Mealiness of Forelle pears - Quo vadis

The original publication is available at http://www.actahort.org/books/671/671_52.htm‘Forelle’ (Pyrus communis), a late season blushed pear cultivar grown in South Africa, requires a minimum of 12-weeks cold storage (-0.5 °C) to ripen evenly. Mealiness, a dry texture disorder, may develop at this time. In contrast to other pear cultivars, longer cold storage periods result in less mealiness. This could be related to insufficient total ACC build up and ethylene production, during the first 12 weeks of cold storage, for juicy texture development, during ripening. ‘Forelle’ pears were stored for 3 weeks at -0.5°C, treated with ethylene (100 μL L-1, 24h, 20°C), stored at 20°C for 2 days and thereafter 3 weeks at -0.5°C. Ethylene treatment led to an increase in mealiness after this period. However there were no differences in treated and control fruit following further ripening at 15°C for 7 days. Mealiness could not be linked to insufficient ethylene during shorter storage periods. Harvest maturity, a factor known to influence mealiness, was tested by harvesting fruit 2 weeks prior to commercial harvest, during commercial harvest, and 2 and 4 weeks after commercial harvest. Mealiness occurred at all harvest dates after 6 weeks at -0.5°C and 7 days at 15°C. Storage temperature was also tested as another factor influencing mealiness. Fruit were stored at -0.5°C, 4°C and 7.5°C for 6 weeks and ripened for 7 days at 15°C. Fruit stored at 4°C and 7.5°C ripened with 0 and 8% mealiness, respectively, in contrast to 70% in control fruit. Results could, however, not be confirmed in 2002 and 2003 as all treatments exhibited low mealiness levels (<4%). As high temperatures prior to harvest may influence mealiness, overhead evaporative cooling was applied during 2003 from early fruit development or from 2 weeks prior to harvest. Little to no mealiness developed in all treatments making it difficult to conclude if cooling prior to harvest affects mealiness

Validation of CIP2A as a Biomarker of Subsequent Disease Progression and Treatment Failure in Chronic Myeloid Leukaemia

From MDPI via Jisc Publications RouterHistory: accepted 2021-04-01, pub-electronic 2021-04-29Publication status: PublishedFunder: Bristol-Myers Squibb; Grant(s): CA180 659Background: It would be clinically useful to prospectively identify the risk of disease progression in chronic myeloid leukaemia (CML). Overexpression of cancerous inhibitor of protein phosphatase 2A (PP2A) (CIP2A) protein is an adverse prognostic indicator in many cancers. Methods: We examined CIP2A protein levels in diagnostic samples from the SPIRIT2 trial in 172 unselected patients, of whom 90 received imatinib and 82 dasatinib as first-line treatment. Results: High CIP2A levels correlated with inferior progression-free survival (p = 0.04) and with worse freedom from progression (p = 0.03), and these effects were confined to dasatinib recipients. High CIP2A levels were associated with a six-fold higher five-year treatment failure rate than low CIP2A levels (41% vs. 7.5%; p = 0.0002), in both imatinib (45% vs. 11%; p = 0.02) and dasatinib recipients (36% vs. 4%; p = 0.007). Imatinib recipients with low CIP2A levels had a greater risk of treatment failure (p = 0.0008). CIP2A levels were independent of Sokal, Hasford, EUTOS (EUropean Treatment and Outcome Study), or EUTOS long-term survival scores (ELTS) or the presence of major route cytogenetic abnormalities. No association was seen between CIP2A levels and time to molecular response or the levels of the CIP2A-related proteins PP2A, SET, SET binding protein 1 (SETBP1), or AKT. Conclusions: These data confirm that high diagnostic CIP2A levels correlate with subsequent disease progression and treatment failure. CIP2A is a simple diagnostic biomarker that may be useful in planning treatment strategies

Estimating Grizzly and Black Bear Population Abundance and Trend in Banff National Park Using Noninvasive Genetic Sampling

We evaluated the potential of two noninvasive genetic sampling methods, hair traps and bear rub surveys, to estimate population abundance and trend of grizzly (Ursus arctos) and black bear (U. americanus) populations in Banff National Park, Alberta, Canada. Using Huggins closed population mark-recapture models, we obtained the first precise abundance estimates for grizzly bears ( = 73.5, 95% CI = 64–94 in 2006;  = 50.4, 95% CI = 49–59 in 2008) and black bears ( = 62.6, 95% CI = 51–89 in 2006;  = 81.8, 95% CI = 72–102 in 2008) in the Bow Valley. Hair traps had high detection rates for female grizzlies, and male and female black bears, but extremely low detection rates for male grizzlies. Conversely, bear rubs had high detection rates for male and female grizzlies, but low rates for black bears. We estimated realized population growth rates, lambda, for grizzly bear males ( = 0.93, 95% CI = 0.74–1.17) and females ( = 0.90, 95% CI = 0.67–1.20) using Pradel open population models with three years of bear rub data. Lambda estimates are supported by abundance estimates from combined hair trap/bear rub closed population models and are consistent with a system that is likely driven by high levels of human-caused mortality. Our results suggest that bear rub surveys would provide an efficient and powerful means to inventory and monitor grizzly bear populations in the Central Canadian Rocky Mountains

