bluuebunny/crossref_metadata_2025 huggingface dataset:
The Effect of Retinoic Acid on Neutrophil Innate Immune Interactions With Cutaneous Bacterial Pathogens
Authors: Stream Alexandra , Corriden Ross , Döhrmann Simon , Gallo Richard L. , Nizet Victor , Anderson Ericka L.
Published: April 2024

Vitamin A and its biologically active derivative, retinoic acid (RA), are important for many immune processes. RA, in particular, is essential for the development of immune cells, including neutrophils, which serve as a front-line defense against infection. While vitamin A deficiency has been linked to higher susceptibility to infections, the precise role of vitamin A/RA in host-pathogen interactions remains poorly understood. Here, we provided evidence that RA boosts neutrophil killing of methicillin-resistant Staphylococcus aureus (MRSA). RA treatment stimulated primary human neutrophils to produce reactive oxygen species, neutrophil extracellular traps, and the antimicrobial peptide cathelicidin (LL-37). Because RA treatment was insufficient to reduce MRSA burden in an in vivo murine model of skin infection, we expanded our analysis to other infectious agents. RA did not affect the growth of a number of common bacterial pathogens, including MRSA, Escherichia coli K1 and Pseudomonas aeruginosa; however, RA directly inhibited the growth of group A Streptococcus (GAS). This antimicrobial effect, likely in combination with RA-mediated neutrophil boosting, resulted in substantial GAS killing in neutrophil killing assays conducted in the presence of RA. Furthermore, in a murine model of GAS skin infection, topical RA treatment showed therapeutic potential by reducing both skin lesion size and bacterial burden. These findings suggest that RA may hold promise as a therapeutic agent against GAS and perhaps other clinically significant human pathogens.
Effect of hemoglobin A1c change on 24-month clinical outcomes in patients with diabetes after acute myocardial infarction
Authors: Park Sangshin , Choi Woong Gil , Bae Dae-Hwan , Kim Min , Lee Ju-Hee , Kim Sangmin , Bae Jang-Whan , Kim Dong-Woon , Cho Myeong-Chan , Kim Chong-Jin , Chae Shung-Chull , Jeong Myung-Ho , Hwang Kyung-Kuk ,   on behalf of the KAMIR-NIH Registry
Published: April 2024

Background

The average glycated hemoglobin (HbA1c) may not accurately reflect glycemic control status during the mid-term after acute myocardial infarction (AMI). We aimed to evaluate changes in HbA1c and their effect on mid-term clinical outcomes in patients with diabetes and AMI.

Methods

We enrolled patients with diabetes (n = 967) who underwent HbA1c measurement in the Korean nationwide registry. These patients were categorized into three groups based on changes in HbA1c from index admission to the 1-year follow-up visit: a decrease in HbA1c > 1%, changes in HbA1c within 1%, and an increase in HbA1c > 1%. Clinical outcomes at 24 months were examined.

Results

The baseline HbA1c levels were 8.55 ± 0.85, 7.00 ± 0.98 and 7.07 ± 1.05 (P = 0.001) and HbA1c levels after 1 year were 6.62 ± 0.73, 7.05 ± 0.98 and 9.26 ± 1.59 (P = 0.001) for patients with 3 groups, respectively. Patients with a 1% decrease in HbA1c had significantly lower incidence of major adverse cardiovascular events (MACE), cardiac death, and rehospitalization after 24 months than those with a 1% increase in HbA1c. However, in the Cox regression analysis, a >1% decrease in HbA1c change was not an independent factor for MACE, cardiac death, and rehospitalization.

Conclusions

Our analysis indicates that an HbA1c decrease of >1% within the first 12 months was not an independent prognostic factor until the 24-month mark. Therefore, standard diabetic control is recommended for patients with diabetes and AMI for up to 2 years.
Mycotic Aneurysms: Uncommon Pathogens and Treatment Conundrums
Authors: Ravindra Akshatha , Naguthevar Santhanam , Kumar Deepak , Rajagopal Rengarajan , Khera Pushpinder Singh , Tak Vibhor , Ramankutty Neetha Thayil , Meena Durga Shankar , Midha Naresh , Bohra Gopal Krishana , Garg Mahendra Kumar
Published: April 2024

Introduction

Mycotic aneurysms, characterized by vessel wall dilation resulting from infections including bacteria, fungi, and viruses, are a rare yet severe consequence of systemic infections.These aneurysms, accounting for 0.6% of Western countries' aneurysms, carry a higher risk of rupture compared to uninfected conditions. While the femoral artery, aorta, and intracranial visceral arteries are commonly affected, pathogens causing mycotic aneurysms vary across regions. Diagnostic challenges arise from nonspecific symptoms such as fever, pulsatile mass, local discomfort, and arterial inflammation.

 

Materials & Methods:
The case series involves three patients diagnosed with mycotic aneurysms due to unusual pathogens. We describe each patient's clinical presentation, medical history, physical examination findings, laboratory results, imaging studies, and the diagnostic process leading to the identification of the causative pathogens.

Results

The first case depicts a 70-year-old male with a ruptured infra-renal abdominal aortic pseudoaneurysm caused by Salmonella Paratyphi A. The second case involves a 66-year-old male with a Streptococcus pneumoniae-associated descending thoracic aortic pseudoaneurysm. The third case pertains to a 70-year-old male with a ruptured descending thoracic aortic aneurysm into the esophagus due to Pseudomonas aeruginosa infection. Each case highlights unique clinical features, laboratory findings, imaging results, and the management approaches undertaken.

