bluuebunny/crossref_metadata_2025 huggingface dataset:
Autoimmune Pancreatitis
Authors: Javed Ammar A. , Wright Michael J. , Ding Ding , Javed Zunaira N. , Faghih Mahya , Rozich Noah S. , Fishman Elliot K. , Burns William R. , Cameron John L. , Weiss Matthew J. , He Jin , Singh Vikesh K. , Wolfgang Christopher L. , Burkhart Richard A.
Published: May 2021

Objective

The aim of this study was to critically analyze the surgical experience of managing autoimmune pancreatitis (AIP) in an era of modern diagnostics and compare these patients with those who were managed conservatively.

Methods

Two prospectively maintained databases were used to retrospectively identify patients with AIP who were either managed conservatively or underwent pancreatectomy.

Results

Eighty-eight patients were included in the study, of which 56 (63.6%) underwent resection and 32 (36.4%) were managed conservatively. Patients who underwent resection were more likely to present with jaundice (64.3% vs 18.1%, P < 0.001) and weight loss (53.6% vs 15.6%, P = 0.005). The cohort who underwent resection had a significantly higher median carbohydrate antigen 19-9 (40.0 vs 18.6 U/mL, P = 0.034) and was less likely to have elevated immunoglobulin G4 (26.1% vs 50.0%, P < 0.001). The most frequent initial diagnosis in the cohort who underwent resection was ductal adenocarcinoma (82.1%). Nine patients (28.1%) in the conservatively managed cohort experienced AIP relapse compared with 6 patients (10.7%) in the cohort who underwent resection.

Conclusions

The most frequent reason for surgical resection of AIP is concern for malignancy. Carbohydrate antigen 19-9 elevations were more common than immunoglobulin G4 in our cohort, suggesting that this laboratory profile is suboptimal for this population.
Giant Cell Arteritis: When an Inspection Is Essential
Authors: Molins-Rojas Cristina , Vicente-Pascual Mikel
Published: May 2021

Introduction:

The diagnosis of giant cell arteritis is based on clinical and analytical data. The definitive diagnosis is based on histopathologic study.

Case Report:

We present a patient with a typical headache, a prominent temporal artery in the examination, anemia, and elevation in erythrocyte sedimentation rate and C-reactive protein in blood analysis, and a halo sign in the sonography study, all compatible with giant cell arteritis.

Conclusion:

When dealing a patient with a typical headache, a prominent artery in the inspection, and a visualization of halo sign in ultrasound examination, this diagnosis must be considered.
Erythropoietin-Associated Posterior Reversible Encephalopathy Syndrome
Authors: White Jessica Daley , Anne Madhurima , Muralidharan Rajanandini
Published: May 2021

Introduction:

This case demonstrates an underrecognized cause of posterior reversible encephalopathy syndrome (PRES).

Case Report:

We report a 51-year-old male with a history of essential hypertension without preexisting renal impairment who presented with 3 days of occipital headache and convulsive status epilepticus in the setting of refractory hypertension. He had been receiving outpatient human recombinant erythropoietin injections for virally mediated bone marrow suppression, which worsened his baseline hypertension. Magnetic resosnance imaging (MRI) of the brain on admission showed diffuse bilateral, symmetric signal hyperintensities and patchy enhancement involving the cortex and white matter in both cerebral hemispheres. His blood pressure and seizures were successfully treated during hospital admission, with complete resolution of his neurological deficits. MRI brain performed 6 weeks from initial scan showed normalization of his prior findings.

Conclusion:

Recombinant human erythropoietin (RhEPO) may be an underrecognized cause of PRES and should be considered in patients receiving this treatment regardless of the absence or presence of renal impairment. RhEPO-mediated precipitation/exacerbation of hypertension, alterations in cerebral blood flow, and changes in endothelial integrity may underlie this association. MRI signal changes are reversible and typical for that of PRES, and significant improvement of symptoms can be expected.
Mixed methods systematic review and metasummary about barriers and facilitators for the implementation of cotrimoxazole and isoniazid – preventive therapies for people living with HIV
Authors: Müller Pia , Velez Lapão Luís
Published: May 2021

Background

Cotrimoxazole and isoniazid preventive therapy (CPT, IPT) have been shown to be efficacious therapies for the prevention of opportunistic infections and tuberculosis (TB) among people living with human immunodeficiency virus (HIV). Despite governments’ efforts to translate World Health Organization recommendations into practice, implementation remains challenging. This review aimed to explore and compare CPT and IPT with respect to similarities and differences of barriers identified across high TB/HIV burden countries. A secondary objective was to identify facilitators for implementing both preventive therapies.

Methods

We searched MEDLINE, Web of Science and SCOPUS databases for peer-reviewed literature published before September 2020. We extracted and synthesized our findings using Maxqda software. We applied framework synthesis in conjunction with metasummary to compare both therapies with respect to similarities and differences of barriers identified across seven health system components (in line with the modified WHO’s Framework for action). Protocol registration: PROSPERO (CRD42019137778).

Findings

We identified four hundred and eighty-two papers, of which we included forty for review. Although most barrier themes were identical for both preventive therapies, we identified seven intervention-specific themes. Like for CPT, barriers identified for IPT were most frequently classified as ‘service delivery-related barriers’ and ‘patient & community-related barriers’. ‘Health provider-related barriers’ played an additional important role for implementing of IPT. Most facilitators identified referred to health system strengthening activities.

