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Umbilical cord blood (UCB) contains hematopoietic stem cells and multipotent mesenchymal cells useful for treatment in malignant/nonmalignant hematologic-immunologic diseases and regenerative medicine. Transplantation outcome is correlated with cord blood volume (CBV), number of total nucleated cells (TNC), CD34+ progenitor cells and colony forming units in UCB donations. Several studies have addressed the role of maternal/neonatal factors associated with the hematopoietic reconstruction potential of UCB, including: gestational age, maternal parity, newborn sex and birth weight, placental weight, labor duration and mode of delivery. Few data exist regarding as to how time influences UCB collection and banking patterns. We retrospectively analyzed 17.936 cord blood donations collected from 1999 to 2011 from Tuscany and Apulia Cord Blood Banks. Results from generalized multivariable linear mixed models showed that CBV, TNC and CD34+ cell were associated with known obstetric and neonatal parameters and showed rhythmic patterns in different time domains and frequency ranges. The present findings confirm that volume, total nucleated cells and stem cells of the UCB donations are hallmarked by rhythmic patterns in different time domains and frequency ranges and suggest that temporal rhythms in addition to known obstetric and neonatal parameters influence CBV, TNC and CD34+ cell content in UBC units.

Knowledge of whole body circadian phase is important for the evaluation of physiological processes and for planning time-qualified therapy. The nightly peak in melatonin secretion and the morning peak in cortisol secretion are well-known, prominent circadian rhythmic phenomena in health. Due to their high-amplitude oscillation and relative stability of phase under standardized light-dark conditions, both hormones, either by frequent, dense sampling for melatonin near the onset and/or offset of sleep, morning vs. evening sampling for cortisol, or around-the-clock dense sampling of either, have been suggested for use as a 24 h marker rhythm. Our study evaluated a feasible sampling protocol of collecting six blood samples over 24 h to individually determine whole body circadian phase (i.e., the acrophase, aO) from each hormone and therein establish synchronization to the light-dark schedule. Cortisol and melatonin serum levels were measured in peripheral blood samples collected every 4 h for 24 h from 11 healthy men, ages 35–53 years, with the sleep/dark span from 23:00–07:00 h. Circadian changes were evaluated by ANOVA and 24 h cosine fitting for original serum levels and also for the fractional variation (FV) that was calculated to evaluate the dynamics (percentage change) of the rise and fall in serum levels between 4 h sampling times. A significant time-effect and 24 h rhythm was detected for both serum melatonin (aO = 01:35 h) and cortisol (aO = 07:48 h), confirming synchronization by the subjects as a group to their 24 h environmental light-dark (sleep-wake) schedule, with the anticipated peak for melatonin during darkness and for cortisol in the morning. Overall 4 h FV levels for melatonin and cortisol also showed prominent 24 h rhythms, with highest values prior to darkness onset for melatonin (aO = 22:29 h) and near mid-dark for cortisol (aO = 02:12 h), which preceded maximal serum levels by ∼3 h for melatonin and ∼5 h for cortisol. On an individual basis, all 11 subjects showed an unmistakable peak in serum melatonin levels at 02:00 h, while eight subjects showed a clear peak in serum cortisol levels at 06:00 h, one subject showed a delayed peak at 10:00 h, and two subjects showed a broad peak between 02:00 h and 14:00 h. The aO spread was 5 h 18 min for melatonin (23:54 h to 05:12 h) and 7 h 11 min for cortisol (04:54 h to 12:05 h). These results show that 4 h sampling over 24 h, in lieu of more frequent sampling, can be useful for determining whole body circadian phase and light-dark synchronization, especially when using melatonin, since cortisol can be more easily influenced by external factors involving stress, thereby resulting in a larger spread in peak times. Calculating fractional variations over 4 h intervals also helps to describe the complex dynamics of hormone secretion rates over 24 h. It is thus possible to describe circadian characteristics of hormone secretion with a sampling and data analysis protocol that allows the definition of both temporal characteristics (by cosine fitting) and dynamics (percentage change) using samples obtained every 4 h over 24 h. This protocol may be useful in the study of hormone secretion levels and dynamics in disease and to guide therapeutic and other interventions by defining whole body circadian phase on an individual basis using melatonin or cortisol.

