Impact of Maternal Anxiety on Human Milk Macronutrients Content: A Prospective Observational Study.

Objective: The impact of maternal anxiety on the macronutrients content of human milk (HM) is unknown. We hypothesized that maternal stress generated by her infant's hospitalization will affect the mother's breast milk's macronutrients content. Materials and Methods: HM samples (2-3 mL) were collected from 21 mothers whose infants were hospitalized for 2-3 days between August 2016 and November 2017 due to neonatal fever. Samples were provided at three time points: first day of admission, second day of admission, and 1 week after discharge. The maternal anxiety level was measured by the State-Trait Anxiety Inventory (STAI). Milk analyses for macronutrients were performed by infrared transmission spectroscopy. Results: Fat and energy contents of HM on day 7 were significantly higher compared with the day of admission (p = 0.019 and p = 0.022, respectively), whereas they were similar to values on day 2. The maternal anxiety level (STAI) at the time of infant admission was significantly higher than at 1 week after discharge (p < 0.001). There was no significant correlation between the changes in fat content and changes in the STAI score between admission and 1 week after discharge. Conclusion: Short infant hospitalization is associated with a significant rise in maternal stress; however, macronutrients content of HM remained unaffected.

A 4-MicroRNA signature can discriminate primary lymphomas from anaplastic carcinomas in thyroid cytology smears.

BACKGROUND: Anaplastic thyroid carcinoma (ATC) and primary thyroid lymphoma (PTL) are uncommon tumors of the thyroid gland with several overlapping clinical and pathologic features that may render their differentiation difficult in fine-needle aspiration (FNA) cytology. MicroRNA (miRNA) signatures have been recently reported as useful diagnostic tools applied to cytology specimens. METHODS: Smears of 23 ATCs, 14 PTLs, and 20 non-neoplastic materials with multinodular goiter (MNG) were retrieved and classified based on their cytologic features and flow cytometric profiles. The ATC-related expression of hsa-miR-26a, hsa-miR-146b, hsa-miR-221, and hsa-miR-222 was quantified using quantitative reverse transcriptase-polymerase chain reaction analysis. RESULTS: All miRNAs were remarkably up-regulated in ATC samples compared with PTL samples (P < .01). Moreover, expression levels of hsa-miR-146b, hsa-miR-221, and hsa-miR-222 were significantly higher in ATCs than in MNG samples (P < .01). Significant down-regulation of hsa-miR-26a was observed in PTLs compared with MNG samples, whereas hsa-miR-146b was overexpressed. Receiver operating characteristic analysis was used to determine the optimal cutoff for distinguishing ATC from PTL. The estimated receiver operating characteristic thresholds displayed a sensitivity level greater than 0.80 in achieving a diagnosis of PTL, allowing the correct identification of 13 of 14 PTL samples (93%). CONCLUSIONS: Histotype-specific miRNA signatures can provide new insight into the molecular mechanisms of thyroid carcinogenesis. The tested 4-miRNA signature is a promising diagnostic tool for differentiating ATC from PTL and non-neoplastic MNG, even in the presence of scant material obtained from minimally invasive procedures.

The miR-17-92 microRNA cluster: a novel diagnostic tool in large B-cell malignancies.

Diffuse large B-cell lymphoma (DLBCL) can present as de novo or can arise through the transformation of many indolent lymphomas, including follicular lymphoma (FL). The morphological differentiation between germinal center-DLBCL (GC-DLBCL) and high-grade (grade 3) FL could be challenging; the accurate sub-classification of large B-cell lymphomas is mandatory in order to select the most appropriate among the new-targeted therapies. Recent expression profiling studies reported microRNAs (miRNAs) (and miR-17-92 cluster, in particular) as useful tools in differentiating DLBCL and FL. However, these preliminary results are based on cell line-derived data or did not consider grade 3 FL cases. To investigate this point, 36 cases of GC-DLBCL and 18 cases of grade 3 non-transforming FL were considered. All diagnoses were based on the World Health Organization criteria and were confirmed by clinical, histological, and immunohistochemical data. Six members of the miR-17-92 cluster (ie, miR-18b, miR-19b, miR-20a, miR-92, miR-93, and miR-106a) and two control miRNAs (ie, miR-150 and miR-210) were quantified by quantitative reverse transcription-polymerase chain reaction. All the considered miR-17-92 cluster miRNAs were significantly overexpressed in GC-DLBCL, being miR-20a and miR-106a the most dysregulated (P<0.001). Receiver operating characteristics (ROCs) analysis was used to find the optimal cut-off in distinguishing the two histotypes. The ROC estimated thresholds for miR-18b, miR-19b, miR-20a, miR-92, and miR-106a displayed a sensitivity level higher than 0.80 in achieving the GC-DLBCL diagnosis. The classification tree built on the six thresholds allowed the correct identification of 35/36 GC-DLBCL (97.2%). Profiling the miR-17-92 cluster is a promising investigative method for differentiating GC-DLBCL from high-grade FL. Subject to the validation of these findings in further larger studies; miR-17-92 cluster could represent a reliable, standardizable diagnostic tool for the sub-classification of large B-cell lymphoid neoplasm.