Prediction of diagnosis and diastolic filling pressure by AI-enhanced cardiac MRI: a modelling study of hospital data

BACKGROUND

With increasing numbers of patients and novel drugs for distinct causes of systolic and diastolic heart failure, automated assessment of cardiac function is important. We aimed to provide a non-invasive method to predict diagnosis of patients undergoing cardiac MRI (cMRI) and to obtain left ventricular end-diastolic pressure (LVEDP).

METHODS

For this modelling study, patients who had undergone cardiac catheterisation at University Hospital Heidelberg (Heidelberg, Germany) between July 15, 2004 and March 16, 2023, were identified, as were individual left ventricular pressure measurements. We used existing patient data from routine cardiac diagnostics. From this initial group, we extracted patients who had been diagnosed with ischaemic cardiomyopathy, dilated cardiomyopathy, hypertrophic cardiomyopathy, or amyloidosis, as well as control individuals with no structural phenotype. Data were pseudonymised and only processed within the university hospital's AI infrastructure. We used the data to build different models to predict either demographic (ie, AI-age and AI-sex), diagnostic (ie, AI-coronary artery disease and AI-cardiomyopathy [AI-CMP]), or functional parameters (ie, AI-LVEDP). We randomly divided our datasets via computer into training, validation, and test datasets. AI-CMP was not compared with other models, but was validated in a prospective setting. Benchmarking was also done.

FINDINGS

66 936 patients who had undergone cardiac catheterisation at University Hospital Heidelberg were identified, with more than 183 772 individual left ventricular pressure measurements. We extracted 4390 patients from this initial group, of whom 1131 (25·8%) had been diagnosed with ischaemic cardiomyopathy, 1064 (24·2%) had been diagnosed with dilated cardiomyopathy, 816 (18·6%) had been diagnosed with hypertrophic cardiomyopathy, 202 (4·6%) had been diagnosed with amyloidosis, and 1177 (26·7%) were control individuals with no structural phenotype. The core cohort only included patients with cardiac catherisation and cMRI within 30 days, and emergency cases were excluded. AI-sex was able to predict patient sex with areas under the receiver operating characteristic curves (AUCs) of 0·78 (95% CI 0·77-0·78) and AI-age was able to predict patient age with a mean absolute error of 7·86 years (7·77-7·95), with a Pearson correlation of 0·57 (95% CI 0·56-0·57). The AUCs for the classification tasks ranged between 0·82 (95% CI 0·79-0·84) for ischaemic cardiomyopathy and 0·92 (0·91-0·94) for hypertrophic cardiomyopathy.

INTERPRETATION

Our AI models could be easily integrated into clinical practice and provide added value to the information content of cMRI, allowing for disease classification and prediction of diastolic function.

FUNDING

Informatics for Life initiative of the Klaus-Tschira Foundation, German Center for Cardiovascular Research, eCardiology section of the German Cardiac Society, and AI Health Innovation Cluster Heidelberg.

Approaching Maximal Precision of Hong-Ou-Mandel Interferometry with Nonperfect Visibility

In quantum mechanics, the precision achieved in parameter estimation using a quantum state as a probe is determined by the measurement strategy employed. The quantum limit of precision is bounded by a value set by the state and its dynamics. Theoretical results have revealed that in interference measurements with two possible outcomes, this limit can be reached under ideal conditions of perfect visibility and zero losses. However, in practice, these conditions cannot be achieved, so precision never reaches the quantum limit. But how do experimental setups approach precision limits under realistic circumstances? In this Letter, we provide a model for precision limits in two-photon Hong-Ou-Mandel interferometry using coincidence statistics for nonperfect visibility and temporally unresolved measurements. We show that the scaling of precision with visibility depends on the effective area in time-frequency phase space occupied by the state used as a probe, and we find that an optimal scaling exists. We demonstrate our results experimentally for different states in a setup where the visibility can be controlled and reaches up to 99.5%. In the optimal scenario, a ratio of 0.97 is observed between the experimental precision and the quantum limit, establishing a new benchmark in the field.

Artificial Intelligence-Derived Risk Prediction: A Novel Risk Calculator Using Office and Ambulatory Blood Pressure

BACKGROUND

Quantification of total cardiovascular risk is essential for individualizing hypertension treatment. This study aimed to develop and validate a novel, machine-learning-derived model to predict cardiovascular mortality risk using office blood pressure (OBP) and ambulatory blood pressure (ABP).

