Systemic sclerosis (SSc) is an autoimmune disease associated with increased mortality and poor morbidity, impairing the quality of life in patients. Whilst we know that SSc affects multiple organs via vasculopathy, inflammation, and fibrosis, its exact pathophysiology remains elusive. Microvascular injury and vasculopathy are the initial pathological features of the disease. Clinically, the vasculopathy in SSc is manifested as Raynaud’s phenomenon (reversible vasospasm in reaction to the cold or emotional stress) and digital ulcers due to ischemic injury. There are several reports that medications for vasculopathy, such as bosentan and soluble guanylate cyclase (sGC) modulators, improve not only vasculopathy but also dermal fibrosis, suggesting that vasculopathy is important in SSc. Although vasculopathy is an important initial step of the pathogenesis for SSc, it is still unclear how vasculopathy is related to inflammation and fibrosis. In this review, we focused on the clinical evidence for vasculopathy, the major cellular players for the pathogenesis, including pericytes, adipocytes, endothelial cells (ECs), and myofibroblasts, and their signaling pathway to elucidate the relationship among vasculopathy, inflammation, and fibrosis in SSc.

Single-cell RNA sequencing (scRNA-seq) has emerged as a powerful technique for investigating biological heterogeneity at the single-cell level in human systems and model organisms. Recent advances in scRNA-seq have enabled the pooling of cells from multiple samples into single libraries, thereby increasing sample throughput while reducing technical batch effects, library preparation time, and the overall cost. However, a comparative analysis of scRNA-seq methods with and without sample multiplexing is lacking. In this study, we benchmarked methods from two representative platforms: Parse Biosciences (Parse; with sample multiplexing) and 10x Genomics (10x; without sample multiplexing). By using peripheral blood mononuclear cells (PBMCs) obtained from two healthy individuals, we demonstrate that demultiplexed scRNA-seq data obtained from Parse showed similar cell type frequencies compared to 10x data where samples were not multiplexed. Despite relatively lower cell capture affecting library preparation, Parse can detect rare cell types (e.g., plasmablasts and dendritic cells) which is likely due to its relatively higher sensitivity in gene detection. Moreover, a comparative analysis of transcript quantification between the two platforms revealed platform-specific distributions of gene length and GC content. These results offer guidance for researchers in designing high-throughput scRNA-seq studies.

The human gut microbiota plays a key role in neurochemical communication, especially through the gut–brain axis. There is growing evidence that the gut microbiota influences dopamine metabolism through both production and consumption mechanisms. Two key bacterial enzymes are central to this process: tyrosine decarboxylase (TDC), which primarily catalyzes the decarboxylation of tyrosine to tyramine but can also act on L-DOPA to produce dopamine in certain bacterial strains, and aromatic L-amino acid decarboxylase (AADC), which can convert precursors such as L-DOPA, tryptophan, or 5-hydroxytryptophan into bioactive amines including dopamine, tryptamine, and serotonin. Identifying the bacterial families corresponding to TDC and AADC enzymes opens new avenues for clinical intervention, particularly in neuropsychiatric and neurodegenerative disorders, such as Parkinson’s disease. Moreover, elucidating strain-specific microbial contribution and host-microbe interactions may enable personalized therapeutic strategies, such as selective microbial enzyme inhibitors or tailored probiotics, to optimize dopamine metabolism. Emerging technologies, including biosensors and organ-on-chip platforms, offer new tools to monitor and manipulate microbial dopamine activity. This article explores the bacterial taxa capable of producing or consuming dopamine, focusing on the enzymatic mechanisms involved and the methodologies available for studying these processes in vivo.

Background: Constipation can precede the motor diagnosis of Parkinson’s disease (PD), but its mechanisms are multifactorial. Gut bacteria can metabolize administered levodopa (LD), and enteric dopamine receptors participate in the regulation of motility. These observations motivate, but do not establish, a connection between microbial LD metabolism and constipation. Evidence: Bacterial tyrosine decarboxylase (TDC) converts LD to dopamine in biochemical and animal systems. Human studies associate fecal TDC abundance with some treatment and pharmacokinetic variables, but gene abundance does not measure enzyme activity. A longitudinal PD cohort found an inverse association between constipation severity and TDC abundance in one model, highlighting the need to consider medication effects and reverse causation. Microbiome alterations in risk-enriched populations do not demonstrate increased TDC activity before PD diagnosis. Hypothesis: In a subset of untreated individuals at increased risk of PD, sufficient luminal endogenous L-DOPA might permit microbial dopamine production that influences intestinal transit, provided that the resulting dopamine reaches relevant receptors at effective concentrations. Endogenous substrate availability, anatomical access, and the net balance of dopamine production and clearance are unresolved. After LD treatment begins, a larger exogenous substrate supply creates a distinct setting for drug–microbe interactions. Conclusions: The proposed continuum is conditional and requires biochemical and functional validation before human biomarker development. We propose substrate tracing, comparisons of TDC-positive and TDC-deficient bacteria, receptor-specific testing, and longitudinal gastrointestinal phenotyping. Current evidence does not justify TDC-directed dietary prevention of PD or clinical prediction from fecal TDC abundance alone.