Terlipressin therapy is associated with increased risk of colonisation with multidrug-resistant bacteria in patients with decompensated cirrhosis

BACKGROUND

Patients with cirrhosis are susceptible to develop bacterial infections that trigger acute decompensation (AD) and acute-on-chronic liver failure (ACLF). Infections with multidrug-resistant organisms (MDRO) are associated with deleterious outcome. MDRO colonisation frequently proceeds MDRO infections and antibiotic therapy has been associated with MDRO colonisation.

AIM

The aim of the study was to assess the influence of non-antibiotic medication contributing to MDRO colonisation.

METHODS

Three hundred twenty-four patients with AD and ACLF admitted to the ICU of Frankfurt University Hospital with MDRO screening were included. Regression models were performed to identify drugs associated with MDRO colonisation. Another cohort (n = 129) from Barcelona was included to validate. A third multi-centre cohort (n = 203) with metagenomic sequencing data of stool was included to detect antibiotic resistance genes.

RESULTS

A total of 97 patients (30%) were identified to have MDRO colonisation and 35 of them (11%) developed MDRO infection. Patients with MDRO colonisation had significantly higher risk of MDRO infection than those without (p = 0.0098). Apart from antibiotic therapy (odds ratio (OR) 2.91, 95%-confidence interval (CI) 1.82-4.93, p < 0.0001), terlipressin therapy in the previous 14 days was the only independent covariate associated with MDRO colonisation in both cohorts, the overall (OR 9.47, 95%-CI 2.96-30.23, p < 0.0001) and after propensity score matching (OR 5.30, 95%-CI 1.22-23.03, p = 0.011). In the second cohort, prior terlipressin therapy was a risk factor for MDRO colonisation (OR 2.49, 95% CI 0.911-6.823, p = 0.075) and associated with risk of MDRO infection during follow-up (p = 0.017). The validation cohort demonstrated that antibiotic inactivation genes were significantly associated with terlipressin administration (p = 0.001).

CONCLUSIONS

Our study reports an increased risk of MDRO colonisation in patients with AD or ACLF, who recently received terlipressin therapy, while other commonly prescribed non-antibiotic co-medications had negligible influence. Future prospective trials are needed to confirm these results.

Riding the waves from epidemic to endemic: Viral mutations, immunological change and policy responses

Nonpharmaceutical interventions (NPI) are an important tool for countering pandemics such as COVID-19. Some are cheap; others disrupt economic, educational, and social activity. The latter force governments to balance the health benefits of reduced infection and death against broader lockdown-induced societal costs. A literature has developed modeling how to optimally adjust lockdown intensity as an epidemic evolves. This paper extends that literature by augmenting the classic SIR model with additional states and flows capturing decay over time in vaccine-conferred immunity, the possibility that mutations create variants that erode immunity, and that protection against infection erodes faster than protecting against severe illness. As in past models, we find that small changes in parameter values can tip the optimal response between very different solutions, but the extensions considered here create new types of solutions. In some instances, it can be optimal to incur perpetual epidemic waves even if the uncontrolled infection prevalence would settle down to a stable intermediate level.

High-throughput anaerobic screening for identifying compounds acting against gut bacteria in monocultures or communities

The human gut microbiome is a key contributor to health, and its perturbations are linked to many diseases. Small-molecule xenobiotics such as drugs, chemical pollutants and food additives can alter the microbiota composition and are now recognized as one of the main factors underlying microbiome diversity. Mapping the effects of such compounds on the gut microbiome is challenging because of the complexity of the community, anaerobic growth requirements of individual species and the large number of interactions that need to be quantitatively assessed. High-throughput screening setups offer a promising solution for probing the direct inhibitory effects of hundreds of xenobiotics on tens of anaerobic gut bacteria. When automated, such assays enable the cost-effective investigation of a wide range of compound-microbe combinations. We have developed an experimental setup and protocol that enables testing of up to 5,000 compounds on a target gut species under strict anaerobic conditions within 5 d. In addition, with minor modifications to the protocol, drug effects can be tested on microbial communities either assembled from isolates or obtained from stool samples. Experience in working in an anaerobic chamber, especially in performing delicate work with thick chamber gloves, is required for implementing this protocol. We anticipate that this protocol will accelerate the study of interactions between small molecules and the gut microbiome and provide a deeper understanding of this microbial ecosystem, which is intimately intertwined with human health.

SPIRE: a Searchable, Planetary-scale mIcrobiome REsource

Meta'omic data on microbial diversity and function accrue exponentially in public repositories, but derived information is often siloed according to data type, study or sampled microbial environment. Here we present SPIRE, a Searchable Planetary-scale mIcrobiome REsource that integrates various consistently processed metagenome-derived microbial data modalities across habitats, geography and phylogeny. SPIRE encompasses 99 146 metagenomic samples from 739 studies covering a wide array of microbial environments and augmented with manually-curated contextual data. Across a total metagenomic assembly of 16 Tbp, SPIRE comprises 35 billion predicted protein sequences and 1.16 million newly constructed metagenome-assembled genomes (MAGs) of medium or high quality. Beyond mapping to the high-quality genome reference provided by proGenomes3 (http://progenomes.embl.de), these novel MAGs form 92 134 novel species-level clusters, the majority of which are unclassified at species level using current tools. SPIRE enables taxonomic profiling of these species clusters via an updated, custom mOTUs database (https://motu-tool.org/) and includes several layers of functional annotation, as well as crosslinks to several (micro-)biological databases. The resource is accessible, searchable and browsable via http://spire.embl.de.

The hammer and the jab: Are COVID-19 lockdowns and vaccinations complements or substitutes?

The COVID-19 pandemic has devastated lives and economies around the world. Initially a primary response was locking down parts of the economy to reduce social interactions and, hence, the virus' spread. After vaccines have been developed and produced in sufficient quantity, they can largely replace broad lock downs. This paper explores how lockdown policies should be varied during the year or so gap between when a vaccine is approved and when all who wish have been vaccinated. Are vaccines and lockdowns substitutes during that crucial time, in the sense that lockdowns should be reduced as vaccination rates rise? Or might they be complementary with the prospect of imminent vaccination increasing the value of stricter lockdowns, since hospitalization and death averted then may be permanently prevented, not just delayed? We investigate this question with a simple dynamic optimization model that captures both epidemiological and economic considerations. In this model, increasing the rate of vaccine deployment may increase or reduce the optimal total lockdown intensity and duration, depending on the values of other model parameters. That vaccines and lockdowns can act as either substitutes or complements even in a relatively simple model casts doubt on whether in more complicated models or the real world one should expect them to always be just one or the other. Within our model, for parameter values reflecting conditions in developed countries, the typical finding is to ease lockdown intensity gradually after substantial shares of the population have been vaccinated, but other strategies can be optimal for other parameter values. Reserving vaccines for those who have not yet been infected barely outperforms simpler strategies that ignore prior infection status. For certain parameter combinations, there are instances in which two quite different policies can perform equally well, and sometimes very small increases in vaccine capacity can tip the optimal solution to one that involves much longer and more intense lockdowns.

