bluuebunny/crossref_metadata_2025 huggingface dataset:
Tips and tricks in the operative management of esophageal, trachea, and bronchial injuries: What you need to know
Authors: Wall Matthew J. , Mattox Kenneth L.
Published: November 2024

Tracheal injuries can be immediately life-threatening. Fiberoptic bronchoscopy in the operating room can make the diagnosis and satisfy the principle of achieving an airway distal to the injury. Repair is performed with a single layer of absorbable suture. Esophageal injuries are diagnosed with imaging, endoscopy, or intraoperatively. In the chest, esophageal injuries are best repaired through posterolateral incisions. Repairs are performed in one or two layers, and drains are routinely used. For a damage-control approach to esophageal injuries, wide drainage can be considered. For both tracheal and esophageal injuries, the operative approach is based on the anatomic location of the injury and muscle flap buttressing of the repairs is routinely employed.
A review on semi-analytical methods for aggregation and coupled aggregation–breakage equations
Authors: Shweta  , Hussain Saddam , Kumar Rajesh
Published: November 2024

This work reviews the semi-analytical technique (SAT) and proposes a unique SAT based on the homotopy analysis method (HAM), called accelerated HAM (AHAM) (recently proposed in Hussain
et al
. (Hussain S, Arora G, Kumar R. 2024 Semi-analytical methods for solving non-linear differential equations: a review.
J. Math. Anal. Appl.
531
, 127821 (doi:
10.1016/j.jmaa.2023.127821
))) to solve pure aggregation and coupled aggregation–fragmentation population balance equations (PBEs), which are nonlinear integro-partial differential equations. The novelty of this approach is demonstrated through a comparative analysis of numerical results against existing findings from the Adomian decomposition (Singh R, Saha J, Kumar J. 2015 Adomian decomposition method for solving fragmentation and aggregation population balance equations.
J. Appl. Math. Comput.
48
, 265–292 (doi:
10.1007/s12190-014-0802-5
)), homotopy analysis (Kaur G, Singh R, Briesen H. 2022 Approximate solutions of aggregation and breakage population balance equations.
J. Math. Anal. Appl.
512
, 126166 (doi:
10.1016/j.jmaa.2022.126166
)), homotopy perturbation (Kaur G, Singh R, Singh M, Kumar J, Matsoukas T. 2019 Analytical approach for solving population balances: a homotopy perturbation method.
J. Phys. A Math. Theor.
52
, 385201 (doi:
10.1088/1751-8121/ab2cf5
)) and optimized decomposition (Kaushik S, Kumar R. 2023 A novel optimized decomposition method for Smoluchowski’s aggregation equation.
J. Comput. Appl. Math.
419
, 114710 (doi:
10.1016/j.cam.2022.114710
)) methods for these models. In addition, the theoretical convergence analysis and error estimation of the proposed method are also investigated. To validate the scheme, we analyse several numerical test cases and the results illustrate that the suggested technique offers the most accurate estimates for the two models under consideration.
Development of acute Pseudomonas aeruginosa and Acinetobacter baumannii lung mono-challenge models in mice using oropharyngeal aspiration
Authors: Jurado-Martín Irene , Ma Chaoying , Rezk Nouran , Sainz-Mejías Maite , Hou Yueran , Baugh John A. , McClean Siobhán
Published: November 2024

Antimicrobial-resistant pathogens such as Pseudomonas aeruginosa and Acinetobacter baumannii can cause potentially fatal infections in susceptible individuals, with respiratory tract infections among the most common clinical presentations. The development of novel treatments or prophylactic interventions to combat these infections is urgently needed and requires robust, reliable animal models for their preclinical evaluation. In particular, the bacterial burden needs to be accurately determined before and after administration of the potential therapy under evaluation to quantify the effectiveness of the treatment. We provide two reliable, non-invasive murine acute lung challenge models with either P. aeruginosa or A. baumannii using an oropharyngeal aspiration technique, which has been widely overlooked in studies testing vaccines or treatments for these pathogens. Here, we show that this non-surgical technique to deliver suspensions into mouse lungs does not significantly impact animal welfare (based on welfare monitoring and weight) and allows uniform bilateral distribution of the bacterial dose, resulting in even bioburden in both lungs. The optimal timepoint for humane killing and organ harvest was 24 h after challenge for both pathogens, and at least 4×106 and 107 c.f.u. per mouse were needed to obtain a reproducible P. aeruginosa or A. baumannii bioburden, respectively. These mouse challenge models offer a valuable tool to assess therapeutic interventions against P. aeruginosa or A. baumannii infections.
Feature selection with vector-symbolic architectures: a case study on microbial profiles of shotgun metagenomic samples of colorectal cancer
Authors: Cumbo Fabio , Truglia Simone , Weitschek Emanuel , Blankenberg Daniel
Published: November 2024

The continuingly decreasing cost of next-generation sequencing has recently led to a significant increase in the number of microbiome-related studies, providing invaluable information for understanding host-microbiome interactions and their relation to diseases. A common approach in metagenomics consists of determining the composition of samples in terms of the amount and types of microbial species that populate them, with the goal to identify microbes whose profiles are able to differentiate samples under different conditions with advanced feature selection techniques. Here we propose a novel backward variable selection method based on the hyperdimensional computing paradigm, which takes inspiration from how the human brain works in the classification of concepts by encoding features into vectors in a high-dimensional space. We validated our method on public metagenomic samples collected from patients affected by colorectal cancer in a case/control scenario, by performing a comparative analysis with other state-of-the-art feature selection methods, obtaining promising results.

