Manufacturing milk producers in Cannon County, Tennessee : Problem A: Characteristics of Cannon County manufacturing milk producers and their farms : Problem B: Management practices of Cannon County manufacturing milk producers : Problem C: Factors influencing dairy management practice adoption by Cannon County manufacturing milk producers : three related special problems in lieu of thesis /

This survey-type study was one of three related problems concerning manufacturing milk production in Cannon County, Tennessee. The specific purpose was to determine the characteristics of Cannon County manufacturing milk producers, including those who annually produce in high, medium, and low thirds in terms of butterfat. A random sample of 60 producers out of 120 was interviewed and comparative analysis was made in simple numbers and percents

A comprehensive portrait of the venom of the giant red bull ant, Myrmecia gulosa, reveals a hyperdiverse hymenopteran toxin gene family

Ants (Hymenoptera: Formicidae) are diverse and ubiquitous, and their ability to sting is familiar to many of us. However, their venoms remain largely unstudied. We provide the first comprehensive characterization of a polypeptidic ant venom, that of the giant red bull ant, Myrmecia gulosa. We reveal a suite of novel peptides with a range of posttranslational modifications, including disulfide bond formation, dimerization, and glycosylation. One venom peptide has sequence features consistent with an epidermal growth factor fold, while the remaining peptides have features suggestive of a capacity to form amphipathic helices. We show that these peptides are derived from what appears to be a single, pharmacologically diverse, gene superfamily (aculeatoxins) that includes most venom peptides previously reported from the aculeate Hymenoptera. Two aculeatoxins purified from the venom were found to be capable of activating mammalian sensory neurons, consistent with the capacity to produce pain but via distinct mechanisms of action. Further investigation of the major venom peptide MIITX1-Mg1a revealed that it can also incapacitate arthropods, indicative of dual utility in both defense and predation. MIITX1-Mg1a accomplishes these functions by generating a leak in membrane ion conductance, which alters membrane potential and triggers neuronal depolarization. Our results provide the first insights into the evolution of the major toxin gene superfamily of the aculeate Hymenoptera and provide a new paradigm in the functional evolution of toxins from animal venoms.ARC, NHMR

Mutations in SLC25A22: hyperprolinaemia, vacuolated fibroblasts and presentation with developmental delay

Mutations in SLC25A22 are known to cause neonatal epileptic encephalopathy and migrating partial seizures in infancy. Using whole exome sequencing we identified four novel SLC25A22 mutations in six children from three families. Five patients presented clinical features similar to those in the literature including hypotonia, refractory neonatal‐onset seizures and developmental delay. However, the sixth patients presented atypically with isolated developmental delay, developing late‐onset (absence) seizures only at 7 years of age. Abnormal metabolite levels have not been documented in the nine patients described previously. One patient in our series was referred to the metabolic clinic because of persistent hyperprolinaemia and another three had raised plasma proline when tested. Analysis of the post‐prandial plasma amino acid response in one patient showed abnormally high concentrations of several amino acids. This suggested that, in the fed state, when amino acids are the preferred fuel for the liver, trans‐deamination of amino acids requires transportation of glutamate into liver mitochondria by SLC25A22 for deamination by glutamate dehydrogenase; SLC25A22 is an important mitochondrial glutamate transporter in liver as well as in brain. Electron microscopy of patient fibroblasts demonstrated widespread vacuolation containing neutral and phospho‐lipids as demonstrated by Oil Red O and Sudan Black tinctorial staining; this might be explained by impaired activity of the proline/pyrroline‐5‐carboxylate (P5C) shuttle if SLC25A22 transports pyrroline‐5‐carboxylate/glutamate‐γ‐semialdehyde as well as glutamate

Correction to: Solve-RD: systematic pan-European data sharing and collaborative analysis to solve rare diseases

In the original publication of the article, consortium author list was missing in the article

Correction to: Solving patients with rare diseases through programmatic reanalysis of genome-phenome data

In the original publication of the article, consortium author lists were missing in the articl

Burden of disease scenarios for 204 countries and territories, 2022–2050: a forecasting analysis for the Global Burden of Disease Study 2021

