37 research outputs found
The sample of choice for detecting Middle East respiratory syndrome coronavirus in asymptomatic dromedary camels using real-time reverse-transcription polymerase chain reaction
The newly identified Middle East respiratory syndrome coronavirus (MERS-CoV), which causes severe respiratory disease, particularly in people with comorbidities, requires further investigation. Studies in Qatar and elsewhere have provided evidence that dromedary camels are a reservoir for the virus, but the exact modes of transmission of MERS-CoV to humans remain unclear. In February 2014, an assessment was made of the suitability and sensitivity of different types of sample for the detection of MERS-CoV by real-time reverse-transcription polymerase chain reaction (RT-PCR) for three gene targets: UpE (upstream of the E gene), the N (nucleocapsid) gene and open reading frame (ORF) 1a. Fifty-three animals presented for slaughter were sampled. A high percentage of the sampled camels (79% [95% confidence interval 66.9-91.5%, standard error 0.0625]; 42 out of 53) were shown to be shedding MERS-CoV at the time of slaughter, yet all the animals were apparently healthy. Among the virus-positive animals, nasal swabs were most often positive (97.6%). Oral swabs were the second most frequently positive (35.7%), followed by rectal swabs (28.5%). In addition, the highest viral load, expressed as a cycle threshold (Ct) value of 11.27, was obtained from a nasal swab. These findings lead to the conclusion that nasal swabs are the candidate sample of choice for detecting MERS-CoV using RT-PCR technology in apparently healthy camels
Occupational exposure to dromedaries and risk for MERS-CoV infection, Qatar, 2013–2014
We determined the presence of neutralizing antibodies to Middle East respiratory syndrome coronavirus in persons in Qatar with and without dromedary contact. Antibodies were only detected in those with contact, suggesting dromedary exposure as a risk factor for infection. Findings also showed evidence for substantial underestimation of the infection in populations at risk in Qatar
Isolation of MERS coronavirus from dromedary camel, Qatar, 2014
We obtained the full genome of Middle East respiratory syndrome coronavirus (MERS-CoV) from a camel in Qatar. This virus is highly similar to the human England/ Qatar 1 virus isolated in 2012. The MERS-CoV from the camel efficiently replicated in human cells, providing further evidence for the zoonotic potential of MERS-CoV from camels
Very accurate parameter estimation of single- and double-diode solar cell models using a modified artificial bee colony algorithm
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Global fertility in 204 countries and territories, 1950–2021, with forecasts to 2100: a comprehensive demographic analysis for the Global Burden of Disease Study 2021
Background
Accurate assessments of current and future fertility—including overall trends and changing population age structures across countries and regions—are essential to help plan for the profound social, economic, environmental, and geopolitical challenges that these changes will bring. Estimates and projections of fertility are necessary to inform policies involving resource and health-care needs, labour supply, education, gender equality, and family planning and support. The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2021 produced up-to-date and comprehensive demographic assessments of key fertility indicators at global, regional, and national levels from 1950 to 2021 and forecast fertility metrics to 2100 based on a reference scenario and key policy-dependent alternative scenarios.
Methods
To estimate fertility indicators from 1950 to 2021, mixed-effects regression models and spatiotemporal Gaussian process regression were used to synthesise data from 8709 country-years of vital and sample registrations, 1455 surveys and censuses, and 150 other sources, and to generate age-specific fertility rates (ASFRs) for 5-year age groups from age 10 years to 54 years. ASFRs were summed across age groups to produce estimates of total fertility rate (TFR). Livebirths were calculated by multiplying ASFR and age-specific female population, then summing across ages 10–54 years. To forecast future fertility up to 2100, our Institute for Health Metrics and Evaluation (IHME) forecasting model was based on projections of completed cohort fertility at age 50 years (CCF50; the average number of children born over time to females from a specified birth cohort), which yields more stable and accurate measures of fertility than directly modelling TFR. CCF50 was modelled using an ensemble approach in which three sub-models (with two, three, and four covariates variously consisting of female educational attainment, contraceptive met need, population density in habitable areas, and under-5 mortality) were given equal weights, and analyses were conducted utilising the MR-BRT (meta-regression—Bayesian, regularised, trimmed) tool. To capture time-series trends in CCF50 not explained by these covariates, we used a first-order autoregressive model on the residual term. CCF50 as a proportion of each 5-year ASFR was predicted using a linear mixed-effects model with fixed-effects covariates (female educational attainment and contraceptive met need) and random intercepts for geographical regions. Projected TFRs were then computed for each calendar year as the sum of single-year ASFRs across age groups. The reference forecast is our estimate of the most likely fertility future given the model, past fertility, forecasts of covariates, and historical relationships between covariates and fertility. We additionally produced forecasts for multiple alternative scenarios in each location: the UN Sustainable Development Goal (SDG) for education is achieved by 2030; the contraceptive met need SDG is achieved by 2030; pro-natal policies are enacted to create supportive environments for those who give birth; and the previous three scenarios combined. Uncertainty from past data inputs and model estimation was propagated throughout analyses by taking 1000 draws for past and present fertility estimates and 500 draws for future forecasts from the estimated distribution for each metric, with 95% uncertainty intervals (UIs) given as the 2·5 and 97·5 percentiles of the draws. To evaluate the forecasting performance of our model and others, we computed skill values—a metric assessing gain in forecasting accuracy—by comparing predicted versus observed ASFRs from the past 15 years (2007–21). A positive skill metric indicates that the model being evaluated performs better than the baseline model (here, a simplified model holding 2007 values constant in the future), and a negative metric indicates that the evaluated model performs worse than baseline.