Conclusion

Mycotic aneurysms, stemming from infections involving diverse pathogens, pose diagnostic challenges due to their nonspecific symptoms. Early identification and intervention are essential to mitigate the severe complications associated with these aneurysms. The presented cases underscore the need for a comprehensive approach to diagnosis and management, ensuring optimal outcomes for patients affected by mycotic aneurysms.
Psychrobacter raelei sp. nov., isolated from a dog with peritonitis
Authors: Manzulli Viviana , Schiavone Antonella , Castellana Stefano , Albenzio Marzia , Cafiero Maria Assunta , Camarda Antonio , Capozzi Loredana , D'Angelo Francesca , Parisi Antonio , Vasco Ilaria , Sciancalepore Dario , Marino Leonardo , Serrecchia Luigina , Rondinone Valeria , Campaniello Maria , Crescenzo Giuseppe , Galante Domenico , Pugliese Nicola
Published: April 2024

A strain belonging to the genus Psychrobacter, named PraFG1T, was isolated from the peritoneal effusion of a stray dog during necropsy procedures. The strain was characterized by the phylogenetic analyses based on the nucleotide sequences of 16S and 23S rRNA genes and of gyrB, which placed the strain in the genus Psychrobacter. The nucleotide sequence of the chromosome confirmed the placement, showing an average nucleotide identity of 72.1, 77.7, and 77.5 % with the closest related species, namely Psychrobacter sanguinis, Psychrobacter piechaudii, and Psychrobacter phenylpyruvicus, respectively, thus indicating a novel species. The polyphasic characterization by biochemical and fatty acid profiling as well as MALDI-TOF supported those findings. The strain was halotolerant, capable of growing within a temperature range between 4 and 37 °C, it was positive for catalase and oxidase, indole producing, nitrate reducing, and not able to use 5-keto-d-gluconic acid as a carbon source. Taken together, the data suggest that strain PraFG1T could be considered as representing a novel species, with the name Psychrobacter raelei sp. nov. (type strain PraFG1T=CIP 111873T=LMG 32233T).
Australian vertebrate hosts of Japanese encephalitis virus; a review of the evidence
Authors: Moore Kevin T. , Mangan Madelyn J. , Linnegar Belinda , Athni Tejas S. , McCallum Hamish I. , Trewin Brendan J. , Skinner Eloise
Published: April 2024

Japanese Encephalitis Virus (JEV) transmission in temperate Australia has underscored a critical need to characterise transmission pathways and identify probable hosts of infection within the country. This systematic review consolidates existing research on the vertebrate hosts of JEV that are known to exist in Australia. Specifically, we aim to identify probable species for JEV transmission, their potential role as either a spillover or maintenance host and identify critical knowledge gaps. Data were extracted from studies involving experimental infection, seroprevalence, and virus isolation and were available for 22 vertebrate species known to reside in Australia. A host competence score was calculated to assess the potential for a given species to infect JEV vectors and to quantity their possible role in JEV transmission. Based on the host competence score and ecology of each species, we find ardeid birds, feral pigs, and flying foxes have potential as maintenance hosts for JEV in the Australian context. We also note that brushtail possums and domestic pigs have potential as spillover hosts under certain outbreak conditions. However, evidence to confirm these roles in localized transmission or outbreaks is sparse, emphasizing the need for further targeted research. This review provides a foundation for future investigations into JEV transmission in Australia, advocating for enhanced surveillance and standardized research methodologies to better understand and mitigate the virus’s impact.
Repix: reliable, reusable, versatile chronic Neuropixels implants using minimal components
Authors: Horan Mattias , Regester Daniel , Mazuski Cristina , Jahans-Price Thomas , Bailey Shanice , Thompson Emmett J , Slonina Zuzanna , Plattner Viktor , Menichini Elena , Toksoz Irmak , Pinto Sandra Romero , Burrell Mark , Varsavsky Isabella , Dalgleish Henry William Peter , Bimbard Celian , Lebedeva Anna , Bauza Marius , Cacucci Francesca , Wills Tom , Akrami Athena , Krupic Julija , Stephenson-Jones Marcus , Barry Caswell , Burgess Neil , O'Keefe John , Isogai Yoh
Published: April 2024

