bluuebunny/crossref_metadata_2025 huggingface dataset:
Antiviral defence systems in the rumen microbiome
Authors: Sáenz Johan S. , Rios-Galicia Bibiana , Seifert Jana
Published: April 2024

The continuous interaction between phages and their respective hosts has resulted in the evolution of multiple bacterial immune mechanism. However, the diversity and prevalence of antiviral defence systems in complex communities is still unknown. We therefore investigated the diversity and abundance of viral defence systems in 3038 high-quality bacterial and archaeal genomes from the rumen. In total, 14,241 defence systems and 31,948 antiviral-related genes were identified. Those genes represented 114 unique system types grouped into 49 families. We observed a high prevalence of defence systems in the genomes. However, the number of defence systems, defence system families and systems density varied widely from genome to genome. Additionally, the number of defence system correlated positively with the number of defence systems families and the genome size. Restriction modification, Abi and cas system families were the most common, but many rare systems were present in only 1% of the genomes. Antiviral defence systems are prevalent and diverse in the rumen, but only a few are dominant, indicating that most systems are rarely present. However, the collection of systems throughout the rumen may represent a pool of mechanisms that can be shared by different members of the community and modulate the phage-host interaction.

Importance

Phages may act antagonistically at the cell level but have a mutualistic interaction at the microbiome level. This interaction shapes the structure of microbial communities and is mainly driven by defence mechanism. However, the diversity of such mechanism is larger than previously thought. Because of that, we described the abundance and diversity of antiviral defence system of a collection of genomes, from the rumen. While defence mechanisms seem to be prevalent among bacteria and archaea, only a few were common. This suggests that most of these defence mechanisms are not present in many rumen microbes but could be shared among different members of the microbial community. This aligned with the ’pan-immune system’ model, which appears to be common across different environments.
lute: estimating the cell composition of heterogeneous tissue with varying cell sizes using gene expression
Authors: Maden Sean K , Huuki-Myers Louise A , Kwon Sang Ho , Collado-Torres Leonardo , Maynard Kristen R , Hicks Stephanie C
Published: April 2024

Relative cell type fraction estimates in bulk RNA-sequencing data are important to control for cell composition differences across heterogenous tissue samples. Current computational tools estimate relative RNA abundances rather than cell type proportions in tissues with varying cell sizes, leading to biased estimates. We present lute, a computational tool to accurately deconvolute cell types with varying sizes. Our software wraps existing deconvolution algorithms in a standardized framework. Using simulated and real datasets, we demonstrate how lute adjusts for differences in cell sizes to improve the accuracy of cell composition. Software is available from https://bioconductor.org/packages/lute.
Structural Models for a Series of Allosteric Inhibitors of IGF1R Kinase
Authors: Verma Jyoti , Vashisth Harish
Published: April 2024

The allosteric inhibition of Insulin-like Growth Factor Receptor 1 Kinase (IGF1RK) is a potential strategy to overcome selectivity barriers in targeting receptor tyrosine kinases. We constructed structural models of a series of 12 indole-butyl-amine derivatives which have been reported as allosteric inhibitors of IGF1RK. We further studied dynamics and interactions of each inhibitor in the allosteric pocket via all-atom explicit-solvent molecular dynamics (MD) simulations. We discovered that a bulky carbonyl substitution at the R1 indole ring is structurally unfavorable for inhibitor binding in the IGF1RK allosteric pocket. Moreover, we found that the most potent derivative (termed C11) acquires a distinct conformation, forming an allosteric pocket channel with better shape complementarity and interactions with the receptor. In addition to a hydrogen bonding interaction with V1063, the cyano derivative C11 forms a stable hydrogen bond with M1156, which is responsible for its unique binding conformation in the allosteric pocket. Our findings show that the position of chemical substituents at the R1 indole ring with different pharmacophore features influences molecular interactions and binding conformations of the indole-butyl-amine derivatives, hence dramatically affecting their potencies. Our results provide a structural framework for the design of allosteric inhibitors with improved affinities and specificities against IGF1RK.
BindCompare: A Novel Integrated Protein-Nucleic Acid Binding Analysis Platform
Authors: Mahableshwarkar Pranav , Shum Jasmine , Ray Mukulika , Larschan Erica
Published: April 2024

Advanced genomic technologies have generated thousands of Protein-Nucleic acid binding datasets that have the potential to identify testable gene regulatory network (GRNs) models governed by combinatorial associations between factors. Transcription factors (TFs) and RNA binding proteins (RBPs) are nucleic-acid binding proteins regulating gene expression and are key drivers of GRN function. However, the combinatorial mechanisms by which the interactions between specific TFs and RBPs regulate gene expression remain largely unknown. To identify possible combinations of TFs and RBPs that may function together, developing a tool that compares and contrasts the interactions of multiple TFs and RBPs with nucleic acids to identify their common and unique targets is necessary. Therefore, we introduce BindCompare, a user-friendly tool that can be run locally to predict new combinatorial relationships between TFs and RBPs. BindCompare can analyze data from any organism with known annotated genome information and outputs files with detailed genomic locations and gene information for targets for downstream analysis. Overall, BindCompare is a new tool that identifies TFs and RBPs that co-bind to the same DNA and/or RNA loci, generating testable hypotheses about their combinatorial regulation of target genes.

