Molecular Weight of Two Oncornavirus Genomes: Derivation from Particle Molecular Weights and RNA Content

Sedimentation analysis and intensity fluctuation spectroscopy have been used in conjunction with the Svedberg equation to determine the particle molecular weights of Rous sarcoma virus (Prague strain) and avian myeloblastosis virus (BAI strain). The molecular weights of these two viruses are (294 +/- 20) x 10(6) and (256 +/- 18) x 10(6), respectively. Values for the molecular weight of the RNA contained in each particle have been calculated as (5.58 +/- 0.5) x 10(6) and (5.88 +/- 0.5) x 10(6). Since the proportion of the viral RNA represented by 4 to 7S low-molecular-weight material is known, the molecular weight of the 60 to 70S genomes may be calculated to lie in the range (3.8 +/- 0.3 to 4.8 +/- 0.4) x 10(6) for both particles. These estimates for the molecular weight of the 60 to 70S genome are much lower than previous estimates and fall within the range of current estimates of the size of a single 35S subunit. The implications of this finding are discussed in terms of current theories for the structure of the genome of RNA tumor viruses.     

Toward a molecular paleontology of primate genomes

KpnI restriction of anthropoid primate DNAs, from a New World monkey to man, releases a series of segments that are remarkable among all of the alphoid DNAs in the constancy of their relative amounts in the various primate genomes, in their long-range organization, and in their internal sequence structure. These segments are labeled the KpnI A, B, C and D segments. Cross-hybridization analysis by Southern filter-transfer hybridization indicates that the KpnI segments represent separate and distinct families of alphoid DNAs. These families are termed the KpnI A, B, C and D families of alphoid sequences, of which only the KpnI A and B families were studied in detail here. - Evidence is presented suggesting that the KpnI segments do not exist as long, tandemly repeated sequences in the primate genome: rather, they may occur interspersed among other, perhaps nonalphoid sequences. From the stained gel patterns and from Southern filter-transfer hybridization experiments, the KpnI families appear to be absent from the genomes of the two prosimians studied - the galago and the black lemur. The KpnI A and B families are found among all of the anthropoid primates, including the New World capuchin monkey. The KpnI C family was detected in the genomes of the Old World anthropoid primates whereas the KpnI D family was detected only among the great apes and man. - The results are in accord with the observation (Musich et al., 1980) that with the continued evolutionary development of the primate Order, there has been a parallel trend toward an increased number and variety of alphoid DNA sequences. The properties of the KpnI families suggest that these sequences, unique among the alphoid DNAs, have been conservatively maintained throughout primate phylogeny and that they are among the most ancient of all primate DNAs.     

Carbon dioxide efflux accompanies release of fertilization acid from sea urchin eggs

“Fertilization acid” is released from sea urchin eggs upon fertilization and decreases the pH of the surrounding seawater. In bicarbonate-free artificial seawater flushed with nitrogen gas, the pH shift still occurs but returns to the original value in a few minutes, suggesting that the released acid is volatile. A likely candidate for a volatile acid is carbon dioxide released from the eggs. Therefore, the total CO₂ content of seawater was measured pre- and post-fertilization and was found to be correlated stoichiometrically with released proton equivalents, leading to the conclusion that fertilization acid is largely carbon dioxide. Manometric analysis of cell extracts and ashed eggs suggest that the carbon dioxide may be stored in the unfertilized egg as an inorganic carbonate.     

Constants of the Alper and Howard-Flanders oxygen equation for damage to bacterial membrane, deduced from observations on the radiation-induced penicillin-sensitive lesion