Neuropixels probes represent the state-of-the-art for high-yield electrophysiology in neuroscience: the simultaneous recording of hundreds of neurons is now routinely carried out in head-restrained animals. In contrast, neural recording in unrestrained animals, as well as recording and tracking neurons over days, remains challenging, though it is possible using chronic implants. A major challenge is the availability of simple methods that can be implemented with limited or no prior experience with Neuropixels probes, while achieving reliable, reusable, versatile high-density electrophysiology. Here we developed, deployed, and evaluated the real-world performance of Repix, a chronic implantation system that permits the repeated re-use of Neuropixels probes. The lightweight system allows implanted animals to express a full range of natural behaviors, including social behaviors. We show that Repix allows the recording of hundreds of neurons across many months, up to a year, with implants across cortical and subcortical brain regions. Probes can be reused repeatedly with stable yield. Repix has been used by 16 researchers in 10 laboratories to date, and we evaluated the real-world performance of Repix in a variety of chronic recording paradigms in both mice and rats with a combined 209 implantations. We found that the key advantage of Repix is robustness and simplicity. Adopters of Repix became proficient at five procedures on average, regardless of prior experience with in vivo electrophysiology. With the companion protocol alongside this article, the performance and user-friendliness of Repix should facilitate a wide uptake of chronic Neuropixels recordings.
Tissue inflammation induced by constitutively active STING is mediated by enhanced TNF signaling
Authors: Luksch Hella , Schulze Felix , Geißler-Lösch David , Sprott David , Höfs Lennart , Szegö Eva M. , Tonnus Wulf , Winkler Stefan , Günther Claudia , Linkermann Andreas , Behrendt Rayk , Teichmann Lino L. , Falkenburger Björn H. , Rösen-Wolff Angela
Published: April 2024

Constitutive activation of STING by gain-of-function mutations triggers manifestation of the systemic autoinflammatory disease STING-associated vasculopathy with onset in infancy (SAVI). In order to investigate the role of signaling by tumor necrosis factor (TNF) in SAVI, we used pharmacological inhibition and genetic inactivation of TNF receptors 1 and 2 in murine SAVI, which is characterized by T cell lymphopenia, inflammatory lung disease and neurodegeneration. Pharmacologic inhibition of TNF signaling improved T cell lymphopenia, but had no effect on interstitial lung disease. Genetic inactivation of TNFR1 and TNFR2, however, rescued the loss of thymocytes, reduced interstitial lung disease and neurodegeneration. Furthermore, genetic inactivation of TNFR1 and TNFR2 blunted transcription of cytokines, chemokines and adhesions proteins, which result from chronic STING activation in SAVI mice. In addition, increased transendothelial migration of neutrophils was ameliorated. Taken together, our results demonstrate a pivotal role of TNFR-signaling in the pathogenesis of SAVI in mice and suggest that available TNFR antagonists could ameliorate SAVI in patients.

Graphic Abstract
Medical Diagnosis Coding Automation: Similarity Search vs. Generative AI
Authors: Klotzman Vanessa
Published: April 2024

Objective

This study aims to predict ICD-10-CM codes for medical diagnoses from short diagnosis descriptions and compare two distinct approaches: similarity search and using a generative model with few-shot learning.

Materials and Methods

The text-embedding-ada-002 model was used to embed textual descriptions of 2023 ICD-10-CM diagnosis codes, provided by the Centers provided for Medicare & Medicaid Services. GPT-4 used few-shot learning. Both models underwent performance testing on 666 data points from the eICU Collaborative Research Database.

Results

The text-embedding-ada-002 model successfully identified the relevant code from a set of similar codes 80% of the time, while GPT-4 achieved a 50 % accuracy in predicting the correct code.

Discussion

The work implies that text-embedding-ada-002 could automate medical coding better than GPT-4, highlighting potential limitations of generative language models for complicated tasks like this.

Conclusion

The research shows that text-embedding-ada-002 outperforms GPT-4 in medical coding, highlighting embedding models’ usefulness in the domain of medical coding.
Order among chaos: high throughput MYCroplanters can distinguish interacting drivers of host infection in a highly stochastic system
Authors: Chen Melissa Y , Fulton Leah , Huang Ivie , Liman Aileen , Hossain Sarzana , Hamilton Corri , Song Siyu , Geissmann Quentin , King Kayla C. , Haney Cara H
Published: April 2024

While microbiomes provide diverse benefits for their host, they are notoriously variable in structure and function. As a result, substantial experimental replication and scalability are required to identify the contributions of and interactions between microbiota, the host and the environment. Here, we describe a novel high throughput plant growth system (MYCroplanters) to test how multiple host, microbiota, and pathogen variables predict host health. Using an Arabidopsis-Pseudomonashost-microbiome-pathogen model, we found that host genotype and order of arrival predict competition outcome between strains in the rhizosphere, but pathogen and microbiota dose can overwhelm these effects. Regardless of host or inoculation conditions, final microbial community structure emerged as a consistent predictor of host health. We demonstrate that high-throughput tools like MYCroplanters can isolate interacting drivers of host health. Increasing the scale at which we can screen components of microbiome-mediated host benefits will facilitate building microbiome engineering solutions for medicine and agricultural applications.
Drosophila Models Uncover Substrate Channeling Effects on Phospholipids and Sphingolipids in Peroxisomal Biogenesis Disorders
Authors: Wangler Michael F , Chao Yu-Hsin , Roth Mary , Welti Ruth , McNew James A.
Published: April 2024

