Concurrent- and After-Effects of Medial Temporal Lobe Stimulation on Directed Information Flow to and from Prefrontal and Parietal Cortices during Memory Formation.

Electrical stimulation of the medial temporal lobe (MTL) has the potential to uncover causal circuit mechanisms underlying memory function. However, little is known about how MTL stimulation alters information flow with frontoparietal cortical regions implicated in episodic memory. We used intracranial EEG recordings from humans (14 participants, 10 females) to investigate how MTL stimulation alters directed information flow between MTL and PFC and between MTL and posterior parietal cortex (PPC). Participants performed a verbal episodic memory task during which they were presented with words and asked to recall them after a delay of ∼20 s; 50 Hz stimulation was applied to MTL electrodes on selected trials during memory encoding. Directed information flow was examined using phase transfer entropy. Behaviorally, we observed that MTL stimulation reduced memory recall. MTL stimulation decreased top-down PFC→MTL directed information flow during both memory encoding and subsequent memory recall, revealing aftereffects more than 20 s after end of stimulation. Stimulation suppressed top-down PFC→MTL influences to a greater extent than PPC→MTL. Finally, MTL→PFC information flow on stimulation trials was significantly lower for successful, compared with unsuccessful, memory recall; in contrast, MTL→ventral PPC information flow was higher for successful, compared with unsuccessful, memory recall. Together, these results demonstrate that the effects of MTL stimulation are behaviorally, regionally, and directionally specific, that MTL stimulation selectively impairs directional signaling with PFC, and that causal MTL-ventral PPC circuits support successful memory recall. Findings provide new insights into dynamic casual circuits underling episodic memory and their modulation by MTL stimulation.SIGNIFICANCE STATEMENT The medial temporal lobe (MTL) and its interactions with prefrontal and parietal cortices (PFC and PPC) play a critical role in human memory. Dysfunctional MTL-PFC and MTL-PPC circuits are prominent in psychiatric and neurologic disorders, including Alzheimer's disease and schizophrenia. Brain stimulation has emerged as a potential mechanism for enhancing memory and cognitive functions, but the underlying neurophysiological mechanisms and dynamic causal circuitry underlying bottom-up and top-down signaling involving the MTL are unknown. Here, we use intracranial EEG recordings to investigate the effects of MTL stimulation on causal signaling in key episodic memory circuits linking the MTL with PFC and PPC. Our findings have implications for translational applications aimed at realizing the promise of brain stimulation-based treatment of memory disorders.

Harnessing weedy rice as functional food and source of novel traits for crop improvement.

A relative of cultivated rice (Oryza sativa L.), weedy or red rice (Oryza spp.) is currently recognized as the dominant weed, leading to a drastic loss of yield of cultivated rice due to its highly competitive abilities like producing more tillers, panicles, and biomass with better nutrient uptake. Due to its high nutritional value, antioxidant properties (anthocyanin and proanthocyanin), and nutrient absorption ability, weedy rice is gaining immense research attentions to understand its genetic constitution to augment future breeding strategies and to develop nutrition-rich functional foods. Consequently, this review focuses on the unique gene source of weedy rice to enhance the cultivated rice for its crucial features like water use efficiency, abiotic and biotic stress tolerance, early flowering, and the red pericarp of the seed. It explores the debating issues on the origin and evolution of weedy rice, including its high diversity, signalling aspects, quantitative trait loci (QTL) mapping under stress conditions, the intricacy of the mechanism in the expression of the gene flow, and ecological challenges of nutrient removal by weedy rice. This review may create a foundation for future researchers to understand the gene flow between cultivated crops and weedy traits and support an improved approach for the applicability of several models in predicting multiomics variables.

Replicable patterns of causal information flow between hippocampus and prefrontal cortex during spatial navigation and spatial-verbal memory formation.

