Cold seep formation from salt diapir-controlled deep biosphere oases.

Deep sea cold seeps are sites where hydrogen sulfide, methane, and other hydrocarbon-rich fluids vent from the ocean floor. They are an important component of Earth's carbon cycle in which subsurface hydrocarbons form the energy source for highly diverse benthic micro- and macro-fauna in what is otherwise vast and spartan sea scape. Passive continental margin cold seeps are typically attributed to the migration of hydrocarbons generated from deeply buried source rocks. Many of these seeps occur over salt tectonic provinces, where the movement of salt generates complex fault systems that can enable fluid migration or create seals and traps associated with reservoir formation. The elevated advective heat transport of the salt also produces a chimney effect directly over these structures. Here, we provide geophysical and geochemical evidence that the salt chimney effect in conjunction with diapiric faulting drives a subsurface groundwater circulation system that brings dissolved inorganic carbon, nutrient-rich deep basinal fluids, and potentially overlying seawater onto the crests of deeply buried salt diapirs. The mobilized fluids fuel methanogenic archaea locally enhancing the deep biosphere. The resulting elevated biogenic methane production, alongside the upward heat-driven fluid transport, represents a previously unrecognized mechanism of cold seep formation and regulation.

Mapping and decoding cortical engagement during motor imagery, mental arithmetic, and silent word generation using MEG.

Accurate quantification of cortical engagement during mental imagery tasks remains a challenging brain-imaging problem with immediate relevance to developing brain-computer interfaces. We analyzed magnetoencephalography (MEG) data from 18 individuals completing cued motor imagery, mental arithmetic, and silent word generation tasks. Participants imagined movements of both hands (HANDS) and both feet (FEET), subtracted two numbers (SUB), and silently generated words (WORD). The task-related cortical engagement was inferred from beta band (17-25 Hz) power decrements estimated using a frequency-resolved beamforming method. In the hands and feet motor imagery tasks, beta power consistently decreased in premotor and motor areas. In the word and subtraction tasks, beta-power decrements showed engagements in language and arithmetic processing within the temporal, parietal, and inferior frontal regions. A support vector machine classification of beta power decrements yielded high accuracy rates of 74 and 68% for classifying motor-imagery (HANDS vs. FEET) and cognitive (WORD vs. SUB) tasks, respectively. From the motor-versus-nonmotor contrasts, excellent accuracy rates of 85 and 80% were observed for hands-versus-word and hands-versus-sub, respectively. A multivariate Gaussian-process classifier provided an accuracy rate of 60% for the four-way (HANDS-FEET-WORD-SUB) classification problem. Individual task performance was revealed by within-subject correlations of beta-decrements. Beta-power decrements are helpful metrics for mapping and decoding cortical engagement during mental processes in the absence of sensory stimuli or overt behavioral outputs. Markers derived based on beta decrements may be suitable for rehabilitation purposes, to characterize motor or cognitive impairments, or to treat patients recovering from a cerebral stroke.

Deep Learning Based Inter-subject Continuous Decoding of Motor Imagery for Practical Brain-Computer Interfaces.

Inter-subject transfer learning is a long-standing problem in brain-computer interfaces (BCIs) and has not yet been fully realized due to high inter-subject variability in the brain signals related to motor imagery (MI). The recent success of deep learning-based algorithms in classifying different brain signals warrants further exploration to determine whether it is feasible for the inter-subject continuous decoding of MI signals to provide contingent neurofeedback which is important for neurorehabilitative BCI designs. In this paper, we have shown how a convolutional neural network (CNN) based deep learning framework can be used for inter-subject continuous decoding of MI related electroencephalographic (EEG) signals using the novel concept of Mega Blocks for adapting the network against inter-subject variabilities. These Mega Blocks have the capacity to repeat a specific architectural block several times such as one or more convolutional layers in a single Mega Block. The parameters of such Mega Blocks can be optimized using Bayesian hyperparameter optimization. The results, obtained on the publicly available BCI competition IV-2b dataset, yields an average inter-subject continuous decoding accuracy of 71.49% (κ = 0.42) and 70.84% (κ = 0.42) for two different training methods such as adaptive moment estimation (Adam) and stochastic gradient descent (SGDM), respectively, in 7 out of 9 subjects. Our results show for the first time that it is feasible to use CNN based architectures for inter-subject continuous decoding with a sufficient level of accuracy for developing calibration-free MI-BCIs for practical purposes.