Peroxisomal Biogenesis Disorders Zellweger Spectrum (PBD-ZSD) disorders are a group of autosomal recessive defects in peroxisome formation that produce a multi-systemic disease presenting at birth or in childhood. Well documented clinical biomarkers such as elevated very long chain fatty acids (VLCFA) are key biochemical diagnostic findings in these conditions. Additional, secondary biochemical alterations such as elevated very long chain lysophosphatidylcholines are allowing newborn screening for peroxisomal disease. In addition, a more widespread impact on metabolism and lipids is increasingly being documented by metabolomic and lipidomic studies. Here we utilizeDrosophilamodels ofpex2andpex16as well as human plasma from individuals withPEX1mutations. We identify phospholipid abnormalities inDrosophilalarvae and brain characterized by differences in the quantities of phosphatidylcholine (PC) and phosphatidylethanolamines (PE) with long chain lengths and reduced levels of intermediate chain lengths. For diacylglycerol (DAG) the precursor of PE and PC through the Kennedy pathway, the intermediate chain lengths are increased suggesting an imbalance between DAGs and PE and PC that suggests the two acyl chain pools are not in equilibrium. Altered acyl chain lengths are also observed in PE ceramides in the fly models. Interestingly, plasma from human subjects exhibit phospholipid alterations similar to the fly model. Moreover, human plasma shows reduced levels of sphingomyelin with 18 and 22 carbon lengths but normal levels of C24. Our results suggest that peroxisomal biogenesis defects alter shuttling of the acyl chains of multiple phospholipid and ceramide lipid classes, whereas DAG species with intermediate fatty acids are more abundant. These data suggest an imbalance betweende novosynthesis of PC and PE through the Kennedy pathway and remodeling of existing PC and PE through the Lands cycle. This imbalance is likely due to overabundance of very long and long acyl chains in PBD and a subsequent imbalance due to substrate channeling effects. Given the fundamental role of phospholipid and sphingolipids in nervous system functions, these observations suggest PBD-ZSD are diseases characterized by widespread cell membrane lipid abnormalities.
Optimal Control Prevents Itself from Eradicating Stochastic Disease Epidemics
Authors: Russell Rachel , Cunniffe Nik J.
Published: April 2024

The resources available for managing disease epidemics – whether in animals, plants or humans – are limited by a range of practical and financial constraints. This motivates study of where these resources should be allocated to maximise their impact. Optimal control has been widely explored for optimising management of epidemics. The most common approach assumes a deterministic, continuous model based on differential equations to approximate the epidemic dynamics. However, real systems are stochastic and so a range of outcomes are possible for any given epidemic situation and choice of control. The deterministic models are also known to be poor approximations in cases where the number of infected hosts is low – either globally or within a subset of the population – and these cases are highly relevant in the context of control. Hence, this work explores the effectiveness of disease management strategies derived using optimal control theory when applied to a more realistic, stochastic form of disease model. We demonstrate that solutions to the deterministic optimal control are not optimal in cases where the disease is eradicated or close to eradication. The range of potential outcomes in the stochastic models means that optimising the deterministic case will not reliably eradicate disease, even when it is possible. For effective eradication, the rate of control must be higher than optimal control as applied to the deterministic model would predict. Using Model Predictive Control, in which the optimisation is performed repeatedly as the system evolves to correct for deviations from the optimal control predictions, improves performance but does not fix the underlying issue and the level of control calculated at each repeated optimisation is still insufficient. To demonstrate this, we present several very simple heuristics to identify which sites to control which can outperform the strategies calculated by MPC when the control budget is sufficient for eradication to be possible. Our illustration uses examples based on stochastic simulation of the spatial spread of plant disease but similar issues would be expected in any deterministic model where infection is driven close to zero or targeted to remain below some critical value.
Assessing the probability and time of weed control failure due to herbicide resistance evolution
Authors: Lauenroth Dana , Gokhale Chaitanya S.
Published: April 2024

The recurrent exposure to herbicides in agricultural landscapes forces weeds to adapt in a race against extinction. What role newly arising mutations and pre-existing variation play in this evolution of herbicide resistance is critical for developing management strategies. Here, we present a model of rapid adaptation in response to strong selection, capturing complex life cycles of sexual and asexual reproduction and dormancy in a perennial weed. Using a multitype Galton-Watson process, we derive the probability of herbicide resistance evolution and the waiting time distribution until resistant plants appear in the field. We analyse the effect of seed bank dynamics and details of the reproductive system in defining the probability and timing of resistance adaptation inSorghum halepense. Further, we investigate key factors determining the primary source of adaptive variation. We find that even small fitness costs associated with resistance reduce adaptation from standing genetic variation. For herbicide resistance inherited in a (incompletely) dominant fashion, self-pollination also diminishes standing variation for herbicide resistance by increasing the homozygosity. Our study highlights the importance of seed banks for weeds’ adaptive potential, preserving genetic information of forgone selection and prolonging the period in which the population can adapt.
Steep logarithmic increase of genetic variation in naturalArabidopsis thalianaaccessions across geographic scales
Authors: Hesen Vera , Boele Yvet , Holmer Rens , Boesten René , Wijfjes Raúl , Aarts Mark G. M. , van der Putten Wim H. , Scheres Ben , Willemsen Viola
Published: April 2024