Availability and Implementation

BindCompare is an open-source package that is available on the Python Packaging Index (PyPI,https://pypi.org/project/bindcompare/) with the source code available on GitHub (https://github.com/pranavmahabs/bindcompare). Complete documentation for the package can be found at both of these links.
Single-cell RNA-Seq data have prevalent blood contamination but can be rescued by Originator, a computational tool separating single-cell RNA-Seq by genetic and contextual information
Authors: Unjitwattana Thatchayut , Huang Qianhui , Yang Yiwen , Tao Leyang , Yang Youqi , Zhou Mengtian , Du Yuheng , Garmire Lana X.
Published: April 2024

Single-cell RNA sequencing (scRNA-Seq) data from complex human tissues have prevalent blood cell contamination during the sample preparation process. They may also comprise cells of different genetic makeups. These issues demand rigorous preprocessing and filtering prior to the downstream functional analysis, to avoid biased conclusions due to cell types not of interest. Towards this, we propose a new computational framework, Originator, which deciphers single cells by the genetic origin and separates immune cells of blood contamination from those of expected tissue-resident cells. We demonstrate the accuracy of Originator at separating immune cells from the blood and tissue as well as cells of different genetic origins, using a variety of artificially mixed and real datasets. We show the prevalence of blood contamination in scRNA-Seq data of many tissue types. We alert the significant consequences if failing to adjust for these confounders, using scRNA-Seq data of pancreatic cancer and placentas as examples.
EMERGENCE OF OXA-48-LIKE CARBAPENEMASES IN CLINICAL ENTEROBACTERALES FROM GUATEMALA
Authors: Mazariegos Carmen J. , Quinto Anna , Herrera Andres , Barillas Sara E. , Valenzuela Laura R. , Ordóñez Gabriela , Sierra Paola , Arevalo Carolina , Seah Christine , Melano Roberto G.
Published: April 2024

Five isolates (fourKlebsiella pneumoniaeand oneEscherichia coli) displaying resistance to piperacillin/tazobactam and ertapenem and reduced susceptibility to imipenem were found positive forblaOXA-48-like genes (blaOXA-181andblaOXA-232) carried on plasmids described previously. Although twoK. pneumoniaerecovered in 2020 were clonally related, the results suggest thatblaOXA-48-like genes have been circulating in Guatemala since 2019. This is the first report of this type of carbapenemase in Central America.
Transiently restricting individual amino acids protectsD. melanogasteragainst multiple stressors
Authors: Fulton Tahlia L. , Johnstone Joshua J. , Tan Jing J. , Balagopal Krithika , Dedman Amy , Johnson Travis K. , Chan Andrea Y. , Mirth Christen K. , Piper Matthew D. W.
Published: April 2024

Nutrition and resilience are linked, though it is not yet clear how diet confers stress resistance or the breadth of stressors that it can protect against. We have previously shown that transiently restricting an essential amino acid can extend lifespan and also protect against nicotine exposure inDrosophila melanogaster, raising the possibility that amino acid restriction is geroprotective because of elevated detoxification capacity. Here, we sought to characterise the nature of this dietary mediated protection, and determine whether it was sex, amino acid, and/or nicotine specific. When we compared between sexes, we found that isoleucine deprivation increases female, but not male, nicotine resistance. Surprisingly, we found that this protection afforded to females was not replicated by dietary protein restriction and was instead specific to individual amino acid restriction. Other studies have documented methionine or leucine restriction conferring stress resistance, though we previously found that individually depriving them did not increase nicotine resistance. We therefore wondered whether reducing the severity of restriction of these amino acids could confer nicotine resistance. This was true for methionine restriction, and we found that flies fed a diet containing 25% methionine for 7 days protected against subsequent nicotine poisoning (∼30% longer lived than controls with all amino acids). However, when dietary leucine was altered, nicotine resistance changed, but no single diet was protective. To understand whether these beneficial effects of diet were specific to nicotine or were generalisable across stressors, we pre-treated with amino acid restriction diets and exposed them to other types of stress. We did not find any diets that protected against heat stress or infection with the bacteriumEnterococcus faecalis. However, we found that some of the diets that protected against nicotine also protected against oxidative and starvation stress, and improved survival following cold shock. Interestingly, we found that a diet lacking isoleucine was the only diet to protect against all these stressors. These data point to isoleucine as a critical determinant of robustness in the face of environmental challenges.
Viscoelastic high-molecular-weight hyaluronic acid hydrogels support rapid glioblastoma cell invasion with leader-follower dynamics
Authors: Carvalho Emily M. , Ding Erika A. , Saha Atul , Weldy Anna , Zushin Peter-James H. , Stahl Andreas , Aghi Manish K. , Kumar Sanjay
Published: April 2024