Interactions between the hippocampus and prefrontal cortex (PFC) play an essential role in both human spatial navigation and episodic memory, but the underlying causal flow of information between these regions across task domains is poorly understood. Here we use intracranial EEG recordings and spectrally resolved phase transfer entropy to investigate information flow during two different virtual spatial navigation and memory encoding/recall tasks and examine replicability of information flow patterns across spatial and verbal memory domains. Information theoretic analysis revealed a higher causal information flow from hippocampus to lateral PFC than in the reverse direction. Crucially, an asymmetric pattern of information flow was observed during memory encoding and recall periods of both spatial navigation tasks. Further analyses revealed frequency specificity of interactions characterized by greater bottom-up information flow from hippocampus to PFC in delta-theta band (0.5-8 Hz); in contrast, top-down information flow from PFC to hippocampus was stronger in beta band (12-30 Hz). Bayesian analysis revealed a high degree of replicability between the two spatial navigation tasks (Bayes factor > 5.46e+3) and across tasks spanning the spatial and verbal memory domains (Bayes factor > 7.32e+8). Our findings identify a domain-independent and replicable frequency-dependent feedback loop engaged during memory formation in the human brain.

Sensing and Automation Technologies for Ornamental Nursery Crop Production: Current Status and Future Prospects.

The ornamental crop industry is an important contributor to the economy in the United States. The industry has been facing challenges due to continuously increasing labor and agricultural input costs. Sensing and automation technologies have been introduced to reduce labor requirements and to ensure efficient management operations. This article reviews current sensing and automation technologies used for ornamental nursery crop production and highlights prospective technologies that can be applied for future applications. Applications of sensors, computer vision, artificial intelligence (AI), machine learning (ML), Internet-of-Things (IoT), and robotic technologies are reviewed. Some advanced technologies, including 3D cameras, enhanced deep learning models, edge computing, radio-frequency identification (RFID), and integrated robotics used for other cropping systems, are also discussed as potential prospects. This review concludes that advanced sensing, AI and robotic technologies are critically needed for the nursery crop industry. Adapting these current and future innovative technologies will benefit growers working towards sustainable ornamental nursery crop production.

Evaluation of multifrequency SAR data for estimating tropical above-ground biomass by employing radiative transfer modeling.

The retrieval of the biophysical parameters and subsequent estimation of the above-ground biomass (AGB) of vegetation stands are made possible by the simulation of the extinction and scattering components from the canopy layer using vector radiative transfer (VRT) theory-based scattering models. With the use of such a model, this study aims to evaluate and compare the potential of dual-pol, multi-frequency SAR data for estimating above-ground biomass. The data selected for this work are L-band dual polarized (HH/HV) ALOS-2 data, S-band dual polarized (HH/HV) NovaSAR data, and C-band dual polarized (VV/VH) Sentinel-1 data. The two key biophysical parameters, tree height, and trunk radius are retrieved using the proposed methodology, applying the frequencies independently. A general allometric equation with vegetation-specific coefficients is used to estimate the AGB from the retrieved biophysical parameters. The retrieval results are validated using ground truth measurements collected from the study area. The L-band, with the coefficient of determination ([Formula: see text]) of 0.73 and the root mean square error (RMSE) of 35.90 t/ha, has the best correlation between the modeled and field AGBs, followed by the S-band with an [Formula: see text] of 0.37 and an RMSE of 63.37 t/ha, and the C-band with an [Formula: see text] of 0.25 and an RMSE of 72.32 t/ha. The L-band has yielded improved estimates of AGB in regression analysis as well, with an [Formula: see text] of 0.48 and an RMSE of 50.02 t/ha, compared to the S- and C-bands, which have the [Formula: see text] of 0.12 and 0.03 and the RMSE of 70.98 t/ha and 80.84 t/ha, respectively.

Asymmetric Frequency-Specific Feedforward and Feedback Information Flow between Hippocampus and Prefrontal Cortex during Verbal Memory Encoding and Recall.

