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Biology subjects

Franca, L. G. S.

Publications and source records attributed to Franca, L. G. S..

7 recordsLinked to original sources

Menstrual cycle irregularity is a biological determinant of mental health independent of sleep in adolescents

INTRODUCTIONSex differences in mental health emerge during adolescence, a period marked by the onset and the establishment of menstrual cycle. However, is rarely examined how menstrual cycle regularity, a marker of hormonal function, modulates mental health. OBJECTIVEto analyse sex differences in mental health symptoms among adolescents considering the menstrual cycle regularity and sleep. METHODSA three-group design (female students with regular cycles/FR, n=77; with irregular cycles/FI, n=59; and male students/M, n=76) in a sample of Brazilian high-school adolescents (n=212; 14-18 years) enrolled in morning and full-time classes was used to test the hypothesis that mental health symptoms follow a graded pattern across these groups. RESULTSMean DASS-21 scores across all groups fell at or above the Mild severity threshold for mental health subscales. GLMs confirmed a monotonic gradient increase in group order (M[->]FR[->]FI) which was associated with higher scores on all outcomes (stress {beta}/step=4.33, p<.001; anxiety {beta}/step=4.08, p<.001; and depression {beta}/step=2.34, p=.010; model R{superscript 2}=.16, .13, .08 respectively). However, no differences were observed in sleep duration, social jetlag, chronotype, sleep quality, or sleep-debt. Then, a secondary analysis assessed sex-specific associations between socioeconomic status (SES) and mental health; higher SES was inversely related to stress, anxiety, and depression, being protective only in males (stress Males {beta}=-2.68, p=.011/Females {beta}=0.46, p=.614). CONCLUSIONThese findings support the reframing of menstrual irregularity not only as a reproductive health concern but also as a biological determinant of mental health risk in female adolescents, a vulnerability that sleep disruption and socioeconomic resources do not adequately explain.

physiology↗

Low-latitude environmental regularity sustains non-photicentrainment in blind adults

The light-dark cycle shaped by Earths rotation provided the evolutionary conditions under which circadian rhythms emerged. Consistent with this, previous studies indicate that less than 40% of total blind individuals, who lack photic input, entrain to the 24-h cycle, further evidencing the critical role of light as the dominant zeitgeber for circadian alignment. However, this assumption has been tested almost exclusively in temperate, high-latitude regions, where environmental cues vary seasonally. Near the equator, by contrast, photoperiod and temperature cycles remain exceptionally stable. This highlights a fundamental gap: can circadian rhythms in humans remain synchronised without light when environmental temporal cues are highly regular? We addressed this question in 58 blind adults (21-77 years; 43.1% female) living near the equator in Rio Grande do Norte, Brazil ([~]5{degrees}S), who wore wrist actigraphy continuously for four weeks. Light sensitivity was assessed through the pupillary light reflex (PLR; 22 PLR-reactive, 36 non-reactive). Applying a semi-supervised machine learning approach to uncover multidimensional patterns without prior categorisation, we identified two distinct phenotypes: a Higher Circadian Stability (HCS; 72%, n = 42) and a Lower Circadian Stability group (LCS; 28%, n = 16). Notably, 64% of PLR-non-reactive individuals (23 of 36) were classified within the HCS group, a proportion approximately 1.6 times higher than previously reported for blind cohorts. These findings demonstrate that, under exceptionally regular equatorial conditions, non-photic cues can sustain a robust circadian entrainment even in the absence of photic input. We propose that environmental regularity promotes the synergy of non-photic timing signals, underscoring ecological context as a key determinant of human circadian temporal organisation.

physiology↗

From Movement to METs: A Validation of ActTrust(R) for Energy Expenditure Estimation and Physical Activity Classification in Young Adults

Estimating physical activity (PA) levels is a challenging and expensive task. An alternative could be the use of actigraphy devices to estimate PA. This has been previously done to a number of devices, including ActiGraph(R) GT3X+. In this study, we validated ActTrust(R) against the widely used GT3X+ and compared activity counts to metabolic equivalents (METs) derived from indirect calorimetry during treadmill walking and running. Fifty-six young adults (34 men, 22 women) participated in controlled effort exercises including light, moderate, vigorous, and very vigorous activity intensities. We developed a linear model to estimate energy expenditure (EE) from movement count of combinations of devices placed at hip or wrist. We then estimated cut-off points for each intensity range. Our results showed correlations between treadmill speed and both METs (r = 0.95, p < 0.05) and movement counts from both GT3X+ and ActTrust devices placed either on the hip (r = 0.94, p < 0.05; r = 0.93, p < 0.05) or on the wrist (r = 0.88, p < 0.05; r = 0.88, p < 0.05), respectively. Our proposed model performed well with balanced accuracies above 0.77 for all intensity ranges and over 0.9 for light and moderate activity. This is the first study to model estimate and validate PA intensity thresholds on ActTrust(R) devices. Our findings support the use of ActTrust(R) devices as simple, cost-effective tool for 24-hour assessments of EE.

bioinformatics↗

Resting-state alpha reactivity is reduced in Parkinson disease and associated with gait variability

