bluuebunny/crossref_metadata_2025 huggingface dataset:
psupertime: supervised pseudotime analysis for time-series single-cell RNA-seq data
Authors: Macnair Will , Gupta Revant , Claassen Manfred
Published: April 2022

Motivation

Improvements in single-cell RNA-seq technologies mean that studies measuring multiple experimental conditions, such as time series, have become more common. At present, few computational methods exist to infer time series-specific transcriptome changes, and such studies have therefore typically used unsupervised pseudotime methods. While these methods identify cell subpopulations and the transitions between them, they are not appropriate for identifying the genes that vary coherently along the time series. In addition, the orderings they estimate are based only on the major sources of variation in the data, which may not correspond to the processes related to the time labels.

Results

We introduce psupertime, a supervised pseudotime approach based on a regression model, which explicitly uses time-series labels as input. It identifies genes that vary coherently along a time series, in addition to pseudotime values for individual cells, and a classifier that can be used to estimate labels for new data with unknown or differing labels. We show that psupertime outperforms benchmark classifiers in terms of identifying time-varying genes and provides better individual cell orderings than popular unsupervised pseudotime techniques. psupertime is applicable to any single-cell RNA-seq dataset with sequential labels (e.g. principally time series but also drug dosage and disease progression), derived from either experimental design and provides a fast, interpretable tool for targeted identification of genes varying along with specific biological processes.

Availability and implementation

R package available at github.com/wmacnair/psupertime and code for results reproduction at github.com/wmacnair/psupplementary.

Supplementary information

Supplementary data are available at Bioinformatics online.
Characterizing domain-specific open educational resources by linking ISCB Communities of Special Interest to Wikipedia
Authors: Kilpatrick Alastair M , Rahman Farzana , Anjum Audra , Shome Sayane , Andalib K M Salim , Banik Shrabonti , Chowdhury Sanjana F , Coombe Peter , Astroz Yesid Cuesta , Douglas J Maxwell , Eranti Pradeep , Kiran Aleyna D , Kumar Sachendra , Lim Hyeri , Lorenzi Valentina , Lubiana Tiago , Mahmud Sakib , Puche Rafael , Rybarczyk Agnieszka , Al Sium Syed Muktadir , Twesigomwe David , Zok Tomasz , Orengo Christine A , Friedberg Iddo , Kelso Janet F , Welch Lonnie
Published: April 2022

Motivation

Wikipedia is one of the most important channels for the public communication of science and is frequently accessed as an educational resource in computational biology. Joint efforts between the International Society for Computational Biology (ISCB) and the Computational Biology taskforce of WikiProject Molecular Biology (a group of expert Wikipedia editors) have considerably improved computational biology representation on Wikipedia in recent years. However, there is still an urgent need for further improvement in quality, especially when compared to related scientific fields such as genetics and medicine. Facilitating involvement of members from ISCB Communities of Special Interest (COSIs) would improve a vital open education resource in computational biology, additionally allowing COSIs to provide a quality educational resource highly specific to their subfield.

Results

We generate a list of around 1500 English Wikipedia articles relating to computational biology and describe the development of a binary COSI-Article matrix, linking COSIs to relevant articles and thereby defining domain-specific open educational resources. Our analysis of the COSI-Article matrix data provides a quantitative assessment of computational biology representation on Wikipedia against other fields and at a COSI-specific level. Furthermore, we conducted similarity analysis and subsequent clustering of COSI-Article data to provide insight into potential relationships between COSIs. Finally, based on our analysis, we suggest courses of action to improve the quality of computational biology representation on Wikipedia.
CMash: fast, multi-resolution estimation of k-mer-based Jaccard and containment indices
Authors: Liu Shaopeng , Koslicki David
Published: April 2022

Motivation

K-mer-based methods are used ubiquitously in the field of computational biology. However, determining the optimal value of k for a specific application often remains heuristic. Simply reconstructing a new k-mer set with another k-mer size is computationally expensive, especially in metagenomic analysis where datasets are large. Here, we introduce a hashing-based technique that leverages a kind of bottom-m sketch as well as a k-mer ternary search tree (KTST) to obtain k-mer-based similarity estimates for a range of k values. By truncating k-mers stored in a pre-built KTST with a large k=kmax value, we can simultaneously obtain k-mer-based estimates for all k values up to kmax. This truncation approach circumvents the reconstruction of new k-mer sets when changing k values, making analysis more time and space-efficient.

Results

We derived the theoretical expression of the bias factor due to truncation. And we showed that the biases are negligible in practice: when using a KTST to estimate the containment index between a RefSeq-based microbial reference database and simulated metagenome data for 10 values of k, the running time was close to 10× faster compared to a classic MinHash approach while using less than one-fifth the space to store the data structure.

Availability and implementation

A python implementation of this method, CMash, is available at https://github.com/dkoslicki/CMash. The reproduction of all experiments presented herein can be accessed via https://github.com/KoslickiLab/CMASH-reproducibles.

