T cell antigen receptor recognition of antigen-presenting molecules.

The Major Histocompatibility Complex (MHC) locus encodes classical MHC class I and MHC class II molecules and nonclassical MHC-I molecules. The architecture of these molecules is ideally suited to capture and present an array of peptide antigens (Ags). In addition, the CD1 family members and MR1 are MHC class I-like molecules that bind lipid-based Ags and vitamin B precursors, respectively. These Ag-bound molecules are subsequently recognized by T cell antigen receptors (TCRs) expressed on the surface of T lymphocytes. Structural and associated functional studies have been highly informative in providing insight into these interactions, which are crucial to immunity, and how they can lead to aberrant T cell reactivity. Investigators have determined over thirty unique TCR-peptide-MHC-I complex structures and twenty unique TCR-peptide-MHC-II complex structures. These investigations have shown a broad consensus in docking geometry and provided insight into MHC restriction. Structural studies on TCR-mediated recognition of lipid and metabolite Ags have been mostly confined to TCRs from innate-like natural killer T cells and mucosal-associated invariant T cells, respectively. These studies revealed clear differences between TCR-lipid-CD1, TCR-metabolite-MR1, and TCR-peptide-MHC recognition. Accordingly, TCRs show remarkable structural and biological versatility in engaging different classes of Ag that are presented by polymorphic and monomorphic Ag-presenting molecules of the immune system.

Unconventional or Preset αß T Cells: Evolutionarily Conserved Tissue-Resident T Cells Recognizing Nonpeptidic Ligands.

A majority of T cells bearing the αß T cell receptor (TCR) are specific for peptides bound to polymorphic classical major histocompatibility complex (MHC) molecules. Smaller subsets of T cells are reactive toward various nonpeptidic ligands associated with nonpolymorphic MHC class-Ib (MHC-Ib) molecules. These cells have been termed unconventional for decades, even though only the composite antigen is different from the one seen by classical T cells. Herein, we discuss the identity of these particular T cells in light of the coevolution of their TCR and MHC-Ib restricting elements. We examine their original thymic development: selection on hematopoietic cells leading to the acquisition of an original differentiation program. Most of these cells acquire memory cell features during thymic maturation and exhibit unique patterns of migration into peripheral nonlymphoid tissues to become tissue resident. Thus, these cells are termed preset T cells, as they also display a variety of effector functions. They may act as microbial or danger sentinels, fight microbes, or regulate tissue homeostasis.

Magnetic resonance linear accelerator technology and adaptive radiation therapy: An overview for clinicians.

Radiation therapy (RT) continues to play an important role in the treatment of cancer. Adaptive RT (ART) is a novel method through which RT treatments are evolving. With the ART approach, computed tomography or magnetic resonance (MR) images are obtained as part of the treatment delivery process. This enables the adaptation of the irradiated volume to account for changes in organ and/or tumor position, movement, size, or shape that may occur over the course of treatment. The advantages and challenges of ART maybe somewhat abstract to oncologists and clinicians outside of the specialty of radiation oncology. ART is positioned to affect many different types of cancer. There is a wide spectrum of hypothesized benefits, from small toxicity improvements to meaningful gains in overall survival. The use and application of this novel technology should be understood by the oncologic community at large, such that it can be appropriately contextualized within the landscape of cancer therapies. Likewise, the need to test these advances is pressing. MR-guided ART (MRgART) is an emerging, extended modality of ART that expands upon and further advances the capabilities of ART. MRgART presents unique opportunities to iteratively improve adaptive image guidance. However, although the MRgART adaptive process advances ART to previously unattained levels, it can be more expensive, time-consuming, and complex. In this review, the authors present an overview for clinicians describing the process of ART and specifically MRgART.

Engineering bionanoreactor in bacteria for efficient hydrogen production.