Hyaluronic acid (HA), the primary component of brain extracellular matrix, is increasingly used to model neuropathological processes, including glioblastoma (GBM) tumor invasion. While elastic hydrogels based on crosslinked low-molecular-weight (LMW) HA are widely exploited for this purpose and have proven valuable for discovery and screening, brain tissue is both viscoelastic and rich in high-MW (HMW) HA, and it remains unclear how these differences influence invasion. To address this question, hydrogels comprised of either HMW (1.5 MDa) or LMW (60 kDa) HA are introduced, characterized, and applied in GBM invasion studies. Unlike LMW HA hydrogels, HMW HA hydrogels relax stresses quickly, to a similar extent as brain tissue, and to a greater extent than many conventional HA-based scaffolds. GBM cells implanted within HMW HA hydrogels invade much more rapidly than in their LMW HA counterparts and exhibit distinct leader-follower dynamics. Leader cells adopt dendritic morphologies, similar to invasive GBM cells observed in vivo. Transcriptomic, pharmacologic, and imaging studies suggest that leader cells exploit hyaluronidase, an enzyme strongly enriched in human GBMs, to prime a path for followers. This study offers new insight into how HA viscoelastic properties drive invasion and argues for the use of highly stress-relaxing materials to model GBM.
Determining the Young’s Modulus of the Bacterial Cell Envelope
Authors: Lee Junsung , Jha Karan , Harper Christine E. , Zhang Wenyao , Ramsukh Malissa , Bouklas Nikolaos , Dörr Tobias , Chen Peng , Hernandez Christopher J.
Published: April 2024

Bacteria experience substantial physical forces in their natural environment including forces caused by osmotic pressure, growth in constrained spaces, and fluid shear. The cell envelope is the primary load-carrying structure of bacteria, but the mechanical properties of the cell envelope are poorly understood; reports of Young’s modulus of the cell envelope ofE. coliare widely range from 2 MPa to 18 MPa. We have developed a microfluidic system to apply mechanical loads to hundreds of bacteria at once and demonstrated the utility of the approach for evaluating whole-cell stiffness. Here we extend this technique to determine Young’s modulus of the cell envelope ofE. coliand of the pathogensV. choleraeandS. aureus.An optimization-based inverse finite element analysis was used to determine the cell envelope Young’s modulus from observed deformations. The Young’s modulus of the cell envelope was 2.06 ± 0.04 MPa forE. coli, 0.84 ± 0.02 MPa forE. colitreated with a chemical known to reduce cell stiffness, 0.12 ± 0.03 MPa forV. cholerae, and 1.52 ± 0.06 MPa forS. aureus(mean ± SD). The microfluidic approach allows examining hundreds of cells at once and is readily applied to Gram-negative and Gram-positive organisms as well as rod-shaped and cocci cells, allowing further examination of the structural causes of differences in cell envelope Young’s modulus among bacteria species and strains.
Structural insights into the human P2X1 receptor and ligand interactions
Authors: Bennetts Felix M. , Venugopal Hariprasad , Glukhova Alisa , Mobbs Jesse I. , Ventura Sabatino , Thal David M.
Published: April 2024

The P2X1 receptor is a trimeric ligand-gated ion channel that plays a pivotal role in urogenital and immune functions. Consequently, it offers numerous potential indications for novel drug treatments. Unfortunately, the progress of drug discovery targeting the P2X1 receptor has been impeded by the absence of structural information. To gain deeper insights into the binding site of the P2X1 receptor, we employed cryogenic electron microscopy (cryo-EM) to elucidate the structures of the P2X1 receptor in both an ATP-bound desensitised state and an NF449-bound closed state. NF449 is a potent P2X1 receptor antagonist and engages with the receptor in a distinctive manner. To gain insights into the molecular machinery governing receptor inhibition and activation and better understand P2X1 receptor ligand subtype selectivity, critical P2X1 receptor residues involved in ligand binding were mutated. Radioligand binding assays with [3H]-α,β-methylene ATP and intracellular calcium influx were employed to assess the effect of these mutations on ligand binding and receptor activation, thereby validating key ligand-receptor interactions. This research expands our understanding of the P2X1 receptor structure at a molecular level and opens new avenues forin silicodrug design targeting the P2X1 receptor.
Effects of spontaneous mutations on survival and reproduction ofDrosophila serratainfected with Drosophila C virus
Authors: Mendel Bonita M. , Asselin Angelique K. , Johnson Karyn N. , McGuigan Katrina
Published: April 2024

The impact of selection on host immune function genes has been widely documented. However, it remains essentially unknown how mutation influences the quantitative immune traits that selection acts on. Applying a classical mutation accumulation (MA) experimental design inDrosophila serrata, we found the mutational variation in susceptibility (median time of death, LT50) to Drosophila C virus (DCV) was of similar magnitude to that reported for intrinsic survival traits. However, the mean LT50 did not change as mutations accumulated, suggestion no directional bias in mutational effects. Maintenance of genetic variance in immune function is hypothesised to be influenced by pleiotropic effects on immunity and other traits that contribute to fitness. To investigate this, we assayed female reproductive output for a subset of MA lines with relatively long or short survival times under DCV infection. Longer survival time tended to be associated with lower reproductive output, suggesting that mutations affecting susceptibility to DCV had pleiotropic effects on investment in reproductive fitness. Further studies are needed to uncover the general patterns of mutational effect on immune responses and other fitness traits, and to determine how selection might typically act on new mutations via their direct and pleiotropic effects.
Effectiveness of BNT162b2 XBB vaccine in the US Veterans Affairs Healthcare System
Authors: Caffrey Aisling R. , Appaneal Haley J. , Lopes Vrishali V. , Puzniak Laura , Zasowski Evan J. , Jodar Luis , LaPlante Kerry L. , McLaughlin John M.
Published: April 2024