Findings
During the period from 1950 to 2021, global TFR more than halved, from 4·84 (95% UI 4·63–5·06) to 2·23 (2·09–2·38). Global annual livebirths peaked in 2016 at 142 million (95% UI 137–147), declining to 129 million (121–138) in 2021. Fertility rates declined in all countries and territories since 1950, with TFR remaining above 2·1—canonically considered replacement-level fertility—in 94 (46·1%) countries and territories in 2021. This included 44 of 46 countries in sub-Saharan Africa, which was the super-region with the largest share of livebirths in 2021 (29·2% [28·7–29·6]). 47 countries and territories in which lowest estimated fertility between 1950 and 2021 was below replacement experienced one or more subsequent years with higher fertility; only three of these locations rebounded above replacement levels. Future fertility rates were projected to continue to decline worldwide, reaching a global TFR of 1·83 (1·59–2·08) in 2050 and 1·59 (1·25–1·96) in 2100 under the reference scenario. The number of countries and territories with fertility rates remaining above replacement was forecast to be 49 (24·0%) in 2050 and only six (2·9%) in 2100, with three of these six countries included in the 2021 World Bank-defined low-income group, all located in the GBD super-region of sub-Saharan Africa. The proportion of livebirths occurring in sub-Saharan Africa was forecast to increase to more than half of the world's livebirths in 2100, to 41·3% (39·6–43·1) in 2050 and 54·3% (47·1–59·5) in 2100. The share of livebirths was projected to decline between 2021 and 2100 in most of the six other super-regions—decreasing, for example, in south Asia from 24·8% (23·7–25·8) in 2021 to 16·7% (14·3–19·1) in 2050 and 7·1% (4·4–10·1) in 2100—but was forecast to increase modestly in the north Africa and Middle East and high-income super-regions. Forecast estimates for the alternative combined scenario suggest that meeting SDG targets for education and contraceptive met need, as well as implementing pro-natal policies, would result in global TFRs of 1·65 (1·40–1·92) in 2050 and 1·62 (1·35–1·95) in 2100. The forecasting skill metric values for the IHME model were positive across all age groups, indicating that the model is better than the constant prediction.
Interpretation
Fertility is declining globally, with rates in more than half of all countries and territories in 2021 below replacement level. Trends since 2000 show considerable heterogeneity in the steepness of declines, and only a small number of countries experienced even a slight fertility rebound after their lowest observed rate, with none reaching replacement level. Additionally, the distribution of livebirths across the globe is shifting, with a greater proportion occurring in the lowest-income countries. Future fertility rates will continue to decline worldwide and will remain low even under successful implementation of pro-natal policies. These changes will have far-reaching economic and societal consequences due to ageing populations and declining workforces in higher-income countries, combined with an increasing share of livebirths among the already poorest regions of the world
CORTICAL CONNECTIVITY OF THE DEFAULT MODE NETWORK AT ALPHA AND GAMMA OSCILLATIONS WAS REDUCED DURING TONIC PAIN- DIFFERENTIAL EFFECT OF EYE STATE
This is Granger causality (connectivity measure) data at alpha and gamma oscillations for four of the default mode network (DMN) connections: (1) right angular gyrus (RAG)-posterior cingulate cortex (PCC), (2) right angular gyrus (RAG)-medial prefrontal cortex (mPFC), (3) left angular gyrus (LAG)-posterior cingulate cortex (PCC), (2) left angular gyrus (LAG)-medial prefrontal cortex (mPFC). Data were collected from 28 subjects who were randomly and balanced assigned to two groups: (EC-EO) group and (EO-EC) group, depending on the order of the eye-states during EEG recording. All subjects experienced two conditions: Placebo and capsaicin (pain). For each condition, data were collected at two time points: baseline and 1 hour post placebo or capsaicin application. For each time point, data were collected during both eyes-closed and eyes-open states.
