Interface Focus. 2024 Jun 7;14(3):20230070. doi: 10.1098/rsfs.2023.0070. eCollection 2024 Jun.

ABSTRACT

Ingesta leaves distinct patterns on mammalian teeth during mastication. However, an unresolved challenge is how to include intraspecific variability into dietary reconstruction and the biomechanical aspects of chewing. Two extant populations of the grey wolf (Canis lupus), one from Alaska and one from Sweden, were analysed with consideration to intraspecific dietary variability related to prey size depending on geographical origin, sex and individual age as well as tooth function. Occlusal enamel facets of the upper fourth premolars, first molars and the second lower molar were analysed via three-dimensional surface texture analysis. The Swedish wolves displayed facets characterized by higher peaks and deeper, more voluminous dales, featuring an overall rougher surface than the wolves from Alaska. Compared to females, the Swedish male wolves had a slightly larger dale area and hill volume on their facets. Upper fourth premolars are smoother and had higher values in texture direction compared to upper first molars. The upper first molars were rougher than the occluding lower second molars and were characterized by larger and deeper dales. We find evidence supporting intraspecific dietary segregation, and antagonistic asymmetry in occlusal wear signatures. The data offer new insights into the roles of apex predators like the grey wolf.

PMID:39081625 | PMC:PMC11285477 | DOI:10.1098/rsfs.2023.0070

Front Immunol. 2024 Jul 16;15:1398000. doi: 10.3389/fimmu.2024.1398000. eCollection 2024.

ABSTRACT

Immunity, as defined by systems biology, encompasses a holistic response throughout the body, characterized by intricate connections with various tissues and compartments. However, this concept has been rarely explored in kidney transplantation. In this proof-of-concept study, we investigated a direct association between the allograft phenotype and serum protein signatures. Time-matched samples of graft biopsies and blood serum were collected in a heterogeneous cohort of kidney-transplanted patients (n = 15) for bulk RNA sequencing and proteomics, respectively. RNA transcripts exhibit distinct and reproducible, coregulated gene networks with specific functional profiles. We measured 159 serum proteins and investigated correlations with gene expression networks. Two opposing axes-one related to metabolism and the other to inflammation-were identified. They may represent a biological continuum between the allograft and the serum and correlate with allograft function, but not with interstitial fibrosis or proteinuria. For signature validation, we used two independent proteomic data sets (n = 21). Our findings establish a biological link between the allograft transcriptome and the blood serum proteome, highlighting systemic immune effects in kidney transplantation and offering a promising framework for developing allograft-linked biomarkers.

PMID:39081308 | PMC:PMC11286594 | DOI:10.3389/fimmu.2024.1398000

J R Soc Interface. 2024 Jul;21(216):20240056. doi: 10.1098/rsif.2024.0056. Epub 2024 Jul 31.

ABSTRACT

Wrinkling instabilities of thin elastic sheets can be used to generate periodic structures over a wide range of length scales. Viscosity of the thin elastic sheet or its surrounding medium has been shown to be responsible for dynamic processes. We here consider wrinkling of fluid deformable surfaces. In contrast with thin elastic sheets, with in-plane and out-of-plane elasticity, these surfaces are characterized by in-plane viscous flow and out-of-plane elasticity and have been established as model systems for biomembranes and cellular sheets. We use this hydrodynamic theory and numerically explore the formation of wrinkles and their coarsening, either by a continuous reduction of the enclosed volume or by the continuous increase of the surface area. Both lead to almost identical results for wrinkle formation and the coarsening process, for which a scaling law for the wavenumber is obtained for a broad range of surface viscosity and rate of change of volume or area. However, for large Reynolds numbers and small changes in volume or area, wrinkling can be suppressed and surface hydrodynamics allows for global shape changes following the minimal energy configurations of the Helfrich energy for corresponding reduced volumes.

PMID:39081114 | DOI:10.1098/rsif.2024.0056

J Hematol Oncol. 2024 Jul 30;17(1):58. doi: 10.1186/s13045-024-01572-3.

ABSTRACT

INTRODUCTION: Small Cell Lung Cancer (SCLC) can be classified into transcriptional subtypes with distinct degrees of neuroendocrine (NE) differentiation. Recent evidence supports plasticity among subtypes with a bias toward adoption of low-NE states during disease progression or upon acquired chemotherapy resistance. Here, we identify a role for SMARCA4, the catalytic subunit of the SWI/SNF complex, as a regulator of subtype shift in SCLC.