Data evaluating effectiveness of XBB.1.5-adapted vaccines against JN.1-related endpoints are scarce. We performed a nationwide test-negative case-control study within the US Veterans Affairs Healthcare System to estimate vaccine effectiveness (VE) of BNT162b2 XBB.1.5-adapted vaccine compared to not receiving an XBB vaccine of any kind against COVID-19 hospitalization, emergency department or urgent care visits (ED/UC), and outpatient visits. Between September 25, 2023 and January 31, 2024, effectiveness was 24–35% during a period of JN.1 predominance and 50–61% during XBB predominance across all outcomes. VE within 60 days of vaccination during the likely JN.1 period was 32% (95% confidence interval 3-52%) against hospitalization, 41% (23–54%) against ED/UC visits, and 31% (1–52%) against outpatient visits. Corresponding VE during the likely XBB period was 62% (44–74%), 52% (37–63%), and 50% (25–66%) by setting, respectively. These data underscore the importance of strain match to maximize the public health impact of COVID-19 vaccination.
Unveiling Associations Between Retinal Microvascular Architecture and Phenotypes Across Thousands of Healthy Subjects
Authors: Shapira Michal , Shilo Smadar , Talmor-Barkan Yeela , Aviv Yaron , Reisner Yotam , Godneva Anastasia , Weinberger Adina , Skaat Alon , Loewenstein Anat , Segal Eran , Rossman Hagai
Published: April 2024

Fundus imaging has emerged as a powerful tool, allowing high-resolution and non-invasive visualization of the fundus microvasculature. Recent advancements in artificial intelligence (AI) have enabled the quantification of fundus microvascular characteristics, paving the way for the development of predictive markers for systemic conditions. In this study, we characterize the fundus microvasculature among 8467 healthy individuals, aged 40-70 years. We employ a fully automated segmentation tool to calculate 12 distinct vessel measures, including tortuosity density, vessel density, average width, fractal dimension, distance tortuosity, and curvature tortuosity for both arteries and veins. We provide reference values for these measures by age and sex, and explore the associations between these fundus vessel measures and various clinical features. Our analysis reveals numerous significant correlations, including connections between fundus arterial measures and cardiovascular measurements, lipid profile, sleep apnea indices, glycemic profile, body composition, and smoking status. This comprehensive analysis of fundus microvasculature anatomy in a large healthy population contributes to the growing field of oculomics and highlights the potential of fundus imaging for earlier detection and monitoring of systemic diseases such as metabolic syndrome, cardiovascular diseases and sleep disorders.
Analytical Validation of a Highly Accurate and Reliable Next-Generation Sequencing-Based Urine Assay
Authors: Couto-Rodriguez Mara , Danko David C , Wells Heather L , Rey Sol , Jirau Serrano Xavier , Papciak John , Combs P Ford , Fidler Gabor , Mason Christopher E. , Otto Caitlin , O’Hara Niamh B. , Nagy-Szakal Dorottya
Published: April 2024

Culture is currently the gold standard for diagnosis of urinary tract infections (UTIs); however, it has poor sensitivity detecting urogenital pathogens, especially if patients have already initiated antimicrobial therapy, or have an infection from an organism that is not commonly cultured. False negative urine culture results can lead to the inappropriate use of antimicrobial therapies or to the progression to urosepsis in high-risk patients. Though not commonly applied to urine in a clinical setting, Next-generation sequencing (NGS)-based metagenomics offer a solution as a precision diagnostic. We developed and validated BIOTIA-ID, a clinical-grade NGS-based diagnostic pipeline for the detection and identification of pathogens in urine specimens. Remnant clinical urine specimens, and contrived sterile urine spiked with common UTI pathogens, were processed with our end-to-end assay including extraction, metagenomic library preparation and Illumina NextSeq 550 sequencing. We trained and applied a bioinformatic pipeline that uses machine learning (ML) to identify pathogens. Internal controls and other quality control measures were incorporated into the process to provide rigorous and standardized results. The assay was tested on 1,470 urine specimens and achieved 99.92% sensitivity, 99.95% specificity and a limit of detection (LoD) of <25,000 CFU/mL and <5,000 CFU/mL in bacteria and fungi, respectively. Discordant results were reconciled with additional testing by target-specific qPCR or 16S Sanger sequencing; 87% of the NGS results were ultimately determined to be the correct result. Overall, these data demonstrate that BIOTIA-ID is a highly accurate clinical-grade diagnostic tool with notable advantages over current culture- based diagnostics.