Energy deposited in the bacterial envelope of E. coli B/r induces lesions which are lethally attacked by penicillin in concentration insufficient to affect unirradiated bacteria. The critical lesions are probably in the membrane moiety. Bacteria were irradiated in the presence of 100 per cent oxygen, oxygen-free nitrogen and mixtures of 1.01, 0.59, 0.3, 0.1 and 0.06 per cent oxygen in nitrogen. Changes in sensitivity with pO2 conformed with the Alper and Howard-Flanders equation, for bacteria treated after irradiation by penicillin as well as for the untreated ones. The values of m were respectively 4.8 and 3.3; the values of K were identical, within experimental error, i.e. 4.4 mmHg. Sensitivity to induction of the penicillin-sensitive lesion was calculated from the difference in the reciprocals of D0 values proper to untreated and treated bacteria, for every gas used. The value of m could not be directly calculated because the effect of penicillin on anoxically irradiated bacteria was not detectable. For that reason, a transformation of the oxygen equation was used which allowed estimates to be made of both m and K, provided the results conformed with the equation. Within experimental error they did so conform. The calculated values of m and K for induction of the penicillin-sensitive lesion were respectively 8 and 5.9 mmHg, but it is shown that the oxygen enhancement ratio was probably underestimated and the K value overestimated. On the assumptions that these values of m and K are specific for radiation damage to bacterial membrane, and that radiation-induced killing is attributable to lethal lesions in the membrane as well as the DNA, the results demonstrate that any interaction of oxygen with sites of energy deposition in the DNA must play a very much smaller role in radiosensitization than does interaction with sites of energy deposition in the membrane.     

Clustering of physical health multimorbidity in people with severe mental illness: An accumulated prevalence analysis of United Kingdom primary care data

BackgroundPeople with severe mental illness (SMI) have higher rates of a range of physical health conditions, yet little is known regarding the clustering of physical health conditions in this population. We aimed to investigate the prevalence and clustering of chronic physical health conditions in people with SMI, compared to people without SMI.Methods and findingsWe performed a cohort-nested accumulated prevalence study, using primary care data from the Clinical Practice Research Datalink (CPRD), which holds details of 39 million patients in the United Kingdom. We identified 68,783 adults with a primary care diagnosis of SMI (schizophrenia, bipolar disorder, or other psychoses) from 2000 to 2018, matched up to 1:4 to 274,684 patients without an SMI diagnosis, on age, sex, primary care practice, and year of registration at the practice. Patients had a median of 28.85 (IQR: 19.10 to 41.37) years of primary care observations. Patients with SMI had higher prevalence of smoking (27.65% versus 46.08%), obesity (24.91% versus 38.09%), alcohol misuse (3.66% versus 13.47%), and drug misuse (2.08% versus 12.84%) than comparators. We defined 24 physical health conditions derived from the Elixhauser and Charlson comorbidity indices and used logistic regression to investigate individual conditions and multimorbidity. We controlled for age, sex, region, and ethnicity and then additionally for health risk factors: smoking status, alcohol misuse, drug misuse, and body mass index (BMI). We defined multimorbidity clusters using multiple correspondence analysis (MCA) and K-means cluster analysis and described them based on the observed/expected ratio. Patients with SMI had higher odds of 19 of 24 conditions and a higher prevalence of multimorbidity (odds ratio (OR): 1.84; 95% confidence interval [CI]: 1.80 to 1.88, p < 0.001) compared to those without SMI, particularly in younger age groups (males aged 30 to 39: OR: 2.49; 95% CI: 2.27 to 2.73; p < 0.001; females aged 18 to 30: OR: 2.69; 95% CI: 2.36 to 3.07; p < 0.001). Adjusting for health risk factors reduced the OR of all conditions. We identified 7 multimorbidity clusters in those with SMI and 7 in those without SMI. A total of 4 clusters were common to those with and without SMI; while 1, heart disease, appeared as one cluster in those with SMI and 3 distinct clusters in comparators; and 2 small clusters were unique to the SMI cohort. Limitations to this study include missing data, which may have led to residual confounding, and an inability to investigate the temporal associations between SMI and physical health conditions.ConclusionsIn this study, we observed that physical health conditions cluster similarly in people with and without SMI, although patients with SMI had higher burden of multimorbidity, particularly in younger age groups. While interventions aimed at the general population may also be appropriate for those with SMI, there is a need for interventions aimed at better management of younger-age multimorbidity, and preventative measures focusing on diseases of younger age, and reduction of health risk factors.

In an observational analysis of primary care data from the UK, Naomi Launders and colleagues study the prevalence and clustering of physical health conditions and multimorbidity in individuals with severe mental illnesses.