bluuebunny/crossref_metadata_2025 huggingface dataset:
Forecasts for broad-band intensity mapping of the ultraviolet-optical background with CASTOR and SPHEREx
Authors: Scott Bryan R , Upton Sanderbeck Phoebe , Bird Simeon
Published: February 2022

Broad-band tomography statistically extracts the redshift distribution of frequency dependent emission from the cross-correlation of intensity maps with a reference catalog of galaxy tracers. We make forecasts for the performance of future all-sky UV experiments doing broad-band tomography. We consider the Cosmological Advanced Survey Telescope for Optical-UV Research (castor) and the Spectro-Photometer for the History of the Universe, Epoch of Reionization, and Ices Explorer (SPHEREx). The dominant uncertainty is from variability in the photometric zero-point, which scales with limiting magnitude and mirror size. With this scaling and assuming a galaxy number density characteristic of future spectroscopic data sets, we find that castor measures the UV background SED 2–10 times better than existing data. The applicable redshift range will expand from the current z < 1 to z ≈ 0–3 with castor and z = 5–9 with SPHEREx. We show that castor can provide competitive constraints on the EBL monopole to those available from galaxy number counts and direct measurement techniques. At high redshift especially, these results will help understand galaxy formation and reionization. Our modelling code and chains are publicly available.
Bursty star formation during the Cosmic Dawn driven by delayed stellar feedback
Authors: Furlanetto Steven R , Mirocha Jordan
Published: February 2022

In recent years, several analytic models have demonstrated that simple assumptions about halo growth and feedback-regulated star formation can match the (limited) existing observational data on galaxies at $z \gtrsim6$. By extending such models, we demonstrate that imposing a time delay on stellar feedback (as inevitably occurs in the case of supernova explosions) induces burstiness in small galaxies. Although supernova progenitors have short lifetimes (∼5–30 Myr), the delay exceeds the dynamical time of galaxies at such high redshifts. As a result, star formation proceeds unimpeded by feedback for several cycles and ‘overshoots’ the expectations of feedback-regulated star formation models. We show that such overshoot is expected even in atomic cooling haloes, with halo masses up to ∼1010.5 M⊙ at z ≳ 6. However, these burst cycles damp out quickly in massive galaxies, because large haloes are more resistant to feedback so retain a continuous gas supply. Bursts in small galaxies – largely beyond the reach of existing observations – induce a scatter in the luminosity of these haloes (of ∼1 mag) and increase the time-averaged star formation efficiency by up to an order of magnitude. This kind of burstiness can have substantial effects on the earliest phases of star formation and reionization.
The spins of compact objects born from helium stars in binary systems
Authors: Fuller Jim , Lu Wenbin
Published: February 2022

The angular momentum (AM) content of massive stellar cores helps us to determine the natal spin rates of neutron stars and black holes. Asteroseismic measurements of low-mass stars have proven that stellar cores rotate slower than predicted by most prior work, so revised models are necessary. In this work, we apply an updated AM transport model based on the Tayler instability to massive helium stars in close binaries, in which tidal spin-up can greatly increase the star’s AM. Consistent with prior work, these stars can produce highly spinning black holes upon core-collapse if the orbital period is less than $P_{\rm orb} \lesssim \! 1 \, {\rm d}$. For neutron stars, we predict a strong correlation between the pre-explosion mass and the neutron star rotation rate, with millisecond periods ($P_{\rm NS} \lesssim 5 \, {\rm ms}$) only achievable for massive ($M \gtrsim 10 \, M_\odot$) helium stars in tight ($P_{\rm orb} \lesssim 1 \, {\rm d}$) binaries. Finally, we discuss our models in relation to type Ib/c supernovae, superluminous supernove, gamma-ray bursts, and LIGO/Virgo measurements of black hole spins. Our models are roughly consistent with the rates and energetics of these phenomena, with the exception of broad-lined Ic supernovae, whose high rates and ejecta energies are difficult to explain.
Key sequence features of CRISPR RNA for dual-guide CRISPR-Cas9 ribonucleoprotein complexes assembled with wild-type or HiFi Cas9
Authors: Okada Keita , Aoki Kanae , Tabei Teruyuki , Sugio Kota , Imai Katsunori , Bonkohara Yuki , Kamachi Yusuke
Published: February 2022

Specific sequence features of the protospacer and protospacer-adjacent motif (PAM) are critical for efficient cleavage by CRISPR-Cas9, but current knowledge is largely derived from single-guide RNA (sgRNA) systems assessed in cultured cells. In this study, we sought to determine gRNA sequence features of a more native CRISPR-Cas9 ribonucleoprotein (RNP) complex with dual-guide RNAs (dgRNAs) composed of crRNA and tracrRNA, which has been used increasingly in recent CRISPR-Cas9 applications, particularly in zebrafish. Using both wild-type and HiFi SpCas9, we determined on-target cleavage efficiencies of 51 crRNAs in zebrafish embryos by assessing indel occurrence. Statistical analysis of these data identified novel position-specific mononucleotide features relevant to cleavage efficiencies throughout the protospacer sequence that may be unique to CRISPR-Cas9 RNPs pre-assembled with perfectly matched gRNAs. Overall features for wild-type Cas9 resembled those for HiFi Cas9, but specific differences were also observed. Mutational analysis of mononucleotide features confirmed their relevance to cleavage efficiencies. Moreover, the mononucleotide feature-based score, CRISPR-kp, correlated well with efficiencies of gRNAs reported in previous zebrafish RNP injection experiments, as well as independently tested crRNAs only in RNP format, but not with Cas9 mRNA co-injection. These findings will facilitate design of gRNA/crRNAs in genome editing applications, especially when using pre-assembled RNPs.
Tatajuba: exploring the distribution of homopolymer tracts
Authors: de Oliveira Martins Leonardo , Bloomfield Samuel , Stoakes Emily , Grant Andrew J , Page Andrew J , Mather Alison E
Published: February 2022