Arabidopsis thaliana’slarge native range across Eurasia and display of considerable genetic variation is key to its increasing use in eco-evolutionary studies. The structure and amount of this genetic variation has been studied on various geographic scales. On a continental scale, the genetic variation was postulated to follow an ‘isolation by distance’ model, implying less genetic variation at smaller geographic distances. However, recent studies showed that the genetic variation is already high on small geographic scales, yet direct comparisons of the genetic variation across different geographic scales are rare. Here, we present a new local diversity panel covering 19 km2with accessions of the Veluwe, the Netherlands. We compared the genetic variation of this local diversity panel to a national and a continentalA. thalianadiversity panel. Direct comparison of these three geographic scales showed that local accessions harbour already 41.8% of the genetic variation found on a continental scale despite the substantial difference in geographic surface area covered. Moreover, a rapidly ascending logarithmic relationship between genetic and geographic distances was observed at continental, national and local scale and thus irrespective of the geographic scale considered. The high level of local genetic variation reported here poses new questions on which evolutionary forces are driving and maintaining this, and how much this constrains experimental design when using localA. thalianapopulations in future eco-evolutionary studies.
Unveiling inverted D genes and D-D fusions in human antibody repertoires unlocks novel antibody diversity
Authors: Ponraj Prabakaran , Gupta Abhinav , Rao Sambasiva P , Rajpal Deepak , Wendt Maria , Qiu Yu , Chowdhury Partha S.
Published: April 2024

Antibodies, fundamental to immune defense, derive their diversity primarily from the intricate rearrangement of variable (V), diversity (D), and joining (J) gene segments. Traditionally, D genes in the forward (5’-3’) direction contribute to this diversity by rearranging with V and J segments. However, the existence and significance of inverted D genes (InvDs), which are D genes oriented in the inverted (3’-5’) direction, were previously obscured by limitations in data and detection methods. Here, we carried out a comprehensive analysis of a large-scale public next-generation sequencing (NGS) dataset encompassing antibody repertoires from 13 healthy donors using a novel immunoinformatics workflow. Our analysis, for the first time, uncovers the existence of all 25 unique InvDs across all three reading frames within human antibody repertoires, including both naïve and memory B cells. This finding challenges previous assumptions, revealing the extensive presence of InvDs and identifying a broad spectrum of D-D fusions, especially those involving InvDs. Notably, InvDs enrich for unique amino acids such as histidine, proline, and lysine, not commonly found in forward D genes, and exhibit reduced use of certain negatively charged and bulky amino acids, including aspartate, tryptophan, and methionine. The unique amino acid profile of InvDs discloses new diversity and functionality in the human antibody repertoire, evidenced by over two dozen documented antibodies featuring InvDs, targeting a wide array of antigens. By opening exciting avenues for immunogenetics research, including new chromatin compaction models, innovative antibody libraries, and advancements in antibody engineering, these findings hold promise for the development of novel therapeutics and vaccines.
Flipping the Script:WolbachiaFavoring Males in a NeotropicalDrosophila
Authors: Moreira Marina Magalhães , Dias Luísa de Paula Bouzada , Guzman Yoan Camilo , Sena Letícia , de Almeida João Paulo Pereira , Yotoko Karla
Published: April 2024

As skilful strategists, intracellular endosymbionts, particularlyWolbachia, have evolved the ability to induce phenotypes that frequently enhance the fitness of female hosts, often at the cost of male fitness, to ensure the transmission to subsequent host generations. Natural selection plays a pivotal role in this interaction, potentially amplifying, diminishing, or eradicating endosymbionts based on their impact on host fitness. This study investigated the relationship between theWolbachiastrainwStv Vi andDrosophila sturtevanti, the most abundant Neotropical drosophilid. We combined field sampling and controlled crosses ofWolbachia-infected and antibiotic-treated individuals to assess the endosymbiont’s host effects. We found that contrary to initial expectations,Wolbachiareduced female fecundity while boosting male fertility, yielding a similar number of offspring in both infected and treated pairs. However, infected females produced fewer larvae when crossed with treated males. A key observation was protogyny in treated but not infected individuals, suggestingWolbachia’sinfluence on host ontogeny, potentially increasing mating among infected siblings and restoring infected females’ fitness. From these results, we concluded that this whole strategy balanced the fitness of infected and non-infected pairs. In fact, repeated sampling, at the same site, revealed fluctuations in Wolbachia prevalence and high, but not perfect, vertical transmission. Our results indicate that the strategies for persistence in a particular host extend far beyond favoring females. They also imply that environmental factors may favor one group over another in varying circumstances, potentially explaining the observed fluctuations in infection and variable prevalence ofWolbachiainD. sturtevantipopulations.
Impacts of Deforestation and Land Use/Land Cover Change on Carbon Stock and Dynamics in the Jomoro District, Ghana
Authors: Grieco Elisa , Vangi Elia , Chiti Tommaso , Collalti Alessio
Published: April 2024

Tropical deforestation in the African continent plays a key role in the global carbon cycle and bears significant implications in terms of climate change and sustainable development. Especially in Sub-Saharan Africa, where more than two-thirds of the population rely on forest and woodland resources for their livelihoods, deforestation and land use changes for crop production lead to a substantial loss of ecosystem-level carbon stock. Unfortunately, the impacts of deforestation and land use change can be more critical than in any other region, but these are poorly quantified. We analyse changes in the main carbon pools (above- and below-ground, soil and litter, respectively) after deforestation and land use/land cover change, for the Jomoro District (Ghana), by assessing the initial reference level of carbon stock for primary forest and the subsequent stock changes and dynamics as a consequence of conversion to the secondary forest and to six different tree plantations (rubber, coconut, cocoa, oil palm, and mixed plantations). Results indicate overall a statistically significant carbon loss across all the land uses/covers and for all the carbon pools compared to the primary forest with the total carbon stock loss ranging between 85% and 35% but with no statistically significant differences observed in the comparison between primary forest and mixed plantations and secondary forest. Results also suggest that above-ground carbon and soil organic carbon are the primary pools contributing to the total carbon stocks but with opposite trends of carbon loss and accumulation. Strategies for sustainable development, policies to reduce emissions from deforestation and forest degradation, carbon stock enhancement (REDD+), and planning for sustainable land use management should carefully consider the type of conversion and carbon stock dynamics behind land use change for a win-win strategy while preserving carbon stocks potential in tropical ecosystems.
To be or not to be - Decoding the Trabecular Meshwork Cell Identity
Authors: Tian Alice , Baidouri Hasna , Kim Sangbae , Li Jin , Cheng Xuesen , Li Yumei , Chen Rui , Raghunathan VijayKrishna
Published: April 2024