Consistency across multi-omics layers in a drug-perturbed gut microbial community

Multi-omics analyses are used in microbiome studies to understand molecular changes in microbial communities exposed to different conditions. However, it is not always clear how much each omics data type contributes to our understanding and whether they are concordant with each other. Here, we map the molecular response of a synthetic community of 32 human gut bacteria to three non-antibiotic drugs by using five omics layers (16S rRNA gene profiling, metagenomics, metatranscriptomics, metaproteomics and metabolomics). We find that all the omics methods with species resolution are highly consistent in estimating relative species abundances. Furthermore, different omics methods complement each other for capturing functional changes. For example, while nearly all the omics data types captured that the antipsychotic drug chlorpromazine selectively inhibits Bacteroidota representatives in the community, the metatranscriptome and metaproteome suggested that the drug induces stress responses related to protein quality control. Metabolomics revealed a decrease in oligosaccharide uptake, likely caused by Bacteroidota depletion. Our study highlights how multi-omics datasets can be utilized to reveal complex molecular responses to external perturbations in microbial communities.

Computational exploration of the global microbiome for antibiotic discovery

Novel antibiotics are urgently needed to combat the antibiotic-resistance crisis. We present a machine learning-based approach to predict prokaryotic antimicrobial peptides (AMPs) by leveraging a vast dataset of 63,410 metagenomes and 87,920 microbial genomes. This led to the creation of AMPSphere, a comprehensive catalog comprising 863,498 non-redundant peptides, the majority of which were previously unknown. We observed that AMP production varies by habitat, with animal-associated samples displaying the highest proportion of AMPs compared to other habitats. Furthermore, within different human-associated microbiota, strain-level differences were evident. To validate our predictions, we synthesized and experimentally tested 50 AMPs, demonstrating their efficacy against clinically relevant drug-resistant pathogens both in vitro and in vivo. These AMPs exhibited antibacterial activity by targeting the bacterial membrane. Additionally, AMPSphere provides valuable insights into the evolutionary origins of peptides. In conclusion, our approach identified AMP sequences within prokaryotic microbiomes, opening up new avenues for the discovery of antibiotics.

Antibacterial activity of novel bacterial topoisomerase inhibitors against key veterinary pathogens

Multidrug-resistant bacteria infect companion animals and livestock in addition to their devastating impact on human health. Novel Bacterial Topoisomerase Inhibitors (NBTIs) with excellent activity against Gram-positive bacteria have previously been identified as promising new antibacterial agents. Herein, we evaluate the antibacterial activity of these NBTIs against a variety of important veterinary pathogens and demonstrate outstanding in vitro activity, especially against staphylococci.

The global economic burden of chronic obstructive pulmonary disease for 204 countries and territories in 2020-50: a health-augmented macroeconomic modelling study

BACKGROUND

Chronic obstructive pulmonary disease (COPD) is the third leading cause of death worldwide and imposes a substantial economic burden. Gaining a thorough understanding of the economic implications of COPD is an important prerequisite for sound, evidence-based policy making. We aimed to estimate the macroeconomic burden of COPD for each country and establish its distribution across world regions.

METHODS

In this health-augmented macroeconomic modelling study we estimated the macroeconomic burden of COPD for 204 countries and territories over the period 2020-50. The model accounted for (1) the effect of COPD mortality and morbidity on labour supply, (2) age and sex specific differences in education and work experience among those affected by COPD, and (3) the impact of COPD treatment costs on physical capital accumulation. We obtained data from various public sources including the Global Burden of Disease Study 2019, the World Bank database, and the literature. The macroeconomic burden of COPD was assessed by comparing gross domestic product (GDP) between a scenario projecting disease prevalence based on current estimates and a counterfactual scenario with zero COPD prevalence from 2020 to 2050.

FINDINGS

Our findings suggest that COPD will cost the world economy INT$4·326 trillion (uncertainty interval 3·327-5·516; at constant 2017 prices) in 2020-50. This economic effect is equivalent to a yearly tax of 0·111% (0·085-0·141) on global GDP. China and the USA face the largest economic burdens from COPD, accounting for INT$1·363 trillion (uncertainty interval 1·034-1·801) and INT$1·037 trillion (0·868-1·175), respectively.

INTERPRETATION

The macroeconomic burden of COPD is large and unequally distributed across countries, world regions, and income levels. Our study stresses the urgent need to invest in global efforts to curb the health and economic burdens of COPD. Investments in effective interventions against COPD do not represent a burden but could instead provide substantial economic returns in the foreseeable future.

FUNDING

Alexander von Humboldt Foundation, National Natural Science Foundation of China, CAMS Innovation Fund for Medical Science, Chinese Academy of Engineering project, Chinese Academy of Medical Sciences and Peking Union Medical College project, and Horizon Europe.

TRANSLATIONS

For the Chinese and German translations of the abstract see Supplementary Materials section.

SPHINGOLIPIDS ARE DEPLETED IN ALCOHOL-RELATED LIVER FIBROSIS

BACKGROUND & AIMS

Alcohol disturbs hepatic lipid synthesis and transport, but the role of lipid dysfunction in alcohol-related liver disease (ALD) is unclear. In this biopsy-controlled, prospective, observational study, we characterized the liver and plasma lipidomes in patients with early ALD.

METHODS

We performed mass spectrometry-based lipidomics of paired liver and plasma samples from 315 ALD patients, and of plasma from 51 matched healthy controls. We associated lipid levels to histological fibrosis, inflammation and steatosis with correction for multiple testing and adjustment for confounders. We further investigated sphingolipid regulation by qPCR sequencing of miRNA, prediction of liver-related events, and tested causality with Mendelian randomization.

RESULTS

We detected 198 lipids in the liver and 236 lipids in the circulation from 18 lipid classes. Most sphingolipids (sphingomyelins and ceramides) and phosphocholines were co-downregulated in both liver and plasma, where lower abundance correlated with higher fibrosis stage. Sphingomyelins showed the most pronounced negative correlation to fibrosis, mirrored by negative correlations in both liver and plasma with hepatic inflammation. Reduced sphingomyelins furthermore predicted future liver-related events. This seemed to be characteristic of 'pure ALD', as sphingomyelin levels were higher in patients with concomitant metabolic syndrome and ALD/NAFLD overlap. Mendelian randomization in FinnGen and UK Biobanks indicated ALD as the cause of low sphingomyelins, while alcohol use disorder did not correlate with genetic susceptibility to low sphingomyelin levels.

CONCLUSION

Alcohol-related liver fibrosis is characterized by selective and progressive lipid depletion in liver and blood, particularly sphingomyelins, which also associates with progression to liver-related events.

Estimates and Projections of the Global Economic Cost of 29 Cancers in 204 Countries and Territories From 2020 to 2050

Importance

Cancers are a leading cause of mortality, accounting for nearly 10 million annual deaths worldwide, or 1 in 6 deaths. Cancers also negatively affect countries' economic growth. However, the global economic cost of cancers and its worldwide distribution have yet to be studied.

Objective

To estimate and project the economic cost of 29 cancers in 204 countries and territories.