Conflict of Interest Statement

MCR, DCD, HLW, SR, XJS, JP, PFC, GF, CEM, CO, NBO and DNS are employees at Biotia, Inc.
A Fast Nonparametric Sampling (NPS) Method for Time-to-Event in Individual-Level Simulation Models
Authors: Garibay-Treviño David U. , Jalal Hawre , Alarid-Escudero Fernando
Published: April 2024

Purpose

Individual-level simulation models often require sampling times to events, however efficient parametric distributions for many processes may often not exist. For example, time to death from life tables cannot be accurately sampled from existing parametric distributions. We propose an efficient nonparametric method to sample times to events that does not require any parametric assumption on the hazards.

Methods

We developed a nonparametric sampling (NPS) approach that simultaneously draws multiple time-to-event samples from a categorical distribution. This approach can be applied to univariate and multivariate processes. We discretize the entire period into equal-length time intervals and then derived the interval-specific probabilities. The times to events can then be used directly in individual-level simulation models. We compared the accuracy of our approach in sampling time-to-events from common parametric distributions, including exponential, gamma, and Gompertz. In addition, we evaluated the method’s performance in sampling age to death from US life tables and sampling times to events from parametric baseline hazards with time-dependent covariates.

Results

The NPS method estimated similar expected times to events from 1 million draws for the three parametric distributions, 100,000 draws for the homogenous cohort, 200,000 draws from the heterogeneous cohort, and 1 million draws for the parametric distributions with time-varying covariates, all in less than a second.

Conclusion

Our method produces accurate and computationally efficient samples for time-to-events from hazards without requiring parametric assumptions.
New IPECAD open-source model framework for the health technology assessment of early Alzheimer’s disease treatment: development and use cases
Authors: Handels Ron , Herring William L. , Grimm Sabine , Sköldunger Anders , Winblad Bengt , Wimo Anders , Jönsson Linus
Published: April 2024

Objectives

Market access and reimbursement decisions for new Alzheimer’s disease (AD) treatments are informed by economic evaluations. An open-source model with intuitive structure for model cross-validation can support the transparency and credibility of such evaluations. We describe the new IPECAD open-source model framework (version 2) for the health-economic evaluation of early AD treatment and use it for cross-validation and addressing uncertainty.

Methods

A cohort state transition model using a categorized composite domain (cognition and function) was developed by replicating an existing reference model and testing it for internal validity. Then, features of existing “ICER” and “AD-ACE” models assessing lecanemab treatment were implemented for model cross-validation. Additional uncertainty scenarios were performed on choice of efficacy outcome from trial, natural disease progression, treatment effect waning and stopping rules, and other methodological choices. The model is available open-source as R code, spreadsheet and web-based version viahttps://github.com/ronhandels/IPECAD.

Results

In the IPECAD model incremental life years, QALY gains and cost savings were 21-31% smaller compared to the ICER model and 36-56% smaller compared to the AD-ACE model. IPECAD model results were particularly sensitive to assumptions on treatment effect waning and stopping rules and choice of efficacy outcome from trial.

Conclusions

We demonstrated the ability of a new IPECAD opens-source model framework for researchers and decision-makers to cross-validate other (HTA submission) models and perform additional uncertainty analyses, setting an example for open science in AD decision modeling and supporting important reimbursement decisions.
An atlas of causal and mechanistic drivers of interpatient heterogeneity in glioma
Authors: Turkarslan Serdar , He Yu , Hothi Parvinder , Murie Carl , Nicolas Abran , Kannan Kavya , Park James H , Pan Min , Awawda Alaa , Cole Zachariah D , Shapiro Mark A , Stuhlmiller Timothy J , Lee Hwahyung , Patel Anoop P , Cobbs Charles , Baliga Nitin S
Published: April 2024

Grade IV glioma, formerly known as glioblastoma multiforme (GBM) is the most aggressive and lethal type of brain tumor, and its treatment remains challenging in part due to extensive interpatient heterogeneity in disease driving mechanisms and lack of prognostic and predictive biomarkers. Using mechanistic inference of node-edge relationship (MINER), we have analyzed multiomics profiles from 516 patients and constructed an atlas of causal and mechanistic drivers of interpatient heterogeneity in GBM (gbmMINER). The atlas has delineated how 30 driver mutations act in a combinatorial scheme to causally influence a network of regulators (306 transcription factors and 73 miRNAs) of 179 transcriptional “programs”, influencing disease progression in patients across 23 disease states. Through extensive testing on independent patient cohorts, we share evidence that a machine learning model trained on activity profiles of programs within gbmMINER significantly augments risk stratification, identifying patients who are super-responders to standard of care and those that would benefit from 2ndline treatments. In addition to providing mechanistic hypotheses regarding disease prognosis, the activity of programs containing targets of 2ndline treatments accurately predicted efficacy of 28 drugs in killing glioma stem-like cells from 43 patients. Our findings demonstrate that interpatient heterogeneity manifests from differential activities of transcriptional programs, providing actionable strategies for mechanistically characterizing GBM from a systems perspective and developing better prognostic and predictive biomarkers for personalized medicine.
Laboratory validation of a simplified DNA extraction protocol followed by a portable qPCR detection ofM. tuberculosisDNA suitable for point of care settings
Authors: dos Santos Soares Tainá , Bello Graziele Lima , dos Santos Petry Ianca Moraes , Nicola Maria Rita Castilho , Vitoria da Silva Larissa , Barcellos Regina Bones , Silvestri Joana Morez , Rossetti Maria Lucia , Costa Alexandre Dias Tavares
Published: April 2024

