Childhood disintegrative disorder misdiagnosed as childhood-onset schizophrenia

Childhood disintegrative disorder (CDD) is a rare pervasive developmental disorder, which is often misdiagnosed as schizophrenia, probably due to the resultant severe social impairment and withdrawn behaviour with stereotypys that could be mistaken for psychosis. We report a case of CDD that was misdiagnosed by a psychiatrist as childhood-onset schizophrenia and treated with high doses of antipsychotics. The patient did not show any improvement. This highlights ethical issues that arise from treatment modalities, with polypharmacy being the biggest culprit, and also points to the need to continue medical education at the level of primary health services and among practising rural doctors where tertiary centres with child guidance facilities and a multidisciplinary team are not available

Securing Public Places with PCA Based Recognition of Criminal Faces Detected from Surveillance CCTV Footage

This paper aims in ensuring the safety of common people at public places by using the existing CCTV systems which are deployed for the surveillance and to determine the security of that place, by identifying the suspicious faces that are captured and notifying the officials. The existing video surveillance systems capture data through CCTVs and store it in their database. After an unpredicted incident already taken place, these databases are used to recognize the culprit. Instead of this, the proposed system keeps a track of the live videos and exacts out frames from it after a fixed interval of time. These frames are then used to fetch faces and compare them with the criminal faces which are already stored in a suspicious faces database, using the feature extraction technique. If the comparison is successful, an alarm is generated which gives an alert about the presence of a criminal at that place. Various face detection algorithms and recognition techniques are used to identify the suspicious face in the crowd and enhances the safety of the public places

Modern Views of Machine Learning for Precision Psychiatry

In light of the NIMH's Research Domain Criteria (RDoC), the advent of functional neuroimaging, novel technologies and methods provide new opportunities to develop precise and personalized prognosis and diagnosis of mental disorders. Machine learning (ML) and artificial intelligence (AI) technologies are playing an increasingly critical role in the new era of precision psychiatry. Combining ML/AI with neuromodulation technologies can potentially provide explainable solutions in clinical practice and effective therapeutic treatment. Advanced wearable and mobile technologies also call for the new role of ML/AI for digital phenotyping in mobile mental health. In this review, we provide a comprehensive review of the ML methodologies and applications by combining neuroimaging, neuromodulation, and advanced mobile technologies in psychiatry practice. Additionally, we review the role of ML in molecular phenotyping and cross-species biomarker identification in precision psychiatry. We further discuss explainable AI (XAI) and causality testing in a closed-human-in-the-loop manner, and highlight the ML potential in multimedia information extraction and multimodal data fusion. Finally, we discuss conceptual and practical challenges in precision psychiatry and highlight ML opportunities in future research

Needle(s) in the Haystack – Synchronous Multifocal Tumor Induced Osteomalacia

This is the author accepted manuscript. The final version is available from Endocrine Society via http://dx.doi.org/10.1210/jc.2015-3854MG is supported by the NIHR Cambridge Biomedical Research Centre

Sleep oscillation-specific associations with Alzheimer’s disease CSF biomarkers : novel roles for sleep spindles and tau

Background: Based on associations between sleep spindles, cognition, and sleep-dependent memory processing, here we evaluated potential relationships between levels of CSF Aβ42, P-tau, and T-tau with sleep spindle density and other biophysical properties of sleep spindles in a sample of cognitively normal elderly individuals. Methods: One-night in-lab nocturnal polysomnography (NPSG) and morning to early afternoon CSF collection were performed to measure CSF Aβ42, P-tau and T-tau. Seven days of actigraphy were collected to assess habitual total sleep time. Results: Spindle density during NREM stage 2 (N2) sleep was negatively correlated with CSF Aβ42, P-tau and T-tau. From the three, CSF T-tau was the most significantly associated with spindle density, after adjusting for age, sex and ApoE4. Spindle duration, count and fast spindle density were also negatively correlated with T-tau levels. Sleep duration and other measures of sleep quality were not correlated with spindle characteristics and did not modify the associations between sleep spindle characteristics and the CSF biomarkers of AD. Conclusions: Reduced spindles during N2 sleep may represent an early dysfunction related to tau, possibly reflecting axonal damage or altered neuronal tau secretion, rendering it a potentially novel biomarker for early neuronal dysfunction. Given their putative role in memory consolidation and neuroplasticity, sleep spindles may represent a mechanism by which tau impairs memory consolidation, as well as a possible target for therapeutic interventions in cognitive decline