Hydrogen production through water splitting is a vital strategy for renewable and sustainable clean energy. In this study, we developed an approach integrating nanomaterial engineering and synthetic biology to establish a bionanoreactor system for efficient hydrogen production. The periplasmic space (20 to 30 nm) of an electroactive bacterium, Shewanella oneidensis MR-1, was engineered to serve as a bionanoreactor to enhance the interaction between electrons and protons, catalyzed by hydrogenases for hydrogen generation. To optimize electron transfer, we used the microbially reduced graphene oxide (rGO) to coat the electrode, which improved the electron transfer from the electrode to the cells. Native MtrCAB protein complex on S. oneidensis and self-assembled iron sulfide (FeS) nanoparticles acted in tandem to facilitate electron transfer from an electrode to the periplasm. To enhance proton transport, S. oneidensis MR-1 was engineered to express Gloeobacter rhodopsin (GR) and the light-harvesting antenna canthaxanthin. This led to efficient proton pumping when exposed to light, resulting in a 35.6% increase in the rate of hydrogen production. The overexpression of native [FeFe]-hydrogenase further improved the hydrogen production rate by 56.8%. The bionanoreactor engineered in S. oneidensis MR-1 achieved a hydrogen yield of 80.4 µmol/mg protein/day with a Faraday efficiency of 80% at a potential of -0.75 V. This periplasmic bionanoreactor combines the strengths of both nanomaterial and biological components, providing an efficient approach for microbial electrosynthesis.

Using clustering of genetic variants in Mendelian randomization to interrogate the causal pathways underlying multimorbidity from a common risk factor.

Mendelian randomization (MR) is an epidemiological approach that utilizes genetic variants as instrumental variables to estimate the causal effect of an exposure on a health outcome. This paper investigates an MR scenario in which genetic variants aggregate into clusters that identify heterogeneous causal effects. Such variant clusters are likely to emerge if they affect the exposure and outcome via distinct biological pathways. In the multi-outcome MR framework, where a shared exposure causally impacts several disease outcomes simultaneously, these variant clusters can provide insights into the common disease-causing mechanisms underpinning the co-occurrence of multiple long-term conditions, a phenomenon known as multimorbidity. To identify such variant clusters, we adapt the general method of agglomerative hierarchical clustering to multi-sample summary-data MR setup, enabling cluster detection based on variant-specific ratio estimates. Particularly, we tailor the method for multi-outcome MR to aid in elucidating the causal pathways through which a common risk factor contributes to multiple morbidities. We show in simulations that our "MR-AHC" method detects clusters with high accuracy, outperforming the existing methods. We apply the method to investigate the causal effects of high body fat percentage on type 2 diabetes and osteoarthritis, uncovering interconnected cellular processes underlying this multimorbid disease pair.

Mouse mucosal-associated invariant T cell receptor recognition of MR1 presenting the vitamin B metabolite, 5-(2-oxopropylideneamino)-6-d-ribitylaminouracil.

Mucosal-associated invariant T (MAIT) cells can elicit immune responses against riboflavin-based antigens presented by the evolutionary conserved MHC class I related protein, MR1. While we have an understanding of the structural basis of human MAIT cell receptor (TCR) recognition of human MR1 presenting a variety of ligands, how the semi-invariant mouse MAIT TCR binds mouse MR1-ligand remains unknown. Here, we determine the crystal structures of 2 mouse TRAV1-TRBV13-2+ MAIT TCR-MR1-5-OP-RU ternary complexes, whose TCRs differ only in the composition of their CDR3ß loops. These mouse MAIT TCRs mediate high affinity interactions with mouse MR1-5-OP-RU and cross-recognize human MR1-5-OP-RU. Similarly, a human MAIT TCR could bind mouse MR1-5-OP-RU with high affinity. This cross-species recognition indicates the evolutionary conserved nature of this MAIT TCR-MR1 axis. Comparing crystal structures of the mouse versus human MAIT TCR-MR1-5-OP-RU complexes provides structural insight into the conserved nature of this MAIT TCR-MR1 interaction and conserved specificity for the microbial antigens, whereby key germline-encoded interactions required for MAIT activation are maintained. This is an important consideration for the development of MAIT cell-based therapeutics that will rely on preclinical mouse models of disease.

MAIT cell-MR1 reactivity is highly conserved across multiple divergent species.