Assessing impact of channel selection on decoding of motor and cognitive imagery from MEG data.

OBJECTIVE: Magnetoencephalography (MEG) based brain-computer interface (BCI) involves a large number of sensors allowing better spatiotemporal resolution for assessing brain activity patterns. There have been many efforts to develop BCI using MEG with high accuracy, though an increase in the number of channels (NoC) means an increase in computational complexity. However, not all sensors necessarily contribute significantly to an increase in classification accuracy (CA) and specifically in the case of MEG-based BCI no channel selection methodology has been performed. Therefore, this study investigates the effect of channel selection on the performance of MEG-based BCI. APPROACH: MEG data were recorded for two sessions from 15 healthy participants performing motor imagery, cognitive imagery and a mixed imagery task pair using a unique paradigm. Performance of four state-of-the-art channel selection methods (i.e. Class-Correlation, ReliefF, Random Forest, and Infinite Latent Feature Selection were applied across six binary tasks in three different frequency bands) were evaluated in this study on two state-of-the-art features, i.e. bandpower and common spatial pattern (CSP). MAIN RESULTS: All four methods provided a statistically significant increase in CA compared to a baseline method using all gradiometer sensors, i.e. 204 channels with band-power features from alpha (8-12 Hz), beta (13-30 Hz), or broadband (α + ß) (8-30 Hz). It is also observed that the alpha frequency band performed better than the beta and broadband frequency bands. The performance of the beta band gave the lowest CA compared with the other two bands. Channel selection improved accuracy irrespective of feature types. Moreover, all the methods reduced the NoC significantly, from 204 to a range of 1-25, using bandpower as a feature and from 15 to 105 for CSP. The optimal channel number also varied not only in each session but also for each participant. Reducing the NoC will help to decrease the computational cost and maintain numerical stability in cases of low trial numbers. SIGNIFICANCE: The study showed significant improvement in performance of MEG-BCI with channel selection irrespective of feature type and hence can be successfully applied for BCI applications.

Quantitative X-ray fluorescence analysis: Trace level detection of toxic elemental impurities in drug product by ED-XRF spectrometer.

Inorganic impurity analysis of pharmaceutical drug products is of paramount importance at trace levels due to the availability of toxic metals. The existing techniques require extensive development and chemical treatment to evaluate the presence of class I (Pb, Cd, Hg and As) and class II (Co, V and Ni) heavy metal elements which are harmful to the environment. To overcome these issues, a cost and time effective wavelength dispersive X-ray fluorescence spectrometry (XRF) was introduced to determine the concentration of trace elements in one of the angiotensin receptor blocker (ARB) (tablet sample 300 mg) according to guidelines addressed in ICH Q3D and USP. The validation study focused on class I and class II elements are also in accordance with regulatory guidelines. Overall it includes the comprehensive characterization of analytical method which is compliant with the requirement of USP. The novelty of this work includes the application of EDXRF in routine analysis of trace elements (especially volatile Hg) present in the pharmaceutical product beyond the previously published studies for the limited number of the non-pharmaceutical regime. Apart from this it also requires minimal sample preparation and method development and is able to quantify toxic impurities which are present in the sample in less than 20 ppm concentration, with the lowest level of detection up to 0.1 ppm.

Brain-Machine Interface-Driven Post-Stroke Upper-Limb Functional Recovery Correlates With Beta-Band Mediated Cortical Networks.

