J Clin Transl Sci. 2024 Apr 5;8(1):e74. doi: 10.1017/cts.2024.513. eCollection 2024.

ABSTRACT

Trauma is a common cause of morbidity and mortality in humans and companion animals. Recent efforts in procedural development, training, quality systems, data collection, and research have positively impacted patient outcomes; however, significant unmet need still exists. Coordinated efforts by collaborative, translational, multidisciplinary teams to advance trauma care and improve outcomes have the potential to benefit both human and veterinary patient populations. Strategic use of veterinary clinical trials informed by expertise along the research spectrum (i.e., benchtop discovery, applied science and engineering, large laboratory animal models, clinical veterinary studies, and human randomized trials) can lead to increased therapeutic options for animals while accelerating and enhancing translation by providing early data to reduce the cost and the risk of failed human clinical trials. Active topics of collaboration across the translational continuum include advancements in resuscitation (including austere environments), acute traumatic coagulopathy, trauma-induced coagulopathy, traumatic brain injury, systems biology, and trauma immunology. Mechanisms to improve funding and support innovative team science approaches to current problems in trauma care can accelerate needed, sustainable, and impactful progress in the field. This review article summarizes our current understanding of veterinary and human trauma, thereby identifying knowledge gaps and opportunities for collaborative, translational research to improve multispecies outcomes. This translational trauma group of MDs, PhDs, and DVMs posit that a common understanding of injury patterns and resulting cellular dysregulation in humans and companion animals has the potential to accelerate translation of research findings into clinical solutions.

PMID:38715566 | PMC:PMC11075112 | DOI:10.1017/cts.2024.513

Clin Epigenetics. 2024 May 7;16(1):62. doi: 10.1186/s13148-024-01652-8.

ABSTRACT

BACKGROUND: Temple syndrome (TS14) is a rare imprinting disorder caused by maternal UPD14, imprinting defects or paternal microdeletions which lead to an increase in the maternal expressed genes and a silencing the paternally expressed genes in the 14q32 imprinted domain. Classical TS14 phenotypic features include pre- and postnatal short stature, small hands and feet, muscular hypotonia, motor delay, feeding difficulties, weight gain, premature puberty along and precocious puberty.

METHODS: An exon array comparative genomic hybridization was performed on a patient affected by psychomotor and language delay, muscular hypotonia, relative macrocephaly, and small hand and feet at two years old. At 6 years of age, the proband presented with precocious thelarche. Genes dosage and methylation within the 14q32 region were analyzed by MS-MLPA. Bisulfite PCR and pyrosequencing were employed to quantification methylation at the four known imprinted differentially methylated regions (DMR) within the 14q32 domain: DLK1 DMR, IG-DMR, MEG3 DMR and MEG8 DMR.

RESULTS: The patient had inherited a 69 Kb deletion, encompassing the entire DLK1 gene, on the paternal allele. Relative hypermethylation of the two maternally methylated intervals, DLK1 and MEG8 DMRs, was observed along with normal methylation level at IG-DMR and MEG3 DMR, resulting in a phenotype consistent with TS14. Additional family members with the deletion showed modest methylation changes at both the DLK1 and MEG8 DMRs consistent with parental transmission.

CONCLUSION: We describe a girl with clinical presentation suggestive of Temple syndrome resulting from a small paternal 14q32 deletion that led to DLK1 whole-gene deletion, as well as hypermethylation of the maternally methylated DLK1-DMR.

PMID:38715103 | DOI:10.1186/s13148-024-01652-8

J Biol Eng. 2024 May 7;18(1):31. doi: 10.1186/s13036-024-00428-1.

ABSTRACT

Alcohol consumption, a pervasive societal issue, poses considerable health risks and socioeconomic consequences. Alcohol-induced hepatic disorders, such as fatty liver disease, alcoholic hepatitis, chronic hepatitis, liver fibrosis, and cirrhosis, underscore the need for comprehensive research. Existing challenges in mimicking chronic alcohol exposure in cellular systems, attributed to ethanol evaporation, necessitate innovative approaches. In this study, we developed a simple, reusable, and controllable device for examining the physiological reactions of hepatocytes to long-term alcohol exposure. Our approach involved a novel device designed to continuously release ethanol into the culture medium, maintaining a consistent ethanol concentration over several days. We evaluated device performance by examining gene expression patterns and cytokine secretion alterations during long-term exposure to ethanol. These patterns were correlated with those observed in patients with alcoholic hepatitis. Our results suggest that our ethanol-releasing device can be used as a valuable tool to study the mechanisms of chronic alcohol-mediated hepatic diseases at the cellular level. Our device offers a practical solution for studying chronic alcohol exposure, providing a reliable platform for cellular research. This innovative tool holds promise for advancing our understanding of the molecular processes involved in chronic alcohol-mediated hepatic diseases. Future research avenues should explore broader applications and potential implications for predicting and treating alcohol-related illnesses.

