bluuebunny/crossref_metadata_2025 huggingface dataset:
The Delta Variant Had Negligible Impact on COVID-19 Vaccine Effectiveness in the USA
Authors: Blaiszik Ben , Graziani Carlo , Olds James L. , Foster Ian
Published: September 2021

The SARS-CoV-2 Delta variant (B.1.617.2) was initially identified in India in December 2020. Due to its high transmissibility, its prevalence in the U.S.A. grew from a near-zero baseline in early May 2021 to nearly 100% by late August 2021, according to CDC tracking. We accessed openly available data sources from the public health authorities of seven U.S. states, five U.S. counties, and the District of Columbia on RT-PCR COVID-19 tests split by the COVID-19 vaccination status of individuals tested during this period. Together, these time series enable estimation and tracking of COVID-19 vaccine effectiveness (VE∗) (against RT-PCR diagnosed infection) concurrently with the growth of Delta variant prevalence in those locations. Our analyses reveal that in each locality the VE∗ for the combined set of all three US vaccines remained relatively stable and quite well-performing, despite the dramatic concurrent rise of Delta variant prevalence. We conclude that the Delta variant does not significantly evade vaccine-induced immunity. The variations in our measured VE∗ appear to be driven by demographic factors affecting the composition of the vaccinated cohorts, particularly as pertains to age distribution. We report that the measured VE∗, aggregated across the collected sites, began at a value of about 0.9 in mid-May, declined to about 0.76 by mid-July, and recovered to about 0.9 by mid-September.

We estimated local COVID-19 vaccine effectiveness using RT-PCR COVID-19 test data broken out by vaccination status from select localities in the U.S.A. between 15 May and 15 September 2021 while the SARS-CoV-2 Delta variant (B.1.617.2) was ascending from essentially zero prevalence to total dominance of the genome, and showed that the rise of the Delta variant had negligible effect on vaccine effectiveness.
Shared decision making and specific informed consent in patients with aortic aneurysms
Authors: Silva Cunha Marcela Juliano , Teivelis Marcelo Passos , de Almeida Mendes Cynthia , Annicchino Baptistella Conrado Dias Pacheco , Henry Sant’Anna Pedro Vasconcelos , Wolosker Nelson
Published: September 2021

Introduction

Studies show that vascular surgery patients have the desire to participate more actively in their treatment, but that they find it difficult to express themselves. Patients prefer to know all the therapeutic options available, not just those that the surgeon considers appropriate. With this knowledge, patients can begin to choose the most appropriate therapeutic modality for themselves, also becoming responsible for the therapeutic decision. Therefore, the objective of this paper was to analyze the refusal rate of elective aortic aneurysm surgery in asymptomatic patients after the presentation of a detailed IC form followed by a meeting where the patient and his or her family could analyze each item;

Methods

Data from 49 patients who had aneurysms and were offered surgical treatment were retrospectively collected and analyzed.

Results

After reading the IC and the described meeting, among the 49 patients, 13 (26.5%) refused surgery. We observed that patients who refused surgery had statistically smaller aneurysms than patients who accepted surgery (9% versus 26%).

Conclusion

One-quarter of patients who were indicated for elective surgical correction of aortic aneurysms rejected surgery after SDM, which consisted of the presentation of an IC form followed by a clarification meeting for the patient and his or her family to analyze each item. The only factor that significantly influenced a rejection of the procedure was the size of the aneurysm, so patients who rejected surgery had smaller aneurysms than those who accepted surgery.
Qatar Genome: Insights on Genomics from the Middle East
Authors: Mbarek Hamdi , Gandhi Geethanjali Devadoss , Selvaraj Senthil , Al-Muftah Wadha , Badji Radja , Al-Sarraj Yasser , Saad Chadi , Darwish Dima , Alvi Muhammad , Fadl Tasnim , Yasin Heba , Alkuwari Fatima , Razali Rozaimi , Aamer Waleed , Abbaszadeh Fatemeh , Ahmed Ikhlak , Mokrab Younes , Suhre Karsten , Albagha Omar , Fakhro Khalid , Badii Ramin , Ismail Said I. , Althani Asma ,   for the Qatar Genome Program Research Consortium
Published: September 2021

Despite recent biomedical breakthroughs and large genomic studies growing momentum, the Middle Eastern population, home to over 400 million people, is under-represented in the human genome variation databases. Here we describe insights from phase 1 of the Qatar Genome Program which whole genome sequenced 6,045 individuals from Qatar. We identified more than 88 million variants of which 24 million are novel and 23 million are singletons. Consistent with the high consanguinity and founder effects in the region, we found that several rare deleterious variants were more common in the Qatari population while others seem to provide protection against diseases and have shaped the genetic architecture of adaptive phenotypes. Insights into the genetic structure of the Qatari population revealed five non-admixed subgroups. Based on sequence data, we also reported the heritability and genetic marker associations for 45 clinical traits. These results highlight the value of our data as a resource to advance genetic studies in the Arab and neighbouring Middle Eastern populations and will significantly boost the current efforts to improve our understanding of global patterns of human variations, human history and genetic contributions to health and diseases in diverse populations.
Evaluation of sleep pattern due to stress in undergraduate medical students and its impact on health and academic performance: A cross-sectional study from tertiary health center of Central India
Authors: Gandhi Kusum , Godaria Yashvardhan , Revadi G
Published: September 2021

Background

Good quality sleep is essential for good health and well-being. Medical students are at no exception to this and are prone to greater risk for sleep deprivation. The major reason being challenges to maintain a high level of academic achievement and constant thirst to acquire new learning skills and knowledge. However, in this process they are circumstanced to various levels of stress that might cause potential damage to their cognitive functioning and mental exhaustion to a certain extent.

