The circadian rhythm plays a fundamental role in regulating biological functions, including sleep–wake preference, body temperature, hormonal secretion, food intake, and cognitive and physical performance. Alterations in circadian rhythm can lead to chronic disease and impaired sleep. The circadian rhythmicity in human beings is represented by a complex phenotype. Indeed, over a 24-h period, a person’s preferred time to be more active or to sleep can be expressed in the concept of morningness–eveningness. Three chronotypes are distinguished: Morning, Neither, and Evening-types. Interindividual differences in chronotypes need to be considered to reduce the negative effects of circadian disruptions on health. In the present review, we examine the bi-directional influences of the rest–activity circadian rhythm and sleep–wake cycle in chronic pathologies and disorders. We analyze the concept and the main characteristics of the three chronotypes.

Several studies have shown the differences among chronotypes in the circadian rhythm of different physiological variables. Individuals show variation in their preference for the daily timing of activity; additionally, there is an association between chronotype and sleep duration/sleep complaints. Few studies have investigated sleep quality during the week days and weekends in relation to the circadian typology using self-assessment questionnaires or actigraphy. The purpose of this study was to use actigraphy to assess the relationship between the three chronotypes and the circadian rhythm of activity levels and to determine whether sleep parameters respond differently with respect to time (weekdays versus the weekend) in Morning-types (M-types), Neither-types (N-types) and Evening-types (E-types). The morningness-eveningness questionnaire (MEQ) was administered to 502 college students to determine their chronotypes. Fifty subjects (16 M-types, 15 N-types and 19 E-types) were recruited to undergo a 7-days monitoring period with an actigraph (Actiwacth® actometers, CNT, Cambridge, UK) to evaluate their sleep parameters and the circadian rhythm of their activity levels. To compare the amplitude and the acrophase among the three chronotypes, we used a one-way ANOVA followed by the Tukey-Kramer post-hoc test. To compare the Midline Estimating Statistic of Rhythm (MESOR) among the three chronotypes, we used a Kruskal-Wallis non-parametric test followed by pairwise comparisons that were performed using Dunn's procedure with a Bonferroni correction for multiple comparisons. The analysis of each sleep parameter was conducted using the mixed ANOVA procedure. The results showed that the chronotype was influenced by sex (χ(2) with p = 0.011) and the photoperiod at birth (χ(2) with p < 0.05). Though the MESOR and amplitude of the activity levels were not different among the three chronotypes, the acrophases compared by the ANOVA post-hoc test were significantly different (p < 0.001). The ANOVA post-hoc test revealed the presence of a significant difference (p < 0.001) between the M-types (14:32 h) and E-types (16:53 h). There was also a significant interaction between the chronotype and four sleep parameters: Sleep end, Assumed Sleep, Immobility Time and Sleep Efficiency. Sleep Efficiency showed the same patterns as did Assumed Sleep and Immobility Time: the Sleep Efficiency of the E-types was poorer than that of the M- and N-types during weekdays (77.9% ± 7.0 versus 84.1% ± 4.9 and 84.1% ± 5.2) but was similar to that measured in the M- and N-types during the weekend. Sleep Latency and Movement and Fragmentation Index were not different among the three chronotypes and did not change on the weekend compared with weekdays. This study highlights two key findings: first, we observed that the circadian rhythm of activity levels was influenced by the chronotype; second, the chronotype had a significant effect on sleep parameters: the E-types had a reduced sleep quality and quantity compared with the M- and N-types during weekdays, whereas the E-types reached the same levels as the other chronotypes during the weekends. These findings suggest that E-types accumulate a sleep deficit during weekdays due to social and academic commitments and that they recover from this deficit during "free days" on the weekend.