Brain-machine interface (BMI)-driven robot-assisted neurorehabilitation intervention has demonstrated improvement in upper-limb (UL) motor function, specifically, with post-stroke hemiparetic patients. However, neurophysiological patterns related to such interventions are not well understood. This paper examined the longitudinal changes in band-limited resting-state (RS) functional connectivity (FC) networks in association with post-stroke UL functional recovery achieved by a multimodal intervention involving motor attempt (MA)-based BMI and robotic hand-exoskeleton. Four adults were rehabilitated with the intervention for a period lasting up to six weeks. RS magnetoencephalography (MEG) signals, Action Research Arm Test (ARAT), and grip strength (GS) measures were recorded at five equispaced sessions over the intervention period. An average post-interventional increase of 100.0% (p=0.00028) and 88.0% was attained for ARAT and GS, respectively. A cluster-based statistical test involving correlation estimates between beta-band (15-26 Hz) RS-MEG FCs and UL functional recovery provided the positively correlated sub-networks in both the contralesional and ipsilesional motor cortices. The frontoparietal FC exhibited hemispheric lateralization wherein the majority of the positively and negatively correlated connections were found in contralesional and ipsilesional hemispheres, respectively. Our findings are consistent with the theory of bilateral motor cortical association with UL recovery and predict novel FC patterns that can be important for higher level cognitive functions.

An EEG-EMG correlation-based brain-computer interface for hand orthosis supported neuro-rehabilitation.

BACKGROUND: Corticomuscular coupling has been investigated for long, to find out the underlying mechanisms behind cortical drives to produce different motor tasks. Although important in rehabilitation perspective, the use of corticomuscular coupling for driving brain-computer interface (BCI)-based neurorehabilitation is much ignored. This is primarily due to the fact that the EEG-EMG coherence popularly used to compute corticomuscular coupling, fails to produce sufficient accuracy in single-trial based prediction of motor tasks in a BCI system. NEW METHOD: In this study, we have introduced a new corticomuscular feature extraction method based on the correlation between band-limited power time-courses (CBPT) associated with EEG and EMG. 16 healthy individuals and 8 hemiplegic patients participated in a BCI-based hand orthosis triggering task, to test the performance of the CBPT method. The healthy population was equally divided into two groups; one experimental group for CBPT-based BCI experiment and another control group for EEG-EMG coherence based BCI experiment. RESULTS: The classification accuracy of the CBPT-based BCI system was found to be 92.81 ±â€¯2.09% for the healthy experimental group and 84.53 ±â€¯4.58% for the patients' group. COMPARISON WITH EXISTING METHOD: The CBPT method significantly (p-value < 0.05) outperformed the conventional EEG-EMG coherence method in terms of classification accuracy. CONCLUSIONS: The experimental results clearly indicate that the EEG-EMG CBPT is a better alternative as a corticomuscular feature to drive a BCI system. Additionally, it is also feasible to use the proposed method to design BCI-based robotic neurorehabilitation paradigms.

Hand-Exoskeleton Assisted Progressive Neurorehabilitation using Impedance Adaptation based Challenge Level Adjustment Method.

This paper presents an underactuated design of a robotic hand exoskeleton and a challenge based neurorehabilitation strategy. The exoskeleton is designed to reproduce natural human fingertip paths during extension and grasping, keeping minimal kinematic complexity. It facilitates an impedance adaptation based trigged assistance control strategy by a switching between active non-assist and passive assistance modes. In active non-assist mode, the exoskeleton motion follows the applied fingertip forces based on an impedance model. If the applied fingertip forces are inadequate, the passive assistance mode is triggered. The impedance parameters are updated at regular intervals based on the user performance, to implement a challenge based rehabilitation strategy. A six-week long hand therapy, conducted on four chronic stroke patients results in significant (p-value<0.05) increase in force generation capacity and decrease (p-value<0.05) in the required assistance. Also, there was a significant (p-value<0.05) increase in the system impedance parameters which adequately challenged the patients. The change in the Action-Research-Arm-Test (ARAT) scores from baseline are also found to be significant (p-value<0.05) and beyond the minimal clinically important difference (MCID) limit. Thus the results prove that the proposed control strategy with has the potential to be a clinically effective solution for personalized rehabilitation of poststroke hand functionality.

Active Physical Practice Followed by Mental Practice Using BCI-Driven Hand Exoskeleton: A Pilot Trial for Clinical Effectiveness and Usability.

