Generalized synchronization in a tritrophic food web metacommunity.

Complete synchronization among the metacommunity is known to elevate the risk of their extinction due to stochasticity and other environmental perturbations. Owing to the inherent heterogeneous nature of the metacommunity, we demonstrate the emergence of generalized synchronization among the patches of dispersally connected tritrophic food web using the framework of an auxiliary system approach and the mutual false nearest neighbor. We find that the critical value of the dispersal rate increases significantly with the size of the metacommunity for both unidirectional and bidirectional dispersals, which in turn corroborates that larger metacommunities are more stable than smaller ones. Further, we find that the critical value of the dispersal for the onset of generalized synchronization is smaller(larger) for bidirectional dispersal than that for unidirectional dispersal for smaller(larger) metacommunities. Most importantly, complete synchronization error remains finite even after the onset of generalized synchronization in a wider range of dispersal rate elucidating that the latter can serve as an early warning signal for the extinction of the metacommunity.

Early warning indicators capture catastrophic transitions driven by explicit rates of environmental change.

In response to external changes, ecosystems can undergo catastrophic transitions. Early warning indicators aim to predict such transitions based on the phenomenon of critical slowing down at bifurcation points found under a constant environment. When an explicit rate of environmental change is considered, catastrophic transitions can become distinct phenomena from bifurcations, and result from a delayed response to noncatastrophic bifurcations. We use a trophic metacommunity model where transitions in time series and bifurcations of the system are distinct phenomena. We calculate early warning indicators from the time series of the continually changing system and show that they predict not the bifurcation of the underlying system but the actual catastrophic transition driven by the explicit rate of change. Predictions based on the bifurcation structure could miss catastrophic transitions that can still be captured by early warning signals calculated from time series. Our results expand the repertoire of mechanistic models used to anticipate catastrophic transitions to nonequilibrium ecological systems exposed to a constant rate of environmental change.

Role of limiting dispersal on metacommunity stability and persistence.

The role of dispersal on the stability and synchrony of a metacommunity is a topic of considerable interest in theoretical ecology. Dispersal is known to promote both synchrony, which enhances the likelihood of extinction, and spatial heterogeneity, which favors the persistence of the population. Several efforts have been made to understand the effect of diverse variants of dispersal in the spatially distributed ecological community. Despite that environmental change strongly affects the dispersal, the effects of controlled dispersal on the metacommunity stability and their persistence remain unknown. We study the influence of limiting the immigration using two-patch prey-predator metacommunity at both local and spatial scales. We find that the spread of the inhomogeneous stable steady states (asynchronous states) decreases monotonically upon limiting the predator dispersal. Nevertheless, at the local scale, the spread of the inhomogeneous steady states increases up to a critical value of the limiting factor, favoring the metacommunity persistence, and then starts decreasing for a further decrease in the limiting factor with varying local interaction. Interestingly, limiting the prey dispersal promotes inhomogeneous steady states in a large region of the parameter space, thereby increasing the metacommunity persistence at both spatial and local scales. Further, we show similar qualitative dynamics in an entire class of complex networks consisting of a large number of patches. We also deduce various bifurcation curves and stability conditions for the inhomogeneous steady states, which we find to agree well with the simulation results. Thus, our findings on the effect of the limiting dispersal can help to develop conservation measures for ecological communities.

Expansion of the measles and rubella laboratory network, India.

Objective: To expand the measles and rubella laboratory network of India by integrating new laboratories. Methods: In collaboration with the World Health Organization (WHO), the Indian government developed a 10-step scheme to systematically expand the number of laboratories performing serological and molecular testing for measles and rubella. The Indian Council of Medical Research and WHO identified suitable laboratories based on their geographical location, willingness, preparedness, past performance and adherence to national quality control and quality assurance mechanisms. The 10-step scheme was initiated with training on measles and rubella diagnostic assays followed by testing of both measles and rubella serology and molecular unknown panels, cross-verification with reference laboratories and ended with WHO on-site accreditation. Findings: After extensive training, technical support, funding and monitoring, all six selected laboratories attained passing scores of 90.0% or more in serological and molecular proficiency testing of measles and rubella. Since 2018, the laboratories are a part of the measles and rubella network of India. Within 12 months of initiation of independent reporting, the six laboratories have tested 2287 serum samples and 701 throat or nasopharyngeal swabs or urine samples. Conclusion: The process led to strengthening and expansion of the network. This proficient laboratory network has helped India in scaling up serological and molecular testing of measles and rubella while ensuring high quality testing. The collaborative model developed by the Indian government with WHO can be implemented by other countries for expanding laboratory networks for surveillance of measles and rubella as well as other infectious diseases.