PMID:38715085 | DOI:10.1186/s13036-024-00428-1

Sci Rep. 2024 May 7;14(1):10440. doi: 10.1038/s41598-024-60875-0.

ABSTRACT

A wide variety of treatments have been developed to improve respiratory function and quality of life in patients with bilateral vocal fold paresis (BVFP). One experimental method is the electrical activation of the posterior cricoarytenoid (PCA) muscle with a laryngeal pacemaker (LP) to open the vocal folds. We used an ovine (sheep) model of unilateral VFP to study the long-term effects of functional electrical stimulation on the PCA muscles. The left recurrent laryngeal nerve was cryo-damaged in all animals and an LP was implanted except for the controls. After a reinnervation phase of six months, animals were pooled into groups that received either no treatment, implantation of an LP only, or implantation of an LP and six months of stimulation with different duty cycles. Automated image analysis of fluorescently stained PCA cross-sections was performed to assess relevant muscle characteristics. We observed a fast-to-slow fibre type shift in response to nerve damage and stimulation, but no complete conversion to a slow-twitch-muscle. Fibre size, proportion of hybrid fibres, and intramuscular collagen content were not substantially altered by the stimulation. These results demonstrate that 30 Hz burst stimulation with duty cycles of 40% and 70% did not induce PCA atrophy or fibrosis. Thus, long-term stimulation with an LP is a promising approach for treating BVFP in humans without compromising muscle conditions.

PMID:38714750 | DOI:10.1038/s41598-024-60875-0

Sci Rep. 2024 May 7;14(1):10450. doi: 10.1038/s41598-024-60447-2.

ABSTRACT

We present an advanced electrochemical immunosensor designed to detect the vascular endothelial growth factor (VEGF) precisely. The sensor is constructed on a modified porous gold electrode through a fabrication process involving the deposition of silver and gold on an FTO substrate. Employing thermal annealing and a de-alloying process, the silver is eliminated from the electrode, producing a reproducible porous gold substrate. Utilizing a well-defined protocol, we immobilize the heavy-chain (VHH) antibody against VEGF on the gold substrate, facilitating VEGF detection through various electrochemical methods. Remarkably, this immunosensor performs well, featuring an impressive detection limit of 0.05 pg/mL and an extensive linear range from 0.1 pg/mL to 0.1 µg/mL. This emphasizes it's to measure biomarkers across a wide concentration spectrum precisely. The robust fabrication methodology in this research underscores its potential for widespread application, offering enhanced precision, reproducibility, and remarkable detection capabilities for the developed immunosensor.

PMID:38714678 | DOI:10.1038/s41598-024-60447-2

Nat Commun. 2024 May 7;15(1):3839. doi: 10.1038/s41467-024-47140-8.

ABSTRACT

Pre-mRNA splicing, a key process in gene expression, can be therapeutically modulated using various drug modalities, including antisense oligonucleotides (ASOs). However, determining promising targets is hampered by the challenge of systematically mapping splicing-regulatory elements (SREs) in their native sequence context. Here, we use the catalytically inactive CRISPR-RfxCas13d RNA-targeting system (dCas13d/gRNA) as a programmable platform to bind SREs and modulate splicing by competing against endogenous splicing factors. SpliceRUSH, a high-throughput screening method, was developed to map SREs in any gene of interest using a lentivirus gRNA library that tiles the genetic region, including distal intronic sequences. When applied to SMN2, a therapeutic target for spinal muscular atrophy, SpliceRUSH robustly identifies not only known SREs but also a previously unknown distal intronic SRE, which can be targeted to alter exon 7 splicing using either dCas13d/gRNA or ASOs. This technology enables a deeper understanding of splicing regulation with applications for RNA-based drug discovery.