Mucosal-associated invariant T (MAIT) cells are a subset of unconventional T cells that recognize small molecule metabolites presented by major histocompatibility complex class I related protein 1 (MR1), via an αß T cell receptor (TCR). MAIT TCRs feature an essentially invariant TCR α-chain, which is highly conserved between mammals. Similarly, MR1 is the most highly conserved major histocompatibility complex-I-like molecule. This extreme conservation, including the mode of interaction between the MAIT TCR and MR1, has been shown to allow for species-mismatched reactivities unique in T cell biology, thereby allowing the use of selected species-mismatched MR1-antigen (MR1-Ag) tetramers in comparative immunology studies. However, the pattern of cross-reactivity of species-mismatched MR1-Ag tetramers in identifying MAIT cells in diverse species has not been formally assessed. We developed novel cattle and pig MR1-Ag tetramers and utilized these alongside previously developed human, mouse, and pig-tailed macaque MR1-Ag tetramers to characterize cross-species tetramer reactivities. MR1-Ag tetramers from each species identified T cell populations in distantly related species with specificity that was comparable to species-matched MR1-Ag tetramers. However, there were subtle differences in staining characteristics with practical implications for the accurate identification of MAIT cells. Pig MR1 is sufficiently conserved across species that pig MR1-Ag tetramers identified MAIT cells from the other species. However, MAIT cells in pigs were at the limits of phenotypic detection. In the absence of sheep MR1-Ag tetramers, a MAIT cell population in sheep blood was identified phenotypically, utilizing species-mismatched MR1-Ag tetramers. Collectively, our results validate the use and define the limitations of species-mismatched MR1-Ag tetramers in comparative immunology studies.

Elucidating the role of liver enzymes as markers and regulators in ovarian cancer: a synergistic approach using Mendelian randomization, single-cell analysis, and clinical evidence.

OBJECTIVE: To investigate the association between liver enzymes and ovarian cancer (OC), and to validate their potential as biomarkers and their mechanisms in OC. Methods Genome-wide association studies for OC and levels of enzymes such as Alkaline phosphatase (ALP), Aspartate aminotransferase (AST), Alanine aminotransferase, and gamma-glutamyltransferase were analyzed. Univariate and multivariate Mendelian randomization (MR), complemented by the Steiger test, identified enzymes with a potential causal relationship to OC. Single-cell transcriptomics from the GSE130000 dataset pinpointed pivotal cellular clusters, enabling further examination of enzyme-encoding gene expression. Transcription factors (TFs) governing these genes were predicted to construct TF-mRNA networks. Additionally, liver enzyme levels were retrospectively analyzed in healthy individuals and OC patients, alongside the evaluation of correlations with cancer antigen 125 (CA125) and Human Epididymis Protein 4 (HE4). RESULTS: A total of 283 single nucleotide polymorphisms (SNPs) and 209 SNPs related to ALP and AST, respectively. Using the inverse-variance weighted method, univariate MR (UVMR) analysis revealed that ALP (P = 0.050, OR = 0.938) and AST (P = 0.017, OR = 0.906) were inversely associated with OC risk, suggesting their roles as protective factors. Multivariate MR (MVMR) confirmed the causal effect of ALP (P = 0.005, OR = 0.938) on OC without reverse causality. Key cellular clusters including T cells, ovarian cells, endothelial cells, macrophages, cancer-associated fibroblasts (CAFs), and epithelial cells were identified, with epithelial cells showing high expression of genes encoding AST and ALP. Notably, TFs such as TCE4 were implicated in the regulation of GOT2 and ALPL genes. OC patient samples exhibited decreased ALP levels in both blood and tumor tissues, with a negative correlation between ALP and CA125 levels observed. CONCLUSION: This study has established a causal link between AST and ALP with OC, identifying them as protective factors. The increased expression of the genes encoding these enzymes in epithelial cells provides a theoretical basis for developing novel disease markers and targeted therapies for OC.

The impact of metabolic syndrome on the cerebral cortex: a Mendelian randomization study.