AUTHOR SUMMARY

Characterizing the microbial composition of metagenomic samples is crucial for identifying potential biomarkers that can distinguish between healthy and diseased states. However, the high dimensionality and complexity of metagenomic data present significant challenges in the context of accurately selecting features. Our backward variable selection method, based on the hyperdimensional computing paradigm, offers a promising approach to overcoming these challenges. By effectively reducing the feature space while preserving essential information, this method enhances the ability to detect critical microbial signatures associated with diseases like colorectal cancer, leading to more precise diagnostic tools.
On non-random mating, adaptive evolution and information theory
Authors: Carvajal-Rodríguez Antonio
Published: November 2024

Population genetics describes evolutionary processes, focusing on the variation within and between species and the forces shaping this diversity. Evolution reflects information accumulated in genomes, enhancing organisms’ adaptation to their environment.

In this paper, we propose a model that begins with the distribution of matings based on mutual fitness and progresses to viable adult genotype distribution. At each stage the changes result in different measures of information. The evolutionary dynamics of each stage of the model correspond to aspects such as the type of mating, the distributions of genotypes within matings, and the distribution of genotypes and haplotypes in the next generation. Changes in these distributions are caused by variation in fitness and result in Jeffreys divergence values other than zero. As an example, a model of hybrid sterility is developed at a biallelic locus, comparing the information indices associated with each stage of the evolutionary process.

In conclusion, the informational perspective seems to facilitate the connection of causes and effects and allows the development of statistics to contrast null models of zero information (random mating, no selection, etc.). The informational perspective could contribute to clarify, deepen and expand the mathematical foundations of evolutionary theory.

SIMPLE SUMMARY

The evolutionary process can be seen as a process of acquisition, storage, and updating of information by a population about the environment in which it lives. In this paper I propose a model that starts with the distribution of matings that occur according to mutual mating fitness and ends with the distribution of viable adult genotypes obtained after these matings. The result of the evolutionary dynamics associated with each stage of the model can be described in terms of information. This informational description facilitates the connection between causes and effects, as well as the development of statistics to test the null model of zero information, i.e. random mating and/or no effect of natural selection. Incorporating the informational perspective into the mathematical formalism of population genetics/genomics contributes to clarifying, expanding and deepening the mathematical description of evolutionary theory.
Modulation of B cell receptor activation by antibody competition
Authors: He Yuanyuan , Guo Zijian , Vahey Michael D.
Published: November 2024

During repeated virus exposure, pre-existing antibodies can mask viral epitopes by competing with B cell receptors for antigen. Although this phenomenon has the potential to steer B cell responses away from conserved epitopes, the factors that influence epitope masking by competing antibodies remain unclear. Using engineered, influenza-reactive B cells, we investigate how antibodies influence the accessibility of epitopes on the viral surface. We find that membrane-proximal epitopes on influenza hemagglutinin are fundamentally at a disadvantage for B cell recognition because they can be blocked by both directly and indirectly competing antibodies. While many influenza-specific antibodies can inhibit B cell activation, the potency of masking depends on proximity of the targeted epitopes as well as antibody affinity, kinetics, and valency. Although most antibodies are inhibitory, we identify one that can enhance accessibility of hidden viral epitopes. Together, these findings establish rules for epitope masking that could help advance immunogen design.
Remote-control meiotic drive of sex chromosomes
Authors: Greenberg Naomi L. , Patten Manus M. , Schenkel Martijn A.
Published: November 2024

Some selfish genetic elements drive at meiosis to achieve transmission distortion, breaking the rules of Mendelian segregation to enhance their own evolutionary success. It has been previously shown that positive modifiers of drive must act incisin order to gain the selfish benefit of drive and that suppressors of drive will be selected at any unlinked loci. Here, we model the evolution of an autosomaltrans-acting gene (Distorter) that causes the Y-chromosome (or even 0-chromosome) to drive. We show that such a gene may spread in the population when linked to a second locus,Assister, whose alleles are transmitted at different frequencies through sperm as compared to eggs, for which we consider various scenarios, e.g. genes subject to sexually antagonistic selection or sex-limited drive. Depending on the mechanistic details of sex-chromosome drive,Distorter’s spread can additionally facilitate transitions between XY and X0 sex determination. We discuss these results in relation to sex allocation theory, and as proof of principle for a novel type of naturally occurring or synthetically useful sex-ratio-distorting selfish genetic element.
Transcriptome sample statistics of the responses the sugar beet root maggot,Tetanops myopaeformishas while experiencing susceptible and resistant reactions with sugar beet,Beta vulgarisssp. vulgaris
Authors: Acharya Sudha , Alkharouf Nadim W. , Tehseen Muhammad Massub , Chu Chenggen , Klink Vincent P.
Published: November 2024