METHODS

The performance of the novel risk score was compared with existing risk scores, and the possibility of predicting ABP phenotypes utilizing clinical variables was assessed. Using data from 59 124 patients enrolled in the Spanish ABP Monitoring registry, machine-learning approaches (logistic regression, gradient-boosted decision trees, and deep neural networks) and stepwise forward feature selection were used.

RESULTS

For the prediction of cardiovascular mortality, deep neural networks yielded the highest clinical performance. The novel mortality prediction models using OBP and ABP outperformed other risk scores. The area under the curve achieved by the novel approach, already when using OBP variables, was significantly higher when compared with the area under the curve of the Framingham risk score, Systemic Coronary Risk Estimation 2, and Atherosclerotic Cardiovascular Disease score. However, the prediction of cardiovascular mortality with ABP instead of OBP data significantly increased the area under the curve (0.870 versus 0.865; P=3.61×10-28), accuracy, and specificity, respectively. The prediction of ABP phenotypes (ie, white-coat, ambulatory, and masked hypertension) using clinical characteristics was limited.

CONCLUSIONS

The receiver operating characteristic curves for cardiovascular mortality using ABP and OBP with deep neural network models outperformed all other risk metrics, indicating the potential for improving current risk scores by applying state-of-the-art machine learning approaches. The prediction of cardiovascular mortality using ABP data led to a significant increase in area under the curve and performance metrics.

SingmiR: a single-cell miRNA alignment and analysis tool

Single-cell RNA sequencing (RNA-seq) has revolutionized our understanding of cell biology, developmental and pathophysiological molecular processes, paving the way toward novel diagnostic and therapeutic approaches. However, most of the gene regulatory processes on the single-cell level are still unknown, including post-transcriptional control conferred by microRNAs (miRNAs). Like the established single-cell gene expression analysis, advanced computational expertise is required to comprehensively process newly emerging single-cell miRNA-seq datasets. A web server providing a workflow tailored for single-cell miRNA-seq data with a self-explanatory interface is currently not available. Here, we present SingmiR, enabling the rapid (pre-)processing and quantification of human miRNAs from noncoding single-cell samples. It performs read trimming for different library preparation protocols, generates automated quality control reports and provides feature-normalized count files. Numerous standard and advanced analyses such as dimension reduction, clustered feature heatmaps, sample correlation heatmaps and differential expression statistics are implemented. We aim to speed up the prototyping pipeline for biologists developing single-cell miRNA-seq protocols on small to medium-sized datasets. SingmiR is freely available to all users without the need for a login at https://www.ccb.uni-saarland.de/singmir.

Experimental capture of miRNA targetomes: disease-specific 3'UTR library-based miRNA targetomics for Parkinson's disease

The identification of targetomes remains a challenge given the pleiotropic effect of miRNAs, the limited effects of miRNAs on individual targets, and the sheer number of estimated miRNA-target gene interactions (MTIs), which is around 44,571,700. Currently, targetome identification for single miRNAs relies on computational evidence and functional studies covering smaller numbers of targets. To ensure that the targetome analysis could be experimentally verified by functional assays, we employed a systematic approach and explored the targetomes of four miRNAs (miR-129-5p, miR-129-1-3p, miR-133b, and miR-873-5p) by analyzing 410 predicted target genes, both of which were previously associated with Parkinson's disease (PD). After performing 13,536 transfections, we validated 442 of the 705 putative MTIs (62,7%) through dual luciferase reporter assays. These analyses increased the number of validated MTIs by at least 2.1-fold for miR-133b and by a maximum of 24.3-fold for miR-873-5p. Our study contributes to the experimental capture of miRNA targetomes by addressing i) the ratio of experimentally verified MTIs to predicted MTIs, ii) the sizes of disease-related miRNA targetomes, and iii) the density of MTI networks. A web service to support the analyses on the MTI level is available online ( https://ccb-web.cs.uni-saarland.de/utr-seremato ), and all the data have been added to the miRATBase database ( https://ccb-web.cs.uni-saarland.de/miratbase ).

Impact of adjuvant radiotherapy and chemotherapy on thymoma

PURPOSE

Thymoma is a rare tumour. The most common treatment for thymoma is surgical resection, while the use of radiotherapy and chemotherapy remains controversial.