METHODS: ATACseq and RNAseq experiments were performed in SCLC cells after pharmacological inhibition of SMARCA4. DNA binding of SMARCA4 was characterized by ChIPseq in high-NE SCLC patient derived xenografts (PDXs). Enrichment analyses were applied to transcriptomic data. Combination of FHD-286 and afatinib was tested in vitro and in a set of chemo-resistant SCLC PDXs in vivo.

RESULTS: SMARCA4 expression positively correlates with that of NE genes in both SCLC cell lines and patient tumors. Pharmacological inhibition of SMARCA4 with FHD-286 induces the loss of NE features and downregulates neuroendocrine and neuronal signaling pathways while activating non-NE factors. SMARCA4 binds to gene loci encoding NE-lineage transcription factors ASCL1 and NEUROD1 and alters chromatin accessibility, enhancing NE programs. Enrichment analysis applied to high-confidence SMARCA4 targets confirmed neuron related pathways as the top GO Biological processes regulated by SMARCA4 in SCLC. In parallel, SMARCA4 also controls REST, a known suppressor of the NE phenotype, by regulating SRRM4-dependent REST transcript splicing. Furthermore, SMARCA4 inhibition drives ERBB pathway activation in SCLC, rendering SCLC tumors sensitive to afatinib.

CONCLUSIONS: This study nominates SMARCA4 as a key regulator of the NE state plasticity and defines a novel therapeutic strategy for SCLC.

PMID:39080761 | DOI:10.1186/s13045-024-01572-3

Respir Care. 2024 Jul 30:respcare.11928. doi: 10.4187/respcare.11928. Online ahead of print.

ABSTRACT

BACKGROUND: Beneficial effects of breathing at FIO2 < 0.21 on disease outcomes have been reported in previous preclinical and clinical studies. However, the safety and intra-hospital feasibility of breathing hypoxic gas for 5 d have not been established. In this study, we examined the physiologic effects of breathing a gas mixture with FIO2 as low as 0.11 in 5 healthy volunteers.

METHODS: All 5 subjects completed the study, spending 5 consecutive days in a hypoxic tent, where the ambient oxygen level was lowered in a stepwise manner over 5 d, from FIO2 of 0.16 on the first day to FIO2 of 0.11 on the fifth day of the study. All the subjects returned to an environment at room air on the sixth day. The subjects' SpO2 , heart rate, and breathing frequency were continuously recorded, along with daily blood sampling, neurologic evaluations, transthoracic echocardiography, and mental status assessments.

RESULTS: Breathing hypoxia concentration dependently caused profound physiologic changes, including decreased SpO2 and increased heart rate. At FIO2 of 0.14, the mean SpO2 was 92%; at FIO2 of 0.13, the mean SpO2 was 93%; at FIO2 of 0.12, the mean SpO2 was 88%; at FIO2 of 0.11, the mean SpO2 was 85%; and, finally, at an FIO2 of 0.21, the mean SpO2 was 98%. These changes were accompanied by increased erythropoietin levels and reticulocyte counts in blood. All 5 subjects concluded the study with no adverse events. No subjects exhibited signs of mental status changes or pulmonary hypertension.

CONCLUSIONS: Results of the current physiologic study suggests that, within a hospital setting, delivering FIO2 as low as 0.11 is feasible and safe in healthy subjects, and provides the foundation for future studies in which therapeutic effects of hypoxia breathing are tested.

PMID:39079724 | DOI:10.4187/respcare.11928

Comput Biol Med. 2024 Jul 29;180:108915. doi: 10.1016/j.compbiomed.2024.108915. Online ahead of print.

ABSTRACT

Collective behavior of biological agents from cells to herds of organisms is a fundamental feature in systems biology and in the emergence of new phenomena in the biological environment. Collective cell migration (CCM) under a physical or chemical cue is an example of this fundamental phenomenon where the individual migration of a cell is driven by the collective behavior of the neighboring cells and vice versa. The goal of this research is to discover the mathematical rules of collective cell migration with dynamic mode decomposition (DMD) with the use of experimental data and to test the predictive nature of the models with independent experimental data sets subject to Dirichlet, Neumann, and mixed boundary conditions. Both single and multi-cellular systems are investigated in this process. Additionally, the goal of this research is to create an optimal trajectory for microscopic robots in the presence of an obstacle course made of both static and dynamic obstacles. Such an optimization is made possible by synthesizing the discovered dynamics for cell migration with a numerical approach to dynamic optimization known as collocation by augmenting the discovered dynamics to the constraint equations. The optimal trajectory results presented in silico have potential design applications for the path planning of microrobots for therapeutic purposes such as cancer cell drug delivery, microsurgery, microsensing for early disease detection, and cleaning of toxic substances.

