bluuebunny/crossref_metadata_2025 huggingface dataset:
Predictive modelling of thrombus formation in diabetic retinal microaneurysms
Authors: Li He , Sampani Konstantina , Zheng Xiaoning , Papageorgiou Dimitrios P. , Yazdani Alireza , Bernabeu Miguel O. , Karniadakis George E. , Sun Jennifer K.
Published: August 2020

Microaneurysms (MAs) are one of the earliest clinically visible signs of diabetic retinopathy (DR). Vision can be reduced at any stage of DR by MAs, which may enlarge, rupture and leak fluid into the neural retina. Recent advances in ophthalmic imaging techniques enable reconstruction of the geometries of MAs and quantification of the corresponding haemodynamic metrics, such as shear rate and wall shear stress, but there is lack of computational models that can predict thrombus formation in individual MAs. In this study, we couple a particle model to a continuum model to simulate the platelet aggregation in MAs with different shapes. Our simulation results show that under a physiologically relevant blood flow rate, thrombosis is more pronounced in saccular-shaped MAs than fusiform-shaped MAs, in agreement with recent clinical findings. Our model predictions of the size and shape of the thrombi in MAs are consistent with experimental observations, suggesting that our model is capable of predicting the formation of thrombus for newly detected MAs. This is the first quantitative study of thrombosis in MAs through simulating platelet aggregation, and our results suggest that computational models can be used to predict initiation and development of intraluminal thrombus in MAs as well as provide insights into their role in the pathophysiology of DR.
The behavioural challenge of the COVID-19 pandemic: indirect measurements and personalized attitude changing treatments (IMPACT)
Authors: Fischer Ilan , Avrashi Shacked , Oz Tomer , Fadul Rabab , Gutman Koral , Rubenstein Daniel , Kroliczak Gregory , Goerg Sebastian , Glöckner Andreas
Published: August 2020

Following the outbreak of COVID-19 pandemic, governments around the globe coerced their citizens to adhere to preventive health behaviours, aiming to reduce theeffectivereproduction numbers of the virus. Driven by game theoretic considerations and inspired by the work of US National Research Council's Committee on Food Habits (1943) during WWII, and the post-WWII Yale Communication Research Program, the present research shows how to achieve enhanced adherence to health regulations without coercion. To this aim, we combine three elements: (i) indirect measurements, (ii) personalized interventions, and (iii) attitude changing treatments (IMPACT). We find that a cluster of short interventions, such as elaboration on possible consequences, induction of cognitive dissonance, addressing next of kin and similar others and receiving advice following severity judgements, improves individuals' health-preserving attitudes. We propose extending the use of IMPACT under closure periods and during the resumption of social and economic activities under COVID-19 pandemic, since efficient and lasting adherence should rely on personal attitudes rather than on coercion alone. Finally, we point to the opportunity of international cooperation generated by the pandemic.
Assessing wildland–urban interface fire risk
Authors: Mahmoud Hussam , Chulahwat Akshat
Published: August 2020

Recent wildfire events, in the United States (USA) and around the world, have resulted in thousands of homes destroyed and many lives lost, leaving communities and policy makers, once again, with the question as to how to manage wildfire risk. This is particularly important given the prevalent trend of increased fire frequency and intensity. Current approaches to managing wildfires focus on fire suppression and managing fuel build-up in wildlands. However, reliance on these strategies alone has clearly proven inadequate. As such, focus should be shifted towards minimizing potential losses to communities. Achieving this goal, however, requires detailed understanding of the factors that contribute to community vulnerability and the interplay between probability of ignition, vulnerability and calculated risk. In this study, we evaluate wildfire risk for four different communities across the USA for the duration of May to September to communicate a different perspective of risk assessment. We show, for the first time, that community risk is closely related to wind speed and direction, pattern of surrounding wildland vegetation, and buildings layout. The importance of the findings lies in the need for exploring unique viable solutions to reduce risk for every community independently as opposed to embracing a generalized approach as is currently the case.
A 22-gene transcriptomic model indicating individual therapy durations in multidrug-resistant tuberculosis
Authors: Heyckendorf Jan , Marwitz Sebastian , Reimann Maja , Avsar Korkut , DiNardo Andrew , Günther Gunar , Hoelscher Michael , Ibraim Elmira , Kalsdorf Barbara , Kaufmann Stefan H.E. , Kontsevaya Irina , Leth Frank van , Mandalakas Anna Maria , Maurer Florian , Müller Marius , Nitschkowski Dörte , Olaru Ioana D. , Popa Cristina , Rachow Andrea , Rolling Thierry , Rybniker Jan , Salzer Helmut J. F. , Sanchez-Carballo Patricia , Schuhmann Maren , Schaub Dagmar , Spinu Victor , Suárez Isabelle , Terhalle Elena , Unnewehr Markus , Weiner January , Goldmann Torsten , Lange Christoph
Published: August 2020