PMID:38714659 | DOI:10.1038/s41467-024-47140-8

Nat Commun. 2024 May 7;15(1):3809. doi: 10.1038/s41467-024-47658-x.

ABSTRACT

Mammalian sex determination is controlled by antagonistic gene cascades operating in embryonic undifferentiated gonads. The expression of the Y-linked gene SRY is sufficient to trigger the testicular pathway, whereas its absence in XX embryos leads to ovarian differentiation. Yet, the potential involvement of non-coding regulation in this process remains unclear. Here we show that the deletion of a single microRNA cluster, miR-17~92, induces complete primary male-to-female sex reversal in XY mice. Sry expression is delayed in XY knockout gonads, which develop as ovaries. Sertoli cell differentiation is reduced, delayed and unable to sustain testicular development. Pre-supporting cells in mutant gonads undergo a transient state of sex ambiguity which is subsequently resolved towards the ovarian fate. The miR-17~92 predicted target genes are upregulated, affecting the fine regulation of gene networks controlling gonad development. Thus, microRNAs emerge as key components for mammalian sex determination, controlling Sry expression timing and Sertoli cell differentiation.

PMID:38714644 | DOI:10.1038/s41467-024-47658-x

Sci Total Environ. 2024 May 5:172958. doi: 10.1016/j.scitotenv.2024.172958. Online ahead of print.

ABSTRACT

Mining activities put the Brazilian savannas, a global biodiversity hotspot, in danger of species and soil carbon losses. Experiments employing biosolids have been applied to rejuvenate this degraded ecosystem, but a lingering question yet to be answered is whether the microbiota that inhabits these impoverished soils can be recovered towards its initial steady state after vegetation recovery. Here, we selected an 18-year-old restoration chronosequence of biosolids-treated, untreated mining and native soils to investigate the soil microbiota recovery based on composition, phylogeny, and diversity, as well as the potential factors responsible for ecosystem recovery. Our results revealed that the soil microbiota holds a considerable recovery potential in the degraded Cerrado biome. Biosolids application not only improved soil health, but also led to 41.7 % recovery of the whole microbial community, featuring significantly higher microbiota diversity and enriched groups (e.g., Firmicutes) that benefit carbon storage compared to untreated mining and native soils. The recovered community showed significant compositional distinctions from the untreated mining or native soils, rather than phylogenetic differences, with physiochemical properties explaining 55 % of the overall community changes. This study advances our understanding of soil microbiota dynamics in response to disturbance and restoration by shedding light on its recovery associated with biosolid application in a degraded biodiverse ecosystem.

PMID:38714255 | DOI:10.1016/j.scitotenv.2024.172958

Plant J. 2024 May 7. doi: 10.1111/tpj.16785. Online ahead of print.

ABSTRACT

CRISPR/Cas9 is currently the most powerful tool to generate mutations in plant genomes and more efficient tools are needed as the scale of experiments increases. In the model plant Arabidopsis, the choice of the promoter driving Cas9 expression is critical to generate germline mutations. Several optimal promoters have been reported. However, it is unclear which promoter is ideal as they have not been thoroughly tested side by side. Furthermore, most plant vectors still use one of the two Cas9 nuclear localization sequence (NLS) configurations initially reported. We genotyped more than 6000 Arabidopsis T2 plants to test seven promoters and six types of NLSs across 14 targets to systematically improve the generation of single and multiplex inheritable mutations. We found that the RPS5A promoter and bipartite NLS were individually the most efficient components. When combined, 99% of T2 plants contained at least one knockout (KO) mutation and 84% contained 4- to 7-plex KOs, the highest multiplexing KO rate in Arabidopsis to date. These optimizations will be useful to generate higher-order KOs in the germline of Arabidopsis and will likely be applicable to other CRISPR systems as well.

PMID:38713824 | DOI:10.1111/tpj.16785

Curr Protoc. 2024 May;4(5):e1040. doi: 10.1002/cpz1.1040.