Design, Setting, and Participants

A decision analytical model that incorporates economic feedback in assessing health outcomes associated with the labor force and investment. A macroeconomic model was used to account for (1) the association of cancer-related mortality and morbidity with labor supply; (2) age-sex-specific differences in education, experience, and labor market participation of those who are affected by cancers; and (3) the diversion of cancer treatment expenses from savings and investments. Data were collected on April 25, 2022.

Main Outcomes and Measures

Economic cost of 29 cancers across countries and territories. Costs are presented in international dollars at constant 2017 prices.

Results

The estimated global economic cost of cancers from 2020 to 2050 is $25.2 trillion in international dollars (at constant 2017 prices), equivalent to an annual tax of 0.55% on global gross domestic product. The 5 cancers with the highest economic costs are tracheal, bronchus, and lung cancer (15.4%); colon and rectum cancer (10.9%); breast cancer (7.7%); liver cancer (6.5%); and leukemia (6.3%). China and the US face the largest economic costs of cancers in absolute terms, accounting for 24.1% and 20.8% of the total global burden, respectively. Although 75.1% of cancer deaths occur in low- and middle-income countries, their share of the economic cost of cancers is lower at 49.5%. The relative contribution of treatment costs to the total economic cost of cancers is greater in high-income countries than in low-income countries.

Conclusions and Relevance

In this decision analytical modeling study, the macroeconomic cost of cancers was found to be substantial and distributed heterogeneously across cancer types, countries, and world regions. The findings suggest that global efforts to curb the ongoing burden of cancers are warranted.

Development of a quantitative proteomics approach for cyclooxygenases and lipoxygenases in parallel to quantitative oxylipin analysis allowing the comprehensive investigation of the arachidonic acid cascade

Oxylipins derived from the cyclooxygenase (COX) and lipoxygenase (LOX) pathways of the arachidonic acid (ARA) cascade are essential for the regulation of the inflammatory response and many other physiological functions. Comprehensive analytical methods comprised of oxylipin and protein abundance analysis are required to fully understand mechanisms leading to changes within these pathways. Here, we describe the development of a quantitative multi-omics approach combining liquid chromatography tandem mass spectrometry-based targeted oxylipin metabolomics and proteomics. As the first targeted proteomics method to cover these pathways, it enables the quantitative analysis of all human COX (COX-1 and COX-2) and relevant LOX pathway enzymes (5-LOX, 12-LOX, 15-LOX, 15-LOX-2, and FLAP) in parallel to the analysis of 239 oxylipins with our targeted oxylipin metabolomics method from a single sample. The detailed comparison between MRM3 and classical MRM-based detection in proteomics showed increased selectivity for MRM3, while MRM performed better in terms of sensitivity (LLOQ, 16-122 pM vs. 75-840 pM for the same peptides), linear range (up to 1.5-7.4 μM vs. 4-368 nM), and multiplexing capacities. Thus, the MRM mode was more favorable for this pathway analysis. With this sensitive multi-omics approach, we comprehensively characterized oxylipin and protein patterns in the human monocytic cell line THP-1 and differently polarized primary macrophages. Finally, the quantification of changes in protein and oxylipin levels induced by lipopolysaccharide stimulation and pharmaceutical treatment demonstrates its usefulness to study molecular modes of action involved in the modulation of the ARA cascade.

Functional characterization of SLC39 family members ZIP5 and ZIP10 in overexpressing HEK293 cells reveals selective copper transport activity

Zinc is the second most prevalent metal element present in living organisms, and control of its concentration is pivotal to physiology. The amount of zinc available to the cell cytoplasm is regulated by the activity of members of the SLC39 family, the ZIP proteins. Selectivity of ZIP transporters has been the focus of earlier studies which provided a biochemical and structural basis for the selectivity for zinc over other metals such as copper, iron, and manganese. However, several previous studies have shown how certain ZIP proteins exhibit higher selectivity for metal elements other than zinc. Sequence similarities suggest an evolutionary basis for the elemental selectivity within the ZIP family. Here, by engineering HEK293 cells to overexpress ZIP proteins, we have studied the selectivity of two phylogenetic clades of ZIP proteins, that is ZIP8/ZIP14 (previously known to be iron and manganese transporters) and ZIP5/ZIP10. By incubating ZIP over-expressing cells in presence of several divalent metals, we found that ZIP5 and ZIP10 are high affinity copper transporters with greater selectivity over other elements, revealing a novel substrate signature for the ZIP5/ZIP10 clade.

proGenomes3: approaching one million accurately and consistently annotated high-quality prokaryotic genomes

The interpretation of genomic, transcriptomic and other microbial 'omics data is highly dependent on the availability of well-annotated genomes. As the number of publicly available microbial genomes continues to increase exponentially, the need for quality control and consistent annotation is becoming critical. We present proGenomes3, a database of 907 388 high-quality genomes containing 4 billion genes that passed stringent criteria and have been consistently annotated using multiple functional and taxonomic databases including mobile genetic elements and biosynthetic gene clusters. proGenomes3 encompasses 41 171 species-level clusters, defined based on universal single copy marker genes, for which pan-genomes and contextual habitat annotations are provided. The database is available at http://progenomes.embl.de/.

Health insurance, endogenous medical progress, health expenditure growth, and welfare

We study the impact of health insurance expansion on medical spending, longevity and welfare in an OLG economy in which individuals purchase health care to lower mortality and medical progress is profit-driven. Three sectors are considered: final goods production; a health care sector, selling medical services to individuals; and an R&D sector, selling increasingly effective medical technology to the health care sector. We calibrate the model to the development of the US economy/health care system from 1965 to 2005 and study numerically the impact of the insurance expansion. We find that more extensive health insurance accounts for a large share of the rise in US health spending but also boosts the rate of medical progress. A welfare analysis shows that while the subsidization of health care through health insurance creates excessive health care spending, the gains in life expectancy brought about by induced medical progress more than compensate for this.

GC-MS analysis of oxysterols and their formation in cultivated liver cells (HepG2)

Oxysterols play a key role in many (patho)physiological processes and they are potential biomarkers for oxidative stress in several diseases. Here we developed a rapid gas chromatographic-mass spectrometry-based method for the separation and quantification of 11 biologically relevant oxysterols bearing hydroxy, epoxy, and dihydroxy groups. Efficient chromatographic separation (resolution ≥ 1.9) was achieved using a medium polarity 35%-diphenyl/65%-dimethyl polysiloxane stationary phase material (30 m × 0.25 mm inner diameter and 0.25 μm film thickness). Based on thorough analysis of the fragmentation during electron ionization we developed a strategy to deduce structural information of the oxysterols. Optimized sample preparation includes (i) extraction with a mixture of n-hexane/iso-propanol, (ii) removal of cholesterol by solid phase extraction with unmodified silica, and (iii) trimethylsilylation. The method was successfully applied on the analysis of brain samples, showing consistent results with previous studies and a good intra- and interday precision of ≤20%. Finally, we used the method for the investigation of oxysterol formation during oxidative stress in HepG2 cells. Incubation with tert-butyl hydroperoxide led to a massive increase in free radical formed oxysterols (7-keto-chol > 7β-OH-chol >> 7α-OH-chol), while 24 h incubation with the glutathione peroxidase 4 inhibitor RSL3 showed no increase in oxidative stress based on the oxysterol pattern. Overall, the new method described here enables the robust analysis of a biologically meaningful pattern of oxysterols with high sensitivity and precision allowing us to gain new insights in the biological formation and role of oxysterols.

