Locomotion and the early Mesozoic success of Archosauromorpha.

The Triassic was a time of ecological upheaval as life recovered from the Permian-Triassic mass extinction. Archosauromorphs were a key component of the recovery, diversifying substantially during the Triassic and encompassing the origins of dinosaurs, pterosaurs and crocodylomorphs. Here, we explore the evolution of locomotion in Archosauromorpha to test whether dinosaurs show any distinctive locomotory features that might explain their success. We implement geometric morphometrics on limb bone shapes and use limb ratios to calculate bipedality and cursoriality metrics. We find that the Avemetatarsalia (dinosaurs, pterosaurs and relatives) exhibit more variable limb form and limb ratios than any other group, indicating a wider range of locomotory modes. The earliest avemetatarsalians were bipedal and cursorial, and their range of form increased through the Triassic with notable diversification shifts following extinction events. This is especially true of dinosaurs, even though these changes cannot be discriminated from a stochastic process. By contrast, the Pseudosuchia (crocodilians and relatives) were more restricted in limb form and locomotor mode with disparity decreasing through time, suggesting more limited locomotor adaptation and vulnerability to extinction. Perhaps the greater locomotor plasticity of dinosaurs gave them a competitive advantage in the changing climates of the Late Triassic.

Predatory synapsid ecomorphology signals growing dynamism of late Palaeozoic terrestrial ecosystems.

Terrestrial ecosystems evolved substantially through the Palaeozoic, especially the Permian, gaining much new complexity, especially among predators. Key among these predators were non-mammalian synapsids. Predator ecomorphology reflect interactions with prey and competitors, which are key controls on carnivore diversity and ecology. Therefore, carnivorous synapsids may offer insight on wider ecological evolution as the first complex, tetrapod-dominated, terrestrial ecosystems formed through the late Palaeozoic. Using morphometric and phylogenetic comparative methods, we chart carnivorous synapsid trophic morphology from the latest Carboniferous to the earliest Triassic (307-251.2 Ma). We find a major morphofunctional shift in synapsid carnivory between the early and middle Permian, via the addition of new feeding modes increasingly specialised for greater biting power or speed that captures the growing antagonism and dynamism of terrestrial tetrapod predator-prey interactions. The further evolution of new hypo- and hypercarnivorous synapsids highlight the nascent intrinsic pressures and complexification of terrestrial ecosystems across the mid-late Permian.

Structural, optical, and thermoluminescence characterizations of 1 mol% Dy3+ion-activated Fluro Boro-phosphate glass for photonic devices.

A novel Fluro boro-phosphate host matrix doped with the 1 mol% of Dy3+ ions (50B2O3 + 20P2O5 + 10TiO2 + 10SrCO3 + 4BaF2 + 5BaCO3 + 1Dy2O3) was prepared using a conventional melt-quenching mechanism, and its structural characteristics were explored through the Powder-XRD, FT-IR, FT-Raman, EDAX and SEM spectroscopic analysis. The XRD spectrum of the glass confirmed its non-crystalline or amorphous structure. FT-IR and FT-Raman spectrum studies revealed that various borate and phosphate groups present with a variety of stretching and bending vibrations. Scanning Electron Microscope (SEM) and Energy Dispersive X-ray analysis (EDAX) analysis have been used to examine the surface morphology and the presence of elements, respectively in the prepared glass. The optical absorption spectrum was used to explore the electronic band structure through the measurements of optical band-gap energy and Urbach energy. The luminescence spectrum reveals the emission characteristics of Dy3+ ions due to the electric-dipole and magnetic-dipole transitions. It is found that the decay time of the 4F9/2 excited level at a concentration of 1 mol% Dy3+ in the glass matrix is tri-fit non-exponential. The CIE chromaticity coordinates and the concentration influence on Y/B intensity ratios were computed for the creation of white light from the luminescence spectrum. The present work also discusses the findings after figuring out the correlated color temperature associated (CCT) with the color purity (Pe). The Thermoluminescence (TL) characteristics and the kinetic parameters of the glass were studied after the γ-irradiation with a dose of 2 kGy. EPR investigation revealed the paramagnetic characteristics through the hyperfine structure of Dy3+ ions and the electron-hole pair formation upon irradiation in the glass matrix.

Whole-lake acoustic telemetry to evaluate survival of stocked juvenile fish.

