Emergence of power law distributions in protein-protein interaction networks through study bias.

Degree distributions in protein-protein interaction (PPI) networks are believed to follow a power law (PL). However, technical and study biases affect the experimental procedures for detecting PPIs. For instance, cancer-associated proteins have received disproportional attention.

MeTEor: an R Shiny app for exploring longitudinal metabolomics data.

Motivation: The availability of longitudinal omics data is increasing in metabolomics research. Viewing metabolomics data over time provides detailed insight into biological processes and fosters understanding of how systems react over time. However, the analysis of longitudinal metabolomics data poses various challenges, both in terms of statistical evaluation and visualization.

Meta-analysis of proteomics data from osteoblasts, bone, and blood: Insights into druggable targets, active factors, and potential biomarkers for bone biomaterial design.

Non-healing bone defects are a pressing public health concern accounting for one main cause for decreased life expectancy and quality. An aging population accompanied with increasing incidence of comorbidities, foreshadows a worsening of this socio-economic problem. Conventional treatments for non-healing bone defects prove ineffective for 5%-10% of fractures.

AI in microbiome-related healthcare.

Artificial intelligence (AI) has the potential to transform clinical practice and healthcare. Following impressive advancements in fields such as computer vision and medical imaging, AI is poised to drive changes in microbiome-based healthcare while facing challenges specific to the field. This review describes the state-of-the-art use of AI in microbiome-related healthcare.

Desflurane Versus Sevoflurane and Postoperative Cardiac Biomarkers in Older Adults Undergoing Low- to Moderate-Risk Noncardiac Surgery-Secondary Analysis of a Prospective, Observer-Blinded, Randomized Clinical Trial.

: Previous preclinical studies have shown that desflurane might have the most significant cardioprotective effect of all volatile anesthetics. However, data regarding the cardioprotective effects of desflurane versus sevoflurane are lacking. Therefore, we evaluated the effect of the maintenance of anesthesia using desflurane versus sevoflurane on the postoperative maximum concentrations of cardiac biomarkers in older adults undergoing low- to moderate-risk noncardiac surgery.

Less Pain, but no changes in maximal inclination angles during an overhead reach task following local anesthetic in patients with ongoing shoulder pain.

This multicenter observational study aimed to assess how pain reduction, induced by local anesthesia, affects the relative angular contributions of the shoulder girdle and trunk to the maximal angular performance during a semi-constrained overhead reach task in patients with ongoing shoulder pain. Twenty-nine individuals (age 59.0 SD 12.

Network medicine-based epistasis detection in complex diseases: ready for quantum computing.

Most heritable diseases are polygenic. To comprehend the underlying genetic architecture, it is crucial to discover the clinically relevant epistatic interactions (EIs) between genomic single nucleotide polymorphisms (SNPs) (1-3). Existing statistical computational methods for EI detection are mostly limited to pairs of SNPs due to the combinatorial explosion of higher-order EIs.

Guiding questions to avoid data leakage in biological machine learning applications.

Machine learning methods for extracting patterns from high-dimensional data are very important in the biological sciences. However, in certain cases, real-world applications cannot confirm the reported prediction performance. One of the main reasons for this is data leakage, which can be seen as the illicit sharing of information between the training data and the test data, resulting in performance estimates that are far better than the performance observed in the intended application scenario.

Desflurane versus sevoflurane anesthesia and postoperative recovery in older adults undergoing minor- to moderate-risk noncardiac surgery - A prospective, randomized, observer-blinded, clinical trial.

Study Objective: The effect of volatile anesthetics on postoperative recovery in older adults is still not entirely clear. Thus, we evaluated the effect of desflurane versus sevoflurane anesthesia on speed of postoperative recovery in older adults eligible for same-day discharge. We further evaluated the incidence of postoperative nausea and vomiting (PONV), bispectral index (BIS) values, and S100B concentrations.

Mitochondrial perturbation in the intestine causes microbiota-dependent injury and gene signatures discriminative of inflammatory disease.

Mitochondrial dysfunction is associated with inflammatory bowel diseases (IBDs). To understand how microbial-metabolic circuits contribute to intestinal injury, we disrupt mitochondrial function in the epithelium by deleting the mitochondrial chaperone, heat shock protein 60 (Hsp60). This metabolic perturbation causes self-resolving tissue injury.

Single-cell transcriptome analysis reveals secretin as a hallmark of human enteroendocrine cell maturation.

The traditional nomenclature of enteroendocrine cells (EECs), established in 1977, applied the "one cell - one hormone" dogma, which distinguishes subpopulations based on the secretion of a specific hormone. These hormone-specific subpopulations included S cells for secretin (SCT), K cells for glucose-dependent insulinotropic polypeptide (GIP), N cells producing neurotensin (NTS), I cells producing cholecystokinin (CCK), D cells producing somatostatin (SST), and others. In the past 15 years, reinvestigations into murine and human organoid-derived EECs, however, strongly questioned this dogma and established that certain EECs coexpress multiple hormones.