Conclusions

For researchers with limited working experience in high TB/HIV burden countries, this review can provide valuable insights about barriers that may arise at different levels of the health system. For policymakers in high TB/HIV burden countries, this review offers strategies for improving the delivery of IPT (or any newer therapy regimen) for the prevention of TB. Based on our findings, we suggest initial and continuous stakeholder involvement, a focus on the efficient use and reinforcement of existing resources for health.
COVID-19 vaccine-associated cerebral venous thrombosis in Germany
Authors: Schulz Jörg B. , Berlit Peter , Diener Hans-Christoph , Gerloff Christian , Greinacher Andreas , Klein Christine , Petzold Gabor C. , Piccininni Marco , Poli Sven , Röhrig Rainer , Steinmetz Helmuth , Thiele Thomas , Kurth Tobias ,   the DGN SARS-CoV-2 Vaccination Study Group
Published: May 2021

Objective

Reports of cerebral sinus and venous thrombosis (CVT) after ChAdOx1 vaccination against SARS-CoV-2 have raised safety concerns. We aimed to estimate the incidence of CVT within one month from first dose administration and the frequency of vaccine-induced immune thrombotic thrombocytopenia (VITT) as the underlying mechanism after vaccination with BNT162b2, ChAdOx1, and mRNA-1273, in Germany.

Methods

A web-based questionnaire was e-mailed to all Departments of Neurology. We asked to report cases of CVT within one month of a COVID-19 vaccination. Other cerebral events could also be reported. Incidence rates of CVT were calculated by using official statistics of nine German States.

Results

A total of 45 CVT cases were reported. In addition, 9 primary ischemic strokes, 4 primary intracerebral hemorrhages, and 4 other neurological events were recorded. Of the CVT patients, 35 (77.8%) were female, and 36 (80.0%) were below the age of 60 years. Fifty-three events were observed after vaccination with ChAdOx1 (85.5%), 9 after BNT162b2 (14.5%), and none after mRNA-1273 vaccination. After 7,126,434 first vaccine doses, the incidence rate of CVT within one month from first dose administration was 6.5 (95% CI, 4.4-9.2) per 100,000 person-years for all vaccines and 17.9 (11.8-26.1) for ChAdOx1 (after 2,320,535 ChAdOx1 first doses). The adjusted incidence rate ratio was 9.68 (3.46-34.98) for ChAdOx1 compared to mRNA-based vaccines and 3.14 (1.22-10.65) for women compared to non-women. In 26/45 patients with CVT (57.8%), VITT was graded highly probable.

Conclusions

Given an incidence of 0.22–1.75 per 100,000 person-years for CVT in the general population, these findings point towards a higher risk for CVT after ChAdOx1 vaccination, especially for women.
Information and Communication Technology (ICT) in Medical Education: A Survey among Medical Students’ of Bangladesh
Authors: Ferdoush Jannatul , Jeenia Fatiha Tasmin , Khan IkramUllah , Chowdhury Tasfia Momtaj , Alam Zahangir , Morshed Md. Masud , Chowdhury Abhijit , Parveen Kohinoor , Ata Maliha , Biswas Rajat Sanker Roy
Published: May 2021

Background

Bangladesh is declared as Digital Bangladesh however medical students are least acquainted with the necessary ICT knowledge in the context of medical education. We have conducted a survey to know about Digital Equipment Ownership, therefore, carried out a self-reported assessment of knowledge and Utilization of ICT in relation to educational and clinical development.

Materials and Methods

A cross-sectional, multi-centered questionnaire survey was conducted among the medical students during the period of October 2019.

Result & Discussions

In total 467 medical students responded to the questionnaire in which 92% of the students owned a Google android smart phone and accessed the internet on their devices. 69% student has (1-5) medical related apps in their device and drug formulary apps most commonly used 43%. 59% of students have gained their present computer knowledge by via self-learning. For study work with fellow student, 90% student preferred Facebook group, Whats app and Viber. While there was a range of variation in the usage of non-academic search engines 72% Google and no usages were found for more dedicated academic services such as PubMed and Medscape. According to 74% of students, inadequate integration of ICT knowledge into their syllabus culminated in insufficient future professional skills. All students were keen for a Basic ICT learning program at the beginning of their medical courses.

Conclusion

The study revealed that to prepare medical students for using ICT in their academic work adequately, introducing ICT training at the initial stage of the undergraduate program and designing the curriculum to develop a multiplicity of skills is essential in addition to an integrated teaching method.
Tree Diet: Reducing the Treewidth to Unlock FPT Algorithms in RNA Bioinformatics
Authors: Marchand Bertrand , Ponty Yann , Bulteau Laurent
Published: May 2021

Hard graph problems are ubiquitous in Bioinformatics, inspiring the design of specialized Fixed-Parameter Tractable algorithms, many of which rely on a combination of tree-decomposition and dynamic programming. The time/space complexities of such approaches hinge critically on low values for the treewidthtwof the input graph. In order to extend their scope of applicability, we introduce the Tree-Dietproblem,i.e. the removal of a minimal set of edges such that a given tree-decomposition can be slimmed down to a prescribed treewidthtw′. Our rationale is that the time gained thanks to a smaller treewidth in a parameterized algorithm compensates the extra post-processing needed to take deleted edges into account.

