Comput Struct Biotechnol J. 2023 Jul 25;21:3696-3704. doi: 10.1016/j.csbj.2023.07.031. eCollection 2023.

ABSTRACT

The assessment of muscle condition is of great importance in various research areas. In particular, evaluating the degree of intramuscular fat (IMF) in tissue sections is a challenging task, which today is still mostly performed qualitatively or quantitatively by a highly subjective and error-prone manual analysis. We here realize the mission to make automated IMF analysis possible that (i) minimizes subjectivity, (ii) provides accurate and quantitative results quickly, and (iii) is cost-effective using standard hematoxylin and eosin (H&E) stained tissue sections. To address all these needs in a deep learning approach, we utilized the convolutional encoder-decoder network SegNet to train the specialized network IMFSegNet allowing to accurately quantify the spatial distribution of IMF in histological sections. Our fully automated analysis was validated on 17 H&E-stained muscle sections from individual sheep and compared to various state-of-the-art approaches. Not only does IMFSegNet outperform all other approaches, but this neural network also provides fully automated and highly accurate results utilizing the most cost-effective procedures of sample preparation and imaging. Furthermore, we shed light on the opacity of black-box approaches such as neural networks by applying an explainable artificial intelligence technique to clarify that the success of IMFSegNet actually lies in identifying the hard-to-detect IMF structures. Embedded in our open-source visual programming language JIPipe that does not require programming skills, it can be expected that IMFSegNet advances muscle condition assessment in basic research across multiple areas as well as in research fields focusing on translational clinical applications.

PMID:37560127 | PMC:PMC10407270 | DOI:10.1016/j.csbj.2023.07.031

iScience. 2023 Jul 13;26(8):107368. doi: 10.1016/j.isci.2023.107368. eCollection 2023 Aug 18.

ABSTRACT

Although dietary fructose is associated with an elevated risk for pancreatic cancer, the underlying mechanisms remain elusive. Here, we report that ketohexokinase (KHK), the rate-limiting enzyme of fructose metabolism, is a driver of PDAC development. We demonstrate that fructose triggers KHK and induces fructolytic gene expression in mouse and human PDAC. Genetic inactivation of KhkC enhances the survival of KPC-driven PDAC even in the absence of high fructose diet. Furthermore, it decreases the viability, migratory capability, and growth of KPC cells in a cell autonomous manner. Mechanistically, we demonstrate that genetic ablation of KHKC strongly impairs the activation of KRAS-MAPK pathway and of rpS6, a downstream target of mTORC signaling. Moreover, overexpression of KHKC in KPC cells enhances the downstream KRAS pathway and cell viability. Our data provide new insights into the role of KHK in PDAC progression and imply that inhibiting KHK could have profound implications for pancreatic cancer therapy.

PMID:37559908 | PMC:PMC10407955 | DOI:10.1016/j.isci.2023.107368

iScience. 2023 Jul 13;26(8):107378. doi: 10.1016/j.isci.2023.107378. eCollection 2023 Aug 18.

ABSTRACT

Cancer is an extremely complex disease and each type of cancer usually has several different subtypes. Multi-omics data can provide more comprehensive biological information for identifying and discovering cancer subtypes. However, existing unsupervised cancer subtyping methods cannot effectively learn comprehensive shared and specific information of multi-omics data. Therefore, a novel method is proposed based on shared and specific representation learning. For each omics data, two autoencoders are applied to extract shared and specific information, respectively. To reduce redundancy and mutual interference, orthogonality constraint is introduced to separate shared and specific information. In addition, contrastive learning is applied to align the shared information and strengthen their consistency. Finally, the obtained shared and specific information for all samples are used for clustering tasks to achieve cancer subtyping. Experimental results demonstrate that the proposed method can effectively capture shared and specific information of multi-omics data and outperform other state-of-the-art methods on cancer subtyping.

PMID:37559907 | PMC:PMC10407241 | DOI:10.1016/j.isci.2023.107378

J Allergy Clin Immunol. 2023 Aug 7:S0091-6749(23)00982-X. doi: 10.1016/j.jaci.2023.08.001. Online ahead of print.

NO ABSTRACT

PMID:37558058 | DOI:10.1016/j.jaci.2023.08.001

Genomics Inform. 2023 Jun;21(2):e23. doi: 10.5808/gi.23003. Epub 2023 Jun 30.

