Cysticercal encephalitis with disseminated cutaneous cysticercosis: A case report

Cysticercal encephalitis is a severe and frequently fatal neurological disorder seen in endemic regions. We report a young male whopresented with refractory status epilepticus along with numerous subcutaneous swellings over the body. His neuroimaging revealedthe classic “starry sky” appearance, suggesting a diagnosis of cysticercal encephalitis along with disseminated cutaneous cysticercosis.He was managed with supportive care, antiepileptics and steroids. In endemic regions, neurocysticercosis should be consideredas a differential diagnosis in children presenting as acute encephalitis syndrome. A careful physical examination along with earlyneuroimaging will help in establishing the diagnosis promptly

Two Level Disambiguation Model for Query Translation

Selection of the most suitable translation among all translation candidates returned by bilingual dictionary has always been quiet challenging task for any cross language query translation. Researchers have frequently tried to use word co-occurrence statistics to determine the most probable translation for user query. Algorithms using such statistics have certain shortcomings, which are focused in this paper. We propose a novel method for ambiguity resolution, named ‘two level disambiguation model’. At first level disambiguation, the model properly weighs the importance of translation alternatives of query terms obtained from the dictionary. The importance factor measures the probability of a translation candidate of being selected as the final translation of a query term. This removes the problem of taking binary decision for translation candidates. At second level disambiguation, the model targets the user query as a single concept and deduces the translation of all query terms simultaneously, taking into account the weights of translation alternatives also. This is contrary to previous researches which select translation for each word in source language query independently. The experimental result with English-Hindi cross language information retrieval shows that the proposed two level disambiguation model achieved 79.53% and 83.50% of monolingual translation and 21.11% and 17.36% improvement compared to greedy disambiguation strategies in terms of MAP for short and long queries respectively

Computational analysis of a 9D model for a small DRG neuron

Small dorsal root ganglion (DRG) neurons are primary nociceptors which are responsible for sensing pain. Elucidation of their dynamics is essential for understanding and controlling pain. To this end, we present a numerical bifurcation analysis of a small DRG neuron model in this paper. The model is of Hodgkin-Huxley type and has 9 state variables. It consists of a Na$\mathrm{_v}$1.7 and a Na$\mathrm{_v}$1.8 sodium channel, a leak channel, a delayed rectifier potassium and an A-type transient potassium channel. The dynamics of this model strongly depends on the maximal conductances of the voltage-gated ion channels and the external current, which can be adjusted experimentally. We show that the neuron dynamics are most sensitive to the Na$\mathrm{_v}$1.8 channel maximal conductance ($\bar{g}_{1.8}$). Numerical bifurcation analysis shows that depending on $\bar{g}_{1.8}$ and the external current, different parameter regions can be identified with stable steady states, periodic firing of action potentials, mixed-mode oscillations (MMOs), and bistability between stable steady states and stable periodic firing of action potentials. We illustrate and discuss the transitions between these different regimes. We further analyze the behavior of MMOs. Within this region, bifurcation analysis shows a sequence of isolated periodic solution branches with one large action potential and a number of small amplitude peaks per period. A closer inspection reveals more complex concatenated MMOs in between these periodic MMOs branches, forming Farey sequences. Lastly, we also find small solution windows with aperiodic oscillations, which seem to be chaotic. The dynamical patterns found here as a function of different parameters contain information of translational importance as their relation to pain sensation and its intensity is a potential source of insight into controlling pain

Study of psycho-social impairment in patients presenting with age related macular degeneration in a tertiary eye care hospital

Background: Age Related Macular Degeneration (ARMD) is an eye condition affecting old age people causing severe vision loss. This study was carried out to assess the psycho-social impairment in the ARMD patients and compare it with the normal eye patients.Methods: A Two study groups were made: 1. ARMD patients. 2. Control group patients. Patients of both the groups were made to fill “The validated Gujarati version of: General Health Quality Questionnaire-28 (GHQ 28)”. Self-scoring was done according to 0-1-2-3 lower to higher disability respectively.Results: Prevalence GHQ Mean score of ARMD patients was 34.27 and that of normal eye patients was 24.66. 80.85% of ARMD patients and 26.73% of normal eye patients were psychosocially impaired.Conclusion: ARMD patients are psychosocially more impaired as compared to control group patients (p value <0.001, highly significant).