Our core result is an FPT dynamic programming algorithm for Tree-Diet, using 2O(tw)ntime and space. We complement this result with parameterized complexity lower-bounds for stronger variants (e.g., NP-hardness whentw′ ortw−tw′ is constant). We propose a prototype implementation for our approach which we apply on difficult instances of selected RNA-based problems: RNA design, sequence-structure alignment, and search of pseudoknotted RNAs in genomes, revealing very encouraging results. This work paves the way for a wider adoption of tree-decomposition-based algorithms in Bioinformatics.
The immunological factors predisposing to severe COVID-19 are already present in healthy elderly and men
Authors: Kilic Gizem , Bulut Ozlem , Jaeger Martin , Horst Rob ter , Koeken Valerie A. C. M. , Moorlag Simone , Mourits Vera P. , de Bree Charlotte , Domínguez-Andrés Jorge , Joosten Leo A. B. , Netea Mihai G.
Published: May 2021

Background

Male sex and old age are risk factors for COVID-19 severity, but the underlying causes are unknown. A possible explanation for this might be the differences in immunological profiles in males and the elderly before the infection. Given the seasonal profile of COVID-19, the seasonal response against SARS-CoV-2 could also be different in these groups.

Methods

The abundance of circulating proteins and immune populations associated with severe COVID-19 was analyzed in 2 healthy cohorts. PBMCs of female, male, young, and old subjects in different seasons of the year were stimulated with heat-inactivated SARS-CoV-2.

Result

Several T cell subsets, which are known to be depleted in severe COVID-19 patients, were intrinsically less abundant in men and older individuals. Plasma proteins increasing with disease severity, including HGF, IL-8, and MCP-1, were more abundant in the elderly and males. The elderly produced significantly more IL-1RA and had a dysregulated IFNγ response with lower production in the summer compared with young individuals.

Conclusions

The immune characteristics of severe COVID-19, described by a differential abundance of immune cells and circulating inflammatory proteins, are intrinsically present in healthy men and the elderly. This might explain the susceptibility of men and the elderly to SARS-CoV-2 infection.

Immunological profile of severe COVID-19, characterized by altered immune cell populations and inflammatory plasma proteins is intrinsically present in healthy men and the elderly. Different age and sex groups show distinct seasonal responses to SARS-CoV-2.
Infection Units: A novel approach to the modeling of COVID-19 spread
Authors: Merchuk Jose C. , García-Camacho Francisco , López-Rosales Lorenzo
Published: May 2021

A novel mechanistic model describing the rate of COVID-19 spread is presented, that differs conceptually from previously published deterministic models. One of its main characteristics is that the pool of infected people is not assumed to be homogeneously mixed, but rather as a passage into which individuals enter upon contagion, move within it in a plug-flow manner and leave at recovery, within a fixed time period. So, the present model differs conceptually in the way it describes the dynamics of infection. An ‘infection unit’ is defined as the amount of COVID-19 virus that generates contagion, if it reaches a susceptible individual. This model separately considers various pools: symptomatic and asymptomatic infected patients; three different pools of recovered individuals; pools of assisted, hospitalized patients; the quarantined and, finally, those who died from COVID-19. The transmission of the disease from an infected person to others is described by aninfection rate function, while anencounter frequency functionmodulates the frequency of effective encounters between the infected and the susceptible. The influence of the model’s parameters on the predicted results is presented. The effect of social restrictions and of quarantine policy on pandemic spread is shown. For model calibration, a set of experimental data is used. The model enables the calculation of the actual behaviour of the studied pools during pandemic spread.
Actigraphy Informs Distinct Patient-Centered Outcomes in Pre-COPD
Authors: Chen Jianhong , Weldemichael Lemlem , Giang Brian , Geerts Jeroen , Zeng Siyang , Ching Wendy Czerina , Nishihama Melissa , Gold Warren M , Arjomandi Mehrdad
Published: May 2021

Background

Actigraphy can clarify useful patient-centered outcomes for quantification of physical activity in the “real-world” setting.

Methods

To characterize the relationship of actigraphy outputs with “in-laboratory” measures of cardiopulmonary function and respiratory symptoms in pre-COPD, we obtained actigraphy data for 8 hours/day for 5 consecutive days a week before in-laboratory administration of respiratory questionnaires, PFT, and CPET to a subgroup of subjects participating in the larger study of the health effects of exposure to secondhand tobacco smoke who had air trapping but no spirometric obstruction (pre-COPD). Using machine learning approaches, we identified the most relevant actigraphy predictors and examined their associations with symptoms, lung function, and exercise outcomes.

Results

Sixty-one subjects (age=66±7years; BMI=24±3kg/m2; FEV1/FVC=0.75±0.05; FEV1=103±17%predicted) completed the nested study. In the hierarchical cluster analysis, the activity, distance, and energy domains of actigraphy, including moderate to vigorous physical activity, were closely correlated with each other, but were only loosely associated with spirometric and peak exercise measures of oxygen consumption, ventilation, oxygen-pulse, and anaerobic threshold (VO2AT), and were divergent from symptom measures. Conversely, the sedentary domain clustered with respiratory symptoms, air trapping, airflow indices, and ventilatory efficiency. In Regression modeling, sedentary domain was inversely associated with baseline lung volumes and tidal breathing at peak exercise, while the activity domains were associated with VO2AT. Respiratory symptoms and PFT data were not associated with actigraphy outcomes.