ABSTRACT

The mammalian sirtuin family, consisting of SIRT1-SIRT7, plays a vital role in various biological processes, including cancer, diabetes, neurodegeneration, cardiovascular disease, cellular metabolism, and cellular homeostasis maintenance. Due to their involvement in these biological processes, modulating sirtuin activity seems promising to impact immune- and aging-related diseases, as well as cancer pathways. However, more understanding is required regarding the safety and efficacy of sirtuin-targeted therapies due to the complex regulatory mechanisms that govern their activity, particularly in the context of multiple targets. In this study, the interaction landscape of the sirtuin family was analyzed using a systems biology approach. A sirtuin protein-protein interaction network was built using the Cytoscape platform and analyzed using the NetworkAnalyzer and stringApp plugins. The result revealed the sirtuin family's association with numerous proteins that play diverse roles, suggesting a complex interplay between sirtuins and other proteins. Based on network topological and functional analysis, SIRT1 was identified as the most prominent among sirtuin family members, demonstrating that 25 of its protein partners are involved in cancer, 22 in innate immune response, and 29 in aging, with some being linked to a combination of two or more pathways. This study lays the foundation for the development of novel therapies that can target sirtuins with precision and efficacy. By illustrating the various interactions among the proteins in the sirtuin family, we have revealed the multifaceted roles of SIRT1 and provided a framework for their possible roles to be precisely understood, manipulated, and translated into therapeutics in the future.

PMID:37557919 | DOI:10.5808/gi.23003

Bioessays. 2023 Aug 9:e2300015. doi: 10.1002/bies.202300015. Online ahead of print.

ABSTRACT

Microbial systems biology has made enormous advances in relating microbial physiology to the underlying biochemistry and molecular biology. By meticulously studying model microorganisms, in particular Escherichia coli and Saccharomyces cerevisiae, increasingly comprehensive computational models predict metabolic fluxes, protein expression, and growth. The modeling rationale is that cells are constrained by a limited pool of resources that they allocate optimally to maximize fitness. As a consequence, the expression of particular proteins is at the expense of others, causing trade-offs between cellular objectives such as instantaneous growth, stress tolerance, and capacity to adapt to new environments. While current computational models are remarkably predictive for E. coli and S. cerevisiae when grown in laboratory environments, this may not hold for other growth conditions and other microorganisms. In this contribution, we therefore discuss the relationship between the instantaneous growth rate, limited resources, and long-term fitness. We discuss uses and limitations of current computational models, in particular for rapidly changing and adverse environments, and propose to classify microbial growth strategies based on Grimes's CSR framework.

PMID:37559168 | DOI:10.1002/bies.202300015

Methods Mol Biol. 2023;2706:177-190. doi: 10.1007/978-1-0716-3397-7_13.

ABSTRACT

Limited proteolysis coupled to mass spectrometry (LiP-MS) is a recent proteomics technique that allows structure-based target engagement profiling on a proteome-wide level. To achieve this, native lysates are first incubated with a compound, followed by a short incubation with a nonspecific protease. Binding of a compound can change accessibility at the binding site or induce other structural changes in the target. This leads to treatment-specific proteolytic fingerprints upon limited proteolysis, which can be analyzed by standard bottom-up MS-based proteomics. Here, we describe a basic LiP-MS protocol using the natural product rapamycin as an example compound. Along with the provided LiP-MS reference data available via ProteomeXchange with identifier PXD035183, this enables the straightforward implementation of the method by scientists with a basic biochemistry and mass spectrometry background. We describe how the procedure can easily be adapted to other protein samples and small molecules.

PMID:37558949 | DOI:10.1007/978-1-0716-3397-7_13

Nature. 2023 Aug 9. doi: 10.1038/s41586-023-06392-y. Online ahead of print.

ABSTRACT

The concomitant occurrence of tissue growth and organization is a hallmark of organismal development1-3. This often means that proliferating and differentiating cells are found at the same time in a continuously changing tissue environment. How cells adapt to architectural changes to prevent spatial interference remains unclear. Here, to understand how cell movements that are key for growth and organization are orchestrated, we study the emergence of photoreceptor neurons that occur during the peak of retinal growth, using zebrafish, human tissue and human organoids. Quantitative imaging reveals that successful retinal morphogenesis depends on the active bidirectional translocation of photoreceptors, leading to a transient transfer of the entire cell population away from the apical proliferative zone. This pattern of migration is driven by cytoskeletal machineries that differ depending on the direction: microtubules are exclusively required for basal translocation, whereas actomyosin is involved in apical movement. Blocking the basal translocation of photoreceptors induces apical congestion, which hampers the apical divisions of progenitor cells and leads to secondary defects in lamination. Thus, photoreceptor migration is crucial to prevent competition for space, and to allow concurrent tissue growth and lamination. This shows that neuronal migration, in addition to its canonical role in cell positioning4, can be involved in coordinating morphogenesis.