Stability and dynamics of a spectral graph model of brain oscillations

AbstractWe explore the stability and dynamic properties of a hierarchical, linearized, and analytic spectral graph model for neural oscillations that integrates the structural wiring of the brain. Previously, we have shown that this model can accurately capture the frequency spectra and the spatial patterns of the alpha and beta frequency bands obtained from magnetoencephalography recordings without regionally varying parameters. Here, we show that this macroscopic model based on long-range excitatory connections exhibits dynamic oscillations with a frequency in the alpha band even without any oscillations implemented at the mesoscopic level. We show that depending on the parameters, the model can exhibit combinations of damped oscillations, limit cycles, or unstable oscillations. We determined bounds on model parameters that ensure stability of the oscillations simulated by the model. Finally, we estimated time-varying model parameters to capture the temporal fluctuations in magnetoencephalography activity. We show that a dynamic spectral graph modeling framework with a parsimonious set of biophysically interpretable model parameters can thereby be employed to capture oscillatory fluctuations observed in electrophysiological data in various brain states and diseases

Iron Oxide-Based Magneto-Optical Nanocomposites for In Vivo Biomedical Applications

Iron oxide nanoparticles (IONPs) have played a pivotal role in the development of nanomedicine owing to their versatile functions at the nanoscale, which facilitates targeted delivery, high contrast imaging, and on-demand therapy. Some biomedical inadequacies of IONPs on their own, such as the poor resolution of IONP-based Magnetic Resonance Imaging (MRI), can be overcome by co-incorporating optical probes onto them, which can be either molecule- or nanoparticulate-based. Optical probe incorporated IONPs, together with two prominent non-ionizing radiation sources (i.e., magnetic field and light), enable a myriad of biomedical applications from early detection to targeted treatment of various diseases. In this context, many research articles are in the public domain on magneto-optical nanoparticles; discussed in detail are fabrication strategies for their application in the biomedical field; however, lacking is a comprehensive review on real-life applications in vivo, their toxicity, and the prospect of bench-to-bedside clinical studies. Therefore, in this review, we focused on selecting such important nanocomposites where IONPs become the magnetic component, conjugated with various types of optical probes; we clearly classified them into class 1 to class 6 categories and present only in vivo studies. In addition, we briefly discuss the potential toxicity of such nanocomposites and their respective challenges for clinical translations

Diversity and status of migratory and resident wetland birds in Haridwar, Uttarakhand, India

Migration is the seasonal habitual movement, exhibited by many avian species along a flyway from breeding to wintering grounds and vice versa all over the world. Migratory birds are very sensitive to even small changes in water level which may be affected by flood or drought on their breeding and wintering grounds. High rains during monsoon season can cause flood conditions in the lower hills and Gangetic plains including Haridwar district. In our study, conducted during last ten years (2009-2018), we covered Bheemgoda Barrage and Missarpur Ganga Ghat of Haridwar, Uttarakhand, where 46 species of Migratory (M) and Resident Migratory (RM) wetland birds were observed. Bird survey indicated that there was a significant increase (p = 0.064, t-test) in the population of certain species such as Bhraminy Shelduck (67%), Black Headed Gull (31%), Gadwall (7%), Northern Pintail (59%), Red Crested Pochard (10%) and Tufted Pochard (47%) in Missarpur Ganga Ghat as compared to Bheemgoda Barrage (based on the average abundance of the species observed during study period). It may be pointed out that after flood and loss of vegetated island, there was significant decrease (p= 0.023, t-test) in the population of species such as Black necked stork (76%), Great crested grebe (56), Pallas gull (47%) at Bheemgoda barrage, while some species such as Bar headed goose, Common pochard did not arrive in Bheemgoda barrage after the flood. The study would help to understand the effect of climatic change on water birds species distribution in natural and man-made wetlands