Estimates of juvenile survival are critical for informing population dynamics and the ecology of fish, yet these demographic parameters are difficult to measure. Here, we demonstrate that advances in animal tracking technology provide opportunities to evaluate survival of juvenile tagged fish. We implemented a whole-lake telemetry array in conjunction with small acoustic tags (including tags < 1.0 g) to track the fate of stocked juvenile cisco (Coregonus artedi) as part of a native species restoration effort in the Finger Lakes region of New York, USA. We used time-to-event modeling to characterize the survival function of stocked fish, where we infer mortality as the cessation of tag detections. Survival estimates revealed distinct stages of juvenile cisco mortality including high immediate post-release mortality, followed by a period of elevated mortality during an acclimation period. By characterizing mortality over time, the whole-lake biotelemetry effort provided information useful for adapting stocking practices that may improve survival of stocked fish, and ultimately the success of the species reintroduction effort. The combination of acoustic technology and time-to-event modeling to inform fish survival may have wide applicability across waterbodies where receiver arrays can be deployed at scale and where basic assumptions about population closure can be satisfied.

A supervised learning approach for the influence of comorbidities in the analysis of COVID-19 mortality in Tamil Nadu.

COVID-19 has created many complications in today's world. It has negatively impacted the lives of many people and emphasized the need for a better health system everywhere. COVID-19 is a life-threatening disease, and a high proportion of people have lost their lives due to this pandemic. This situation enables us to dig deeper into mortality records and find meaningful patterns to save many lives in future. Based on the article from the New Indian Express (published on January 19, 2021), a whopping 82% of people who died of COVID-19 in Tamil Nadu had comorbidities, while 63 percent of people who died of the disease were above the age of 60, as per data from the Health Department. The data, part of a presentation shown to Union Health Minister Harsh Vardhan, show that of the 12,200 deaths till January 7, as many as 10,118 patients had comorbidities, and 7613 were aged above 60. A total of 3924 people (32%) were aged between 41 and 60. Compared to the 1st wave of COVID-19, the 2nd wave had a high mortality rate. Therefore, it is important to find meaningful insights from the mortality records of COVID-19 patients to know the most vulnerable population and to decide on comprehensive treatment strategies.

Toward absolute abundance for conservation applications: Estimating the number of contributors via microhaplotype genotyping of mixed-DNA samples.

Molecular methods including metabarcoding and quantitative polymerase chain reaction have shown promise for estimating species abundance by quantifying the concentration of genetic material in field samples. However, the relationship between specimen abundance and detectable concentrations of genetic material is often variable in practice. DNA mixture analysis represents an alternative approach to quantify specimen abundance based on the presence of unique alleles in a sample. The DNA mixture approach provides novel opportunities to inform ecology and conservation by estimating the absolute abundance of target taxa through molecular methods; yet, the challenges associated with genotyping many highly variable markers in mixed-DNA samples have prevented its widespread use. To advance molecular approaches for abundance estimation, we explored the utility of microhaplotypes for DNA mixture analysis by applying a 125-marker panel to 1179 Chinook salmon (Oncorhynchus tshawytscha) smolts from the Sacramento-San Joaquin Delta, California, USA. We assessed the accuracy of DNA mixture analysis through a combination of mock mixtures containing DNA from up to 20 smolts and a trophic ecological application enumerating smolts in predator diets. Mock DNA mixtures of up to 10 smolts could reliably be resolved using microhaplotypes, and increasing the panel size would likely facilitate the identification of more individuals. However, while analysis of predator gastrointestinal tract contents indicated DNA mixture analysis could discern the presence of multiple prey items, poor and variable DNA quality prevented accurate genotyping and abundance estimation. Our results indicate that DNA mixture analysis can perform well with high-quality DNA, but methodological improvements in genotyping degraded DNA are necessary before this approach can be used on marginal-quality samples.

Detecting and analysing intraspecific genetic variation with eDNA: From population genetics to species abundance.