Background: Future trends in disease burden and drivers of health are of great interest to policy makers and the public at large. This information can be used for policy and long-term health investment, planning, and prioritisation. We have expanded and improved upon previous forecasts produced as part of the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) and provide a reference forecast (the most likely future), and alternative scenarios assessing disease burden trajectories if selected sets of risk factors were eliminated from current levels by 2050. Methods: Using forecasts of major drivers of health such as the Socio-demographic Index (SDI; a composite measure of lag-distributed income per capita, mean years of education, and total fertility under 25 years of age) and the full set of risk factor exposures captured by GBD, we provide cause-specific forecasts of mortality, years of life lost (YLLs), years lived with disability (YLDs), and disability-adjusted life-years (DALYs) by age and sex from 2022 to 2050 for 204 countries and territories, 21 GBD regions, seven super-regions, and the world. All analyses were done at the cause-specific level so that only risk factors deemed causal by the GBD comparative risk assessment influenced future trajectories of mortality for each disease. Cause-specific mortality was modelled using mixed-effects models with SDI and time as the main covariates, and the combined impact of causal risk factors as an offset in the model. At the all-cause mortality level, we captured unexplained variation by modelling residuals with an autoregressive integrated moving average model with drift attenuation. These all-cause forecasts constrained the cause-specific forecasts at successively deeper levels of the GBD cause hierarchy using cascading mortality models, thus ensuring a robust estimate of cause-specific mortality. For non-fatal measures (eg, low back pain), incidence and prevalence were forecasted from mixed-effects models with SDI as the main covariate, and YLDs were computed from the resulting prevalence forecasts and average disability weights from GBD. Alternative future scenarios were constructed by replacing appropriate reference trajectories for risk factors with hypothetical trajectories of gradual elimination of risk factor exposure from current levels to 2050. The scenarios were constructed from various sets of risk factors: environmental risks (Safer Environment scenario), risks associated with communicable, maternal, neonatal, and nutritional diseases (CMNNs; Improved Childhood Nutrition and Vaccination scenario), risks associated with major non-communicable diseases (NCDs; Improved Behavioural and Metabolic Risks scenario), and the combined effects of these three scenarios. Using the Shared Socioeconomic Pathways climate scenarios SSP2-4.5 as reference and SSP1-1.9 as an optimistic alternative in the Safer Environment scenario, we accounted for climate change impact on health by using the most recent Intergovernmental Panel on Climate Change temperature forecasts and published trajectories of ambient air pollution for the same two scenarios. Life expectancy and healthy life expectancy were computed using standard methods. The forecasting framework includes computing the age-sex-specific future population for each location and separately for each scenario. 95% uncertainty intervals (UIs) for each individual future estimate were derived from the 2·5th and 97·5th percentiles of distributions generated from propagating 500 draws through the multistage computational pipeline. Findings: In the reference scenario forecast, global and super-regional life expectancy increased from 2022 to 2050, but improvement was at a slower pace than in the three decades preceding the COVID-19 pandemic (beginning in 2020). Gains in future life expectancy were forecasted to be greatest in super-regions with comparatively low life expectancies (such as sub-Saharan Africa) compared with super-regions with higher life expectancies (such as the high-income super-region), leading to a trend towards convergence in life expectancy across locations between now and 2050. At the super-region level, forecasted healthy life expectancy patterns were similar to those of life expectancies. Forecasts for the reference scenario found that health will improve in the coming decades, with all-cause age-standardised DALY rates decreasing in every GBD super-region. The total DALY burden measured in counts, however, will increase in every super-region, largely a function of population ageing and growth. We also forecasted that both DALY counts and age-standardised DALY rates will continue to shift from CMNNs to NCDs, with the most pronounced shifts occurring in sub-Saharan Africa (60·1% [95% UI 56·8–63·1] of DALYs were from CMNNs in 2022 compared with 35·8% [31·0–45·0] in 2050) and south Asia (31·7% [29·2–34·1] to 15·5% [13·7–17·5]). This shift is reflected in the leading global causes of DALYs, with the top four causes in 2050 being ischaemic heart disease, stroke, diabetes, and chronic obstructive pulmonary disease, compared with 2022, with ischaemic heart disease, neonatal disorders, stroke, and lower respiratory infections at the top. The global proportion of DALYs due to YLDs likewise increased from 33·8% (27·4–40·3) to 41·1% (33·9–48·1) from 2022 to 2050, demonstrating an important shift in overall disease burden towards morbidity and away from premature death. The largest shift of this kind was forecasted for sub-Saharan Africa, from 20·1% (15·6–25·3) of DALYs due to YLDs in 2022 to 35·6% (26·5–43·0) in 2050. In the assessment of alternative future scenarios, the combined effects of the scenarios (Safer Environment, Improved Childhood Nutrition and Vaccination, and Improved Behavioural and Metabolic Risks scenarios) demonstrated an important decrease in the global burden of DALYs in 2050 of 15·4% (13·5–17·5) compared with the reference scenario, with decreases across super-regions ranging from 10·4% (9·7–11·3) in the high-income super-region to 23·9% (20·7–27·3) in north Africa and the Middle East. The Safer Environment scenario had its largest decrease in sub-Saharan Africa (5·2% [3·5–6·8]), the Improved Behavioural and Metabolic Risks scenario in north Africa and the Middle East (23·2% [20·2–26·5]), and the Improved Nutrition and Vaccination scenario in sub-Saharan Africa (2·0% [–0·6 to 3·6]). Interpretation: Globally, life expectancy and age-standardised disease burden were forecasted to improve between 2022 and 2050, with the majority of the burden continuing to shift from CMNNs to NCDs. That said, continued progress on reducing the CMNN disease burden will be dependent on maintaining investment in and policy emphasis on CMNN disease prevention and treatment. Mostly due to growth and ageing of populations, the number of deaths and DALYs due to all causes combined will generally increase. By constructing alternative future scenarios wherein certain risk exposures are eliminated by 2050, we have shown that opportunities exist to substantially improve health outcomes in the future through concerted efforts to prevent exposure to well established risk factors and to expand access to key health interventions

Solve-RD: systematic pan-European data sharing and collaborative analysis to solve rare diseases.

For the first time in Europe hundreds of rare disease (RD) experts team up to actively share and jointly analyse existing patient's data. Solve-RD is a Horizon 2020-supported EU flagship project bringing together >300 clinicians, scientists, and patient representatives of 51 sites from 15 countries. Solve-RD is built upon a core group of four European Reference Networks (ERNs; ERN-ITHACA, ERN-RND, ERN-Euro NMD, ERN-GENTURIS) which annually see more than 270,000 RD patients with respective pathologies. The main ambition is to solve unsolved rare diseases for which a molecular cause is not yet known. This is achieved through an innovative clinical research environment that introduces novel ways to organise expertise and data. Two major approaches are being pursued (i) massive data re-analysis of >19,000 unsolved rare disease patients and (ii) novel combined -omics approaches. The minimum requirement to be eligible for the analysis activities is an inconclusive exome that can be shared with controlled access. The first preliminary data re-analysis has already diagnosed 255 cases form 8393 exomes/genome datasets. This unprecedented degree of collaboration focused on sharing of data and expertise shall identify many new disease genes and enable diagnosis of many so far undiagnosed patients from all over Europe