Early-responsive molecular signatures associated with halophytic adaptation in Sesuvium portulacastrum (L.).

Sesuvium portulacastrum (L.) is a halophyte, adapted to grow naturally under saline environments. The ability to use Na and K interchangeably indicated its facultative halophyte nature. No significant growth reduction occurs in seedlings up to 250 mM NaCl, except for curling of the youngest leaf. Within 8 h of salt treatment, seedlings accumulate proline, glycine betaine and other amino acids in both root and shoot. Despite a continued increase of tissue Na content, the number of differentially expressed genes (DEGs) decreases between 8 and 24 h of salt exposure, indicating transcriptional restoration after the initial osmotic challenge. At 8 h, upregulated genes mainly encode transporters and transcription factors, while genes in growth-related pathways such as photosynthesis and ribosome-associated biogenesis are suppressed. Overexpression of SpRAB18 (an ABA-responsive dehydrin), one of the most strongly induced DEGs, in soybean was found to increase biomass in control conditions and the growth benefit was maintained when plants were grown in 100 mM NaCl, indicating conservation of function in halophyte and glycophyte. An open-access transcriptome database "SesuviumKB" (https://cb.imsc.res.in/sesuviumkb/) was developed to involve the scientific community in wide-scale functional studies of S. portulacastrum genes, that could pave the way to engineer salt tolerance in crops.

Impact of Climate Change on Altered Fruit Quality with Organoleptic, Health Benefit, and Nutritional Attributes.

As a consequence of global climate change, acute water deficit conditions, soil salinity, and high temperature have been on the rise in their magnitude and frequency, which have been found to impact plant growth and development negatively. However, recent evidence suggests that many fruit plants that face moderate abiotic stresses can result in beneficial effects on the postharvest storage characters of the fruits. Salinity, drought, and high temperature conditions stimulate the synthesis of abscisic acid (ABA), and secondary metabolites, which are vital for fruit quality. The secondary metabolites like phenolic acids and anthocyanins that accumulate under abiotic stress conditions have antioxidant activity, and therefore, such fruits have health benefits too. It has been noticed that fruits accumulate more sugar and anthocyanins owing to upregulation of phenylpropanoid pathway enzymes. The novel information that has been generated thus far indicates that the growth environment during fruit development influences the quality components of the fruits. But the quality depends on the trade-offs between productivity, plant defense, and the frequency, duration, and intensity of stress. In this review, we capture the current knowledge of the irrigation practices for optimizing fruit production in arid and semiarid regions and enhancement in the quality of fruit with the application of exogenous ABA and identify gaps that exist in our understanding of fruit quality under abiotic stress conditions.

Incidental Presentation of Dandy Walker Variant in 66 Year Male Patient.

Dandy-Walker variant consists of vermian hypoplasia and cystic dilatation of the fourth ventricle, without enlargement of the posterior fossa is a distinctive entity believed to represent a mild subtype of Dandy-Walker complex. We report a case of 66 year male presented with right sided hemiparesis due to ischemic stroke whose imaging showed incidental findings Dandy walker variant. This Incidental Dandy Walker malformation finding in adult is rare with only a few cases reported till date.

Halotolerant Rhizobacteria Promote Growth and Enhance Salinity Tolerance in Peanut.

Use of Plant growth promoting rhizobacteria (PGPR) is a promising strategy to improve the crop production under optimal or sub-optimal conditions. In the present study, five diazotrophic salt tolerant bacteria were isolated from the roots of a halophyte, Arthrocnemum indicum. The isolates were partially characterized in vitro for plant growth promoting traits and evaluated for their potential to promote growth and enhanced salt tolerance in peanut. The 16S rRNA gene sequence homology indicated that these bacterial isolates belong to the genera, Klebsiella, Pseudomonas, Agrobacterium, and Ochrobactrum. All isolates were nifH positive and able to produce indole -3-acetic acid (ranging from 11.5 to 19.1 µg ml-1). The isolates showed phosphate solubilisation activity (ranging from 1.4 to 55.6 µg phosphate /mg dry weight), 1-aminocyclopropane-1-carboxylate deaminase activity (0.1 to 0.31 µmol α-kB/µg protein/h) and were capable of reducing acetylene in acetylene reduction assay (ranging from 0.95 to 1.8 µmol C2H4 mg protein/h). These isolates successfully colonized the peanut roots and were capable of promoting the growth under non-stress condition. A significant increase in total nitrogen (N) content (up to 76%) was observed over the non-inoculated control. All isolates showed tolerance to NaCl ranging from 4 to 8% in nutrient broth medium. Under salt stress, inoculated peanut seedlings maintained ion homeostasis, accumulated less reactive oxygen species (ROS) and showed enhanced growth compared to non-inoculated seedlings. Overall, the present study has characterized several potential bacterial strains that showed an enhanced growth promotion effect on peanut under control as well as saline conditions. The results show the possibility to reduce chemical fertilizer inputs and may promote the use of bio-inoculants.