The sugar beet root maggot (SBRM),Tetanops myopaeformis(von Röder), is a devastating insect pathogen of sugar beet (SB), Beta vulgaris ssp, vulgaris (B. vulgaris), one of only two plants in the world from which significant global raw sugar is produced, $1 billion, U.S., $4.6 B, globally. Experiments reveal the SBRM larval transcriptome experiencing two different susceptible or resistant responses by sugar beet SBRM larvae were sampled at time = 0 hours post infection [hpi]), prior to being introduced toB. vulgarisand after infection on F1016 and F1024 (resistant), and F1010 and L19 (susceptible) for 24, 48, and 72 hpi when the larvae were removed for transcriptomic analysis. The transcriptomic analyses included determining the number of reads per sample, mapping the transcripts to the recently sequenced SBRM TmSBRM_v1.0 draft genome, identifying genes that relate to the resistant and susceptible responses. Moreover, the RNA-seq experiments provide data for generating differential expression analyses between the various sample types, thus, yielding an understanding SBRM biology, the development of new control strategies for this pathogen, relationship to model genetic organisms likeDrosophila melanogaster, relationship to pathogenic non-model organisms, and aid in agronomic improvement of sugar beet for stakeholders.
Design and Synthesis of Triazine-Based Hydrogel for Combined Targeted Doxorubicin Delivery and PI3K Inhibition
Authors: Mandal Subhasis , Bhoumick Avinandan , Singh Arpana , Konar Sukanya , Banerjee Arkajyoti , Ghosh Arnab , Sen Prosenjit
Published: November 2024

Melanoma, an aggressive skin cancer originating from melanocytes, presents substantial challenges due to its high metastatic potential and resistance to conventional therapies. Hydrogels, three-dimensional networks of hydrophilic polymers with high water-retention capacities, offer significant promise for controlled drug delivery applications. In this study, we report the synthesis and characterization of hydrogelators based on the triazine molecular scaffold, which self-assemble into fibrous networks conducive to hydrogel formation. Rheological analysis confirmed their hydrogelation properties, while microscopic techniques including FE-SEM and FEG-TEM provided insights into their morphological networks. The drug delivery capability of these hydrogelators was evaluated using doxorubicin, a widely employed anticancer agent, demonstrating enhanced biocompatibility and reduced side effects compared to free doxorubicin. Additionally, the hydrogelators exhibited inhibitory activity against phosphoinositide 3-kinase (PI3K), a key enzyme frequently mutated in cancer, and also involved in melanoma progression. The dual functionality of this delivery system – controlled drug release and PI3K inhibition – highlights the potential of triazine-based hydrogelators as innovative therapeutic platforms for melanoma treatment.
The Protein Language Visualizer: Sequence Similarity Networks for the Era of Language Models
Authors: Espinoza-Herrera Javier , Manríquez-García María F. , Medina-Bermejo Sofía , López-Jasso Ailyn , Shi Karry , Mead Dyllan , Veskimägi Sarah M. , O’Connor Maeve , Siordia Adriana , Roethler Nathaniel , Jinich Adrian
Published: November 2024

Abstract

The advent of high-throughput sequencing technologies and the availability of biological “big data” has accelerated the discovery of new protein sequences, making it challenging to keep pace with their functional annotation. To address this annotation challenge, techniques such as Sequence Similarity Networks (SSNs) have been employed to visually group proteins for faster identification. In this paper, we introduce an alternative visual analysis tool. Our simple and modular Protein Language Visualizer (PLVis) pipeline combines pre-trained PLM embeddings, dimensionality reduction algorithms and clustering methods to enable rapid assessment of proteins based on their neighbors. The resulting interactive visualizations can be enriched with multiple layers of biological and structural annotations. We present a head-to-head comparison of PLVis with SSNs and find concordant clustering patterns, with PLVis offering the additional advantage of revealing relationships between proteins that would appear as isolated nodes in an SSN. Next, we quantitatively validate the intuitive notion that well-separated clusters in a PLVis capture sequence similarity information with more fidelity than large, central “fuzzy” regions of the projection, where relative distances should be interpreted with caution. Also, we present case studies that demonstrate the value of the pipeline for exploring multi-organism full proteome comparisons. Finally, we make this pipeline accessible to a wider research community by sharing thePLVis Colab Notebook. PLVis offers a low-barrier platform for researchers to explore and compare proteomes through the lens of language models.
Spatial context allows the evolution the control of nitrification by plants
Authors: Ardichvili Alice Nadia , Barot Sébastien , Lata Jean-Christophe , Loeuille Nicolas
Published: November 2024