A Metabolomics Approach for Early Prediction of Vincristine-Induced Peripheral Neuropathy

Vincristine is a core chemotherapeutic drug administered to pediatric acute lymphoblastic leukemia patients. Despite its efficacy in treating leukemia, it can lead to severe peripheral neuropathy in a subgroup of the patients. Peripheral neuropathy is a debilitating and painful side-effect that can severely impact an individual’s quality of life. Currently, there are no established predictors of peripheral neuropathy incidence during the early stage of chemotherapeutic treatment. As a result, patients who are not susceptible to peripheral neuropathy may receive sub-therapeutic treatment due to an empirical upper cap on the dose, while others may experience severe neuropathy at the same dose. Contrary to previous genomics based approaches, we employed a metabolomics approach to identify small sets of metabolites that can be used to predict a patient’s susceptibility to peripheral neuropathy at different time points during the treatment. Using those identified metabolites, we developed a novel strategy to predict peripheral neuropathy and subsequently adjust the vincristine dose accordingly. In accordance with this novel strategy, we created a free user-friendly tool, VIPNp, for physicians to easily implement our prediction strategy. Our results showed that focusing on metabolites, which encompasses both genotypic and phenotypic variations, can enable early prediction of peripheral neuropathy in pediatric leukemia patients

Phylogeography of mtDNA haplogroup R7 in the Indian peninsula.

BACKGROUND: Human genetic diversity observed in Indian subcontinent is second only to that of Africa. This implies an early settlement and demographic growth soon after the first 'Out-of-Africa' dispersal of anatomically modern humans in Late Pleistocene. In contrast to this perspective, linguistic diversity in India has been thought to derive from more recent population movements and episodes of contact. With the exception of Dravidian, which origin and relatedness to other language phyla is obscure, all the language families in India can be linked to language families spoken in different regions of Eurasia. Mitochondrial DNA and Y chromosome evidence has supported largely local evolution of the genetic lineages of the majority of Dravidian and Indo-European speaking populations, but there is no consensus yet on the question of whether the Munda (Austro-Asiatic) speaking populations originated in India or derive from a relatively recent migration from further East. RESULTS: Here, we report the analysis of 35 novel complete mtDNA sequences from India which refine the structure of Indian-specific varieties of haplogroup R. Detailed analysis of haplogroup R7, coupled with a survey of approximately 12,000 mtDNAs from caste and tribal groups over the entire Indian subcontinent, reveals that one of its more recently derived branches (R7a1), is particularly frequent among Munda-speaking tribal groups. This branch is nested within diverse R7 lineages found among Dravidian and Indo-European speakers of India. We have inferred from this that a subset of Munda-speaking groups have acquired R7 relatively recently. Furthermore, we find that the distribution of R7a1 within the Munda-speakers is largely restricted to one of the sub-branches (Kherwari) of northern Munda languages. This evidence does not support the hypothesis that the Austro-Asiatic speakers are the primary source of the R7 variation. Statistical analyses suggest a significant correlation between genetic variation and geography, rather than between genes and languages. CONCLUSION: Our high-resolution phylogeographic study, involving diverse linguistic groups in India, suggests that the high frequency of mtDNA haplogroup R7 among Munda speaking populations of India can be explained best by gene flow from linguistically different populations of Indian subcontinent. The conclusion is based on the observation that among Indo-Europeans, and particularly in Dravidians, the haplogroup is, despite its lower frequency, phylogenetically more divergent, while among the Munda speakers only one sub-clade of R7, i.e. R7a1, can be observed. It is noteworthy that though R7 is autochthonous to India, and arises from the root of hg R, its distribution and phylogeography in India is not uniform. This suggests the more ancient establishment of an autochthonous matrilineal genetic structure, and that isolation in the Pleistocene, lineage loss through drift, and endogamy of prehistoric and historic groups have greatly inhibited genetic homogenization and geographical uniformity.RIGHTS : This article is licensed under the BioMed Central licence at http://www.biomedcentral.com/about/license which is similar to the 'Creative Commons Attribution Licence'. In brief you may : copy, distribute, and display the work; make derivative works; or make commercial use of the work - under the following conditions: the original author must be given credit; for any reuse or distribution, it must be made clear to others what the license terms of this work are