Supplementary information

Supplementary data are available at Bioinformatics online.
Fast and interpretable genomic data analysis using multiple approximate kernel learning
Authors: Bektaş Ayyüce Begüm , Ak Çiğdem , Gönen Mehmet
Published: April 2022

Motivation

Dataset sizes in computational biology have been increased drastically with the help of improved data collection tools and increasing size of patient cohorts. Previous kernel-based machine learning algorithms proposed for increased interpretability started to fail with large sample sizes, owing to their lack of scalability. To overcome this problem, we proposed a fast and efficient multiple kernel learning (MKL) algorithm to be particularly used with large-scale data that integrates kernel approximation and group Lasso formulations into a conjoint model. Our method extracts significant and meaningful information from the genomic data while conjointly learning a model for out-of-sample prediction. It is scalable with increasing sample size by approximating instead of calculating distinct kernel matrices.

Results

To test our computational framework, namely, Multiple Approximate Kernel Learning (MAKL), we demonstrated our experiments on three cancer datasets and showed that MAKL is capable to outperform the baseline algorithm while using only a small fraction of the input features. We also reported selection frequencies of approximated kernel matrices associated with feature subsets (i.e. gene sets/pathways), which helps to see their relevance for the given classification task. Our fast and interpretable MKL algorithm producing sparse solutions is promising for computational biology applications considering its scalability and highly correlated structure of genomic datasets, and it can be used to discover new biomarkers and new therapeutic guidelines.

Availability and implementation

MAKL is available at https://github.com/begumbektas/makl together with the scripts that replicate the reported experiments. MAKL is also available as an R package at https://cran.r-project.org/web/packages/MAKL.

Supplementary information

Supplementary data are available at Bioinformatics online.
The minimizer Jaccard estimator is biased and inconsistent
Authors: Belbasi Mahdi , Blanca Antonio , Harris Robert S , Koslicki David , Medvedev Paul
Published: April 2022

Motivation

Sketching is now widely used in bioinformatics to reduce data size and increase data processing speed. Sketching approaches entice with improved scalability but also carry the danger of decreased accuracy and added bias. In this article, we investigate the minimizer sketch and its use to estimate the Jaccard similarity between two sequences.

Results

We show that the minimizer Jaccard estimator is biased and inconsistent, which means that the expected difference (i.e. the bias) between the estimator and the true value is not zero, even in the limit as the lengths of the sequences grow. We derive an analytical formula for the bias as a function of how the shared k-mers are laid out along the sequences. We show both theoretically and empirically that there are families of sequences where the bias can be substantial (e.g. the true Jaccard can be more than double the estimate). Finally, we demonstrate that this bias affects the accuracy of the widely used mashmap read mapping tool.

Availability and implementation

Scripts to reproduce our experiments are available at https://github.com/medvedevgroup/minimizer-jaccard-estimator/tree/main/reproduce.

Supplementary information

Supplementary data are available at Bioinformatics online.
Sparse and skew hashing of K-mers
Authors: Pibiri Giulio Ermanno
Published: April 2022

Motivation

A dictionary of k-mers is a data structure that stores a set of n distinct k-mers and supports membership queries. This data structure is at the hearth of many important tasks in computational biology. High-throughput sequencing of DNA can produce very large k-mer sets, in the size of billions of strings—in such cases, the memory consumption and query efficiency of the data structure is a concrete challenge.

Results

To tackle this problem, we describe a compressed and associative dictionary for k-mers, that is: a data structure where strings are represented in compact form and each of them is associated to a unique integer identifier in the range [0,n). We show that some statistical properties of k-mer minimizers can be exploited by minimal perfect hashing to substantially improve the space/time trade-off of the dictionary compared to the best-known solutions.

Availability and implementation

https://github.com/jermp/sshash.

Supplementary information

Supplementary data are available at Bioinformatics online.
Topsy-Turvy: integrating a global view into sequence-based PPI prediction
Authors: Singh Rohit , Devkota Kapil , Sledzieski Samuel , Berger Bonnie , Cowen Lenore
Published: April 2022

Computational methods to predict protein–protein interaction (PPI) typically segregate into sequence-based ‘bottom-up’ methods that infer properties from the characteristics of the individual protein sequences, or global ‘top-down’ methods that infer properties from the pattern of already known PPIs in the species of interest. However, a way to incorporate top-down insights into sequence-based bottom-up PPI prediction methods has been elusive. We thus introduce Topsy-Turvy, a method that newly synthesizes both views in a sequence-based, multi-scale, deep-learning model for PPI prediction. While Topsy-Turvy makes predictions using only sequence data, during the training phase it takes a transfer-learning approach by incorporating patterns from both global and molecular-level views of protein interaction. In a cross-species context, we show it achieves state-of-the-art performance, offering the ability to perform genome-scale, interpretable PPI prediction for non-model organisms with no existing experimental PPI data. In species with available experimental PPI data, we further present a Topsy-Turvy hybrid (TT-Hybrid) model which integrates Topsy-Turvy with a purely network-based model for link prediction that provides information about species-specific network rewiring. TT-Hybrid makes accurate predictions for both well- and sparsely-characterized proteins, outperforming both its constituent components as well as other state-of-the-art PPI prediction methods. Furthermore, running Topsy-Turvy and TT-Hybrid screens is feasible for whole genomes, and thus these methods scale to settings where other methods (e.g. AlphaFold-Multimer) might be infeasible. The generalizability, accuracy and genome-level scalability of Topsy-Turvy and TT-Hybrid unlocks a more comprehensive map of protein interaction and organization in both model and non-model organisms.