Objectives

Thus, our study objectives were to evaluate the sleep pattern in first- and second-year medical students. To understand how the stress levels and academic performance are related to sleep pattern and to explore the copying strategies of stress in our study participants.

Methodology

This cross-sectional study was conducted using a self-reported, web-based, questionnaire that included questions on sleep quality and deprivation through Pittsburgh sleep quality index. All the eligible students of first and second year who were part of a premiere teaching hospital during February and March 2021 were included. Data was analysed using IBM SPSS version 24.

Results

Out of 180 participants, 91(50.55%) had their initiation of sleeping time from 12-2 am and also, majority of students 112 (62.22%) had a sleep duration of six to eight hours. However, 119 (66.1%) students had self-reported change in sleeping pattern which was found to be significantly associated with relatively greater number of academic factors as compared to social factors. Most of the students scored between 50-60% score in their four assessments amongst which their first assessment was significantly associated with change in sleep pattern (P 0.040). Also, these individual assessment score was found to significantly affect their duration of sleep. The common coping strategies adopted by students under study were talking to family members/ friends, music/ book reading (hobby).

Conclusion

Majority of students in our study had reported change in sleeping pattern. Also, association between stress factors and change in sleeping pattern were observed with academic stress factors proving to be more significantly associated than social stress factors. The academic performance of students was also found to be associated with change in sleeping pattern and duration of sleep.
The apportionment of citations: A scientometric analysis of Lewontin, 1972
Authors: Carlson Jedidiah , Harris Kelley
Published: September 2021

“The Apportionment of Human Diversity” (1972) is the most highly cited research article published by geneticist Richard Lewontin in his career. This study’s primary result—that most genetic diversity in humans can be accounted for by within-population differences, not between-population differences—along with Lewontin’s outspoken, politically-charged interpretations thereof, has become foundational to the scientific and cultural discourse pertaining to human genetic variation. The article has an unusual bibliometric trajectory in that it is much more salient in the bibliographic record today compared to the first 20 years after its publication. Here, we show how the paper’s fame was shaped by four factors: 1) citations in influential publications across several disciplines; 2) Lewontin’s own popular books and media appearances; 3) the renaissance of population genetics research of the early 1990s; and 4) the serendipitous collision of scientific progress, influential books/papers, and heated controversies in the year 1994. We conclude with an analysis of Twitter data to characterize the communities and conversations that continue to keep this study at the epicenter of discussions about race and genetics, prompting new challenges for scientists who have inherited Lewontin’s legacy.
deCS: A Tool for Systematic Cell Type Annotations of Single-cell RNA Sequencing Data among Human Tissues
Authors: Pei Guangsheng , Yan Fangfang , Simon Lukas M. , Dai Yulin , Jia Peilin , Zhao Zhongming
Published: September 2021

Single-cell RNA sequencing (scRNA-seq) is revolutionizing the study of complex and dynamic cellular mechanisms. However, cell-type annotation remains a main challenge as it largely relies on a priori knowledge and manual curation, which is cumbersome and less accurate. The increasing number of scRNA-seq data sets, as well as numerous published genetic studies, motivated us to build a comprehensive human cell type reference atlas. Here, we present deCS (decoding Cell type-Specificity), an automatic cell type annotation method augmented by a comprehensive collection of human cell type expression profiles and marker genes. We used deCS to annotate scRNA-seq data from various tissue types and systematically evaluated the annotation accuracy under different conditions, including reference panels, sequencing depth and feature selection strategies. Our results demonstrated that expanding the references is critical for improving annotation accuracy. Compared to many existing state-of-the-art annotation tools, deCS significantly reduced computation time and increased accuracy. deCS can be integrated into the standard scRNA-seq analytical pipeline to enhance cell type annotation. Finally, we demonstrated the broad utility of deCS to identify trait-cell type associations in 51 human complex traits, providing deeper insights into the cellular mechanisms of disease pathogenesis. All documents, including source code, user manual, demo data, and tutorials, are freely available at https://github.com/bsml320/deCS.
Mathematical modelling of activation-induced heterogeneity reveals cell state transitions underpinning macrophage responses to LPS
Authors: Dey S. , Boucher D. , Pitchford J. W. , Lagos D.
Published: September 2021