The trabecular meshwork within the conventional outflow apparatus is critical in maintaining intraocular pressure homeostasis.In vitrostudies employing primary cell cultures of the human trabecular meshwork (hTM) have conventionally served as surrogates for investigating the pathobiology of TM dysfunction. Despite its abundant use, translation of outcomes fromin vitrostudies toex vivoand/orin vivostudies remains a challenge. Given the cell heterogeneity, performing single-cell RNA sequencing comparing primary hTM cell cultures to hTM tissue may provide important insights on cellular identity and translatability, as such an approach has not been reported before. In this study, we assembled a total of 14 primary hTMin vitrosamples across passages 1-4, including 4 samples from individuals diagnosed with glaucoma. This dataset offers a comprehensive transcriptomic resource of primary hTMin vitroscRNA-seq data to study global changes in gene expression in comparison to cells in tissuein situ. We have performed extensive preprocessing and quality control, allowing the research community to access and utilize this public resource.
A comparative analysis of Parkinson’s disease and inflammatory bowel disease gut microbiomes highlights shared depletions in key butyrate-producing bacteria
Authors: Krueger Maeve E. , Boles Jake Sondag , Simon Zachary D. , Alvarez Stephan D. , McFarland Nikolaus R. , Okun Michael S. , Zimmermann Ellen M. , Forsmark Christopher E. , Tansey Malú Gámez
Published: April 2024

Epidemiological studies reveal that a diagnosis of inflammatory bowel disease (IBD) is associated with an increased risk of developing Parkinson’s disease (PD). The presence of gut dysbiosis has been documented in both PD and IBD patients, however it is currently unknown how alterations in the gut microbiome may contribute to the epidemiological link between both diseases. To identify shared and distinct features of the PD and IBD microbiome, we performed the first joint analysis of 54 PD, 26 IBD, and 16 healthy control gut metagenomes recruited from clinics at the University of Florida, and directly compared the gut microbiomes from PD and IBD persons. Larger, publicly available PD and IBD metagenomic datasets were also analyzed to validate and extend our findings. Depletions in short-chain fatty acid (SCFA) producing bacteria, includingRoseburia intestinalis, Faecalibacterium prausnitzii, Anaerostipes hadrus,andEubacterium rectale, as well as depletions in SCFA synthesis pathways, were demonstrated across PD and IBD datasets. We posit that direct comparison of PD and IBD gut microbiomes will be important in identifying features within the IBD gut which may be associated with PD. The data revealed a consistent depletion in SCFA-producing bacteria across both PD and IBD, suggesting that loss of these microbes may influence the pathophysiology of both disease states.
EYE-Llama, an in-domain large language model for ophthalmology
Authors: Haghighi Tania , Gholami Sina , Sokol Jared Todd , Kishnani Enaika , Ahsaniyan Adnan , Rahmanian Holakou , Hedayati Fares , Leng Theodore , Alam Minhaj Nur
Published: April 2024

Background

Training Large Language Models (LLMs) with in-domain data can significantly enhance their performance, leading to more accurate and reliable question-answering (QA) systems essential for supporting clinical decision-making and educating patients.

Methods

This study introduces LLMs trained on in-domain, well-curated ophthalmic datasets. We also present an open-source substantial ophthalmic language dataset for model training. Our LLMs (EYE-Llama), first pre-trained on an ophthalmology-specific dataset, including paper abstracts, textbooks, EyeWiki, and Wikipedia articles. Subsequently, the models underwent fine-tuning using a diverse range of QA datasets. The LLMs at each stage were then compared to baseline Llama 2, ChatDoctor, and ChatGPT (GPT3.5) models, using four distinct test sets, and evaluated quantitatively (Accuracy, F1 score, and BERTScore) and qualitatively by two ophthalmologists.

Results

Upon evaluating the models using the American Academy of Ophthalmology (AAO) test set and BERTScore as the metric, our models surpassed both Llama 2 and ChatDoctor in terms of F1 score and performed equally to ChatGPT, which was trained with 175 billion parameters (EYE-Llama: 0.57, Llama 2: 0.56, ChatDoctor: 0.56, and ChatGPT: 0.57). When evaluated on the MedMCQA test set, the fine-tuned models demonstrated a higher accuracy compared to the Llama 2 and ChatDoctor models (EYE-Llama: 0.39, Llama 2: 0.33, ChatDoctor: 0.29). However, ChatGPT outperformed EYE-Llama with an accuracy of 0.55. When tested with the PubmedQA set, the fine-tuned model showed improvement in accuracy over both the Llama 2, ChatGPT, and ChatDoctor models (EYE-Llama: 0.96, Llama 2: 0.90, ChatGPT: 0.93, ChatDoctor: 0.92).