Evaluation of Three Feature Dimension Reduction Techniques for Machine Learning-Based Crop Yield Prediction Models

Machine learning (ML) has been widely used worldwide to develop crop yield forecasting models. However, it is still challenging to identify the most critical features from a dataset. Although either feature selection (FS) or feature extraction (FX) techniques have been employed, no research compares their performances and, more importantly, the benefits of combining both methods. Therefore, this paper proposes a framework that uses non-feature reduction (All-F) as a baseline to investigate the performance of FS, FX, and a combination of both (FSX). The case study employs the vegetation condition index (VCI)/temperature condition index (TCI) to develop 21 rice yield forecasting models for eight sub-regions in Vietnam based on ML methods, namely linear, support vector machine (SVM), decision tree (Tree), artificial neural network (ANN), and Ensemble. The results reveal that FSX takes full advantage of the FS and FX, leading FSX-based models to perform the best in 18 out of 21 models, while 2 (1) for FS-based (FX-based) models. These FXS-, FS-, and FX-based models improve All-F-based models at an average level of 21% and up to 60% in terms of RMSE. Furthermore, 21 of the best models are developed based on Ensemble (13 models), Tree (6 models), linear (1 model), and ANN (1 model). These findings highlight the significant role of FS, FX, and specially FSX coupled with a wide range of ML algorithms (especially Ensemble) for enhancing the accuracy of predicting crop yield.

Comparative effectiveness of three versions of a stepped care model for insomnia differing in the amount of therapist support in internet-delivered treatment: study protocol for a pragmatic cluster randomised controlled trial (GET Sleep)

INTRODUCTION

It is unclear how internet-delivered cognitive-behavioural therapy for insomnia (CBT-I) can be integrated into healthcare systems, and little is known about the optimal level of therapist guidance. The aim of this study is to investigate three different versions of a stepped care model for insomnia (IG1, IG2, IG3) versus treatment as usual (TAU). IG1, IG2 and IG3 rely on treatment by general practitioners (GPs) in the entry level and differ in the amount of guidance by e-coaches in internet-delivered CBT-I.

METHODS AND ANALYSIS

In this randomised controlled trial, 4268 patients meeting International Classification of Diseases, Tenth Revision (ICD-10) criteria for insomnia will be recruited. The study will use cluster randomisation of GPs with an allocation ratio of 3:3:3:1 (IG1, IG2, IG3, TAU). In step 1 of the stepped care model, GPs will deliver psychoeducational treatment; in step 2, an internet-delivered CBT-I programme will be used; in step 3, GPs will refer patients to specialised treatment. Outcomes will be collected at baseline, and 4 weeks, 12 weeks and 6 months after baseline assessment. The primary outcome is insomnia severity at 6 months. An economic evaluation will be conducted and qualitative interviews will be used to explore barriers and facilitators of the stepped care model.

ETHICS AND DISSEMINATION

The study protocol was approved by the Ethics Committee of the Medical Centre-University of Freiburg. The results of the study will be published irrespective of the outcome.

TRIAL REGISTRATION NUMBER

DRKS00021503.

Socioeconomic environment and survival in patients after ST-segment elevation myocardial infarction (STEMI): a longitudinal study for the City of Vienna

OBJECTIVES

This study investigates the relationship between socioeconomic environment (SEE) and survival after ST-segment elevation myocardial infarction (STEMI) separately for women and men in the City of Vienna, Austria.

DESIGN

Hospital-based observational data of STEMI patients are linked with district-level information on SEE and the mortality register, enabling survival analyses with a 19-year follow-up (2000-2018).

SETTING

The analysis is set at the main tertiary care hospital of the City of Vienna. On weekends, it is the only hospital in charge of treating STEMIs and thus provides representative data for the Viennese population.

PARTICIPANTS

The study comprises a total of 1481 patients with STEMI, including women and men aged 24-94 years.

PRIMARY AND SECONDARY OUTCOME MEASURES

Primary outcome measures are age at STEMI and age at death. We further distinguish between deaths from coronary artery disease (CAD), deaths from acute coronary syndrome (ACS), and other causes of death. SEE is proxied via mean individual gross income from employment in each municipal district.

RESULTS

Results are based on Kaplan-Meier survival probability estimates, Cox proportional hazard regressions and competing risk models, always using age as the time scale. Descriptive findings suggest a socioeconomic gradient in the age at death after STEMI. This finding is, however, not supported by the regression results. Female patients with STEMI have better survival outcomes, but only for deaths related to CAD (HR: 0.668, 95% CIs 0.452 to 0.985) and other causes of deaths (HR: 0.627, 95% CIs 0.444 to 0.884), and not for deaths from the more acute ACS.

CONCLUSIONS

Additional research is necessary to further disentangle the interaction between SEE and age at STEMI, as our findings suggest that individuals from poorer districts have STEMI at younger ages, which indicates vulnerability in regard to health conditions in these neighbourhoods.

Chasing up and locking down the virus: Optimal pandemic interventions within a network

During the COVID-19 pandemic countries invested significant amounts of resources into its containment. In early stages of the pandemic most of the (nonpharmaceutical) interventions can be classified into two groups: (i) testing and identification of infected individuals, (ii) social distancing measures to reduce the transmission probabilities. Furthermore, both groups of measures may, in principle, be targeted at certain subgroups of a networked population. To study such a problem, we propose an extension of the SIR model with additional compartments for quarantine and different courses of the disease across several network nodes. We develop the structure of the optimal allocation and study a numerical example of three symmetric regions that are subject to an asymmetric progression of the disease (starting from an initial hotspot). Key findings include that (i) for our calibrations policies are chosen in a "flattening-the-curve," avoiding hospital congestion; (ii) policies shift from containing spillovers from the hotspot initially to establishing a symmetric pattern of the disease; and (iii) testing that can be effectively targeted allows to reduce substantially the duration of the disease, hospital congestion and the total cost, both in terms of lives lost and economic costs.

Incidence of fatigue associated with immune checkpoint inhibitors in patients with cancer: a meta-analysis

Background

Fatigue is one of the most common adverse effects associated with cancer immunotherapy using checkpoint inhibitors (CPIs). Because treatment-related fatigue also frequently occurs in patients treated with non-immunological therapies, our study aimed to compare the incidence of fatigue in CPI-treated patients with that associated with non-immune therapies in randomised trials.

Methods

PubMed and ClinicalTrials.gov were searched for phase III studies using a CPI alone or in combination with chemotherapy or non-immunologic targeted therapy in the experimental arm and control arm using inactive therapies such as placebo or observation, chemotherapy, or non-immunologic targeted therapy. Adverse events listed in the full texts as well as those available from clinicaltrials.gov were reviewed for all identified studies.