Emerging multidrug-resistant tuberculosis is a major global health challenge. The World Health Organization currently recommends treatment durations of 9–18 months or more for patients with multidrug-resistant tuberculosis. We identified and validated a host-RNA signature to serve as a biomarker for individualized therapy durations for patients with multidrug-resistant tuberculosis. Adult patients with pulmonary tuberculosis were prospectively enrolled into 5 independent cohorts in Germany and Romania. Clinical and microbiological data, and whole-blood for RNA transcriptomic analysis were collected at pre-defined timepoints throughout therapy. Treatment outcomes were ascertained one year after end-of-therapy. A whole-blood RNA therapy end model was developed in a multi-step process involving a machine-learning algorithm to identify hypothetical individual end-of-treatment timepoints. Fifty patients with drug-susceptible tuberculosis and 30 patients with multidrug-resistant tuberculosis were recruited in the German identification cohorts (DS- and MDR-GIC), 28 patients with drug-susceptible tuberculosis and 32 patients with multidrug-resistant tuberculosis in the German validation cohorts (DS- and MDR-GVC), and 52 patients with multidrug-resistant tuberculosis in the Romanian validation cohort (MDR-RVC). A 22-gene RNA model that defined cure-associated end-of-therapy timepoints was derived from the DS- and MDR-GIC data. The model accurately predicted clinical outcomes for patients in the DS-GVC (AUC=0.937 [95%CI:0.899–0.976]) and suggested that cure may be achieved with shorter treatment durations for tuberculosis patients in the MDR-GIC (mean reduction 218.0 days, 34.2%, p<0.001), the MDR-GVC (mean reduction 211.0 days, 32.9%, p<0.001), and the MDR-RVC (mean reduction of 161.0 days, 23.4%, p=0.001). Biomarker-guided management may substantially shorten the duration of therapy for many patients with multidrug-resistant tuberculosis.

One Sentence Summary

We identified and validated a transcriptome model based on a 22-gene signature to predict individual treatment durations for patients with multidrug-resistant tuberculosis.
Role of interfering substances in the survival of coronaviruses on surfaces and their impact on the efficiency of hand and surface disinfection
Authors: Szpiro L , Pizzorno A , Durimel L , Julien T , Traversier A , Bouchami D , Marie Y , Rosa-Calatrava M , Terrier O , Moules V
Published: August 2020

Contaminated environmental surfaces are considered to represent a significant vector for hospital-acquired viral infections. In this study, we have evaluated the impact of interfering substances on SARS-CoV-2 surface stability and virucidal efficiency of hand sanitizers and surface disinfectant. To this end, surface stability of SARS-CoV-2 was measured on stainless steel in different experimental conditions, with or without an artificial mucus/saliva mixture and compared against that of human coronavirus HCoV-229E and feline coronavirus FCoV. The impact of the mucus/saliva mixture on the virucidal efficiency of 3 commercial alcohol hand sanitizers and 1 surface chemical disinfectant against SARS-CoV-2, HCoV-229E and FCoV was then measured. Our results indicate that mucus/saliva mixture did not demonstrate a beneficial effect on the surface survival of tested viruses, with temperature being an important parameter. In addition, we demonstrated that interfering substances may play an important role in the virucidal efficacy of hand sanitizers and disinfectants, highlighting the need for adapted testing protocols that better reflect current “real life” conditions of use.

Highlights

Contaminated environmental surfaces are a significant vector for viral infections.

We studied the impact of interfering substances on SARS-CoV-2 surface stability and virucidal efficiency.

Mucus/saliva did not demonstrate a beneficial effect on viral surface stability, with temperature being an important parameter.

Interfering substances are important for virucidal surface activity of disinfectants.
Combined Use of Stress Echocardiography and Cardiopulmonary Exercise Testing to Assess Exercise Intolerance after Acute Myocardial Infarction
Authors: Smarz Krzysztof , Jaxa-Chamiec Tomasz , Zaborska Beata , Tysarowski Maciej , Budaj Andrzej
Published: August 2020

Background

Exercise capacity (EC) after acute myocardial infarction (AMI) influences prognosis, but the causes of its reduction are complex and not sufficiently studied.

Methods

We prospectively enrolled consecutive patients who underwent percutaneous coronary intervention for their first AMI with left ventricular ejection fraction (LV EF) >40% at least 4 weeks after AMI. We performed combined stress echocardiography and cardiopulmonary exercise testing (CPET-SE) using a semi-supine cycle ergometer to determine predictors of EC (peak oxygen uptake [VO2]).

Results

Among 81 patients (70% male, mean age 58 ± 11 years), 40% had AMI with ST-segment elevation, and 60% non ST-segment elevation, LV EF was 57 ± 7%; wall motion score index, 1.18 (IQR 1.06 – 1.31); peak VO2, 19.5 ± 5.4 mL/kg/min. Multivariate analysis revealed that parameters at peak exercise: heart rate (β = 0.17, p < 0.001), stroke volume (β = 0.09, p < 0.001), and arteriovenous oxygen difference (A-VO2Diff, β = 93.51, p < 0.001) were independently positively correlated with peak VO2, with A-VO2Diff being its strongest contributor.

Conclusions

In patients treated for AMI with normal/mildly reduced LV EF, EC is associated with peak peripheral oxygen extraction as well as peak heart rate and peak stroke volume. CPET-SE is a useful tool to evaluate decreased fitness in this group.
Promoter methylation and gene expression of Pin1 is associated to the risk on Alzheimer’s disease in Southern Chinese
Authors: Ma Suk Ling , Tang Nelson Leung Sang , Wa Lam Linda Chiu
Published: August 2020

Background

Pin1 is a propyl cis-trans isomerase and it has been associated with age-at-onset of Alzheimer’s disease (AD) and other pathological characteristic of AD. DNA methylation is one of the gene regulation and it might affect the gene expression.

Objectives

This study was aimed to examine the correlation between DNA methylation and gene expression of Pin1 and its effect on the risk of AD in a Chinese population.

Methods

80 AD patients and 180 normal controls were recruited in this study and their cognitive function were assessed. Pin1 gene expression and methylation were quantified by real-time RT-PCR and Melting Curve Analysis-Methylation assay (MCA-Meth) respectively.

