bluuebunny/crossref_metadata_2025_split huggingface dataset:
Spatial scaling of beta diversity supports the regional community concept for clades as different as ants, birds, diatoms, and trees
Authors: Ohyama Leo , Bogota-Gregory Juan D. , Jenkins David G. 
Published: October 2023

AbstractAimThree fundamental and inter-related concepts have accrued debates: ecological communities, beta diversity (β), and spatial scale. Spatial scaling of β informs the community concept because the scale of maximal β corresponds to the most apparent size of an ecological community (without invoking external features of habitat, etc.). Here we test five alternative hypotheses about spatial scaling of β for ants, birds, diatoms, and trees across the contiguous USA, using spatial grains from 1 to 106km2. We compare β scaling among clades and test hypotheses about repeatability where data permit for: (a) summer and winter bird β in six consecutive years; (b) trees through time (4 years, spaced 5 years apart). Finally, we compare different forms of β (i.e., observed and deviations from null models based on spatial heterogeneity and spatial homogeneity).LocationThe contiguous United States of AmericaTime PeriodRecent but varying with cladeTaxa Studiedants, birds, diatoms, and treesMethodsWe obtained data from publicly-available sources and assigned point locations to hexagonal grids ranging from 1 to 106km2. At each spatial grain, we calculated mean pairwise β between each hexagon and its neighboring grids. We also compared alternative β measures and evaluated potential confounding effects of neighborhood size and species richness on results.ResultsSpatial scaling of β repeatedly supported the regional community concept among clades, though with different spatial scales per clade. Based on peak mean β, community size for trees (∼300 km2) < winter birds (∼500 km2) < summer birds (∼2000 km2) ≈ ants (∼2000 km2) < diatoms (∼11,000 km2). We note that community scales represent peaks on gradients rather than definitive one-size-fits-all scales. Spatial scaling of β was sensitive to seasonality (birds) and consistent among years for both birds and trees. Also, β deviation from a null model based on spatial heterogeneity adjusted observed β but was less sensitive to neighborhood size and species richness than β deviation based on spatial homogeneity.Main conclusionsResults here indicate that: (a) similar patterns should occur across the tree of life; (b) local ecological and evolutionary forces scale up to form repeatable regional community patterns in ways not yet fully understood; (c) local biodiversity conservation efforts need to be coordinated at biogeographical scales to best achieve goals; and (d) a recent method to calculate β deviation from a null model based on spatial heterogeneity improves β research.
A novel bioinformatics pipeline for the identification of immune inhibitory receptors as potential therapeutic targets
Authors: Singh Akashdip , Bedate Alberto Miranda , von Richthofen Helen J. , Vijver Saskia V. , van der Vlist Michiel , Kuhn Raphael , Yermanos Alexander , Kuball Jurgen , Keşmir Can , Ramos M. Ines Pascoal , Meyaard Linde 
Published: October 2023

AbstractBlocking inhibitory receptors like PD-1 and CTLA-4 has revolutionized cancer treatment in recent years. However, despite major successes in melanoma and lung cancer, the majority of cancer types are not responsive to these immunotherapies. As such, there is an ongoing need for the identification of novel inhibitory receptors as drug targets. Most inhibitory receptors signal via immunoreceptor tyrosine-based inhibitory motifs (ITIMs) and previous studies have estimated that our genome contains over 1600 ITIM- bearing transmembrane proteins. However, further testing and development of this large number of candidates requires increased understanding of their expression patterns and likelihood to function as inhibitory receptor.To assist in the selection of novel inhibitory receptor as therapeutic targets, we designed a novel bioinformatics pipeline integrating machine learning-guided structural predictions and sequence-based likelihood models to identify 51 known and 390 putative inhibitory receptors. Using publicly available transcriptomics data of immune cells, we determined the expression of these novel inhibitory receptors, and classified them into previously proposed functional categories.Known and putative inhibitory receptors were expressed across a wide variety of immune cells, and we found cell type-specific patterns in expression of these receptors. We used our pipeline to study inhibitory receptor expression patterns in single cell transcriptomics data of tumour infiltrating T cells. We determined that putative immune inhibitory receptors were expressed differentially in CD4+and CD8+T cell subsets, including exhausted CD8+T cells and CD4+memory T cells, which could allow for subset-specific targeting.In conclusion, we present an inhibitory receptor pipeline that identifies 51 known and 390 novel inhibitory receptors. This pipeline will support future drug target selection across diseases where therapeutic targeting of immune inhibitory receptors is warranted.
Human RAMP1 overexpressing mice are resistant to migraine therapies for motion sensitivity
Authors: Rahman Shafaqat M. , Guo Linda , Minarovich Carissa , Moon Laura , Guo Anna , Luebke Anne E. 
Published: October 2023