Results

A total of 60 studies involving 41 435 patients were included in the analysis. All-grade fatigue was reported in 30.4% of patients [95% confidence interval (CI) 29.9% to 31.0%] in the immunotherapy arms of the analysed studies. Using anti-programmed cell death protein 1 agents as reference, the odds ratio (OR) for fatigue was significantly higher both for anti-cytotoxic T lymphocyte-associated antigen 4 agents (OR 1.46, 95% CI 1.04-2.04) and the combination of anti-cytotoxic T lymphocyte-associated antigen 4 and anti-programmed cell death protein agents (OR 1.43, 95% CI 1.12-1.83). Fatigue was significantly less likely to occur in patients treated with CPI compared with patients receiving chemotherapy (OR 0.79, 95% CI 0.73-0.85), but significantly was more common in patients receiving the combination of CPI/chemotherapy compared with patients receiving chemotherapy alone (OR 1.12, 95% CI 1.03-1.22).

Conclusions

Although immunotherapy using CPIs was associated with treatment-related fatigue, the occurrence of all-grade fatigue was significantly higher in patients treated with chemotherapy compared with patients receiving CPIs. The risk of fatigue was higher for CPI/chemotherapy combinations than for chemotherapy alone. These results suggest that although the effects of CPIs and chemotherapy are additive, chemotherapy was the dominant cause of treatment-related fatigue in the analysed trials.

•

Fatigue is a common adverse event associated with cancer immunotherapy but also with other therapies and with cancer itself.

•

This meta-analysis analysed the incidence of fatigue reported in phase III trials of checkpoint inhibitors.

•

Fatigue was more common in patients treated with chemotherapy compared with patients receiving checkpoint inhibitors.

•

Chemotherapy was the dominant cause of fatigue in combinations of chemotherapy and checkpoint inhibitors.

Testing a knowledge-based approach for inferring spatio-temporal characteristics of groundwater in the Australian State of Victoria

Groundwater spatio-temporal characteristics are important information for groundwater development and management. However, such information is usually insufficient or even unavailable in many regions around the world due to insufficient or even lack of in-situ data such as from boreholes. Recently, a knowledge-based approach was proposed to infer 'where' and 'when' to find groundwater using Lake Victoria Basin (LVB) as an example for data-deficient regions. In this knowledge-based approach, groundwater model and inversion analysis of groundwater impact factors are used to infer groundwater storage potential and recharge timing. In the LVB's case, only 10 borehole data were used to test the spatio-temporal behaviours of groundwater, which are insufficient. In this contribution, therefore, using the Australian State of Victoria as an example, with over 15,000 boreholes data, the performance of the same knowledge-based approach is further tested in a well-controlled area. The results indicate that the knowledge-based approach is able to correctly infer regions with large groundwater storage potential suitable for extraction. The recharge timing of groundwater is also correctly indicated as the results show consistency with the borehole data. This provides further evidence of the reliability of the knowledge-based approach for inferring spatio-temporal characteristics of groundwater.

Effectiveness of Child-Focused Interventions for Externalizing Behavior: a Rapid Evidence Review

Parent behavior management training (BMT) is well established as an effective, evidence-based treatment for children with externalizing behavior. Despite the wealth of data supporting BMT, many community providers use a variety of child-focused and non-directive interventions to target behavior problems. There is lack of clarity as to whether the evidence supporting child-focused externalizing treatments is sufficiently compelling to support offering these treatments rather than or in addition to BMT. This rapid evidence review compares the effectiveness of BMT with several common child-focused interventions for externalizing behavior including cognitive behavioral (CBT), social skill (SS), and play/dynamic (PT) approaches. PubMed, PsychINFO, and Web of Science were searched for English-language articles from year 2000 onwards for each intervention type. Inclusion criteria were child age (12 and under), presence of a child-focused behavioral treatment condition, and externalizing behavior as an outcome variable. A total of 30 studies met inclusion criteria and were coded (13 CBT, 10 SS, 7 PT). Results supported social skills interventions with accompanying BMT as effective in improving externalizing problems, with generally moderate effect sizes. Individual social skills interventions were promising but needing further evaluation compared to treatment as usual. CBT treatments with and without accompanying BMT showed moderate effects over waitlist but produced less consistently significant effects compared to more robust controls. Play therapy approaches showed inconsistent effects and require further evaluation. This review supports social skills plus BMT treatments as a child-focused intervention with probable efficacy for child externalizing problems. Implications for policy and community practice are discussed.

Enhancing Crop Yield Prediction Utilizing Machine Learning on Satellite-Based Vegetation Health Indices

Accurate crop yield forecasting is essential in the food industry's decision-making process, where vegetation condition index (VCI) and thermal condition index (TCI) coupled with machine learning (ML) algorithms play crucial roles. The drawback, however, is that a one-fits-all prediction model is often employed over an entire region without considering subregional VCI and TCI's spatial variability resulting from environmental and climatic factors. Furthermore, when using nonlinear ML, redundant VCI/TCI data present additional challenges that adversely affect the models' output. This study proposes a framework that (i) employs higher-order spatial independent component analysis (sICA), and (ii), exploits a combination of the principal component analysis (PCA) and ML (i.e., PCA-ML combination) to deal with the two challenges in order to enhance crop yield prediction accuracy. The proposed framework consolidates common VCI/TCI spatial variability into their respective subregions, using Vietnam as an example. Compared to the one-fits-all approach, subregional rice yield forecasting models over Vietnam improved by an average level of 20% up to 60%. PCA-ML combination outperformed ML-only by an average of 18.5% up to 45%. The framework generates rice yield predictions 1 to 2 months ahead of the harvest with an average of 5% error, displaying its reliability.

Rapidly Accumulating Pleural Effusion: A Sequela of Chronic Pancreatitis

Chronic pancreatitis presents with epigastric abdominal pain, nausea, vomiting, and weight loss. Acute pancreatitis can also present with a pleural effusion which is typically left-sided, mild in nature, and self-limiting. However, recurrent bouts of pancreatitis may lead to a pancreaticopleural fistula (PPF) with a large, rapidly recurring, unilateral pleural effusion. Among patients with PPF, the most common presenting complaint is dyspnea. We present the case of a 53-year-old man with recurrent bouts of pancreatitis in the setting of alcohol who presented with progressively worsening shortness of breath. A high-resolution computed topography scan of the thorax demonstrated a large right-sided pleural effusion. A thoracentesis was performed with pleural fluid studies showing an exudative effusion with amylase significantly elevated at 18 382 U/L. An endoscopic retrograde cholangiopancreatography was performed which showed a pancreatic duct leak in the tail of the pancreas. A pancreatic sphincterotomy was performed, and a stent was placed into the ventral pancreatic duct. The patient’s shortness of breath improved, and he was discharged home with outpatient follow-up. The aim of this report is to present the diagnosis of a rare complication of chronic pancreatitis and discuss the management and options for treatment.

