Multi-wavelength, all-solid-state, continuous wave mode locked picosecond Raman laser

We demonstrate the operation of a cascaded continuous wave (CW) mode-locked Raman oscillator. The output pulses were compressed from 28 ps at 532 nm down to 6.5 ps at 559 nm (first Stokes) and 5.5 ps at 589 nm (second Stokes). The maximum output was 2.5 W at 559 nm and 1.4 W at 589 nm with slope efficiencies up to 52%. This technique allows simple and efficient generation of short-pulse radiation to the cascaded Stokes wavelengths, extending the mode-locked operation of Raman lasers to a wider range of visible wavelengths between 500 - 650 nm based on standard inexpensive picosecond Nd:YAG oscillators

Complete Hemodynamic Profiling With Pulmonary Artery Catheters in Cardiogenic Shock Is Associated With Lower In-Hospital Mortality

OBJECTIVES: The purpose of this study was to investigate the association between obtaining hemodynamic data from early pulmonary artery catheter (PAC) placement and outcomes in cardiogenic shock (CS). BACKGROUND: Although PACs are used to guide CS management decisions, evidence supporting their optimal use in CS is lacking. METHODS: The Cardiogenic Shock Working Group (CSWG) collected retrospective data in CS patients from 8 tertiary care institutions from 2016 to 2019. Patients were divided by Society for Cardiovascular Angiography and Interventions (SCAI) stages and outcomes analyzed by the PAC-use group (no PAC data, incomplete PAC data, complete PAC data) prior to initiating mechanical circulatory support (MCS). RESULTS: Of 1,414 patients with CS analyzed, 1,025 (72.5%) were male, and 494 (34.9%) presented with myocardial infarction; 758 (53.6%) were in SCAI Stage D shock, and 263 (18.6%) were in Stage C shock. Temporary MCS devices were used in 1,190 (84%) of those in advanced CS stages. PAC data were not obtained in 216 patients (18%) prior to MCS, whereas 598 patients (42%) had complete hemodynamic data. Mortality differed significantly between PAC-use groups within the overall cohort (p \u3c 0.001), and each SCAI Stage subcohort (Stage C: p = 0.03; Stage D: p = 0.05; Stage E: p = 0.02). The complete PAC assessment group had the lowest in-hospital mortality than the other groups across all SCAI stages. Having no PAC assessment was associated with higher in-hospital mortality than complete PAC assessment in the overall cohort (adjusted odds ratio: 1.57; 95% confidence interval: 1.06 to 2.33). CONCLUSIONS: The CSWG is a large multicenter registry representing real-world patients with CS in the contemporary MCS era. Use of complete PAC-derived hemodynamic data prior to MCS initiation is associated with improved survival from CS

Impaired immunological synapse in sperm associated antigen 6 (SPAG6) deficient mice

This work is supported by grant RO1AI18697 from NIAID/NIH, American Asthma Foundation 11-0094 AAF, VCU School of Medicine Bridge grant, NIH HD076257, and VCU Massey Cancer Award. Flow cytometry is supported by the Massey Cancer Center Core P30 CA16059. Microscopy was performed at the VCU Department of Neurobiology and Anatomy Facility, supported in part with funding from NIH-NINDS center core grant 5P30N5S047463

Global age-sex-specific mortality, life expectancy, and population estimates in 204 countries and territories and 811 subnational locations, 1950–2021, and the impact of the COVID-19 pandemic: a comprehensive demographic analysis for the Global Burden of Disease Study 2021