Cortical Pain Processing in the Rat Anterior Cingulate Cortex and Primary Somatosensory Cortex

Pain is a complex multidimensional experience encompassing sensory-discriminative, affective-motivational and cognitive-emotional components mediated by different neural mechanisms. Investigations of neurophysiological signals from simultaneous recordings of two or more cortical circuits may reveal important circuit mechanisms on cortical pain processing. The anterior cingulate cortex (ACC) and primary somatosensory cortex (S1) represent two most important cortical circuits related to sensory and affective processing of pain. Here, we recorded in vivo extracellular activity of the ACC and S1 simultaneously from male adult Sprague-Dale rats (n = 5), while repetitive noxious laser stimulations were delivered to animalÕs hindpaw during pain experiments. We identified spontaneous pain-like events based on stereotyped pain behaviors in rats. We further conducted systematic analyses of spike and local field potential (LFP) recordings from both ACC and S1 during evoked and spontaneous pain episodes. From LFP recordings, we found stronger phase-amplitude coupling (theta phase vs. gamma amplitude) in the S1 than the ACC (n = 10 sessions), in both evoked (p = 0.058) and spontaneous pain-like behaviors (p = 0.017, paired signed rank test). In addition, pain-modulated ACC and S1 neuronal firing correlated with the amplitude of stimulus-induced event-related potentials (ERPs) during evoked pain episodes. We further designed statistical and machine learning methods to detect pain signals by integrating ACC and S1 ensemble spikes and LFPs. Together, these results reveal differential coding roles between the ACC and S1 in cortical pain processing, as well as point to distinct neural mechanisms between evoked and putative spontaneous pain at both LFP and cellular levels

Study of Damping Characteristics in Fiber Reinforced Composite Beams

Vibration has adverse effects in many applications ranging from small components used in electronics to huge building constructions and bridges. In mechanical systems, it affects machine tool structure as well as decreases accuracy, surface finish and increases noise. Hence, it becomes necessary to avoid vibrations by increasing damping of the structures. Damping is resistance to vibrations. One such way of increasing damping of the structure is by using composites. Composites are nowadays replacing conventional materials owing to their better damping and mechanical properties. For replacement of conventional materials with composites considering vibrational parameters, it is necessary to study damping properties of composites. The current research deals with estimating the damping properties of composites. Glass fiber reinforced epoxy (GFE) and Glass fiber reinforced polyester (GFP) were initially used as raw materials to study damping in composites. It was found that GFE possesses more damping compared to GFP and hence used for further study. Processing of GFE was done using hand-lay technique. Various design parameters such as numbers of glass fiber layers and orientations of fibers were varied while manufacturing GFE composites. Further, experimental parameters such as loading frequency and cantilever length were varied during damping tests. It was found that as the number of layers increases damping of GFE increases. Also +45-(-45) fiber orientation gives better damping compared to 0-90 orientation

Sparsity-Driven Methods for Tracing of Tubular Structures in 3-D Confocal and SD-OCT Images: Application to Reconstruction of Astrocyte Arbors and Blood Vessels