Discussion

Outpatient actigraphy can provide information for “real-world” patient-centered outcomes that are not captured by standardized respiratory questionnaires, lung function, or exercise testing. Actigraphy activity and sedentary domains inform of distinct outcomes.

VISUAL ABSTRACT
COVID-19 wastewater surveillance in rural communities: Comparison of lagoon and pumping station samples
Authors: D’Aoust Patrick M. , Towhid Syeda Tasneem , Mercier Élisabeth , Hegazy Nada , Tian Xin , Bhatnagar Kamya , Zhang Zhihao , Naughton Colleen C. , MacKenzie Alex E. , Graber Tyson E. , Delatolla Robert
Published: May 2021

Wastewater-based epidemiology/wastewater surveillance has been a topic of significant interest over the last year due to its application in SARS-CoV-2 surveillance to track prevalence of COVID-19 in communities. Although SARS-CoV-2 surveillance has been applied in more than 50 countries to date, the application of this surveillance has been largely focused on relatively affluent urban and peri-urban communities. As such, there is a knowledge gap regarding the implementation of reliable wastewater surveillance in small and rural communities for the purpose of tracking rates of incidence of COVID-19 and other pathogens or biomarkers. This study examines the relationships existing between SARS-CoV-2 viral signal from wastewater samples harvested from an upstream pumping station and from an access port at a downstream wastewater treatment lagoon with the community’s COVID-19 rate of incidence (measured as percent test positivity) in a small, rural community in Canada. Real-time quantitative polymerase chain reaction (RT-qPCR) targeting the N1 and N2 genes of SARS-CoV-2 demonstrate that all 24-hr composite samples harvested from the pumping station over a period of 5.5 weeks had strong viral signal, while all samples 24-hr composite samples harvested from the lagoon over the same period were below the limit of quantification. RNA concentrations and integrity of samples harvested from the lagoon were both lower and more variable than from samples from the upstream pumping station collected on the same date, indicating a higher overall stability of SARS-CoV-2 RNA upstream of the lagoon. Additionally, measurements of PMMoV signal in wastewater allowed to normalize SARS-CoV-2 viral signal for fecal matter content, permitting the detection of actual changes in community prevalence with a high level of granularity. As a result, in sewered small and rural communities or low-income regions operating wastewater lagoons, samples for wastewater surveillance should be harvested from pumping stations or the sewershed as opposed to lagoons.
Mapping of pseudouridine residues on cellular and viral transcripts using a novel antibody-based technique
Authors: Campos Cecilia Martinez , Tsai Kevin , Courtney David G. , Bogerd Hal P. , Holley Christopher L. , Cullen Bryan R.
Published: May 2021

Pseudouridine (Ψ) is the most common non-canonical ribonucleoside present on mammalian non-coding RNAs (ncRNAs), including rRNAs, tRNAs and snRNAs, where it contributes ∼7% of the total uridine level. However, Ψ constitutes only ∼0.1% of the uridines present on mRNAs and its effect on mRNA function remains unclear. Ψ residues have been shown to inhibit the detection of exogenous RNA transcripts by host innate immune factors, thus raising the possibility that viruses might have subverted the addition of Ψ residues to mRNAs by host pseudouridine synthase (PUS) enzymes as a way to inhibit antiviral responses in infected cells. Here, we describe and validate a novel antibody-based Ψ mapping technique called photo-crosslinking assisted Ψ sequencing (PA-Ψ-seq) and use it to map Ψ residues on not only multiple cellular RNAs but also on the mRNAs and genomic RNA encoded by HIV-1. We describe several 293T-derived cell lines in which human PUS enzymes previously reported to add Ψ residues to human mRNAs, specifically PUS1, PUS7 and TRUB1/PUS4, were inactivated by gene editing. Surprisingly, while this allowed us to assign several sites of Ψ addition on cellular mRNAs to each of these three PUS enzymes, the Ψ sites present on HIV-1 transcripts remained unaffected. Moreover, loss of PUS1, PUS7 or TRUB1 function did not significantly reduce the level of Ψ residues detected on total human mRNA below the ∼0.1% level seen in wild type cells, thus implying that the PUS enzyme(s) that adds the bulk of Ψ residues to human mRNAs remains to be defined.
SARS-CoV-2 Genome Sequencing Methods Differ In Their Ability To Detect Variants From Low Viral Load Samples
Authors: Lam C. , Gray K. , Gall M. , Sadsad R. , Arnott A. , Johnson-Mackinnon J. , Fong W. , Basile K. , Kok J. , Dwyer D. E. , Sintchenko V. , Rockett R.J.
Published: May 2021