Length variation of homopolymeric tracts, which induces phase variation, is known to regulate gene expression leading to phenotypic variation in a wide range of bacterial species. There is no specialized bioinformatics software which can, at scale, exhaustively explore and describe these features from sequencing data. Identifying these is non-trivial as sequencing and bioinformatics methods are prone to introducing artefacts when presented with homopolymeric tracts due to the decreased base diversity. We present tatajuba, which can automatically identify potential homopolymeric tracts and help predict their putative phenotypic impact, allowing for rapid investigation. We use it to detect all tracts in two separate datasets, one of Campylobacter jejuni and one of three Bordetella species, and to highlight those tracts that are polymorphic across samples. With this we confirm homopolymer tract variation with phenotypic impact found in previous studies and additionally find many more with potential variability. The software is written in C and is available under the open source licence GNU GPLv3.
nf-core/mag: a best-practice pipeline for metagenome hybrid assembly and binning
Authors: Krakau Sabrina , Straub Daniel , Gourlé Hadrien , Gabernet Gisela , Nahnsen Sven
Published: February 2022

The analysis of shotgun metagenomic data provides valuable insights into microbial communities, while allowing resolution at individual genome level. In absence of complete reference genomes, this requires the reconstruction of metagenome assembled genomes (MAGs) from sequencing reads. We present the nf-core/mag pipeline for metagenome assembly, binning and taxonomic classification. It can optionally combine short and long reads to increase assembly continuity and utilize sample-wise group-information for co-assembly and genome binning. The pipeline is easy to install-all dependencies are provided within containers-portable and reproducible. It is written in Nextflow and developed as part of the nf-core initiative for best-practice pipeline development. All codes are hosted on GitHub under the nf-core organization https://github.com/nf-core/mag and released under the MIT license.
Longitudinal Electronic Cigarette Use Among Patients Recently Diagnosed With Cancer Enrolled in a Smoking Cessation Trial
Authors: Kalkhoran Sara , Streck Joanna M , Kruse Gina R , Rigotti Nancy A , Perez Giselle K , Regan Susan , Ponzani Colin J , Muzikansky Alona , Park Elyse R , Ostroff Jamie S
Published: February 2022

Introduction

Many cancer patients who smoke report concurrent e-cigarette use. Using a mixed-methods approach, we aimed to (1) describe longitudinal e-cigarette use over 6 months after a cancer diagnosis and (2) assess the association between e-cigarette use and smoking cessation, among cancer patients in a smoking cessation trial.

Aims and Methods

Data were from a 2-site randomized controlled trial of Standard (brief counseling) versus Intensive treatment (sustained counseling plus smoking cessation medication) in individuals who smoke recently diagnosed with cancer. Participants (n = 303) reported e-cigarette use at baseline, 3 months, and 6 months. Biochemically-verified past 7-day cigarette abstinence was collected at 6 months. Qualitative interviews at 6 months explored factors related to e-cigarette use.

Results

E-cigarette use prevalence was highest between baseline and 3 months (16%) and declined over time. Participants using e-cigarettes at follow-up had higher baseline cigarette dependence and smoked more heavily. Multivariable analyses found no significant association between follow-up e-cigarette use and 6-month cigarette abstinence. E-cigarette use at follow-up was higher in the Standard versus Intensive treatment group (p = .003 and .001 at 3 and 6 mo, respectively). Smoking cessation and health concerns were primary reasons for using e-cigarettes.

Conclusions

Among individuals who smoke recently diagnosed with cancer and enrolled in a smoking cessation intervention trial, e-cigarette use during trial participation was not associated with smoking abstinence. Individuals who chose to use e-cigarettes were less likely to be receiving intensive cessation support as part of the trial. Further studies are needed to evaluate the association between e-cigarette use and smoking cessation in cancer patients.

Implications

E-cigarette use was not associated with cigarette abstinence at 6 months among adults who smoke recently diagnosed with cancer enrolled in a smoking cessation trial. Individuals with easier access to evidence-based smoking cessation treatment may be less likely to use e-cigarettes.
Failure and Complication Rates in Common Sports and Arthroscopic Procedures: Reality Check
Authors: Taylor Mathew Z. , Caldwell Paul E. , Pearson Sara E.
Published: February 2022