Hippocampus and prefrontal cortex (PFC) circuits are thought to play a prominent role in human episodic memory, but the precise nature, and electrophysiological basis, of directed information flow between these regions and their role in verbal memory formation has remained elusive. Here we investigate nonlinear causal interactions between hippocampus and lateral PFC using intracranial EEG recordings (26 participants, 16 females) during verbal memory encoding and recall tasks. Direction-specific information theoretic analysis revealed higher causal information flow from the hippocampus to PFC than in the reverse direction. Crucially, this pattern was observed during both memory encoding and recall, and the strength of causal interactions was significantly greater during memory task performance than resting baseline. Further analyses revealed frequency specificity of interactions with greater causal information flow from hippocampus to the PFC in the delta-theta frequency band (0.5-8 Hz); in contrast, PFC to hippocampus causal information flow were stronger in the beta band (12-30 Hz). Across all hippocampus-PFC electrode pairs, propagation delay between the source and target signals was estimated to be 17.7 ms, which is physiologically meaningful and corresponds to directional signal interactions on a timescale consistent with monosynaptic influence. Our findings identify distinct asymmetric feedforward and feedback signaling mechanisms between the hippocampus and PFC and their dissociable roles in memory recall, demonstrate that these regions preferentially use different frequency channels, and provide novel insights into the electrophysiological basis of directed information flow during episodic memory formation in the human brain.SIGNIFICANCE STATEMENT Hippocampal-PFC circuits play a critical role in episodic memory in rodents, nonhuman primates, and humans. Investigations using noninvasive fMRI techniques have provided insights into coactivation of the hippocampus and PFC during memory formation; however, the electrophysiological basis of dynamic causal hippocampal-PFC interactions in the human brain is poorly understood. Here, we use data from a large cohort of intracranial EEG recordings to investigate the neurophysiological underpinnings of asymmetric feedforward and feedback hippocampal-PFC interactions and their nonlinear causal dynamics during both episodic memory encoding and recall. Our findings provide novel insights into the electrophysiological basis of directed bottom-up and top-down information flow during episodic memory formation in the human brain.

Electrophysiological foundations of the human default-mode network revealed by intracranial-EEG recordings during resting-state and cognition.

Investigations using noninvasive functional magnetic resonance imaging (fMRI) have provided significant insights into the unique functional organization and profound importance of the human default mode network (DMN), yet these methods are limited in their ability to resolve network dynamics across multiple timescales. Electrophysiological techniques are critical to address these challenges, yet few studies have explored the neurophysiological underpinnings of the DMN. Here we investigate the electrophysiological organization of the DMN in a common large-scale network framework consistent with prior fMRI studies. We used intracranial EEG (iEEG) recordings, and evaluated intra- and cross-network interactions during resting-state and its modulation during a cognitive task involving episodic memory formation. Our analysis revealed significantly greater intra-DMN phase iEEG synchronization in the slow-wave (< 4 Hz), while DMN interactions with other brain networks was higher in the beta (12-30 Hz) and gamma (30-80 Hz) bands. Crucially, slow-wave intra-DMN synchronization was observed in the task-free resting-state and during both verbal memory encoding and recall. Compared to resting-state, slow-wave intra-DMN phase synchronization was significantly higher during both memory encoding and recall. Slow-wave intra-DMN phase synchronization increased during successful memory retrieval, highlighting its behavioral relevance. Finally, analysis of nonlinear dynamic causal interactions revealed that the DMN is a causal outflow network during both memory encoding and recall. Our findings identify frequency specific neurophysiological signatures of the DMN which allow it to maintain stability and flexibility, intrinsically and during task-based cognition, provide novel insights into the electrophysiological foundations of the human DMN, and elucidate network mechanisms by which it supports cognition.

Validation of at-the-bedside formulae for estimating ventilator driving pressure during airway pressure release ventilation using computer simulation.

BACKGROUND: Airway pressure release ventilation (APRV) is widely available on mechanical ventilators and has been proposed as an early intervention to prevent lung injury or as a rescue therapy in the management of refractory hypoxemia. Driving pressure ([Formula: see text]) has been identified in numerous studies as a key indicator of ventilator-induced-lung-injury that needs to be carefully controlled. [Formula: see text] delivered by the ventilator in APRV is not directly measurable in dynamic conditions, and there is no "gold standard" method for its estimation. METHODS: We used a computational simulator matched to data from 90 patients with acute respiratory distress syndrome (ARDS) to evaluate the accuracy of three "at-the-bedside" methods for estimating ventilator [Formula: see text] during APRV. RESULTS: Levels of [Formula: see text] delivered by the ventilator in APRV were generally within safe limits, but in some cases exceeded levels specified by protective ventilation strategies. A formula based on estimating the intrinsic positive end expiratory pressure present at the end of the APRV release provided the most accurate estimates of [Formula: see text]. A second formula based on assuming that expiratory flow, volume and pressure decay mono-exponentially, and a third method that requires temporarily switching to volume-controlled ventilation, also provided accurate estimates of true [Formula: see text]. CONCLUSIONS: Levels of [Formula: see text] delivered by the ventilator during APRV can potentially exceed levels specified by standard protective ventilation strategies, highlighting the need for careful monitoring. Our results show that [Formula: see text] delivered by the ventilator during APRV can be accurately estimated at the bedside using simple formulae that are based on readily available measurements.