SARS-CoV-2 genomic surveillance has been vital in understanding the spread of COVID-19, the emergence of viral escape mutants and variants of concern. However, low viral loads in clinical specimens affect variant calling for phylogenetic analyses and detection of low frequency variants, important in uncovering infection transmission chains. We systematically evaluated three widely adopted SARS-CoV-2 whole genome sequencing methods for their sensitivity, specificity, and ability to reliably detect low frequency variants. Our analyses highlight that the ARTIC v3 protocol consistently displays high sensitivity for generating complete genomes at low viral loads compared with the probe-based Illumina respiratory viral oligo panel, and a pooled long-amplicon method. We show substantial variability in the number and location of low-frequency variants detected using the three methods, highlighting the importance of selecting appropriate methods to obtain high quality sequence data from low viral load samples for public health and genomic surveillance purposes.
In silicoandin vitroDemonstration of Homoharrintonine’s Antagonism of RBD-ACE2 Binding and its Anti-inflammatory and anti-thrombogenic Properties in a 3D human vascular lung model
Authors: Saxena Shalini , Meher Kranti , Rotella Madhuri , Vangala Subhramanyam , Chandran Satish , Malhotra Nikhil , Palakodeti Ratnakar , Voleti Sreedhara R , Saxena Uday
Published: May 2021

Since 2019 the world has seen severe onslaught of SARS-CoV-2 viral pandemic. There is an urgent need for drugs that can be used to either prevent or treat the potentially fatal disease COVD-19. To this end, we screened FDA approved antiviral drugs which could be repurposed for COVID-19 through molecular docking approach in the various active sites of receptor binding domain (RBD). The RBD domain of SARS-CoV-2 spike protein is a promising drug target due to its pivotal role in viral-host attachment. Specifically, we focussed on identifying antiviral drugs which could a) block the entry of virus into host cells, b) demonstrate anti-inflammatory and/or anti-thrombogenic properties. Drugs which poses both properties could be useful for prevention and treatment of the disease. While we prioritized a few antiviral drugs based on molecular docking, corroboration within vitrostudies including a new 3D human vascular lung model strongly supported the potential ofHomoharringtonine, a drug approved for chronic myeloid leukaemia to be repurposed for COVID-19. This natural product drug not only antagonized the biding of SARS-CoV-2 spike protein RBD binding to human angiotensin receptor 2 (ACE-2) protein but also demonstrated for the first time anti-thrombogenic and anti-leukocyte adhesive properties in a human cell model system. Overall, this work provides an important lead for development of rapid treatment of COVID-19 and also establishes a screening paradigm using molecular modelling and 3D human vascular lung model of disease to identify drugs with multiple desirable properties for prevention and treatment of COVID-19.
Human organoid systems reveal in vitro correlates of fitness for SARS-CoV-2 B.1.1.7
Authors: Lamers Mart M. , Breugem Tim I. , Mykytyn Anna Z. , Wang Yiquan , Groen Nathalie , Knoops Kèvin , Schipper Debby , van der Vaart Jelte , Koopman Charlotte D. , Zhang Jingshu , Wu Douglas C. , van den Doel Petra B. , Bestebroer Theo , GeurtsvanKessel Corine H. , Peters Peter J. , Muraro Mauro J. , Clevers Hans , Wu Nicholas C. , Haagmans Bart L.
Published: May 2021

A new phase of the COVID-19 pandemic has started as several SARS-CoV-2 variants are rapidly emerging globally, raising concerns for increased transmissibility. As animal models and traditional in vitro systems may fail to model key aspects of the SARS-CoV-2 replication cycle, representative in vitro systems to assess variants phenotypically are urgently needed. We found that the British variant (clade B.1.1.7), compared to an ancestral SARS-CoV-2 clade B virus, produced higher levels of infectious virus late in infection and had a higher replicative fitness in human airway, alveolar and intestinal organoid models. Our findings unveil human organoids as powerful tools to phenotype viral variants and suggest extended shedding as a correlate of fitness for SARS-CoV-2.

One-Sentence Summary

British SARS-CoV-2 variant (clade B.1.1.7) infects organoids for extended time and has a higher fitness in vitro.
Context Free and Context-Dependent Conceptual Representation in the Brain
Authors: Gao Zhiyao , Zheng Li , Gouws André , Krieger-Redwood Katya , Wang Xiuyi , Varga Dominika , Smallwood Jonathan , Jefferies Elizabeth
Published: May 2021

How concepts are coded in the brain is a core issue in cognitive neuroscience. Studies have focused on how individual concepts are processed, but the way in which conceptual representation changes to suit the context is unclear. We parametrically manipulated the association strength between words, presented in pairs one word at a time using a slow event-related fMRI design. We combined representational similarity analysis and computational linguistics to probe the neurocomputational content of these trials. Individual word meaning was maintained in supramarginal gyrus (associated with verbal short-term memory) when items were judged to be unrelated, but not when a linking context was retrieved. Context-dependent meaning was instead represented in left lateral prefrontal gyrus (associated with controlled retrieval), angular gyrus and ventral temporal lobe (regions associated with integrative aspects of memory). Analyses of informational connectivity, examining the similarity of activation patterns across trials between sites, showed that control network regions had more similar multivariate responses across trials when association strength was weak, reflecting a common controlled retrieval state when the task required more unusual associations. These findings indicate that semantic control and representational sites amplify contextually-relevant meanings in trials judged to be related.
MLL4 is a critical mediator of differentiation and ferroptosis in the epidermis
Authors: Egolf Shaun , Zou Jonathan , Anderson Amy , Aubert Yann , Ge Kai , Seykora John T. , Capell Brian C.
Published: May 2021