PMID:39079415 | DOI:10.1016/j.compbiomed.2024.108915

EMBO Mol Med. 2024 Jul 30. doi: 10.1038/s44321-024-00107-0. Online ahead of print.

ABSTRACT

Extracellularly released molecular inflammasome assemblies -ASC specks- cross-seed Aβ amyloid in Alzheimer's disease. Here we show that ASC governs the extent of inflammation-induced amyloid A (AA) amyloidosis, a systemic disease caused by the aggregation and peripheral deposition of the acute-phase reactant serum amyloid A (SAA) in chronic inflammatory conditions. Using super-resolution microscopy, we found that ASC colocalized tightly with SAA in human AA amyloidosis. Recombinant ASC specks accelerated SAA fibril formation and mass spectrometry after limited proteolysis showed that ASC interacts with SAA via its pyrin domain (PYD). In a murine model of inflammatory AA amyloidosis, splenic amyloid load was conspicuously decreased in Pycard-/- mice which lack ASC. Treatment with anti-ASCPYD antibodies decreased amyloid loads in wild-type mice suffering from AA amyloidosis. The prevalence of natural anti-ASC IgG (-logEC50 ≥ 2) in 19,334 hospital patients was <0.01%, suggesting that anti-ASC antibody treatment modalities would not be confounded by natural autoimmunity. These findings expand the role played by ASC and IL-1 independent inflammasome employments to extraneural proteinopathies and suggest that anti-ASC immunotherapy may contribute to resolving such diseases.

PMID:39080493 | DOI:10.1038/s44321-024-00107-0

Nat Commun. 2024 Jul 30;15(1):6411. doi: 10.1038/s41467-024-50867-z.

ABSTRACT

Proteins in the open ocean represent a significant source of organic matter, and their profiles reflect the metabolic activities of marine microorganisms. Here, by analyzing metaproteomic samples collected from the Pacific, Atlantic and Southern Ocean, we reveal size-fractionated patterns of the structure and function of the marine microbiota protein pool in the water column, particularly in the dark ocean (>200 m). Zooplankton proteins contributed three times more than algal proteins to the deep-sea community metaproteome. Gammaproteobacteria exhibited high metabolic activity in the deep-sea, contributing up to 30% of bacterial proteins. Close virus-host interactions of this taxon might explain the dominance of gammaproteobacterial proteins in the dissolved fraction. A high urease expression in nitrifiers suggested links between their dark carbon fixation and zooplankton urea production. In summary, our results uncover the taxonomic contribution of the microbiota to the oceanic protein pool, revealing protein fluxes from particles to the dissolved organic matter pool.

PMID:39080340 | DOI:10.1038/s41467-024-50867-z

Free Radic Res. 2024 Jul 30:1-16. doi: 10.1080/10715762.2024.2386457. Online ahead of print.

ABSTRACT

Ovarian cancer, marked by high rate of recurrence, novel therapeutic strategies are needed to improve patient outcome. One of the potential strategies is inducing ferroptosis in ovarian cancer cells. Ferroptosis is an iron-dependent, lipid peroxidation-driven mode of cell death primarily occurring on the cell membrane. PTRF, an integral component of the caveolae structures located on the cell membrane, is involved in a multitude of physiological processes, including but not limited to, endocytosis, signal transduction, and lipid metabolism. This study elucidates the relationship between PTRF and ferroptosis in ovarian cancer, offering a fresh perspective for the development of new therapeutic strategies. We knocked down PTRF employing siRNA in the ovarian cancer cell lines HEY and SKOV3, following which we stimulated ferroptosis with Erastin (Era). Our research indicates that the lack of PTRF sensitizes cancer cell to ferroptosis, likely by altering membrane stability and tension, thereby affecting signal pathways related to ferroptosis, such as lipid and atherosclerosis, fluid shear stress and atherosclerosis. Our findings provide new insights for developing new treatments for ovarian cancer.