ABSTRACT

In rodents, the first weeks of postnatal life feature remarkable changes in fear memory acquisition, retention, extinction, and discrimination. Early development is also marked by profound changes in brain circuits underlying fear memory processing, with heightened sensitivity to environmental influences and stress, providing a powerful model to study the intersection between brain structure, function, and the impacts of stress. Nevertheless, difficulties related to breeding and housing young rodents, preweaning manipulations, and potential increased variability within that population pose considerable challenges to developmental fear research. Here we discuss several factors that may promote variability in studies examining fear conditioning in young rodents and provide recommendations to increase replicability. We focus primarily on experimental conditions, design, and analysis of rodent fear data, with an emphasis on mouse studies. The convergence of anatomical, synaptic, physiological, and behavioral changes during early life may increase variability, but careful practice and transparency in reporting may improve rigor and consensus in the field. © 2024 The Authors. Current Protocols published by Wiley Periodicals LLC.

PMID:38713136 | DOI:10.1002/cpz1.1040

Ter Arkh. 2024 Apr 16;96(3):205-211. doi: 10.26442/00403660.2024.03.202635.

ABSTRACT

The COVID-19 pandemic has highlighted pressing challenges in biomedical research methodology. It has become obvious that the rapid and effective development of treatments for "new" viral infections is impossible without the coordination of interdisciplinary research and in-depth analysis of data obtained within the framework of the post-genomic paradigm. Presents the results of a systematic computer analysis of 290,000 scientific articles on COVID-19, with an emphasis on the results of post-genomic studies of SARS-CoV-2. The futility of the overly simplified approach, which considers only one "most important receptor protein", only one "key virus gene", etc., is shown. It is shown how post-genomic technologies will make it possible to find informative biomarkers of severe coronavirus infection, including those based on complex immune disorders associated with COVID-19.

PMID:38713033 | DOI:10.26442/00403660.2024.03.202635

Syst Biol. 2024 May 7:syae019. doi: 10.1093/sysbio/syae019. Online ahead of print.

ABSTRACT

Phylogenetic and discrete-trait evolutionary inference depend heavily on an appropriate characterization of the underlying character substitution process. In this paper, we present random-effects substitution models that extend common continuous-time Markov chain models into a richer class of processes capable of capturing a wider variety of substitution dynamics. As these random-effects substitution models often require many more parameters than their usual counterparts, inference can be both statistically and computationally challenging. Thus, we also propose an efficient approach to compute an approximation to the gradient of the data likelihood with respect to all unknown substitution model parameters. We demonstrate that this approximate gradient enables scaling of sampling-based inference, namely Bayesian inference via Hamiltonian Monte Carlo, under random-effects substitution models across large trees and state-spaces. Applied to a dataset of 583 SARS-CoV-2 sequences, an HKY model with random-effects shows strong signals of nonreversibility in the substitution process, and posterior predictive model checks clearly show that it is a more adequate model than a reversible model. When analyzing the pattern of phylogeographic spread of 1441 influenza A virus (H3N2) sequences between 14 regions, a random-effects phylogeographic substitution model infers that air travel volume adequately predicts almost all dispersal rates. A random-effects state-dependent substitution model reveals no evidence for an effect of arboreality on the swimming mode in the tree frog subfamily Hylinae. Simulations reveal that random-effects substitution models can accommodate both negligible and radical departures from the underlying base substitution model. We show that our gradient-based inference approach is over an order of magnitude more time efficient than conventional approaches.

PMID:38712512 | DOI:10.1093/sysbio/syae019

Essays Biochem. 2024 May 7:EBC20230094. doi: 10.1042/EBC20230094. Online ahead of print.

ABSTRACT

The vast structural diversity of sulfated polysaccharides demands an equally diverse array of enzymes known as polysaccharide sulfotransferases (PSTs). PSTs are present across all kingdoms of life, including algae, fungi and archaea, and their sulfation pathways are relatively unexplored. Sulfated polysaccharides possess anti-inflammatory, anticoagulant and anti-cancer properties and have great therapeutic potential. Current identification of PSTs using Pfam has been predominantly focused on the identification of glycosaminoglycan (GAG) sulfotransferases because of their pivotal roles in cell communication, extracellular matrix formation and coagulation. As a result, our knowledge of non-GAG PSTs structure and function remains limited. The major sulfotransferase families, Sulfotransfer_1 and Sulfotransfer_2, display broad homology and should enable the capture of a wide assortment of sulfotransferases but are limited in non-GAG PST sequence annotation. In addition, sequence annotation is further restricted by the paucity of biochemical analyses of PSTs. There are now high-throughput and robust assays for sulfotransferases such as colorimetric PAPS (3'-phosphoadenosine 5'-phosphosulfate) coupled assays, Europium-based fluorescent probes for ratiometric PAP (3'-phosphoadenosine-5'-phosphate) detection, and NMR methods for activity and product analysis. These techniques provide real-time and direct measurements to enhance the functional annotation and subsequent analysis of sulfated polysaccharides across the tree of life to improve putative PST identification and characterisation of function. Improved annotation and biochemical analysis of PST sequences will enhance the utility of PSTs across biomedical and biotechnological sectors.