Availability and implementation

https://topsyturvy.csail.mit.edu.

Supplementary information

Supplementary data are available at Bioinformatics online.
Deep kernel learning improves molecular fingerprint prediction from tandem mass spectra
Authors: Dührkop Kai
Published: April 2022

Motivation

Untargeted metabolomics experiments rely on spectral libraries for structure annotation, but these libraries are vastly incomplete; in silico methods search in structure databases, allowing us to overcome this limitation. The best-performing in silico methods use machine learning to predict a molecular fingerprint from tandem mass spectra, then use the predicted fingerprint to search in a molecular structure database. Predicted molecular fingerprints are also of great interest for compound class annotation, de novo structure elucidation, and other tasks. So far, kernel support vector machines are the best tool for fingerprint prediction. However, they cannot be trained on all publicly available reference spectra because their training time scales cubically with the number of training data.

Results

We use the Nyström approximation to transform the kernel into a linear feature map. We evaluate two methods that use this feature map as input: a linear support vector machine and a deep neural network (DNN). For evaluation, we use a cross-validated dataset of 156 017 compounds and three independent datasets with 1734 compounds. We show that the combination of kernel method and DNN outperforms the kernel support vector machine, which is the current gold standard, as well as a DNN on tandem mass spectra on all evaluation datasets.

Availability and implementation

The deep kernel learning method for fingerprint prediction is part of the SIRIUS software, available at https://bio.informatik.uni-jena.de/software/sirius.
Self-supervised learning of cell type specificity from immunohistochemical images
Authors: Murphy Michael , Jegelka Stefanie , Fraenkel Ernest
Published: April 2022

Motivation

Advances in bioimaging now permit in situ proteomic characterization of cell–cell interactions in complex tissues, with important applications across a spectrum of biological problems from development to disease. These methods depend on selection of antibodies targeting proteins that are expressed specifically in particular cell types. Candidate marker proteins are often identified from single-cell transcriptomic data, with variable rates of success, in part due to divergence between expression levels of proteins and the genes that encode them. In principle, marker identification could be improved by using existing databases of immunohistochemistry for thousands of antibodies in human tissue, such as the Human Protein Atlas. However, these data lack detailed annotations of the types of cells in each image.

Results

We develop a method to predict cell type specificity of protein markers from unlabeled images. We train a convolutional neural network with a self-supervised objective to generate embeddings of the images. Using non-linear dimensionality reduction, we observe that the model clusters images according to cell types and anatomical regions for which the stained proteins are specific. We then use estimates of cell type specificity derived from an independent single-cell transcriptomics dataset to train an image classifier, without requiring any human labelling of images. Our scheme demonstrates superior classification of known proteomic markers in kidney compared to selection via single-cell transcriptomics.

Availability and implementation

Code and trained model are available at www.github.com/murphy17/HPA-SimCLR.

Supplementary information

Supplementary data are available at Bioinformatics online.
spicyR: spatial analysis ofin situcytometry data in R
Authors: Canete Nicolas P , Iyengar Sourish S , Ormerod John T , Baharlou Heeva , Harman Andrew N , Patrick Ellis
Published: April 2022

Motivation

High parameter histological techniques have allowed for the identification of a variety of distinct cell types within an image, providing a comprehensive overview of the tissue environment. This allows the complex cellular architecture and environment of diseased tissue to be explored. While spatial analysis techniques have revealed how cell–cell interactions are important within the disease pathology, there remains a gap in exploring changes in these interactions within the disease process. Specifically, there are currently few established methods for performing inference on cell-type co-localization changes across images, hindering an understanding of how cellular environments change with a disease pathology.

Results

We have developed the spicyR R package to perform inference on changes in the spatial co-localization of types across groups of images. Application to simulated data demonstrates a high sensitivity and specificity. We the utility of spicyR by applying it to a type 1 diabetes imaging mass cytometry dataset, revealing changes in cellular associations that were relevant to the disease progression. Ultimately, spicyR allows changes in cellular environments to be explored under different pathologies or disease states.

Availability and implementation

R package is freely available at http://bioconductor.org/packages/release/bioc/html/spicyR.html and shiny app implementation at http://shiny.maths.usyd.edu.au/spicyR/.

Supplementary information

Supplementary data are available at Bioinformatics online.
PltDB: a blood platelets-based gene expression database for disease investigation
Authors: Zou Danyi , Yuan Ye , Xu Luming , Lei Shijun , Li Xingbo , Lu Xiaohuan , Wang Xingyue , Li XiaoQiong , Wang Lin , Wang Zheng
Published: April 2022

Motivation

Molecular profiling of blood-based liquid biopsies is a promising disease detection method, which overcomes the limitations of invasive diagnostic strategies. Recently, gene expression profiling of platelets reportedly provides valuable resource for developing new biomarkers for the detection of diseases, including cancer. However, there is no database containing RNAs in platelets.