Conclusion

The study shows that pre-training and fine-tuning LLMs like EYE-Llama enhances their performance in specific medical domains. Our EYE-Llama models surpass baseline Llama 2 in all evaluations, highlighting the effectiveness of specialized LLMs in medical QA systems. (Funded by NEI R15EY035804 (MNA) and UNC Charlotte Faculty Research Grant (MNA).)
Discovering Fragile Clades And Causal Sequences In Phylogenomics By Evolutionary Sparse Learning
Authors: Sharma Sudip , Kumar Sudhir
Published: April 2024

Phylogenomic analyses of long sequences, consisting of many genes and genomic segments, infer organismal relationships with high statistical confidence. But, these relationships can be sensitive to excluding just a few sequences. Currently, there is no direct way to identify fragile relationships and the associated individual gene sequences in species. Here, we introduce novel metrics for gene-species sequence concordance and clade probability derived from evolutionary sparse learning models. We validated these metrics using fungi, plant, and animal phylogenomic datasets, highlighting the ability of the new metrics to pinpoint fragile clades and the sequences responsible. The new approach does not necessitate the investigation of alternative phylogenetic hypotheses, substitution models, or repeated data subset analyses. Our methodology offers a streamlined approach to evaluating major inferred clades and identifying sequences that may distort reconstructed phylogenies using large datasets.
Stress granule induction in rat retinas damaged by constant LED light
Authors: Benedetto María M. , Malcolm Melisa , Bruera Manuel G. , Penazzi Laura G. , Guido Mario E. , Contín María A. , Garbarino-Pico Eduardo
Published: April 2024

Objectives

Stress granules (SGs) are cytoplasmic biocondensates formed in response to various cellular stressors, contributing to cell survival. While implicated in diverse pathologies, their role in retinal degeneration (RD) remain unclear. We aimed to investigate SG formation in the retina and its induction by excessive LED light in a RD model.

Methods

Rat retinas were immunohistochemically analyzed for SG markers G3BP1 and eIF3, and SGs were also visualized by RNA FISH. Additionally, SGs were induced in primary retinal cell and eyeball cultures using sodium arsenite. Light exposure experiments utilized LED lamps with a color temperature of 5,500 K and 200 lux intensity for short-term or 2-8-day exposures.

Results

SGs were predominantly detected in retinal ganglion cells (RGCs) and inner nuclear layer (INL) cells, confirmed by sodium arsenite induction. SG abundance was higher in animals exposed to light for 2-8 days compared to light/dark cycle controls. RGCs consistently exhibited more SGs than INL cells, and INL cells more than outer nuclear layer cells (Scheirer-Ray-Hare test: H 13.2, p = 0.0103 for light condition, and H 278.2, p < 0.00001 for retinal layer). These observations were consistent across four independent experiments, each with three animals per light condition.

Conclusions

This study identifies SGs in the mammalian retina for the first time, with increased prevalence following excessive LED light exposure. RGCs and INL cells showed heightened SG formation, suggesting a potential protective mechanism against photodamage. Further investigations are warranted to elucidate SGs’ role in shielding against light stress and their implications in retinopathies.
Aperiodic pupil fluctuations at rest predict orienting of visual attention
Authors: Wang Rongwei , Jia Jianrong
Published: April 2024

The aperiodic exponent features signals in various neuroimaging modalities and has been linked to the excitation/inhibition balance of the neural system. Leveraging the rich temporal dynamics of resting-state pupil fluctuations, the present study investigated the association between the aperiodic exponent of pupil fluctuations and the neural excitation/inhibition balance in attentional processing. In separate phases, we recorded participants’ pupil size during resting state and assessed their attentional orienting using the Posner cueing tasks with different cue validities (i.e., 100% and 50%). We found significant correlations between the aperiodic exponent of resting pupil fluctuations and both the microsaccadic and behavioral cueing effects. Critically, this relationship was particularly evident in the 50% cue-validity condition rather than in the 100% cue-validity condition. The microsaccadic responses mediated the association between the aperiodic exponent and the behavioral response. Further analysis showed that the aperiodic exponent of pupil fluctuations predicted the self-rated hyperactivity/impulsivity trait across individuals, suggesting its potential as a marker of attentional deficits. These findings highlight the rich information contained in pupil fluctuations and provide a novel approach to assessing the neural excitation/inhibition balance in attentional processing.
Integrative Mendelian Randomization approaches for therapeutic target prioritisation in immune-mediated diseases
Authors: Sobczyk Maria K , Gaunt Tom R
Published: April 2024