PMID:38712401 | DOI:10.1042/EBC20230094

NAR Genom Bioinform. 2024 May 6;6(2):lqae046. doi: 10.1093/nargab/lqae046. eCollection 2024 Jun.

ABSTRACT

Variations in serum amino acid levels are linked to a multitude of complex disorders. We report the largest genome-wide association study (GWAS) on nine serum amino acids in the UK Biobank participants (117 944, European descent). We identified 34 genomic loci for circulatory levels of alanine, 48 loci for glutamine, 44 loci for glycine, 16 loci for histidine, 11 loci for isoleucine, 19 loci for leucine, 9 loci for phenylalanine, 32 loci for tyrosine and 20 loci for valine. Our gene-based analysis mapped 46-293 genes associated with serum amino acids, including MIP, GLS2, SLC gene family, GCKR, LMO1, CPS1 and COBLL1.The gene-property analysis across 30 tissues highlighted enriched expression of the identified genes in liver tissues for all studied amino acids, except for isoleucine and valine, in muscle tissues for serum alanine and glycine, in adrenal gland tissues for serum isoleucine and leucine, and in pancreatic tissues for serum phenylalanine. Mendelian randomization (MR) phenome-wide association study analysis and subsequent two-sample MR analysis provided evidence that every standard deviation increase in valine is associated with 35% higher risk of type 2 diabetes and elevated levels of serum alanine and branched-chain amino acids with higher levels of total cholesterol, triglyceride and low-density lipoprotein, and lower levels of high-density lipoprotein. In contrast to reports by observational studies, MR analysis did not support a causal association between studied amino acids and coronary artery disease, Alzheimer's disease, breast cancer or prostate cancer. In conclusion, we explored the genetic architecture of serum amino acids and provided evidence supporting a causal role of amino acids in cardiometabolic health.

PMID:38711861 | PMC:PMC11071119 | DOI:10.1093/nargab/lqae046

Front Med (Lausanne). 2024 Apr 22;11:1243659. doi: 10.3389/fmed.2024.1243659. eCollection 2024.

ABSTRACT

Skin cancer mortality rates continue to rise, and survival analysis is increasingly needed to understand who is at risk and what interventions improve outcomes. However, current statistical methods are limited by inability to synthesize multiple data types, such as patient genetics, clinical history, demographics, and pathology and reveal significant multimodal relationships through predictive algorithms. Advances in computing power and data science enabled the rise of artificial intelligence (AI), which synthesizes vast amounts of data and applies algorithms that enable personalized diagnostic approaches. Here, we analyze AI methods used in skin cancer survival analysis, focusing on supervised learning, unsupervised learning, deep learning, and natural language processing. We illustrate strengths and weaknesses of these approaches with examples. Our PubMed search yielded 14 publications meeting inclusion criteria for this scoping review. Most publications focused on melanoma, particularly histopathologic interpretation with deep learning. Such concentration on a single type of skin cancer amid increasing focus on deep learning highlight growing areas for innovation; however, it also demonstrates opportunity for additional analysis that addresses other types of cutaneous malignancies and expands the scope of prognostication to combine both genetic, histopathologic, and clinical data. Moreover, researchers may leverage multiple AI methods for enhanced benefit in analyses. Expanding AI to this arena may enable improved survival analysis, targeted treatments, and outcomes.

PMID:38711781 | PMC:PMC11070520 | DOI:10.3389/fmed.2024.1243659

Data Brief. 2024 Apr 20;54:110449. doi: 10.1016/j.dib.2024.110449. eCollection 2024 Jun.