Pre-hospital continuous positive airway pressure after blast lung injury and hypovolaemic shock: a modelling study.

BACKGROUND: In non-traumatic respiratory failure, pre-hospital application of CPAP reduces the need for intubation. Primary blast lung injury (PBLI) accompanied by haemorrhagic shock is common after mass casualty incidents. We hypothesised that pre-hospital CPAP is also beneficial after PBLI accompanied by haemorrhagic shock. METHODS: We performed a computer-based simulation of the cardiopulmonary response to PBLI followed by haemorrhage, calibrated from published controlled porcine experiments exploring blast injury and haemorrhagic shock. The effect of different CPAP levels was simulated in three in silico patients who had sustained mild, moderate, or severe PBLI (10%, 25%, 50% contusion of the total lung) plus haemorrhagic shock. The primary outcome was arterial partial pressure of oxygen (Pao2) at the end of each simulation. RESULTS: In mild blast lung injury, 5 cm H2O ambient-air CPAP increased Pao2 from 10.6 to 12.6 kPa. Higher CPAP did not further improve Pao2. In moderate blast lung injury, 10 cm H2O CPAP produced a larger increase in Pao2 (from 8.5 to 11.1 kPa), but 15 cm H2O CPAP produced no further benefit. In severe blast lung injury, 5 cm H2O CPAP inceased Pao2 from 4.06 to 8.39 kPa. Further increasing CPAP to 10-15 cm H2O reduced Pao2 (7.99 and 7.90 kPa, respectively) as a result of haemodynamic impairment resulting from increased intrathoracic pressures. CONCLUSIONS: Our modelling study suggests that ambient air 5 cm H2O CPAP may benefit casualties suffering from blast lung injury, even with severe haemorrhagic shock. However, higher CPAP levels beyond 10 cm H2O after severe lung injury reduced oxygen delivery as a result of haemodynamic impairment.

Optimising respiratory support for early COVID-19 pneumonia: a computational modelling study.

BACKGROUND: Optimal respiratory support in early COVID-19 pneumonia is controversial and remains unclear. Using computational modelling, we examined whether lung injury might be exacerbated in early COVID-19 by assessing the impact of conventional oxygen therapy (COT), high-flow nasal oxygen therapy (HFNOT), continuous positive airway pressure (CPAP), and noninvasive ventilation (NIV). METHODS: Using an established multi-compartmental cardiopulmonary simulator, we first modelled COT at a fixed FiO2 (0.6) with elevated respiratory effort for 30 min in 120 spontaneously breathing patients, before initiating HFNOT, CPAP, or NIV. Respiratory effort was then reduced progressively over 30-min intervals. Oxygenation, respiratory effort, and lung stress/strain were quantified. Lung-protective mechanical ventilation was also simulated in the same cohort. RESULTS: HFNOT, CPAP, and NIV improved oxygenation compared with conventional therapy, but also initially increased total lung stress and strain. Improved oxygenation with CPAP reduced respiratory effort but lung stress/strain remained elevated for CPAP >5 cm H2O. With reduced respiratory effort, HFNOT maintained better oxygenation and reduced total lung stress, with no increase in total lung strain. Compared with 10 cm H2O PEEP, 4 cm H2O PEEP in NIV reduced total lung stress, but high total lung strain persisted even with less respiratory effort. Lung-protective mechanical ventilation improved oxygenation while minimising lung injury. CONCLUSIONS: The failure of noninvasive ventilatory support to reduce respiratory effort may exacerbate pulmonary injury in patients with early COVID-19 pneumonia. HFNOT reduces lung strain and achieves similar oxygenation to CPAP/NIV. Invasive mechanical ventilation may be less injurious than noninvasive support in patients with high respiratory effort.