Expectations following sports medicine and arthroscopic procedures have been elevated because of captivating modern-day media coverage of high-profile athletic injuries, surgery, and rapid return to sports. Unfortunately, this general perception may be misleading, and orthopedic sports medicine physicians must be aware of the harsh reality of the trials and tribulations associated with the subspecialty. The purpose of this review article is to provide an updated brief overview of the complications and failure rates associated with common arthroscopic procedures including rotator cuff repair, biceps tenodesis, Bankart procedure, Latarjet procedure, anterior cruciate ligament reconstruction, anterior cruciate ligament repair, meniscal repair, tibial tubercle osteotomy, and medial patellofemoral ligament reconstruction. Highlighting the complications is the first step toward early recognition, enhancing preventative measures, and successful management.
Profiling of the full-length transcriptome in abdominal aortic aneurysm using nanopore-based direct RNA sequencing
Authors: Xin Hai , He Xingqiang , Li Jun , Guan Xiaomei , Liu Xukui , Wang Yuewei , Niu Liyuan , Qiu Deqiang , Wu Xuejun , Wang Haofu
Published: February 2022

Abdominal aortic aneurysm (AAA) is a common and serious disease with a high mortality rate, but its genetic determinants have not been fully identified. In this feasibility study, we aimed to elucidate the transcriptome profile of AAA and further reveal its molecular mechanisms through the Oxford Nanopore Technologies (ONT) MinION platform. Overall, 9574 novel transcripts and 781 genes were identified by comparing and analysing the redundant-removed transcripts of all samples with known reference genome annotations. We characterized the alternative splicing, alternative polyadenylation events and simple sequence repeat (SSR) loci information based on full-length transcriptome data, which would help us further understand the genome annotation and gene structure of AAA. Moreover, we proved that ONT methods were suitable for the identification of lncRNAs via identifying the comprehensive expression profile of lncRNAs in AAA. The results of differentially expressed transcript (DET) analysis showed that a total of 7044 transcripts were differentially expressed, of which 4278 were upregulated and 2766 were downregulated among two groups. In the KEGG analysis, 4071 annotated DETs were involved in human diseases, organismal systems and environmental information processing. These pilot findings might provide novel insights into the pathogenesis of AAA and provide new ideas for the optimization of personalized treatment of AAA, which is worthy of further study in subsequent studies.
Recurrence of COVID-19 associated with reduced T-cell responses in a monozygotic twin pair
Authors: de Castro Mateus V. , Santos Keity S. , Apostolico Juliana S. , Fernandes Edgar R. , Almeida Rafael R. , Levin Gabriel , Magawa Jhosiene Y. , Nunes João Paulo S. , Bruni Mirian , Yamamoto Marcio M. , Lima Ariane C. , Silva Monize V. R. , Matos Larissa R. B. , Coria Vivian R. , Castelli Erick C. , Scliar Marilia O. , Kuramoto Andreia , Bruno Fernanda R. , Jacintho Lucas C. , Nunes Kelly , Wang Jaqueline Y. T. , Coelho Veronica P. , Neto Miguel Mitne , Maciel Rui M. B. , Naslavsky Michel S. , Passos-Bueno Maria Rita , Boscardin Silvia B. , Rosa Daniela S. , Kalil Jorge , Zatz Mayana , Cunha-Neto Edecio
Published: February 2022

Recurrence of COVID-19 in recovered patients has been increasingly reported. However, the immune mechanisms behind the recurrence have not been thoroughly investigated. The presence of neutralizing antibodies (nAbs) in recurrence/reinfection cases suggests that other types of immune response are involved in protection against recurrence. Here, we investigated the innate type I/III interferon (IFN) response, binding and nAb assays and T-cell responses to severe acute respiratory distress syndrome coronavirus 2 (SARS-CoV-2) with IFN gamma (IFN
γ
) enzyme-linked spot assay (ELISPOT) in three pairs of young adult monozygotic (MZ) twins with previous confirmed COVID-19, one of them presenting a severe recurrence four months after the initial infection. Twin studies have been of paramount importance to comprehend the immunogenetics of infectious diseases. Each MZ twin pair was previously exposed to SARS-CoV-2, as seen by clinical reports. The six individuals presented similar overall recovered immune responses except for the recurrence case, who presented a drastically reduced number of recognized SARS-CoV-2 T-cell epitopes on ELISPOT as compared to her twin sister and the other twin pairs. Our results suggest that the lack of a broad T-cell response to initial infection may have led to recurrence, emphasizing that an effective SARS-CoV-2-specific T-cell immune response is key for complete viral control and avoidance of clinical recurrence of COVID-19.
A pseudotyped lentivirus-based assay to titer SARS-CoV-2 neutralizing antibodies in Mexico
Authors: Cruz-Cardenas José Antonio , Gutierrez-Mayret Michelle , López-Arredondo Alejandra , Castañeda-Delgado Julio Enrique , Rojas-Martinez Augusto , García-Rivas Gerardo , Enciso-Moreno José Antonio , Palomares Laura A. , Brunck Marion E. G.
Published: February 2022