PMID:39079051 | DOI:10.1080/10715762.2024.2386457

J Phys Chem Lett. 2024 Jul 30:8000-8006. doi: 10.1021/acs.jpclett.4c01103. Online ahead of print.

ABSTRACT

Bacterial microcompartments (BMCs) are self-assembling, selectively permeable protein shells that encapsulate enzymes to enhance catalytic efficiency of segments of metabolic pathways through means of confinement. The modular nature of BMC shells' structure and assembly enables programming of shell permeability and underscores their promise in biotechnology engineering efforts for applications in industry, medicine, and clean energy. Realizing this potential requires methods for encapsulation of abiotic molecules, which have been developed here for the first time. We report in vitro cargo loading of BMC shells with ruthenium photosensitizers (RuPS) by two approaches─one involving site-specific covalent labeling and the other driven by diffusion, requiring no specific interactions between cargo molecules and shell proteins. The highly stable shells retain encapsulated cargo over 1 week without egress and preserve RuPS photophysical activity. This study is an important foundation for further work that will converge biological BMC architecture with synthetic chemistry to facilitate biohybrid photocatalysis.

PMID:39079038 | DOI:10.1021/acs.jpclett.4c01103

Bioinformatics. 2024 Jul 30:btae489. doi: 10.1093/bioinformatics/btae489. Online ahead of print.

ABSTRACT

SUMMARY: Harmonizing variant indexing and allele assignments across datasets is crucial for data integrity in cross-dataset studies such as multi-cohort genome-wide association studies, meta-analyses, and the development, validation, and application of polygenic risk scores. Ensuring this indexing and allele consistency is a laborious, time-consuming, and error-prone process requiring a certain degree of computational proficiency. Here, we introduce GRIEVOUS, a command-line tool for cross-dataset variant homogenization. By means of an internal database and a custom indexing methodology, GRIEVOUS identifies, formats, and aligns all biallelic SNPs across all summary statistic and genotype files of interest. Upon completion of dataset harmonization, GRIEVOUS can also be used to extract the maximal set of biallelic SNPs common to all datasets.

AVAILABILITY AND IMPLEMENTATION: GRIEVOUS and all supporting documentation and tutorials can be found at https://github.com/jvtalwar/GRIEVOUS. It is freely and publicly available under the MIT license and can be installed via pip.

SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

PMID:39078222 | DOI:10.1093/bioinformatics/btae489

mSystems. 2024 Jul 30:e0029524. doi: 10.1128/msystems.00295-24. Online ahead of print.

ABSTRACT

Microbiome studies have revealed gut microbiota's potential impact on complex diseases. However, many studies often focus on one disease per cohort. We developed a meta-analysis workflow for gut microbiome profiles and analyzed shotgun metagenomic data covering 11 diseases. Using interpretable machine learning and differential abundance analysis, our findings reinforce the generalization of binary classifiers for Crohn's disease (CD) and colorectal cancer (CRC) to hold-out cohorts and highlight the key microbes driving these classifications. We identified high microbial similarity in disease pairs like CD vs ulcerative colitis (UC), CD vs CRC, Parkinson's disease vs type 2 diabetes (T2D), and schizophrenia vs T2D. We also found strong inverse correlations in Alzheimer's disease vs CD and UC. These findings, detected by our pipeline, provide valuable insights into these diseases.

IMPORTANCE: Assessing disease similarity is an essential initial step preceding a disease-based approach for drug repositioning. Our study provides a modest first step in underscoring the potential of integrating microbiome insights into the disease similarity assessment. Recent microbiome research has predominantly focused on analyzing individual diseases to understand their unique characteristics, which by design excludes comorbidities in individuals. We analyzed shotgun metagenomic data from existing studies and identified previously unknown similarities between diseases. Our research represents a pioneering effort that utilizes both interpretable machine learning and differential abundance analysis to assess microbial similarity between diseases.

PMID:39078158 | DOI:10.1128/msystems.00295-24

Bioinformatics. 2024 Jul 30:btae465. doi: 10.1093/bioinformatics/btae465. Online ahead of print.

