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Summary: Deconvolution algorithms mostly rely on single-cell RNA-sequencing (scRNA-seq) data applied onto bulk RNA-sequencing (bulk RNA-seq) to estimate tissues’ cell-type composition, with performance accuracy validated on deposited databases. Adipose tissues’ cellular composition is highly variable, and adipocytes can only be captured by single-nucleus RNA-sequencing (snRNA-seq). Here we report the development of sNucConv, a Scaden deep-learning-based deconvolution tool, trained using 5 hSAT and 7 hVAT snRNA-seq-based data corrected by (i) snRNA-seq/bulk RNA-seq highly correlated genes and (ii) individual cell-type regression models. Applying sNucConv on our bulk RNA-seq data resulted in cell-type proportion estimation of 15 and 13 cell types, with accuracy of R = 0.93 (range: 0.76–0.97) and R = 0.95 (range: 0.92–0.98) for hVAT and hSAT, respectively. This performance level was further validated on an independent set of samples (5 hSAT; 5 hVAT). The resulting model was depot specific, reflecting depot differences in gene expression patterns. Jointly, sNucConv provides proof-of-concept for producing validated deconvolution models for tissues un-amenable to scRNA-seq.

Conclusion: Our findings suggest that IORT in selected low-risk patients can achieve an excellent prognosis with low rates of recurrence and metastasis.

Background: Abdominal aspergillosis is a life-threatening, opportunistic fungal infection that mainly affects immunocompromised patients. In this report, we present a case of abdominal surgical site aspergillosis in an immunocompetent patient. Case presentation: A 74-year-old immune-competent woman that had a prolonged hospitalization in the Intensive Care (ICU) Unit with several abdominal surgeries and multiple antibiotic treatment regimens. The abdomen remained open between interventions. 21 days following ICU admission a diagnosis of surgical site aspergillosis was made, treated with systemic and topical antifungal treatment. Conclusions: While nosocomial aspergillosis typically affects immunocompromised patients, immunocompetent patients also become susceptible when the skin barrier is broken and tissue is exposed to the environment. Treatment consisted with surgical debridement and systemic antifungal therapy. This case provides an example of extensive and rare surgical infection.

Objective: Up-regulated expression of transcription-factor E2F1 in human visceral adipose tissue (VAT) characterizes a dysmetabolic obesity sub-phenotype. An E2F1-miRNA network has been described in multiple cancers. Here we investigated whether elevated VAT-E2F1 in obesity is associated with VAT-miRNA alterations similar to, or distinct from, those described in cancer. Furthermore, we assessed if E2F1-associated miRNA changes may contribute to the link between high- VAT-E2F1 and a dysmetabolic obesity phenotype. Methods: We assembled a cohort of patients with obesity and high-VAT-E2F1, matched by age, sex, ±BMI to patients with low-VAT-E2F1, with and without obesity (8 patients/groupX3 groups). We performed Nanostring©-based miRNA profiling of VAT samples from all 24 patients. Candidate E2F1-related miRNAs were validated by qPCR in an independent cohort of patients with extreme obesity, with or without type-2-diabetes (T2DM) (n = 20). Bioinformatic tools and manipulation of E2F1 expression in cells were used to establish the plausibility of the functional VAT-E2F1-miRNA network in obesity. Results: Among n = 798 identified miRNAs, 17 were differentially expressed in relation to E2F1 and not to obesity itself. No evidence for the cancer-related E2F1-miRNA network was identified in human VAT in obesity. In HEK293-cells, overexpression/downregulation of E2F1 correspondingly altered the expression of miRNA-206 and miRNA-210-5p, two miRNAs with reported metabolic functions consistent with those of E2F1. In VAT from both cohorts, the expression of both miRNA-206 and 210-5p intercorrelated, and correlated with the expression of E2F1. In cohort 1 we did not detect significant associations with biochemical parameters. In cohort 2 of patients with extreme obesity, all those with high VAT-E2F1 showed a diabetes-complicated obesity phenotype and higher expression of miRNA-206 and miRNA-210-5p, which also correlated with fasting glucose levels (both miRNAs) and fasting insulin (miRNA-210-5p). Conclusions: Whilst the previously described cancer-related E2F1-miRNA network does not appear to operate in VAT in obesity, miRNAs-206 and 210-5p may link high-E2F1 expression in VAT with diabetes-complicated extreme obesity phenotype.