AbstractBoth enhanced motion-induced nausea and increased static imbalance are observed symptoms in migraine and especially vestibular migraine (VM). Motion-induced nausea and static imbalance were investigated in a mouse model, nestin/hRAMP1, expressing elevated levels of human RAMP1 which enhances CGRP signaling in the nervous system, and compared to non-affected littermate controls. Behavioral surrogates such as the motion- induced thermoregulation and postural sway center of pressure (CoP) assays were used to assess motion sensitivity.Nausea readouts revealed that the nestin/hRAMP1 mouse exhibit an increased sensitivity to CGRP’s effects at lower doses compared to unaffected controls. In addition, the nestin/hRAMP1 mice exhibit a higher dynamic range in postural sway than their wildtype counterparts, along with increased sway observed in nestin/hRAMP1 male mice that was not present in male unaffected controls. Results from migraine blocker experiments were challenging to interpret, but the data suggests that olcegepant is incapable of reversing CGRP-induced or endogenous alterations in the nestin/hRAMP1 mice, while rizatriptan was ineffective in both the nestin/hRAMP1 and control mice. The results indicate that overexpression of hRAMP1 leads to heightened endogenous CGRP signaling. Results also suggest that both olcegepant and rizatriptan are ineffective in reducing nausea and sway in this hypersensitive CGRP mouse model. This study suggests that the hypersensitive nestin/hRAMP1 mouse may serve as a model for difficult to treat cases of migraine that exhibit increased motion sensitivity.
Integrative systems biology framework discovers common gene regulatory signatures in multiple mechanistically distinct inflammatory skin diseases
Authors: Mishra Bharat , Athar Mohammad , Mukhtar M. Shahid 
Published: October 2023

ABSTRACTAimMore than 20% of the population across the world is affected by non-communicable inflammatory skin diseases including psoriasis, atopic dermatitis, hidradenitis suppurativa, rosacea, etc. Many of these chronic diseases are painful and debilitating with limited effective therapeutic interventions. However, recent advances in psoriasis treatment have improved the effectiveness and provide better management of the disease. Similar effective treatments are also needed for other chronic skin disorders regulated molecular pathogenesis. This study aims to identify common regulatory pathways and master regulators that regulate molecular pathogenesis.MethodsWe designed an integrative systems biology framework to identify the significant regulators across several inflammatory skin diseases. We exploited the gene co-expression-, and protein-protein interaction-based networks to identify shared genes and pro components in different diseases with relevant functional implications. Further, we utilized network analytics to unravel the high-priority proteins, that play a crucial role in disease pathogenesis.ResultsWith conventional transcriptome analysis we identified 55 shared genes, which are enriched in several immune-associated pathways in eight inflammatory skin diseases. Our correlation-based co-expression networks identified the core co-expression networks and the integrative multi-omics interactomes providing core interactions across four of the eight diseases. Next, by implementing network analytics, we unraveled 55 high-value proteins as significant regulators in molecular pathogenesis. We believe that these significant regulators should be explored with critical experimental approaches to identify the putative drug targets for more effective treatments. As an example, we identified IKZF1 as a shared significant master regulator in three inflammatory skin diseases, which can serve as a putative drug target with known disease-derived molecules for developing efficacious combinatorial treatments for hidradenitis suppurativa, atopic dermatitis, and rosacea.ConclusionThe conventional transcriptome results identify huge complexity among inflammatory skin diseases, which demands a systems biology perspective for comprehensive understanding. The proposed framework is very modular, which can indicate a significant path of molecular mechanism-based drug development from complex transcriptomics data and other multi-omics data.
Integrated integral population models
Authors: Portillo-Tzompa Paola , Martín-Cornejo Paulina R. , González Edgar J. 
Published: October 2023

SummaryData integration allows obtaining better descriptions and forecasting of a population’s behaviour by incorporating data at both the individual and population levels. Structured population models include the matrix population models (MPMs), which structure a population through a discrete state variable, and the integral population models (IPMs), which use a continuous variable. Two decades ago, the integrated version of MPMs appeared, but their corresponding version for IPMs is still missing.Here, we propose the integrated integral population model (IIPM). This model takes up the ideas behind existing models used to describe and forecast the dynamics of continuously structured populations: IPMs, which use individual data, and inverse IPMs, which use population data. Particularly, we emphasise the construction and fitting of the IIPM under a Bayesian framework and use the Soay sheep database to compare the population dynamics generated by the IIPM and these existing models.The IIPM constructed with the Soay sheep data had a good performance both at the individual (vital rates) and population (size and structure) levels, because, as they are constrained to fit both sets of data, they produce a balanced population dynamics. In turn, the IPM produced the best individual estimates and the worst population estimates, whilst the inverse IPM produced the worst individual estimates and the best population estimates.The objective of a structured population model should be to correctly describe population patterns. IPMs, by not using population data, fail in this objective. An IIPM solves this problem.
LOXL2 inhibition ameliorates pulmonary artery remodeling in pulmonary hypertension
Authors: Steppan Jochen , Wang Huilei , Nandakumar Kavitha , Poe Alan , Pak Lydia , Brady Travis , Gadkari Mahin , Berkowitz Dan E. , Shimoda Larissa A. , Santhanam Lakshmi 
Published: October 2023