PMID:37558872 | DOI:10.1038/s41586-023-06392-y

Nat Med. 2023 Aug 9. doi: 10.1038/s41591-023-02512-3. Online ahead of print.

NO ABSTRACT

PMID:37558759 | DOI:10.1038/s41591-023-02512-3

Sci Rep. 2023 Aug 9;13(1):12942. doi: 10.1038/s41598-023-40189-3.

ABSTRACT

Abiotic stress in cucumber (Cucumis sativus L.) may trigger distinct transcriptome responses, resulting in significant yield loss. More insight into the molecular underpinnings of the stress response can be gained by combining RNA-Seq meta-analysis with systems biology and machine learning. This can help pinpoint possible targets for engineering abiotic tolerance by revealing functional modules and key genes essential for the stress response. Therefore, to investigate the regulatory mechanism and key genes, a combination of these approaches was utilized in cucumber subjected to various abiotic stresses. Three significant abiotic stress-related modules were identified by gene co-expression network analysis (WGCNA). Three hub genes (RPL18, δ-COP, and EXLA2), ten transcription factors (TFs), one transcription regulator, and 12 protein kinases (PKs) were introduced as key genes. The results suggest that the identified PKs probably govern the coordination of cellular responses to abiotic stress in cucumber. Moreover, the C2H2 TF family may play a significant role in cucumber response to abiotic stress. Several C2H2 TF target stress-related genes were identified through co-expression and promoter analyses. Evaluation of the key identified genes using Random Forest, with an area under the curve of ROC (AUC) of 0.974 and an accuracy rate of 88.5%, demonstrates their prominent contributions in the cucumber response to abiotic stresses. These findings provide novel insights into the regulatory mechanism underlying abiotic stress response in cucumber and pave the way for cucumber genetic engineering toward improving tolerance ability under abiotic stress.

PMID:37558755 | DOI:10.1038/s41598-023-40189-3

Nat Commun. 2023 Aug 9;14(1):4808. doi: 10.1038/s41467-023-40482-9.

ABSTRACT

Chemokine receptors constitute an important subfamily of G protein-coupled receptors (GPCRs), and they are critically involved in a broad range of immune response mechanisms. Ligand promiscuity among these receptors makes them an interesting target to explore multiple aspects of biased agonism. Here, we comprehensively characterize two chemokine receptors namely, CXCR4 and CXCR7, in terms of their transducer-coupling and downstream signaling upon their stimulation by a common chemokine agonist, CXCL12, and a small molecule agonist, VUF11207. We observe that CXCR7 lacks G-protein-coupling while maintaining robust βarr recruitment with a major contribution of GRK5/6. On the other hand, CXCR4 displays robust G-protein activation as expected but exhibits significantly reduced βarr-coupling compared to CXCR7. These two receptors induce distinct βarr conformations even when activated by the same agonist, and CXCR7, unlike CXCR4, fails to activate ERK1/2 MAP kinase. We also identify a key contribution of a single phosphorylation site in CXCR7 for βarr recruitment and endosomal localization. Our study provides molecular insights into intrinsic-bias encoded in the CXCR4-CXCR7 system with broad implications for drug discovery.

PMID:37558722 | DOI:10.1038/s41467-023-40482-9

Nat Commun. 2023 Aug 9;14(1):4816. doi: 10.1038/s41467-023-40541-1.

ABSTRACT

Cholesterol biosynthesis is a highly regulated, oxygen-dependent pathway, vital for cell membrane integrity and growth. In fungi, the dependency on oxygen for sterol production has resulted in a shared transcriptional response, resembling prolyl hydroxylation of Hypoxia Inducible Factors (HIFs) in metazoans. Whether an analogous metazoan pathway exists is unknown. Here, we identify Sterol Regulatory Element Binding Protein 2 (SREBP2), the key transcription factor driving sterol production in mammals, as an oxygen-sensitive regulator of cholesterol synthesis. SREBP2 degradation in hypoxia overrides the normal sterol-sensing response, and is HIF independent. We identify MARCHF6, through its NADPH-mediated activation in hypoxia, as the main ubiquitin ligase controlling SREBP2 stability. Hypoxia-mediated degradation of SREBP2 protects cells from statin-induced cell death by forcing cells to rely on exogenous cholesterol uptake, explaining why many solid organ tumours become auxotrophic for cholesterol. Our findings therefore uncover an oxygen-sensitive pathway for governing cholesterol synthesis through regulated SREBP2-dependent protein degradation.