Orthogonal moments for determining correspondence between vessel bifurcations for retinal image registration.

Retinal image registration is a necessary step in diagnosis and monitoring of Diabetes Retinopathy (DR), which is one of the leading causes of blindness. Long term diabetes affects the retinal blood vessels and capillaries eventually causing blindness. This progressive damage to retina and subsequent blindness can be prevented by periodic retinal screening. The extent of damage caused by DR can be assessed by comparing retinal images captured during periodic retinal screenings. During image acquisition at the time of periodic screenings translation, rotation and scale (TRS) are introduced in the retinal images. Therefore retinal image registration is an essential step in automated system for screening, diagnosis, treatment and evaluation of DR. This paper presents an algorithm for registration of retinal images using orthogonal moment invariants as features for determining the correspondence between the dominant points (vessel bifurcations) in the reference and test retinal images. As orthogonal moments are invariant to TRS; moment invariants features around a vessel bifurcation are unaltered due to TRS and can be used to determine the correspondence between reference and test retinal images. The vessel bifurcation points are located in segmented, thinned (mono pixel vessel width) retinal images and labeled in corresponding grayscale retinal images. The correspondence between vessel bifurcations in reference and test retinal image is established based on moment invariants features. Further the TRS in test retinal image with respect to reference retinal image is estimated using similarity transformation. The test retinal image is aligned with reference retinal image using the estimated registration parameters. The accuracy of registration is evaluated in terms of mean error and standard deviation of the labeled vessel bifurcation points in the aligned images. The experimentation is carried out on DRIVE database, STARE database, VARIA database and database provided by local government hospital in Pune, India. The experimental results exhibit effectiveness of the proposed algorithm for registration of retinal images.

Modeling the impact of common noise inputs on the network activity of retinal ganglion cells.

Synchronized spontaneous firing among retinal ganglion cells (RGCs), on timescales faster than visual responses, has been reported in many studies. Two candidate mechanisms of synchronized firing include direct coupling and shared noisy inputs. In neighboring parasol cells of primate retina, which exhibit rapid synchronized firing that has been studied extensively, recent experimental work indicates that direct electrical or synaptic coupling is weak, but shared synaptic input in the absence of modulated stimuli is strong. However, previous modeling efforts have not accounted for this aspect of firing in the parasol cell population. Here we develop a new model that incorporates the effects of common noise, and apply it to analyze the light responses and synchronized firing of a large, densely-sampled network of over 250 simultaneously recorded parasol cells. We use a generalized linear model in which the spike rate in each cell is determined by the linear combination of the spatio-temporally filtered visual input, the temporally filtered prior spikes of that cell, and unobserved sources representing common noise. The model accurately captures the statistical structure of the spike trains and the encoding of the visual stimulus, without the direct coupling assumption present in previous modeling work. Finally, we examined the problem of decoding the visual stimulus from the spike train given the estimated parameters. The common-noise model produces Bayesian decoding performance as accurate as that of a model with direct coupling, but with significantly more robustness to spike timing perturbations.

Chronux: a platform for analyzing neural signals.

Chronux is an open-source software package developed for the analysis of neural data. The current version of Chronux includes software for signal processing of neural time-series data including several specialized mini-packages for spike-sorting, local regression, audio segmentation, and other data-analysis tasks typically encountered by a neuroscientist. Chronux is freely available along with user tutorials, sample data, and extensive documentation from http://chronux.org/.

Attention enhances the retrieval and stability of visuospatial and olfactory representations in the dorsal hippocampus.

A key question in the analysis of hippocampal memory relates to how attention modulates the encoding and long-term retrieval of spatial and nonspatial representations in this region. To address this question, we recorded from single cells over a period of 5 days in the CA1 region of the dorsal hippocampus while mice acquired one of two goal-oriented tasks. These tasks required the animals to find a hidden food reward by attending to either the visuospatial environment or a particular odor presented in shifting spatial locations. Attention to the visuospatial environment increased the stability of visuospatial representations and phase locking to gamma oscillations--a form of neuronal synchronization thought to underlie the attentional mechanism necessary for processing task-relevant information. Attention to a spatially shifting olfactory cue compromised the stability of place fields and increased the stability of reward-associated odor representations, which were most consistently retrieved during periods of sniffing and digging when animals were restricted to the cup locations. Together, these results suggest that attention selectively modulates the encoding and retrieval of hippocampal representations by enhancing physiological responses to task-relevant information.