Results

Our finding revealed a positive correlation between methylation and gene expression of Pin1 (p=0.001) and increased Pin1 methylation was predisposed to the risk of AD (p<0.001). CG genotype of Pin1 SNP rs2287839 was associated with higher gene expression of Pin1 (p=0.036) and the effect was only prominent in normal controls as AD patients were already methylated at Pin1 promoter. Furthermore, methylation of Pin1 was associated with better performance in cognition (p=0.018).

Conclusions

Our result further supported the involvement of Pin1 in AD and the increased level of Pin1 might be a protective factor for AD.
Asthma inflammatory phenotypes on four continents: most asthma cases are non-eosinophilic
Authors: Pembrey Lucy , Brooks Collin , Mpairwe Harriet , Figueiredo Camila A , Oviedo Aida Y. , Chico Martha , Nambuya Irene , Tumwesige Pius , Robertson Steven , Ring Susan , Barreto Mauricio L. , Cooper Philip J. , Henderson John , Cruz Alvaro A. , Douwes Jeroen , Pearce Neil ,   the WASP Study Group
Published: August 2020

The World Asthma Phenotypes (WASP) study is being conducted in five centres in Brazil, Ecuador, Uganda, New Zealand and the United Kingdom, with a range of prevalence levels and exposures, and a likely range of phenotype distributions. Here we present the main findings with regards to asthma inflammatory phenotypes. We recruited 998 cases and 356 controls: 204/40 in Brazil, 176/67 in Ecuador, 207/50 in Uganda, 235/132 in New Zealand, and 176/67 in the United Kingdom. All centres studied children and adolescents (age-range 8–20 years), with the exception of the UK centre which involved 26–27 year olds. The proportion of participants who produced sputum samples was 87%, with a range from 74% (Brazil) to 91% (Ecuador), and of these 62% were countable with regards to the inflammatory cell types.The proportions of asthma cases who were classified as eosinophilic or mixed granulocytic asthma (the two inflammatory phenotypes which involve eosinophilia) was 39% overall: 35% in Brazil, 32% in Ecuador, 33% in Uganda, 50% in New Zealand, and 28% in the United Kingdom. The non-eosinophilic asthmatics (NEA) had similar chronic severity (e.g. in terms of attacks in the previous year) to the eosinophilic asthmatics (EA). Of the 61% of cases with NEA, 50% showed no signs of inflammation (paucigranulocytic), with 11% having neutrophilic inflammation. This is the first time that sputum induction has been used in a standardised manner to compare asthma inflammatory phenotypes in high income countries (HICs) and low-and-middle-income countries (LMICs). It confirms that most cases are non-eosinophilic, with the proportions ranging from 50% to 72%, across these varied environments; most of these non-eosinophilic cases were paucigranulocytic, with no sign of airways inflammation.
COVID-19 is associated with relative ADAMTS13 deficiency and VWF multimer formation resembling TTP
Authors: Doevelaar Adrian , Bachmann Martin , Hölzer Bodo , Seibert Felix S. , Rohn Benjamin S. , Bauer Frederic , Witzke Oliver , Dittmer Ulf , Bachmann Michael , Yilmaz Serap , Dittmer Rita , Schneppenheim Sonja , Babel Nina , Budde Ulrich , Westhoff Timm H.
Published: August 2020

Background

Thrombotic microangiopathy (TMA) has been repeatedly described in COVID-19 and may contribute to SARS-CoV-2 associated hypercoagulability. The underlying mechanisms remain elusive. We hypothesized that endothelial damage may lead to substantially increased concentrations of Von Willebrand Factor (VWF) with subsequent relative deficiency of ADAMTS13.

Methods

A prospective controlled trial was performed on 75 patients with COVID-19 of mild to critical severity and 10 healthy controls. VWF antigen (VWF:Ag), ADAMTS13 and VWF multimer formation were analyzed in a German hemostaseologic laboratory.

Results

VWF:Ag was 4.8 times higher in COVID-19 patients compared to healthy controls (p< 0.0001), whereas ADAMTS13 activities were not significantly different (p = 0.24). The ADAMTS13/VWF:Ag ratio was significantly lower in COVID-19 than in the control group (24.4±20.5 vs. 79.7±33.2, p< 0.0001). Fourteen patients (18.7%) undercut a critical ratio of 10 as described in thrombotic thrombocytopenic purpura (TTP). Gel analysis of multimers resembled the TTP constellation with loss of the largest multimers in 75% and a smeary triplet pattern in 39% of the patients. The ADAMTS13/VWF:Ag ratio decreased continuously from mild to critical disease (ANOVA p = 0.026). Moreover, it differed significantly between surviving patients and those who died from COVID-19 (p = 0.001) yielding an AUC of 0.232 in ROC curve analysis.

Conclusion

COVID-19 is associated with a substantial increase in VWF levels, which can exceed the ADAMTS13 processing capacity resulting in the formation of large VWF multimers identical to TTP. The ADAMTS13/VWF:Ag ratio is an independent predictor of severity of disease and mortality. These findings render further support to perform studies on the use of plasma exchange in COVID-19 and to include VWF and ADAMTS13 in the diagnostic workup.
Deep learning-based Helicobacter pylori detection for histopathology: A diagnostic study
Authors: Zhou Sharon , Marklund Henrik , Blaha Ondrej , Desai Manisha , Martin Brock , Bingham David , Berry Gerald J. , Gomulia Ellen , Ng Andrew Y. , Shen Jeanne
Published: August 2020

Aims

Deep learning (DL), a sub-area of artificial intelligence, has demonstrated great promise at automating diagnostic tasks in pathology, yet its translation into clinical settings has been slow. Few studies have examined its impact on pathologist performance, when embedded into clinical workflows. The identification of H. pylori on H&E stain is a tedious, imprecise task which might benefit from DL assistance. Here, we developed a DL assistant for diagnosing H. pylori in gastric biopsies and tested its impact on pathologist diagnostic accuracy and turnaround time.