Some plant species inhibit or stimulate soil nitrification, the transformation of ammonium into nitrate by microorganisms. The control of nitrification may in turn alter ecosystem productivity and functioning. Given the potential positive impacts of nitrification control on plant fitness, we aim to determine the conditions under which nitrification control is likely to have been selected, and the consequences of that selection on ecosystem functioning. We investigate both the role of the abiotic context (nutrient availability and diffusion) and the role of other plant traits (mortality and dispersal). A first mean-field model shows that when nitrogen pools are shared among individuals within the plant population, the control of nitrification is counter-selected. A tragedy of the commons occurs because the costs of controlling nitrification (ie. of producing root exudates) only affect the controlling individuals while benefits are shared among all individuals. We then assume that the effects of the control of nitrification are spatially restricted to the rhizosphere, and we build a spatially explicit, individual-based model in which mutation of control of nitrification is possible. Plant capacity to control nitrification evolves when the plant environment is sufficiently private and generation time sufficiently long, leading to higher fitness benefits of the construction process. In such cases, plants evolve to inhibit nitrification when losses of nitrate are greater than losses of ammonium and evolve to stimulate nitrification when losses of ammonium are greater than losses of nitrate. Finally, biomass production tends to be maximal at the selected strategy when the diffusion of ammonium and nitrate is low. Our results help predict which strategies should be selected and likely to be found in different plants in different parts of the world.
Electrical charge-mediated transformation for efficient plant genome editing
Authors: Augustine Sruthy Maria , Cherian Anoop Vadakan , Paridhi Paridhi , Rashid Md Mamunur , Ugwuanyi Samson , Knoblauch Babette , Tzigos Stavros , Pullamsetti Soni Savai , Snowdon Rod
Published: November 2024

Genome editing technologies possess significant potential to enhance plant breeding; however, the delivery of editing constructs poses challenges in numerous crop species due to their resistance to transformation or tissue culture. This study introduces an innovative approach for the delivery of ribonucleoprotein (RNP) complexes and plasmid vectors into intact, regenerable faba bean plant tissues. This is accomplished by applying an electric current that makes plant cell walls and membranes permeable, thereby allowing the entry of macromolecular constructs into the cell and nucleus. This study assessed the efficacy of electric pulse-mediated transfection in faba bean by generating stable GFP-expressing faba bean plants. Furthermore, we incorporated it into faba bean leaf tissue and demonstrated its application in both embryos and leaf tissues. We demonstrate DNA-free genome editing by targeting the endogenous phytoene desaturase gene (PDS), achieving a mutation success rate of 50%. This method is efficient and economical, necessitating limited technical training. It is applicable to both leaf and embryo tissues, thereby enhancing its utility for crop improvement. This technique shows potential for the development of new crop varieties that can more effectively address global climate challenges.
Towards robust machine olfaction: debiasing GC-MS data enhances prostate cancer diagnosis from urine volatiles
Authors: Rotteveel Adan , Lee Wen-Yee , Kountouri Zoi , Stefanou Nikolas , Kivell Howard , Gluck Clifford , Zhang Shuguang , Mershin Andreas
Published: November 2024

We present here a generalizable approach to de-biasing and de-trending before clustering complex datasets, using the specific example of prostate cancer diagnosis from gas chromatography-mass spectrometry ion chromatograms. We endeavor to mimic the olfactory cancer diagnostic prowess of trained dogs to establish, in perceptual space (as opposed to analytical chemistry space), a robustly recognizable signal that can be associated with the presence or absence of prostate cancer in the person who provided the urine sample. Upon performing principal component analysis, we found that using unsupervised clustering, the data had a strong tendency to cluster with respect to the urine sample source medical center, so a bias detector and baseline-drift remover had to be created as part of our pre-processing. Our machine olfaction approach marks a departure from conventional analytical chemistry sample analysis that leads to identification of the constituent compounds by name and concentration and moves us towards a generalizable, adaptable biomarker which in this case we call the emergent scent character. These scent characters are informed by measurements performed on volatile organic compounds (VOCs) but are not in themselves lists of VOCs or any of their physicochemical parameters added linearly. Ultimately, we use techniques prevalent in machine vision repurposed for machine olfaction by allowing for recognition and categorization of our scent character patterns as if they were images.
Population genomics ofMarchantia polymorphasubspeciesruderalisreveals evidence of climate adaptation
Authors: Wu Shuangyang , Jandrasits Katharina , Swarts Kelly , Roetzer Johannes , Akimcheva Svetlana , Shimamura Masaki , Hisanaga Tetsuya , Berger Frédéric , Dolan Liam
Published: November 2024