Despite extensive work on macrophage heterogeneity, the mechanisms driving activation induced heterogeneity (AIH) in macrophages remain poorly understood. Here, we use two in vitro cellular models of LPS-induced tolerance (bone marrow-derived macrophages or BMDMs and RAW 264.7 cells), single-cell protein measurements, and mathematical modelling to explore how AIH underpins primary and secondary responses to LPS. We measure expression of TNF, IL-6, pro-IL-1β, and NOS2 and demonstrate that macrophage community AIH is dependent on LPS dose. We show that altered AIH kinetics in macrophages responding to a second LPS challenge underpin hypo-responsiveness to LPS. These empirical data can be explained by a mathematical 3-state model including negative, positive, and non-responsive states (NRS), but they are also compatible with a 4-state model that includes distinct reversibly NRS and non-responsive permanently states (NRPS). Our mathematical model, termed NoRM (Non-Responsive Macrophage) model identifies similarities and differences between BMDM and RAW 264.7 cell responses. In both cell types, transition rates between states in the NoRM model are distinct for each of the tested proteins and, crucially, macrophage hypo-responsiveness is underpinned by changes in transition rates to and from NRS. Overall, our findings provide support for a critical role for phenotypically negative macrophage populations as an active component of AIH and primary and secondary responses to LPS. This reveals unappreciated aspects of cellular ecology and community dynamics associated with LPS-driven training of macrophages.
Epidemic models characterize seizure propagation and the effects of epilepsy surgery in individualized brain networks based on MEG and invasive EEG recordings
Authors: Millán Ana. P. , van Straaten Elisabeth C.W. , Stam Cornelis J. , Nissen Ida A. , Idema Sander , Baayen Johannes C. , Van Mieghem Piet , Hillebrand Arjan
Published: September 2021

Background

Epilepsy surgery is the treatment of choice for drug-resistant epilepsy patients. However, seizure-freedom is currently achieved in only 2/3 of the patients after surgery. In this study we have developed an individualized computational model based on functional brain networks to explore seizure propagation and the efficacy of different virtual resections. Eventually, the goal is to obtain individualized models to optimize resection strategy and outcome.

Methods

We have modelled seizure propagation as an epidemic process using the susceptible-infected (SI) model on individual functional networks derived from presurgical MEG. We included 10 patients who had received epilepsy surgery and for whom the surgery outcome at least one year after surgery was known. The model parameters were tuned in order to reproduce the patient-specific seizure propagation patterns as recorded with invasive EEG. We defined a personalized search algorithm that combined structural and dynamical information to find resections that maximally decreased seizure propagation for a given resection size. The optimal resection for each patient was defined as the smallest resection leading to at least a 90% reduction in seizure propagation.

Results

The individualized model reproduced the basic aspects of seizure propagation for 9 out of 10 patients when using the resection area as the origin of epidemic spreading, and for 10 out of 10 patients with an alternative definition of the seed region. We found that, for 7 patients, the optimal resection was smaller than the resection area, and for 4 patients we also found that a resection smaller than the resection area could lead to a 100% decrease in propagation. Moreover, for two cases these alternative resections included nodes outside the resection area.

Conclusion

Epidemic spreading models fitted with patient specific data can capture the fundamental aspects of clinically observed seizure propagation, and can be used to test virtual resectionsin silico. Combined with optimization algorithms, smaller or alternative resection strategies, that are individually targeted for each patient, can be determined with the ultimate goal to improve surgery outcome.
Mind the gap: Mapping Variation between National and Local Clinical Practice Guidelines for Acute Paediatric Asthma from the United Kingdom and the Netherlands
Authors: Koldeweij Charlotte , Clarke Jonathan , Rodriguez Gonzalvez Carmen , Nijman Joppe , Sinha Ruchi , Maconochie Ian , Appelbaum Nicholas
Published: September 2021

Background

Clinical practice guidelines (CPGs) aim to standardize clinical care. Increasingly, hospitals rely on locally produced guidelines alongside national guidance. This study examines variation between national and local CPGs, using the example of acute paediatric asthma guidance from the United Kingdom and the Netherlands.

Methods

Fifteen British and Dutch local CPGs were collected with the matching national guidance for the management of acute asthma in children under 18 years old. The drug sequences, routes and methods of administration recommended for patients with severe asthma and the tone of recommendation across both types of CPGs were schematically represented. Deviations from national guidance were measured. Variation in recommended doses of intravenous salbutamol was examined.

Results

British and Dutch national CPGs differed in the recommended drug choices, sequences, routes and methods of administration for severe asthma. Dutch national guidance was more rigidly defined. Local British CPGs diverged from national guidance for 23% of their recommended interventions compared to 8% for Dutch local CPGs. Five British local guidelines and two Dutch local guidelines differed from national guidance for multiple treatment steps. Variation in second-line recommendations was greater than for first-line recommendations across local CPGs from both countries. Recommended starting doses for salbutamol infusions varied by more than tenfold.

Conclusions

Local CPGs for the management of severe acute paediatric asthma featured substantial variation and frequently diverged from national guidance. Although limited to one condition, this study suggests that unmeasured variation across local CPGs may contribute to variation of care more broadly, with possible effects on healthcare quality.
Can we distinguish the roles of demographic and temporal changes in the incidence and prevalence of musculoskeletal disorders? A systematic search and review
Authors: Bouziri Hanifa , Descatha Alexis , Roquelaure Yves , Dab William , Jean Kévin
Published: September 2021

Background

Musculoskeletal disorders (MSDs) represent a major public health issue, affecting more than 40 million European workers in 2017. The overall ageing of the working population is expected to increase the burden of disease, but temporal changes in exposures or diagnosis may also drive global trends in MSDs. We, therefore, sought to review and summarize evidence describing the role of demographic and temporal changes in the occurrence of MSDs.