Tuberculosis, caused byMycobacterium tuberculosis, is a treatable and curable disease, and yet remains one of the leading causes of death worldwide. Diagnosis is essential to reducing the number of cases and starting treatment, but costly tests and equipments that require complex infrastructure hamper their widespread use as a tool to contain the disease in vulnerable populations as well countries lacking resources. Therefore, it becomes necessary to develop new technological approaches to molecular methods as well as screening tests that can be rapidly conducted among people presenting to a health facility to differentiate those who should have further diagnostic evaluation for TB from those who should undergo further investigation for non-TB diagnoses. The present study aimed to evaluate two experimental DNA extraction methods from clinical samples (FTA card versus sonication) followed by analysis in a portable qPCR instrument (the Q3-plus). The FTA card-based protocol showed 100% sensitivity and specificity, while the sonication protocol showed 80% sensitivity and 89% specificity when compared to the traditional gold standard culture. The portable protocol, comprised by the FTA card method and the portable instrument Q3-Plus, showed sensitivity and specificity of 92% and 61%, respectively, when compared to culture, and 75% and 81%, respectively, when compared to the standard TB case classification. The ROC curve showed an AUC of 0.78 (p<0.001) for the portable protocol and 0.93 (p<0.001) for the GeneXpert MTB/RIF. The limit of detection (LOD) forMycobacterium tuberculosis(H37Rv strain) detection in spiked samples obtained using the portable protocol (FTA card and Q3-Plus) was 19.3 CFU/mL. As an added benefit, using the FTA card facilitates sample handling, transport, and storage. It is concluded that the use of the FTA card protocol and the Q3-Plus yields similar sensitivity and specificity as the gold standard diagnostic tests and case classification. We suggest that the platform is suitable to use as a point of care tool, assisting in the screening of tuberculosis in hard-to-reach or resource-limited areas.
Classification of Schizophrenic Traits in Transcriptions of Audio Spectra from Patient Literature: Artificial Intelligence Models Enhanced by Geometric Properties
Authors: Marques Paulo César F. , Soares Lucas Rafael F. , Araujo André Victor de A. , Monteiro Arthur Ribeiro , Batista Arthur Almeida Leitão , Pimentel Túlio Farias , Calheiros Lis de Lima , Padilla Maria Helena N. S. , Pacheco André , Queda Fabio , Oliveira João Ricardo M. , Filho José Luiz de Lima , Bocanegra Silvana , Albuquerque Jones
Published: April 2024

Schizophrenia is a severe mental illness that affects approximately 1% of the global population and presents significant challenges for patients, families, and healthcare professionals. Characterized by symptoms such as delusions, hallucinations, disorganized speech or behavior, and cognitive impairment, this condition has an early onset and chronic trajectory, making it a debilitating challenge. Schizophrenia also imposes a substantial burden on society, exacerbated by the stigma associated with mental disorders. Technological advancements, such as computerized semantic, linguistic, and acoustic analyses, are revolutionizing the understanding and assessment of communication alterations, a significant aspect in various severe mental illnesses. Early and accurate diagnosis is crucial for improving prognosis and implementing appropriate treatments. In this context, the advancement of Artificial Intelligence (AI) has provided new perspectives for the treatment of schizophrenia, with machine learning techniques and natural language processing allowing a more detailed analysis of clinical, neurological, and behavioral data sets. The present article aims to present a proposal for computational models for the identification of schizophrenic traits in texts. The database used in this article was created with 139 excerpts of patients’ speeches reported in the book “Memories of My Nervous Disease” by German judge Daniel Paul Schreber, classifying them into three categories: 1 - schizophrenic, 2 - with schizophrenic traits and 3 - without any relation to the disorder. Of these speeches, 104 were used for training the models and the others 35 for validation.Three classification models were implemented using features based on geometric properties of graphs (number of vertices, number of cycles, girth, vertex of maximum degree, maximum clique size) and text entropy. Promising results were observed in the classification, with the Decision Tree-based model [1] achieving 100% accuracy, the KNN-k-Nearest Neighbor model observed with 62.8% accuracy, and the ‘centrality-based’ model with 59% precision. The high precision rates, observed when geometric properties are incorporated into Artificial Intelligence Models, suggest that the models can be improved to the point of capturing the language deviation traits that are indicative of schizophrenic disorders. In summary, this study paves the way for significant advances in the use of geometric properties in the field of psychiatry, offering a new data-based approach to the understanding and therapy of schizophrenia.
Quantifying the Regional Disproportionality of COVID-19 Spread
Authors: Sasaki Kenji , Ikeda Yoichi , Nakano Takashi
Published: April 2024

Background

The COVID-19 pandemic has caused serious health problems and has had major economic and social consequences worldwide. Understanding how infectious diseases spread can help mitigating the social and economic impact.

Objective

The study focuses to capture the degrees of disproportionality in prevalence rates of infectious disease across different regions over time.