Sexual reproduction results in the development of haploid and diploid cell states during the life cycle. In bryophytes the dominant multicellular haploid phase produces motile sperm that swim through water to the egg to effect fertilization from which a relatively small diploid phase develops. In angiosperms, the reduced multicellular haploid phase produces non-motile sperm that is delivered to the egg through a pollen tube to effect fertilization from which the dominant diploid phase develops. These different life cycle characteristics are likely to impact the distribution of genetic variation among populations. However, little is known about the distribution of genetic variation among populations of bryophytes. To understand how genetic variation is distributed among populations of a bryophyte and to establish the foundation for population genetics research in bryophytes, we described the genetic diversity of collections ofMarchantia polymorphasubspeciesruderalis, a cosmopolitan ruderal liverwort. We explored genetic diversity of this species using 78 genetically unique (non-clonal) accessions from a total of 209 collected from 37 sites in Europe and Japan. There was no detectable population structure among European populations but significant genetic differentiation between Japanese and European populations. By associating genetic variation across the genome with global climate data, we identified summer temperature and precipitation as climate factors influencing the frequency of adaptative alleles. We speculate that the requirement for water through which motile sperm swim imposes a constraint on the life cycle to which the plant genetically adapts.
Longitudinal blood microsampling and proteome monitoring facilitate timely intervention in experimental type 1 diabetes
Authors: Parajuli Anirudra , Bendes Annika , Byvald Fabian , Stone Virginia M. , Ringqvist Emma E. , Butrym Marta , Angelis Emmanouil , Kipper Sophie , Bauer Stefan , Roxhed Niclas , Schwenk Jochen M. , Flodström-Tullberg Malin
Published: November 2024

Symptoms of immune-mediated diseases (IMIDs) typically appear after irreversible tissue damage, making early interventions based on pre-symptomatic indicators crucial. Current efforts to identify molecular markers of early disease lack the resolution, convenience and cost efficiency required to prevent irreversible tissue damage. Analyzing frequently self-collected samples, such as dried blood spots (DBS), could enable the earlier detection of diseases, identify disease-predictive markers and facilitate tailored interventions. To test this, we regularly microsampled a mouse model infected with a type 1-diabetes (T1D)-associated virus. This longitudinal DBS sample collection was analyzed for 92 circulating proteins, revealing transient molecular changes in virus-infected animals that would have been missed with less frequent sampling. Machine learning predicted infection status after day 2 post-infection with >90% accuracy, enabling well-timed treatment of virus-infected animals and diabetes prevention. Our study demonstrates the utility of frequent blood microsampling to monitor disease during the pre-symptomatic phase, allowing for timely interventions.

Teaser

Frequent blood microsampling detects early biomarkers, enabling timely intervention in immune-mediated diseases
Mechanistic pathways of tick exposure risk in native and invaded plant communities
Authors: Hiatt Drew , Dillon Whalen W. , Gardner Allison , Cabrera Steven , Dietze Michael , Allan Brian F. , Flory S. Luke
Published: November 2024

Plant invasions may alter vector abundance by several mechanistic pathways, including modifying microclimates that influence vector survival or changing habitats to influence host use. Here, we used a field experiment and observational data to evaluate multiple mechanistic pathways (tick survival and host abundance) by which plant invasions may alter vector-borne disease risk using the common disease vector lone star tick (Amblyomma americanum) and the widespread invasive cogongrass (Imperata cylindrica) in the southeastern USA. In the field experiment, ticks survived over 50% longer in areas dominated by the invasive plant compared to those with only native plant species. Invaded areas had lower temperatures and higher humidity that likely reduced tick desiccation. The observational study showed greater average tick abundance in native plant communities and no difference in wildlife host (white-tailed deer) activity between plant communities. There was also a positive relationship between tick abundance and white-tailed deer activity, but only in native areas. Together, these results suggest that more favorable microclimate conditions resulting in greater tick longevity is the dominant driver of tick abundance in invaded areas, while tick abundance in native-dominated areas is promoted, at least in part, by white-tailed deer activity. Our results demonstrate that plant invaders affect multiple, potentially off-setting mechanistic pathways contributing to tick exposure risk. The complexity of these relationships highlights the need for better understanding of how invasive species and other global change drivers influence abundance of disease vectors and, ultimately, disease transmission.
The impact of transplant location on the gut microbiome and resistome in patients undergoing hematopoietic stem cell transplantation at home versus in the hospital
Authors: Andermann T.M. , Zeng K. , Guirales-Medrano S. , Groth A. , Ramachandran B.C. , Sun S. , Sorgen A.A. , Hill L. , Bush A.T. , Liu H. , Jones C. , Roach J. , Conlon B.P. , Rao G. , Chao N.J. , Fodor A.A. , Sung A.D.
Published: November 2024

Objectives

Home-based hematopoietic stem cell transplantation (HCT) is a novel approach that has the potential to improve outcomes, however, the impact of transplant location on the gut microbiome remains uncharacterized. We hypothesized that patients randomized to undergo home HCT would have higher gut taxonomic diversity and lower antimicrobial resistance (AMR) gene abundance compared to those undergoing standard hospital HCT.

Methods

We identified 28 patients enrolled in Phase II randomized trials of home (n=16) v. hospital (n=12) HCT at Duke and performed shotgun metagenomic sequencing of stools to compare taxonomic and AMR gene composition between groups. We performed a secondary analysis of patients from each group transplanted at an outpatient infusion clinic with those who underwent standard inpatient HCT (“outpatient” v. “inpatient”).