Appropriately combining mental practice (MP) and physical practice (PP) in a poststroke rehabilitation is critical for ensuring a substantially positive rehabilitation outcome. Here, we present a rehabilitation protocol incorporating a separate active PP stage followed by MP stage, using a hand exoskeleton and brain-computer interface (BCI). The PP stage was mediated by a force sensor feedback-based assist-as-needed control strategy, whereas the MP stage provided BCI-based multimodal neurofeedback combining anthropomorphic visual feedback and proprioceptive feedback of the impaired hand extension attempt. A six week long clinical trial was conducted on four hemiparetic stroke patients (screened out of 16) with a left-hand disability. The primary outcome, motor functional recovery, was measured in terms of changes in grip-strength (GS) and action research arm test (ARAT) scores; whereas the secondary outcome, usability of the system was measured in terms of changes in mood, fatigue, and motivation on a visual-analog-scale. A positive rehabilitative outcome was found as the group mean changes from the baseline in the GS and ARAT were +6.38 kg and +5.66 accordingly. The VAS scale measurements also showed betterment in mood ( 1.38), increased motivation (+2.10) and reduced fatigue (0.98) as compared to the baseline. Thus, the proposed neurorehabilitation protocol is found to be promising both in terms of clinical effectiveness and usability.

Synergistic effects of ultrasonication and ethanol washing in controlling the stoichiometry, phase-purity and morphology of rare-earth doped ceria nanoparticles.

Over a period of last thirty years, use of ethanol has been historically reported for obtaining nanopowders with low agglomeration for various oxide systems. In addition to these benefits, we show for the first time that treatments in ethanol medium coupled with an ultrasonication step can impart crucial additional advantages in controlling the phase purity and stoichiometry/composition for such systems. This is an important issue especially for any complex multicationic oxide nanoparticles system and hence we selected one of the most popular catalyst systems of doped-ceria (CeO2) nanoparticles with very high (50%) level of rare-earth (lanthanum) doping for this case study. The effect of an ultrasonication combined ethanol treatment was compared with the other solvent media (pure water and ethanol) without ultrasonication. The underlying mechanism for this process involves lowering the deprotonation rate in ethanol medium which eventually reduces the condensation of the individual metal oxides while the ultrasonication ensures the reproducibility of the synthesis by providing a homogeneous colloidal solution for each washing stages. This novel modification in synthesis of nanoparticles aims to provide meaningful solutions in optimising the phase, composition and morphology of multicationic complex system of nanocrystals.

Metagenomic Analysis of Hot Springs in Central India Reveals Hydrocarbon Degrading Thermophiles and Pathways Essential for Survival in Extreme Environments.

Extreme ecosystems such as hot springs are of great interest as a source of novel extremophilic species, enzymes, metabolic functions for survival and biotechnological products. India harbors hundreds of hot springs, the majority of which are not yet explored and require comprehensive studies to unravel their unknown and untapped phylogenetic and functional diversity. The aim of this study was to perform a large-scale metagenomic analysis of three major hot springs located in central India namely, Badi Anhoni, Chhoti Anhoni, and Tattapani at two geographically distinct regions (Anhoni and Tattapani), to uncover the resident microbial community and their metabolic traits. Samples were collected from seven distinct sites of the three hot spring locations with temperature ranging from 43.5 to 98°C. The 16S rRNA gene amplicon sequencing of V3 hypervariable region and shotgun metagenome sequencing uncovered a unique taxonomic and metabolic diversity of the resident thermophilic microbial community in these hot springs. Genes associated with hydrocarbon degradation pathways, such as benzoate, xylene, toluene, and benzene were observed to be abundant in the Anhoni hot springs (43.5-55°C), dominated by Pseudomonas stutzeri and Acidovorax sp., suggesting the presence of chemoorganotrophic thermophilic community with the ability to utilize complex hydrocarbons as a source of energy. A high abundance of genes belonging to methane metabolism pathway was observed at Chhoti Anhoni hot spring, where methane is reported to constitute >80% of all the emitted gases, which was marked by the high abundance of Methylococcus capsulatus. The Tattapani hot spring, with a high-temperature range (61.5-98°C), displayed a lower microbial diversity and was primarily dominated by a nitrate-reducing archaeal species Pyrobaculum aerophilum. A higher abundance of cell metabolism pathways essential for the microbial survival in extreme conditions was observed at Tattapani. Taken together, the results of this study reveal a novel consortium of microbes, genes, and pathways associated with the hot spring environment.