Metabolic syndrome exhibits associations with diverse neurological disorders, and its potential influence on the cerebral cortex may be one of the many potential factors contributing to these adverse outcomes. In this study, we aimed to investigate the causal relationship between metabolic syndrome and changes in cerebral cortex structure using Mendelian randomization analysis. Genome-wide association study data for the 5 components of metabolic syndrome were obtained from individuals of European descent in the UK Biobank. Genome-wide association study data for 34 known cortical functional regions were sourced from the ENIGMA Consortium. Data on Alzheimer's disease, major depression, and anxiety disorder were obtained from the IEU Open genome-wide association study database. The causal links between metabolic syndrome elements and cerebral cortex architecture were evaluated using inverse variance weighting, Mendelian randomization-Egger, and weighted median techniques, with inverse variance weighting as the primary method. Inverse variance weighting, Mendelian randomization Egger, weighted median, simple mode, and weighted mode methods were employed to assess the relationships between metabolic syndrome and neurological diseases (Alzheimer's disease, major depression, and anxiety disorder). Outliers, heterogeneity, and pleiotropy were assessed using Cochran's Q test, MR-PRESSO, leave-one-out analysis, and funnel plots. Globally, no causal link was found between metabolic syndrome and overall cortical thickness or surface area. However, regionally, metabolic syndrome may influence the surface area of specific regions, including the caudal anterior cingulate, postcentral, posterior cingulate, rostral anterior cingulate, isthmus cingulate, superior parietal, rostral middle frontal, middle temporal, insula, pars opercularis, cuneus, and inferior temporal. It may also affect the thickness of the medial orbitofrontal, caudal middle frontal, paracentral, superior frontal, superior parietal, and supramarginal regions. These findings were nominally significant and withstood sensitivity analyses, showing no substantial heterogeneity or pleiotropy. Furthermore, we found an association between metabolic syndrome and the risk of Alzheimer's disease, major depression, and anxiety disorder. This study suggests a potential association between metabolic syndrome and changes in cerebral cortex structure, which may underlie certain neurological disorders. Furthermore, we found an association between metabolic syndrome and the risk of Alzheimer's disease, major depression, and anxiety disorder. Early diagnosis of metabolic syndrome holds significance in preventing these neurological disorders.

A diffusion MRI-based spatiotemporal continuum of the embryonic mouse brain for probing gene-neuroanatomy connections.

The embryonic mouse brain undergoes drastic changes in establishing basic anatomical compartments and laying out major axonal connections of the developing brain. Correlating anatomical changes with gene-expression patterns is an essential step toward understanding the mechanisms regulating brain development. Traditionally, this is done in a cross-sectional manner, but the dynamic nature of development calls for probing gene-neuroanatomy interactions in a combined spatiotemporal domain. Here, we present a four-dimensional (4D) spatiotemporal continuum of the embryonic mouse brain from E10.5 to E15.5 reconstructed from diffusion magnetic resonance microscopy (dMRM) data. This study achieved unprecedented high-definition dMRM at 30- to 35-µm isotropic resolution, and together with computational neuroanatomy techniques, we revealed both morphological and microscopic changes in the developing brain. We transformed selected gene-expression data to this continuum and correlated them with the dMRM-based neuroanatomical changes in embryonic brains. Within the continuum, we identified distinct developmental modes comprising regional clusters that shared developmental trajectories and similar gene-expression profiles. Our results demonstrate how this 4D continuum can be used to examine spatiotemporal gene-neuroanatomical interactions by connecting upstream genetic events with anatomical changes that emerge later in development. This approach would be useful for large-scale analysis of the cooperative roles of key genes in shaping the developing brain.

The immune system in neurological diseases: What innate-like T cells have to say.

The immune system classically consists of 2 lines of defense, innate and adaptive, both of which interact with one another effectively to protect us against any pathogenic threats. Importantly, there is a diverse subset of cells known as innate-like T cells that act as a bridge between the innate and adaptive immune systems and are pivotal players in eliciting inflammatory immune responses. A growing body of evidence has demonstrated the regulatory impact of these innate-like T cells in central nervous system (CNS) diseases and that such immune cells can traffic into the brain in multiple pathological conditions, which can be typically attributed to the breakdown of the blood-brain barrier. However, until now, it has been poorly understood whether innate-like T cells have direct protective or causative properties, particularly in CNS diseases. Therefore, in this review, our attention is focused on discussing the critical roles of 3 unique subsets of unconventional T cells, namely, natural killer T cells, γδ T cells, and mucosal-associated invariant T cells, in the context of CNS diseases, disorders, and injuries and how the interplay of these immune cells modulates CNS pathology, in an attempt to gain a better understanding of their complex functions.

Ultrathin Gd-Oxide Nanosheet as Ultrasensitive Companion Diagnostic Tool for MR Imaging and Therapy of Submillimeter Microhepatocellular Carcinoma.

