Physicochemical and biochemical interactions in yeast immobilization by adhesion to a cellulose based support

An important quality of yeast cell wall is the ability to adhere to other cell walls or solid surfaces. This feature of yeast is responsible for technologically important phenomena such as flocculation at the end of beer fermentation and cell adhesion to immobilization supports e.g. spent grains, DEAE-cellulose etc. Physicochemical properties of yeast surfaces, e.g. hydrophobicity and surface charge, have a substantial impact on cell adhesion and flocculation. The interaction energies calculated according to DLVO theory and interfacial free energies were compared with yeast adhesion experiments carried out in continuous gaslift reactor. Four different brewing yeast strains (Saccharomyces cerevisiae) were tested for their adhesion onto spent grain particles. The role of physicochemical surface properties in cell-cell and cell-carrier interactions was evaluated by comparing the computed predictions with experimental results. In view of the somewhat contradictory results, the importance of specific biological interactions is outlined. Preliminary results on the presence of FLO 11 gene in studied yeast stains are presented.info:eu-repo/semantics/publishedVersio

Multi-institutional evaluation of a Pareto navigation guided automated radiotherapy planning solution for prostate cancer

\ua9 The Author(s) 2024.Background: Current automated planning solutions are calibrated using trial and error or machine learning on historical datasets. Neither method allows for the intuitive exploration of differing trade-off options during calibration, which may aid in ensuring automated solutions align with clinical preference. Pareto navigation provides this functionality and offers a potential calibration alternative. The purpose of this study was to validate an automated radiotherapy planning solution with a novel multi-dimensional Pareto navigation calibration interface across two external institutions for prostate cancer. Methods: The implemented ‘Pareto Guided Automated Planning’ (PGAP) methodology was developed in RayStation using scripting and consisted of a Pareto navigation calibration interface built upon a ‘Protocol Based Automatic Iterative Optimisation’ planning framework. 30 previous patients were randomly selected by each institution (IA and IB), 10 for calibration and 20 for validation. Utilising the Pareto navigation interface automated protocols were calibrated to the institutions’ clinical preferences. A single automated plan (VMATAuto) was generated for each validation patient with plan quality compared against the previously treated clinical plan (VMATClinical) both quantitatively, using a range of DVH metrics, and qualitatively through blind review at the external institution. Results: PGAP led to marked improvements across the majority of rectal dose metrics, with Dmean reduced by 3.7 Gy and 1.8 Gy for IA and IB respectively (p < 0.001). For bladder, results were mixed with low and intermediate dose metrics reduced for IB but increased for IA. Differences, whilst statistically significant (p < 0.05) were small and not considered clinically relevant. The reduction in rectum dose was not at the expense of PTV coverage (D98% was generally improved with VMATAuto), but was somewhat detrimental to PTV conformality. The prioritisation of rectum over conformality was however aligned with preferences expressed during calibration and was a key driver in both institutions demonstrating a clear preference towards VMATAuto, with 31/40 considered superior to VMATClinical upon blind review. Conclusions: PGAP enabled intuitive adaptation of automated protocols to an institution’s planning aims and yielded plans more congruent with the institution’s clinical preference than the locally produced manual clinical plans

Bet Hedging in Yeast by Heterogeneous, Age-Correlated Expression of a Stress Protectant

A new experimental approach reveals a bet-hedging strategy in unstressed, clonal yeast cells, whereby they adopt a range of growth states that correlate with expression of a trehalose-synthesis regulator and predict resistance to future stress

Mortality Among Adults With Cancer Undergoing Chemotherapy or Immunotherapy and Infected With COVID-19

Importance: Large cohorts of patients with active cancers and COVID-19 infection are needed to provide evidence of the association of recent cancer treatment and cancer type with COVID-19 mortality. // Objective: To evaluate whether systemic anticancer treatments (SACTs), tumor subtypes, patient demographic characteristics (age and sex), and comorbidities are associated with COVID-19 mortality. // Design, Setting, and Participants: The UK Coronavirus Cancer Monitoring Project (UKCCMP) is a prospective cohort study conducted at 69 UK cancer hospitals among adult patients (≥18 years) with an active cancer and a clinical diagnosis of COVID-19. Patients registered from March 18 to August 1, 2020, were included in this analysis. // Exposures: SACT, tumor subtype, patient demographic characteristics (eg, age, sex, body mass index, race and ethnicity, smoking history), and comorbidities were investigated. // Main Outcomes and Measures: The primary end point was all-cause mortality within the primary hospitalization. // Results: Overall, 2515 of 2786 patients registered during the study period were included; 1464 (58%) were men; and the median (IQR) age was 72 (62-80) years. The mortality rate was 38% (966 patients). The data suggest an association between higher mortality in patients with hematological malignant neoplasms irrespective of recent SACT, particularly in those with acute leukemias or myelodysplastic syndrome (OR, 2.16; 95% CI, 1.30-3.60) and myeloma or plasmacytoma (OR, 1.53; 95% CI, 1.04-2.26). Lung cancer was also significantly associated with higher COVID-19–related mortality (OR, 1.58; 95% CI, 1.11-2.25). No association between higher mortality and receiving chemotherapy in the 4 weeks before COVID-19 diagnosis was observed after correcting for the crucial confounders of age, sex, and comorbidities. An association between lower mortality and receiving immunotherapy in the 4 weeks before COVID-19 diagnosis was observed (immunotherapy vs no cancer therapy: OR, 0.52; 95% CI, 0.31-0.86). // Conclusions and Relevance: The findings of this study of patients with active cancer suggest that recent SACT is not associated with inferior outcomes from COVID-19 infection. This has relevance for the care of patients with cancer requiring treatment, particularly in countries experiencing an increase in COVID-19 case numbers. Important differences in outcomes among patients with hematological and lung cancers were observed