Results

In this study, we constructed PltDB (http://www.pltdb-hust.com), a blood platelets-based gene expression database featuring integration and visualization of RNA expression profiles based on RNA-seq and microarray data spanning both normal individuals and patients with different diseases. PltDB currently contains the expression landscape of mRNAs, lncRNAs, circRNAs and miRNAs in platelets from patients with different disease types and healthy controls. Moreover, PltDB provides users with the tools for visualizing results of comparison and correlation analysis and for downloading expression profiles and analysis results. A submission interface for the scientific community is also embraced for uploading novel RNA expression profiles derived from platelet samples. PltDB will offer a comprehensive review of the clinical use of platelets, overcome technical problems when analyzing data from diverse studies and serve as a powerful platform for developing new blood biomarkers.

Availability and implementation

PltDB is accessible at http://www.pltdb-hust.com.

Supplementary information

Supplementary data are available at Bioinformatics online.
Taenia saginata: unexpected finding during laparoscopic Roux-en-Y gastric bypass
Authors: Ferrer-Inaebnit Ester , Metzger Alejandro , Naef Markus , Fringeli Yannick
Published: April 2022

Laparoscopic finding showing a tapeworm in the intestinal lumen during the creation of the jejuno-jejunal anastomosis.
Freedom in Chains? Religious Freedom Rights in an International Frame: Addressing the Increasing Intolerance and Violence Directed Toward People of Faith
Authors: Hodge David R
Published: April 2022

Violations of religious freedom rights are accelerating across the globe, with levels of religious harassment reaching record levels. Yet, despite social work’s commitment to challenging religious discrimination and promoting human rights, little, if any, attention has focused on this issue in the profession’s literature. In keeping with calls from the United Nations, this article highlights a human rights concern of critical importance to many vulnerable people, namely those who experience acts of intolerance, hate and violence for peacefully practicing the tenets of their faith. Accordingly, the parameters of religious freedom are delineated along with the status of religious freedom rights in the world, in conjunction with the populations that experience particularly extensive discrimination. After discussing the systemic factors that legitimise discrimination against people of faith, strategies are offered that social workers might implement to promote more equitable and socially just societies.
Disclosure of Child Sexual Abuse: Experiences of Men Survivors in India
Authors: Sharma Alankaar
Published: April 2022

Little is known about men and boys’ experiences of child sexual abuse (CSA) in India, particularly about their experiences of disclosing abuse. Disclosure experiences are often important as they can potentially make the path to recovery and healing more tractable or challenging for survivors. Using the Interpretative Phenomenological Analysis approach, in-depth qualitative interviews were conducted with eleven adult men survivors of CSA in India varying in age, location and sexual orientation, to learn about their experiences of disclosing abuse. Barriers to disclosure included guilt, shame, protecting the perpetrator, protecting others from emotional stress and pain, stigma about same-sex sexual activity, and fear of minimisation of abuse experiences. Disclosure was further inhibited by pervasive silence in society about sexuality and sexual abuse. Responses to disclosure were varied and included supportive responses, silence and victim blaming. Findings demonstrate that disclosure experiences of men survivors were strongly influenced by patriarchal and heteronormative norms and practices. Social work has a role to play in building awareness of sexual abuse of boys, helping create a social environment where survivors can feel safe about disclosing abuse, and challenging the oppressive structures of patriarchy and heteronormativity.
(Re-)Imagining Social Work in the Anthropocene
Authors: Panagiotaros Chris Victor , Boddy Jennifer , Gray Tonia , Ife Jim
Published: April 2022

The ecological crisis, marked by the Anthropocene epoch, is having a major impact on the global ecosystem, and the consequences are predicted to become increasingly severe in coming decades. The turbulence and uncertainty of the crisis means social work must begin planning, reflecting and reorientating. The first half of the article contextualises the climate crisis within neoliberal capitalism, whereas the second half proposes alternatives for social work practice that attempt to exist outside these structures. We have argued that social work should have a greater focus on developing an eco-social transition which means engaging with alternative economic systems, intentional communities, community gardens and localism. These approaches can practically espouse the profession’s values whilst beginning to conceptualise a response to the climate crisis that operates outside neoliberal capitalism.
The anatomy of melancholy revisited after 400 years
Authors: Larner A J
Published: April 2022

First published over 400 years ago, this new edition of Robert Burton's The Anatomy of Melancholy still has the capacity to engage and edify readers in ways which may impact on their clinical practice.
Differential gene expression between callosal and ipsilateral projection neurons in the monkey dorsolateral prefrontal and posterior parietal cortices
Authors: Arion Dominique , Enwright John F , Gonzalez-Burgos Guillermo , Lewis David A
Published: April 2022

Reciprocal connections between primate dorsolateral prefrontal (DLPFC) and posterior parietal (PPC) cortices, furnished by subsets of layer 3 pyramidal neurons (PNs), contribute to cognitive processes including working memory (WM). A different subset of layer 3 PNs in each region projects to the homotopic region of the contralateral hemisphere. These ipsilateral (IP) and callosal (CP) projections, respectively, appear to be essential for the maintenance and transfer of information during WM. To determine if IP and CP layer 3 PNs in each region differ in their transcriptomes, fluorescent retrograde tracers were used to label IP and CP layer 3 PNs in the DLPFC and PPC from macaque monkeys. Retrogradely-labeled PNs were captured by laser microdissection and analyzed by RNAseq. Numerous differentially expressed genes (DEGs) were detected between IP and CP neurons in each region and the functional pathways containing many of these DEGs were shared across regions. However, DLPFC and PPC displayed opposite patterns of DEG enrichment between IP and CP neurons. Cross-region analyses indicated that the cortical area targeted by IP or CP layer 3 PNs was a strong correlate of their transcriptome profile. These findings suggest that the transcriptomes of layer 3 PNs reflect regional, projection type and target region specificity.
The hyper-brain neural couplings distinguishing high-creative group dynamics: an fNIRS hyperscanning study
Authors: Lu Kelong , Gao Zhenni , Wang Xinyue , Qiao Xinuo , He Yingyao , Zhang Yu , Hao Ning
Published: April 2022