Methods

We analyze the numbers of daily COVID-19 confirmed cases in the United States collected by Johns Hopkins University over 1100 days since the first reported case in January 2020 in order to assess quantitatively the disproportionality of the confirmed cases using the Theil index, a measure of imbalance used in economics. Results:

Our results reveal a dynamic pattern of interregional disproportionality in the confirmed cases by monitoring variations in regional contributions to the Theil index as the pandemic progresses.

Conclusions

The combined monitoring of this indicator and the confirmed cases is crucial for understanding regional differences in infectious diseases and for effective planning of response and resource allocation.
Functional divergence between the two cerebral hemispheres contributes to human fluid intelligence
Authors: Liang Xinyu , Luo Junhao , Yang Liyuan , Vatansever Deniz , Jefferies Elizabeth , Gong Gaolang
Published: April 2024

Hemispheric lateralization is linked to potential cognitive advantages. It is considered a driving force behind the generation of human intelligence. However, establishing quantitative links between the degree of lateralization and intelligence in humans remains elusive. In this study, we propose a framework that utilizes the functional aligned multidimensional representation space derived from hemispheric functional gradients to compute between-hemisphere distances within this space. Applying this framework to a large cohort (N=777 from the Human Connectome Project), we identified high functional divergence across the two hemispheres within the frontoparietal control network. We found that both global divergence between the cerebral hemispheres and regional divergence within the multiple demand network were positively associated with fluid composite score and partially mediated the influence of brain size on individual differences in fluid intelligence. Together, these findings illuminate the profound significance of brain lateralization as a fundamental organizational principle of the human brain, providing direct evidence that hemispheric lateralization supports human fluid intelligence.
Effective population size of X chromosomes and haplodiploids under cyclical parthenogenesis
Authors: Hitchcock Thomas
Published: April 2024

Many organisms can reproduce both sexually and asexually. Many such groups also exhibit ploidy differences between males and females during the sexual phase of their life, including aphids, nematodes, wasps, and rotifers. The constraints of combining asexual reproduction with asymmetric ploidy often results in X chromosomes (or haplodiploids) which show distinct transmission genetics from conventional systems. This may be expected to impact the effective population size; however, we currently lack analytical expressions for such life cycles. To remedy this, here we generate expressions for the effective population size of X chromosomes and haplodiploids under cyclical parthenogenesis. By first analysing a purely sexual scenario, we show how these distinct transmission genetics generate an effective population size substantially smaller than that of the autosomes, and how it may be further altered by aspects of sex-specific ecology, inbreeding, and non-random X elimination. Considering this inheritance system in an explicit population structure also demonstrates how genetic differentiation builds up differently between autosomes and X chromosomes. By introducing asexual reproduction into the model, we can see how low frequencies of sex cause these differences between autosomes and X chromosomes to dissipate. We discuss the relevance of these results to some different groups and consider future avenues for both empirical and theoretical work.
A blueprint for national assessments of the blue carbon capacity of kelp forests applied to Canada’s coastline
Authors: McHenry Jennifer , Okamoto Daniel K. , Filbee-Dexter Karen , Krumhansl Kira , MacGregor Kathleen A. , Hessing-Lewis Margot , Timmer Brian , Archambault Philippe , Attridge Claire M. , Cottier Delphine , Costa Maycira , Csordas Matt , Johnson Ladd E. , Lessard Joanne , Mora-Soto Alejandra , Metaxas Anna , Neufeld Chris , Pontier Ondine , Reshitnyk Luba , Starko Samuel , Yakimishyn Jennifer , Baum Julia K.
Published: April 2024

Kelp forests offer substantial carbon fixation, with the potential to contribute to natural climate solutions (NCS). However, to be included in national NCS inventories, governments must first quantify the kelp-derived carbon stocks and fluxes leading to carbon sequestration. Here, we present a blueprint for assessing the national carbon sequestration capacity of kelp forests in which data synthesis and Bayesian hierarchical modelling enable estimates of kelp forest carbon production, storage, and export capacity from limited data. Applying this blueprint to Canada’s extensive coastline, we find kelp forests store an estimated 1.4 Tg C in short-term biomass and produce 3.1 Tg C yr-1with modest carbon fluxes to the deep ocean. Arctic kelps had the highest carbon stocks and production capacity, while Pacific kelps had greater carbon fluxes overall due to their higher productivity and export rates. Our transparent, reproducible blueprint represents an important step towards accurate carbon accounting for kelp forests.
wwLearning the language of proteins and predicting the impact of mutations
Authors: Hu Bin , Babinski Michal , Gibson Kaetlyn , Li Po-E , Li Valerie , Chain Patrick
Published: April 2024