Platelet mass cytometry reveals dysregulation of prothrombotic pathways in essential thrombocythemia.

Thromboembolic events are common in patients with essential thrombocythemia (ET). However, the pathophysiological mechanisms underlying the increased thrombotic risk remain to be determined. Here, we perform the first phenotypical characterization of platelet expression using single-cell mass cytometry in six ET patients and six age- and sex-matched healthy individuals.

Drugst.One - a plug-and-play solution for online systems medicine and network-based drug repurposing.

In recent decades, the development of new drugs has become increasingly expensive and inefficient, and the molecular mechanisms of most pharmaceuticals remain poorly understood. In response, computational systems and network medicine tools have emerged to identify potential drug repurposing candidates. However, these tools often require complex installation and lack intuitive visual network mining capabilities.

Diurnal rhythmicity of infant fecal microbiota and metabolites: A randomized controlled interventional trial with infant formula.

Microbiota assembly in the infant gut is influenced by diet. Breastfeeding and human breastmilk oligosaccharides promote the colonization of beneficial bifidobacteria. Infant formulas are supplemented with bifidobacteria or complex oligosaccharides, notably galacto-oligosaccharides (GOS), to mimic breast milk.

Inference of differential gene regulatory networks using boosted differential trees.

Summary: Diseases can be caused by molecular perturbations that induce specific changes in regulatory interactions and their coordinated expression, also referred to as network rewiring. However, the detection of complex changes in regulatory connections remains a challenging task and would benefit from the development of novel nonparametric approaches. We develop a new ensemble method called BoostDiff (boosted differential regression trees) to infer a differential network discriminating between two conditions.

Making mouse transcriptomics deconvolution accessible with immunedeconv.

Summary: Transcriptome deconvolution has emerged as a reliable technique to estimate cell-type abundances from bulk RNA sequencing data. Unlike their human equivalents, methods to quantify the cellular composition of complex tissues from murine transcriptomics are sparse and sometimes not easy to use. We extended the immunedeconv R package to facilitate the deconvolution of mouse transcriptomics, enabling the quantification of murine immune-cell types using 13 different methods.

Cracking the black box of deep sequence-based protein-protein interaction prediction.

Identifying protein-protein interactions (PPIs) is crucial for deciphering biological pathways. Numerous prediction methods have been developed as cheap alternatives to biological experiments, reporting surprisingly high accuracy estimates. We systematically investigated how much reproducible deep learning models depend on data leakage, sequence similarities and node degree information, and compared them with basic machine learning models.

On the limits of 16S rRNA gene-based metagenome prediction and functional profiling.

Molecular profiling techniques such as metagenomics, metatranscriptomics or metabolomics offer important insights into the functional diversity of the microbiome. In contrast, 16S rRNA gene sequencing, a widespread and cost-effective technique to measure microbial diversity, only allows for indirect estimation of microbial function. To mitigate this, tools such as PICRUSt2, Tax4Fun2, PanFP and MetGEM infer functional profiles from 16S rRNA gene sequencing data using different algorithms.

Comprehensive benchmark of differential transcript usage analysis for static and dynamic conditions.

RNA sequencing offers unique insights into transcriptome diversity, and a plethora of tools have been developed to analyze alternative splicing. One important task is to detect changes in the relative transcript abundance in differential transcript usage (DTU) analysis. The choice of the right analysis tool is non-trivial and depends on experimental factors such as the availability of single- or paired-end and bulk or single-cell data.

Blood transcriptomics analysis offers insights into variant-specific immune response to SARS-CoV-2.

Bulk RNA sequencing (RNA-seq) of blood is typically used for gene expression analysis in biomedical research but is still rarely used in clinical practice. In this study, we propose that RNA-seq should be considered a diagnostic tool, as it offers not only insights into aberrant gene expression and splicing but also delivers additional readouts on immune cell type composition as well as B-cell and T-cell receptor (BCR/TCR) repertoires. We demonstrate that RNA-seq offers insights into a patient's immune status via integrative analysis of RNA-seq data from patients infected with various SARS-CoV-2 variants (in total 196 samples with up to 200 million reads sequencing depth).

Multicenter Study of Long-Term Outcomes and Quality of Life in PHACE Syndrome after Age 10.

Objective: To characterize long-term outcomes of PHACE syndrome.

Study Design: Multicenter study with cross-sectional interviews and chart review of individuals with definite PHACE syndrome ≥10 years of age. Data from charts were collected across multiple PHACE-related topics.

Network medicine-based epistasis detection in complex diseases: ready for quantum computing.

Most heritable diseases are polygenic. To comprehend the underlying genetic architecture, it is crucial to discover the clinically relevant epistatic interactions (EIs) between genomic single nucleotide polymorphisms (SNPs). Existing statistical computational methods for EI detection are mostly limited to pairs of SNPs due to the combinatorial explosion of higher-order EIs.