Modeling Mechanical Ventilation In Silico-Potential and Pitfalls.

Computer simulation offers a fresh approach to traditional medical research that is particularly well suited to investigating issues related to mechanical ventilation. Patients receiving mechanical ventilation are routinely monitored in great detail, providing extensive high-quality data-streams for model design and configuration. Models based on such data can incorporate very complex system dynamics that can be validated against patient responses for use as investigational surrogates. Crucially, simulation offers the potential to "look inside" the patient, allowing unimpeded access to all variables of interest. In contrast to trials on both animal models and human patients, in silico models are completely configurable and reproducible; for example, different ventilator settings can be applied to an identical virtual patient, or the same settings applied to different patients, to understand their mode of action and quantitatively compare their effectiveness. Here, we review progress on the mathematical modeling and computer simulation of human anatomy, physiology, and pathophysiology in the context of mechanical ventilation, with an emphasis on the clinical applications of this approach in various disease states. We present new results highlighting the link between model complexity and predictive capability, using data on the responses of individual patients with acute respiratory distress syndrome to changes in multiple ventilator settings. The current limitations and potential of in silico modeling are discussed from a clinical perspective, and future challenges and research directions highlighted.

Evaluation of N doped rGO-ZnO-CoPc(COOH)8 nanocomposite in cyanide degradation and its bactericidal activities.

In the present study, an attempt has been made to design a solar light driven N-rGO-ZnO- CoPc(COOH)8 nanocomposite for the degradation of cyanide. The morphological and structural characterization of the synthesized nanocomposite was performed by XRD, FT-IR, XPS, UV-vis DRS, FESEM, TEM, EDS, PL spectra and BET surface area. The results revealed that almost 91% degradation and 86% toxicity removal occurred at 25 mgL-1 of initial cyanide concentration by the N-rGO-ZnO-CoPc(COOH)8 nanocomposite under illumination of solar light within 120 min. Analysis of free radicals reveals that the generation of OH. radicals was the predominant species in the photocatalytic degradation process. The cyanide degradation follows pseudo-first order kinetics. The estimated apparent rate constant (Kapp) of the above nanocomposite was 3 times higher than that of the ZnO photocatalyst alone together with a very good recycle activities. This might be due to the application of metallpthalocyanine photosensitizer CoPc(COOH)8 which enhances the rate of visible light absorption efficiency and activates the higher band gap ZnO photocatalyst under visible light. In addition, the presence of residual oxygen in N-rGO also promotes nucleation and anchor sites for interfacial contact between ZnO and N-rGO for effective charge transfer. Further, the N-rGO-ZnO-CoPc(COOH)8 photocatalytic system showed significant antibacterial activities against mixed culture systems. Therefore, the N-rGO-ZnO-CoPc(COOH)8 nanocomposite may be an alternative solar light driven photocatalyst system for the removal of cyanide from the wastewater along with its strong disinfectant activities.

Restoring soil carbon in marginal land of Indian Himalayas: Impact of crop intensification and conservation tillage.

Soil carbon (C) loss is the prime sign of land degradation, and C pools have a great impact on soil quality and climate change mitigation. Hence, a field experiment was conducted for three consecutive years to assess the impact of crop intensification and conservation tillage practices on changes in the C pool at different soil depths of marginal land of the Indian Himalayas. The experiment consisted of two intensified cropping systems viz., CS1-Summer maize (Zea mays L.) -rainy season maize-lentil (Lens esculenta L.) and CS2-Summer maize-rainy season maize-mustard (Brassica juncea (L.) Czern) and five tillage practices viz., No-till (NT); NT + live mulch of cowpea (NT + LMC); reduced tillage (RT); RT + LMC and conventional tillage (CT). Results revealed that CS2 produced significantly higher biomass, C retention efficiency (9.85%), and sequestrated greater C (0.42 Mg ha-1 yr-1) in the soil system than CS1. Of the various tillage practices, RT + LMC registered higher biomass and recycled greater biomass and C than those under other tillage practices. However, the highest soil organic carbon (SOC) content (7.03 g kg-1) and pool (9.62 Mg ha-1) in 0-10 cm depth were observed under NT + LMC. The non-labile C pool size under NT in 0-10 cm and 10-20 cm depths was significantly greater than those under CT. The NT + LMC sequestrated significantly higher SOC (0.57 Mg ha-1 yr-1) than other tillage practices. Thus, the study indicated that the adoption of an intensified maize-based system under RT + LMC or NT + LMC would increase SOC storage and C sequestration in marginal lands of the Indian Himalayas.