Mutations in proteins directly impact their structure and function. Understanding the “language” of proteins, or the sequence to function (genotype-phenotype) relationship has many real-world applications. One set of applications includes those in biodefense, such as biological threat detection and biosurveillance, antibody engineering, and medical countermeasure development. In this study, we present a novel language model-based approach that can rapidly analyze vast collections of sequences, and make near real-time functional predictions that compare favorably to those made using conventional bioinformatic and experimental methods. Our findings reveal that tailored protein language models can predict protein mutation phenotypes, such as binding affinity or level of expression, when they are trained with high-throughput functional data. Protein language models applied to viral genomes can also discern the lineage within a family (e.g., sarbecovirus sequences). Coupled with sequenced-based biosurveillance, this type of model may provide early warning signals of potential zoonotic spillovers (i.e. host jumping) or “escape” from existing medical countermeasures posed by novel mutations. This research not only underscores the potential of ML and language models in addressing pressing challenges in understanding the mapping of sequence to function, but further elucidates their potential application in accelerating the response to biological threats as they evolve.
A new high-quality genome assembly and annotation for the threatened Florida Scrub-Jay (Aphelocoma coerulescens)
Authors: Romero Faye G. , Beaudry Felix E.G. , Hovmand Warner Eyvind , Nguyen Tram N. , Fitzpatrick John W. , Chen Nancy
Published: April 2024

The Florida Scrub-Jay (Aphelocoma coerulescens), a Federally Threatened, cooperatively-breeding bird, is an emerging model system in evolutionary biology and ecology. Extensive individual-based monitoring and genetic sampling for decades has yielded a wealth of data, allowing for the detailed study of social behavior, demography, and population genetics of this natural population. Here, we report a linkage map and a chromosome-level genome assembly and annotation for a female Florida Scrub-Jay made with long-read sequencing technology, chromatin conformation data, and the linkage map. We constructed a linkage map comprising 4,468 SNPs that had 34 linkage groups and a total sex-averaged autosomal genetic map length of 2446.78 cM. The new genome assembly is 1.32 Gb in length, consisting of 33 complete or near-complete autosomes and the sex chromosomes (ZW). This highly contiguous assembly has an N50 of 68 Mb and a Benchmarking Universal Single-Copy Orthologs (BUSCO) completeness score of 97.1% with respect to theAvesdatabase. The annotated gene set has a BUSCO transcriptome completeness score of 95.5% and 18,051 identified protein-coding genes, 92.2% of which have associated functional annotations. This new, high-quality genome assembly and linkage map of the Florida Scrub-Jay provides valuable tools for future research into the evolutionary dynamics of small, natural populations of conservation concern.
SPARROW reveals cell states and functions influenced by microenvironment zones in complex tissues
Authors: Zhao Peiyao A , Garber Jessica , Gustafson Claire , Kim June , Malone Jocelin , Savage Adam , Skene Peter , Li Xiao-jun
Published: April 2024

Spatially resolved transcriptomics technologies have significantly enhanced our ability to understand cellular characteristics within tissue contexts. However, they present a trade-off between spatial resolution and transcriptome coverage. This limitation, compounded with analytical tools treating cell type inference and cellular neighbourhood identification as separate processes, hinders a unified understanding of tissue features across scales. Our computational framework, SPARROW, infers cell types and delineates cellular organization patterns as microenvironment zones using an interconnected architecture. SPARROW algorithmically achieves single cell spatial resolution and whole transcriptome coverage by integrating spatially resolved transcriptomics and scRNA-seq data. Using SPARROW, we identified established and novel microenvironment zone-specific ligand-receptor mediated interactions in human tonsils, discoveries that would not be possible using either modality alone. Moreover, SPARROW uncovered novel cell states in the mouse hypothalamus, underscoring the influence of microenvironment zones on cell identities. Lastly, through its common latent spaces that facilitate cross-tissue comparisons, SPARROW revealed distinct inflammation states between different lymph node tissues. Overall, SPARROW integrates cellular gene expression with spatial organization, providing a comprehensive characterization of tissue features across scales and samples.
Coordinated regulation by lncRNAs results in tight lncRNA–target couplings
Authors: Chiu Hua-Sheng , Somvanshi Sonal , de Lavergne Eric de Bony , Wei Zhaowen , Trypsteen Wim , Scorsone Kathleen A. , Patel Ektaben , Tang Tien T. , Flint David B. , Panah Mohammad Javad Najaf , Kim Hyunjae Ryan , Rathi Purva , Lee Yan-Hwa Wu , Woodfield Sarah , Vasudevan Sanjeev A. , Heczey Andras Attila , Chen Ting-Wen , Gaber M. Waleed , Sawakuchi Gabriel Oliveira , Mestdagh Pieter , Yang Xuerui , Sumazin Pavel
Published: April 2024

The determination of long non-coding RNA (lncRNA) function is a major challenge in RNA biology with applications to basic, translational, and medical research [1–7]. Our efforts to improve the accuracy of lncRNA-target inference identified lncRNAs that coordinately regulate both the transcriptional and post-transcriptional processing of their targets. Namely, these lncRNAs may regulate the transcription of their target and chaperone the resulting message until its translation, leading to tightly coupled lncRNA and target abundance. Our analysis suggested that hundreds of cancer genes are coordinately and tightly regulated by lncRNAs and that this unexplored regulatory paradigm may propagate the effects of non-coding alterations to effectively dysregulate gene expression programs. As a proof-of-principle we studied the regulation of DICER1 [8, 9]—a cancer gene that controls microRNA biogenesis—by the lncRNAZFAS1, showing thatZFAS1activatesDICER1transcription and blocks its post-transcriptional repression to phenomimic and regulate DICER1 and its target microRNAs.