Measuring the neutralizing potential of SARS-CoV-2 antigens-exposed sera informs on effective humoral immunity. This is relevant to 1-monitor levels of protection within an asymptomatic population, 2-evaluate the efficacy of existing and novel vaccines against emerging variants, 3-test prospective therapeutic monoclonal neutralizing antibodies (NAbs) and, overall, to contribute to understand SARS-CoV-2 immunity. However, the gold-standard method to titer NAbs is a functional assay of virus-mediated infection, which requires biosafety level 3 (BSL-3) facilities. As these facilities are insufficient in Latin American countries, including Mexico, scant information has been obtained about NAb in these countries during the COVID-19 pandemic. An alternative solution to acquire NAb information locally is to use non-replicative viral particles that display the SARS-CoV-2 Spike (S) protein on their surface, and deliver a reporter gene into target cells upon transduction. Here we present the development of a NAb-measuring assay based on Nanoluc-mediated luminescence measurements from SARS-CoV-2 S-pseudotyped lentiviral particle-infected cells. The successive steps of development are presented, including lentiviral particles production, target cell selection, and TCID50 determination. We applied the optimized assay in a BSL-2 facility to measure NAbs in 15 pre-pandemic, 18 COVID-19 convalescent and 32 BNT162b2 vaccinated serum samples, which evidenced the assay with 100% sensitivity, 86.6% specificity and 96% accuracy. The assay highlighted heterogeneity in neutralization curves which are relevant in discussing neutralization potency dynamics. Overall, this is the first report of a BSL-2 safe functional assay to measure SARS-CoV-2 in Mexico and a cornerstone methodology necessary to measure NAb with a functional assay in the context of limited resources settings.

Importance

Evaluating effective humoral immunity against SARS-CoV-2 requires a functional assay with infectious virus. Handling the authentic SARS-CoV-2 virus requires specialized facilities that are not readily available in Latin America, including Mexico. Here we produce non-replicative viral particles pseudotyped with the SARS-CoV-2 S protein that are used as safe surrogate viral particles in an optimized BSL-2 ready neutralization assay. The establishment of this assay is critical to allow the evaluation of effective humoral immunity to SARS-CoV-2 post-infection and to monitor the efficacy of existing or novel vaccines against emerging variants in the Mexican population.
Zero-COVID Policies: Melbourne’s 112-Day Hard Lockdown Experiment Harmed Mostly Mothers
Authors: Schurer Stefanie , Atalay Kadir , Glozier Nick , Vera-Toscano Esperanza , Wooden Mark
Published: February 2022

Lockdowns were used worldwide to mitigate the spread of SARS-CoV-2. We demonstrate that the 112-day hard lockdown in Melbourne, Australia, the longest among OECD jurisdictions, exclusively penalized families with young children. To identify the causal impact of lockdown, we interrogated nationally-representative longitudinal survey data and exploited quasi- experimental variation in Melbourne’s lockdown, one that left other jurisdictions unaffected. Using difference-in-differences estimation, we found that, surprisingly, most vulnerable groups (the young, poor, lonely and those with previous mental health conditions) were left unscathed. However, we found mothers experienced significant, sizable declines in health and work hours, and increases in loneliness, despite feeling safer and being more active. Zero-COVID policies are not as harmful as may have been expected but came at high cost to mothers in society.

One-Sentence Summary:

Melbourne’s hard lockdown left most vulnerable groups unscathed but led to greater ill- health and loneliness in mothers.
Deep proteome analysis of plasma reveals novel biomarkers of mild cognitive impairment and Alzheimer’s disease: A longitudinal study
Authors: Kaur Gurjeet , Poljak Anne , Sachdev Perminder
Published: February 2022

Ageing is the primary risk factor for AD; however, there is a poor understanding of the biological mechanisms by which the ageing process contributes to the development of AD in some individuals, while others progress to advanced age with relatively little AD neuropathology. To halt the progression of AD, the preclinical stage of neurodegeneration (before the onset of clinical symptoms) is anticipated to be the more effective time point for applying potentially disease-modifying interventions in AD. The main objective of this study was to understand the age and disease related proteomic changes are detectable in plasma, based on retrospective analysis of longitudinal data and cross-sectional analyses of clinically diagnosed cases. We conducted an in-depth plasma proteomics analysis using intensive depletion of high-abundant plasma proteins using the Agilent multiple affinity removal liquid chromatography (LC) column-Human 14 (Hu14) followed by sodium dodecyl sulfate-polyacrylamide gel electrophoresis (SDS PAGE) technique. In this study, we have begun to address the following questions; (1) differences in plasma proteomic profiles between normal ageing, vs ageing with progress to cognitive decline (MCI) or disease (dementia, probable AD), (2) cross-sectional analysis of baseline data, when all subjects are clinically identified as cognitively normal, provides insight into the preclinical changes which precede subsequent progression to AD and potentially provide early biomarkers, and (3) comparison of plasma at the point of progression to clinically diagnosed onset of cognitive decline or AD, can provide potential plasma biomarkers to facilitate clinical diagnosis. Furthermore, our findings also identified some proteins previously discovered in AD CSF and brain proteomics signatures that could provide clinically meaningful information. We identified differentially expressed proteins which were associated with several biological and molecular processes that may serve as therapeutic targets and fluid biomarkers for the disease.
Inside-out tracking and projection mapping for robot-assisted transcranial magnetic stimulation
Authors: Liu Yihao , Liu Shuya (Joshua) , Sefati Shahriar , Tian Jing , Kheradmand Amir , Armand Mehran
Published: February 2022