Background: Estimates of demographic metrics are crucial to assess levels and trends of population health outcomes. The profound impact of the COVID-19 pandemic on populations worldwide has underscored the need for timely estimates to understand this unprecedented event within the context of long-term population health trends. The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2021 provides new demographic estimates for 204 countries and territories and 811 additional subnational locations from 1950 to 2021, with a particular emphasis on changes in mortality and life expectancy that occurred during the 2020–21 COVID-19 pandemic period. Methods: 22 223 data sources from vital registration, sample registration, surveys, censuses, and other sources were used to estimate mortality, with a subset of these sources used exclusively to estimate excess mortality due to the COVID-19 pandemic. 2026 data sources were used for population estimation. Additional sources were used to estimate migration; the effects of the HIV epidemic; and demographic discontinuities due to conflicts, famines, natural disasters, and pandemics, which are used as inputs for estimating mortality and population. Spatiotemporal Gaussian process regression (ST-GPR) was used to generate under-5 mortality rates, which synthesised 30 763 location-years of vital registration and sample registration data, 1365 surveys and censuses, and 80 other sources. ST-GPR was also used to estimate adult mortality (between ages 15 and 59 years) based on information from 31 642 location-years of vital registration and sample registration data, 355 surveys and censuses, and 24 other sources. Estimates of child and adult mortality rates were then used to generate life tables with a relational model life table system. For countries with large HIV epidemics, life tables were adjusted using independent estimates of HIV-specific mortality generated via an epidemiological analysis of HIV prevalence surveys, antenatal clinic serosurveillance, and other data sources. Excess mortality due to the COVID-19 pandemic in 2020 and 2021 was determined by subtracting observed all-cause mortality (adjusted for late registration and mortality anomalies) from the mortality expected in the absence of the pandemic. Expected mortality was calculated based on historical trends using an ensemble of models. In location-years where all-cause mortality data were unavailable, we estimated excess mortality rates using a regression model with covariates pertaining to the pandemic. Population size was computed using a Bayesian hierarchical cohort component model. Life expectancy was calculated using age-specific mortality rates and standard demographic methods. Uncertainty intervals (UIs) were calculated for every metric using the 25th and 975th ordered values from a 1000-draw posterior distribution. Findings: Global all-cause mortality followed two distinct patterns over the study period: age-standardised mortality rates declined between 1950 and 2019 (a 62·8% [95% UI 60·5–65·1] decline), and increased during the COVID-19 pandemic period (2020–21; 5·1% [0·9–9·6] increase). In contrast with the overall reverse in mortality trends during the pandemic period, child mortality continued to decline, with 4·66 million (3·98–5·50) global deaths in children younger than 5 years in 2021 compared with 5·21 million (4·50–6·01) in 2019. An estimated 131 million (126–137) people died globally from all causes in 2020 and 2021 combined, of which 15·9 million (14·7–17·2) were due to the COVID-19 pandemic (measured by excess mortality, which includes deaths directly due to SARS-CoV-2 infection and those indirectly due to other social, economic, or behavioural changes associated with the pandemic). Excess mortality rates exceeded 150 deaths per 100 000 population during at least one year of the pandemic in 80 countries and territories, whereas 20 nations had a negative excess mortality rate in 2020 or 2021, indicating that all-cause mortality in these countries was lower during the pandemic than expected based on historical trends. Between 1950 and 2021, global life expectancy at birth increased by 22·7 years (20·8–24·8), from 49·0 years (46·7–51·3) to 71·7 years (70·9–72·5). Global life expectancy at birth declined by 1·6 years (1·0–2·2) between 2019 and 2021, reversing historical trends. An increase in life expectancy was only observed in 32 (15·7%) of 204 countries and territories between 2019 and 2021. The global population reached 7·89 billion (7·67–8·13) people in 2021, by which time 56 of 204 countries and territories had peaked and subsequently populations have declined. The largest proportion of population growth between 2020 and 2021 was in sub-Saharan Africa (39·5% [28·4–52·7]) and south Asia (26·3% [9·0–44·7]). From 2000 to 2021, the ratio of the population aged 65 years and older to the population aged younger than 15 years increased in 188 (92·2%) of 204 nations. Interpretation: Global adult mortality rates markedly increased during the COVID-19 pandemic in 2020 and 2021, reversing past decreasing trends, while child mortality rates continued to decline, albeit more slowly than in earlier years. Although COVID-19 had a substantial impact on many demographic indicators during the first 2 years of the pandemic, overall global health progress over the 72 years evaluated has been profound, with considerable improvements in mortality and life expectancy. Additionally, we observed a deceleration of global population growth since 2017, despite steady or increasing growth in lower-income countries, combined with a continued global shift of population age structures towards older ages. These demographic changes will likely present future challenges to health systems, economies, and societies. The comprehensive demographic estimates reported here will enable researchers, policy makers, health practitioners, and other key stakeholders to better understand and address the profound changes that have occurred in the global health landscape following the first 2 years of the COVID-19 pandemic, and longer-term trends beyond the pandemic

25th annual computational neuroscience meeting: CNS-2016

The same neuron may play different functional roles in the neural circuits to which it belongs. For example, neurons in the Tritonia pedal ganglia may participate in variable phases of the swim motor rhythms [1]. While such neuronal functional variability is likely to play a major role the delivery of the functionality of neural systems, it is difficult to study it in most nervous systems. We work on the pyloric rhythm network of the crustacean stomatogastric ganglion (STG) [2]. Typically network models of the STG treat neurons of the same functional type as a single model neuron (e.g. PD neurons), assuming the same conductance parameters for these neurons and implying their synchronous firing [3, 4]. However, simultaneous recording of PD neurons shows differences between the timings of spikes of these neurons. This may indicate functional variability of these neurons. Here we modelled separately the two PD neurons of the STG in a multi-neuron model of the pyloric network. Our neuron models comply with known correlations between conductance parameters of ionic currents. Our results reproduce the experimental finding of increasing spike time distance between spikes originating from the two model PD neurons during their synchronised burst phase. The PD neuron with the larger calcium conductance generates its spikes before the other PD neuron. Larger potassium conductance values in the follower neuron imply longer delays between spikes, see Fig. 17.Neuromodulators change the conductance parameters of neurons and maintain the ratios of these parameters [5]. Our results show that such changes may shift the individual contribution of two PD neurons to the PD-phase of the pyloric rhythm altering their functionality within this rhythm. Our work paves the way towards an accessible experimental and computational framework for the analysis of the mechanisms and impact of functional variability of neurons within the neural circuits to which they belong