ABSTRACT

MOTIVATION: Chemical reaction networks (CRNs) play a pivotal role in diverse fields such as systems biology, biochemistry, chemical engineering, and epidemiology. High-level definitions of CRNs enables to use various simulation approaches, including deterministic and stochastic methods, from the same model. However, existing Python tools for simulation of CRN typically wrap external C/C ++ libraries for model definition, translation into equations and/or numerically solving them, limiting their extensibility and integration with the broader Python ecosystem.

RESULTS: In response, we developed Poincaré and SimBio, two novel Python packages for simulation of dynamical systems and CRNs. Poincaré serves as a foundation for dynamical systems modelling, while SimBio extends this functionality to CRNs, including support for the Systems Biology Markup Language (SBML). Poincaré and SimBio are developed as pure Python packages enabling users to easily extend their simulation capabilities by writing new or leveraging other Python packages. Moreover, this does not compromise the performance, as code can be just-in-time (JIT) compiled with Numba. Our benchmark tests using curated models from the BioModels repository demonstrate that these tools may provide a potentially superior performance advantage compared to other existing tools. Additionally, to ensure a user-friendly experience, our packages use standard typed modern Python syntax that provides a seamless integration with integrated development environments (IDEs). Our Python-centric approach significantly enhances code analysis, error detection, and refactoring capabilities, positioning Poincaré and SimBio as valuable tools for the modelling community.

AVAILABILITY: Poincaré and SimBio are released under the MIT license. their source code is available on GitHub (https://github.com/maurosilber/poincare and https://github.com/hgrecco/simbio). and can be installed from PyPI or conda-forge.

PMID:39078116 | DOI:10.1093/bioinformatics/btae465

Food Nutr Bull. 2024 Jul 30:3795721241250104. doi: 10.1177/03795721241250104. Online ahead of print.

ABSTRACT

BACKGROUND: A randomized controlled trial in Bangladeshi children aged 12 to 18 months with moderate acute malnutrition found that dietary supplementation with the microbiota-directed complementary food (MDCF-2) significantly improved weight gain and repaired gut microbiota compared to the ready-to-use supplementary food. However, the MDCF-2 formulation was made daily from locally available ingredients and the need for a packaged, nutritionally compliant, and organoleptically acceptable MDCF-2 prototype was essential for future large-scale clinical studies.

OBJECTIVE: The study aimed to develop and assess the acceptability of 3 alternative foil-packaged formulations of MDCF-2 in comparison to current MDCF-2.

METHODS: Of the 3 packaged formulations, the Jumpstart version was provided in 2 sachets, the other 2 formulations were provided in a retort-stable foil pouch extended by sterilization, and microbiological growth was monitored over 10 months. The acceptability study included 40 children aged 8 to 12 months living in an urban slum in Dhaka, and the organoleptic properties were assessed using a 7-point hedonic scale.

RESULTS: In the 100 g distributed over the 2 sessions, children consumed 82.5 ± 7.84 g (mean ± SD) of kitchen-prepared MDCF-2, 85.4 ± 7.15 g of the "Jumpstart" MDCF-2 formulation, 85.4 ± 8.70 g of the MDCF-2 with green banana powder, and 86.2 ± 4.26 g of the MDCF-2 with sweet potato formulation. The "Jumpstart" MDCF-2 and MDCF-2 with sweet potato achieved the highest overall acceptability scores on the hedonic scale; although none of the shelf-stable formulations were significantly different from the kitchen-prepared MDCF-2.

CONCLUSIONS: Packaged, shelf-stable prototypes of MDCF-2 exhibited comparable acceptability among Bangladeshi children aged 8 to 12 months to the original freshly prepared formulation.

PMID:39077991 | DOI:10.1177/03795721241250104

Adv Sci (Weinh). 2024 Jul 29:e2400163. doi: 10.1002/advs.202400163. Online ahead of print.

ABSTRACT

Mastering the self-organization of nanoparticle morphologies is pivotal in soft matter physics and film growth. Silicon dioxide (SiO2) nanoparticles are an archetypical model of nanomotor in soft matter. Here, the emphasis is on the self-organizing behavior of SiO2 nanoparticles under extreme conditions. It is unveiled that manipulating the states of the metal substrate profoundly dictates the motion characteristics of SiO2 nanoparticles. This manipulation triggers the emergence of intricate morphologies and distinctive patterns. Employing a reaction-diffusion model, the fundamental roles played by Brownian motion and Marangoni-driven motion in shaping fractal structures and radial Turing patterns are demonstrated, respectively. Notably, these radial Turing patterns showcase hyperuniform order, challenging conventional notions of film morphology. These discoveries pave the way for crafting non-equilibrium morphological materials, poised with the potential for self-healing, adaptability, and innovative applications.