Methods

We conducted a systematic search and review of articles reporting temporal trends in MSDs in the general working-age population. Only articles controlling for age in the analysis were included. The risk of bias was assessed. The main indicators extracted were age-controlled time trends in MSD incidence or prevalence.

Results

Among 2,680 articles, 16 fulfilled the inclusion criteria, representing 23 results according to the indicators extracted. No study was found with a high risk of bias. Twelve results reported time trends in prevalence and 11 in incidence. After controlling for age, the reported temporal trends varied, mostly between non-monotonic changes (n=12/23) and increases (n=10/23); one article also highlighted an increase among women and non-monotonic changes among men (n = 1/23). Several factors other than ageing were suggested to explain temporal trends in MSDs, main trends in obesity, changing occupational exposures, and cultural factors regarding pain tolerance.

Conclusion

This review shows that different kinds of factors in addition to ageing may contribute to varying or increasing trends in MSDs. This review also highlighted the scarcity of evidence regarding time trends in the burden of MSDs and their underlying causes.
Quantifying Epistemic and Aleatoric Uncertainty in 3D U-Net Segmentation
Authors: Jones Craig K , Wang Guoqing , Yedavalli Vivek , Sair Haris
Published: September 2021

This work shows a derivation of a multinomial probability function and quantitative measures of the data and epistemic uncertainty as direct output of a 3D U-Net segmentation network. A set of T1 brain MRI images were downloaded from the Connectome Project and segmented using FMRIB’s FAST algorithm to be used as ground truth. A 3D U-Net neural network was trained with sample sizes of 200, 500, and 898 T1 brain images using a loss function defined as the negative logarithm of the likelihood based on a derivation of the definition of the multinomial probability function. From this definition, the epistemic (model) and aleatoric (data) uncertainty equations were derived and used to quantify maps of the uncertainty in data prediction. The epistemic and aleatoric uncertainty decreased based on the increasing number of training data used to train the neural network. The neural network trained with 898 volumes resulted in uncertainty maps that were high primarily in the tissue boundary regions. The uncertainty was averaged over all test data (connectome and tumor separately) and the epistemic uncertainty showed a decreasing trend, as expected, with increasing numbers of data used to train the model. The aleatoric uncertainty showed a similar trend, but it was less obvious, which was also expected as the aleatoric uncertainty is not expected to be as dependent on the number of training data. The derived data and epistemic uncertainty equations from a multinomial probability distribution are applicable for all 2D and 3D neural networks.
Large-scale social media language analysis reveals emotions and behaviours associated with nonmedical prescription drug use
Authors: Al-Garadi Mohammed Ali , Yang Yuan-Chi , Guo Yuting , Kim Sangmi , Love Jennifer S. , Perrone Jeanmarie , Sarker Abeed
Published: September 2021

Nonmedical use of prescription drugs (NMPDU) is a global health concern. The extent of, behaviors and emotions associated with, and reasons for NMPDU are not well-captured through traditional instruments such as surveys, prescribing databases and insurance claims. Therefore, this study analyses ∼130 million public posts from 87,718 Twitter users in terms of expressed emotions, sentiments, concerns, and potential reasons for NMPDU via natural language processing. Our results show that users in the NMPDU group express more negative emotions and less positive emotions, more concerns about family, the past and body, and less concerns related to work, leisure, home, money, religion, health and achievement, compared to a control group (i.e., users who never reported NMPDU). NMPDU posts tend to be highly polarized, indicating potential emotional triggers. Gender-specific analysis shows that female users in the NMPDU group express more content related to positive emotions, anticipation, sadness, joy, concerns about family, friends, home, health and the past, and less about anger, compared to males. The findings of the study can enrich our understanding of NMPDU.
Complex population structure and haplotype patterns in Western Europe honey bee from sequencing a large panel of haploid drones
Authors: Wragg David , Eynard Sonia E. , Basso Benjamin , Canale-Tabet Kamila , Labarthe Emmanuelle , Bouchez Olivier , Bienefeld Kaspar , Bieńkowska Małgorzata , Costa Cecilia , Gregorc Aleš , Kryger Per , Parejo Melanie , Pinto M. Alice , Bidanel Jean-Pierre , Servin Bertrand , Le Conte Yves , Vignal Alain
Published: September 2021

Honey bee subspecies originate from specific geographic areas in Africa, Europe and the Middle East. The interest of beekeepers in specific phenotypes has led them to import subspecies to regions outside of their original range. The resulting admixture complicates population genetics analyses and population stratification can be a major problem for association studies. As a typical example, the case of the French population is studied here. We sequenced 870 haploid drones for SNP detection and identified nine genetic backgrounds in 629 samples. Five correspond to subspecies, two to isolated populations and two to human-mediated population management. We also highlight several large haplotype blocks, some of which coincide with the position of centromeres. The largest is 3.6 Mb long on chromosome 11, representing 1.6 % of the genome and has two major haplotypes, corresponding to the two dominant genetic backgrounds identified.
Extracellular Vesicles Carry Distinct Proteo-Transcriptomic Signatures That are Different from Their Cancer Cell of Origin
Authors: Chen Tzu-Yi , Gonzalez-Kozlova Edgar , Soleymani Taliah , La Salvia Sabrina , Kyprianou Natasha , Sahoo Susmita , Tewari Ashutosh K. , Cordon-Cardo Carlos , Stolovitzky Gustavo , Dogra Navneet
Published: September 2021