Methods and results

H&E-stained whole-slide images (WSI) of 303 gastric biopsies with ground truth confirmation by immunohistochemistry formed the study dataset; 47 and 126 WSI were respectively used to train and optimize our DL assistant to detect H. pylori, and 130 were used in a clinical experiment in which 3 experienced GI pathologists reviewed the same test set with and without assistance. On the test set, the assistant achieved high performance, with a WSI-level area-under-the-receiver-operating-characteristic curve (AUROC) of 0.965 (95% CI 0.934–0.987). On H. pylori-positive cases, assisted diagnoses were faster (, the fixed effect size for assistance = –0.557, p = 0.003) and much more accurate (OR = 13.37, p< 0.001) than unassisted diagnoses. However, assistance increased diagnostic uncertainty on H. pylori- negative cases, resulting in an overall decrease in assisted accuracy (OR = 0.435, p = 0.016) and negligible impact on overall turnaround time ( for assistance = 0.010, p = 0.860).

Conclusions

DL can assist pathologists with H. pylori diagnosis, but its integration into clinical workflows requires optimization to mitigate diagnostic uncertainty as a potential consequence of assistance.
Allocation of COVID-19 Vaccines Under Limited Supply
Authors: Chen Xin , Li Menglong , Simchi-Levi David , Zhao Tiancheng
Published: August 2020

Problem definition

This paper considers how to allocate COVID-19 vaccines to different age groups when limited vaccines are available over time.

Academic/practical relevance

Vaccine is one of the most effective interventions to contain the ongoing COVID-19 pandemic. However, the initial supply of the COVID-19 vaccine will be limited. An urgent problem for the government is to determine who to get the first dose of the future COVID-19 vaccine.

Methodology

We use epidemic data from New York City to calibrate an age-structured SAPHIRE model that captures the disease dynamics within and across various age groups. The model and data allow us to derive effective static and dynamic vaccine allocation policies minimizing the number of confirmed cases or the numbers of deaths.

Results

The optimal static policies achieve a much smaller number of confirmed cases and deaths compared to other static benchmark policies including the pro rata policy. Dynamic allocation policies, including various versions of the myopic policy, significantly improve on static policies.

Managerial implications

For static policies, our numerical study shows that prioritizing the older groups is beneficial to reduce deaths while prioritizing younger groups is beneficial to avert infections. For dynamic policies, the older groups should be vaccinated at early days and then switch to younger groups. Our analysis provides insights on how to allocate vaccines to the various age groups, which is tightly connected to the decision-maker’s objective.
Discretizing clinical information can reduce antibiotic misuse: a game theoretic approach
Authors: Diamant Maya , Baruch Shoham , Kassem Eias , Muhsen Khitam , Samet Dov , Leshno Moshe , Obolski Uri
Published: August 2020

The overuse of antibiotics is exacerbating the antibiotic resistance crisis. Since this problem is a classic common-goods dilemma, it naturally lends itself to a game-theoretic analysis. Hence, we designed a model wherein physicians weigh whether antibiotics should be prescribed, given that antibiotic usage depletes its future effectiveness. The physicians’ decisions rely on the probability of a bacterial infection before definitive laboratory results are available. We show that the physicians’ equilibrium decision-rule of antibiotic prescription is not socially optimal. However, we prove that discretizing the information provided to physicians can mitigate the gap between their equilibrium decisions and the social optimum of antibiotic prescription. Despite this problem’s complexity, the effectiveness of the discretization solely depends on the distribution of available information. This is demonstrated on theoretic distributions and a clinical dataset. Our results provide a game-theory based guide for optimal output of current and future decision support systems of antibiotic prescription.
SARS-CoV-2 infections and antibody responses among health care workers in a Spanish hospital after a month of follow-up
Authors: Moncunill Gemma , Mayor Alfredo , Santano Rebeca , Jiménez Alfons , Vidal Marta , Tortajada Marta , Sanz Sergi , Méndez Susana , Llupià Anna , Aguilar Ruth , Alonso Selena , Barrios Diana , Carolis Carlo , Cisteró Pau , Chóliz Eugenia , Cruz Angeline , Fochs Silvia , Jairoce Chenjerai , Hecht Jochen , Lamoglia Montserrat , Martínez Mikel J. , Moreno Javier , Mitchell Robert A. , Ortega Natalia , Pey Nuria , Puyol Laura , Ribes Marta , Rosell Neus , Sotomayor Patricia , Torres Sara , Williams Sarah , Barroso Sonia , Vilella Anna , Trilla Antoni , Varela Pilar , Dobaño Carlota , Garcia-Basteiro Alberto L
Published: August 2020

Background

At the peak of the COVID-19 pandemic in Spain, cumulative prevalence of SARS-CoV-2 infection in a cohort of 578 randomly selected health care workers (HCW) from Hospital Clínic de Barcelona was 11.2%.

Methods

A follow-up survey one month after the baseline (April-May 2020) measured SARS-CoV-2 infection by real time reverse-transcriptase polymerase chain reaction (rRT-PCR) and IgM, IgA, IgG and subclasses to the receptor-binding domain of the SARS-CoV-2 spike protein by Luminex. Prevalence of infection was defined by a positive SARS-CoV-2 rRT-PCR and/or antibody seropositivity.