This hyperscanning study aimed to identify a neural coupling profile that distinguishes high-creative group dynamics through functional near infrared spectroscopy. A total of 123 dyads completed one creativity task (alternative uses task, AUT) and contrast task (objective characteristics task). A K-means clustering analysis on AUT performance grouped 31/29 dyads into high/low-creative group, respectively. In comparison with the low-creative group, the high-creative group showed: (i) higher collective flexibility and delayed perspective-taking behaviors, but lower immediate perspective-taking behaviors; (ii) enhanced interpersonal brain synchronization (IBS) between the left inferior frontal gyrus (lIFG) and right motor cortex, and nodal Eloc at the right superior temporal gyrus (rSTG); (iii) declined intrapersonal functional connectivity between the right angular gyrus (rAG) and rSTG, and IBS between the lIFG and rAG. The enhanced neural couplings positively correlated with group creative performance, whereas a reverse correlation pattern existed in the declined ones. A leave-one-out cross-validation analysis showed these neural couplings reliably predicted group creative performance within the sample. These indicate that high-creative group dynamics are characterized by utilizing partners’ shared information when necessary (e.g. encountering idea exhaustion). A neural coupling profile consisting of sophisticated interplays between regions within frontal, temporal, and parietal lobes may underlie high-creative creative dynamics.
How distinct functional insular subdivisions mediate interacting neurocognitive systems
Authors: Zhao Haichao , Turel Ofir , Bechara Antoine , He Qinghua
Published: April 2022

Recent neurocognitive models propose that the insula serves as a hub of interoceptive awareness system, modulating 2 interplaying neurocognitive systems: The posterior insula (PI) receives and integrates various interoceptive signals; these signals are then transmitted to the anterior insula for processing higher-order representations into awareness, where the dorsal anterior insula (dAI) modulates the prefrontal self-control system and the ventral anterior insula (vAI) modulates the amygdala (AMG)-striatal reward-seeking circuit. We sought to test this view using a multimodal approach. We first used a resting-state functional magnetic resonance imaging (fMRI) approach with a sample of 120 undergraduate students. Then, we unpacked the neuro-cognitive association between insular connectivity and cognitive performance during an Iowa gambling fMRI task. Lastly, an independent Open Southwest University Longitudinal Imaging Multimodal dataset was used to validate the results. Findings suggested that the dAI was predominantly connected to the prefrontal regions; the vAI was primarily connected to the AMG–ventral–striatum system; and the PI was mainly connected to the visceral-sensorimotor system. Moreover, cognitive scores were positively correlated with FC between dAI and the self-control process of ventrolateral prefrontal cortex and were negatively correlated with FC between vAI and the reward-seeking process of orbitofrontal cortex and subgenual anterior cingulate cortex. The findings highlight the roles of our theorized subinsular functionality in the overall operation of the neural cognitive systems.
Neural evidence for age-related deficits in the representation of state spaces
Authors: Ruel Alexa , Bolenz Florian , Li Shu-Chen , Fischer Adrian , Eppinger Ben
Published: April 2022

Under high cognitive demands, older adults tend to resort to simpler, habitual, or model-free decision strategies. This age-related shift in decision behavior has been attributed to deficits in the representation of the cognitive maps, or state spaces, necessary for more complex model-based decision-making. Yet, the neural mechanisms behind this shift remain unclear. In this study, we used a modified 2-stage Markov task in combination with computational modeling and single-trial EEG analyses to establish neural markers of age-related changes in goal-directed decision-making under different demands on the representation of state spaces. Our results reveal that the shift to simpler decision strategies in older adults is due to (i) impairments in the representation of the transition structure of the task and (ii) a diminished signaling of the reward value associated with decision options. In line with the diminished state space hypothesis of human aging, our findings suggest that deficits in goal-directed, model-based behavior in older adults result from impairments in the representation of state spaces of cognitive tasks.
Infectious Diseases Society of America 2022 Guidance on the Treatment of Extended-Spectrum β-lactamase Producing Enterobacterales (ESBL-E), Carbapenem-Resistant Enterobacterales (CRE), and Pseudomonas aeruginosa with Difficult-to-Treat Resistance (DTR-P. aeruginosa)
Authors: Tamma Pranita D , Aitken Samuel L , Bonomo Robert A , Mathers Amy J , van Duin David , Clancy Cornelius J
Published: April 2022

Background

The Infectious Diseases Society of America (IDSA) is committed to providing up-to-date guidance on the treatment of antimicrobial-resistant infections. The initial guidance document on infections caused by extended-spectrum β-lactamase producing Enterobacterales (ESBL-E), carbapenem-resistant Enterobacterales (CRE), and Pseudomonas aeruginosa with difficult-to-treat resistance (DTR-P. aeruginosa) was published on 17 September 2020. Over the past year, there have been a number of important publications furthering our understanding of the management of ESBL-E, CRE, and DTR-P. aeruginosa infections, prompting a rereview of the literature and this updated guidance document.