PMID:39075843 | DOI:10.1002/advs.202400163

bioRxiv [Preprint]. 2024 Jul 21:2024.07.20.604399. doi: 10.1101/2024.07.20.604399.

ABSTRACT

The mammalian cerebral cortex comprises a complex neuronal network that maintains a delicate balance between excitatory neurons and inhibitory interneurons. Previous studies, including our own research, have shown that specific interneuron subtypes are closely associated with particular pyramidal neuron types, forming stereotyped local inhibitory microcircuits. However, the developmental processes that establish these precise networks are not well understood. Here we show that pyramidal neuron types are instrumental in driving the terminal differentiation and maintaining the survival of specific associated interneuron subtypes. In a wild-type cortex, the relative abundance of different interneuron subtypes aligns precisely with the pyramidal neuron types to which they synaptically target. In Fezf2 mutant cortex, characterized by the absence of layer 5 pyramidal tract neurons and an expansion of layer 6 intratelencephalic neurons, we observed a corresponding decrease in associated layer 5b interneurons and an increase in layer 6 subtypes. Interestingly, these shifts in composition are achieved through mechanisms specific to different interneuron types. While SST interneurons adjust their abundance to the change in pyramidal neuron prevalence through the regulation of programmed cell death, parvalbumin interneurons alter their identity. These findings illustrate two key strategies by which the dynamic interplay between pyramidal neurons and interneurons allows local microcircuits to be sculpted precisely. These insights underscore the precise roles of extrinsic signals from pyramidal cells in the establishment of interneuron diversity and their subsequent integration into local cortical microcircuits.

PMID:39071350 | PMC:PMC11275907 | DOI:10.1101/2024.07.20.604399

Phys Biol. 2024 Jul 29. doi: 10.1088/1478-3975/ad68b6. Online ahead of print.

ABSTRACT

Analyzing transcription data requires intensive statistical analysis to obtain useful biological information and knowledge. A significant portion of this data is affected by random noise or even noise intrinsic to the modeling of the experiment. Without robust treatment, the data might not be explored thoroughly, and incorrect conclusions could be drawn. Examining the correlation between gene expression profiles is one way bioinformaticians extract information from transcriptomic experiments. However, the correlation measurements traditionally used have worrisome shortcomings that need to be addressed. This paper compares five already published and experimented with correlation measurements to the newly developed coincidence index, a similarity measurement that combines Jaccard and interiority indexes and generalizes them to be applied to vectors containing real values. We used microarray and RNA-Seq data from the archaeon Halobacterium salinarum and the bacterium Escherichia coli, respectively, to evaluate the capacity of each correlation/similarity measurement. The utilized method explores the co-expressed metabolic pathways by measuring the correlations between the expression levels of enzymes that share metabolites, represented in the form of a weighted graph. It then searches for local maxima in this graph using a simulated annealing algorithm. We demonstrate that the coincidence index extracts larger, more comprehensive, and more statistically significant pathways for microarray experiments. In RNA-Seq experiments, the results are more limited, but the coincidence index managed the largest percentage of significant components in the graph.

PMID:39074502 | DOI:10.1088/1478-3975/ad68b6

Nephron. 2024 Jul 29. doi: 10.1159/000540307. Online ahead of print.

ABSTRACT

Diabetic kidney disease is the most common driver of chronic kidney disease (CKD)-associated mortality and kidney replacement therapy. Despite recent therapeutic advances (SGLT2 inhibitors, finerenone), the residual kidney and mortality risk remains high for patients already diagnosed of having CKD (i.e., estimated glomerular filtration rate &lt;60 ml/min/1.73 m2 or urinary albumin:creatinine ratio &gt;30 mg/g). The challenge for the near future is to identify patients at higher risk of developing CKD to initiate therapy before CKD develops (primary prevention of CKD) and to identify patients with CKD and high risk of progression or death, in order to intensify therapy. We now discuss recent advances in biomarkers that may contribute to identify such high-risk individuals for clinical trials of novel primary prevention or treatment approaches for CKD. The most advanced biomarker from a clinical development point of view is the urinary peptidomics classifier CKD273, that integrates prognostic information from 273 urinary peptides and identifies high risk individuals before CKD develops.