Inference of the spatio-temporal variability and storage potential of groundwater in data-deficient regions through groundwater models and inversion of impact factors on groundwater, as exemplified by the Lake Victoria Basin

Groundwater is an important resource for supporting domestic water use for people's livelihoods and for maintaining ecosystems. Borehole observations provide the first-hand data that characterise the fluctuation, depth, and aquifer conditions of the groundwater. Unfortunately, such observations are not available or are insufficient for scientific use in many regions. Taking the Lake Victoria Basin (LVB) as an example of data-deficient regions, this study proposes a simple knowledge-based approach that uses the Global Land Data Assimilation System (GLDAS) Catchment Land Surface Model (CLSM) for the main data, with rainfall, hydrological, topographical and geological datasets as supports, by which to infer the spatio-temporal variability and storage potential of groundwater. The method is based on analysis and inversion of impact factors on groundwater, and the feasibility of such a method is proven by showing that the groundwater results from GLDAS CLSM can correctly indicate the seasonality, as well as the link to topographical and geological features. For example, both results from the water balance equation (WBE) and GLDAS CLSM indicate that there are two groundwater recharge seasons in the basin, e.g., March to May and September to November. Compared to the eastern side of the LVB, the western side has mountains blocking surface runoff, and thus, reasonably, has larger storage potential estimates in GLDAS CLSM. Due to the low degree of weathering of the basement rocks, it is expected that there is only small storage potential and variation of groundwater in the southeastern parts of the LVB. GLDAS CLSM also correctly reflects this behaviour. Additionally, the largest groundwater storage potential over the LVB is found in regions near the Kagera River and the western shoreline, since it associates with unconsolidated rocks and behaviours of large groundwater recharge from GLDAS CSLM during the wet year of 2006. The major limitation of this knowledge-based method is that the uncertainty in terms of magnitude on GLDAS CLSM groundwater changes cannot be assessed, in addition to the fact that the reliability of the results cannot be quantified in terms of specific numbers. Therefore, the results and interpretation of groundwater behaviours using such methods can only be a guide for 'where' and 'when' to find groundwater.

Unravelling the collateral damage of antibiotics on gut bacteria

Antibiotics are used to fight pathogens but also target commensal bacteria, disturbing the composition of gut microbiota and causing dysbiosis and disease1. Despite this well-known collateral damage, the activity spectrum of different antibiotic classes on gut bacteria remains poorly characterized. Here we characterize further 144 antibiotics from a previous screen of more than 1,000 drugs on 38 representative human gut microbiome species2. Antibiotic classes exhibited distinct inhibition spectra, including generation dependence for quinolones and phylogeny independence for β-lactams. Macrolides and tetracyclines, both prototypic bacteriostatic protein synthesis inhibitors, inhibited nearly all commensals tested but also killed several species. Killed bacteria were more readily eliminated from in vitro communities than those inhibited. This species-specific killing activity challenges the long-standing distinction between bactericidal and bacteriostatic antibiotic classes and provides a possible explanation for the strong effect of macrolides on animal3-5 and human6,7 gut microbiomes. To mitigate this collateral damage of macrolides and tetracyclines, we screened for drugs that specifically antagonized the antibiotic activity against abundant Bacteroides species but not against relevant pathogens. Such antidotes selectively protected Bacteroides species from erythromycin treatment in human-stool-derived communities and gnotobiotic mice. These findings illluminate the activity spectra of antibiotics in commensal bacteria and suggest strategies to circumvent their adverse effects on the gut microbiota.

Macro-level efficiency of health expenditure: Estimates for 15 major economies

The coronavirus disease 2019 (COVID-19) pandemic highlights the importance of strong and resilient health systems. Yet how much a society should spend on healthcare is difficult to determine because additional health expenditures imply lower expenditures on other types of consumption. Furthermore, the welfare-maximizing ("efficient") aggregate amount and composition of health expenditures depend on efficiency concepts at three levels that often get blurred in the debate. While the understanding of efficiency is good at the micro- and meso-levels-that is, relating to minimal spending for a given bundle of treatments and to the optimal mix of different treatments, respectively-this understanding rarely links to the efficiency of aggregate health expenditure at the macroeconomic level. While micro- and meso-efficiency are necessary for macro-efficiency, they are not sufficient. We propose a novel framework of a macro-efficiency score to assess welfare-maximizing aggregate health expenditure. This allows us to assess the extent to which selected major economies underspend or overspend on health relative to their gross domestic products per capita. We find that all economies under consideration underspend on healthcare with the exception of the United States. Underspending is particularly severe in China, India, and the Russian Federation. Our study emphasizes that the major and urgent issue in many countries is underspending on health at the macroeconomic level, rather than containing costs at the microeconomic level.

The economic burden of COVID-19 in the United States: Estimates and projections under an infection-based herd immunity approach

OBJECTIVES

To assess the economic burden of COVID-19 that would arise absent behavioral or policy responses under the herd immunity approach in the United States and compare it to the total burden that also accounts for estimates of the value of lives lost.

METHODS

We use the trajectories of age-specific human and physical capital in the production process to calculate output changes based on a human capital-augmented production function. We also calculate the total burden that results when including the value of lives lost as calculated from mortality rates of COVID-19 and estimates for the value of a statistical life in the United States based on studies assessing individual's willingness to pay to avoid risks.

RESULTS

Our results indicate that the GDP loss associated with unmitigated COVID-19 would amount to a cumulative US$1.4 trillion by 2030 assuming that 60 percent of the population is infected over three years. This is equivalent to around 7.7 percent of GDP in 2019 (in constant 2010 US$) or an average tax on yearly output of 0.6 percent. After applying the value of a statistical life to account for the value of lives lost, our analyses show that the total burden can mount to between US$17 and 94 trillion over the next decade, which is equivalent to an annual tax burden between 8 and 43 percent.

CONCLUSION

Our results show that the United States would incur a sizeable burden if it adopted a non-interventionist herd immunity approach.

FUNDING

Research reported in this paper was supported by the Alexander von Humboldt Foundation, the Bill & Melinda Gates Foundation (Project INV-006261), and the Sino-German Center for Research Promotion (Project C-0048), which is funded by the German Research Foundation (DFG) and the National Natural Science Foundation of China (NSFC). Preparation of this article was also supported by the Value of Vaccination Research Network (VoVRN) through a grant from the Bill & Melinda Gates Foundation (Grant OPP1158136). The content is solely the responsibility of the authors.

Coupling proteomics and metabolomics for the unsupervised identification of protein-metabolite interactions in Chaetomium thermophilum

Protein-metabolite interactions play an important role in the cell's metabolism and many methods have been developed to screen them in vitro. However, few methods can be applied at a large scale and not alter biological state. Here we describe a proteometabolomic approach, using chromatography to generate cell fractions which are then analyzed with mass spectrometry for both protein and metabolite identification. Integrating the proteomic and metabolomic analyses makes it possible to identify protein-bound metabolites. Applying the concept to the thermophilic fungus Chaetomium thermophilum, we predict 461 likely protein-metabolite interactions, most of them novel. As a proof of principle, we experimentally validate a predicted interaction between the ribosome and isopentenyl adenine.