Assessment of mangrove cover dynamics and its health status in the Gulf of Khambhat, Western India, using high-resolution multi-temporal satellite data and Google Earth Engine.

Anthropogenic activity is a major driving factor of greenhouse gas emission, leading to climate change worldwide. So, the best natural approach to lowering the carbon from the atmosphere is mangroves which have more potential to sequestrate carbon. But mangroves are under threat due to land use land cover change. This research has been carried out on the mangroves of Gulf of Khambhat, Gujarat, India, where anthropic activity is affecting the mangrove forest cover with spatiotemporal heterogeneity. In the present study, multi-temporal high-resolution satellite data AVNIR-2 (Advanced Visible and Near Infrared Radiometer type-2) and LISS-4 (Linear Imaging Self-Scanning Sensors-4) were used for the demarcation of various land use/land cover class (LULC), and change analysis and assessment of mangroves health for the years 2009, 2014, and 2019. The impact of saltpan/aquaculture on mangroves growth and its health status has been calculated by various MODIS (Moderate Resolution Imaging Spectroradiometer) satellite data products such as gross primary productivity (GPP), enhanced vegetation index (EVI), and leaf area index (LAI) in Google Earth Engine (GEE), and field-based method was also considered. This study suggests that there is a marginal increase (17.11 km2) in mangrove cover during the assessment period 2009-2019; on other side, 65.42 km2 was degraded also. However, increase in saltpan/aquaculture is imposing an adverse effect on mangroves' basal area, plant density, and productivity. Change analysis also suggests a reduction in healthy mangrove area (from 25.20 to 2.84 km2), which will have an impact on ecosystem services.

Integration of C-band SAR and high-resolution optical images for delineating palaeo-channels in Nagaur and Barmer districts, western Rajasthan, India.

Identifying hitherto unknown palaeo-channels, especially in the arid regions of the Thar Desert, is crucial since these channels may form excellent aquifers, and are also associated with valuable ore deposits of many precious minerals. This study employed integrated C-band Synthetic Aperture Radar (SAR) of Sentinel-1A and high-resolution multispectral Sentinel-2A data of pre- and post-monsoon seasons (June and November) to delineate playas and palaeo-channels. This approach is the first of its kind for this area. The palaeo-channels were delineated through a detailed visual inspection of colour composite (CC) images of Sentinel-2A data, SAR backscatter (VH) images and fused SAR and optical images. Then, we studied the topographic profiles generated from the Shuttle Radar Topography Mission - Digital Elevation Model (SRTM-DEM) across the identified palaeo-channels, Normalized Difference Vegetation Index (NDVI) and Normalized Difference Water Index (NDWI) to further confirm the existence of a palaeo-channel's course and playas. As a result, several playas and palaeo-channels in the area were successfully identified, some of which were previously unmapped and undetected. The results indicate that the post-monsoon datasets are more useful for the precise delineation of palaeo-channels due to the presence of relatively higher moisture along the palaeo-channels' courses.

Ventilation strategies for front of neck airway rescue: an in silico study.