PMID:37558666 | DOI:10.1038/s41467-023-40541-1

Anal Chem. 2023 Aug 9. doi: 10.1021/acs.analchem.3c02564. Online ahead of print.

ABSTRACT

There remains an unmet need for a fully integrated microfluidic platform that can automatically perform multistep and multireagent immunoassays. Here, we proposed a novel online dual-active valve-based centrifugal microfluidic chip, termed DAVM, for fully automatic point-of-care immunoassay. Practically, the puncture valve, one of the dual active valves, is capable of achieving precise, on-demand, sequential release of prestored reagents, while the other valve-reversible active valve enables controlled retention and drainage of the reaction solutions. Thereby, our technology mitigates the challenges of hydrophilic/hydrophobic modifications and unstable valve control performance commonly observed in passive valve controls. As a proof of concept, the indirect enzymatic immunoblotting technique was employed on DAVM for fully automated immunological analysis of eight targets, yielding outcomes within an hour. Furthermore, we conducted a comparative analysis of 28 clinical samples with autoimmune diseases. According to 224 clinical data, the sample testing concordance rate between DAVM and the traditional instrument was 82%, with a target compliance rate of 97%. Therefore, our DAVM system has powerful potential for fully automated immunoassays.

PMID:37556853 | DOI:10.1021/acs.analchem.3c02564

PLoS Comput Biol. 2023 Aug 9;19(8):e1011371. doi: 10.1371/journal.pcbi.1011371. Online ahead of print.

ABSTRACT

The purple non-sulfur bacterium Rhodopseudomonas palustris is recognized as a critical microorganism in the nitrogen and carbon cycle and one of the most common members in wastewater treatment communities. This bacterium is metabolically extremely versatile. It is capable of heterotrophic growth under aerobic and anaerobic conditions, but also able to grow photoautotrophically as well as mixotrophically. Therefore R. palustris can adapt to multiple environments and establish commensal relationships with other organisms, expressing various enzymes supporting degradation of amino acids, carbohydrates, nucleotides, and complex polymers. Moreover, R. palustris can degrade a wide range of pollutants under anaerobic conditions, e.g., aromatic compounds such as benzoate and caffeate, enabling it to thrive in chemically contaminated environments. However, many metabolic mechanisms employed by R. palustris to breakdown and assimilate different carbon and nitrogen sources under chemoheterotrophic or photoheterotrophic conditions remain unknown. Systems biology approaches, such as metabolic modeling, have been employed extensively to unravel complex mechanisms of metabolism. Previously, metabolic models have been reconstructed to study selected capabilities of R. palustris under limited experimental conditions. Here, we developed a comprehensive metabolic model (M-model) for R. palustris Bis A53 (iDT1294) consisting of 2,721 reactions, 2,123 metabolites, and comprising 1,294 genes. We validated the model using high-throughput phenotypic, physiological, and kinetic data, testing over 350 growth conditions. iDT1294 achieved a prediction accuracy of 90% for growth with various carbon and nitrogen sources and close to 80% for assimilation of aromatic compounds. Moreover, the M-model accurately predicts dynamic changes of growth and substrate consumption rates over time under nine chemoheterotrophic conditions and demonstrated high precision in predicting metabolic changes between photoheterotrophic and photoautotrophic conditions. This comprehensive M-model will help to elucidate metabolic processes associated with the assimilation of multiple carbon and nitrogen sources, anoxygenic photosynthesis, aromatic compound degradation, as well as production of molecular hydrogen and polyhydroxybutyrate.

PMID:37556472 | DOI:10.1371/journal.pcbi.1011371

Biofactors. 2023 Aug 9. doi: 10.1002/biof.1996. Online ahead of print.