Background: Immune-mediated diseases (IMD) encompass a wide range of autoimmune and inflammatory disorders with aetiology related to immune system dysfunction, signifying a disease area with great potential for drug repurposing. In this study, we employed the genetically informed Mendelian Randomization (MR) method with two distinct exposure types: immune blood cell abundance and protein quantitative trait loci (pQTL) to validate and repurpose 834 drug targets which have been investigated for IMD treatment. Methods: Utilizing two-sample MR, we first established causal relationships between major peripheral immune cell types and 14 IMD. Robust associations, particularly with eosinophils, were confirmed across diseases such as asthma, eczema, sinusitis, and rheumatoid arthritis, revealing 59 high-confidence relationships. Intragenic variants associated with causal immune cell types were then extracted to create instruments for 371 existing IMD drug targets ("intermediate trait" MR). In parallel, we leveraged four large blood plasma protein QTL datasets to obtain complementary instruments for 361 targets ("pQTL" MR). Results: In the intermediate trait MR analysis, we identified 811 gene-IMD associations (p-value <0.05), 169 of which were supported by strong colocalisation evidence (PPH4 > 0.8). In the pQTL MR analysis, we similarly found 841 protein-IMD associations (p-value <0.05), 83 of which were confirmed with colocalization. Comparison with a list of approved drugs indicated low sensitivities across disease outcomes for both exposure types (intermediate trait MR: 0.49 +/- 0.23 SD, pQTL MR: 0.28 +/- 0.12 SD). Conclusions: Drug targets identified in the pQTL and intermediate trait MR analyses show limited overlap (13%), presenting a comprehensive source of drug repurposing opportunities when the two approaches are combined.
Dementia Risk Scores,APOE,and risk of Alzheimer disease: one size does not fit all
Authors: Andrews Shea J. , Boeriu Ana I. , Belloy Michael E. , Renton Alan E. , Fulton-Howard Brian , Brenowitz Willa D. , Yaffe Kristine ,   the Alzheimer’s Disease Neuroimaging Initiative
Published: April 2024

Introduction

Evaluating the generalizability of dementia risk scores, primarily developed in non-Latinx White (NLW) participants, and interactions with genetic risk factors in diverse populations is crucial for addressing health disparities.

Methods

We analyzed the association of the Cardiovascular Risk Factors, Aging, and Incidence of Dementia (CAIDE) and modified CAIDE (mCAIDE) scores with dementia risk using logistic regression models stratified by race/ethnicity in NACC and ADNI, and assessed their interaction withAPOE.

Results

Higher CAIDE scores were associated with an increased risk of dementia in Asian, Latinx, and NLW participants but not in Black participants. In contrast, higher mCAIDE scores were also associated with an increased risk of dementia in Black participants. Unfavorable mCAIDE risk profiles exacerbated theAPOE*ε4 risk effect and attenuated theAPOE*ε2 protective effect.

Discussion

Our findings underscore the importance of evaluating the validity of dementia risk scores in diverse populations for their use in personalized medicine approaches to promote brain health.
Contributions of statistical learning to learning from reward feedback
Authors: Yazdanpanah Aryan , Wang Michael Chong , Trepka Ethan , Benz Marissa , Soltani Alireza
Published: April 2024

Natural environments are abundant with patterns and regularities. These regularities can be captured through statistical learning, which strongly influences perception, memory, and other cognitive functions. By combining a sequence-prediction task with an orthogonal multidimensional reward learning task, we tested whether detecting environmental regularities can also enhance reward learning. We found that participants used regularities about features from the sequence-prediction task to bias their behavior in the learning task. Fitting choice behavior with computational models revealed that this effect was more consistent with attentional modulations of learning, rather than decision making. Specifically, the learning rates for the feature with regularity were higher, particularly when learning from forgone options during unrewarded trials, demonstrating that statistical learning can intensify confirmation bias in reward learning. Overall, our findings suggest that by enhancing learning about certain features, detecting regularities in the environment can reduce dimensionality and thus mitigate the curse of dimensionality in reward learning.

Significance statement

Natural environments are filled with detectable patterns and regularities, which, once identified through statistical learning, engage our attentional system and significantly influence multiple cognitive functions. This study explores whether these processes can enhance reward learning in high-dimensional environments with limited reward feedback. Using a novel experimental paradigm and computational methods, we discovered that detecting regularities in specific stimulus features increases learning rates for those features, especially for unrewarded, forgone options. Our findings suggest that identifying environmental regularities can improve feature-based learning and mitigate the curse of dimensionality.
xSiGra: Explainable model for single-cell spatial data elucidation
Authors: Budhkar Aishwarya , Tang Ziyang , Liu Xiang , Zhang Xuhong , Su Jing , Song Qianqian
Published: April 2024

Recent advancements in spatial imaging technologies have revolutionized the acquisition of high-resolution multi-channel images, gene expressions, and spatial locations at the single-cell level. Our study introduces xSiGra, an interpretable graph-based AI model, designed to elucidate interpretable features of identified spatial cell types, by harnessing multi-modal features from spatial imaging technologies. By constructing a spatial cellular graph with immunohistology images and gene expression as node attributes, xSiGra employs hybrid graph transformer models to delineate spatial cell types. Additionally, xSiGra integrates a novel variant of Grad-CAM component to uncover interpretable features, including pivotal genes and cells for various cell types, thereby facilitating deeper biological insights from spatial data. Through rigorous benchmarking against existing methods, xSiGra demonstrates superior performance across diverse spatial imaging datasets. Application of xSiGra on a lung tumor slice unveils the importance score of cells, illustrating that cellular activity is not solely determined by itself but also impacted by neighboring cells. Moreover, leveraging the identified interpretable genes, xSiGra reveals endothelial cell subset interacting with tumor cells, indicating its heterogeneous underlying mechanisms within the complex cellular communications.