Results

No significant differences in duration of hospitalization were found in those randomized to home v. hospital HCT. Taxonomic and AMR gene α- and β-diversity were comparable. In contrast, secondary analyses demonstrated that patients from both home and hospital groups transplanted at an outpatient infusion clinic spent significantly less time in the hospital and demonstrated higher taxonomic α-diversity and differential β-diversity compared to standard inpatient HCT, although AMR gene α-diversity did not differ, and comparisons were confounded by both differences in transplant type and use of antibiotics.

Conclusions

Randomization by transplant location did not impact the gut microbiota to the same extent as the duration of hospitalization, although secondary analyses were heavily confounded. Even when taxonomic differences were observed, AMR genes were similar between groups.
Representation Learning of Human Disease Mechanisms for a Foundation Model in Rare and Common Diseases
Authors: Ravandi Babak , Mowrey William R. , Chatterjee Ayan , Haddadi Parham , Abdelmessih Mario , Ding Wei , Lambden Simon , Ughetto Michaël , Barrett Ian , Diethe Tom , Del Angel Guillermo , Eliassi-Rad Tina , Ricchiuto Piero
Published: November 2024

The limited amount of data available renders it challenging to characterize which biological processes are relevant to a rare disease. Hence, there is a need to leverage the knowledge of disease pathogenesis and treatment from the wider disease landscape to understand rare disease mechanisms. Furthermore, it is well understood that rare disease discoveries can inform the our knowledge of common diseases. In this paper, we introduce Dis2Vec (Disease to Vector), a new representation learning method for characterizing diseases with a focus on learning the underlying biological mechanisms, which is a step toward developing a foundation model for disease-association learning. Dis2Vec is trained on human genetic evidence and observed symptoms, and then evaluated through cross-modal transfer-learning scenarios based on a proposed drug association learning benchmark with drug targets (positive controls) and Orphanet Rare Disease Ontology (negative controls). Finally, we argue that clustering diseases in the Dis2Vec space, which captures biological mechanisms instead of drug-repurposing information, could increase the efficiency of translational research in rare and common diseases, and ultimately improve treatment strategies for patients.
Using mathematical constraints to explain narrow ranges for allele-sharing dissimilarities
Authors: Liu Xiran , Ahsan Zarif , Rosenberg Noah A.
Published: November 2024

Allele-sharing dissimilarity (ASD) statistics are measures of genetic differentiation for pairs of individuals or populations. Given the allele-frequency distributions of two populations—possibly the same population—the expected value of an ASD statistic is computed by evaluating the expectation of the pairwise dissimilarity between two individuals drawn at random, each from its associated allele-frequency distribution. For each of two ASD statistics, which we term 𝒟1and 𝒟2, we investigate the extent to which the expected ASD is constrained by allele frequencies in the two populations; in other words, how is the magnitude of the measure bounded as a function of the frequency of the most frequent allelic type? We first consider dissimilarity of a population with itself, obtaining bounds on expected ASD in terms of the frequency of the most frequent allelic type in the population. We then examine pairs of populations that might or might not possess the same most frequent allelic type. Across the unit interval for the frequency of the most frequent allelic type, the expected allele-sharing dissimilarity has a range that is more restricted than the r0, 1s interval. The mathematical constraints on expected ASD assist in explaining a pattern observed empirically in human populations, namely that when averaging across loci, allele-sharing dissimilarities between pairs of individuals often tend to vary only within a relatively narrow range.
The Accuracy of the Uganda National Tuberculosis and Leprosy Program algorithm and the World Health Organisation treatment decision algorithms for childhood tuberculosis: A retrospective analysis
Authors: Kitonsa Peter J , Kikaire Bernard , Wambi Peter , Nalutaaya Annet , Nakafeero Jascent , Nanyonga Gertrude , Kiconco Emma , Atwiine Deus , Castro Robert , Oumo Ernest A , Aanyu Hellen T , Mudiope Mary N , Mupere Ezekiel , Sekadde Moorine P , Mohanty Swomitra , Cattamanchi Adithya , Wobudeya Eric , Jaganath Devan
Published: November 2024

Diagnosing childhood pulmonary tuberculosis (TB) is a challenge, and this led the Uganda National Tuberculosis and Leprosy Program (NTLP) to develop a clinical treatment decision algorithm (TDA) for children. However, there is limited data on its accuracy and how it compares to new World Health Organization (WHO) TB TDAs for children. This study aimed to evaluate and compare the accuracy of the 2017 Uganda NTLP algorithm with the 2022 WHO TDAs for TB among children in Kampala, Uganda.

We retrospectively assessed children <15 years old who underwent an evaluation for TB between November 2018 and November 2022. Children were classified as per National Institutes of Health (NIH) consensus definitions. We applied the 2017 Uganda NTLP and 2022 WHO algorithms (A with chest x-ray [CXR], B without CXR) to make a decision to treat for TB or not, and calculated accuracy in reference to Confirmed vs. Unlikely TB, as well as a microbiological and composite reference standard. We compared accuracy of the Uganda NTLP algorithm to the WHO TDAs among children <10 years old.