Methods

A panel of 6 infectious diseases specialists with expertise in managing antimicrobial-resistant infections reviewed, updated, and expanded previously developed questions and recommendations about the treatment of ESBL-E, CRE, and DTR-P. aeruginosa infections. Because of differences in the epidemiology of resistance and availability of specific anti-infectives internationally, this document focuses on the treatment of infections in the United States.

Results

Preferred and alternative treatment recommendations are provided with accompanying rationales, assuming the causative organism has been identified and antibiotic susceptibility results are known. Approaches to empiric treatment, duration of therapy, and other management considerations are also discussed briefly. Recommendations apply for both adult and pediatric populations.

Conclusions

The field of antimicrobial resistance is highly dynamic. Consultation with an infectious diseases specialist is recommended for the treatment of antimicrobial-resistant infections. This document is current as of 24 October 2021. The most current versions of IDSA documents, including dates of publication, are available at www.idsociety.org/practice-guideline/amr-guidance/.
High Rate of Hepatitis C Virus Reinfection Among Recently Injecting Drug Users: Results From the TraP Hep C Program—A Prospective Nationwide, Population-Based Study
Authors: Johannesson Jon M , Fridriksdottir Ragnheidur H , Löve Thorvardur J , Runarsdottir Valgerdur , Hansdóttir Ingunn , Löve Arthur , Thordardottir Marianna , Hernandez Ubaldo B , Olafsson Sigurdur , Gottfredsson Magnus ,   Treatment as Prevention for Hepatitis C (TraP Hep C) group, Bjornsson Einar Stefan , Bergmann Ottar Mar , Sigurdardottir Bryndis , Johannsson Birgir , Heimisdottir Maria , Tyrfingsson Thorarinn , Tomasdottir Anna , Karlsdottir Bergthora , Ingibergsdottir Bjartey , Fridjonsdottir Hildigunnur , Alexiusdottir Kristin , Bjornsdottir Thora , Olafsdottir Bryndis , Finnbogadottir Asdis M
Published: April 2022

Background

The Treatment as Prevention for Hepatitis C program started in 2016 in Iceland, offering treatment with direct-acting antivirals to hepatitis C virus (HCV)-infected individuals. Reinfections through injection drug use (IDU) can hamper elimination efforts. We determined reinfection rates of HCV among patients in the program.

Methods

Clinical data were gathered prospectively. The study cohort consisted of HCV-cured patients with an estimated sustained virologic response between 1 February 2016 and 20 November 2018, with follow-up until 20 November 2019. The observation period and time until reinfection was estimated using a single random point imputation method coupled with Monte Carlo simulation. The reinfection rates were expressed as reinfections per 100 person-years (PY).

Results

In total, 640 treatments of 614 patients (417 male; mean age, 44.3 years) resulted in cure, with 52 reinfections subsequently confirmed in 50 patients (37 male). Follow-up was 672.1 PY, with a median time to reinfection of 232 days. History of IDU was reported by 523 patients (84.8%) and recent IDU with 220 treatments (34.4%). Stimulants were the preferred injected drug in 85.5% of patients with a history of IDU. The reinfection rate was 7.7/100 PY. Using multivariate Cox proportional hazards models for interval-censored data, age (hazard ratio, 0.96 [95% confidence interval, .94–.99]) and recent IDU (2.91 [1.48–5.76]) were significantly associated with reinfection risk.

Conclusions

The reinfection rate is high in a setting of widespread stimulant use, particularly in young people with recent IDU. Regular follow-up is important among high-risk populations to diagnose reinfections early and reduce transmission.

Clinical Trials Registration

NCT02647879.
Vaccination of Ukrainian Refugees: Need for Urgent Action
Authors: Rzymski Piotr , Falfushynska Halina , Fal Andrzej
Published: April 2022

The unprovoked aggression of Russian military forces on Ukraine in February 2022 has caused a high influx of refugees, including children, to neighboring countries, particularly Poland. This caused additional pressures on the healthcare system and the need to meet challenges for public health, such as those related to infectious diseases. Here, we discuss the potential epidemiological risks associated with the war-induced influx of refugees (coronavirus disease 2019, measles, pertussis, tetanus, and poliomyelitis) and highlight the need for their swift management through institutional support, educational campaigns, counteracting antiscience misinformation, and pursuing vaccinations of refugees but also improving or maintaining good levels of immunization in populations of countries welcoming them. These are necessary actions to avoid overlapping of war and infectious diseases and associated public health challenges.
Anal Human Papillomavirus Infection in Kidney Transplant Recipients Compared With Immunocompetent Controls
Authors: Larsen Helle Kiellberg , Kjaer Susanne K , Haedersdal Merete , Kjaer Alexander K , Bonde Jesper Hansen , Sørensen Søren Schwartz , Thomsen Louise T
Published: April 2022

Background

Kidney transplant recipients (KTRs) have increased risk of human papillomavirus (HPV)–related anogenital (pre)cancers, including anal high-grade intraepithelial lesions and cancer. Previous studies on anal high-risk HPV (hrHPV) among KTRs are sparse.