BACKGROUND: During induction of general anaesthesia a 'cannot intubate, cannot oxygenate' (CICO) situation can arise, leading to severe hypoxaemia. Evidence is scarce to guide ventilation strategies for small-bore emergency front of neck airways that ensure effective oxygenation without risking lung damage and cardiovascular depression. METHODS: Fifty virtual subjects were configured using a high-fidelity computational model of the cardiovascular and pulmonary systems. Each subject breathed 100% oxygen for 3 min and then became apnoeic, with an obstructed upper airway. When arterial haemoglobin oxygen saturation reached 40%, front of neck airway access was simulated with various configurations. We examined the effect of several ventilation strategies on re-oxygenation, pulmonary pressures, cardiovascular function, and oxygen delivery. RESULTS: Re-oxygenation was achieved in all ventilation strategies. Smaller airway configurations led to dynamic hyperinflation for a wide range of ventilation strategies. This effect was absent in airways with larger internal diameter (≥3 mm). Intrapulmonary pressures increased quickly to supra-physiological values with the smallest airways, resulting in pronounced cardio-circulatory depression (cardiac output <3 L min-1 and mean arterial pressure <60 mm Hg), impeding oxygen delivery (<600 ml min-1). Limiting tidal volume (≤200 ml) and ventilatory frequency (≤8 bpm) for smaller diameter cannulas reduced dynamic hyperinflation and gas trapping, preventing cardiovascular depression. CONCLUSIONS: Dynamic hyperinflation can be demonstrated for a wide range of front of neck airway cannulae when the upper airway is obstructed. When using small-bore cannulae in a CICO situation, ventilation strategies should be chosen that prevent gas trapping to prevent severe adverse events including cardio-circulatory depression.

Spatiotemporal Integrity and Spontaneous Nonlinear Dynamic Properties of the Salience Network Revealed by Human Intracranial Electrophysiology: A Multicohort Replication.

The salience network (SN) plays a critical role in cognitive control and adaptive human behaviors, but its electrophysiological foundations and millisecond timescale dynamic temporal properties are poorly understood. Here, we use invasive intracranial EEG (iEEG) from multiple cohorts to investigate the neurophysiological underpinnings of the SN and identify dynamic temporal properties that distinguish it from the default mode network (DMN) and dorsolateral frontal-parietal network (FPN), two other large-scale brain networks that play important roles in human cognition. iEEG analysis of network interactions revealed that the anterior insula and anterior cingulate cortex, which together anchor the SN, had stronger intranetwork interactions with each other than cross-network interactions with the DMN and FPN. Analysis of directionality of information flow between the SN, DMN, and FPN revealed causal outflow hubs in the SN consistent with its role in fast temporal switching of network interactions. Analysis of regional iEEG temporal fluctuations revealed faster temporal dynamics and higher entropy of neural activity within the SN, compared to the DMN and FPN. Critically, these results were replicated across multiple cohorts. Our findings provide new insights into the neurophysiological basis of the SN, and more broadly, foundational mechanisms underlying the large-scale functional organization of the human brain.

Determinants of minimum acceptable diet feeding among children aged 6-23 months in Odisha, India.

OBJECTIVE: To assess the level, pattern and determinants of minimum acceptable diet (MAD) feeding in Odisha, India. DESIGN: Utilising cross-sectional data, the MAD was estimated through a dietary assessment method wherein the child's mother was asked to recall all the food intake of the youngest child the previous day and night of the surveyed date. SETTING: National Family Health Survey 2015-2016. PARTICIPANTS: Children aged 6-23 months, living with mother and for whom complete information on MAD was available (n 3073). RESULTS: Only 8·4 % of the children aged 6-23 months were fed MAD, and the MAD feeding varies considerably by socio-demographic characteristics. Children aged 12-17 months had two times (OR: 2·51, 95 % CI (1·48, 4·26)) and those aged 18-23 months had three times (OR: 3·77, 95 % CI (2·25, 6·30)) higher odds of having a MAD than their counterparts aged 6-8 months. Children whose mother was exposed to any mass media had a higher chance of MAD feeding (OR: 1·46, 95 % CI (1·01, 2·11)). CONCLUSIONS: The children of higher age, second or higher-order births, with mother exposed to mass media are significantly more likely to be fed with a MAD. At the same time, children from scheduled caste (SC) households have a lower probability of MAD feeding. The lower MAD feeding among the SC households suggests strengthening the ongoing programmes with a higher emphasis on the inclusion of this disadvantaged and marginalised group. Findings from the current study would assist policymakers, and public health managers improve MAD feeding practices in Odisha, India, in a targeted manner.

Impact of 28 year old agroforestry systems on soil carbon dynamics in Eastern Himalayas.