The epigenetic regulator,MLL4(KMT2D), has been described as an essential gene in both humans and mice1,2. In addition, it is one of the most commonly mutated genes in all of cancer biology3–7. Here, we identify a critical role for Mll4 in the promotion of epidermal differentiation and ferroptosis, a key mechanism of tumor suppression8,9. Mice lacking epidermalMll4, but not the related enzymeMll3(Kmt2c), display features of impaired differentiation and human pre-cancerous neoplasms, including epidermal hyperplasia, atypical keratinocytes, and a loss of polarization, all of which progress with age. Mll4 deficiency profoundly alters epidermal gene expression, and uniquely rewires the expression of key genes and markers of ferroptosis (Alox12,Alox12b,Aloxe3)10. Beyond identifying a novel role forMll4-mediated tumor suppression in the skin, our data reveal a potentially much more broad and general role for ferroptosis in the process of epidermal differentiation and skin homeostasis.
Predicting Environmental Chemical Carcinogenicity using a Hybrid Machine-Learning Approach
Authors: Limbu Sarita , Dakshanamurthy Sivanesan
Published: May 2021

Determining environmental chemical carcinogenicity is an urgent need as humans are increasingly exposed to these chemicals. In this study, we determined the carcinogenicity of wide variety real-life exposure chemicals in large scale. To determine chemical carcinogenicity, we have developed carcinogenicity prediction models based on the hybrid neural network (HNN) architecture. In the HNN model, we included new SMILES feature representation method, by modifying our previous 3D array representation of 1D SMILES simulated by the convolutional neural network (CNN). We used 653 molecular descriptors modeled by feed forward neural network (FFNN), and SMILES as chemical features to train the models. We have developed three types of machine learning models: binary classification models to predict chemical is a carcinogenic or non-carcinogenic, multiclass classification models to predict severity of the chemical carcinogenicity, and regression models to predict median toxic dose of the chemicals. Along with the hybrid neural network (HNN) model that we developed, Random Forest (RF), Bootstrap Aggregating (Bagging) and Adaptive Boosting (AdaBoost) methods were also used for binary and multiclass classification. Regression models were developed using HNN, RF, Support Vector Regressor (SVR), Gradient Boosting (GB), Kernel Ridge (KR), Decision Tree with AdaBoost (DT), KNeighbors (KN), and a consensus method. For binary classification, our HNN model predicted with an average accuracy of 74.33% and an average AUC of 0.806, for multiclass classification, the HNN model predicted with an average accuracy of 50.58% and an average micro-AUC of 0.68, and for regression model, the consensus method achieved R2of 0.40. The predictive performance of our models based on a highly diverse chemicals is comparable to the literature reported models that included the similar and less diverse molecules. Our models can be used in identifying the potentially carcinogenic chemicals for a wide variety of chemical classes.
Digital 3D Brain MRI Arterial Territories Atlas
Authors: Liu Chin-Fu , Hsu Johnny , Xu Xin , Kim Ganghyun , Sheppard Shannon M. , Meier Erin L. , Miller Michael I. , Hillis Argye E. , Faria Andreia V.
Published: May 2021

The locus and extent of brain damage in the event of vascular insult can be quantitatively established quickly and easily with vascular atlases. Although highly anticipated by clinicians and clinical researchers, no digital MRI arterial atlas is readily available for automated data analyses. We created a digital arterial territory atlas based on lesion distributions in 1,298 patients with acute stroke. The lesions were manually traced in the diffusion-weighted MRIs, binary stroke masks were mapped to a common space, probability maps of lesions were generated and the boundaries for each arterial territory was defined based on the ratio between probabilistic maps. The atlas contains the definition of four major supra- and infra-tentorial arterial territories: Anterior, Middle, Posterior Cerebral Arteries and Vertebro-Basilar, and sub-territories (thalamoperforating, lenticulostriate, basilar and cerebellar arterial territories), in two hierarchical levels. This study provides the first publicly-available, digital, 3D deformable atlas of arterial brain territories, which may serve as a valuable resource for large-scale, reproducible processing and analysis of brain MRIs of patients with stroke and other conditions.
Gain control by sparse, ultra-slow glycinergic synapses
Authors: Jain Varsha , Hanson Laura , Sethuramanujam Santhosh , Gregg Ronald G. , Zhang Chi , Smith Robert G. , Berson David , McCall Maureen A. , Awatramani Gautam B.
Published: May 2021

Summary

Retinal ON starburst amacrine cells (SACs) play a critical role in computing stimulus direction, partly in service of image stabilization by optokinetic nystagmus. ON SAC responses are sculpted by rich GABAergic innervation, mostly from neighbouring SACs. Surprisingly, however, we find that glycinergic narrow field amacrine cells (NACs) serve as their dominant source of inhibition during sustained activity. Although NAC inputs constitute only ∼5% of inhibitory synapses to ON SACs, their distinct input patterns enable them to drive glycine inhibition during the both light increments and decrements. NAC-to-ON-SAC inhibition appears to be mediated by ultra-slow non-canonical glycine receptors containing the α4 subunit, which effectively summate during repetitive stimulation. Glycinergic inhibition strongly decreases the output gain of the SACs, ensuring that their direction-selective output is maintained over their operating range. These results reveal an unexpected role for glycinergic pathways and receptor kinetics in modulating direction selectivity in the retina.
Recovering mixtures of fast diffusing states from short single particle trajectories
Authors: Heckert Alec , Dahal Liza , Tjian Robert , Darzacq Xavier
Published: May 2021

Single particle tracking (SPT) directly measures the dynamics of proteins in living cells and is a powerful tool to dissect molecular mechanisms of cellular regulation. Interpretation of SPT with fast-diffusing proteins in mammalian cells, however, is complicated by technical limitations imposed by fast image acquisition. These limitations include short trajectory length due to photobleaching and shallow depth of field, high localization error due to the low photon budget imposed by short integration times, and cell-to-cell variability. To address these issues, we developed methods to infer distributions of diffusion coefficients from SPT data with short trajectories, variable localization accuracy, and absence of prior knowledge about the number of underlying states. We discuss advantages and disadvantages of these approaches relative to other frameworks for SPT analysis.

