Prevalence and risk factors of perinatal depression among women in rural Bihar: A community-based cross-sectional study.

BACKGROUND: Perinatal depression (PND) is one of the most common mental disorders occurring during the perinatal period among women. Few studies examined prevalence and risk factors of PND from rural settings in India. This study aimed to estimate the prevalence of perinatal depression and identify social risk factors for it among women from rural Bihar. MATERIALS AND METHODS: A cross sectional study was conducted in a community setting in rural areas of Bihar. All perinatal women were screened through a door to door survey and recruited after obtaining informed consent. A semi-structured proforma was used to collect sociodemographic characteristics and family related variables. Edinburgh postnatal depression scale (EPDS) was used to screen for perinatal depression. RESULTS: A total of 564 perinatal women were recruited into the study. The estimated prevalence of PND was 23.9 % (95 % CI: 20.6,27.6). Multivariate analysis showed perinatal depression was associated with physical illness in the mother, previous history of abortion, poor financial status and ill-treatment by in-laws. CONCLUSION: Prevalence of perinatal depression among women is high in rural settings of North India. A multitude of factors ranging from physical, obstetric, economic and family related confer a high risk for PND. Comprehensive interventions are needed to address these risk factors of perinatal depression.

Early Cognitive Training Rescues Remote Spatial Memory but Reduces Cognitive Flexibility in Alzheimer's Disease Mice.

BACKGROUND: Spatial memory dysfunction has been demonstrated in mouse models of Alzheimer's disease (AD) which is consistent with the clinical finding that the early signature of AD includes difficulties in the formation and/or storage of a memory. A stored memory-a long term memory-can be modulated via process called as memory retrieval that can either lead toward memory reconsolidation or even memory extinction. OBJECTIVE: We aim to shed light on the fate of the spatial memory during memory reactivation and memory extinction using a water maze task. METHODS: In Set-up I, we trained 3-month-old mice (wild-type mice and mice with cerebral ß-amyloidosis) and assessed the fate of remote memory after four months of retention interval (RI). In Set-up II, we performed an early-extensive training at 2 months of age, retrained the same mice at 3 months of age, introduced four months of RI, and finally assessed remote spatial memory at 7 months of age. RESULTS: We find in ß-amyloidosis mice that memory reactivation problems were detectable at 7 months of age and were alleviated by cognitive overtraining. Similarly, forgetting of remote spatial memory was also minimized by cognitive overtraining. Finally, we show that the cognitive training facilitates the recovery of the reactivated spatial memory while reducing the ability to form new spatial memory in AD mice. CONCLUSION: This result may explain the rationality behind the cognitive reserve observed in AD patients and elderly with severe ß-amyloidosis not corresponding to the actual low dementia symptoms.

Detection and Prediction of Mild Cognitive Impairment in Alzheimer's Disease Mice.

BACKGROUND: The recent failure of clinical trials to treat Alzheimer's disease (AD) indicates that the current approach of modifying disease is either wrong or is too late to be efficient. Mild cognitive impairment (MCI) denotes the phase between the preclinical phase and clinical overt dementia. AD mouse models that overexpress human amyloid-ß (Aß) are used to study disease pathogenesis and to conduct drug development/testing. However, there is no direct correlation between the Aß deposition, the age of onset, and the severity of cognitive dysfunction. OBJECTIVE: To detect and predict MCI when Aß plaques start to appear in the hippocampus of an AD mouse. METHODS: We trained wild-type and AD mice in a Morris water maze (WM) task with different inter-trial intervals (ITI) at 3 months of age and assessed their WM performance. Additionally, we used a classification algorithm to predict the genotype (APPtg versus wild-type) of an individual mouse from their respective WM data. RESULTS: MCI can be empirically detected using a short-ITI protocol. We show that the ITI modulates the spatial learning of AD mice without affecting the formation of spatial memory. Finally, a simple classification algorithm such as logistic regression on WM data can give an accurate prediction of the cognitive dysfunction of a specific mouse. CONCLUSION: MCI can be detected as well as predicted simultaneously with the onset of Aß deposition in the hippocampus in AD mouse model. The mild cognitive impairment prediction can be used for assessing the efficacy of a treatment.