ABSTRACT

Vector-borne infectious diseases are still an important global health problem. Malaria is the most important among them, mainly pediatric, life-threatening disease. Malaria and other vector-borne disorders caused by parasites, bacteria, and viruses have a strong impact on public health and significant economic costs. Most vector-borne diseases could be prevented by vector control, with attention to the ecological and biodiversity conservation aspects. Chemical control with pesticides and insecticides is widely used as a measure of prevention although increasing resistance to insecticides is a serious issue in vector control. Metabolic resistance is the most common mechanism and poses a big challenge. Insect enzyme systems, including monooxygenase CYP P450 enzymes, are employed by vectors mainly to metabolize insecticides thus causing resistance. The discovery and application of natural specific inhibitors/blockers of vector P450 enzymes as synergists for commonly used pesticides will contribute to the "greening" of insecticides. Besides vector CYPs, host CYP enzymes could also be exploited to fight against vector-borne diseases: using mostly their detoxifying properties and involvement in the immune response. Here, we review published research data on P450 enzymes from all players in vector-borne infections, that is, pathogens, vectors, and hosts, regarding the potential role of CYPs in disease. We discuss strategies on how to exploit cytochromes P450 in vector-borne disease control.

PMID:37555735 | DOI:10.1002/biof.1996

Biol Chem. 2023 Aug 9. doi: 10.1515/hsz-2023-0198. Online ahead of print.

ABSTRACT

Amyotrophic lateral sclerosis (ALS) is a progressive neurological disorder with currently no cure. Central to the cellular dysfunction associated with this fatal proteinopathy is the accumulation of unfolded/misfolded superoxide dismutase 1 (SOD1) in various subcellular locations. The molecular mechanism driving the formation of SOD1 aggregates is not fully understood but numerous studies suggest that aberrant aggregation escalates with folding instability of mutant apoSOD1. Recent advances on combining organelle-targeting therapies with the anti-aggregation capacity of chemical chaperones have successfully reduce the subcellular load of misfolded/aggregated SOD1 as well as their downstream anomalous cellular processes at low concentrations (micromolar range). Nevertheless, if such local aggregate reduction directly correlates with increased folding stability remains to be explored. To fill this gap, we synthesized and tested here the effect of 9 ER-, mitochondria- and lysosome-targeted chemical chaperones on the folding stability of truncated monomeric SOD1 (SOD1bar) mutants directed to those organelles. We found that compound ER-15 specifically increased the native state stability of ER-SOD1bar-A4V, while scaffold compound FDA-approved 4-phenylbutyric acid (PBA) decreased it. Furthermore, our results suggested that ER15 mechanism of action is distinct from that of PBA, opening new therapeutic perspectives of this novel chemical chaperone on ALS treatment.

PMID:37555646 | DOI:10.1515/hsz-2023-0198

J Proteome Res. 2023 Aug 9. doi: 10.1021/acs.jproteome.3c00092. Online ahead of print.

ABSTRACT

The ongoing pandemic of the coronavirus disease 2019 (COVID-19) caused by the severe acute respiratory syndrome coronavirus 2 still has limited treatment options. Our understanding of the molecular dysregulations that occur in response to infection remains incomplete. We developed a web application COVIDpro (https://www.guomics.com/covidPro/) that includes proteomics data obtained from 41 original studies conducted in 32 hospitals worldwide, involving 3077 patients and covering 19 types of clinical specimens, predominantly plasma and serum. The data set encompasses 53 protein expression matrices, comprising a total of 5434 samples and 14,403 unique proteins. We identified a panel of proteins that exhibit significant dysregulation, enabling the classification of COVID-19 patients into severe and non-severe disease categories. The proteomic signatures achieved promising results in distinguishing severe cases, with a mean area under the curve of 0.87 and accuracy of 0.80 across five independent test sets. COVIDpro serves as a valuable resource for testing hypotheses and exploring potential targets for novel treatments in COVID-19 patients.

PMID:37555633 | DOI:10.1021/acs.jproteome.3c00092

Amyotroph Lateral Scler Frontotemporal Degener. 2023 Aug 9:1-7. doi: 10.1080/21678421.2023.2239300. Online ahead of print.

ABSTRACT

Objective: To assemble and characterize an electronic health record (EHR) dataset for a large cohort of US military Veterans diagnosed with ALS (Amyotrophic Lateral Sclerosis). Methods: An EHR dataset for 19,662 Veterans diagnosed with ALS between January 1, 2000 to December 31, 2020 was compiled from the Veterans Health Administration (VHA) EHR database by a query for ICD9 diagnosis (335.20) or ICD10 diagnosis (G12.21) for Amyotrophic Lateral Sclerosis. Results: The cohort is predominantly male (98.94%) and white (72.37%) with a median age at disease onset of 68 years and median survival from the date of diagnosis of 590 days. With the designation of ALS as a compensable illness in 2009, there was a subsequent increase in the number of Veterans diagnosed per year in the VHA, but no change in median survival. The cohort included a greater-than-expected proportion of individuals whose branch of service at the time of separation was the Army. Conclusions: The composition of the cohort reflects the VHA population who are at greatest risk for ALS. The greater than expected proportion of individuals whose branch of service at the time of separation was the Army suggests the possibility of a branch-specific risk factor for ALS.