Significance statement

Single particle tracking (SPT) uses fluorescent probes to track the motions of individual molecules inside living cells, providing biologists with a close view of the cell’s inner machinery at work. Commonly used SPT imaging approaches, however, result in fragmentation of trajectories into small pieces as the probes move through the microscope’s plane of focus. This makes it challenging to extract usable biological information. This paper describes a method to reconstruct an SPT target’s dynamic profile from these trajectory fragments. The method builds on previous approaches to provide information about challenging SPT targets without discrete dynamic states while accounting for some known biases, enabling observation of previously hidden features in mammalian SPT experiments.
Benchmark of data processing methods and machine learning models for gut microbiome-based diagnosis of inflammatory bowel disease
Authors: Kubinski Ryszard , Djamen-Kepaou Jean-Yves , Zhanabaev Timur , Hernandez-Garcia Alex , Bauer Stefan , Hildebrand Falk , Korcsmaros Tamas , Karam Sani , Jantchou Prévost , Kafi Kamran , Martin Ryan D.
Published: May 2021

Background

Inflammatory bowel disease (IBD) patients wait months and undergo numerous invasive procedures between the initial appearance of symptoms and receiving a diagnosis. In order to reduce time until diagnosis and improve patient wellbeing, machine learning algorithms capable of diagnosing IBD from the gut microbiome’s composition are currently being explored. To date, these models have had limited clinical application due to decreased performance when applied to a new cohort of patient samples. Various methods have been developed to analyze microbiome data which may improve the generalizability of machine learning IBD diagnostic tests. With an abundance of methods, there is a need to benchmark the performance and generalizability of various machine learning pipelines (from data processing to training a machine learning model) for microbiome-based IBD diagnostic tools.

Results

We collected fifteen 16S rRNA microbiome datasets (7707 samples) from North America to benchmark combinations of gut microbiome features, data normalization methods, batch effect reduction methods, and machine learning models. Pipeline generalizability to new cohorts of patients was evaluated with four binary classification metrics following leave-one dataset-out cross validation, where all samples from one study were left out of the training set and tested upon. We demonstrate that taxonomic features obtained from QIIME2 lead to better classification of samples from IBD patients than inferred functional features obtained from PICRUSt2. In addition, machine learning models that identify non-linear decision boundaries between labels are more generalizable than those that are linearly constrained. Prior to training a non-linear machine learning model on taxonomic features, it is important to apply a compositional normalization method and remove batch effects with the naive zero-centering method. Lastly, we illustrate the importance of generating a curated training dataset to ensure similar performance across patient demographics.

Conclusions

These findings will help improve the generalizability of machine learning models as we move towards non-invasive diagnostic and disease management tools for patients with IBD.
Ablation ofmpeg+ macrophages exacerbatesmfrp-related hyperopia
Authors: Brandt Zachary J. , Collery Ross F , Besharse Joseph C , Link Brian A.
Published: May 2021

PURPOSE

Proper refractive development of the eye, termed emmetropization, is critical for focused vision and impacted by both genetic determinants and several visual environment factors. Improper emmetropization caused by genetic variants can lead to congenital hyperopia, which is characterized by small eyes and relatively short ocular axial length. To date variants in only four genes have been firmly associated with human hyperopia, one of which isMFRP. Zebrafishmfrpmutants also have hyperopia and similar to reports in mice, exhibit increased macrophage recruitment to the retina. The goal of this research was to examine the effects of macrophage ablation on emmetropization andmfrp-related hyperopia.

METHODS

We utilized a chemically inducible, cell-specific ablation system to deplete macrophages in both wild-type andmfrpmutant zebrafish. Spectral-domain optical coherence tomography (SD-OCT) was used to measure components of the eye and determine relative refractive state. Histology, immunohistochemistry, and transmission electron microscopy was used to further study the eyes.

RESULTS

While macrophage ablation does not cause significant changes to the relative refractive state of wild-type zebrafish, macrophage ablation inmfrpmutants significantly exacerbates their hyperopic phenotype.