Adherence to safety precautions in the operation theatre among anaesthesiologists in the COVID era.

Background and Aims: The COVID-19 pandemic led to significant infections among healthcare workers and deaths warranting the need for personal protective equipment. This study aimed to estimate the proportion of anaesthesiologists adhering to safety precautions and to evaluate their adherence patterns, difficulties faced and coping mechanisms in the operation theatre during the pandemic. Methods: This was a multicentric mixed methods study conducted among anaesthesiologists from two tertiary care hospitals. A paper-based questionnaire was given to all participants. The first part consisted of 21 questions regarding safety measures and extent of adherence. The second part was a response sheet regarding the various difficulties faced and coping mechanisms adopted. Following this, an in-depth interview was conducted to understand the same. The proportion of anaesthesiologists in different categories of adherence, patterns of adherence, difficulties faced, and coping mechanisms were computed and compared. Thematic framework analysis was done for in-depth interview. Results: Sixty participants were included. The adherence levels for N95 masks and face shields were higher. Most participants practised frequent handwashing and took showers after work. Fogging, difficulty in communication, marks on the face were the commonly faced difficulties. Self reassurance, adjusting the fit of masks/face shields, or taking breaks were the coping mechanisms mostly followed. Themes generated from in-depth interview include waning of caution, adaptation through innovative methods and stress due to uncertainty. Conclusion: The N95 mask was the most preferred safety precaution. Ease of use and safety were important considerations for adherence. Physical and mental acclimatisation and improved knowledge of disease played a vital role.

Metacommunity persistence to environmental change: Stabilizing and destabilizing effects of individual species dispersal.

Ecological communities face a high risk of extinction to climate change which can destabilize ecological systems. In the face of accelerating environmental change, understanding the factors and the mechanisms that stabilize the ecological communities is a central focus in ecology. Although dispersal has been widely used as an important stabilizing process, it remains unclear how individual species dispersal affects the stability and persistence of an ecological community. In this study, using a spatially coupled predator-prey community, we address the effects of individual species dispersal and nutrient enrichment on metacommunity stability in constant and varying environments. We show two contrasting effects of dispersal on metacommunity persistence in temporally constant and varying environments. Specifically, predator dispersal in constant environments shows stronger stability through inhomogeneous (asynchronized) states, whereas prey dispersal shows an increasing extinction risk through a homogeneous (synchronized) state. On the contrary, the metacommunity dynamics in temporally varying environments reveal that predator dispersal causes a local extinction through tracking unstable states and also a delayed shift between dynamical states. Moreover, our results emphasize that metacommunity persistence depends on individual species dispersal and environmental variations. Thus, our findings of the individual species dispersal can help to develop conservation measures that are tailored to varying environmental conditions.

Advances of Inorganic Materials in the Detection and Therapeutic Uses against Coronaviruses.

Coronaviruses (CoVs) are enveloped viruses with particle-like characteristics and a diameter of 60-140 nm, positively charged, and single-stranded RNA genomes, which caused a major outbreak of human fatal pneumonia in the beginning of the 21st century. COVID-19 is currently considered a continuous potential pandemic threat across the globe. Therefore, considerable efforts have been made to develop innovative methods and technologies for suppressing the spread of viruses as well as inactivating the viruses but COVID-19 vaccines are still in the development phase. This perspective focuses on the sensing, detection and therapeutic applications of CoVs using inorganic- based nanomaterials, metal complexes, and metal-conjugates. Synthetic inorganic- based nanoparticles interact strongly with proteins of viruses due to their morphological similarities, and therefore, numerous antivirals have been tested for efficacy against different viruses in vitro through colorimetric and electrochemical assays. Metal complexes- based agents such as bismuth complexes form an attractive class of drugs with a number of therapeutic applications, including the inhibition and duplex-unwinding activity of SARS-CoV helicase by quantitative real-time PCR (Q-RT-PCR), phosphate release assay and radioassay studies. Metal-conjugates show major effects on inhibiting the 3Clike protease of SARS-CoV and the replication of RNA-dependent RNA polymerase (RdRp). We anticipate that these approaches will provide rapid and accurate antiviral strategies in the development of these innovative sensors for the detection, inhibition and antiviral activities of coronaviruses.