Critical assessment of day time traffic noise level at curbside open-air microenvironment of Kolkata City, India.

BACKGROUND: The objective of the research work is to assess day time traffic noise level at curbside open-air microenvironment of Kolkata city, India under heterogeneous environmental conditions. RESULTS: Prevailing traffic noise level in terms of A-weighted equivalent noise level (Leq) at the microenvironment was in excess of 12.6 ± 2.1 dB(A) from the day time standard of 65 dB(A) for commercial area recommended by the Central Pollution Control Board (CPCB) of India. Noise Climate and Traffic Noise Index of the microenvironment were accounted for 13 ± 1.8 dB(A) and 88.8 ± 6.1 dB(A) respectively. A correlation analysis explored that prevailing traffic noise level of the microenvironment had weak negative (-0.21; p < 0.01) and very weak positive (0.19; p < 0.01) correlation with air temperature and relative humidity. A Varimax rotated principal component analysis explored that motorized traffic volume had moderate positive loading with background noise component (L90, L95, L99) and prevailing traffic noise level had very strong positive loading with peak noise component (L1, L5, L10). Background and peak noise component cumulatively explained 80.98 % of variance in the data set. CONCLUSIONS: Traffic noise level at curbside open-air microenvironment of Kolkata City was higher than the standard recommended by CPCB of India. It was highly annoying also. Air temperature and relative humidity had little influence and the peak noise component had the most significant influence on the prevailing traffic noise level at curbside open-air microenvironment. Therefore, traffic noise level at the microenvironment of the city can be reduced with careful honking and driving.

Respiratory response to tobacco dust exposure among biddi binders: A follow up and bronchodilator study.

INTORDUCTION: The tobacco dusts get air borne during biddi making and it is inhaled by the biddi binders, which affects their health. RESULTS: In a follow-up study, 86 biddi binders (male, 41; female, 45) were studied at a gap of 2 years. A high respiratory morbidity was observed among males than females both in the initial and follow-up study. The main complaints such as cough, sputum, and breathlessness showed high prevalence rates in the follow-up study. The high prevalence rates of weakness, giddiness, chronic diarrhea, and dyspepsia were noted in most of the cases the above complaints showed higher rates in the follow-up study. Pulmonary function test (PFT) values in the follow-up study of male and female biddi binders showed lowered compared with the initial study of same gender. In male and female biddi binders, the lung volumes SVC, FVC, FEV1, and the flow rates FEF0.2-1.2 l, FEF25%-75%, FEF75%-85% were significantly lowered in the follow-up study compared with the initial study. Age-related decrement in PFT was observed in both the studies. In nonsmokers, smokers, and ex-smokers, the PFT values are lowered. The current smokers have the lowest values in both the studies. With the administration of the bronchodilator aerosol (salbutamol) in 63 biddi binders (male, 27; female, 36), the effect of bronchodilator aerosol on the PFT parameters showed significant changes as all PFT parameters showed positive bronchodilatation. CONCLUSION: The pattern of bronchodilator response on PFT values of the biddi binders suggests that the obstructions in the airways are reversible in nature.

Nanomaterials in the field of design ergonomics: present status.

Application of nanotechnology and nanomaterials is not new in the field of design, but a recent trend of extensive use of nanomaterials in product and/or workplace design is drawing attention of design researchers all over the world. In the present paper, an attempt has been made to describe the diverse use of nanomaterials in product and workplace design with special emphasis on ergonomics (occupational health and safety; thermo-regulation and work efficiency, cognitive interface design; maintenance of workplace, etc.) to popularise the new discipline 'nanoergonomics' among designers, design users and design researchers. Nanoergonomics for sustainable product and workplace design by minimising occupational health risks has been felt by the authors to be an emerging research area in coming years. PRACTITIONER SUMMARY: Use of nanomaterials in the field of design ergonomics is less explored till date. In the present review, an attempt has been made to extend general awareness among ergonomists/designers about applications of nanomaterials/nanotechnology in the field of design ergonomics and about health implications of nanomaterials during their use.