Results

The cumulative prevalence of infection at month 1 was 14.9% (84/565) and the seroprevalence 14.5% (82/565) for IgM and/or IgG and/or IgA. We found 25 (5%) new infections in participants without previous evidence of infection at baseline (501) and two participants seroreverted for IgM and/or IgG and/or IgA. Among seropositive participants at baseline, IgM and IgA levels generally declined at month 1 (antibody decay rates of 0.49 (95% CI, 0.40-0.60) and 0.34 (95% CI, 0.26-0.44)), respectively. Eight percent of the participants seroreverted for IgM and 11% for IgA. Subjects reporting COVID-19-like symptoms and laboratory and other technicians had higher risk of infection. The most frequent subclass responses were IgG1 and IgG2, followed by IgG3, with higher levels of IgG1, and only IgA1 but no IgA2 was detected.

Conclusions

Our findings highlight the importance of a continuous and improved surveillance of SARS-CoV-2 infections in HCW, particularly in high risk groups. The decay of IgA and IgM levels have implications for seroprevalence studies using these isotypes.
The Role of Machine Learning Techniques to Tackle COVID-19 Crisis: A Systematic Review
Authors: Syeda Hafsa Bareen , Syed Mahanazuddin , Sexton Kevin , Syed Shorabuddin , Begum Salma , Syed Farhan , Yu Feliciano
Published: August 2020

Background

The novel coronavirus responsible for COVID-19 has caused havoc with patients presenting a spectrum of complications forcing the healthcare experts around the globe to explore new technological solutions, and treatment plans. Machine learning (ML) based technologies have played a substantial role in solving complex problems, and several organizations have been swift to adopt and customize them in response to the challenges posed by the COVID-19 pandemic.

Objective

The objective of this study is to conduct a systematic literature review on the role of ML as a comprehensive and decisive technology to fight the COVID-19 crisis in the arena of epidemiology, diagnosis, and disease progression.

Methods

A systematic search in PubMed, Web of Science, and CINAHL databases was performed according to the Preferred Reporting Items for Systematic Reviews and Meta-analysis (PRISMA) guidelines to identify all potentially relevant studies published and made available between December 1, 2019, and June 27, 2020. The search syntax was built using keywords specific to COVID-19 and ML. A total of 128 qualified articles were reviewed and analyzed based on the study objectives.

Results

The 128 publications selected were classified into three themes based on ML applications employed to combat the COVID-19 crisis: Computational Epidemiology (CE), Early Detection and Diagnosis (EDD), and Disease Progression (DP). Of the 128 studies, 70 focused on predicting the outbreak, the impact of containment policies, and potential drug discoveries, which were grouped into the CE theme. For the EDD, we grouped forty studies that applied ML techniques to detect the presence of COVID-19 using the patients’ radiological images or lab results. Eighteen publications that focused on predicting the disease progression, outcomes (recovery and mortality), Length of Stay (LOS), and number of Intensive Care Unit (ICU) days for COVID-19 positive patients were classified under the DP theme.

Conclusions

In this systematic review, we assembled the current COVID-19 literature that utilized ML methods to provide insights into the COVID-19 themes, highlighting the important variables, data types, and available COVID-19 resources that can assist in facilitating clinical and translational research.
Genetic Variation in Blood Pressure and Lifetime Risk of Peripheral Artery Disease: A Mendelian Randomization Study
Authors: Levin Michael G. , Klarin Derek , Walker Venexia M. , Gill Dipender , Lynch Julie , Lee Kyung M. , Assimes Themistocles L. , Natarajan Pradeep , Hung Adriana M. , Edwards Todd , Rader Daniel J. , Gaziano J. Michael , Davies Neil M. , Tsao Philip S. , Chang Kyong-Mi , Voight Benjamin F. , Damrauer Scott M.
Published: August 2020

Aims

We aimed to estimate the effect of blood pressure and blood pressure lowering medications (via genetic proxies) on peripheral artery disease.

Methods and Results

GWAS summary statistics were obtained for BP (International Consortium for Blood Pressure + UK Biobank GWAS; N = up to 757,601 individuals), peripheral artery disease (PAD; VA Million Veteran Program; N = 24,009 cases, 150,983 controls), and coronary artery disease (CAD; CARDIoGRAMplusC4D 1000 Genomes; N = 60,801 cases, 123,504 controls). Genetic correlations between systolic BP (SBP), diastolic BP (DBP), pulse pressure (PP) and CAD and PAD were estimated using LD score regression. The strongest correlation was between SBP and CAD (rg= 0.36; p = 3.9 × 10−18). Causal effects were estimated by two-sample MR using a range of pleiotropy-robust methods. Increased SBP, DBP, and PP increased risk of both PAD (SBP OR 1.25 [1.19–1.31] per 10mmHg increase, p = 3 × 10−18; DBP OR 1.27 [1.17–1.39], p = 4 × 10−8; PP OR 1.51 [1.38–1.64], p = 1 × 10−20) and CAD (SBP OR 1.37 [1.29–1.45], p = 2 × 10−24; DBP OR 1.6 [1.45–1.76], p = 7 × 10−22; PP OR 1.56 [1.4–1.75], p = 1 × 10−15). The effects of SBP and DBP were greater for CAD than PAD (pdiff= 0.024 for SBP, pdiff= 4.9 × 10−4for DBP). Increased liability to PAD increased PP (beta = 1.04 [0.62–1.45] mmHg per 1 unit increase in log-odds in liability to PAD, p = 1 × 10−6). MR was also used to estimate the effect of BP lowering through different classes of antihypertensive medications using genetic instruments containing BP-trait associated variants located within genes encoding protein targets of each medication. SBP lowering via calcium channel blocker-associated variants was protective of CAD (OR 0.38 per 10mmHg decrease in SBP; 95% CI 0.19–0.77; p = 0.007).