BackgroundThe extent to which the cholinergic system contributes to gait impairments in Parkinsons disease (PD) remains unclear. Electroencephalography (EEG) alpha reactivity, which refers to change in alpha power over occipital electrodes upon opening the eyes, has been suggested as a marker of cholinergic function. We compared alpha reactivity between people with PD and healthy individuals and explored its potential association with gait measures. MethodsEyes-closed and eyes-open resting-state EEG data were recorded from 20 people with idiopathic PD and 19 healthy individuals with a 64-channel EEG system. Alpha reactivity was calculated as the relative change in alpha power (8-13 Hz) over occipital electrodes from eyes-closed to eyes-open. Gait spatiotemporal measures were obtained with an electronic walkway. ResultsAlpha reactivity was reduced in people with PD compared to healthy individuals (U = 105, p = 0.017); the rank-biserial correlation of 0.447 indicated a moderate effect size. When controlling for global cognition (Mini Mental State Examination), the group difference in alpha reactivity was no longer significant. Alpha reactivity associated with measures of gait variability only (rho = -0.437 to -0.532). ConclusionsReduced alpha reactivity in PD is driven by levels of global cognition and suggests impaired cholinergic function in PD. Reduced alpha reactivity was associated with greater gait variability, indicating a role of the cholinergic system in the mechanisms underlying gait variability. Therefore, the cholinergic system may represent a target for treatments aiming to reduce gait variability and alpha reactivity should be further explored as an endpoint for clinical trials.

neuroscience↗

Non-invasive canine electroencephalography (EEG): a systematic review

AO_SCPLOWBSTRACTC_SCPLOWThe emerging field of canine cognitive neuroscience uses neuroimaging tools such as electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) to map the cognitive processes of dogs to neural substrates in their brain. Within the past decade, the non-invasive use of EEG has provided real-time, accessible, and portable neuroimaging insight into canine cognitive processes. To promote systematization and create an overview of framings, methods and findings for future work, we provide a systematic review of non-invasive canine EEG studies (N=22), dissecting their study makeup, technical setup, and analysis frameworks and highlighting emerging trends. We further propose new directions of development, such as the standardization of data structures and integrating predictive modeling with descriptive statistical approaches. Our review ends by underscoring the advances and advantages of EEG-based canine cognitive neuroscience and the potential for accessible canine neuroimaging to inform both fundamental sciences as well as practical applications for cognitive neuroscience, working dogs, and human-canine interactions.

animal behavior and cognition↗

Neonatal brain dynamic functional connectivity: impact of preterm birth and association with early childhood neurodevelopment

Brain dynamic functional connectivity characterises transient connections between brain regions, changing over time. Features of brain dynamics have been linked to emotion and cognition in adult individuals, and atypical patterns have been associated with neurodevelopmental conditions such as autism. Although reliable functional brain networks have been consistently identified in neonates, little is known about the early development of dynamic functional connectivity. In this study we characterise dynamic functional connectivity with functional magnetic resonance imaging (fMRI) in the first few weeks of postnatal life in term-born (n = 324) and preterm-born (n = 66) individuals. We show that a dynamic landscape of brain connectivity is already established by the time of birth in the human brain, characterised by six transient states of neonatal functional connectivity with changing dynamics through the neonatal period. The pattern of dynamic connectivity is atypical in preterm-born infants, and associated with atypical social, sensory, and repetitive behaviours measured by the Quantitative Checklist for Autism in Toddlers (Q-CHAT) scores at 18 months of age.

neuroscience↗

Clinical, socio-demographic, and parental correlates of early autism traits

BackgroundAutism traits emerge between the ages of 1 and 2. It is not known if experiences which increase the likelihood of childhood autism are related to early trait emergence, or if other exposures are more important. Identifying factors linked to toddler autism traits in the general population may improve our understanding of the mechanisms underlying atypical neurodevelopment. MethodsClinical, socio-demographic, and parental information was collected at birth from 536 toddlers in London, UK (gestational age at birth, sex, maternal body mass index, age, parental education level, parental first language, parental history of neurodevelopmental disorders) and at 18 months (parent cohabiting status, two measures of social deprivation, three measures of maternal parenting style, and a measure of maternal postnatal depression). General neurodevelopment was assessed with the Bayley Scales of Infant and Toddler Development, 3rd Edition (BSID-III), and autism traits were assessed using the Quantitative Checklist for Autism in Toddlers (Q-CHAT). Multivariable models were used to identify associations between variables and Q-CHAT. A model including BSID-III was used to identify factors associated with Q-CHAT independent of general neurodevelopment. Models were also evaluated addressing variable collinearity with principal component analysis (PCA). ResultsA multivariable model explained 20% of Q-CHAT variance, with four individually significant variables (two measures of parenting style and two measures of socio-economic deprivation). After adding general neurodevelopment into the model 36% of Q-CHAT variance was explained, with three individually significant variables (two measures of parenting style and one measure of language development). After addressing variable collinearity with PCA, parenting style and social deprivation were positively correlated with Q-CHAT score via a single principal component, independently of general neurodevelopment. Neither sex nor family history of autism were associated with Q-CHAT score. LimitationsThe Q-CHAT is parent rated and is therefore a subjective opinion rather than a clinical assessment. We measured Q-CHAT at a single timepoint, and to date no participant has been followed up in later childhood, so we are focused purely on emerging traits rather than clinical autism diagnoses. ConclusionsAutism traits are common at age 18 months, and greater emergence is specifically related to exposure to early life adversity.

neuroscience↗