PMID:37555559 | DOI:10.1080/21678421.2023.2239300

Psychol Med. 2023 Aug 9:1-10. doi: 10.1017/S0033291723001812. Online ahead of print.

ABSTRACT

BACKGROUND: Smoking contributes to a variety of neurodegenerative diseases and neurobiological abnormalities, suggesting that smoking is associated with accelerated brain aging. However, the neurobiological mechanisms affected by smoking, and whether they are genetically influenced, remain to be investigated.

METHODS: Using structural magnetic resonance imaging data from the UK Biobank (n = 33 293), a brain age predictor was trained on non-smoking healthy groups and tested on smokers to obtain the BrainAge Gap (BAG). The cumulative effect of multiple common genetic variants associated with smoking was then calculated to acquire a polygenic risk score (PRS). The relationship between PRS, BAG, total gray matter volume (tGMV), and smoking parameters was explored and further genes included in the PRS were annotated to identify potential molecular mechanisms affected by smoking.

RESULTS: The BrainAge in smokers was predicted with very high accuracy (r = 0.725, MAE = 4.16). Smokers had a greater BAG (Cohen's d = 0.074, p < 0.0001) and higher PRS (Cohen's d = 0.63, p < 0.0001) than non-smokers. A higher PRS was associated with increased amount of smoking, mediated by BAG and tGMV. Several neurotransmitters and ion channel pathways were enriched in the group of smoking-related genes involved in addiction, brain synaptic plasticity, and some neurological disorders.

CONCLUSION: By using a simplified single indicator of the entire brain (BAG) in combination with the PRS, this study highlights the greater BAG in smokers and its linkage with genes and smoking behavior, providing insight into the neurobiological underpinnings and potential features of smoking-related aging.

PMID:37555321 | DOI:10.1017/S0033291723001812

Lasers Surg Med. 2023 Aug 9. doi: 10.1002/lsm.23715. Online ahead of print.

ABSTRACT

OBJECTIVES: Normothermic machine perfusion (NMP) provides a platform for pre-transplant kidney quality assessment that is essential for the use of marginal donor kidneys. Laser speckle contrast imaging (LSCI) presents distinct advantages as a real-time and noncontact imaging technique for measuring microcirculation. In this study, we aimed to assess the value of LSCI in visualizing renal cortical perfusion and investigate the additional value of dual-side LSCI measurements compared to single aspect measurement during NMP.

METHODS: Porcine kidneys were obtained from a slaughterhouse and then underwent NMP. LSCI was used to measure one-sided cortical perfusion in the first 100 min of NMP. Thereafter, the inferior renal artery branch was occluded to induce partial ischemia and LSCI measurements on both ventral and dorsal sides were performed.

RESULTS: LSCI fluxes correlated linearly with the renal blood flow (R2 = 0.90, p < 0.001). After renal artery branch occlusion, absence of renal cortical perfusion could be visualized and semiquantified by LSCI. The overall ischemic area percentage of the ventral and dorsal sides was comparable (median interquartile range [IQR], 38 [24-43]% vs. 29 [17-46]%, p = 0.43), but heterogenous patterns between the two aspects were observed. There was a significant difference in oxygen consumption (mean ± standard deviation [SD], 2.57 ± 0.63 vs. 1.83 ± 0.49 mLO2 /min/100 g, p < 0.001), urine output (median [IQR], 1.3 [1.1-1.7] vs. 0.8 [0.6-1.3] mL/min, p < 0.05), lactate dehydrogenase (mean ± SD, 768 ± 370 vs. 905 ± 401 U/L, p < 0.05) and AST (mean ± SD, 352 ± 285 vs. 462 ± 383 U/L, p < 0.01) before and after renal artery occlusion, while no significant difference was found in creatinine clearance, fractional excretion of sodium, total sodium reabsorption and histological damage.

CONCLUSIONS: LSCI fluxes correlated linearly with renal blood flow during NMP. Renal cortical microcirculation and absent perfusion can be visualized and semiquantified by LSCI. It provides a relative understanding of perfusion levels, allowing for a qualitative comparison between regions in the kidney. Dual-side LSCI measurements are of added value compared to single aspect measurement and renal function markers.

PMID:37555246 | DOI:10.1002/lsm.23715