Globally, various estimates are available on the above-ground (plant parts) carbon (C) sequestering potential of agroforestry systems (AFSs). However, information on soil organic carbon (SOC) sequestration potential is limited for AFSs. Furthermore, the impacts of AFSs established for the restoration of C in degraded soils (prone to soil erosion, C and nutrients loss, etc.) of Himalayas are rarely investigated. Thus, a study was conducted on an agroforestry block established in 1989 at the Indian Council of Agricultural Research (ICAR), Research Complex for North Eastern Hill (NEH) Region, Lembucherra, Tripura, India. The AFSs comprised of four multipurpose tree species viz., teak (Tectona grandis Linn), sissoo (Dalbergia sissoo Roxb. Ex DC.), eucalyptus (Eucalyptus globulus L.), and neem (Azadirachta indica A. Juss) in combination with pineapple (Ananas comosus L. merr.). Planted in three times replicated randomized block design. After 28 years of establishment, the impacts of these AFSs were assessed on SOC stocks and its fraction pools. Results revealed that sissoo + pineapple system stored the highest SOC stocks in 0-15 cm (22.1 ± 1.4 Mg/ha) and 30-60 cm (18.0 ± 4.3 Mg/ha) depths, whereas the SOC stocks in 15-30 cm (12.2 ± 1.2 Mg/ha) and 0-30 cm (34.0 ± 1.6 Mg/ha) were the highest under teak + pineapple. When considering the entire 0-100 cm soil profile, the SOC stocks ranged between 65.3 and 71.6 Mg/ha across the diverse AFSs which was significantly higher than that under cultivated land (52.8 ± 2.6 Mg/ha). The sissoo + pineapple system had the highest SOC stock in 0-100 cm (71.6 ± 5.8 Mg/ha). The share of passive carbon (PC, less labile + non-labile) pools to SOC stocks under AFSs followed the order of sissoo + pineapple > teak + pineapple > neem + pineapple > eucalyptus + pineapple. The PC or recalcitrant pools of SOC stocks at 0-100 cm were 54.2-60.6% under various AFSs. Results revealed that the establishment of AFSs with pineapple on degraded lands increased a significant amount of C and had a considerable effect on soil quality in comparison to C present in soils under cropland. Thus, a large scale adoption of AFSs may restore C lost through the cultivation of the crop in degraded lands and provide a feasible option for livelihood through concurrent cultivation of multipurpose tree species and agri-horticulture crops.

Energy and carbon budgeting of traditional land use change with groundnut based cropping system for environmental quality, resilient soil health and farmers income in eastern Indian Himalayas.

Energy intensive traditional cereals based monoculture often lead to high greenhouse gas emissions and degradation of land and environmental quality. Present study aimed at evaluating the energy and carbon budget of diversified groundnut (Arachis hypogea L) based cropping system with over existing traditional practice towards the development of a sustainable production technology through restoration of soil and environmental quality and enhancement of farming resiliency by stabilizing farmers' income. The trials comprised of three introduced groundnut based systems viz. groundnut- pea (Pisum sativum), groundnut-lentil (Lens esculenta) and groundnut-toria (Brasssica campestris var. Toria) replacing three existing systems viz. maize (Zea mays L) - fallow, maize - toria, and rice (Oryza sativa L)-fallow systems. Four years study revealed that adoption of groundnut based systems reduced non-renewable energy input use (fertilizers, chemical, machinery and fossil fuels) by 25.5%, consequently that reduced the cost of production. Repeated analysis of variance measurement also affirmed that groundnut based systems (groundnut-pea>groundnut-lentil> groundnut-toria) increased the energy use efficiency, energy productivity, carbon use efficiency, net returns and decreased the specific energy and energy intensiveness. Groundnut based systems increased the mean system productivity and water productivity in terms of groundnut equivalent yield by 3.7 and 3.1 folds over existing practice. The savings of fossil fuel reduced greenhouse gas emissions owing to reduced use of farm machinery and synthetic fertilizers. Groundnut based systems significantly (p < 0.05) enhanced the soil carbon concentration (8.7-18.1%) and enzymatic activities (27.1-51.8%) over existing practice. Consequently, estimated soil quality index values were 35.9-77.3% higher under groundnut based systems than existing practice. Thus, the study indicated the resilient nature of groundnut based systems as an environmentally safe and sustainable production technology for enhancing resource use efficiency, reduce carbon emission, energy intensiveness and cost of production in the Eastern Himalaya region of India and similar ecosystems.