Circulating extracellular vesicles (EVs) contain molecular footprints from their cell of origin and may provide potential non-invasive access for detection, characterization, and monitoring of numerous diseases. Despite their growing promise, the integrated proteo-transcriptomic landscape of EVs and their donor cells remain poorly understood. To assess their cargo, we conducted small RNA sequencing and mass spectrometry (LC-MS/MS) of EVs isolated fromin vitrocancer cell culture and prostate cancer patients’ serum. Here, we report that EVs enrich for distinct molecular cargo, and their proteo-transcriptome is predominantly different from their cancer cell of origin, implicating a coordinated disposal and delivery mechanism. We have discovered that EVs package their cargo in a non-random fusion, as their most enriched RNAs and proteins are not the most abundant cargo from their donor cells. We show that EVs enrich for 4 times more cytoskeletal and 2 times extracellular proteins than their donor cells. While the donor cells carry 10 times more mitochondrial and 3 times nuclear proteins than their EVs. EVs predominantly (40-60%) enrich for small RNA (~15-200 nucleotides) molecules that implicate cell differentiation, development, and signaling signatures. Finally, our integrated proteo-transcriptomic analyses reveal that EVs are enriched of RNAs (RNY3, vtRNA, and MIRLET-7) and their complementary proteins (YBX1, IGF2BP2, SRSF1/2), implicating an interrelated mechanism that may protect and regulate transcripts until a biological function is achieved. Based on these results, we envision that the next-generation clinical assays will take an integrative multi-omic (proteomic and transcriptomic) approach for liquid biopsy in numerous diseases.
Sensing Local Field Potentials with a Directional and Scalable Depth Array: the DISC electrode array
Authors: Abrego Amada M. , Khan Wasif , Wright Christopher E. , Islam M. Rabiul , Ghajar Mohammad H. , Bai Xiaokang , Tandon Nitin , Seymour John P.
Published: September 2021

A variety of electrophysiology tools are available to the neurosurgeon for diagnosis, functional therapy, and neural prosthetics. However, no tool can currently address these three critical needs: (i) access to all cortical regions in a minimally invasive manner; (ii) recordings with microscale, mesoscale, and macroscale resolutions simultaneously; and (iii) access to spatially distant multiple brain regions that constitute distributed cognitive networks. We present a novel device for recording local field potentials (LFPs) with the form factor of a stereo-electroencephalographic electrode but combined with radially positioned microelectrodes and using the lead body to shield LFP sources, enablingdirectional sensitivity andscalability, referred to as the DISC array. As predicted by our electro-quasistatic models, DISC demonstrated significantly improved signal-to-noise ratio, directional sensitivity, and decoding accuracy from rat barrel cortex recordings during whisker stimulation. Critically, DISC demonstrated equivalent fidelity to conventional electrodes at the macroscale and uniquely, revealed stereoscopic information about current source density. Directional sensitivity of LFPs may significantly improve brain-computer interfaces and many diagnostic procedures, including epilepsy foci detection and deep brain targeting.
Balanced, Orientation-Dependent Dichoptic Masking in Cortex of Visually Normal Humans Measured Using Electroencephalography (EEG)
Authors: Zhang Jerry J. , Tang Yichen , Dakin Steven C. , Hallum Luke E.
Published: September 2021

In the human visual system, cerebral cortex combines left- and right-eye retinal inputs, enabling single, comfortable binocular vision. In visual cortex, the signals from each eye inhibit one another (interocular suppression). While this mechanism may be disrupted by e.g. traumatic brain injury, clinical assessments of interocular suppression are subjective, qualitative, and lack reliability. EEG is a potentially useful clinical tool for objective, quantitative assessment of binocular vision. In a cohort of normal participants, we measured occipital, visual evoked potentials (VEPs) in response to dichoptically-presented vertical and/or horizontal sine-wave gratings. Response amplitudes to orthogonal gratings were greater than that of parallel gratings, which were in turn greater than that of monocular gratings. Our results indicate that interocular suppression is (normally) balanced, orientation-tuned, and that suppression per se is reduced for orthogonal gratings. This objective measure of suppression may have application in clinical settings.
Next-generation ultrasonic recorders facilitate effective bat activity and distribution monitoring by citizen scientists
Authors: Lundberg Piia , Meierhofer Melissa B. , Vasko Ville , Suutari Miina , Ojala Ann , Vainio Annukka , Lilley Thomas M.
Published: September 2021

Time and budgetary resources are often a limiting factor in the collection of large-scale ecological data. If data collected by citizen scientists were comparable to data collected by researchers, it would allow for more efficient data collection over a broad geographic area. Here, we compare the quality of data on bat activity collected by citizens (high school students and teachers) and researchers. Both researchers and citizen scientists used the same comprehensive instructions when choosing study sites. We found no differences in total bat activity minutes recorded by citizens and researchers. Instead, citizen scientists collected data from a wider variety of habitats than researchers. Involvement of citizens also increased the geographical coverage of data collection, resulting in the northernmost documentation of the Nathusius’s pipistrelle so far in Finland. Therefore, bat research can benefit from the use of citizen science when participants are given precise instructions and calibrated data collection equipment. Citizen science projects also have other far-reaching benefits, increasing, for example, the scientific literacy and interest in natural sciences of citizens. Involving citizens in science projects also has the potential to enhance their willingness to conserve nature.