Early stage hepatocellular carcinoma (HCC) presents a formidable challenge in clinical settings due to its asymptomatic progression and the limitations of current imaging techniques in detecting micro-HCC lesions. Addressing this critical issue, we introduce a novel ultrathin gadolinium-oxide (Gd-oxide) nanosheet-based platform with heightened sensitivity for high-field MRI and as a therapeutic agent for HCC. Synthesized via a digestive ripening process, these Gd-oxide nanosheets exhibit an exceptional acid-responsive profile. The integration of the ultrathin Gd-oxide with an acid-responsive polymer creates an ultrasensitive high-field MRI probe, enabling the visualization of submillimeter-sized tumors with superior sensitivity. Our research underscores the ultrasensitive probe's efficacy in the treatment of orthotopic HCC. Notably, the ultrasensitive probe functions dually as a companion diagnostic tool, facilitating simultaneous imaging and therapy with real-time treatment monitoring capabilities. In conclusion, this study showcases an innovative companion diagnostic tool that holds promise for the early detection and effective treatment of micro-HCC.

Weak and pleiotropy robust sex-stratified Mendelian randomization in the one sample and two sample settings.

BACKGROUND: Mendelian randomization (MR) leverages genetic data as an instrumental variable to provide estimates for the causal effect of an exposure X on a health outcome Y that is robust to confounding. Unfortunately, horizontal pleiotropy-the direct association of a genetic variant with multiple phenotypes-is highly prevalent and can easily render a genetic variant an invalid instrument. METHODS: Building on existing work, we propose a simple method for leveraging sex-specific genetic associations to perform weak and pleiotropy-robust MR analysis. This is achieved by constructing an MR estimator in which pleiotropy is perfectly removed by cancellation, while placing it within the powerful machinery of the robust adjusted profile score (MR-RAPS) method. Pleiotropy cancellation has the attractive property that it removes heterogeneity and therefore justifies a statistically efficient fixed effects model. We extend the method from the typical two-sample summary-data MR setting to the one-sample setting by adapting the technique of Collider-Correction. Simulation studies and applied examples are used to assess how the sex-stratified MR-RAPS estimator performs against other common approaches. RESULTS: The sex-stratified MR-RAPS method is shown to be robust to pleiotropy even in cases where all genetic variants violated the standard Instrument Strength Independent of Direct Effect assumption. In some cases where the strength of the pleiotropic effect additionally varied by sex (and so perfect cancellation was not achieved), over-dispersed MR-RAPS implementations can still consistently estimate the true causal effect. In applied analyses, we investigate the causal effect of waist-hip ratio (WHR), an important marker of central obesity, on a range of downstream traits. While the conventional approaches suggested paradoxical links between WHR and height and body mass index, the sex-stratified approach obtained a more realistic null effect. Nonzero effects were also detected for systolic and diastolic blood pressure as well as high-density and low-density lipoprotein cholesterol. DISCUSSION: We provide a simple but attractive method for weak and pleiotropy robust causal estimation of sexually dimorphic traits on downstream outcomes, by combining several existing approaches in a novel fashion.

Field study of the fire-blight-resistant cisgenic apple line C44.4.146.

Cisgenesis, the genetic modification of a plant with genes from a sexually compatible plant, was used to confer fire blight resistance to the cultivar 'Gala Galaxy' by amendment of the resistance gene FB_MR5, resulting in the line C44.4.146. To verify whether cisgenesis changed other tree-, flower- or fruit-related traits, a 5-year field trial was conducted with trees of C44.4.146 and multiple control genotypes, including members of the 'Gala' sports group. None of the 44 investigated tree-, flower- or fruit-related traits significantly differed between C44.4.146 and at least one of the control genotypes in all observation years. However, fruits of C44.4.146 and its wild-type 'Gala Galaxy' from tissue culture were paler in color than fruits of 'Gala Galaxy' that had not undergone tissue culture. There was no significant and consistently detected difference in the fruit flesh and peel metabolome of C44.4.146 compared with the control genotypes. Finally, the disease resistance of C44.4.146 was confirmed also when the fire blight pathogen was inoculated through the flowers. We conclude that the use of cisgenesis to confer fire blight resistance to 'Gala Galaxy' in C44.4.146 did not have unintended effects, and that the in vitro establishment of 'Gala Galaxy' had a greater effect on C44.4.146 properties than its generation applying cisgenesis.

Perfusion parameter map generation from TOF-MRA in stroke using generative adversarial networks.