Conclusions

Higher BP is likely to cause both PAD and CAD but may have a larger effect on CAD risk. BP-lowering through calcium-channel blockers (as proxied by genetic variants) decreased risk of CAD.
A deterministic linear infection model to inform Risk-Cost-Benefit Analysis of activities during the SARS-CoV-2 pandemic
Authors: McCarthy John E. , Dumas Bob A. , McCarthy Myles T. , Dewitt Barry D.
Published: August 2020

August 16, 2020

Risk-cost-benefit analysis requires the enumeration of decision alternatives, their associated outcomes, and the quantification of uncertainty. Public and private decision-making surrounding the COVID-19 pandemic must contend with uncertainty about the probability of infection during activities involving groups of people, in order to decide whether that activity is worth undertaking. We propose a deterministic linear model of SARS-CoV-2 infection probability that can produce estimates of relative risk for diverse activities, so long as those activities meet a list of assumptions, including that they do not last longer than one day. We show how the model can be used to inform decisions facing governments and industry, such as opening stadiums or flying on airplanes. We prove that the model is a good approximation of a more refined model in which we assume infections come from a series of independent risks. The linearity assumption makes interpreting and using the model straightforward, and we argue that it does so without significantly diminishing the reliability of the model.
Bromodomain and Extraterminal Inhibition Blocks Inflammation-Induced Cardiac Dysfunction and SARS-CoV-2 Infection (Pre-Clinical)
Authors: Mills Richard J , Humphrey Sean J , Fortuna Patrick RJ , Lor Mary , Foster Simon R , Quaife-Ryan Gregory A , Johnston Rebecca L. , Dumenil Troy , Bishop Cameron , Ruraraju Rajeev , Rawle Daniel J , Le Thuy , Zhao Wei , Lee Leo , Mackenzie-Kludas Charley , Mehdiabadi Neda R , Halliday Christopher , Gilham Dean , Fu Li , Nicholls Stephen J. , Johansson Jan , Sweeney Michael , Wong Norman C.W. , Kulikowski Ewelina , Sokolowski Kamil A. , Tse Brian W. C. , Devilée Lynn , Voges Holly K , Reynolds Liam T , Krumeich Sophie , Mathieson Ellen , Abu-Bonsrah Dad , Karavendzas Kathy , Griffen Brendan , Titmarsh Drew , Elliott David A , McMahon James , Suhrbier Andreas , Subbarao Kanta , Porrello Enzo R , Smyth Mark J , Engwerda Christian R , MacDonald Kelli PA , Bald Tobias , James David E , Hudson James E
Published: August 2020

Cardiac injury and dysfunction occur in COVID-19 patients and increase the risk of mortality. Causes are ill defined, but could be direct cardiac infection and/or inflammation-induced dysfunction. To identify mechanisms and cardio-protective drugs, we use a state-of-the-art pipeline combining human cardiac organoids with phosphoproteomics and single nuclei RNA sequencing. We identify an inflammatory ‘cytokine-storm’, a cocktail of interferon gamma, interleukin 1β and poly(I:C), induced diastolic dysfunction. Bromodomain-containing protein 4 is activated along with a viral response that is consistent in both human cardiac organoids and hearts of SARS-CoV-2 infected K18-hACE2 mice. Bromodomain and extraterminal family inhibitors (BETi) recover dysfunction in hCO and completely prevent cardiac dysfunction and death in a mouse cytokine-storm model. Additionally, BETi decreases transcription of genes in the viral response, decreases ACE2 expression and reduces SARS-CoV-2 infection of cardiomyocytes. Together, BETi, including the FDA breakthrough designated drug apabetalone, are promising candidates to prevent COVID-19 mediated cardiac damage.
Dynamic Expression of Brain Functional Systems Disclosed by Fine-Scale Analysis of Edge Time Series
Authors: Sporns Olaf , Faskowitz Joshua , Teixera Andreia Sofia , Betzel Richard F.
Published: August 2020

Functional connectivity (FC) describes the statistical dependence between brain regions in resting-state fMRI studies and is usually estimated as the Pearson correlation of time courses. Clustering reveals densely coupled sets of regions constituting a set of resting-state networks or functional systems. These systems manifest most clearly when FC is sampled over longer epochs lasting many minutes but appear to fluctuate on shorter time scales. Here, we propose a new approach to track these temporal fluctuations. Un-wrapping FC signal correlations yields pairwise co-fluctuation time series, one for each node pair/edge, and reveals fine-scale dynamics across the network. Co-fluctuations partition the network, at each time step, into exactly two communities. Sampled over time, the overlay of these bipartitions, a binary decomposition of the original time series, very closely approximates functional connectivity. Bipartitions exhibit characteristic spatiotemporal patterns that are reproducible across participants and imaging sessions and disclose fine-scale profiles of the time-varying levels of expression of functional systems. Our findings document that functional systems appear transiently and intermittently, and that FC results from the overlay of many variable instances of system expression. Potential applications of this decomposition of functional connectivity into a set of binary patterns are discussed.
Structural basis for the allosteric regulation of Human Topoisomerase 2α
Authors: Broeck Arnaud Vanden , Lotz Christophe , Drillien Robert , Bedez Claire , Lamour Valérie
Published: August 2020