CONCLUSIONS

Genetic inactivation ofmfrpleads to hyperopia as well as abnormal accumulation of macrophages in the retina. Ablation of the mpeg1-positive macrophage population exacerbates the hyperopia, suggesting that macrophages are recruited in an effort help preserve emmetropization and ameliorate hyperopia.
Accuratede novoidentification of biosynthetic gene clusters with GECCO
Authors: Carroll Laura M. , Larralde Martin , Fleck Jonas Simon , Ponnudurai Ruby , Milanese Alessio , Cappio Elisa , Zeller Georg
Published: May 2021

Biosynthetic gene clusters (BGCs) are enticing targets for (meta)genomic mining efforts, as they may encode novel, specialized metabolites with potential uses in medicine and biotechnology. Here, we describe GECCO (GEne Cluster prediction with COnditional random fields;https://gecco.embl.de), a high-precision, scalable method for identifying novel BGCs in (meta)genomic data using conditional random fields (CRFs). Based on an extensive evaluation ofde novoBGC prediction, we found GECCO to be more accurate and over 3x faster than a state-of-the-art deep learning approach. When applied to over 12,000 genomes, GECCO identified nearly twice as many BGCs compared to a rule-based approach, while achieving higher accuracy than other machine learning approaches. Introspection of the GECCO CRF revealed that its predictions rely on protein domains with both known and novel associations to secondary metabolism. The method developed here represents a scalable, interpretable machine learning approach, which can identify BGCsde novowith high precision.
Epigenetic Programming during thymic development sets the stage for optimal function in effector T cells via DNA demethylation
Authors: Teghanemt Athmane , Pulipati Priyanjali , Day Kenneth , Yorek Matt , Yi Ren , Misel-Wuchter Kara , Keen Henry L , Au Christy , Maretzky Thorsten , Gurung Prajwal , Littman Dan R. , Issuree Priya D.
Published: May 2021

The repressive effect of DNA methylation at promoters is well-known. However, its role within conserved sequences in intragenic and intergenic regions is less clear. UsingCd4as a model gene, here we show that DNA methylation regulates the function of stimulus-responsive regulatory elements in effector T cells. Twocis-elements orchestrate intra-and intergenic DNA demethylation of theCd4gene during thymic development, which in turn licenses a stimulus-responsive element, E4a, for its later function in effector cells. Deficiency in DNA demethylation leads to impaired E4a function, reduced H3K4me3 promoter levels and an inability to repelde novoDNA methylation during replication, ultimately leading to gene silencing. This physiological reduction in CD4 expression leads to a defect in Th1 polarization during cutaneous Leishmaniasis. Similar patterns of regulation were observed in a broad number of genes, highlighting an essential role for DNA demethylation during thymic development in modulating the function of stimulus-responsive elements.
Automation Assisted Anaerobic Phenotyping For Metabolic Engineering
Authors: Raj Kaushik , Venayak Naveen , Diep Patrick , Golla Sai Akhil , Yakunin Alexander F. , Mahadevan Radhakrishnan
Published: May 2021

Microorganisms can be metabolically engineered to produce a wide range of commercially important chemicals. Advancements in computational strategies for strain design and synthetic biological techniques to construct the designed strains have facilitated the generation of large libraries of potential candidates for chemical production. Consequently, there is a need for a high-throughput, laboratory scale techniques to characterize and screen these candidates to select strains for further investigation in large scale fermentation processes. Several small-scale fermentation techniques, in conjunction with laboratory automation have enhanced the throughput of enzyme and strain phenotyping experiments. However, such high throughput experimentation typically entails large operational costs and generate massive amounts of laboratory plastic waste. In this work, we develop an eco-friendly automation workflow that effectively calibrates and decontaminates fixed-tip liquid handling systems to reduce tip waste. We also investigate inexpensive methods to establish anaerobic conditions in microplates for high-throughput anaerobic phenotyping. To validate our phenotyping platform, we perform two case studies - an anaerobic enzyme screen, and a microbial phenotypic screen. We used our automation platform to investigate conditions under which several strains ofE. coliexhibit the same phenotypes in 0.5 L bioreactors and in our scaled-down fermentation platform. Further, we propose the use of dimensionality reduction through t-distributed stochastic neighbours embedding in conjunction with our phenotyping platform to serve as an effective scale-down model for bioreactor phenotypes. By integrating an in-house data-analysis pipeline, we were able to accelerate the ‘test’ phase of the design-build-test-learn cycle of metabolic engineering.
Semantic object-scene inconsistencies affect eye movements, but not in the way predicted by contextualized meaning maps
Authors: Pedziwiatr Marek A. , Kümmerer Matthias , Wallis Thomas S.A. , Bethge Matthias , Teufel Christoph
Published: May 2021

Semantic information is important in eye-movement control. An important semantic influence on gaze guidance relates to object-scene relationships: objects that are semantically inconsistent with the scene attract more fixations than consistent objects. One interpretation of this effect is that fixations are driven towards inconsistent objects because they are semantically more informative. We tested this explanation using contextualized meaning maps, a method that is based on crowd-sourced ratings to quantify the spatial distribution of context-sensitive ‘meaning’ in images. In Experiment 1, we compared gaze data and contextualized meaning maps for images, in which objects-scene consistency was manipulated. Observers fixated more on inconsistent vs. consistent objects. However, contextualized meaning maps did not assigned higher meaning to image regions that contained semantic inconsistencies. In Experiment 2, a large number of raters evaluated the meaningfulness of a set of carefully selected image-regions. The results suggest that the same scene locations were experienced as slightlylessmeaningful when they contained inconsistent compared to consistent objects. In summary, we demonstrated that – in the context of our rating task – semantically inconsistent objects are experienced as less meaningful than their consistent counterparts, and that contextualized meaning maps do not capture prototypical influences of image meaning on gaze guidance.