combination with metformin and standard-of-care radiotherapy. Therapeutic adaptation was assessed using spatial transcriptomics and ATAC-Seq, identifying changes in myelination and tumor immune microenvironment crosstalk. Collectively, this study has identified what we believe to be a clinically relevant DIPG therapeutic combinational strategy