Open Research Statement

Data are not yet provided, but will uploaded Dryad upon publication.
Multi-locus transcranial magnetic stimulation system for electronically targeted brain stimulation
Authors: Nieminen Jaakko O. , Sinisalo Heikki , Souza Victor H. , Malmi Mikko , Yuryev Mikhail , Tervo Aino E. , Stenroos Matti , Milardovich Diego , Korhonen Juuso T. , Koponen Lari M. , Ilmoniemi Risto J.
Published: September 2021

Background

Transcranial magnetic stimulation (TMS) allows non-invasive stimulation of the cortex. In multi-locus TMS (mTMS), the stimulating electric field (E-field) is controlled electronically without coil movement by adjusting currents in the coils of a transducer.

Objective

To develop an mTMS system that allows adjusting the location and orientation of the E-field maximum within a cortical region.

Methods

We designed and manufactured a planar 5-coil mTMS transducer to allow controlling the maximum of the induced E-field within a cortical region approximately 30 mm in diameter. We developed electronics with a design consisting of independently controlled H-bridge circuits to drive up to six TMS coils. To control the hardware, we programmed software that runs on a field-programmable gate array and a computer. To induce the desired E-field in the cortex, we developed an optimization method to calculate the currents needed in the coils. We characterized the mTMS system and conducted a proof-of-concept motor-mapping experiment on a healthy volunteer. In the motor mapping, we kept the transducer placement fixed while electronically shifting the E-field maximum on the precentral gyrus and measuring electromyography from the contralateral hand.

Results

The transducer consists of an oval coil, two figure-of-eight coils, and two four-leaf-clover coils stacked on top of each other. The technical characterization indicated that the mTMS system performs as designed. The measured motor evoked potential amplitudes varied consistently as a function of the location of the E-field maximum.

Conclusion

The developed mTMS system enables electronically targeted brain stimulation within a cortical region.
Detection of m6A from direct RNA sequencing using a Multiple Instance Learning framework
Authors: Hendra Christopher , Pratanwanich Ploy N. , Wan Yuk Kei , Goh W.S. Sho , Thiery Alexandre , Göke Jonathan
Published: September 2021

RNA modifications such as m6A methylation form an additional layer of complexity in the transcriptome. Nanopore direct RNA sequencing captures this information in the raw current signal for each RNA molecule, enabling the detection of RNA modifications using supervised machine learning. However, experimental approaches provide only site-level training data, whereas the modification status for each single RNA molecule is missing. Here we present m6Anet, a neural network-based method that leverages the Multiple Instance Learning framework to specifically handle missing read-level modification labels in site-level training data. m6Anet outperforms existing computational methods, shows similar accuracy as experimental approaches, and generalises to different cell lines with almost identical accuracy. We demonstrate that m6Anet captures the underlying read-level stoichiometry that can be used to approximate differences in modification rates. m6Anet achieves this without retraining model parameters, enabling the transcriptome-wide identification and quantification of m6A from a single run of direct RNA sequencing.

Code Availability

The source code for m6Anet is available at https://github.com/GoekeLab/m6anet. Installation instructions and online documentation is available at https://m6anet.readthedocs.io/en/latest/.
CompoundRay: An open-source tool for high-speed and high-fidelity rendering of compound eyes
Authors: Millward Blayze , Maddock Steve , Mangan Michael
Published: September 2021

Revealing the functioning of non-standard visual systems such as compound eyes is of interest to biologists and engineers alike. A key investigative method is to replicate the sensory apparatus using artificial systems, allowing for investigation of the visual information that drives animal behaviour when exposed to environmental cues. To date, ‘Compound Eye Models’ (CEMs) have largely explored the impact of features such as spectral sensitivity, field of view, and angular resolution on behaviour. Yet, the role of shape and overall structure have been largely overlooked due to modelling complexity. However, modern real-time raytracing technologies are enabling the construction of a new generation of computationally fast, high-fidelity CEMs. This work introduces new open-source CEM software (CompoundRay) alongside standardised usage techniques, while also discussing the diffculties inherent with visual data display and analysis of compound eye perceptual data. CompoundRay is capable of accurately rendering the visual perspective of a desert ant at over 5,000 frames per second in a 3D mapped natural environment. It supports ommatidial arrangements at arbitrary positions with per-ommatidial heterogeneity.
ProMetheusDB: an in-depth analysis of the high-quality human methyl-proteome
Authors: Massignani Enrico , Giambruno Roberto , Maniaci Marianna , Nicosia Luciano , Yadav Avinash , Cuomo Alessandro , Raimondi Francesco , Bonaldi Tiziana
Published: September 2021