The rhythmic recurrence of biological processes is driven by the functioning of cellular circadian clocks, operated by a set of genes and proteins that generate self-sustaining transcriptional-translational feedback loops with a free-running period of about 24 h. In the gastrointestinal apparatus, the functioning of the biological clocks shows distinct patterns in the different organs. The aim of this study was to evaluate the time-related variation of clock gene expression in mouse liver and stomach, two components of the digestive system sharing vascular and autonomic supply, but performing completely different functions. The authors analyzed the periodicity by cosinor analysis and the dynamics of variation by computing the fractional variation to assess the rate of change in gene expression. Five-week-old male Balb/c mice were exposed to 2 wks of 12-h light/12-h dark cycles, then kept in complete darkness for 3 d as a continuation of the dark span of the last light-dark cycle. The authors evaluated the expression of Bmal1, Clock, Cry1, Cry2, Per1, Per2, Per3, Rev-erbα, Rev-erbβ, Npas2, Timeless, Dbp, Csnk1d, and Csnk1e by using real-time quantitative reverse transcriptase–polymerase chain reaction (RT-PCR) in mouse liver and stomach. A significant 24-h rhythmic component was found for 10 genes in the liver (Bmal1, Clock, Cry1, Per1, Per2, Per3, Rev-erbα, Rev-erbβ, Npas2, and Dbp), and for 9 genes in the stomach (Bmal1, Cry1, Per1, Per2, Per3, Rev-erbα, Rev-erbβ, Npas2, and Dbp). In particular, Clock showed marked rhythm differences between liver and stomach, putatively due to some compensation by Npas2. The acrophase of the original values of Bmal1, Per2, Per3, Rev-erbα, Rev-erbβ, Npas2, and Dbp expression was delayed in the stomach, and the average delay expressed as mean ± SD was 14.30 ± 7.94 degrees (57.20 ± 31.78 minutes). A statistically significant difference was found in the acrophases of Bmal1 (p= .015) and Npas2 (p= .011). Fractional variations provided significant circadian rhythms for nine genes in the liver (Bmal1, Per1, Per2, Per3, Reverbα, Rev-erbβ, Npas2, Timeless, and Dbp), and for seven genes in the stomach (Bmal1, Clock, Per2, Rev-erbα, Npas2, Dbp, and Csnk1e). The acrophase of the fractional variations of Bmal1, Per2, Per3, Rev-erbα, Rev-erbβ, and Dbp expression was delayed in the stomach, and the average delay expressed as mean ± SD was 19.10 ± 9.39 degrees (76.40 ± 37.59 minutes). A significantly greater fractional variation was found in the liver for Clock at 06:00 h (p= .034), Per1 at 02:00 h (p= .037), and Per3 at 02:00 h (p= .029), whereas the fractional variation was greater in the stomach for Clock at 10:00 h (p= .016), and for Npas2 at 02:00 h (p= .029) and at 06:00 h (p= .044). In conclusion, liver and stomach show different phasing and dynamics of clock gene expression, which are probably related to prevailing control by different driving cues, and allow them to keep going the various metabolic pathways and diverse functional processes that they manage. (Author correspondence: g.mazzoccoli@operapadrepio.it)

Carcinogenesis is related to the loss of homeostatic control of cellular processes regulated by transcriptional circuits and epigenetic mechanisms. Among these, the activities of peroxisome proliferator-activated receptors (PPARs) and DNA methyltransferases (DNMTs) are crucial and intertwined. PPARγis a key regulator of cell fate, linking nutrient sensing to transcription processes, and its expression oscillates with circadian rhythmicity. Aim of our study was to assess the periodicity of PPARγand DNMTs in pancreatic cancer (PC). We investigated the time-related patterns ofPPARG, DNMT1, andDNMT3Bexpression monitoring their mRNA levels by qRT-PCR at different time points over a 28-hour span in BxPC-3, CFPAC-1, PANC-1, and MIAPaCa-2 PC cells after synchronization with serum shock.PPARGandDNMT1expression in PANC-1 cells andPPARGexpression in MIAPaCa-2 cells were characterized by a 24 h period oscillation, and a borderline significant rhythm was observed for thePPARG, DNMT1, andDNMT3Bexpression profiles in the other cell lines. The time-qualified profiles of gene expression showed different shapes and phase relationships in the PC cell lines examined. In conclusion,PPARGandDNMTsexpression is characterized by different time-qualified patterns in cell lines derived from human PC, and this heterogeneity could influence cell phenotype and human disease behaviour.