PURPOSE: To generate perfusion parameter maps from Time-of-flight magnetic resonance angiography (TOF-MRA) images using artificial intelligence to provide an alternative to traditional perfusion imaging techniques. MATERIALS AND METHODS: This retrospective study included a total of 272 patients with cerebrovascular diseases; 200 with acute stroke (from 2010 to 2018), and 72 with steno-occlusive disease (from 2011 to 2014). For each patient the TOF MRA image and the corresponding Dynamic susceptibility contrast magnetic resonance imaging (DSC-MRI) were retrieved from the datasets. The authors propose an adapted generative adversarial network (GAN) architecture, 3D pix2pix GAN, that generates common perfusion maps (CBF, CBV, MTT, TTP, Tmax) from TOF-MRA images. The performance was evaluated by the structural similarity index measure (SSIM). For a subset of 20 patients from the acute stroke dataset, the Dice coefficient was calculated to measure the overlap between the generated and real hypoperfused lesions with a time-to-maximum (Tmax) > 6 s. RESULTS: The GAN model exhibited high visual overlap and performance for all perfusion maps in both datasets: acute stroke (mean SSIM 0.88-0.92, mean PSNR 28.48-30.89, mean MAE 0.02-0.04 and mean NRMSE 0.14-0.37) and steno-occlusive disease patients (mean SSIM 0.83-0.98, mean PSNR 23.62-38.21, mean MAE 0.01-0.05 and mean NRMSE 0.03-0.15). For the overlap analysis for lesions with Tmax>6 s, the median Dice coefficient was 0.49. CONCLUSION: Our AI model can successfully generate perfusion parameter maps from TOF-MRA images, paving the way for a non-invasive alternative for assessing cerebral hemodynamics in cerebrovascular disease patients. This method could impact the stratification of patients with cerebrovascular diseases. Our results warrant more extensive refinement and validation of the method.

The multidimensional value of natriuretic peptides in heart failure, integrating laboratory and clinical aspects.

Natriuretic peptides (NP) play an essential role in heart failure (HF) regulation, and their measurement has improved diagnostic and prognostic accuracy. Clinical symptoms and objective measurements, such as NP levels, should be included in the HF definition to render it more reliable and consistent among observers, hospitals, and healthcare systems. BNP and NT-proBNP are reasonable surrogates for cardiac disease, and their measurement is critical to early diagnosis and risk stratification of HF patients. NPs should be measured in all patients presenting with dyspnea or other symptoms suggestive of HF to facilitate early diagnosis and risk stratification. Both BNP and NT-proBNP are currently used for guided HF management and display comparable diagnostic and prognostic accuracy. Standardized cutoffs for each NP assay are essential for data comparison. The value of NP testing is recognized at various levels, including patient empowerment and education, analytical and operational issues, clinical HF management, and cost-effectiveness.

Peripheral blood MR1 tetramer-positive mucosal-associated invariant T-cell function is modulated by mammalian target of rapamycin complex 1 in patients with active tuberculosis.

Tuberculosis (TB) is still an urgent global public health problem. Notably, mucosal-associated invariant T (MAIT) cells play an important role in early anti-TB immune response. Targeted control of them may be an effective method to improve vaccine efficacy and TB treatment. However, the biology and signal regulation mechanisms of MAIT cells in TB patients are still poorly understood. Previous studies have been limited by the lack of reagents to specifically identify MAIT cells. In addition, the use of alternative markers may subsume non-MAIT cell into MAIT cell populations. In this study, the human MR1 tetramer which can specifically identify MAIT cells was used to further explore the effect and mechanism of MAIT cells in anti-TB immune response. Our results showed that the tetramer+ MAIT cells in peripheral blood of TB patients were mainly CD8+ or CD4-CD8- cells, and very few were CD4+ cells. After BCG infecting autologous antigen-presenting cells, MAIT cells in patients produced significantly higher levels of cytokines, lysis and proliferation compared with healthy controls. After suppression of mTORC1 by the mTORC1-specific inhibitor rapamycin, the immune response of MAIT cells in patients was significantly reduced. This study demonstrates that peripheral blood tetramer+ MAIT cells from TB patients have significant anti-TB immune effect, which is regulated by mTORC1. This could provide ideas and potential therapeutic targets for the development of novel anti-TB immunotherapy.

Gastroesophageal reflux disease and the risk of respiratory diseases: a Mendelian randomization study.