Towards Understanding Neuropathy from Cancer Chemotherapy and Pathophysiology of Pain Sensation: an Engineering Approach

This thesis addresses chemotherapy-induced peripheral neuropathy (CIPN)- a form of pain sensation and a prevalent dose-limiting side-effect of several chemotherapy agents such as vincristine, paclitaxel, and oxaliplatin. These agents are used for treating various cancers such as leukemia, brain tumor, lung cancer. Peripheral neuropathy is a numbing, tingling, and burning sensation felt in the palms and feet, which occurs due to damage to neurons (nerve cells). Prolonged CIPN can impact the quality of life of cancer patients. Occasionally, severe CIPN can result in termination of chemotherapy treatment altogether. Currently, there are no established strategies for treating CIPN due to a lack of understanding of its mechanisms. Moreover, different patients react differently to the same treatment; a subgroup of patient population may never experience CIPN, while another may experience severe CIPN for the same dose. In addition, there are no established strategies for predicting CIPN either. This thesis addresses both prediction and mechanisms of CIPN. The following paragraphs reflect the organization of this thesis. Each paragraph introduces a research problem, the approaches taken to investigate it, and states the key results. First, a metabolomics-based approach was used to investigate CIPN prediction. Blood samples of pediatric leukemic cancer patients who underwent treatment with a chemotherapy agent - vincristine were provided. These blood samples were analyzed at different treatment time points using mass spectrometry to obtain the metabolite profiles. Machine learning was then employed to identify specific metabolites that can predict overall susceptibility to peripheral neuropathy in those patients at specific treatment time points. Subsequently, selected metabolites were used to train machine learning models to predict neuropathy susceptibility. Finally, the models were deployed into an open-source interactive tool- VIPNp- that can be used by researchers to predict CIPN in new pediatric leukemic cancer patients. Second, the focus was shifted to the pathophysiology of pain and the pain-sensing neuron; specifically: (i) investigating pain sensation mutations and the dynamics of the pain-sensing neuron, and (ii) exploring chemotherapy-induced peripheral neuropathy mechanisms While pain is a common experience, genetic mutations in individuals can alter their experience of pain, if any at all (certain mutations yield individuals insensitive to pain). Despite its ubiquity, we do not have a complete understanding of the onset and/or mechanisms of pain sensation. Pain sensation can be broadly classified into three types: (i) nociceptive, (ii) neuropathic, and (iii) inflammatory. Nociceptive pain arises due to a noxious external stimulus (e.g., upon touching a hot object). Neuropathic pain (which is felt as a side-effect of the aforementioned chemotherapy agents) is the numbing and tingling sensation due to nerve damage. Inflammatory pain occurs due to damage to internal tissues. Pain in any form can be characterized in terms of electrical signaling by the pain-sensing neuron. Signal transmission regarding pain occurs through generation of an electrical signal called the action potential- a peak in neuron membrane potential. Excessive firing of action potentials by a pain-sensing neuron indicates pain of a specific form and intensity. In order to investigate this electrical signaling, a mathematical modeling approach was employed. The neuron membrane was assumed to be an electrical circuit and the potential across the membrane was modeled in terms of the sodium and potassium ions flowing across it via voltage-gated sodium and potassium channels, respectively