Transcranial Magnetic Stimulation (TMS) is a neurostimulation technique based on the principle of electromagnetic induction of an electric field in the brain with both research and clinical applications. To produce an optimal neuro-modulatory effect, the TMS coil must be placed on the head and oriented accurately with respect to the region of interest within the brain. A robotic method can enhance the accuracy and facilitate the procedure for TMS coil placement. This work presents two system improvements for robot-assisted TMS (RA-TMS) application. Previous systems have used outside-in tracking method where a stationary external infrared (IR) tracker is used as a reference point to track the head and TMS coil position. This method is prone to losing track of the coil or the head if the IR camera is blocked by the robotic arm during its motion. To address this issue, we implemented an inside-out tracking method by mounting a portable IR camera on the robot end-effector. This method guarantees that the line of sight of the IR camera is not obscured by the robotic arm at any time during its motion. We also integrated a portable projection mapping device (PPMD) into the RA-TMS system to provide visual guidance during TMS application. PPMD can track the head via an IR tracker, and can project a planned contact point of the TMS coil on the head or overlay the underlying brain anatomy in real-time.
Blood Gene Expression Risk Profiles and Interstitial Lung Abnormalities: COPDGene and ECLIPSE cohort studies
Authors: Moll Matthew , Hobbs Brian D. , Menon Aravind , Ghosh Auyon J. , Putman Rachel K. , Hino Takuya , Hata Akinori , Silverman Edwin K. , Quackenbush John , Castaldi Peter J. , Hersh Craig P. , McGeachie Michael J. , Sin Don D. , Tal-Singer Ruth , Nishino Mizuki , Hatabu Hiroto , Hunninghake Gary M. , Cho Michael H.
Published: February 2022

Rationale

Interstitial lung abnormalities (ILA) are radiologic findings that may progress to idiopathic pulmonary fibrosis (IPF). Blood gene expression profiles can predict IPF mortality, but whether these same genes associate with ILA and ILA outcomes is unknown.

Objectives

To evaluate if a previously described blood gene expression profile associated with IPF mortality is associated with ILA and all-cause mortality.

Methods

In COPDGene and ECLIPSE study participants with visual scoring of ILA and gene expression data, we evaluated the association of a previously described IPF mortality score with ILA and mortality. We also trained a new ILA score, derived using genes from the IPF score, in a subset of COPDGene. We tested the association with ILA and mortality on the remainder of COPDGene and ECLIPSE.

Measurements and Main Results

In 1,469 COPDGene (training n=734; testing n=735) and 571 ECLIPSE participants, the IPF score was not associated with ILA or mortality. However, an ILA score derived from IPF score genes was associated with ILA (meta-analysis of test datasets OR 1.4 [95% CI: 1.2-1.6]) and mortality (HR 1.25 [95% CI: 1.12-1.41]). Six of the 11 genes in the ILA score had discordant directions of effects compared to the IPF score. The ILA score partially mediated the effects of age on mortality (11.8% proportion mediated).

Conclusions

An ILA gene expression score, derived from IPF mortality-associated genes, identified genes with concordant and discordant effects on IPF mortality and ILA. These results suggest shared, and unique biologic processes, amongst those with ILA, IPF, aging, and death.

Key messages

What is the key question

Interstitial lung abnormalities (ILA) are radiologic findings that may progress to idiopathic pulmonary fibrosis (IPF). Do blood gene expression profiles that predict IPF mortality also associate with ILA?

What is the bottom line

An ILA gene expression score, derived from IPF mortality-associated genes, was associated with ILA and all-cause mortality. This score identified genes with concordant and discordant effects on IPF mortality and ILA. Our results suggest shared, and unique biologic processes, amongst those with ILA, IPF, aging, and death.

Why read on

Our results lend insight into how gene expression profiles and biological pathways associated with IPF prognosis relate to ILA and all-cause mortality
Vaginal microbiome is associated with endometrial cancer grade and histology
Authors: Hakimjavadi Hesamedin , George Sophia , Taub Michael , Dodds Leah , Sanchez-Covarrubias Alex , Huang Marilyn , Pearson Matthew , Slomovitz Brian , Kobetz Erin , Gharaibeh Raad Z. , Sowamber Ramlogan , Pinto Andre , Chamala Srikar , Schlumbrecht Matthew
Published: February 2022

Background

The vaginal microbiome is an underexplored environment which may yield insights about endometrial cancer (EC) pathophysiology and serve as an early marker of disease. Our objective was to evaluate the preoperative vaginal microbiome in women undergoing hysterectomy for benign conditions and EC to identify patterns which could segregate benign disease from EC, and to assess if the microbiome distinguishes low-grade (LG) from high-grade (HG) histologies.

Methods

Vaginal microbiome samples were prospectively collected at the time of hysterectomy, and clinicopathologic data collected. Extracted DNA underwent shotgun metagenomics sequencing. Microbial diversity was calculated using the Shannon Index (α-diversity) and PERMANOVA (β-diversity). Hierarchical clustering was used to describe community state types (CST), which were then compared by microbial diversity and grade. Machine learning was utilized to assess the predictive value of grade and histology based on relative bacterial abundance.

Results

61 patients participated: 1) benign gynecologic disease (n=11), 2) LG EC (n=30), and 3) HG EC (n=20). 40 (62.5%) were White, 22 (34.3%) were Black, and 37 (57.8%) were Hispanic. Both α- and β-diversity were associated with tumor grade (p□=□0.026 and p□=□0.035, respectively). Four CST were identified that associated with grade of disease (p=0.036). Different histologies demonstrated variation in CST even within tumor grades (p=0.017). Markers at the species level informed models that predicted benign vs cancer (AUC 0.878), HG versus benign (AUC=0.803), and HG versus LG (AUC=0.771) with high accuracy.