ABSTRACT

In the last few decades, perennial mountain streams are becoming increasingly intermittent, due to global climate change and anthropogenic pressures. This phenomenon leads to negative effects on benthic communities' biodiversity and river ecosystems functionality. However, the impact of flow intermittency in previously perennial Alpine streams is still poorly investigated. This dataset consists of all the data collected during a spring sampling campaign performed in April-May 2017 along 13 mountain streams located in the SW Italian Alps. These watercourses have been selected because it was possible to identify two different sampling sites: one perennial, where water has always been flowing throughout the years, and one intermittent, which showed flowing water during the sampling campaign but, in the last decade, has experienced summer dry phases. All the sites have been characterized defining the microhabitats in which samples were retrieved, and physico-chemical data were collected at each site. Biological sampling included benthic macroinvertebrates and diatoms. Therefore, the present dataset offers various biological, ecological and physico-chemical information regarding Alpine streams which have recently become intermittent. Potentially, it could be used for comparisons with different benthic communities present in mountain rivers worldwide which are facing drying events too. The broad range of information present in this dataset offers the possibility to examine only the perennial sites themselves, as an example of good river functionality due to continuous flowing water, or only the intermittent ones, to better understand the effects of drying events on these peculiar ecosystems.

PMID:38711741 | PMC:PMC11070659 | DOI:10.1016/j.dib.2024.110449

Front Immunol. 2024 Apr 22;15:1395642. doi: 10.3389/fimmu.2024.1395642. eCollection 2024.

ABSTRACT

[This corrects the article DOI: 10.3389/fimmu.2022.935692.].

PMID:38711502 | PMC:PMC11070787 | DOI:10.3389/fimmu.2024.1395642

iScience. 2024 Apr 16;27(5):109736. doi: 10.1016/j.isci.2024.109736. eCollection 2024 May 17.

ABSTRACT

Discovering causal effects is at the core of scientific investigation but remains challenging when only observational data are available. In practice, causal networks are difficult to learn and interpret, and limited to relatively small datasets. We report a more reliable and scalable causal discovery method (iMIIC), based on a general mutual information supremum principle, which greatly improves the precision of inferred causal relations while distinguishing genuine causes from putative and latent causal effects. We showcase iMIIC on synthetic and real-world healthcare data from 396,179 breast cancer patients from the US Surveillance, Epidemiology, and End Results program. More than 90% of predicted causal effects appear correct, while the remaining unexpected direct and indirect causal effects can be interpreted in terms of diagnostic procedures, therapeutic timing, patient preference or socio-economic disparity. iMIIC's unique capabilities open up new avenues to discover reliable and interpretable causal networks across a range of research fields.

PMID:38711452 | PMC:PMC11070693 | DOI:10.1016/j.isci.2024.109736

Brief Bioinform. 2024 Mar 27;25(3):bbae217. doi: 10.1093/bib/bbae217.

ABSTRACT

Hi-C data are commonly normalized using single sample processing methods, with focus on comparisons between regions within a given contact map. Here, we aim to compare contact maps across different samples. We demonstrate that unwanted variation, of likely technical origin, is present in Hi-C data with replicates from different individuals, and that properties of this unwanted variation change across the contact map. We present band-wise normalization and batch correction, a method for normalization and batch correction of Hi-C data and show that it substantially improves comparisons across samples, including in a quantitative trait loci analysis as well as differential enrichment across cell types.

PMID:38711367 | DOI:10.1093/bib/bbae217

Elife. 2024 May 7;13:e85694. doi: 10.7554/eLife.85694.

ABSTRACT

Collaborative hunting, in which predators play different and complementary roles to capture prey, has been traditionally believed to be an advanced hunting strategy requiring large brains that involve high-level cognition. However, recent findings that collaborative hunting has also been documented in smaller-brained vertebrates have placed this previous belief under strain. Here, using computational multi-agent simulations based on deep reinforcement learning, we demonstrate that decisions underlying collaborative hunts do not necessarily rely on sophisticated cognitive processes. We found that apparently elaborate coordination can be achieved through a relatively simple decision process of mapping between states and actions related to distance-dependent internal representations formed by prior experience. Furthermore, we confirmed that this decision rule of predators is robust against unknown prey controlled by humans. Our computational ecological results emphasize that collaborative hunting can emerge in various intra- and inter-specific interactions in nature, and provide insights into the evolution of sociality.

PMID:38711355 | DOI:10.7554/eLife.85694