AbstractBackgroundConduit pulmonary arterial stiffening and the resultant increase in pulmonary vascular impedance has emerged as an important underlying driver of pulmonary arterial hypertension (PAH). Given that matrix deposition is central to vascular remodeling, we evaluated the role of the collagen crosslinking enzyme lysyl oxidase like 2 (LOXL2) in this study.Methods and ResultsHuman pulmonary artery smooth muscle cells (PASMCs) subjected to hypoxia showed increased LOXL2 secretion. LOXL2 activity and expression were markedly higher in primary PASMCs isolated from pulmonary arteries of the rat Sugen 5416 + hypoxia (SuHx) model of severe PH. Similarly, LOXL2 protein and mRNA levels were increased in pulmonary arteries (PA) and lungs of rats with PH (SuHx and monocrotaline (MCT) models). Pulmonary arteries (PAs) isolated from rats with PH exhibited hypercontractility to phenylephrine and attenuated vasorelaxation elicited by acetylcholine, indicating severe endothelial dysfunction. Tensile testing revealed a a significant increase in PA stiffness in PH. Treatment with PAT-1251, a novel small-molecule LOXL2 inhibitor, improved active and passive properties of the PA ex vivo. There was an improvement in right heart function as measured by right ventricular pressure volume loopsin-vivowith PAT-1251. Importantly PAT-1251 treatment ameliorated PH, resulting in improved pulmonary artery pressures, right ventricular remodeling, and survival.ConclusionHypoxia induced LOXL2 activation is a causal mechanism in pulmonary artery stiffening in PH, as well as pulmonary artery mechanical and functional decline. LOXL2 inhibition with PAT-1251 is a promising approach to improve pulmonary artery pressures, right ventricular elastance, cardiac relaxation, and survival in PAH.New & NoteworthyPulmonary arterial stiffening contributes to the progression of PAH and the deterioration of right heart function. This study shows that LOXL2 is upregulated in rat models of PH. LOXL2 inhibition halts pulmonary vascular remodeling and improves PA contractility, endothelial function and improves PA pressure, resulting in prolonged survival. Thus, LOXL2 is an important mediator of PA remodeling and stiffening in PH and a promising target to improve PA pressures and survival in PH.
Machine Learning Based Identification and Characterization of Mast cells in Eosinophilic Esophagitis
Authors: Zhang Simin , Caldwell Julie M. , Rochman Mark , Collins Margaret H. , Rothenberg Marc E. 
Published: October 2023

AbstractBackgroundEosinophilic esophagitis (EoE) is diagnosed and monitored using esophageal eosinophil levels; however, EoE also exhibits a marked, understudied esophageal mastocytosis.ObjectiveUsing machine learning, we localized and characterized esophageal mast cells to decipher their potential role in disease pathology.MethodsEsophageal biopsy samples (EoE, control) were stained for mast cells by anti-tryptase and imaged using immunofluorescence; high-resolution whole tissue images were digitally assembled. Machine learning software was trained to identify, enumerate, and characterize mast cells, designated Mast Cell-Artificial Intelligence (MC-AI).ResultsMC-AI enumerated cell counts with high accuracy. During active EoE, epithelial mast cells increased and lamina propria (LP) mast cells decreased. In controls and EoE remission patients, papillae had the highest mast cell density and negatively correlated with epithelial mast cell density. Mast cell density in the epithelium and papillae correlated with the degree of epithelial eosinophilic inflammation, basal zone hyperplasia, and LP fibrosis. MC-AI detected greater mast cell degranulation in the epithelium, papillae, and LP in EoE patients compared with control individuals. Mast cells were localized further from the basement membrane in active EoE than EoE remission and controls individuals but were closer than eosinophils to the basement membrane in active EoE.ConclusionUsing MC-AI, we identified a distinct population of homeostatic esophageal papillae mast cells; during active EoE, this population decreases, undergoes degranulation, negatively correlates with epithelial mast cell levels, and significantly correlates with distinct histologic features. Overall, MC-AI provides a means to understand the potential involvement of mast cells in EoE and other disorders.Clinical ImplicationWe have developed a methodology for identifying, enumerating, and characterizing mast cells using artificial intelligence; this has been applied to decipher eosinophilic esophagitis and provides a platform approach for other diseases.Capsule SummaryA machine learning protocol for identifying mast cells, designated Mast Cell–Artificial Intelligence, readily identified spatially distinct and dynamic populations of mast cells in EoE, providing a platform to better understand this cell type in EoE and other diseases.
Microbubble dynamics in brain microvessels
Authors: Bezer James H. , Prentice Paul , Kee Chang William Lim , Morse Sophie V. , Christensen-Jeffries Kirsten , Rowlands Christopher J. , Kozlov Andriy S. , Choi James J. 
Published: October 2023