Protein Arginine (R) methylation is a post-translational modification involved in various biological processes, such as RNA splicing, DNA repair, immune response, signal transduction, and tumour development. Although several advancements were made in the study of this modification by mass spectrometry, researchers still face the problem of a high false discovery rate. We present a dataset of high-quality methylations obtained from several different heavy methyl SILAC (hmSILAC) experiments analysed with a machine learning-based tool doublets and show that this model allows for improved high-confidence identification of real methyl-peptides. Overall, our results are consistent with the notion that protein R methylation modulates protein:RNA interactions and suggest a role in rewiring protein:protein interactions, for which we provide experimental evidence for a representative case (i.e. NONO:PSPC1). Upon intersecting our R-methyl-sites dataset with a phosphosites dataset, we observed that R methylation correlates differently with S/T-Y phosphorylation in response to various stimuli. Finally, we explored the application of hmSILAC to identify unconventional methylated residues and successfully identified novel histone methylation marks on Serine 28 and Threonine 32 of H3.
Top2a promotes the development of social behavior via PRC2 and H3K27me3
Authors: Geng Yijie , Zhang Tejia , Godar Sean C. , Pluimer Brock R. , Harrison Devin L. , Nath Anjali K. , Yeh Jing-Ruey Joanna , Drummond Iain A. , Bortolato Marco , Peterson Randall T.
Published: September 2021

Human infants exhibit innate social behaviors at birth, yet little is understood about the embryonic development of sociality. We screened 1120 known drugs and found that embryonic inhibition of topoisomerase IIα (Top2a) resulted in lasting social deficits in zebrafish. In mice, prenatal Top2 inhibition caused behavioral defects related to core symptoms of autism, including impairments in social interaction and communication. Mutation of Top2a in zebrafish caused downregulation of a set of genes highly enriched for genes associated with autism in humans. Both the Top2a-regulated and autism-associated gene sets possess binding sites for polycomb repressive complex 2 (PRC2), a regulatory complex responsible for H3K27 trimethylation. Moreover, both gene sets are highly enriched for H3K27me3. Inhibition of PRC2 component Ezh2 rescued social deficits caused by Top2 inhibition. Therefore, Top2a is a key component of an evolutionarily conserved pathway that promotes the development of social behavior through PRC2 and H3K27me3.
Context-aware deconvolution of cell-cell communication with Tensor-cell2cell
Authors: Armingol Erick , Baghdassarian Hratch M. , Martino Cameron , Perez-Lopez Araceli , Aamodt Caitlin , Knight Rob , Lewis Nathan E.
Published: September 2021

Cell interactions determine phenotypes, and intercellular communication is shaped by cellular contexts such as disease state, organismal life stage, and tissue microenvironment. Single-cell technologies measure the molecules mediating cell-cell communication, and emerging computational tools can exploit these data to decipher intercellular communication. However, current methods either disregard cellular context or rely on simple pairwise comparisons between samples, thus limiting the ability to decipher complex cell-cell communication across multiple time points, levels of disease severity, or spatial contexts. Here we present Tensor-cell2cell, an unsupervised method using tensor decomposition, which is the first strategy to decipher context-driven intercellular communication by simultaneously accounting for multiple stages, states, or locations of the cells. To do so, Tensor-cell2cell uncovers context-driven patterns of communication associated with different phenotypic states and determined by unique combinations of cell types and ligand-receptor pairs. As such, Tensor-cell2cell robustly improves upon and extends the analytical capabilities of existing tools. We show Tensor-cell2cell can identify multiple modules associated with distinct communication processes (e.g., participating cell-cell and ligand receptor pairs) linked to COVID-19 severities and Autism Spectrum Disorder. Thus, we introduce an effective and easy-to-use strategy for understanding complex communication patterns across diverse conditions.
GBSmode: a pipeline for haplotype-aware analysis of genotyping-by-sequencing data
Authors: Yates Steven , Studer Bruno
Published: September 2021

2

Abstract

2.1

Background

Genotyping-by-sequencing (GBS) has revolutionised molecular genetic analysis. It enables simultaneous genotyping of thousands of DNA markers in the genome of any species. In contrast to whole-genome shotgun sequencing, GBS exploits a restriction enzyme to reduce genome complexity and directs the sequencing to begin at fixed digestion sites. However, currently used tools for the analysis of GBS data, such as SAMtools, often neglect the fundamental technical differences between GBS and shotgun sequencing.

2.2

Results

Here we present GBSmode, a dedicated pipeline to call DNA sequence variants using whole-read information from GBS data. It removes false positives by incorporating biological features such as the ploidy level and the number of possible alleles in the population under investigation. Comparison of GBSmode with SAMtools in an F2 population of rice (Oryza sativa L.) showed both identified a similar number of polymorphisms (13,449 and 14,445, respectively) with a high overlap (8,143). However, differences were found in the number of read misalignments (8.0% and 14.3% for GBSmode and SAMtools, respectively) and genotyping errors (5.0% and 8.3% for GBSmode and SAMtools, respectively). Further tests in a bi-parental F1 population of cassava (Manihot esculenta Crantz) showed GBSmode found 31,489 polymorphic loci, whereas the number was higher with SAMtools (43,860). However, this difference was mainly attributable to GBSmode rejecting 11,695 loci that were biologically not possible.