COVID-19-related strokes are associated with increased mortality and morbidity: A multicenter comparative study from Bengaluru, South India.

BACKGROUND: COVID-19-related strokes are increasingly being diagnosed across the world. Knowledge about the clinical profile, imaging findings, and outcomes is still evolving. Here we describe the characteristics of a cohort of 62 COVID-19-related stroke patients from 13 hospitals, from Bangalore city, south India. OBJECTIVE: To describe the clinical profile, neuroimaging findings, interventions, and outcomes in COVID-19-related stroke patients. METHODS: This is a multicenter retrospective study of all COVID-19-related stroke patients from 13 hospitals from south India; 1st June 2020-31st August 2020. The demographic, clinical, laboratory, and neuroimaging data were collected along with treatment administered and outcomes. SARS-CoV-2 infection was confirmed in all cases by RT-PCR testing. The data obtained from the case records were entered in SPSS 25 for statistical analysis. RESULTS: During the three-month period, we had 62 COVID-19-related stroke patients, across 13 centers; 60 (97%) had ischemic strokes, while 2 (3%) had hemorrhagic strokes. The mean age of patients was 55.66 ± 13.20 years, with 34 (77.4%) males. Twenty-six percent (16/62) of patients did not have any conventional risk factors for stroke. Diabetes mellitus was seen in 54.8%, hypertension was present in 61.3%, coronary artery disease in 8%, and atrial fibrillation in 4.8%. Baseline National Institutes of Health Stroke Scale score was 12.7 ± 6.44. Stroke severity was moderate (National Institutes of Health Stroke Scale 5-15) in 27 (61.3%) patients, moderate to severe (National Institutes of Health Stroke Scale 16-20) in 13 (20.9%) patients and severe (National Institutes of Health Stroke Scale 21-42) in 11 (17.7%) patients. According to TOAST classification, 48.3% was stroke of undetermined etiology, 36.6% had large artery atherosclerosis, 10% had small vessel occlusion, and 5% had cardioembolic strokes. Three (5%) received intravenous thrombolysis with tenecteplase 0.2 mg/kg and 3 (5%) underwent mechanical thrombectomy, two endovascular and one surgical. Duration of hospital stay was 16.16 ± 6.39 days; 21% (13/62) died in hospital, while 37 (59.7%) had a modified Rankin score of 3-5 at discharge. Hypertension, atrial fibrillation, and higher baseline National Institutes of Health Stroke Scale scores were associated with increased mortality. A comparison to 111 historical controls during the non-COVID period showed a higher proportion of strokes of undetermined etiology, higher mortality, and higher morbidity in COVID-19-related stroke patients. CONCLUSION: COVID-19-related strokes are increasingly being recognized in developing countries, like India. Stroke of undetermined etiology appears to be the most common TOAST subtype of COVID-19-related strokes. COVID-19-related strokes were more severe in nature and resulted in higher mortality and morbidity. Hypertension, atrial fibrillation, and higher baseline National Institutes of Health Stroke Scale scores were associated with increased mortality.

Dynamic environment-induced multistability and critical transition in a metacommunity ecosystem.

We study a metacommunity model of consumer-resource populations coupled via dispersal under an environment-dependent framework, and we explore the occurrence of multistability and critical transition. By emphasizing two magnitudes acting on a dynamic environment at temporal and spatial scales, the coupled system with simple diffusive coupling and the nonlinear environmental coupling enables various interesting complex dynamics such as bistability, multistability, and critical transitions. Using the basin stability measure, we find the probability of attaining each alternative state in a multistable region. In addition, critical transitions (one from a high to a low species density and the other from a low to a high species density) are identified at different magnitudes in the presence of stochastic fluctuations. We also explore the robustness of critical slowing-down indicators, e.g., lag-1 autocorrelation and variance, to forewarn the critical transition in the metacommunity model. Further, a network structure also identifies synchronization and multiclustering for a different choice of initial conditions. In contrast with the earlier studies on dynamic environmental coupling, our results based on the defined magnitudes provide important insights into environmental heterogeneity, which determines the set of environmental conditions to predict metacommunity stability and persistence.