Conclusions

The vaginal microbiome segregates benign disease from EC, and is predictive of histology and grade, suggesting it may be an effective tool for screening.
Metabolic switch in the aging astrocyte supported via integrative approach comprising network and transcriptome analyses
Authors: Acevedo Alejandro , Torres Felipe , Kiwi Miguel , Baeza-Lehnert Felipe , Felipe Barros L. , Lee-Liu Dasfne , González-Billault Christian
Published: February 2022

Dysregulated central-energy metabolism is a hallmark of brain aging. Supplying enough energy for neurotransmission relies on the neuron-astrocyte metabolic network. To identify genes contributing to age-associated brain functional decline, we formulated an approach to analyze the metabolic network by integrating flux, network structure and transcriptomic databases of neurotransmission and aging. Our findings support that during brain aging: 1) The astrocyte undergoes a metabolic switch from aerobic glycolysis to oxidative phosphorylation, decreasing lactate supply to the neuron, while the neuron suffers intrinsic energetic deficit by downregulation of Krebs cycle genes, including mdh1 and mdh2 (Malate-Aspartate Shuttle); 2) Branched-chain amino acid degradation genes were downregulated, identifying dld as a central regulator; 3) Ketone body synthesis increases in the neuron, while the astrocyte increases their utilization, in line with neuronal energy deficit in favor of astrocytes. We identified candidates for preclinical studies targeting energy metabolism to prevent age-associated cognitive decline.
GLMsingle: a toolbox for improving single-trial fMRI response estimates
Authors: Prince Jacob S. , Charest Ian , Kurzawski Jan W. , Pyles John A. , Tarr Michael J. , Kay Kendrick N.
Published: February 2022

Advances in modern artificial intelligence (AI) have inspired a paradigm shift in human neuroscience, yielding large-scale functional magnetic resonance imaging (fMRI) datasets that provide high-resolution brain responses to tens of thousands of naturalistic visual stimuli. Because such experiments necessarily involve brief stimulus durations and few repetitions of each stimulus, achieving sufficient signal-to-noise ratio can be a major challenge. We address this challenge by introducing GLMsingle, a scalable, user-friendly toolbox available in MATLAB and Python that enables accurate estimation of single-trial fMRI responses (glmsingle.org). Requiring only fMRI time-series data and a design matrix as inputs, GLMsingle integrates three techniques for improving the accuracy of trial-wise general linear model (GLM) beta estimates. First, for each voxel, a custom hemodynamic response function (HRF) is identified from a library of candidate functions. Second, cross-validation is used to derive a set of noise regressors from voxels unrelated to the experimental paradigm. Third, to improve the stability of beta estimates for closely spaced trials, betas are regularized on a voxel-wise basis using ridge regression. Applying GLMsingle to the Natural Scenes Dataset and BOLD5000, we find that GLMsingle substantially improves the reliability of beta estimates across visually-responsive cortex in all subjects. Furthermore, these improvements translate into tangible benefits for higher-level analyses relevant to systems and cognitive neuroscience. Specifically, we demonstrate that GLMsingle: (i) improves the decorrelation of response estimates between trials that are nearby in time; (ii) enhances representational similarity between subjects both within and across datasets; and (iii) boosts one-versus-many decoding of visual stimuli. GLMsingle is a publicly available tool that can significantly improve the quality of past, present, and future neuroimaging datasets that sample brain activity across many experimental conditions.
Genetic diversity analysis and characterization of Ugandan sorghum
Authors: Chakrabarty Subhadra , Mufumbo Raphael , Windpassinger Steffen , Jordan David , Mace Emma , Snowdon Rod J. , Hathorn Adrian
Published: February 2022

The National Genebank of Uganda houses diverse and rich Sorghum bicolor germplasm collection. This genetic diversity resource is untapped, under-utilized and has not been systematically incorporated into sorghum breeding programs. In this study, we characterized the germplasm collection using whole genome SNP markers. Discriminant analysis of principal components (DAPC) was implemented to study racial ancestry of the accessions in comparison to a global sorghum diversity set and characterize sub-groups and admixture in the Ugandan germplasm. Genetic structure and phylogenetic analysis was conducted to identify distinct genotypes in the Ugandan collection and relationships among groups. Furthermore, in a case study for identification of potentially useful adaptive trait variation for breeding, we performed genome-wide association studies for juvenile cold tolerance. Genomic regions potentially involved in adaptation of Ugandan sorghum varieties to cooler climatic conditions were identified that could be of interest for expansion of sorghum production into temperate latitudes. The study demonstrates how genebank genomics can potentially facilitate effective and efficient usage of valuable, untapped germplasm collections for agronomic trait evaluation and subsequent allele mining.
The effect of treatment of auxin producing bacterial culture supernatant in combination with organic and inorganic fertilizers
Authors: Park Seunghye , Shin Ji-Hwan
Published: February 2022