PATIENTS AND METHODS

We conducted a monocentric observational study of 31 patients diagnosed with thymoma from June 2004 to July 2020 at cancer centre in Strasbourg, France. We analysed the outcomes of the patients.

RESULTS

The 2- and 5- year locoregional relapse-free survival rates were 96.3% (95% confidence interval [CI]: 76.5-99.5%) and 68.0% (95% CI: 43.8-83.5%), respectively. Radiotherapy and chemotherapy significantly improved local tumour control (P=0.0008 and 0.04, respectively), while a larger initial tumour size significantly worsened local control rates (P=0.04). The 5- and 10-year overall survival rates were 87.1% (95% CI: 69.2-95%) and 81.7% (95% CI: 60.3-92.2%), respectively. The median overall survival was not reached, and no favourable factor was retrieved. For relapsed patients, the median overall survival after relapse was 115 months.

CONCLUSION

Despite the inherent limitations of retrospective studies with a limited patient sample size, we demonstrated that chemotherapy and radiotherapy in addition to surgery were effective in achieving local control and contributed to improving patient outcomes in thymoma. Notably, an aggressive treatment strategy at the time of relapse resulted in favourable outcomes for retreated patients.

Time series of chicken stool metagenomics and egg metabolomics in changing production systems: preliminary insights from a proof-of-concept

BACKGROUND

Different production systems of livestock animals influence various factors, including the gut microbiota.

METHODS

We investigated whether changing the conditions from barns to free-range chicken farming impacts the microbiome over the course of three weeks. We compared the stool microbiota of chicken from industrial barns after introducing them either in community or separately to a free-range environment.

RESULTS

Over the six time points, 12 taxa-mostly lactobacilli-changed significantly. As expected, the former barn chicken cohort carries more resistances to common antibiotics. These, however, remained positive over the observed period. At the end of the study, we collected eggs and compared metabolomic profiles of the egg white and yolk to profiles of eggs from commercial suppliers. Here, we observed significant differences between commercial and fresh collected eggs as well as differences between the former barn chicken and free-range chicken.

CONCLUSION

Our data indicate that the gut microbiota can undergo alterations over time in response to changes in production systems. These changes subsequently exert an influence on the metabolites found in the eggs. The preliminary results of our proof-of-concept study motivate larger scale observations with more individual chicken and longer observation periods.

SRF transcriptionally regulates the oligodendrocyte cytoskeleton during CNS myelination

Myelination of neuronal axons is essential for nervous system development. Myelination requires dramatic cytoskeletal dynamics in oligodendrocytes, but how actin is regulated during myelination is poorly understood. We recently identified serum response factor (SRF)-a transcription factor known to regulate expression of actin and actin regulators in other cell types-as a critical driver of myelination in the aged brain. Yet, a major gap remains in understanding the mechanistic role of SRF in oligodendrocyte lineage cells. Here, we show that SRF is required cell autonomously in oligodendrocytes for myelination during development. Combining ChIP-seq with RNA-seq identifies SRF-target genes in oligodendrocyte precursor cells and oligodendrocytes that include actin and other key cytoskeletal genes. Accordingly, SRF knockout oligodendrocytes exhibit dramatically reduced actin filament levels early in differentiation, consistent with its role in actin-dependent myelin sheath initiation. Surprisingly, oligodendrocyte-restricted loss of SRF results in upregulation of gene signatures associated with aging and neurodegenerative diseases. Together, our findings identify SRF as a transcriptional regulator that controls the expression of cytoskeletal genes required in oligodendrocytes for myelination. This study identifies an essential pathway regulating oligodendrocyte biology with high relevance to brain development, aging, and disease.

The miRNA-target interactions: An underestimated intricacy

MicroRNAs (miRNAs) play indispensable roles in posttranscriptional gene regulation. Their cellular regulatory impact is determined not solely by their sheer number, which likely amounts to >2000 individual miRNAs in human, than by the regulatory effectiveness of single miRNAs. Although, one begins to develop an understanding of the complex mechanisms underlying miRNA-target interactions (MTIs), the overall knowledge of MTI functionality is still rather patchy. In this critical review, we summarize key features of mammalian MTIs. We especially highlight latest insights on (i) the dynamic make-up of miRNA binding sites including non-canonical binding sites, (ii) the cooperativity between miRNA binding sites, (iii) the adaptivity of MTIs through sequence modifications, (iv) the bearing of intra-cellular miRNA localization changes and (v) the role of cell type and cell status specific miRNA interaction partners. The MTI biology is discussed against the background of state-of-the-art approaches with particular emphasis on experimental strategies for evaluating miRNA functionality.