Global burden of 288 causes of death and life expectancy decomposition in 204 countries and territories and 811 subnational locations, 1990–2021: a systematic analysis for the Global Burden of Disease Study 2021

BACKGROUND Regular, detailed reporting on population health by underlying cause of death is fundamental for public health decision making. Cause-specific estimates of mortality and the subsequent effects on life expectancy worldwide are valuable metrics to gauge progress in reducing mortality rates. These estimates are particularly important following large-scale mortality spikes, such as the COVID-19 pandemic. When systematically analysed, mortality rates and life expectancy allow comparisons of the consequences of causes of death globally and over time, providing a nuanced understanding of the effect of these causes on global populations. METHODS The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2021 cause-of-death analysis estimated mortality and years of life lost (YLLs) from 288 causes of death by age-sex-location-year in 204 countries and territories and 811 subnational locations for each year from 1990 until 2021. The analysis used 56 604 data sources, including data from vital registration and verbal autopsy as well as surveys, censuses, surveillance systems, and cancer registries, among others. As with previous GBD rounds, cause-specific death rates for most causes were estimated using the Cause of Death Ensemble model-a modelling tool developed for GBD to assess the out-of-sample predictive validity of different statistical models and covariate permutations and combine those results to produce cause-specific mortality estimates-with alternative strategies adapted to model causes with insufficient data, substantial changes in reporting over the study period, or unusual epidemiology. YLLs were computed as the product of the number of deaths for each cause-age-sex-location-year and the standard life expectancy at each age. As part of the modelling process, uncertainty intervals (UIs) were generated using the 2·5th and 97·5th percentiles from a 1000-draw distribution for each metric. We decomposed life expectancy by cause of death, location, and year to show cause-specific effects on life expectancy from 1990 to 2021. We also used the coefficient of variation and the fraction of population affected by 90% of deaths to highlight concentrations of mortality. Findings are reported in counts and age-standardised rates. Methodological improvements for cause-of-death estimates in GBD 2021 include the expansion of under-5-years age group to include four new age groups, enhanced methods to account for stochastic variation of sparse data, and the inclusion of COVID-19 and other pandemic-related mortality-which includes excess mortality associated with the pandemic, excluding COVID-19, lower respiratory infections, measles, malaria, and pertussis. For this analysis, 199 new country-years of vital registration cause-of-death data, 5 country-years of surveillance data, 21 country-years of verbal autopsy data, and 94 country-years of other data types were added to those used in previous GBD rounds. FINDINGS The leading causes of age-standardised deaths globally were the same in 2019 as they were in 1990; in descending order, these were, ischaemic heart disease, stroke, chronic obstructive pulmonary disease, and lower respiratory infections. In 2021, however, COVID-19 replaced stroke as the second-leading age-standardised cause of death, with 94·0 deaths (95% UI 89·2-100·0) per 100 000 population. The COVID-19 pandemic shifted the rankings of the leading five causes, lowering stroke to the third-leading and chronic obstructive pulmonary disease to the fourth-leading position. In 2021, the highest age-standardised death rates from COVID-19 occurred in sub-Saharan Africa (271·0 deaths [250·1-290·7] per 100 000 population) and Latin America and the Caribbean (195·4 deaths [182·1-211·4] per 100 000 population). The lowest age-standardised death rates from COVID-19 were in the high-income super-region (48·1 deaths [47·4-48·8] per 100 000 population) and southeast Asia, east Asia, and Oceania (23·2 deaths [16·3-37·2] per 100 000 population). Globally, life expectancy steadily improved between 1990 and 2019 for 18 of the 22 investigated causes. Decomposition of global and regional life expectancy showed the positive effect that reductions in deaths from enteric infections, lower respiratory infections, stroke, and neonatal deaths, among others have contributed to improved survival over the study period. However, a net reduction of 1·6 years occurred in global life expectancy between 2019 and 2021, primarily due to increased death rates from COVID-19 and other pandemic-related mortality. Life expectancy was highly variable between super-regions over the study period, with southeast Asia, east Asia, and Oceania gaining 8·3 years (6·7-9·9) overall, while having the smallest reduction in life expectancy due to COVID-19 (0·4 years). The largest reduction in life expectancy due to COVID-19 occurred in Latin America and the Caribbean (3·6 years). Additionally, 53 of the 288 causes of death were highly concentrated in locations with less than 50% of the global population as of 2021, and these causes of death became progressively more concentrated since 1990, when only 44 causes showed this pattern. The concentration phenomenon is discussed heuristically with respect to enteric and lower respiratory infections, malaria, HIV/AIDS, neonatal disorders, tuberculosis, and measles. INTERPRETATION Long-standing gains in life expectancy and reductions in many of the leading causes of death have been disrupted by the COVID-19 pandemic, the adverse effects of which were spread unevenly among populations. Despite the pandemic, there has been continued progress in combatting several notable causes of death, leading to improved global life expectancy over the study period. Each of the seven GBD super-regions showed an overall improvement from 1990 and 2021, obscuring the negative effect in the years of the pandemic. Additionally, our findings regarding regional variation in causes of death driving increases in life expectancy hold clear policy utility. Analyses of shifting mortality trends reveal that several causes, once widespread globally, are now increasingly concentrated geographically. These changes in mortality concentration, alongside further investigation of changing risks, interventions, and relevant policy, present an important opportunity to deepen our understanding of mortality-reduction strategies. Examining patterns in mortality concentration might reveal areas where successful public health interventions have been implemented. Translating these successes to locations where certain causes of death remain entrenched can inform policies that work to improve life expectancy for people everywhere. FUNDING Bill & Melinda Gates Foundation

Is there a single ideal parameter for halogen-bonding-based Lewis acidity?

Halogen-bond donors (halogen-based Lewis acids) have now found various applications in diverse fields of chemistry. The goal of this study was to identify a parameter obtainable from a single DFT calculation that reliably describes halogen-bonding strength (Lewis acidity). First, several DFT methods were benchmarked against the CCSD(T) CBS binding data of complexes of 17 carbon-based halogen-bond donors with chloride and ammonia as representative Lewis bases, which revealed M05-2X with a partially augmented def2-TZVP(D) basis set as the best model chemistry. The best single parameter to predict halogen-bonding strengths was the static σ-hole depth, but it still provided inaccurate predictions for a series of compounds. Thus, a more reliable parameter, $\Omega\sigma$*, has been developed through the linear combination of the $\sigma$-hole depth and the $\sigma$*(C−I) energy, which was further validated against neutral, cationic, halogen- and nitrogen-based halogen-bond donors with very good performance

Characterizing the interplay of Pauli repulsion, electrostatics, dispersion and charge transfer in halogen bonding with energy decomposition analysis.

The halogen bond is a class of non-covalent interaction that has attracted considerable attention recently. A widespread theory for describing them is the σ-hole concept, which predicts that the strength of the interaction is proportional to the size of the σ-hole, a region of positive electrostatic potential opposite a σ bond. Previous work shows that in the case of CX3I, with X equal to F, Cl, Br, and I, the σ-hole trend is exactly opposite to the trend in binding energy with common electron pair donors. Using energy decomposition analysis (EDA) applied to a potential energy scan as well as the recent adiabatic EDA technique, we show that the observed trend is a result of charge transfer. Therefore a picture of the halogen bond that excludes charge transfer cannot be complete, and permanent and induced electrostatics do not always provide the dominant stabilizing contributions to halogen bonds. Overall, three universally attractive factors, polarization, dispersion and charge transfer, together with permanent electrostatics, which is usually attractive, drive halogen bonding, against Pauli repulsion

Characterizing the interplay of Pauli repulsion, electrostatics, dispersion and charge transfer in halogen bonding with energy decomposition analysis.

The halogen bond is a class of non-covalent interaction that has attracted considerable attention recently. A widespread theory for describing them is the σ-hole concept, which predicts that the strength of the interaction is proportional to the size of the σ-hole, a region of positive electrostatic potential opposite a σ bond. Previous work shows that in the case of CX3I, with X equal to F, Cl, Br, and I, the σ-hole trend is exactly opposite to the trend in binding energy with common electron pair donors. Using energy decomposition analysis (EDA) applied to a potential energy scan as well as the recent adiabatic EDA technique, we show that the observed trend is a result of charge transfer. Therefore a picture of the halogen bond that excludes charge transfer cannot be complete, and permanent and induced electrostatics do not always provide the dominant stabilizing contributions to halogen bonds. Overall, three universally attractive factors, polarization, dispersion and charge transfer, together with permanent electrostatics, which is usually attractive, drive halogen bonding, against Pauli repulsion