BACKGROUND: Observational studies have suggested a suspected association between gastroesophageal reflux disease (GERD) and respiratory diseases, but the causality remains equivocal. The goal of this study was to evaluate the causal role of GERD in respiratory diseases by employing Mendelian randomization (MR) studies. METHODS: We conducted Mendelian randomization analysis based on summary data of genome-wide association studies (GWASs) and three MR statistical techniques (inverse variance weighted, weighted median and MR-Egger) were employed to assess the probable causal relationship between GERD and the risk of respiratory diseases. Sensitivity analysis was also carried out to ensure more trustworthy results, which involves examining the heterogeneity, pleiotropy and leave-one-SNP-out method. We also identified 33 relevant genes and explored their distribution in 26 normal tissues. RESULTS: In the analysis, for every unit increase in developing GERD, the odds ratio for developing COPD, bronchitis, pneumonia, lung cancer and pulmonary embolism rose by 72% (ORIVW = 1.72, 95% CI 1.50; 1.99), 19% (ORIVW = 1.19, 95% CI 1.11; 1.28), 16% (ORIVW = 1.16, 95% CI 1.07; 1.26), 0. 3% (ORIVW = 1.003, 95% CI 1.0012; 1.0043) and 33% (ORIVW = 1.33, 95% CI 1.12; 1.58), respectively, in comparison with non-GERD cases. In addition, neither heterogeneity nor pleiotropy was found in the study. This study also found that gene expression was higher in the central nervous system and brain tissue than in other normal tissues. CONCLUSIONS: This study provided evidence that people who developed GERD had a higher risk of developing COPD, bronchitis, pneumonia, lung cancer and pulmonary embolism. Our research suggests physicians to give effective treatments for GERD on respiratory diseases. By exploring the gene expression, our study may also help to reveal the role played by the central nervous system and brain tissue in developing respiratory diseases caused by GERD.

Knowledge-driven deep learning for fast MR imaging: Undersampled MR image reconstruction from supervised to un-supervised learning.

Deep learning (DL) has emerged as a leading approach in accelerating MRI. It employs deep neural networks to extract knowledge from available datasets and then applies the trained networks to reconstruct accurate images from limited measurements. Unlike natural image restoration problems, MRI involves physics-based imaging processes, unique data properties, and diverse imaging tasks. This domain knowledge needs to be integrated with data-driven approaches. Our review will introduce the significant challenges faced by such knowledge-driven DL approaches in the context of fast MRI along with several notable solutions, which include learning neural networks and addressing different imaging application scenarios. The traits and trends of these techniques have also been given which have shifted from supervised learning to semi-supervised learning, and finally, to unsupervised learning methods. In addition, MR vendors' choices of DL reconstruction have been provided along with some discussions on open questions and future directions, which are critical for the reliable imaging systems.

Diffusion-weighted MR spectroscopy of the prostate.

PURPOSE: Prostate tissue has a complex microstructure, mainly composed of epithelial and stromal cells, and of extracellular (acinar-luminal) spaces. Diffusion-weighted MR spectroscopy (DW-MRS) is ideally suited to explore complex microstructure in vivo with metabolites selectively distributed in different subspaces. To date, this technique has been applied to brain and muscle. This study presents the development and pioneering utilization of 1H-DW-MRS in the prostate, accompanied by in vitro studies to support interpretations of in vivo findings. METHODS: Nine healthy volunteers underwent a prostate MR examination (mean age, 56 years; range, 31-66). Metabolic complexation was studied in vitro using solutions with major compounds found in prostatic fluid of the lumen. DW-MRS was performed at 3 T with a non-water-suppressed single-voxel sequence with metabolite-cycling to concurrently measure metabolite and water signals. The water signal was used in postprocessing as a reference in a motion-compensation scheme. The spectra were fitted simultaneously in the spectral and diffusion-weighting dimensions. Apparent diffusion coefficients (ADCs) were derived by fitting signal decays that were assumed to be mono-exponential for metabolites and biexponential for water. RESULTS: DW-MRS of the prostate revealed relatively low ADCs for Cho and Cr compounds, aligning with their intracellular location and higher ADCs for citrate and spermine supporting their luminal origin. In vitro assessments of the ADCs of citrate and spermine demonstrated their complex formation and protein binding. Tissue concentrations of MRS-detectable metabolites were as expected for the voxel location. CONCLUSIONS: This work successfully demonstrates the feasibility of 1H-DW-MRS of the prostate and its potential for providing valuable microstructural information.