Bacteria that secret plant growth promoting substances are good candidate for field application to improve crop yield. Especially, bacteria that excrete auxin can enhance root growth and settlement of crops to help adapting new soil environment when transplanted. In this study, we applied culture supernatant of an auxin producing bacteria Ignatzschineria sp. CG20001. The bacterial culture supernatant (BCS) was applied in combination with chicken manure and liquid chemical fertilizer. The treatment of bacterial culture supernatant enhanced growth of red kohlrabi, Brassica oleraceae var. gongyloides, especially in combination with chicken manure. To understand mechanisms related higher growth, we compared photosynthetic efficiency by measuring chlorophyll fluorescence and light harvesting antenna pigments composition. The performance index PS II was higher in BCS treated plants, and recovered faster after leaf harvest. Photoprotective mechanism was also increased in BCS treated plants, however, and DTT infiltration, non-photochemical quenching (NPQ) reduced to similar level, implying higher xanthophyll cycle dependent NPQ induction mechanism in BCS treated plants. However, in liquid chemical fertilized plants, BCS treated and non-treated plants showed the opposite pattern in the change of NPQ. The chlorophyll a/b ratio was highest in no-fertilized non-treated control, and lowest in chicken manure and BCS combination, implying impact of nutrition availability between the two groups. Through these results, we conclude that the appropriate combination of organic fertilizer and plant growth promoting bacterial metabolite can improve plant growth more than chemical fertilizers. This study also provides physiological understanding for strategic fertilization regime of organic fertilizer and biofertilizer combination.
Robust deep learning object recognition models rely on low frequency information in natural images
Authors: Li Zhe , Caro Josue Ortega , Rusak Evgenia , Brendel Wieland , Bethge Matthias , Anselmi Fabio , Patel Ankit B. , Tolias Andreas S. , Pitkow Xaq
Published: February 2022

Machine learning models have difficulty generalizing to data outside of the distribution they were trained on. In particular, vision models are usually vulnerable to adversarial attacks or common corruptions, to which the human visual system is robust. Recent studies have found that regularizing machine learning models to favor brain-like representations can improve model robustness, but it is unclear why. We hypothesize that the increased model robustness is partly due to the low spatial frequency preference inherited from the neural representation. We tested this simple hypothesis with several frequency-oriented analyses, including the design and use of hybrid images to probe model frequency sensitivity directly. We also examined many other publicly available robust models that were trained on adversarial images or with data augmentation, and found that all these robust models showed a greater preference to low spatial frequency information. We show that preprocessing by blurring can serve as a defense mechanism against both adversarial attacks and common corruptions, further confirming our hypothesis and demonstrating the utility of low spatial frequency information in robust object recognition.
Evaluation of taxonomic classification and profiling methods for long-read shotgun metagenomic sequencing datasets
Authors: Portik Daniel M. , Brown C. Titus , Pierce-Ward N. Tessa
Published: February 2022

Background

Long-read shotgun metagenomic sequencing is gaining in popularity and offers many advantages over short-read sequencing. The higher information content in long reads is useful for a variety of metagenomics analyses, including taxonomic classification and profiling. The development of long-read specific tools for taxonomic classification is accelerating, yet there is a lack of information regarding their relative performance. Here, we perform a critical benchmarking study using 11 methods, including five methods designed specifically for long reads. We applied these tools to several mock community datasets generated using Pacific Biosciences (PacBio) HiFi or Oxford Nanopore Technology (ONT) sequencing, and evaluated their performance based on read utilization, detection metrics, and relative abundance estimates.

Results

Our results show that long-read classifiers generally performed best. Several short-read classification and profiling methods produced many false positives (particularly at lower abundances), required heavy filtering to achieve acceptable precision (at the cost of reduced recall), and produced inaccurate abundance estimates. By contrast, two long-read methods (BugSeq, MEGAN-LR & DIAMOND) and one generalized method (sourmash) displayed high precision and recall without any filtering required. Furthermore, in the PacBio HiFi datasets these methods detected all species down to the 0.1% abundance level with high precision. Some long-read methods, such as MetaMaps and MMseqs2, required moderate filtering to reduce false positives to resemble the precision and recall of the top-performing methods. We found read quality affected performance for methods relying on protein prediction or exact k-mer matching, and these methods performed better with PacBio HiFi datasets. We also found that long-read datasets with a large proportion of shorter reads (<2kb length) resulted in lower precision and worse abundance estimates, relative to length-filtered datasets. Finally, for classification methods, we found that the long-read datasets produced significantly better results than short-read datasets, demonstrating clear advantages for long-read metagenomic sequencing.

Conclusions

Our critical assessment of available methods provides best-practice recommendations for current research using long reads and establishes a baseline for future benchmarking studies.
JUN Regulation of Injury-induced Enhancers in Schwann Cells
Authors: Ramesh Raghu , Manurung Yanti , Ma Ki H. , Blakely Todd , Won Seongsik , Wyatt Eugene , Awatramani Rajeshwar , Svaren John
Published: February 2022