ZEBRA: a hierarchically integrated gene expression atlas of the murine and human brain at single-cell resolution

The molecular causes and mechanisms of neurodegenerative diseases remain poorly understood. A growing number of single-cell studies have implicated various neural, glial, and immune cell subtypes to affect the mammalian central nervous system in many age-related disorders. Integrating this body of transcriptomic evidence into a comprehensive and reproducible framework poses several computational challenges. Here, we introduce ZEBRA, a large single-cell and single-nucleus RNA-seq database. ZEBRA integrates and normalizes gene expression and metadata from 33 studies, encompassing 4.2 million human and mouse brain cells sampled from 39 brain regions. It incorporates samples from patients with neurodegenerative diseases like Alzheimer's disease, Parkinson's disease, and Multiple sclerosis, as well as samples from relevant mouse models. We employed scVI, a deep probabilistic auto-encoder model, to integrate the samples and curated both cell and sample metadata for downstream analysis. ZEBRA allows for cell-type and disease-specific markers to be explored and compared between sample conditions and brain regions, a cell composition analysis, and gene-wise feature mappings. Our comprehensive molecular database facilitates the generation of data-driven hypotheses, enhancing our understanding of mammalian brain function during aging and disease. The data sets, along with an interactive database are freely available at https://www.ccb.uni-saarland.de/zebra.

ABC-HuMi: the Atlas of Biosynthetic Gene Clusters in the Human Microbiome

The human microbiome has emerged as a rich source of diverse and bioactive natural products, harboring immense potential for therapeutic applications. To facilitate systematic exploration and analysis of its biosynthetic landscape, we present ABC-HuMi: the Atlas of Biosynthetic Gene Clusters (BGCs) in the Human Microbiome. ABC-HuMi integrates data from major human microbiome sequence databases and provides an expansive repository of BGCs compared to the limited coverage offered by existing resources. Employing state-of-the-art BGC prediction and analysis tools, our database ensures accurate annotation and enhanced prediction capabilities. ABC-HuMi empowers researchers with advanced browsing, filtering, and search functionality, enabling efficient exploration of the resource. At present, ABC-HuMi boasts a catalog of 19 218 representative BGCs derived from the human gut, oral, skin, respiratory and urogenital systems. By capturing the intricate biosynthetic potential across diverse human body sites, our database fosters profound insights into the molecular repertoire encoded within the human microbiome and offers a comprehensive resource for the discovery and characterization of novel bioactive compounds. The database is freely accessible at https://www.ccb.uni-saarland.de/abc_humi/.

Characterizing expression changes in noncoding RNAs during aging and heterochronic parabiosis across mouse tissues

Molecular mechanisms of organismal and cell aging remain incompletely understood. We, therefore, generated a body-wide map of noncoding RNA (ncRNA) expression in aging (16 organs at ten timepoints from 1 to 27 months) and rejuvenated mice. We found molecular aging trajectories are largely tissue-specific except for eight broadly deregulated microRNAs (miRNAs). Their individual abundance mirrors their presence in circulating plasma and extracellular vesicles (EVs) whereas tissue-specific ncRNAs were less present. For miR-29c-3p, we observe the largest correlation with aging in solid organs, plasma and EVs. In mice rejuvenated by heterochronic parabiosis, miR-29c-3p was the most prominent miRNA restored to similar levels found in young liver. miR-29c-3p targets the extracellular matrix and secretion pathways, known to be implicated in aging. We provide a map of organism-wide expression of ncRNAs with aging and rejuvenation and identify a set of broadly deregulated miRNAs, which may function as systemic regulators of aging via plasma and EVs.