Dispersal strategies shape persistence and evolution of human gut bacteria

Human gut bacterial strains can co-exist with their hosts for decades, but little is known about how these microbes persist and disperse, and evolve thereby. Here, we examined these processes in 5,278 adult and infant fecal metagenomes, longitudinally sampled in individuals and families. Our analyses revealed that a subset of gut species is extremely persistent in individuals, families, and geographic regions, represented often by locally successful strains of the phylum Bacteroidota. These “tenacious” bacteria show high levels of genetic adaptation to the human host but a high probability of loss upon antibiotic interventions. By contrast, heredipersistent bacteria, notably Firmicutes, often rely on dispersal strategies with weak phylogeographic patterns but strong family transmissions, likely related to sporulation. These analyses describe how different dispersal strategies can lead to the long-term persistence of human gut microbes with implications for gut flora modulations.

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Bacterial strains may persist within family members through transfer

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Bacteria adapt dispersal strategies: heredipersistent, spatiopersistent, and tenacious

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Dispersal strategies correlate with genetic bottlenecks and effective population size

Impacts of extreme climate on Australia's green cover (2003-2018): A MODIS and mascon probe

Australia as a continent represents a semi-arid environment that is generally water-limited. Changes in rainfall pattern will inevitably occur due to rising temperatures caused by climate change, which has a direct impact on the distribution of Australia's vegetation (green cover). As variability in rainfall continues to increase, i.e., in frequency and/or magnitude, due to climate change, extreme climate events such as droughts are predicted to become more pervasive and severe that will have an adverse effect on vegetation. This study investigates the effects of extreme climate on Australia's green cover during 2003-2018 for the end of rainy seasons of April and October in the northern and southern parts, respectively, to (i) determine the state of vegetation and its changes, (ii) identify "hotspots", i.e., regions that constantly experienced statistically significant decrease in NDVI, and (iii), relate changes in the identified hotspots to GRACE-hydrological changes. These are achieved through the exploitation of the statistical tools of Principal Component Analysis (PCA) and Mann-Kendel Test on Gravity Recovery and Climate Experiment (GRACE) hydrological products on the one hand, and the utilization of Australia's rainfall product and Moderate Resolution Imaging Spectroradiometer Normalized Difference Vegetation Index (MODIS-NDVI) used here with its native spatial resolution of 0.002413^∘ × 0.002413^∘ on the other hand. Differences between 3-year intervals from 2003 to 2018 for both April and October datasets are used to quantify vegetation variations. Through area change analysis, the vegetation differences (2003-2018) indicate that April exhibited larger increase (13.77% of total vegetation area) than decrease (7.83%) compared to October, which experienced slightly larger decrease (9.41%) than increase (8.71%). South Australia and Western Australia emerge as "hotspots" in which vegetation statistically decreased in October, with no noticeable change in April. GRACE-based hydrological changes in both hotspots reflect a decreasing trend (2003-2009) and increasing trend (2009-2012) that peaks in 2011, which then transitions towards a gradually decreasing trend after 2012. Australia-wide climate variability (ENSO and IOD) influenced vegetation variations during the data period 2003 to 2018.

Scanning Compton X-ray microscopy

X-ray microscopy offers the opportunity to image biological and radiosensitive materials without special sample preparations, bridging optical and electron microscopy capabilities. However, the performance of such microscopes, when imaging radiosensitive samples, is not limited by their intrinsic resolution, but by the radiation damage induced on such samples. Here, we demonstrate a novel, to the best of our knowledge, radio-efficient microscope, scanning Compton X-ray microscopy (SCXM), which uses coherently and incoherently (Compton) scattered photons to minimize the deposited energy per unit of mass for a given imaging signal. We implemented SCXM, using lenses capable of efficiently focusing 60 keV X-ray photons into the sub-micrometer scale, and probe its radio-efficient capabilities. SCXM, when implemented in high-energy diffraction-limited storage rings, e.g., European Synchrotron Radiation Facility Extremely Brilliant Source and PETRA IV, will open the opportunity to explore the nanoscale of unstained, unsectioned, and undamaged radiosensitive materials.

Koala cathelicidin PhciCath5 has antimicrobial activity, including against Chlamydia pecorum

Devastating fires in Australia over 2019-20 decimated native fauna and flora, including koalas. The resulting population bottleneck, combined with significant loss of habitat, increases the vulnerability of remaining koala populations to threats which include disease. Chlamydia is one disease which causes significant morbidity and mortality in koalas. The predominant pathogenic species, Chlamydia pecorum, causes severe ocular, urogenital and reproductive tract disease. In marsupials, including the koala, gene expansions of an antimicrobial peptide family known as cathelicidins have enabled protection of immunologically naïve pouch young during early development. We propose that koala cathelicidins are active against Chlamydia and other bacteria and fungi. Here we describe ten koala cathelicidins, five of which contained full length coding sequences that were widely expressed in tissues throughout the body. Focusing on these five, we investigate their antimicrobial activity against two koala C. pecorum isolates from distinct serovars; MarsBar and IPTaLE, as well as other bacteria and fungi. One cathelicidin, PhciCath5, inactivated C. pecorum IPTaLE and MarsBar elementary bodies and significantly reduced the number of inclusions compared to the control (p<0.0001). Despite evidence of cathelicidin expression within tissues known to be infected by Chlamydia, natural PhciCath5 concentrations may be inadequate in vivo to prevent or control C. pecorum infections in koalas. PhciCath5 also displayed antimicrobial activity against fungi and Gram negative and positive bacteria, including methicillin-resistant Staphylococcus aureus (MRSA). Electrostatic interactions likely drive PhciCath5 adherence to the pathogen cell membrane, followed by membrane permeabilisation leading to cell death. Activity against E. coli was reduced in the presence of 10% serum and 20% whole blood. Future modification of the PhciCath5 peptide to enhance activity, including in the presence of serum/blood, may provide a novel solution to Chlamydia infection in koalas and other species.

Efficacy of Retreatment After Failed Direct-acting Antiviral Therapy in Patients With HCV Genotype 1-3 Infections

Hepatitis C virus infection is causing chronic liver disease, cirrhosis, and hepatocellular carcinoma. By combining direct-acting antivirals (DAAs), high sustained virologic response rates (SVRs) can be achieved. Resistance-associated substitutions (RASs) are commonly observed after DAA failure, and especially nonstructural protein 5A (NS5A) RASs may impact retreatment options.^1-3 Data on retreatment of DAA failure patients using first-generation DAAs are limited.^4-7 Recently, a second-generation protease- and NS5A-inhibitor plus sofosbuvir (voxilaprevir/velpatasvir/sofosbuvir [VOX/VEL/SOF]) was approved for retreatment after DAA failure.⁸ However, this and other second-generation regimens are not available in many resource-limited countries or are not reimbursed by regular insurance, and recommendations regarding the selection of retreatment regimens using first-generation DAAs are very important. This study aimed to analyze patients who were re-treated with first-generation DAAs after failure of a DAA combination therapy.

Revisiting the association between temperature and COVID-19 transmissibility across 117 countries

The association between ambient temperature and coronavirus disease 2019 (COVID-19) transmissibility has important implications for containing the disease's spread, yet it is still highly debated. Using a dataset including 65 Chinese cities, Yaoet al. [1] found no significant association between COVID-19 transmissibility and temperature or ultraviolet (UV) radiation. Using a dataset including 154 Chinese cities, Ranet al. [2] reran the analyses and found a nonlinear negative association between temperature and COVID-19 transmissibility.