2.3

Conclusions

This study shows that GBSmode is a versatile tool for the analysis of GBS data. Moreover, GBSmode was able to reduce genotyping errors arising from read misalignments by combining haplotype data with biological information. Whilst other tools may find more markers, GBSmode is designed for accuracy.
Effects of the collagen–glycosaminoglycan mesh on gene expression as determined by using principal component analysis-based unsupervised feature extraction
Authors: Taguchi Y-h. , Turki Turki
Published: September 2021

Development of the medical applications for substances or materials that contact the cells is important. Hence, it is necessary to elucidate how substance that surround cells affect the gene expression during incubation. Here, we compared the gene expression profiles of cell lines that were in contact with the collagen–glycosaminoglycan mesh and control cells. Principal component analysis-based unsupervised feature extraction was applied to identify genes with altered expression during incubation in the treated cell lines but not in the controls. The identified genes were enriched in various biological terms. Our method also outperformed a conventional methodology, namely, gene selection based on linear regression with time course.
Emotion Down- and Up-Regulation Act on Spatially Distinct Brain Areas: Interoceptive Regions to Calm Down and Other Affective Regions to Amp Up
Authors: Min Jungwon , Nashiro Kaoru , Yoo Hyun Joo , Cho Christine , Nasseri Padideh , Bachman Shelby L. , Porat Shai , Thayer Julian F. , Chang Catie , Lee Tae-ho , Mather Mara
Published: September 2021

Prior studies on emotion regulation identified a set of brain regions specialized for generating and controlling affect. Researchers generally agree that when up- and down-regulating emotion, control regions in the prefrontal cortex turn up or down activity in affect-generating areas. However, the assumption that turning up and down emotions produces opposite effects in the same affect-generating regions is untested. We call this assumption the ‘affective dial hypothesis.’ Our study tested this hypothesis by examining the overlap between the sets of regions activated during up-regulation and those deactivated during down-regulation in a large number of participants (N=105). We found that up- and down-regulation both recruit regulatory regions such as the inferior frontal gyrus and dorsal anterior cingulate gyrus but act on distinct affect-generating regions. While up-regulation increases BOLD signal in regions associated with emotion such as the amygdala, anterior insula, striatum and anterior cingulate gyrus as well as in regions associated with sympathetic vascular activity such as periventricular white matter, down-regulation decreases signal in regions receiving interoceptive input such as the posterior insula and postcentral gyrus. These findings indicate that up- and down-regulation do not generally exert opposing effects on the same affect-generating regions. Instead, they target different brain circuits.

Significance Statement

Many contexts require modulating one’s own emotions. Identifying the brain areas implementing these regulatory processes should advance understanding emotional disorders and designing potential interventions. The emotion regulation field has an implicit assumption we call the affective dial hypothesis: that both emotion up- and down-regulation modulate the same emotion-generating brain areas. Countering the hypothesis, our findings indicate that up- and down-modulating emotions target different brain areas. Thus, the mechanisms underlying emotion regulation differ more than previously appreciated for up- versus down-regulation. In addition to their theoretical importance, these findings are critical for researchers attempting to target activity in particular brain regions during an emotion regulation intervention.
Functional and Structural Characterization of OXA-935, a Novel OXA-10-family β-lactamase from Pseudomonas aeruginosa
Authors: Pincus Nathan , Rosas-Lemus Monica , Gatesy Samuel , Shuvalova Ludmilla , Brunzelle Joseph , Minasov George , Satchell Karla , Lebrun-Corbin Marine , Ozer Egon , Hauser Alan , Bachta Kelly
Published: September 2021

Resistance to antipseudomonal penicillins and cephalosporins is often driven by the overproduction of the intrinsic β-lactamase AmpC. However, OXA-10-family β-lactamases are a rich source of resistance in Pseudomonas aeruginosa. OXA β-lactamases have a propensity for mutation leading to extended spectrum cephalosporinase and carbapenemase activity. In this study, we identified isolates from a subclade of the multidrug-resistant (MDR) high risk clonal complex CC446 with resistance to ceftazidime. Genomic analysis revealed that these isolates harbored a plasmid containing a novel allele of blaOXA-10, named blaOXA-935, which was predicted to produce an OXA-10 variant with two amino acid substitutions: an aspartic acid instead of glycine at position 157 and a serine instead of phenylalanine at position 153. The G157D mutation, present in OXA-14, is associated with resistance to ceftazidime. Deletion of blaOXA-935 restored sensitivity to ceftazidime and susceptibility profiling of P. aeruginosa laboratory strains expressing blaOXA-935 revealed that OXA-935 conferred ceftazidime resistance. To better understand the impact of the variant amino acids, we determined the crystal structures of OXA-14 and OXA-935. In OXA-14, one of two monomers contained the canonical carbamylated lysine-70 (K70). In contrast, both monomers of OXA-935 were decarbamylated at K70, and the F153S mutation conferred increased flexibility to the omega (Ω) loop. Compared to OXA-14, the catalytic efficiency of OXA-935 for nitrocefin was significantly reduced. Amino acid changes that confer extended spectrum cephalosporinase activity to OXA-10-family β-lactamases are concerning given rising reliance on novel β-lactam/β-lactamase inhibitor combinations such as ceftolozane-tazobactam and ceftazidime-avibactam to treat MDR P. aeruginosa infections.