The human type IIA topoisomerases (Top2) are essential enzymes that regulate DNA topology and chromosome organization. The Top2α isoform is a prime target for antineoplastic compounds used in cancer therapy that form ternary cleavage complexes with the DNA. Despite extensive studies, structural information on this large dimeric assembly is limited to the catalytic domains, hindering the exploration of allosteric mechanism governing the enzyme activities and the contribution of its non-conserved C-terminal domain (CTD). Herein we present cryo-EM structures of the entire human Top2α nucleoprotein complex in different conformations solved at subnanometer resolutions. Our data unveils the molecular determinants that fine tune the allosteric connections between the ATPase domain and the DNA binding/cleavage domain. Strikingly, the reconstruction of the DNA-binding/cleavage domain uncovers a linker leading to the CTD, which plays a critical role in modulating the enzyme’s activities and opens perspective for the analysis of post-translational modifications.
Estimating Heritability of Glycaemic Response to Metformin using Nationwide Electronic Health Records and Population-Sized Pedigree
Authors: Kalka Iris N. , Gavrieli Amir , Shilo Smadar , Rossman Hagai , Artzi Nitzan Shalom , Segal Eran
Published: August 2020

Variability of response to medication is a well known phenomenon, determined by both environmental and genetic factors. Understanding the heritable component of the response to medication is of great interest but challenging due to several reasons, including small study cohorts and computational limitations. Here, we studied the heritability of variation in the glycaemic response to metformin, first-line therapeutic agent for type 2 diabetes (T2D), by leveraging 17 years of electronic health records (EHR) data from Israel’s largest healthcare service provider, consisting of over five million patients of diverse ethnicities and socio-economic background. Our cohort consisted of 74,871 T2D patients treated with metformin, with an accumulated number of 1,358,776 HbA1C measurements and 323,260 metformin prescriptions. We estimated the explained variance of glycated hemoglobin (HbA1c%) reduction due to heritability by constructing a six-generation population-size pedigree from pedigree information linked to medical health records. Using a Linear Mixed Model-based framework, a common-practice method for heritability estimation, we calculated a heritability measure of h2 = 10.5% (95% CI, 3.5%-17.5%) for absolute reduction of HbA1c% after metformin treatment, which remained unchanged after adjusting for pre-treatment HbA1c%, and h2 = 12.2% (95% CI, 5.2%-19.3%) for proportional reduction in HbA1c%. To the best of our knowledge, our work is the first to estimate heritability of drug response using EHR data. We demonstrated that while response to metformin treatment has a heritable component, most of the variation is likely due to other factors, further motivating non-genetic analyses aimed at unraveling metformin’s mechanism of action.
Using temperature to analyse the neural basis of a time-based decision
Authors: Monteiro Tiago , Rodrigues Filipe S. , Pexirra Margarida , Cruz Bruno F. , Gonçalves Ana I. , Rueda-Orozco Pavel E. , Paton Joseph J.
Published: August 2020

The basal ganglia (BG) are thought to contribute to decision-making and motor control by influencing action selection based on consequences. These functions are critically dependent on timing information that can be extracted from the evolving state of neural populations in the striatum, the major input area of the BG. However, it is debated whether striatal activity underlies latent, dynamic decision processes or kinematics of overt movement. Here, we measured the impact of temperature on striatal population activity and the behavior of rats and compared the observed effects to neural activity and behavior collected in multiple versions of a temporal categorization task. Cooler temperatures caused dilation, and warmer temperatures contraction, of both neural activity and patterns of judgment in time, mimicking endogenous decision-related variability in striatal activity. However, temperature did not similarly affect movement kinematics. These data provide compelling evidence that the time course of evolving striatal population activity dictates the speed of a latent process that is used to guide choices, but not moment by moment kinematics. More broadly, they establish temporal scaling of population activity as a likely cause and not simply a correlate of timing behavior in the brain.
The spatial landscape of gene expression isoforms in tissue sections
Authors: Lebrigand Kevin , Bergenstråhle Joseph , Thrane Kim , Mollbrink Annelie , Meletis Konstantinos , Barbry Pascal , Waldmann Rainer , Lundeberg Joakim
Published: August 2020

In situcapturing technologies add tissue context to gene expression data, with the potential of providing a greater understanding of complex biological systems. However, splicing variants and fulllength sequence heterogeneity cannot be characterized at spatial resolution with current transcriptome profiling methods. To that end, we introduce Spatial Isoform Transcriptomics (SiT), an explorative method for characterizing spatial isoform variation and sequence heterogeneity. We show in mouse brain how SIT can be used to profile isoform expression and sequence heterogeneity in different areas of the tissue. SiT reveals regional isoform switching ofPlp1gene between different layers of the olfactory bulb, and use of external single cell data allowed to nominate cell types expressing each isoform. Furthermore, SiT identifies differential isoform usage for several major genes implicated in brain function (Snap25, Bin1, Gnas) that we independently validated byin situsequencing. SiT also provides for the first time an in-depth A-to-I RNA editing map of the adult mouse brain. Data exploration can be performed through an online resource (https://www.isomics.eu), where isoform expression and RNA editing can be visualized in a spatial context.
Ecology of inorganic sulfur auxiliary metabolism in widespread bacteriophages
Authors: Kieft Kristopher , Zhou Zhichao , Anderson Rika E. , Buchan Alison , Campbell Barbara J. , Hallam Steven J. , Hess Matthias , Sullivan Matthew B. , Walsh David A. , Roux Simon , Anantharaman Karthik
Published: August 2020