Variable sequences outside the SAM-binding core critically influence the conformational dynamics of the SAM-III/SMK box riboswitch.

The S(MK) box (SAM-III) translational riboswitches were identified in S-adenosyl-l-methionine (SAM) synthetase metK genes in members of Lactobacillales. This riboswitch switches between two alternative conformations in response to intracellular SAM concentration and controls metK expression at the level of translation initiation. We previously reported the crystal structure of the SAM-bound S(MK) box riboswitch. In this study, we combined selective 2'-hydroxyl acylation analyzed by primer extension chemical probing with mutagenesis to probe the ligand-induced conformational switching mechanism. We revealed that while the majority of the apo S(MK) box RNA molecules exist in an alternatively base-paired (ON) conformation, a subset of them pre-organize into a SAM-bound-like (READY) conformation, which, upon SAM exposure, is selectively stabilized into the SAM-bound (OFF) conformation through an induced-fit mechanism. Mutagenesis showed that the ON state is only slightly more stable than the READY state, as several single-nucleotide substitutions in a hypervariable region outside the SAM-binding core can alter the folding landscape to favor the READY state. Such S(MK) variants display a "constitutively OFF" behavior both in vitro and in vivo. Time-resolved and temperature-dependent selective 2'-hydroxyl acylation analyzed by primer extension analyses revealed adaptation of the S(MK) box RNA to its mesothermal working environment. The latter analysis revealed that the SAM-bound S(MK) box RNA follows a two-step folding/unfolding process.

SAM recognition and conformational switching mechanism in the Bacillus subtilis yitJ S box/SAM-I riboswitch.

S-box (SAM-I) riboswitches are a widespread class of riboswitches involved in the regulation of sulfur metabolism in Gram-positive bacteria. We report here the 3.0-Å crystal structure of the aptamer domain of the Bacillus subtilis yitJ S-box (SAM-I) riboswitch bound to S-adenosyl-L-methionine (SAM). The RNA folds into two sets of helical stacks spatially arranged by tertiary interactions including a K-turn and a pseudoknot at a four-way junction. The tertiary structure is further stabilized by metal coordination, extensive ribose zipper interactions, and SAM-mediated tertiary interactions. Despite structural differences in the peripheral regions, the SAM-binding core of the B. subtilis yitJ riboswitch is virtually superimposable with the previously determined Thermoanaerobacter tengcongensis yitJ riboswitch structure, suggesting that a highly conserved ligand-recognition mechanism is utilized by all S-box riboswitches. SHAPE (selective 2'-hydroxyl acylation analyzed by primer extension) chemical probing analysis further revealed that the alternative base-pairing element in the expression platform controls the conformational switching process. In the absence of SAM, the apo yitJ aptamer domain folds predominantly into a pre-binding conformation that resembles, but is not identical with, the SAM-bound state. We propose that SAM enters the ligand-binding site through the "J1/2-J3/4" gate and "locks" down the SAM-bound conformation through an induced-fit mechanism. Temperature-dependent SHAPE revealed that the tertiary interaction-stabilized SAM-binding core is extremely stable, likely due to the cooperative RNA folding behavior. Mutational studies revealed that certain modifications in the SAM-binding region result in loss of SAM binding and constitutive termination, which suggests that these mutations lock the RNA into a form that resembles the SAM-bound form in the absence of SAM.

Pro-healing effect of Cinnamomum zeylanicum bark.

The ethanol extract of the bark of Cinnamomum zeylanicum was evaluated for wound healing activity in Wistar rats. The extract was administered by the oral route at a dose of 250 mg/kg and 500 mg/kg body weight (1/8 and 1/4 of LD(50), respectively) for all the wound models selected, excision, incision and dead space wounds. The extract significantly enhanced the wound breaking strength in the case of incision wound, the rate of wound contraction and the period of epithelization in the case of excision wound. The granulation tissue weight, its breaking strength and its hydroxyproline content was also increased by the extract in the dead space wound.