A total of 699 children were included in this analysis with 64% (451/699) under 5 years, 53% (373/669) were male, 12% (85/699) were Xpert Ultra positive, 11% (74/669) were HIV positive and 6% had severe acute malnutrition (SAM). The Uganda NTLP algorithm had a sensitivity of 97.9% (95% CI: 96.4-99.4) and specificity of 25.9% (95% CI: 21.2-30.7). If CXR was considered unavailable, sensitivity was 97.9% (95% CI: 96.4-99.4) and specificity 28.1% (95% CI: 23.2-33.0). Accuracy remained similar among high-risk children. In comparison, WHO TDAs had similar sensitivity to the Uganda NTLP, but algorithm A was more specific (32.2%, 95% CI: 26.9-37.5) and algorithm B was less specific (15.4%, 95% CI: 11.3-19.5).

Both the Uganda NTLP and WHO TDAs had high sensitivity but low specificity. The WHO TDAs had better specificity than the NTLP algorithm with CXR, and worse specificity without CXR. Further optimization of the algorithms is needed to improve specificity and reduce over-treatment of TB in children.
CellBinDB: A Large-Scale Multimodal Annotated Dataset for Cell Segmentation with Benchmarking of Universal Models
Authors: Shi Can , Fan Jinghong , Deng Zhonghan , Liu Huanlin , Kang Qiang , Li Yumei , Guo Jing , Wang Jingwen , Gong Jinjiang , Liao Sha , Chen Ao , Zhang Ying , Li Mei
Published: November 2024

In recent years, cell segmentation techniques have played a critical role in the analysis of biological images, especially for quantitative studies. Deep learning-based cell segmentation models have demonstrated remarkable performance in segmenting cell and nucleus boundaries, however, they are typically tailored to specific modalities or require manual tuning of hyperparameters, limiting their generalizability to unseen data. Comprehensive datasets that support both the training of universal models and the evaluation of various segmentation techniques are essential for overcoming these limitations and promoting the development of more versatile cell segmentation solutions. Here, we present CellBinDB, a large-scale multimodal annotated dataset established for these purposes. CellBinDB contains more than 1,000 annotated images, each labeled to identify the boundaries of cells or nuclei, including 4’,6-Diamidino-2-Phenylindole (DAPI), Single-stranded DNA (ssDNA), Hematoxylin and Eosin (H&E), and Multiplex Immunofluorescence (mIF) staining, covering over 30 normal and diseased tissue types from human and mouse samples. Based on CellBinDB, we benchmarked seven state-of-the-art and widely used cell segmentation technologies/methods, and further analyzed the effects of four cell morphology indicators and image gradient on the segmentation results.
Strikingly different neurotransmitter release strategies in dopaminergic subclasses
Authors: Dorrego-Rivas Ana , Byrne Darren J. , Liu Yunyi , Cheah Menghon , Arslan Ceren , Lipovsek Marcela , Ford Marc C. , Grubb Matthew S.
Published: November 2024

Neuronal function is intimately tied to axodendritic polarity. Neurotransmitter release, for example, is usually the role of the axon. There are widespread exceptions to this rule, however, including many mammalian neuronal types that can release neurotransmitter from their dendrites. In the mouse olfactory bulb, closely related subclasses of dopaminergic interneuron differ markedly in their polarity, with one subtype lacking an axon entirely. These axon-bearing and anaxonic dopaminergic subclasses have distinct developmental profiles and sensory responses, but how their fundamental polarity differences translate to functional outputs remains entirely unknown. Here, we provide anatomical evidence for distinct neurotransmitter release strategies among these closely related dopaminergic subtypes: anaxonic cells release from their dendrites, while axon-bearing neurons release exclusively from their intermittently myelinated axon. These structural differences are linked to a clear functional distinction: anaxonic, but not axon-bearing dopaminergic neurons are capable of self-inhibition. Our findings suggest that variations in polarity can produce striking distinctions in neuronal outputs, and that even closely related neuronal subclasses may play entirely separate roles in sensory information processing.
Integration of multi-modal measurements identifies critical mechanisms of tuberculosis drug action
Authors: Johnson William C. , Alivisatos Ares , Smith Trever C. , Van Nhi , Soni Vijay , Wallach Joshua B. , Clark Nicholas A. , Fitzgerald Timothy A. , Whiteley Joshua J. , Sokolov Artem , Ando D. Michael , Schnappinger Dirk , Rhee Kyu Y. , Aldridge Bree B.
Published: November 2024