Skin treatment with non-thermal plasma modulates the immune system through miR-223-3p and its target genes

Non-thermal plasma, a partially ionized gas, holds significant potential for clinical applications, including wound-healing support, oral therapies, and anti-tumour treatments. While its applications showed promising outcomes, the underlying molecular mechanisms remain incompletely understood. We thus apply non-thermal plasma to mouse auricular skin and conducted non-coding RNA sequencing, as well as single-cell blood sequencing. In a time-series analysis (five timepoints spanning 2 hours), we compare the expression of microRNAs in the plasma-treated left ears to the unexposed right ears of the same mice as well as to the ears of unexposed control mice. Our findings indicate specific effects in the treated ears for a set of five miRNAs: mmu-miR-144-5p, mmu-miR-144-3p, mmu-miR-142a-5p, mmu-miR-223-3p, and mmu-miR-451a. Interestingly, mmu-miR-223-3p also exhibits an increase over time in the right non-treated ear of the exposed mice, suggesting systemic effects. Notably, this miRNA, along with mmu-miR-142a-5p and mmu-miR-144-3p, regulates genes and pathways associated with wound healing and tissue regeneration (namely ErbB, FoxO, Hippo, and PI3K-Akt signalling). This co-regulation is particularly remarkable considering the significant seed dissimilarities among the miRNAs. Finally, single-cell sequencing of PBMCs reveals the downregulation of 12 from 15 target genes in B-cells, Cd4+ and Cd8+ T-cells. Collectively, our data provide evidence for a systemic effect of non-thermal plasma.

Feasibility Study of Using Augmented Mirrors for Alignment Task during Orthopaedic Procedures in Mixed Reality

Accurate depth estimation poses a significant challenge in egocentric Augmented Reality (AR), particularly for precision-dependent tasks in the medical field, such as needle or tool insertions during percutaneous procedures. Augmented Mirrors (AMs) provide a unique solution to this problem by offering additional non-egocentric viewpoints that enhance spatial understanding of an AR scene. Despite the perceptual advantages of using AMs, their practical utility has yet to be thoroughly tested. In this work, we present results from a pilot study involving five participants tasked with simulating epidural injection procedures in an AR environment, both with and without the aid of an AM. Our findings indicate that using AM contributes to reducing mental effort while improving alignment accuracy. These results highlight the potential of AM as a powerful tool for AR-enabled medical procedures, setting the stage for future exploration involving medical professionals.

Zfp362 potentiates murine colonic inflammation by constraining Treg cell function rather than promoting Th17 cell differentiation

Mucosal barrier integrity and pathogen clearance is a complex process influenced by both Th17 and Treg cells. Previously, we had described the DNA methylation profile of Th17 cells and identified Zinc finger protein (Zfp)362 to be uniquely demethylated. Here, we generated Zfp362-/- mice to unravel the role of Zfp362 for Th17 cell biology. Zfp362-/- mice appeared clinically normal, showed no phenotypic alterations in the T-cell compartment, and upon colonization with segmented filamentous bacteria, no effect of Zfp362 deficiency on Th17 cell differentiation was observed. By contrast, Zfp362 deletion resulted in increased frequencies of colonic Foxp3+ Treg cells and IL-10+ and RORγt+ Treg cell subsets in mesenteric lymph nodes. Adoptive transfer of naïve CD4+ T cells from Zfp362-/- mice into Rag2-/- mice resulted in a significantly lower weight loss when compared with controls receiving cells from Zfp362+/+ littermates. However, this attenuated weight loss did not correlate with alterations of Th17 cells but instead was associated with an increase of effector Treg cells in mesenteric lymph nodes. Together, these results suggest that Zfp362 plays an important role in promoting colonic inflammation; however, this function is derived from constraining the effector function of Treg cells rather than directly promoting Th17 cell differentiation.

Long-Term Urinary Toxicity Follow-Up of Combined External Beam Radiation and Cs-131 LDR Brachytherapy Boost for Prostate Cancer

PURPOSE/OBJECTIVE(S)

To evaluate and update our institutional data on chronic patient-reported urinary symptoms in patients with prostate cancer treated with combined external beam radiation therapy (EBRT) and Cesium-131 (Cs-131) LDR brachytherapy boost.

MATERIALS/METHODS

Patients treated from September 2006-July 2022 and with at least 6 months of follow-up were analyzed. Patients filled out the Expanded Prostate Cancer Index Composite (EPIC) questionnaire pre-treatment and at each scheduled follow-up. Mean EPIC urinary scores were calculated for urinary summary, urinary function, urinary bother, urinary incontinence, and urinary irritative/obstructive domains. Changes of 7-points or more in mean domain scores were deemed clinically significant. The prevalence of urinary bleeding was calculated and bleeding occurring more than "about once a week" ("more than once a week", "about once a day", and "more than once a day") was deemed clinically significant. Outcomes were analyzed at each follow-up timepoint using paired t-test.