Advancements in environmental DNA (eDNA) approaches have allowed for rapid and efficient species detections in diverse environments. Although most eDNA research is focused on leveraging genetic diversity to identify taxa, some recent studies have explored the potential for these approaches to detect within-species genetic variation, allowing for population genetic assessments and abundance estimates from environmental samples. However, we currently lack a framework outlining the key considerations specific to generating, analysing and applying eDNA data for these two purposes. Here, we discuss how various genetic markers differ with regard to genetic information and detectability in environmental samples and how analysis of eDNA samples differs from common tissue-based analyses. We then outline how it may be possible to obtain species absolute abundance estimates from eDNA by detecting intraspecific genetic variation in mixtures of DNA under multiple scenarios. We also identify the major causes contributing to allele detection and frequency errors in eDNA data, discuss their consequences for population-level analyses and outline bioinformatic approaches to detect and remove erroneous sequences. This review summarizes the key advances required to harness the full potential of eDNA-based intraspecific genetic variation to inform population-level questions in ecology, evolutionary biology and conservation management.

Rapid population growth and high management costs have created a narrow window for control of introduced hippos in Colombia.

The introduction of hippos into the wild in Colombia has been marked by their rapid population growth and widespread dispersal on the landscape, high financial costs of management, and conflicting social perspectives on their management and fate. Here we use population projection models to investigate the effectiveness and cost of management options under consideration for controlling introduced hippos. We estimate there are 91 hippos in the middle Magdalena River basin, Colombia, and the hippo population is growing at an estimated rate of 9.6% per year. At this rate, there will be 230 hippos by 2032 and over 1,000 by 2050. Applying the population control methods currently under consideration will cost at least 1-2 million USD to sufficiently decrease hippo population growth to achieve long-term removal, and depending on the management strategy selected, there may still be hippos on the landscape for 50-100 years. Delaying management actions for a single decade will increase minimum costs by a factor of 2.5, and some methods may become infeasible. Our approach illustrates the trade-offs inherent between cost and effort in managing introduced species, as well as the importance of acting quickly, especially when dealing with species with rapid population growth rates and potential for significant ecological and social impacts.

Biodiversity underpins fisheries resilience to exploitation in the Amazon river basin.

Inland fisheries feed greater than 150 million people globally, yet their status is rarely assessed due to their socio-ecological complexity and pervasive lack of data. Here, we leverage an unprecedented landings time series from the Amazon, Earth's largest river basin, together with theoretical food web models to examine (i) taxonomic and trait-based signatures of exploitation in inland fish landings and (ii) implications of changing biodiversity for fisheries resilience. In both landings time series and theory, we find that multi-species exploitation of diverse inland fisheries results in a hump-shaped landings evenness curve. Along this trajectory, abundant and large species are sequentially replaced with faster growing and smaller species. Further theoretical analysis indicates that harvests can be maintained for a period of time but that continued biodiversity depletion reduces the pool of compensating species and consequently diminishes fisheries resilience. Critically, higher fisheries biodiversity can delay fishery collapse. Although existing landings data provide an incomplete snapshot of long-term dynamics, our results suggest that multi-species exploitation is affecting freshwater biodiversity and eroding fisheries resilience in the Amazon. More broadly, we conclude that trends in landings evenness could characterize multi-species fisheries development and aid in assessing their sustainability.

Twitter sentiment analysis using ensemble based deep learning model towards COVID-19 in India and European countries.

As of November 2021, more than 24.80 crore people are diagnosed with the coronavirus in that around 50.20 lakhs people lost their lives, because of this infectious disease. By understanding the people's sentiment's expressed in their social media (Facebook, Twitter, Instagram etc.) helps their governments in controlling, monitoring, and eradicating the coronavirus. Compared to other social media's, the twitter data are indispensable in the extraction of useful awareness information related to any crisis. In this article, a sentiment analysis model is proposed to analyze the real time tweets, which are related to coronavirus. Initially, around 3100 Indian and European people's tweets are collected between the time period of 23.03.2020 to 01.11.2021. Next, the data pre-processing and exploratory investigation are accomplished for better understanding of the collected data. Further, the feature extraction is performed using Term Frequency-Inverse Document Frequency (TF-IDF), GloVe, pre-trained Word2Vec, and fast text embedding's. The obtained feature vectors are fed to the ensemble classifier (Gated Recurrent Unit (GRU) and Capsule Neural Network (CapsNet)) for classifying the user's sentiment's as anger, sad, joy, and fear. The obtained experimental outcomes showed that the proposed model achieved 97.28% and 95.20% of prediction accuracy in classifying the both Indian and European people's sentiments.

Effectiveness of ChAdOx1 nCoV-19 Corona Virus Vaccine (CovishieldTM) in preventing SARS-CoV2 infection, