The translocator protein (TSPO) is an 18kDa transmembrane protein primarily found in the outer mitochondrial membrane where it forms a key part of the mitochondrial permeability transition pore ...(MPTP). Omnipresent in almost all tissues, TSPO up-regulation has been connected to neuronal damage and inflammation, making the protein an important bio-imaging marker for disease progression. More recently, TSPO has attracted attention as a possible molecular target for tumour imaging and chemotherapy. In this review we summarize TSPO's molecular characteristics and highlight research progress in recent years in the field of TSPO-targeted cancer diagnostics and treatments.
Understanding potential trajectories in health and drivers of health is crucial to guiding long-term investments and policy implementation. Past work on forecasting has provided an incomplete ...landscape of future health scenarios, highlighting a need for a more robust modelling platform from which policy options and potential health trajectories can be assessed. This study provides a novel approach to modelling life expectancy, all-cause mortality and cause of death forecasts —and alternative future scenarios—for 250 causes of death from 2016 to 2040 in 195 countries and territories.
We modelled 250 causes and cause groups organised by the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) hierarchical cause structure, using GBD 2016 estimates from 1990–2016, to generate predictions for 2017–40. Our modelling framework used data from the GBD 2016 study to systematically account for the relationships between risk factors and health outcomes for 79 independent drivers of health. We developed a three-component model of cause-specific mortality: a component due to changes in risk factors and select interventions; the underlying mortality rate for each cause that is a function of income per capita, educational attainment, and total fertility rate under 25 years and time; and an autoregressive integrated moving average model for unexplained changes correlated with time. We assessed the performance by fitting models with data from 1990–2006 and using these to forecast for 2007–16. Our final model used for generating forecasts and alternative scenarios was fitted to data from 1990–2016. We used this model for 195 countries and territories to generate a reference scenario or forecast through 2040 for each measure by location. Additionally, we generated better health and worse health scenarios based on the 85th and 15th percentiles, respectively, of annualised rates of change across location-years for all the GBD risk factors, income per person, educational attainment, select intervention coverage, and total fertility rate under 25 years in the past. We used the model to generate all-cause age-sex specific mortality, life expectancy, and years of life lost (YLLs) for 250 causes. Scenarios for fertility were also generated and used in a cohort component model to generate population scenarios. For each reference forecast, better health, and worse health scenarios, we generated estimates of mortality and YLLs attributable to each risk factor in the future.
Globally, most independent drivers of health were forecast to improve by 2040, but 36 were forecast to worsen. As shown by the better health scenarios, greater progress might be possible, yet for some drivers such as high body-mass index (BMI), their toll will rise in the absence of intervention. We forecasted global life expectancy to increase by 4·4 years (95% UI 2·2 to 6·4) for men and 4·4 years (2·1 to 6·4) for women by 2040, but based on better and worse health scenarios, trajectories could range from a gain of 7·8 years (5·9 to 9·8) to a non-significant loss of 0·4 years (–2·8 to 2·2) for men, and an increase of 7·2 years (5·3 to 9·1) to essentially no change (0·1 years –2·7 to 2·5) for women. In 2040, Japan, Singapore, Spain, and Switzerland had a forecasted life expectancy exceeding 85 years for both sexes, and 59 countries including China were projected to surpass a life expectancy of 80 years by 2040. At the same time, Central African Republic, Lesotho, Somalia, and Zimbabwe had projected life expectancies below 65 years in 2040, indicating global disparities in survival are likely to persist if current trends hold. Forecasted YLLs showed a rising toll from several non-communicable diseases (NCDs), partly driven by population growth and ageing. Differences between the reference forecast and alternative scenarios were most striking for HIV/AIDS, for which a potential increase of 120·2% (95% UI 67·2–190·3) in YLLs (nearly 118 million) was projected globally from 2016–40 under the worse health scenario. Compared with 2016, NCDs were forecast to account for a greater proportion of YLLs in all GBD regions by 2040 (67·3% of YLLs 95% UI 61·9–72·3 globally); nonetheless, in many lower-income countries, communicable, maternal, neonatal, and nutritional (CMNN) diseases still accounted for a large share of YLLs in 2040 (eg, 53·5% of YLLs 95% UI 48·3–58·5 in Sub-Saharan Africa). There were large gaps for many health risks between the reference forecast and better health scenario for attributable YLLs. In most countries, metabolic risks amenable to health care (eg, high blood pressure and high plasma fasting glucose) and risks best targeted by population-level or intersectoral interventions (eg, tobacco, high BMI, and ambient particulate matter pollution) had some of the largest differences between reference and better health scenarios. The main exception was sub-Saharan Africa, where many risks associated with poverty and lower levels of development (eg, unsafe water and sanitation, household air pollution, and child malnutrition) were projected to still account for substantive disparities between reference and better health scenarios in 2040.
With the present study, we provide a robust, flexible forecasting platform from which reference forecasts and alternative health scenarios can be explored in relation to a wide range of independent drivers of health. Our reference forecast points to overall improvements through 2040 in most countries, yet the range found across better and worse health scenarios renders a precarious vision of the future—a world with accelerating progress from technical innovation but with the potential for worsening health outcomes in the absence of deliberate policy action. For some causes of YLLs, large differences between the reference forecast and alternative scenarios reflect the opportunity to accelerate gains if countries move their trajectories toward better health scenarios—or alarming challenges if countries fall behind their reference forecasts. Generally, decision makers should plan for the likely continued shift toward NCDs and target resources toward the modifiable risks that drive substantial premature mortality. If such modifiable risks are prioritised today, there is opportunity to reduce avoidable mortality in the future. However, CMNN causes and related risks will remain the predominant health priority among lower-income countries. Based on our 2040 worse health scenario, there is a real risk of HIV mortality rebounding if countries lose momentum against the HIV epidemic, jeopardising decades of progress against the disease. Continued technical innovation and increased health spending, including development assistance for health targeted to the world's poorest people, are likely to remain vital components to charting a future where all populations can live full, healthy lives.
Bill & Melinda Gates Foundation.
•The mechanisms by which TDO/IDO1/IDO2 exert their immunosuppressive effects in cancer.•Active site topological features important to drug design for each enzyme.•Outlines specific inhibitors for ...each enzyme.•Speculates on the design a global, single molecule TDO/IDO1/IDO2 inhibitor.
Tryptophan to kynurenine metabolism is controlled by three distinct dioxygenase enzymes: tryptophan 2,3-dioxygenase (TDO), indoleamine 2,3-dioxygenase 1 (IDO1), and indoleamine 2,3-dioxygenase 2 (IDO2). Collectively, the activity of these enzymes contributes to tumour immune tolerance and immune dysregulation in a variety of disease pathologies, including cancer. Whereas IDO1 inhibitor drug design has been the focus of study for more than two decades (with novel compounds currently in Phase II clinical trials), only recently have the roles of TDO and IDO2 been elucidated in immunosuppression. Consequently, little comparative work on inhibitor cross-reactivity and selectivity has been performed. Here, we provide an overview of the current and future drug discovery landscape for targeting TDO, IDO1, and IDO2 (individually and collectively) for pharmacological intervention.
Genetic characterisation (SSU rRNA genotyping) and Scanning Electron Microscope (SEM) imaging of individual tests were used in tandem to determine the modern species richness of the foraminiferal ...family Elphidiidae (Elphidium, Haynesina and related genera) across the Northeast Atlantic shelf biomes. Specimens were collected at 25 locations from the High Arctic to Iberia, and a total of 1013 individual specimens were successfully SEM imaged and genotyped. Phylogenetic analyses were carried out in combination with 28 other elphidiid sequences from GenBank and seventeen distinct elphidiid genetic types were identified within the sample set, seven being sequenced for the first time. Genetic types cluster into seven main clades which largely represent their general morphological character. Differences between genetic types at the genetic, morphological and biogeographic levels are indicative of species level distinction. Their biogeographic distributions, in combination with elphidiid SSU sequences from GenBank and high resolution images from the literature show that each of them exhibits species-specific rather than clade-specific biogeographies. Due to taxonomic uncertainty and divergent taxonomic concepts between schools, we believe that morphospecies names should not be placed onto molecular phylogenies unless both the morphology and genetic type have been linked to the formally named holotype, or equivalent. Based on strict morphological criteria, we advocate using only a three-stage approach to taxonomy for practical application in micropalaeontological studies. It comprises genotyping, the production of a formal morphological description of the SEM images associated with the genetic type and then the allocation of the most appropriate taxonomic name by comparison with the formal type description. Using this approach, we were able to apply taxonomic names to fifteen genetic types. One of the remaining two may be potentially cryptic, and one is undescribed in the literature. In general, the phylogeographic distribution is in agreement with our knowledge of the ecology and biogeographical distribution of the corresponding morphospecies, highlighting the generally robust taxonomic framework of the Elphidiidae in time and space.
•Extensive sampling from the High Arctic to Portugal;•Linking DNA and morphological data with SEM images of the sequenced specimens;•17/22 European genetic types sampled in this study, among them 7 newly sequenced;•Molecular phylogeny of the 24 presently recognised genetic types of elphidiids grouped in 7 clades;•Biogeographic distribution of the 17 European genetic types studied here;•Morphological characterisation of the 17 genetic types;•Three-stage approach for taxonomy: Genetic characterisation, Morphological description, Allocation of the most appropriate taxonomic name;•15/17 genetic types linked to morphospecies names, 1 cryptic species, 1 unknown species.
Background
Previous studies have demonstrated an association between a diagnosis of cancer and the risk of suicide; however, they failed to account for psychiatric care before a cancer diagnosis, ...which may confound this relationship. The objective of this study was to assess the effect of a cancer diagnosis on the risk of suicide, accounting for prediagnosis psychiatric care utilization.
Methods
All adult residents of Ontario, Canada who were diagnosed with cancer (1 of prostate, breast, colorectal, melanoma, lung, bladder, endometrial, thyroid, kidney, or oral cancer) between 1997 and 2014 were identified. Noncancer controls were matched 4:1 based on sociodemographics, including a psychiatric utilization gradient (PUG) score (with 0 indicating none; 1, outpatient; 2, emergency department; and 3, hospital admission). A marginal, cause‐specific hazard model was used to assess the effect of cancer on the risk of suicidal death.
Results
Among 676,470 patients with cancer and 2,152,682 matched noncancer controls, there were 8.2 and 11.4 suicides per 1000 person‐years of follow‐up, respectively. Patients with cancer had an overall higher risk of suicidal death compared with matched patients without cancer (hazard ratio, 1.34; 95% CI, 1.22‐1.48). This effect was pronounced in the first 50 months after cancer diagnosis (hazard ratio, 1.60; 95% CI, 1.42‐1.81); patients with cancer did not demonstrate an increased risk thereafter. Among individuals with a PUG score 0 or 1, those with cancer were significantly more likely to die of suicide compared with controls. There was no difference in suicide risk between patients with cancer and controls for those who had a PUG score of 2 or 3.
Conclusions
A cancer diagnosis is associated with increased risk of death from suicide compared with the general population even after accounting for precancer diagnosis psychiatric care utilization. The specific factors underlying the observed associations remain to be elucidated.
In this study of 676,470 patients diagnosed with cancer (1 of prostate, breast, colorectal, melanoma, lung, bladder, endometrial, thyroid, kidney, or oral cancer) in Ontario, Canada, who are hard matched to 2,152,682 noncancer controls, a cancer diagnosis is associated with a significant increase in the risk of suicidal death. These results are consistent after accounting for prediagnosis utilization of psychiatric care.
Timely, accurate, and comprehensive estimates of SARS-CoV-2 daily infection rates, cumulative infections, the proportion of the population that has been infected at least once, and the effective ...reproductive number (Reffective) are essential for understanding the determinants of past infection, current transmission patterns, and a population's susceptibility to future infection with the same variant. Although several studies have estimated cumulative SARS-CoV-2 infections in select locations at specific points in time, all of these analyses have relied on biased data inputs that were not adequately corrected for. In this study, we aimed to provide a novel approach to estimating past SARS-CoV-2 daily infections, cumulative infections, and the proportion of the population infected, for 190 countries and territories from the start of the pandemic to Nov 14, 2021. This approach combines data from reported cases, reported deaths, excess deaths attributable to COVID-19, hospitalisations, and seroprevalence surveys to produce more robust estimates that minimise constituent biases.
We produced a comprehensive set of global and location-specific estimates of daily and cumulative SARS-CoV-2 infections through Nov 14, 2021, using data largely from Johns Hopkins University (Baltimore, MD, USA) and national databases for reported cases, hospital admissions, and reported deaths, as well as seroprevalence surveys identified through previous reviews, SeroTracker, and governmental organisations. We corrected these data for known biases such as lags in reporting, accounted for under-reporting of deaths by use of a statistical model of the proportion of excess mortality attributable to SARS-CoV-2, and adjusted seroprevalence surveys for waning antibody sensitivity, vaccinations, and reinfection from SARS-CoV-2 escape variants. We then created an empirical database of infection–detection ratios (IDRs), infection–hospitalisation ratios (IHRs), and infection–fatality ratios (IFRs). To estimate a complete time series for each location, we developed statistical models to predict the IDR, IHR, and IFR by location and day, testing a set of predictors justified through published systematic reviews. Next, we combined three series of estimates of daily infections (cases divided by IDR, hospitalisations divided by IHR, and deaths divided by IFR), into a more robust estimate of daily infections. We then used daily infections to estimate cumulative infections and the cumulative proportion of the population with one or more infections, and we then calculated posterior estimates of cumulative IDR, IHR, and IFR using cumulative infections and the corrected data on reported cases, hospitalisations, and deaths. Finally, we converted daily infections into a historical time series of Reffective by location and day based on assumptions of duration from infection to infectiousness and time an individual spent being infectious. For each of these quantities, we estimated a distribution based on an ensemble framework that captured uncertainty in data sources, model design, and parameter assumptions.
Global daily SARS-CoV-2 infections fluctuated between 3 million and 17 million new infections per day between April, 2020, and October, 2021, peaking in mid-April, 2021, primarily as a result of surges in India. Between the start of the pandemic and Nov 14, 2021, there were an estimated 3·80 billion (95% uncertainty interval 3·44–4·08) total SARS-CoV-2 infections and reinfections combined, and an estimated 3·39 billion (3·08–3·63) individuals, or 43·9% (39·9–46·9) of the global population, had been infected one or more times. 1·34 billion (1·20–1·49) of these infections occurred in south Asia, the highest among the seven super-regions, although the sub-Saharan Africa super-region had the highest infection rate (79·3 per 100 population 69·0–86·4). The high-income super-region had the fewest infections (239 million 226–252), and southeast Asia, east Asia, and Oceania had the lowest infection rate (13·0 per 100 population 8·4–17·7). The cumulative proportion of the population ever infected varied greatly between countries and territories, with rates higher than 70% in 40 countries and lower than 20% in 39 countries. There was no discernible relationship between Reffective and total immunity, and even at total immunity levels of 80%, we observed no indication of an abrupt drop in Reffective, indicating that there is not a clear herd immunity threshold observed in the data.
COVID-19 has already had a staggering impact on the world up to the beginning of the omicron (B.1.1.529) wave, with over 40% of the global population infected at least once by Nov 14, 2021. The vast differences in cumulative proportion of the population infected across locations could help policy makers identify the transmission-prevention strategies that have been most effective, as well as the populations at greatest risk for future infection. This information might also be useful for targeted transmission-prevention interventions, including vaccine prioritisation. Our statistical approach to estimating SARS-CoV-2 infection allows estimates to be updated and disseminated rapidly on the basis of newly available data, which has and will be crucially important for timely COVID-19 research, science, and policy responses.
Bill & Melinda Gates Foundation, J Stanton, T Gillespie, and J and E Nordstrom.
Indoleamine 2,3-dioxygenase (INDO) and tryptophan 2,3-dioxygenase (TDO) each catalyze the first step in the kynurenine pathway of tryptophan metabolism. We describe the discovery of another enzyme ...with this activity, indoleamine 2,3-dioxygenase-like protein (INDOL1), which is closely related to INDO and is expressed in mice and humans. The corresponding genes have a similar genomic structure and are situated adjacent to each other on human and mouse chromosome 8. They are likely to have arisen by gene duplication before the origin of the tetrapods. The expression of INDOL1 is highest in the mouse kidney, followed by epididymis, and liver. Expression of mouse INDOL1 was further localized to the tubular cells in the kidney and the spermatozoa. INDOL1 was assigned its name because of its structural similarity to INDO. We demonstrate that INDOL1 catalyses the conversion of tryptophan to kynurenine therefore a more appropriate nomenclature for the enzymes might be INDO-1 and INDO-2, or the more commonly-used abbreviations, IDO-1 and IDO-2. Although the two proteins have similar enzymatic activities, their different expression patterns within tissues and during malaria infection, suggests a distinct role for each protein. This identification of INDOL1 may help to explain the regulation of the diversity of physiological and patho-physiological processes in which the kynurenine pathway is involved.
Among patients with cancer, prior research suggests that patients with mental illness may have reduced survival. The objective was to assess the impact of psychiatric utilisation (PU) prior to cancer ...diagnosis on survival outcomes.
All residents of Ontario diagnosed with one of the top 10 malignancies (1997-2014) were included. The primary exposure was psychiatric utilisation gradient (PUG) score in 5 years prior to cancer: 0: none, 1: outpatient, 2: emergency department, 3: hospital admission. A multivariable, cause-specific hazard model was used to assess the effect of PUG score on cancer-specific mortality (CSM), and a Cox proportional hazard model for effect on all-cause mortality (ACM).
A toal of 676,125 patients were included: 359,465 (53.2%) with PUG 0, 304,559 (45.0%) PUG 1, 7901 (1.2%) PUG 2, and 4200 (0.6%) PUG 3. Increasing PUG score was independently associated with worse CSM, with an effect gradient across the intensity of pre-diagnosis PU (vs PUG 0): PUG 1 h 1.05 (95% CI 1.04-1.06), PUG 2 h 1.36 (95% CI 1.30-1.42), and PUG 3 h 1.73 (95% CI 1.63-1.84). Increasing PUG score was also associated with worse ACM.
Pre-cancer diagnosis PU is independently associated with worse CSM and ACM following diagnosis among patients with solid organ malignancies.
The kynurenine pathway of tryptophan metabolism converts the amino acid tryptophan into a number of biologically active metabolites. The first and rate-limiting step in this pathway is the conversion ...of tryptophan to N-formylkynurenine and until recently this reaction was thought to be performed by either of two enzymes, tryptophan 2,3-dioxygenase and indoleamine 2,3-dioxygenase. A third enzyme, indoleamine 2,3-dioxygenase-2, indoleamine 2,3-dioxygenase-like protein or proto-indoleamine 2,3-dioxygenase (IDO2, IDO-2, INDOL1 or proto-IDO), with this activity recently has been described. The gene encoding IDO2 is adjacent and structurally similar to the indoleamine 2,3-dioxygenase gene and both mouse genes use multiple promoters to express transcripts with alternate 5′ exons. The IDO2 protein is expressed in the murine kidney, liver, male and female reproductive system. The two IDO enzymes can utilise a similar range of substrates, however they differ in their selectivity for some inhibitors. The selective inhibition of IDO2 by 1-methyl-d-tryptophan suggests that IDO2 activity may have a role in the inhibition of immune responses to tumours.
Research shows women experience higher mortality than men after cardiac surgery but information on sex-differences during postoperative recovery is limited. Days alive and out of hospital (DAH) ...combines death, readmission and length of stay, and may better quantify sex-differences during recovery. This main objective is to evaluate (i) how DAH at 30-days varies between sex and surgical procedure, (ii) DAH responsiveness to patient and surgical complexity, and (iii) longer-term prognostic value of DAH.
We evaluated 111,430 patients (26% female) who underwent one of three types of cardiac surgery (isolated coronary artery bypass CABG, isolated non-CABG, combination procedures) between 2009 - 2019. Primary outcome was DAH at 30 days (DAH
), secondary outcomes were DAH at 90 days (DAH
) and 180 days (DAH
). Data were stratified by sex and surgical group. Unadjusted and risk-adjusted analyses were conducted to determine the association of DAH with patient-, surgery-, and hospital-level characteristics. Patients were divided into two groups (below and above the 10th percentile) based on the number of days at DAH
Proportion of patients below the 10th percentile at DAH
that remained in this group at DAH
and DAH
were determined.
DAH
were lower for women compared to men (22 vs. 23 days), and seen across all surgical groups (isolated CABG 23 vs. 24, isolated non-CABG 22 vs. 23, combined surgeries 19 vs. 21 days). Clinical risk factors including multimorbidity, socioeconomic status and surgical complexity were associated with lower DAH
values, but women showed lower values of DAH
compared to men for many factors. Among patients in the lowest 10th percentile at DAH
, 80% of both females and males remained in the lowest 10th percentile at 90 days, while 72% of females and 76% males remained in that percentile at 180 days.
DAH is a responsive outcome to differences in patient and surgical risk factors. Further research is needed to identify new care pathways to reduce disparities in outcomes between male and female patients.
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