RESULTS

A total of 341 patients with prostate cancer were included in the analysis of which 183 were intermediate-risk and 158 high-risk. 174 patients were treated with tri-modality therapy, and SpaceOAR was used in 108 patients. Long-term statistically significant decreases in mean EPIC QOL scores were seen in urinary summary, urinary function, urinary bother, urinary incontinence, and urinary irritative/obstructive domains at 6 months, with clinically and statistically significant decreases in urinary function and urinary incontinence at 6 months (86±17.4, 83.4±22.2 respectively) and up to 18 months post-treatment (84.8±17.4, 83.6±20.7 respectively) compared with pre-treatment scores (93.1±10.7, 90.8±14.8 respectively), with both domains returning to clinical baseline at 24 months. Urinary irritative/obstructive mean scores clinically and significantly decreased at 9 months (77±17.4) compared to pre-treatment (84.7±13.5), returning to clinical baseline at 12 months. The prevalence of clinically significant urinary bleeding at 6, 12, 24, 36, 48, and 60 months was 1.3%, 2.6%, 3.7%, 0.7%, 0.9%, and 2.3% respectively. At the median follow-up of 42 months (IQR 54, 18-72), mean EPIC scores were clinically improved (≥7-point increase) from pre-treatment baseline in 15-30% of patients across the analyzed urinary domains.

CONCLUSION

Long-term patient-reported clinically significant decreases in urinary function and urinary incontinence mean EPIC scores occurred up to 18 months following combined external beam radiation and Cs-131 prostate brachytherapy and returned to baseline at 24 months, while clinically significant decrease in urinary irritability/obstructive mean scores occurred at 9 months and returned to baseline at 12 months. At 42 months follow-up, mean urinary domain scores improved from pre-treatment baseline in 15-30% of patients.

Atlas of the aging mouse brain reveals white matter as vulnerable foci

Aging is the key risk factor for cognitive decline, yet the molecular changes underlying brain aging remain poorly understood. Here, we conducted spatiotemporal RNA sequencing of the mouse brain, profiling 1,076 samples from 15 regions across 7 ages and 2 rejuvenation interventions. Our analysis identified a brain-wide gene signature of aging in glial cells, which exhibited spatially defined changes in magnitude. By integrating spatial and single-nucleus transcriptomics, we found that glial aging was particularly accelerated in white matter compared with cortical regions, whereas specialized neuronal populations showed region-specific expression changes. Rejuvenation interventions, including young plasma injection and dietary restriction, exhibited distinct effects on gene expression in specific brain regions. Furthermore, we discovered differential gene expression patterns associated with three human neurodegenerative diseases, highlighting the importance of regional aging as a potential modulator of disease. Our findings identify molecular foci of brain aging, providing a foundation to target age-related cognitive decline.

Cas9-mediated knockout of Ndrg2 enhances the regenerative potential of dendritic cells for wound healing

Chronic wounds impose a significant healthcare burden to a broad patient population. Cell-based therapies, while having shown benefits for the treatment of chronic wounds, have not yet achieved widespread adoption into clinical practice. We developed a CRISPR/Cas9 approach to precisely edit murine dendritic cells to enhance their therapeutic potential for healing chronic wounds. Using single-cell RNA sequencing of tolerogenic dendritic cells, we identified N-myc downregulated gene 2 (Ndrg2), which marks a specific population of dendritic cell progenitors, as a promising target for CRISPR knockout. Ndrg2-knockout alters the transcriptomic profile of dendritic cells and preserves an immature cell state with a strong pro-angiogenic and regenerative capacity. We then incorporated our CRISPR-based cell engineering within a therapeutic hydrogel for in vivo cell delivery and developed an effective translational approach for dendritic cell-based immunotherapy that accelerated healing of full-thickness wounds in both non-diabetic and diabetic mouse models. These findings could open the door to future clinical trials using safe gene editing in dendritic cells for treating various types of chronic wounds.

miEAA 2023: updates, new functional microRNA sets and improved enrichment visualizations

MicroRNAs (miRNAs) are small non-coding RNAs that play a critical role in regulating diverse biological processes. Extracting functional insights from a list of miRNAs is challenging, as each miRNA can potentially interact with hundreds of genes. To address this challenge, we developed miEAA, a flexible and comprehensive miRNA enrichment analysis tool based on direct and indirect miRNA annotation. The latest release of miEAA includes a data warehouse of 19 miRNA repositories, covering 10 different organisms and 139 399 functional categories. We have added information on the cellular context of miRNAs, isomiRs, and high-confidence miRNAs to improve the accuracy of the results. We have also improved the representation of aggregated results, including interactive Upset plots to aid users in understanding the interaction among enriched terms or categories. Finally, we demonstrate the functionality of miEAA in the context of ageing and highlight the importance of carefully considering the miRNA input list. MiEAA is free to use and publicly available at https://www.ccb.uni-saarland.de/mieaa/.