ABSTRACTBackgroundFocused ultrasound stimulation of microbubbles is being tested in clinical trials for its ability to deliver drugs across the blood-brain barrier (BBB). This technique has the potential to treat neurological diseases by preferentially delivering drugs to targeted regions. Yet despite its potential, the physical mechanisms by which microbubbles alter the BBB permeability remain unclear, as direct observations of microbubbles oscillating in cerebral capillaries have never been previously recorded.The purpose of this study was to reveal how microbubbles respond to ultrasound when within the microvessels of living brain tissue.MethodsMicrobubbles in acute brain slices acquired from juvenile rats perfused with a concentrated solution of SonoVue® and dye were exposed to ultrasound pulses typically used in BBB disruption (center frequency: 1 MHz, peak-negative pressure: 0.2–1 MPa, pulse length: up to 10 ms) and observed using high-speed microscopy at up to 10 million frames per second.ResultsWe observed that microbubbles can exert mechanical stresses on a wide region of tissue beyond their initial location and immediate surroundings. A single microbubble can apply mechanical stress to parenchymal tissues several micrometers away from the vessel. Microbubbles can travel at high velocities within the microvessels, extending their influence across tens of micrometers during a single pulse. With longer pulses and higher pressures, microbubbles could penetrate the vessel wall and move through the parenchyma, refuting a previous assumption that microbubbles are confined to vessels. The probability of extravasation scales approximately with mechanical index, being rare at low pressures, but much more common at a mechanical index ≥ 0.6.ConclusionsThese observations provide important insight into microbubble dynamics in microvessels, and are critical leads into ultimately identifying the microbubble activities that lead to both safe drug delivery and into activities we seek to avoid, such as petechiae and other bioeffects.
High-content fluorescence bioassay to investigate pore formation, ion channel modulation and cell membrane lysis induced by venoms
Authors: Kramer Simon , Kotapati Charan , Cao Yuanzhao , Fry Bryan G , Palpant Nathan J , King Glenn F , Cardoso Fernanda C 
Published: October 2023

AbstractVenoms comprise highly evolved bioactive molecules modulating ion channels, receptors, coagulation factors, and the cellular membrane. This array of targets and bioactivity requires high-content bioassays to aid the development of novel envenomation treatments and biotechnological and pharmacological agents. To address this gap in venom’s research, we developed a fluorescence-based high-throughput and high-content cellular assay to simultaneously identify common cellular activities produced by venoms: membrane lysis, pore-formation, and ion channel modulation. By combining intracellular calcium with extracellular nucleic acid measurements, we distinguished these venom mechanisms using one cellular assay. We applied our high-content bioassay in three cell types exposed to venom components representing lytic, ion pore-forming or ion channel modulator toxins. Beyond the distinct profiles produced by these three types of action mechanisms, we found that the pore-forming latrotoxin α-Lt1a prefers human neuroblastoma to kidney cells and cardiomyocytes, while the lytic bee peptide melittin is not selective. Furthermore, evaluation of snake venoms showed that Elapid species induced rapid membrane lysis, while Viper species showed variable to no activity on neuroblastoma cells. These findings demonstrate that our high-content bioassay distinguish clades and interspecific traits and capture the clinical observations at venom level and is capable of differentiate ion pore-forming from membrane lysis and ion channel modulation. We hope our research will accelerate the understanding of venom biology and the diversity of toxins inducing cytotoxic, cardiotoxic and neurotoxic effects and assist in identifying venom components whose properties could benefit humankind.
Not all Bacterial Outer Membrane Proteins are β-Barrels
Authors: Heido John , Keng Simon , Kadevari Pream , Poyrazoglu Hulya , Priyam Ekta , Jayasinghe Sajith 
Published: October 2023

AbstractThe discovery of WzA, an octomeric helical barrel integral bacterial outer membrane protein, has challenged the widely held understanding that all integral outer membrane proteins of gram-negative bacteria are closed β-barrels composed of transmembrane β-strands. WzA is a member of the outer membrane polysaccharide exporter family and a bioinformatics analysis suggests that other members of the family may also contain outer membrane transmembrane segments that are helical. A review of the literature indicates that in addition to Wza, outer membrane core complex proteins of the type IV secretion systems also contain transmembrane segments that are helical.