Neural decoding of hand motion using a linear state-space model with hidden states.

The Kalman filter has been proposed as a model to decode neural activity measured from the motor cortex in order to obtain real-time estimates of hand motion in behavioral neurophysiological experiments. However, currently used linear state-space models underlying the Kalman filter do not take into account other behavioral states such as muscular activity or the subject's level of attention, which are often unobservable during experiments but may play important roles in characterizing neural controlled hand movement. To address this issue, we depict these unknown states as one multidimensional hidden state in the linear state-space framework. This new model assumes that the observed neural firing rate is directly related to this hidden state. The dynamics of the hand state are also allowed to impact the dynamics of the hidden state, and vice versa. The parameters in the model can be identified by a conventional expectation-maximization algorithm. Since this model still uses the linear Gaussian framework, hand-state decoding can be performed by the efficient Kalman filter algorithm. Experimental results show that this new model provides a more appropriate representation of the neural data and generates more accurate decoding. Furthermore, we have used recently developed computationally efficient methods by incorporating a priori information of the targets of the reaching movement. Our results show that the hidden-state model with target-conditioning further improves decoding accuracy.

Common-input models for multiple neural spike-train data.

Recent developments in multi-electrode recordings enable the simultaneous measurement of the spiking activity of many neurons. Analysis of such multineuronal data is one of the key challenge in computational neuroscience today. In this work, we develop a multivariate point-process model in which the observed activity of a network of neurons depends on three terms: (1) the experimentally-controlled stimulus; (2) the spiking history of the observed neurons; and (3) a hidden term that corresponds, for example, to common input from an unobserved population of neurons that is presynaptic to two or more cells in the observed population. We consider two models for the network firing-rates, one of which is computationally and analytically tractable but can lead to unrealistically high firing-rates, while the other with reasonable firing-rates imposes a greater computational burden. We develop an expectation-maximization algorithm for fitting the parameters of both the models. For the analytically tractable model the expectation step is based on a continuous-time implementation of the extended Kalman smoother, and the maximization step involves two concave maximization problems which may be solved in parallel. The other model that we consider necessitates the use of Monte Carlo methods for the expectation as well as maximization step. We discuss the trade-off involved in choosing between the two models and the associated methods. The techniques developed allow us to solve a variety of inference problems in a straightforward, computationally efficient fashion; for example, we may use the model to predict network activity given an arbitrary stimulus, infer a neuron's ring rate given the stimulus and the activity of the other observed neurons, and perform optimal stimulus decoding and prediction. We present several detailed simulation studies which explore the strengths and limitations of our approach.

Effects of chronic treatment with cromakalim and glibenclamide in alloxan-induced diabetic rats.

We have studied the effects of chronic treatment with cromakalim (75 ug kg(-1) per day) and glibenclamide (20 mg kg(-1) per day) in alloxan-induced diabetic rats. Injection of alloxan (60 mg kg(-1)/i.v., single dose) produced a significant increase in the blood pressure, bradycardia, hyperglycemia, hypoinsulinemia, hyperlipidemia, hypothyroidism and depression in left ventricular developed pressure (LVDP). While glibenclamide significantly prevented alloxan-induced hyperglycemia and hypoinsulinaemia, it failed to alter hypertension, bradycardia, hypertriglyceridaemia and hypercholesterolemia. Treatment with cromakalim-prevented hypertension and bradycardia, but not the hyperglycemia or hypoinsulinaemia. Co-administration of cromakalim with glibenclamide antagonized the effect of glibenclamide on these parameters. Cromakalim treatment also prevented alloxan-induced hypercholesterolemia and hypertriglyceridaemia. It also produced a significant increase in serum T(3) and T(4) levels. Glibenclamide did not significantly alter alloxan-induced hypothyroidism. In conclusion our data suggest that cromakalim and glibenclamide produce some metabolic effects that are either not related to K(ATP) channel modulation or may involve different sub-types of potassium channels. Further glibenclamide when combined with cromakalim may not be beneficial in a condition when diabetes mellitus and hypertension co-exits.