In addition, the data shows subjective pain ratings on a numerical rating scale (NRS). Throughout the one-hour patch application, participants were asked to report their pain NRS ratings every 5 minutes. Three pain parameters were then calculated: average pain intensity across all the 5-minute NRS reports, current pain intensity as the pain NRS level reported at the end of one-hour patch application, and the peak pain intensity as the highest pain NRS score reported
CORTICAL CONNECTIVITY OF THE DEFAULT MODE NETWORK AT ALPHA AND GAMMA OSCILLATIONS WAS REDUCED DURING TONIC PAIN- DIFFERENTIAL EFFECT OF EYE STATE
This is Granger causality (connectivity measure) data at alpha and gamma oscillations for four of the default mode network (DMN) connections: (1) right angular gyrus (RAG)-posterior cingulate cortex (PCC), (2) right angular gyrus (RAG)-medial prefrontal cortex (mPFC), (3) left angular gyrus (LAG)-posterior cingulate cortex (PCC), (2) left angular gyrus (LAG)-medial prefrontal cortex (mPFC). Data were collected from 28 subjects who were randomly and balanced assigned to two groups: (EC-EO) group and (EO-EC) group, depending on the order of the eye-states during EEG recording. All subjects experienced two conditions: Placebo and capsaicin (pain). For each condition, data were collected at two time points: baseline and 1 hour post placebo or capsaicin application. For each time point, data were collected during both eyes-closed and eyes-open states.
In addition, the data shows subjective pain ratings on a numerical rating scale (NRS). Throughout the one-hour patch application, participants were asked to report their pain NRS ratings every 5 minutes. Three pain parameters were then calculated: average pain intensity across all the 5-minute NRS reports, current pain intensity as the pain NRS level reported at the end of one-hour patch application, and the peak pain intensity as the highest pain NRS score reported
THE ANGULAR GURUS CONNECTIVITY AT ALPHA AND BETA OSCILLATIONS WAS REDUCED DURING TONIC PAIN- DIFFERENTIAL EFFECT OF EYE STATE
This is Granger causality (connectivity measure) data at alpha and beta oscillations for five connections: (1) right angular gyrus (RAG)-posterior cingulate cortex (PCC), (2) right angular gyrus (RAG)-medial prefrontal cortex (mPFC), (3) left angular gyrus (LAG)-posterior cingulate cortex (PCC), (4) left angular gyrus (LAG)-medial prefrontal cortex (mPFC), and (5) right angular gyrus (RAG)- left angular gyrus (LAG). Data were collected from 28 subjects who were randomly and balanced assigned to two groups: (EC-EO) group and (EO-EC) group, depending on the order of the eye-states during EEG recording. All subjects experienced two conditions: Placebo and capsaicin (pain). For each condition, data were collected at two time points: baseline and 1 hour post placebo or capsaicin application. For each time point, data were collected during both eyes-closed and eyes-open states.
In addition, the data shows subjective pain ratings on a numerical rating scale (NRS). Throughout the one-hour patch application, participants were asked to report their pain NRS ratings every 5 minutes. Three pain parameters were then calculated: average pain intensity across all the 5-minute NRS reports, current pain intensity as the pain NRS level reported at the end of one-hour patch application, and the peak pain intensity as the highest pain NRS score reported
CORTICAL CONNECTIVITY OF THE DEFAULT MODE NETWORK AT ALPHA AND BETA OSCILLATIONS WAS REDUCED DURING TONIC PAIN- DIFFERENTIAL EFFECT OF EYE STATE
This is Granger causality (connectivity measure) data at alpha and gamma oscillations for four of the default mode network (DMN) connections: (1) right angular gyrus (RAG)-posterior cingulate cortex (PCC), (2) right angular gyrus (RAG)-medial prefrontal cortex (mPFC), (3) left angular gyrus (LAG)-posterior cingulate cortex (PCC), (2) left angular gyrus (LAG)-medial prefrontal cortex (mPFC). Data were collected from 28 subjects who were randomly and balanced assigned to two groups: (EC-EO) group and (EO-EC) group, depending on the order of the eye-states during EEG recording. All subjects experienced two conditions: Placebo and capsaicin (pain). For each condition, data were collected at two time points: baseline and 1 hour post placebo or capsaicin application. For each time point, data were collected during both eyes-closed and eyes-open states.
In addition, the data shows subjective pain ratings on a numerical rating scale (NRS). Throughout the one-hour patch application, participants were asked to report their pain NRS ratings every 5 minutes. Three pain parameters were then calculated: average pain intensity across all the 5-minute NRS reports, current pain intensity as the pain NRS level reported at the end of one-hour patch application, and the peak pain intensity as the highest pain NRS score reported