The convincing background of the recent studies, investigating the different potentials of platelet-rich plasma, offers the clinician an appealing alternative for the treatment of cartilage lesions and osteoarthritis. Recent evidences in literature have shown that PRP may be helpful both as an adjuvant for surgical treatment of cartilage defects and as a therapeutic tool by intra-articular injection in patients affected by osteoarthritis. In this review, the authors introduce the trophic and anti-inflammatory properties of PRP and the different products of the available platelet concentrates. Then, in a complex scenario made of a great number of clinical variables, they resume the current literature on the PRP applications in cartilage surgery as well as the use of intra-articular PRP injections for the conservative treatment of cartilage degenerative lesions and osteoarthritis in humans, available as both case series and comparative studies. The result of this review confirms the fascinating biological role of PRP, although many aspects yet remain to be clarified and the use of PRP in a clinical setting has to be considered still exploratory.

Hypotheses. Sleep disorders are associated with an increased risk of cancer, including breast cancer (BC). Physical activity (PA) can produce beneficial effects on sleep. Study design. We designed a randomized controlled trial to test the effect of 3 months of physical activity on sleep and circadian rhythm activity level evaluated by actigraphy. Methods. 40 BC women, aged 35-70 years, were randomized into an intervention (IG) and a control group (CG). IG performed a 3 month of aerobic exercise. At baseline and after 3 months, the following parameters were evaluated both for IG and CG: anthropometric and body composition measurements, energy expenditure and motion level; sleep parameters (Actual Sleep Time-AST, Actual Wake Time-AWT, Sleep Efficiency-SE, Sleep Latency-SL, Mean Activity Score-MAS, Movement and Fragmentation Index-MFI and Immobility Time-IT) and activity level circadian rhythm using the Actigraph Actiwatch. Results. The CG showed a deterioration of sleep, whereas the IG showed a stable pattern. In the CG the SE, AST and IT decreased and the AWT, SL, MAS and MFI increased. In the IG, the SE, IT, AWT, SL, and MAS showed no changes and AST and MFI showed a less pronounced change in the IG than in the CG. The rhythmometric analysis revealed a significant circadian rhythm in two groups. After 3 months of PA, IG showed reduced fat mass %, while CG had improved weight and BMI. Conclusion. Physical activity may be beneficial against sleep disruption. Indeed, PA prevented sleep worsening in IG. PA can represent an integrative intervention therapy able to modify sleep behaviour.

Actigraphy is the reference objective method to measure circadian rhythmicity. One simpler subjective approach to assess the circadian typology is the Morningness–Eveningness Questionnaire (MEQ) by Horne and Ostberg. In this study, we compared the MEQ score against the actigraphy-based circadian parameters MESOR, amplitude and acrophase in a sample of 54 students of the University of Milan in Northern Italy. MEQ and the acrophase resulted strongly and inversely associated (r = −0.84, p < 0.0001), and their relationship exhibited a clear-cut linear trend. We thus used linear regression to develop an equation enabling us to predict the value of the acrophase from the MEQ score. The parameters of the regression model were precisely estimated, with the slope of the regression line being significantly different from 0 (p < 0.0001). The best-fit linear equation was: acrophase (min) = 1238.7–5.49·MEQ, indicating that each additional point in the MEQ score corresponded to a shortening of the acrophase of approximately 5 min. The coefficient of determination, R², was 0.70. The residuals were evenly distributed and did not show any systematic pattern, thus indicating that the linear model yielded a good, balanced prediction of the acrophase throughout the range of the MEQ score. In particular, the model was able to accurately predict the mean values of the acrophase in the three chronotypes (Morning-, Neither-, and Evening-types) in which the study subjects were categorized. Both the confidence and prediction limits associated to the regression line were calculated, thus providing an assessment of the uncertainty associated with the prediction of the model. In particular, the size of the two-sided prediction limits for the acrophase was about ±100 min in the midrange of the MEQ score. Finally, k-fold cross-validation showed that both the model’s predictive ability on new data and the model’s stability to changes in the data set used for parameter estimation were good. In conclusion, the actigraphy-based acrophase can be predicted using the MEQ score in a population of college students of North Italy.