Occurrence, resistance patterns and management of carbapenemase-producing bacteria in war-wounded refugees from Ukraine

We analysed consecutive clinical cases of infections due to carbapenemase-producing Gram-negative bacteria detected in war-wounded patients from Ukraine who were treated at one University medical centre in southwest Germany between June and December 2022. Isolates of multiresistant Gram-negative bacteria were subjected to a thorough microbiological characterisation and whole-genome sequencing. We identified five war-wounded Ukrainian patients who developed infections with NDM-1-positive Klebsiella pneumoniae. Two isolates also carried OXA-48 carbapenemases. The bacteria were resistant to novel antibiotics such as ceftazidime/avibactam and cefiderocol. Employed treatment strategies included combinations of ceftazidime/avibactam + aztreonam, colistin, or tigecycline. Whole-genome sequencing suggested transmission during primary care in Ukraine. We conclude that there is an urgent need for thorough surveillance of multiresistant pathogens in patients from war zones.

The Effect of a Planetary Health Diet on the Human Gut Microbiome: A Descriptive Analysis

In 2019, researchers from the EAT-Lancet Commission developed the 'Planetary Health (PH) diet'. Specifically, they provided recommendations pertaining to healthy diets derived from sustainable food systems. Thus far, it has not been analysed how such a diet affects the human intestinal microbiome, which is important for health and disease development. Here, we present longitudinal genome-wide metagenomic sequencing and mass spectrometry data on the gut microbiome of healthy volunteers adhering to the PH diet, as opposed to vegetarian or vegan (VV) and omnivorous (OV) diets. We obtained basic epidemiological information from 41 healthy volunteers and collected stool samples at inclusion and after 2, 4, and 12 weeks. Individuals opting to follow the PH diet received detailed instructions and recipes, whereas individuals in the control groups followed their habitual dietary pattern. Whole-genome DNA was extracted from stool specimens and subjected to shotgun metagenomic sequencing (~3 GB per patient). Conventional bacterial stool cultures were performed in parallel and bacterial species were identified with matrix-assisted laser desorption/ionization time-of-flight (MALDI-TOF) mass spectrometry. We analysed samples from 16 PH, 16 OV, and 9 VV diet patterns. The α-diversity remained relatively stable for all dietary groups. In the PH group, we observed a constant increase from 3.79% at inclusion to 4.9% after 12 weeks in relative abundance of Bifidobacterium adolescentis. Differential PH abundance analysis highlighted a non-significant increase in possible probiotics such as Paraprevotella xylaniphila and Bacteroides clarus. The highest abundance of these bacteria was observed in the VV group. Dietary modifications are associated with rapid alterations to the human gut microbiome, and the PH diet led to a slight increase in probiotic-associated bacteria at ≥4 weeks. Additional research is required to confirm these findings.

miR-34a-5p as molecular hub of pathomechanisms in Huntington's disease

BACKGROUND

Although a pivotal role of microRNA (miRNA, miR) in the pathogenesis of Huntington's disease (HD) is increasingly recognized, the molecular functions of miRNAs in the pathomechanisms of HD await further elucidation. One of the miRNAs that have been associated with HD is miR-34a-5p, which was deregulated in the mouse R6/2 model and in human HD brain tissues.

METHODS

The aim of our study was to demonstrate interactions between miR-34a-5p and HD associated genes. By computational means we predicted 12 801 potential target genes of miR-34a-5p. An in-silico pathway analysis revealed 22 potential miR-34a-5p target genes in the KEGG (Kyoto Encyclopedia of Genes and Genomes) pathway "Huntington's disease".