Schwann cells play a critical role after peripheral nerve injury by clearing myelin debris, forming axon-guiding Bands of Bungner, and re-myelinating regenerating axons. Schwann cells undergo epigenomic remodeling to differentiate into a repair state that expresses unique genes, some of which are not expressed at other stages of Schwann cell development. We previously identified a set of enhancers that are activated in Schwann cells after nerve injury, and we determined if these enhancers are pre-programmed into the Schwann cell epigenome as poised enhancers prior to injury. Poised enhancers share many attributes of active enhancers, such as open chromatin, but are marked by repressive H3K27 trimethylation (H3K27me3) rather than H3K27ac. We find that most injury-induced enhancers are not marked as poised enhancers prior to injury indicating that injury-induced enhancers are not pre-programmed in the Schwann cell epigenome. Injury-induced enhancers are enriched with AP-1 binding motifs, and the c-JUN subunit of AP-1 had been shown to be critical to drive the transcriptional response of Schwann cells after injury. Using in vivo ChIP-seq analysis we find that c-JUN binds to a subset of injury-induced enhancers. To test the role of specific injury-induced enhancers, we focused on c-JUN-binding enhancers upstream of the Sonic Hedgehog (Shh) gene, which is only upregulated in repair Schwann cells compared to other stages of Schwann cell development. We confirm that c-JUN regulates these enhancers and also show that the enhancers are required for robust induction of the Shh gene after injury.

Significance Statement

The pro-regenerative actions of Schwann cells after nerve injury depends on upon profound reprogramming of the epigenome. The repair state is directed by injury-induced transcription factors, like JUN, which is uniquely required after nerve injury. In this study, we test whether the injury program is pre-programmed into the epigenome as poised enhancers and define which enhancers bind JUN. Finally, we test the roles of these enhancers by performing CRISPR-mediated deletion of JUN-bound injury enhancers in the Sonic hedgehog gene. While many long range enhancers drive expression of Sonic hedgehog at different developmental stages of specific tissues, these studies identify an entirely new set of enhancers that are required for Sonic hedgehog induction in Schwann cells after injury.
Soil amendments and suppression of Phytophthora root rot in avocado (Persea indica)
Authors: Farooq Qurrat Ul Ain , McComb Jen , Hardy Giles StJ. , Burgess Treena
Published: February 2022

The ability of microbial or mineral-based soil additives to suppress root rot caused by Phytophthora cinnamomi was assessed. Phosphite and metalaxyl treatments for the control of disease, and glyphosate for weed control were also assessed. A treatment simulating avocado orchard conditions had chicken manure, wood mulch, and mulch from beneath trees in an avocado orchard added to the pots. Soil treatments (three probiotic and two mineral-based) were applied to 9-month-old saplings growing in containers in a glasshouse. After one-month, half of the plants of each treatment were inoculated with the pathogen. Three months after inoculation, plants were harvested and plant growth and root damage were measured. In the first experiment infestation with P. cinnamomi significantly reduced fine root dry weight in all plants except those in soil treated with one silicon-based mineral mulch. Visible root damage was higher in plants treated with probiotics. In this experiment, and in a repeat experiment the reduction of fine root damage achieved by spraying plants with phosphite or addition of a silica based mineral mulch was similar. Phosphite was preferable to metalaxyl as a chemical treatment, as the latter reduced shoot and root growth of non-infected plants. Glyphosate treatment of wheat seedlings growing in the pots with the avocados reduced shoot and fine root growth of both non-infected and infected plants. These observations need to be confirmed under field conditions.
mSigHdp: hierarchical Dirichlet process mixture modeling for mutational signature discovery
Authors: Liu Mo , Wu Yang , Jiang Nanhai , Boot Arnoud , Rozen Steven G.
Published: February 2022

Mutational signatures are characteristic patterns of mutations caused by endogenous or exogenous mutational processes. These signatures can be discovered by analyzing mutations in large sets of samples – usually somatic mutations in tumor samples. Most programs for discovering mutational signatures are based on non-negative matrix factorization (NMF). Alternatively, signatures can be discovered using hierarchical Dirichlet process (HDP) mixture models, an approach that has been explored less. These models assign mutations to clusters and view each cluster as being generated from the signature of a particular mutational process. Here we describe mSigHdp, an improved approach to using HDP mixture models to discover mutational signatures. We benchmarked mSigHdp and state-of-the-art NMF-based approaches on 4 realistic synthetic data sets. These data sets encompassed 18 cancer types. In total they contained 3.5×107single-base-substitution mutations representing 32 signatures and 6.1×106small-insertion-and-deletion mutations representing 13 signatures. For 3 of the 4 data sets, mSigHdp had the best positive predictive value for discovering mutational signatures, and for all 4 data sets, it had the best true positive rate. Its CPU usage was similar to that of the NMF-based approaches. Thus, mSigHdp is an important and practical addition to the set of tools available for discovering mutational signatures.

Data and code availability

mSigHdp is available at public repositorieshttps://github.com/steverozen/mSigHdpandhttps://github.com/steverozen/hdpx. The synthetic data, code for generating the synthetic data, code for running the mutational-signature discovery programs, the main outputs of the programs, and code for analyzing their results and for generating the data figures in this paper are available athttps://github.com/Rozen-Lab/mSigHdpsup files. A singularity container with mSigHdp can be downloaded from cloud.sylabs.io with the shell command “singularity pull library://rozen-lab/msighdp/msighdp:2.1.2”. A toy-example Rscript for using this container is athttps://github.com/steverozen/mSigHdp/blob/master/data-raw/container_scripts/test_mSigHdp.R.

Supplementary material

One excel file of supplementary tables and one PDF file of supplementary figures have been submitted along with this manuscript.