This paper describes the fundamentals of a custom method derived by previous studies based on PCA (Principal Component Analysis) [1]. Its objective is to automatically define the evaluable area of an ultrasound image and, once that it is defined, to characterize the relationship between the gain variation and the ultrasound image.

Alterations in hormone secretion and cytokine levels have been evidenced in many neoplastic diseases. In this study we have evaluated the circadian profile of growth hormone (GH), insulin-like growth factor-1 (IGF-1), interleukin-2 (IL2), melatonin (MEL) and Cortisol (COR) serum levels in non-small cell lung cancer patients. Blood was sampled every 4 h for 24 h in 11 healthy (H) men (ages 35–53 years) and 9 men with stage 2, 3 or 4 non-small cell lung cancer (C) (ages 43–63 years). Serum GH, total IGF1, IL2, MEL and COR were measured and examined for group differences, trends, and rhythm characteristics. 24-h means were significantly higher in C234 vs H for GH, GH/IGF1, IL2 and COR, and lower for IGF1, but IL2 and COR were not different for C23 vs H. A linear regression across 4 groups (H, C2, C3, C4) found a positive trend for COR, GH, GH/IGF1 and IL2, and a negative trend for IGF1. A linear regression run between the 24-h mean levels of GH, IGF1, COR, MEL and IL2 in healthy subjects evidenced a statistically significant positive trend between MEL and GH (R=0.281, p=0.022) and in cancer patients showed a statistically significant negative trend between GH and IGF1 (R=0.332, p=0.01), COR and IGF1 (R=0.430, p=0.001), and a statistically significant positive trend between the 24-h mean of COR and GH (R=0.304, p=0.02). Rhythms in MEL and COR (peaks near 01:00h and 08:00h, respectively) indicated identical synchronization to the light-dark cycle for both groups. A circadian rhythm was detected in GH and GH/IGF1 for C23 and H, with IGF1 and IL2 non-rhythmic in any group. In conclusion, an increasing trend and progressive loss of circadian rhythmicity in GH and GH/IGF1, an increasing trend in Cortisol and IL2, and a decreasing trend in IGF1 in C, reflect a complex chain of events that could be involved in progression of neoplastic disease. A therapeutic strategy needs to take into account circadian patterns and complex interactions of the multiple functions that characterize the hormone and cytokine levels in the frame cancer progression.

Background: Hunter syndrome (HS) is a lysosomal storage disease caused by iduronate-2-sulfatase (IDS) deficiency and loss of ability to break down and recycle the glycosaminoglycans, heparan and dermatan sulfate, leading to impairment of cellular processes and cell death. Cell activities and functioning of intracellular organelles are controlled by the clock genes (CGs), driving the rhythmic expression of clock controlled genes (CCGs). We aimed to evaluate the expression of CGs and downstream CCGs in HS, before and after enzyme replacement treatment with IDS. Methods: The expression levels of CGs and CCGs were evaluated by a whole transcriptome analysis through Next Generation Sequencing in normal primary human fibroblasts and fibroblasts of patients affected by HS before and 24 h/144 h after IDS treatment. The time related expression of CGs after synchronization by serum shock was also evaluated by qRT-PCR before and after 24 hours of IDS treatment. Results: In HS fibroblasts we found altered expression of several CGs and CCGs, with dynamic changes 24 h and 144 h after IDS treatment. A semantic hypergraph-based analysis highlighted five gene clusters significantly associated to important biological processes or pathways, and five genes, AHR, HIF1A, CRY1, ITGA5 and EIF2B3, proven to be central players in these pathways. After synchronization by serum shock and 24 h treatment with IDS the expression of ARNTL2 at 10 h (p = 0.036), PER1 at 4 h (p = 0.019), PER2 at 10 h (p = 0.041) and 16 h (p = 0.043) changed in HS fibroblasts. Conclusion: CG and CCG expression is altered in HS fibroblasts and IDS treatment determines dynamic modifications, suggesting a direct involvement of the CG machinery in the physiopathology of cellular derangements that characterize HS.