3D genomics across the tree of life reveals condensin II as a determinant of architecture type

We investigated genome folding across the eukaryotic tree of life. We find two types of three-dimensional(3D) genome architectures at the chromosome scale. Each type appears and disappears repeatedlyduring eukaryotic evolution. The type of genome architecture that an organism exhibits correlates with theabsence of condensin II subunits. Moreover, condensin II depletion converts the architecture of thehuman genome to a state resembling that seen in organisms such as fungi or mosquitoes. In this state,centromeres cluster together at nucleoli, and heterochromatin domains merge. We propose a physicalmodel in which lengthwise compaction of chromosomes by condensin II during mitosis determineschromosome-scale genome architecture, with effects that are retained during the subsequent interphase.This mechanism likely has been conserved since the last common ancestor of all eukaryotes.C.H. is supported by the Boehringer Ingelheim Fonds; C.H., Á.S.C., and B.D.R. are supported by an ERC CoG (772471, “CohesinLooping”); A.M.O.E. and B.D.R. are supported by the Dutch Research Council (NWO-Echo); and J.A.R. and R.H.M. are supported by the Dutch Cancer Society (KWF). T.v.S. and B.v.S. are supported by NIH Common Fund “4D Nucleome” Program grant U54DK107965. H.T. and E.d.W. are supported by an ERC StG (637597, “HAP-PHEN”). J.A.R., T.v.S., H.T., R.H.M., B.v.S., and E.d.W. are part of the Oncode Institute, which is partly financed by the Dutch Cancer Society. Work at the Center for Theoretical Biological Physics is sponsored by the NSF (grants PHY-2019745 and CHE-1614101) and by the Welch Foundation (grant C-1792). V.G.C. is funded by FAPESP (São Paulo State Research Foundation and Higher Education Personnel) grants 2016/13998-8 and 2017/09662-7. J.N.O. is a CPRIT Scholar in Cancer Research. E.L.A. was supported by an NSF Physics Frontiers Center Award (PHY-2019745), the Welch Foundation (Q-1866), a USDA Agriculture and Food Research Initiative grant (2017-05741), the Behavioral Plasticity Research Institute (NSF DBI-2021795), and an NIH Encyclopedia of DNA Elements Mapping Center Award (UM1HG009375). Hi-C data for the 24 species were created by the DNA Zoo Consortium (www.dnazoo.org). DNA Zoo is supported by Illumina, Inc.; IBM; and the Pawsey Supercomputing Center. P.K. is supported by the University of Western Australia. L.L.M. was supported by NIH (1R01NS114491) and NSF awards (1557923, 1548121, and 1645219) and the Human Frontiers Science Program (RGP0060/2017). The draft A. californica project was supported by NHGRI. J.L.G.-S. received funding from the ERC (grant agreement no. 740041), the Spanish Ministerio de Economía y Competitividad (grant no. BFU2016-74961-P), and the institutional grant Unidad de Excelencia María de Maeztu (MDM-2016-0687). R.D.K. is supported by NIH grant RO1DK121366. V.H. is supported by NIH grant NIH1P41HD071837. K.M. is supported by a MEXT grant (20H05936). M.C.W. is supported by the NIH grants R01AG045183, R01AT009050, R01AG062257, and DP1DK113644 and by the Welch Foundation. E.F. was supported by NHGR

Multiple Invasions into Freshwater by Pufferfishes (Teleostei: Tetraodontidae): A Mitogenomic Perspective

Pufferfishes of the Family Tetraodontidae are the most speciose group in the Order Tetraodontiformes and mainly inhabit coastal waters along continents. Although no members of other tetraodontiform families have fully discarded their marine lives, approximately 30 tetraodontid species spend their entire lives in freshwaters in disjunct tropical regions of South America, Central Africa, and Southeast Asia. To investigate the interrelationships of tetraodontid pufferfishes and thereby elucidate the evolutionary origins of their freshwater habitats, we performed phylogenetic analysis based on whole mitochondrial genome sequences from 50 tetraodontid species and closely related species (including 31 newly determined sequences). The resulting phylogenies reveal that the family is composed of four major lineages and that freshwater species from the different continents are independently nested in two of the four lineages. A monophyletic origin of the use of freshwater habitats was statistically rejected, and ancestral habitat reconstruction on the resulting tree demonstrates that tetraodontids independently entered freshwater habitats in different continents at least three times. Relaxed molecular-clock Bayesian divergence time estimation suggests that the timing of these invasions differs between continents, occurring at 0–10 million years ago (MA) in South America, 17–38 MA in Central Africa, and 48–78 MA in Southeast Asia. These timings are congruent with geological events that could facilitate adaptation to freshwater habitats in each continent