Synchronization and entrainment of metapopulations: A trade-off among time-induced heterogeneity, dispersal, and seasonal force.

Demographic and environmental heterogeneities are prevalent across many natural systems. Earlier studies on metapopulation models have mostly considered heterogeneities either in the demographic parameters or in the interaction strength and topology between the spatially separated patches. In contrast, here we study the dynamics of a metapopulation model where each of the uncoupled patches has different periods of oscillations (period mismatch). We show different synchronization dynamics governed by both period mismatch and dispersal in neighboring patches. Indeed, we find both appearance and disappearance of phase synchronization, quasiperiodic oscillations, and period doubling of limit cycle. We also quantify the effect of seasonal variation (entrainment) and dispersal on species synchrony using phase-response curve and a synchrony measure, which thereof identify the influence of stochasticity on species persistence through trade-off mechanisms. Our results show that trade-offs among period mismatch, dispersal, and external force can drive entrained oscillations as well as asynchronous population dynamics that structure ecological communities.

Environmental coupling in ecosystems: From oscillation quenching to rhythmogenesis.

How landscape fragmentation affects ecosystems diversity and stability is an important and complex question in ecology with no simple answer, as spatially separated habitats where species live are highly dynamic rather than just static. Taking into account the species dispersal among nearby connected habitats (or patches) through a common dynamic environment, we model the consumer-resource interactions with a ring type coupled network. By characterizing the dynamics of consumer-resource interactions in a coupled ecological system with three fundamental mechanisms such as the interaction within the patch, the interaction between the patches, and the interaction through a common dynamic environment, we report the occurrence of various collective behaviors. We show that the interplay between the dynamic environment and the dispersal among connected patches exhibits the mechanism of generation of oscillations, i.e., rhythmogenesis, as well as suppression of oscillations, i.e., amplitude death and oscillation death. Also, the transition from homogeneous steady state to inhomogeneous steady state occurs through a codimension-2 bifurcation. Emphasizing a network of a spatially extended system, the coupled model exposes the collective behavior of a synchrony-stability relationship with various synchronization occurrences such as in-phase and out-of-phase.

Generation and cessation of oscillations: Interplay of excitability and dispersal in a class of ecosystems.

We investigate the complex spatiotemporal dynamics of an ecological network with species dispersal mediated via a mean-field coupling. The local dynamics of the network are governed by the Truscott-Brindley model, which is an important ecological model showing excitability. Our results focus on the interplay of excitability and dispersal by always considering that the individual nodes are in their (excitable) steady states. In contrast to the previous studies, we not only observe the dispersal induced generation of oscillation but also report two distinct mechanisms of cessation of oscillations, namely, amplitude and oscillation death. We show that the dispersal between the nodes influences the intrinsic dynamics of the system resulting in multiple oscillatory dynamics such as period-1 and period-2 limit cycles. We also show the existence of multi-cluster states, which has much relevance and importance in ecology.

Dispersal-induced synchrony, temporal stability, and clustering in a mean-field coupled Rosenzweig-MacArthur model.

In spatial ecology, dispersal among a set of spatially separated habitats, named as metapopulation, preserves the diversity and persistence by interconnecting the local populations. Understanding the effects of several variants of dispersion in metapopulation dynamics and to identify the factors which promote population synchrony and population stability are important in ecology. In this paper, we consider the mean-field dispersion among the habitats in a network and study the collective dynamics of the spatially extended system. Using the Rosenzweig-MacArthur model for individual patches, we show that the population synchrony and temporal stability, which are believed to be of conflicting outcomes of dispersion, can be simultaneously achieved by oscillation quenching mechanisms. Particularly, we explore the more natural coupling configuration where the rates of dispersal of different habitats are disparate. We show that asymmetry in dispersal rate plays a crucial role in determining inhomogeneity in an otherwise homogeneous metapopulation. We further identify an unusual emergent state in the network, namely, a multi-branch clustered inhomogeneous steady state, which arises due to the intrinsic parameter mismatch among the patches. We believe that the present study will shed light on the cooperative behavior of spatially structured ecosystems.