Methods

In a cross-sectional study, we included 247 KTRs and 248 controls from a dermatology department and 5 nephrology departments in Denmark during 2016–2017. All participants provided an anal cytobrush sample that was tested for HPV DNA. Participants completed a questionnaire on lifestyle and sexual habits. We used logistic regression to estimate odds ratios (ORs) of anal hrHPV in KTRs compared with controls and risk factors for anal hrHPV in KTRs.

Results

The anal hrHPV prevalence was higher in female KTRs (45.5%) than in controls (27.2%). Female KTRs had almost 3-fold higher adjusted odds of anal hrHPV than controls (adjusted OR, 2.87 [95% confidence interval, 1.57–5.22]). In contrast, among men we did not observe increased prevalence or odds of anal hrHPV in KTRs compared with controls (prevalence, 19.4% vs 23.6%; adjusted OR, 0.85 [95% 95% confidence interval, .44–1.64]). Among hrHPV-positive KTRs, 63% and 52% of men and women, respectively, were infected with hrHPV types covered by the nonavalent HPV vaccine (type 16, 18, 31, 33, 45, 52, or 58). Current smoking, >10 lifetime sexual partners, history of genital warts, and among men having had receptive anal sex were risk factors for anal hrHPV in KTRs.

Conclusions

Female KTRs had an increased risk of anal hrHPV compared with immunocompetent controls. Our findings indicate that pretransplant HPV vaccination should be considered to prevent anal high-grade intraepithelial lesions and cancer caused by anal hrHPV infection in KTRs.

Clinical Trials Registration

NCT03018327.
Two-Dose Severe Acute Respiratory Syndrome Coronavirus 2 Vaccine Effectiveness With Mixed Schedules and Extended Dosing Intervals: Test-Negative Design Studies From British Columbia and Quebec, Canada
Authors: Skowronski Danuta M , Febriani Yossi , Ouakki Manale , Setayeshgar Solmaz , El Adam Shiraz , Zou Macy , Talbot Denis , Prystajecky Natalie , Tyson John R , Gilca Rodica , Brousseau Nicholas , Deceuninck Geneviève , Galanis Eleni , Fjell Chris D , Sbihi Hind , Fortin Elise , Barkati Sapha , Sauvageau Chantal , Naus Monika , Patrick David M , Henry Bonnie , Hoang Linda M N , De Wals Philippe , Garenc Christophe , Carignan Alex , Drolet Mélanie , Jassem Agatha N , Sadarangani Manish , Brisson Marc , Krajden Mel , De Serres Gaston
Published: April 2022

Background

The Canadian coronavirus disease 2019 (COVID-19) immunization strategy deferred second doses and allowed mixed schedules. We compared 2-dose vaccine effectiveness (VE) by vaccine type (mRNA and/or ChAdOx1), interval between doses, and time since second dose in 2 of Canada’s larger provinces.

Methods

Two-dose VE against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection or hospitalization among adults ≥18 years, including due to Alpha, Gamma, and Delta variants of concern (VOCs), was assessed ≥14 days postvaccination by test-negative design studies separately conducted in British Columbia and Quebec, Canada, between 30 May and 27 November (epi-weeks 22–47) 2021.

Results

In both provinces, all homologous or heterologous mRNA and/or ChAdOx1 2-dose schedules were associated with ≥90% reduction in SARS-CoV-2 hospitalization risk for ≥7 months. With slight decline from a peak of >90%, VE against infection was ≥80% for ≥6 months following homologous mRNA vaccination, lower by ∼10% when both doses were ChAdOx1 but comparably high following heterologous ChAdOx1 + mRNA receipt. Findings were similar by age group, sex, and VOC. VE was significantly higher with longer 7–8-week versus manufacturer-specified 3–4-week intervals between mRNA doses.

Conclusions

Two doses of any mRNA and/or ChAdOx1 combination gave substantial and sustained protection against SARS-CoV-2 hospitalization, spanning Delta-dominant circulation. ChAdOx1 VE against infection was improved by heterologous mRNA series completion. A 7–8-week interval between first and second doses improved mRNA VE and may be the optimal schedule outside periods of intense epidemic surge. Findings support interchangeability and extended intervals between SARS-CoV-2 vaccine doses, with potential global implications for low-coverage areas and, going forward, for children.
Epidemiology, Clinical Characteristics, and Outcomes of Influenza-Associated Hospitalizations in US Children Over 9 Seasons Following the 2009 H1N1 Pandemic
Authors: Kamidani Satoshi , Garg Shikha , Rolfes Melissa A , Campbell Angela P , Cummings Charisse N , Haston Julia C , Openo Kyle P , Fawcett Emily , Chai Shua J , Herlihy Rachel , Yousey-Hindes Kimberly , Monroe Maya L , Kim Sue , Lynfield Ruth , Smelser Chad , Muse Alison , Felsen Christina B , Billing Laurie , Thomas Ann , Talbot H Keipp , Schaffner William , Risk Ilene , Anderson Evan J
Published: April 2022

Background

Recent population-based data are limited regarding influenza-associated hospitalizations in US children.