There is a robust and significant negative association between #COVID19 transmissibility and ambient temperature at the country level. An increase of 1°C in temperature is associated with a decrease in the prevalence of COVID-19 by ∼5.4%.https://bit.ly/32OTBiS

Noncommunicable Diseases Attributable To Tobacco Use In China: Macroeconomic Burden And Tobacco Control Policies

Smoking causes health problems for individuals and imposes a sizable macroeconomic burden on countries. As the world's leading tobacco producer and consumer, China is at the epicenter of this health crisis. However, no studies have examined the macroeconomic burden of all relevant noncommunicable diseases (NCDs) attributable to tobacco or secondhand smoke exposure. We assessed how tobacco-attributable NCDs affect China's productive capacity and estimated that these diseases would impose a total cost of 16.7 trillion yuan (US$2.3 trillion, in constant 2018 prices) in the period 2015-30, which corresponds to an annual tax of 0.9 percent on aggregate income. Secondhand smoke exposure accounts for 14 percent of the burden. If China raised the tax on cigarettes to 75 percent of their retail price and implemented wide-ranging tobacco-control policies, the Chinese economy could save 7.1 trillion yuan (US$1.0 trillion) for 2015-30-the equivalent of adding a 0.4 percent dividend annually.

Identification of metabolites from tandem mass spectra with a machine learning approach utilizing structural features

Motivation

Untargeted mass spectrometry (MS/MS) is a powerful method for detecting metabolites in biological samples. However, fast and accurate identification of the metabolites’ structures from MS/MS spectra is still a great challenge.

Results

We present a new analysis method, called SubFragment-Matching (SF-Matching) that is based on the hypothesis that molecules with similar structural features will exhibit similar fragmentation patterns. We combine information on fragmentation patterns of molecules with shared substructures and then use random forest models to predict whether a given structure can yield a certain fragmentation pattern. These models can then be used to score candidate molecules for a given mass spectrum. For rapid identification, we pre-compute such scores for common biological molecular structure databases. Using benchmarking datasets, we find that our method has similar performance to CSI: FingerID and those very high accuracies can be achieved by combining our method with CSI: FingerID. Rarefaction analysis of the training dataset shows that the performance of our method will increase as more experimental data become available.

Availability and implementation

SF-Matching is available from http://www.bork.embl.de/Docu/sf_matching.

Supplementary information

Supplementary data are available at Bioinformatics online.

Swelling properties of roasted coffee particles

BACKGROUND

In this study, the swelling behavior of roasted coffee particles in water and particularly its impact on particle diameter is examined by applying laser-diffraction analysis and microscopy. Several potential influencing factors are investigated: initial particle size, roasting degree, and temperature. Additionally, the time dependency of swelling and particle shape is evaluated at two different temperatures.

RESULTS

We verify that particle erosion occurs - as observed by an increase of the fine particle fraction after wetting - and it is revealed that this effect is more pronounced with a rise in temperature. The total relative increase in particle size is determined as approximately 15% based on a broad range of different sized coffee grounds. It is demonstrated that the degree of swelling is independent of both the initial particle diameter and the roasting degree. The particle shape is found to be unaffected by swelling. This research reveals that swelling is initially quick, with 60-80% of the final steady-state diameter being reached after 30 s and completed after 4 min of wetting, i.e. within the timescale of conventional coffee brewing methods.

CONCLUSION

This work provides a better understanding of the impact of wetting as part of the coffee brewing process, thus aiding the design, modeling, and optimization of coffee extraction. It clarifies the strong deviation of previous results on coffee-particle swelling by considering particle erosion and degassing and provides a robust method for quantification. © 2020 The Authors. Journal of The Science of Food and Agriculture published by John Wiley & Sons Ltd on behalf of Society of Chemical Industry.

Magnetic Curvatures of a Uniformly Magnetized Tesseroid Using the Cartesian Kernels

In recent years, the gravitational curvatures, the third-order derivatives of the gravitational potential (GP), of a tesseroid have been introduced in the context of gravity field modeling. Analogous to the gravity field, magnetic field modeling can be expanded by magnetic curvatures (MC), the third-order derivatives of the magnetic potential (MP), which are the change rates of the magnetic gradient tensor (MGT). Exploiting Poisson's relations between ( n + 1 ) th-order derivatives of the GP and nth-order derivatives of the MP, this paper derives expressions for the MC of a uniformly magnetized tesseroid using the fourth-order derivatives of the GP of a uniform tesseroid expressed in terms of the Cartesian kernel functions. Based on the magnetic effects of a uniform spherical shell, all expressions for the MP, magnetic vector (MV), MGT and MC of tesseroids have been examined for numerical problems due to singularity of the respective integral kernels (i.e., near zone and polar singularity problems). For this, the closed analytical expressions for the MP, MV, MGT and MC of the uniform spherical shell have been provided and used to generate singularity-free reference values. Varying both height and latitude of the computation point, it is found numerically that the near zone problem also exists for all magnetic quantities (i.e., MP, MV, MGT and MC). The numerical tests also reveal that the polar singularity problems do not occur for the magnetic quantity as a result of the use of Cartesian as opposed to spherical integral kernels. This demonstrates that the magnetic quantity including the newly derived MC 'inherit' the same numerical properties as the corresponding gravitational functional. Possible future applications (e.g., geophysical information) of the MC formulas of a uniformly magnetized tesseroid could be improved modeling of the Earth's magnetic field by dedicated satellite missions.

COVID-19 and climate: global evidence from 117 countries

Visual inspection of world maps shows that coronavirus disease 2019 (COVID-19) is less prevalent in countries closer to the equator, where heat and humidity tend to be higher. Scientists disagree how to interpret this observation because the relationship between COVID-19 and climatic conditions may be confounded by many factors. We regress confirmed COVID-19 cases per million inhabitants in a country against the country’s distance from the equator, controlling key confounding factors: air travel, distance to Wuhan, testing intensity, cell phone usage, vehicle concentration, urbanization, and income. A one-degree increase in absolute latitude is associated with a 2.6% increase in cases per million inhabitants (p value <0.001). The Northern hemisphere may see a decline in new COVID-19 cases during summer and a resurgence during winter.

An increase in absolute latitude by one degree is associated with a 2.6% increase in COVID-19 cases per million inhabitants after controlling for several important factors.

On the Anatomy of Medical Progress Within an Overlapping Generations Economy

We study medical progress within a two-sector economy of overlapping generations subject to endogenous mortality. Individuals demand health care with a view to lowering mortality over their life-cycle. We characterise the individual optimum and the general equilibrium, and study the impact of a major medical innovation leading to an improvement in the effectiveness of health care. We find that general equilibrium effects dampen strongly the increase in health care usage following medical innovation. Moreover, an increase in savings offsets the negative impact on GDP per capita of a decline in the support ratio. Finally, we show that the reallocation of resources between the final goods and health care sector, following the innovation, plays a crucial role in shaping the general equilibrium impact.