PMID:39074450 | DOI:10.1159/000540307

J Transl Med. 2024 Jul 29;22(1):697. doi: 10.1186/s12967-024-05507-x.

ABSTRACT

BACKGROUND: Aldehyde dehydrogenase 2 (ALDH2) is critical for alcohol metabolism by converting acetaldehyde to acetic acid. In East Asian descendants, an inactive genetic variant in ALDH2, rs671, triggers an alcohol flushing response due to acetaldehyde accumulation. As alcohol flushing is not exclusive to those of East Asian descent, we questioned whether additional ALDH2 genetic variants can drive facial flushing and inefficient acetaldehyde metabolism using human testing and biochemical assays.

METHODS: After IRB approval, human subjects were given an alcohol challenge (0.25 g/kg) while quantifying acetaldehyde levels and the physiological response (heart rate and skin temperature) to alcohol. Further, by employing biochemical techniques including human purified ALDH2 proteins and transiently transfected NIH 3T3 cells, we characterized two newly identified ALDH2 variants for ALDH2 enzymatic activity, ALDH2 dimer/tetramer formation, and reactive oxygen species production after alcohol treatment.

RESULTS: Humans heterozygous for rs747096195 (R101G) or rs190764869 (R114W) had facial flushing and a 2-fold increase in acetaldehyde levels, while rs671 (E504K) had facial flushing and a 6-fold increase in acetaldehyde levels relative to wild type ALDH2 carriers. In vitro studies with recombinant R101G and R114W ALDH2 enzyme showed a reduced efficiency in acetaldehyde metabolism that is unique when compared to E504K or wild-type ALDH2. The effect is caused by a lack of functional dimer/tetramer formation for R101G and decreased Vmax for both R101G and R114W. Transiently transfected NIH-3T3 cells with R101G and R114W also had a reduced enzymatic activity by ~ 50% relative to transfected wild-type ALDH2 and when subjected to alcohol, the R101G and R114W variants had a 2-3-fold increase in reactive oxygen species formation with respect to wild type ALDH2.

CONCLUSIONS: We identified two additional ALDH2 variants in humans causing facial flushing and acetaldehyde accumulation after alcohol consumption. As alcohol use is associated with a several-fold higher risk for esophageal cancer for the E504K variant, the methodology developed here to characterize ALDH2 genetic variant response to alcohol can lead the way precision medicine strategies to further understand the interplay of alcohol consumption, ALDH2 genetics, and cancer.

PMID:39075523 | DOI:10.1186/s12967-024-05507-x

BMC Biol. 2024 Jul 29;22(1):159. doi: 10.1186/s12915-024-01959-1.

ABSTRACT

BACKGROUND: Recent studies have shown that several long non-coding RNAs (lncRNAs) in the placenta are associated with preeclampsia (PE). However, the extent to which lncRNAs may contribute to the pathological progression of PE is unclear.

RESULTS: Here, we report a hierarchical regulatory network involved in early-onset severe PE (EOSPE). We have carried out transcriptome sequencing on the placentae from patients and normal subjects to identify the differentially expressed genes (DEGs), including some lncRNAs (DElncRNAs). We then constructed a high-quality hierarchical regulatory network of lncRNAs, transcription factors (TFs), and target DEGs, containing 1851 lncRNA-TF interactions and 6901 TF-promoter interactions. The lncRNA-to-target regulatory interactions were further validated by the triplex structures between the DElncRNAs and the promoters of the target DEGs. The DElncRNAs in the regulatory network were clustered into 3 clusters, one containing DElncRNAs correlated with the blood pressure, including FLNB-AS1 with targeting 27.89% (869/3116) DEGs in EOSPE. We further demonstrated that FLNB-AS1 could bind the transcription factor JUNB to regulate a series members of the HIF-1 signaling pathway in trophoblast cells.

CONCLUSIONS: Our results suggest that the differential expression of lncRNAs may perturb the lncRNA-TF-DEG hierarchical regulatory network, leading to the dysregulation of many genes involved in EOSPE. Our study provides a new strategy and a valuable resource for studying the mechanism underlying gene dysregulation in EOSPE patients.

PMID:39075446 | DOI:10.1186/s12915-024-01959-1