Microbial sulfur metabolism contributes to biogeochemical cycling on global scales. Sulfur metabolizing microbes are infected by phages that can encode auxiliary metabolic genes (AMGs) to alter sulfur metabolism within host cells but remain poorly characterized. Here we identified 191 phages derived from twelve environments that encoded 227 AMGs for oxidation of sulfur and thiosulfate (dsrA, dsrC/tusE, soxC, soxD and soxYZ). Evidence for retention of AMGs during niche-differentiation of diverse phage populations provided evidence that auxiliary metabolism imparts measurable fitness benefits to phages with ramifications for ecosystem biogeochemistry. Gene abundance and expression profiles of AMGs suggested significant contributions by phages to sulfur and thiosulfate oxidation in freshwater lakes and oceans, and a sensitive response to changing sulfur concentrations in hydrothermal environments. Overall, our study provides novel insights on the distribution, diversity and ecology of phage auxiliary metabolism associated with sulfur and reinforces the necessity of incorporating viral contributions into biogeochemical configurations.
dbGuide: A database of functionally validated guide RNAs for genome editing in human and mouse cells
Authors: Gooden Alexander A. , Evans Christine N. , Sheets Timothy P. , Clapp Michelle E. , Chari Raj
Published: August 2020

With the technology’s accessibility and ease of use, CRISPR has been employed widely in many different organisms and experimental settings. As a result, thousands of publications have used CRISPR to make specific genetic perturbations, establishing in itself a resource of validated guide RNA sequences. While numerous computational tools to assist in the design and identification of candidate guide RNAs exist, these are still just at best predictions and generally, researchers inevitably will test multiple sequences for functional activity. Here, we presentdbGuide(https://sgrnascorer.cancer.gov/dbguide), a database of functionally validated guide RNA sequences for CRISPR/Cas9-based knockout in human and mouse. Our database not only contains computationally determined candidate guide RNA sequences, but of even greater value, over 4000 sequences which have been functionally validated either through direct amplicon sequencing or manual curation of literature from over 1000 publications. Finally, our established framework will allow for continual addition of newly published and experimentally validated guide RNA sequences for CRISPR/Cas9-based knockout as well as incorporation of sequences from different gene editing systems, additional species, and other types of site-specific functionalities such as base editing, gene activation, repression, and epigenetic modification.
αKG inhibits Regulatory T cell differentiation by coupling lipidome remodelling to mitochondrial metabolism
Authors: Matias Maria I. , Yong Carmen S. , Foroushani Amir , Sezgin Erdinc , Levental Kandice R. , Talebi Ali , Mongellaz Cédric , Dehair Jonas , Wong Madeline , Kinet Sandrina , Zimmermann Valérie S. , Levental Ilya , Yvan-Charvet Laurent , Swinnen Johannes V. , Muljo Stefan A. , Tardito Saverio , Dardalhon Valérie , Taylor Naomi
Published: August 2020

The differentiation of CD4 T cells to a specific effector fate is metabolically regulated, integrating glycolysis and mitochondrial oxidative phosphorylation (OXPHOS) with transcriptional and epigenetic changes. OXPHOS is tightly coordinated with the tricarboxylic acid (TCA) cycle but the precise role of TCA intermediates in CD4 T cell differentiation remain unclear. Here we demonstrate that α-ketoglutarate (αKG) inhibited regulatory T cell (Treg) generation while conversely, increasing Th1 polarization. In accord with these data, αKG promoted the effector profile of Treg-polarized chimeric antigen receptor-engineered T cells against the ErbB2 tumor antigen. Mechanistically, αKG significantly altered transcripts of genes involved in lipid-related processes, inducing a robust lipidome-wide remodelling and decreased membrane fluidity. A massive increase in storage and mitochondria lipids was associated with expression of mitochondrial genes and a significantly augmented OXPHOS. Notably, inhibition of succinate dehydrogenase activity, the bridge between the TCA cycle and the electron transport chain, enforced Treg generation. Thus, our study identifies novel connections between αKG, lipidome remodelling and OXPHOS in CD4 T cell fate decisions.
Discovery and Development of Novel DNA-PK Inhibitors by Targeting the unique Ku-DNA Interaction
Authors: Gavande Navnath S. , VanderVere-Carozza Pamela S. , Pawelczak Katherine S. , Vernon Tyler L. , Hanakahi Leslyn A. , Summerlin Matthew , Dynlacht Joseph R. , Farmer Annabelle H. , Sears Catherine R. , Nasrallah Nawar Al , Garrett Joy , Turchi John J.
Published: August 2020

DNA-dependent protein kinase (DNA-PK) plays a critical role in the non-homologous end joining (NHEJ) repair pathway and the DNA damage response (DDR). DNA-PK has therefore been pursued for the development of anti-cancer therapeutics in combination with ionizing radiation (IR). We report the discovery of a new class of DNA-PK inhibitors that act via a novel mechanism of action, inhibition of the Ku-DNA interaction. We have developed a series of highly potent and specific Ku-DNA binding inhibitors (Ku-DBi’s) that block the Ku-DNA interaction and inhibit DNA-PK kinase activity. Ku-DBi’s directly interact with the Ku and inhibitin vitroNHEJ, cellular NHEJ, and potentiate the activity of IR and radiomimetics. Analysis of Ku-null cells demonstrates that Ku-DBi’s cellular activity is a direct result of Ku inhibition, as Ku-null cells are insensitive to Ku-DBi’s. The utility of Ku-DBi’s was also demonstrated in a CRISPR gene-editing model where we demonstrate that the efficiency of gene insertion events was increased in cells pre-treated with Ku-DBi’s, consistent with inhibition of NHEJ and activation of homologous recombination to facilitate gene insertion. These data demonstrate the discovery and application of new series of compounds that modulate DNA repair pathways via a unique mechanism of action.