Methods

We identified children <18 years hospitalized with laboratory-confirmed influenza during 2010–2019 seasons, through the Centers for Disease Control and Prevention’s Influenza Hospitalization Surveillance Network. Adjusted hospitalization and in-hospital mortality rates were calculated, and multivariable logistic regression was conducted to evaluate risk factors for pneumonia, intensive care unit (ICU) admission, mechanical ventilation, and death.

Results

Over 9 seasons, adjusted influenza-associated hospitalization incidence rates ranged from 10 to 375 per 100 000 persons each season and were highest among infants <6 months old. Rates decreased with increasing age. The highest in-hospital mortality rates were observed in children <6 months old (0.73 per 100 000 persons). Over time, antiviral treatment significantly increased, from 56% to 85% (P < .001), and influenza vaccination rates increased from 33% to 44% (P = .003). Among the 13 235 hospitalized children, 2676 (20%) were admitted to the ICU, 2262 (17%) had pneumonia, 690 (5%) required mechanical ventilation, and 72 (0.5%) died during hospitalization. Compared with those <6 months of age, hospitalized children ≥13 years old had higher odds of pneumonia (adjusted odds ratio, 2.7 [95% confidence interval, 2.1–3.4], ICU admission (1.6 [1.3–1.9]), mechanical ventilation (1.6 [1.1–2.2]), and death (3.3 [1.2–9.3]).

Conclusions

Hospitalization and death rates were greatest in younger children at the population level. Among hospitalized children, however, older children had a higher risk of severe outcomes. Continued efforts to prevent and attenuate influenza in children are needed.
Protective Effect of Intestinal Blautia Against Neutropenic Fever in Allogeneic Transplant Recipients
Authors: Rashidi Armin , Peled Jonathan U , Ebadi Maryam , Rehman Tauseef Ur , Elhusseini Heba , Marcello LeeAnn T , Halaweish Hossam , Kaiser Thomas , Holtan Shernan G , Khoruts Alexander , Weisdorf Daniel J , Staley Christopher
Published: April 2022

Background

Neutropenic fever (NF) occurs in >70% of hematopoietic cell transplant (HCT) recipients, without a documented cause in most cases. Antibiotics used to prevent and treat NF disrupt the gut microbiota; these disruptions predict a higher posttransplantation mortality rate. We hypothesized that specific features in the gut microbial community may mediate the risk of NF.

Methods

We searched a large gut microbiota database in allogeneic HCT recipients (12 546 stool samples; 1278 patients) to find pairs with NF (cases) versus without NF (controls) on the same day relative to transplantation and with a stool sample on the previous day. A total of 179 such pairs were matched as to the underlying disease and graft source. Several other important clinical variables were similar between the groups.

Results

The gut microbiota of cases on the day before NF occurrence had a lower abundance of Blautia than their matched controls on the same day after transplantation, suggesting a protective role for Blautia. Microbiota network analysis did not find any differences in community structure between the groups, suggesting a single-taxon effect. To identify putative mechanisms, we searched a gut microbiome and serum metabolome database of patients with acute leukemia receiving chemotherapy and identified 139 serum samples collected within 24 hours after a stool sample from the same patient. Greater Blautia abundances predicted higher levels of next-day citrulline, a biomarker of total enterocyte mass.

Conclusions

These findings support a model in which Blautia protects against NF by improving intestinal health. Therapeutic restoration of Blautia may help prevent NF, thus reducing antibiotic exposures and transplantation-related deaths.
A Tribute to Frank Wilkinson
Authors: Rubery Jill , Burchell Brendan , Deakin Simon , Konzelmann Suzanne J
Published: April 2022

This tribute article acknowledges the lifetime contributions of Frank Wilkinson to social sciences in general and the Cambridge Journal of Economics in particular. He was not only a founding editor of the Cambridge Journal of Economics but also in his later years he was elected a Patron of the Journal in recognition of his contributions.
Globalisation in reverse? Reconfiguring the geographies of value chains and production networks
Authors: Gong Huiwen , Hassink Robert , Foster Christopher , Hess Martin , Garretsen Harry
Published: April 2022

Standing at a crossroads, where ongoing ‘slowbalisation’ coincides with new forces such as the outbreak of the Covid-19 pandemic, heightened geopolitical tensions, the emergence of disruptive technologies and the increasing urgency of addressing environmental challenges, many important questions remain unsolved regarding the nature and impact of the current economic globalisation. This special issue on ‘Globalisation in Reverse? Reconfiguring the Geographies of Value Chains and Production Networks’ aims at showcasing recent work that seeks to contribute to, and advance, the debates on economic globalisation and the reconfiguration of global value chains and production networks. This introductory article has three objectives: first, based on a broad literature review, we aim to identify four key forces, as well as the fundamental relatively stable capitalist logics contributing to the complex reconfiguration of global economic activities. Second, we will position the papers included in this special issue against the four main forces identified and discuss the contributions of each article to capture some emerging cross-paper patterns among them. Finally, we outline the contours of a research agenda that suggests promising avenues for further investigation of the phenomenon of value chain and production network reconfigurations in times of uncertainty.