RESULTS

Using our high-throughput miRNA interaction reporter assay (HiTmIR) we identified NDUFA9, TAF4B, NRF1, POLR2J2, DNALI1, HIP1, TGM2 and POLR2G as direct miR-34a-5p target genes. Direct binding of miR-34a-5p to target sites in the 3'UTRs of TAF4B, NDUFA9, HIP1 and NRF1 was verified by a mutagenesis HiTmIR assay and by determining endogenous protein levels for HIP1 and NDUFA9. STRING (Search Tool for the Retrieval of Interacting Genes/Proteins) analysis identified protein-protein interaction networks associated with HD like "Glutamine Receptor Signaling Pathway" and "Calcium Ion Transmembrane Import Into Cytosol".

CONCLUSION

Our study demonstrates multiple interactions between miR-34a-5p and HD associated target genes and thereby lays the ground for future therapeutic interventions using this miRNA.

Artificial-intelligence-based decision support tools for the differential diagnosis of colitis

BACKGROUND

Whereas Artificial Intelligence (AI) based tools have recently been introduced in the field of gastroenterology, application in inflammatory bowel disease (IBD) is in its infancies. We established AI-based algorithms to distinguish IBD from infectious and ischemic colitis using endoscopic images and clinical data.

METHODS

First, we trained and tested a Convolutional Neural Network (CNN) using 1796 real-world images from 494 patients, presenting with three diseases (IBD [n = 212], ischemic colitis [n = 157], and infectious colitis [n = 125]). Moreover, we evaluated a Gradient Boosted Decision Trees (GBDT) algorithm using five clinical parameters as well as a hybrid approach (CNN + GBDT). Patients and images were randomly split into two completely independent datasets. The proposed approaches were benchmarked against each other and three expert endoscopists on the test set.

RESULTS

For the image-based CNN, the GBDT algorithm and the hybrid approach global accuracies were .709, .792, and .766, respectively. Positive predictive values were .602, .702, and .657. Global areas under the receiver operating characteristics (ROC) and precision recall (PR) curves were .727/.585, .888/.823, and .838/.733, respectively. Global accuracy did not differ between CNN and endoscopists (.721), but the clinical parameter-based GBDT algorithm outperformed CNN and expert image classification.

CONCLUSIONS

Decision support systems exclusively based on endoscopic image analysis for the differential diagnosis of colitis, representing a complex clinical challenge, seem not yet to be ready for primetime and more diverse image datasets may be necessary to improve performance in future development. The clinical value of the proposed clinical parameters algorithm should be evaluated in prospective cohorts.

Changes in the characteristics of patients treated for brain metastases with repeat stereotactic radiotherapy (SRT): a retrospective study of 184 patients

PURPOSE

Brain metastases (BMs) are the leading cause of intracranial malignant neoplasms in adults. WHO, Karnofsky performance status (KPS), age, number of BMs, extracerebral progression (ECP), recursive partitioning analysis (RPA), diagnosis-specific graded prognostic assessment (Ds-GPA) are validated prognostic tools to help clinicians decide on treatment. No consensus exists for repeat stereotactic radiotherapy (SRT) for BMs. The aim of this study was to review the changes in patient characteristics treated with repeated SRTs.

METHODS AND MATERIALS

The data of patients treated between 2010 and 2020 with at least two courses of SRT without previous whole brain radiotherapy (WBRT) were reviewed. Age, WHO, KPS, ECP, type of systemic treatment, number of BMs were recorded. RPA, Ds-GPA and brain metastasis velocity (BMV) were calculated.

RESULTS

184 patients were treated for 915 BMs and received two to six SRTs for local or distant brain recurrence. The median number of BMs treated per SRT was 1 (range: 1-6), for a median of 4 BMs treated during all sessions (range: 2-19). WHO, Ds-GPA and RPA were stable between each session of SRT, whereas KPS was significantly better in SRT1 than in the following SRT. The number of BMs was not significantly different between each SRT, but there was a tendency for more BM at SRT1 (p = 0.06). At SRT1, patients had largest BM and undergo more surgery than during the following SRT (p < 0.001). 6.5%, 37.5% and 56% of patients were classified as high, intermediate, and low BMV, respectively, at the last SRT session. There was almost perfect concordance between the BMV-grade calculated at the last SRT session and at SRT2 (r = 0.89; p < 0.001).

CONCLUSION

Repeated SRT doesn't lead to a marked alteration in the general condition, KPS was maintained at over 70% for more than 95% of patients during all SRTs. Long survival can be expected, especially in low-grade BMV patients. WBRT shouldn't be aborted, especially for patients developing more than twelve BMs annually.