Tubular structures with complex morphologies occur frequently in biomedical research, often at a scale which necessitates their large-scale comprehensive and computational analysis. In this thesis, we focus on two such structures, astrocytes and blood vessels. The majority of the glial cells present in the brain are astrocytes which play critical roles in brain development, physiology and pathology. Astrocytes can be imaged as three-dimensional (3-D) objects in the brain tissue using fluorescence confocal microscopy. However, their vast number and the complexity of the patterns and mechanisms associated with their dynamics hinder an objective quantitative study. Therefore it is critical to develop automated computational methods facilitating comprehensive analysis of the astroglial networks. Congenital cardiovascular defects are one of the most common diseases responsible for infant mortality. These defects are closely associated with development of embryonic yolk sac vasculature. Recently developed imaging techniques such as optical coherence tomography (OCT) allow non-invasive imaging of embryonic structures including blood vessels. However, the reconstruction of blood vessels as such is a non-trivial task, mainly due to low signal-to-noise ratio (SNR). Therefore, it is critical to develop automated methods for longitudinal quantification of embryonic vascular networks as imaged using OCT. Understanding the commonalities between these two diverse problems, we propose to investigate the use of sparse representations for reconstruction of tubular structures from biological data. For astrocyte quantification, we propose a novel two-step approach. In the first step, we use a machine-learning method for detecting astrocyte root points while the second step is responsible for efficient tracing of astrocyte arbors. For OCT blood vessel reconstruction, we propose the use of anomaly detection from hyper-spectral imaging to handle the low SNR problem, followed by a smooth reconstruction using a parametric dictionary. Finally, we propose an integrated software framework for tracing, visualization, editing and feature-computation. To the best of our knowledge, this is the first reported comprehensive framework for reconstruction of astrocyte arbors from confocal data. The proposed approach includes a robust method for astrocyte nuclei detection which has not been effectively addressed by the prior work. Additionally, we propose the parallel arbor reconstruction algorithm which has been specifically designed to address the challenges involved in tracing astrocyte arbors. With regards to OCT blood vessel reconstruction, the application of anomaly detection improves upon the reconstruction quality compared to the prior methods such as speckle variance. Additionally, this work also introduces the application of sparsity-based methods for analysis of tubular biological objects. Results demonstrate that the proposed methods can facilitate efficient large-scale automated analysis of these important biological structures. Validation of the results provides convincing evidence to substantiate this claim. To this end, the error rate for the proposed reconstruction method was found to be 3.2%, compared to the fast-marching method (FMM) which had an error rate of 9%. With regards to OCT vessel reconstruction, the proposed method resulted in reconstructions with overall higher vesselness (0.8±0.09) compared to the standard speckle variance (SV) method which resulted in a vesselness of (0.6±0.2). The proposed methods, being integrated and distributed through FARSIGHT, an open source image analysis toolkit, can potentially have major contributions in two broad areas. Firstly, in advancing the state of the art understanding of the role of astrocytes in brain development, physiology and pathology and secondly, in advancing the longitudinal image-based quantification of embryonic yolk sac vascular development.Electrical and Computer Engineering, Department o

Diversity of avifauna of Nigade in Raigad, Konkan, India A casefor conservation

Abstract: India is rich in Biodiversity with two global Hotspots. The avifauna of India includes around 1301 species, Present study was carried out for two years from June 2011-to June 2013. Visits were planned periodically covering all the seasons of the year. The visits were made during early mornings and late evening, since activity of birds is at its peak during this time. Total of 131 birds were observed which included residents, winter visitors and also summer visitors. Few rare and threatened species were also occasionally spotted. This work, will not only establish a base line data on bird diversity of Nigade but also assess probable and likely impact of expansion plans of administration for the highway and the rail route. As about 90% of the bird species observed in the region were residents, we strongly recommend the need for conservation of such sites

Illustrative checklist of opisthobranchs from selected beaches of Mumbai

1024-1028Opisthobranchs are marine slugs belonging to phylum Mollusca. Till date, Mumbai is least studied for opisthobranch biodiversity with very few official reports on opisthobranch fauna. The present study documents a list of opisthobranchs from Mumbai. The opisthobranchs were collected from selected beaches along the Mumbai coast and identified using standard guidelines. Eight species of opisthobranchs belonging to three families were identified. All of these are new records to Mumbai with five species being new records to India. This study is a preliminary data for further investigations, monitoring and conservation of opisthobranch fauna