Treatments for tuberculosis remain lengthy, motivating a search for new drugs with novel mechanisms of action. However, it remains challenging to elucidate the direct targets of a drug, and even more so, to determine which disrupted cellular processes lead to bacterial killing. We developed a computational tool, DECIPHAER (DEcoding Cross-modal Information of PHarmacologies via AutoEncodeRs), to select the important correlated transcriptional and morphological responses ofMycobacterium tuberculosisto drug treatments. By finding a reduced feature space from these measurements, DECIPHAER highlighted essential features of Mtb cellular damage such as phosphosugar stress and inhibition of translation and DNA replication. After training, DECIPHAER provides cell-death-relevant insight into single-modal datasets, enabling interrogation of drug treatment responses for which transcriptional data are unavailable. Using morphological data alone with DECIPHAER, we discovered that respiration inhibition by the poly-pharmacological drugs, SQ109 and BM212, can influence cell death more than their effects on the cell wall. This study demonstrates that DECIPHAER can extract the critical shared information from multi-modal measurements to identify cell death-relevant mechanisms of TB drugs.
Computer assisted multi-level optimization of malonyl-CoA availability inPseudomonas putida
Authors: Batianis Christos , van Rosmalen Rik P. , Moñino Fernandez Pedro , Asin-Garcia Enrique , Martin-Pascual Maria , Jeschek Markus , Weusthuis Ruud , Suarez-Diez Maria , Martins dos Santos Vitor A. P.
Published: November 2024

Malonyl-CoA is the major precursor for the biosynthesis of diverse industrially valuable products such as fatty acids/alcohols, flavonoids, and polyketides. However, its intracellular availability is limited in most microbial hosts, hampering the biological synthesis of such chemicals. To address this limitation, we present a multi-level optimization workflow using modern metabolic engineer-ing technologies to systematically increase the malonyl-CoA levels in Pseudomonas putida. The workflow involves the identification of gene downregulations, chassis selection, and optimization of the acetyl-CoA carboxylase complex through ribosome binding site engineering. Computa-tional tools and high-throughput screening with a malonyl-CoA biosensor enabled the rapid eval-uation of numerous genetic targets. Combining the most beneficial targets led to a 5.8-fold en-hancement in the production titer of the valuable polyketide phloroglucinol. This study demon-strates the effective integration of computational and genetic technologies for engineering P. putida, opening new avenues for the development of industrially relevant strains and the investi-gation of fundamental biological questions.
Piezo1 balances membrane tension and cortical contractility to stabilize intercellular junctions and maintain epithelial barrier integrity
Authors: Javed Ahsan , Stubb Aki , Villeneuve Clémentine , Peters Franziska , Rübsam Matthias , Niessen Carien M. , Biggs Leah C. , Wickström Sara A.
Published: November 2024

Formation of a bi-directional skin barrier is essential for organismal survival and maintenance of tissue homeostasis. Barrier formation requires positioning of functional tight junctions (TJ) to the most suprabasal viable layer of the epidermis through a mechanical circuit that is driven by generation of high tension at adherens junctions. However, what allows the sensing of tension build-up at these adhesions and how this tension is balanced to match the requirements of tissue mechanical properties is unclear. Here we show that the mechanosensitive ion channel Piezo1 is essential for the maturation of intercellular junctions into functional, continuous adhesions. Deletion of Piezo1 results in an imbalance of cell contractility and membrane tension, leading to a delay in adhesion maturation. Consequently, the requirement for Piezo1 activity can be bypassed by lowering contractility or elevating membrane tension.In vivo, Piezo1 function in adhesion integrity becomes essential only in aged mice where alterations in tissue mechanics lead to impaired TJs and barrier dysfunction. Collectively these studies reveal an essential function of Piezo1 in the timely establishment and maintenance of cell-cell junctions in the context of a mechanically tensed epidermis.
G-quadruplex Structures in Dysregulated Long Non-Coding RNA of Ovarian Cancer and their Binding Interactions with Human Serum Albumin
Authors: Singh Deepshikha , Shukla Chinmayee , Datta Bhaskar
Published: November 2024

Ovarian carcinoma (OC) is a major cause of cancer-related mortality among women worldwide, with especially poor outcomes in resource-constrained regions. Long non-coding RNAs (lncRNAs) have emerged as critical players in OC progression, influencing drug resistance, metastasis, and other cellular processes. This study examines the potential of dysregulated lncRNAs in OC to form G-quadruplex (G4) structures. Using in silico predictions and experimental validation, we identified five lncRNAs ERLNC1, DLX6-AS1, LINC01127, FMNL1-DT, and LINP1 as candidates with a high propensity towards G4 formation. A combination of circular dichroism (CD) spectroscopy, Thioflavin T (ThT) fluorescence assay, Dot Blot assay, and reverse transcriptase stop assay, confirmed the ability of the lncRNAs to fold into stable G4 structures. Competitive DNA binding assays enabled the identification of essential G-tracts within each G4 motif highlighting the subtle differences in structure and stability of the different quadruplexes. Human serum albumin (HSA), a major circulatory protein, was found to interact with these G4-forming lncRNAs, albeit with different affinities and structural implications on the G4 motifs. This study provides the first detailed characterization of G4 structures in OC-dysregulated lncRNAs and elucidates their interactions with HSA. The G4 structures identified in these lncRNAs and their interaction with HSA can be of potential value for early OC diagnosis.

Graphical Abstract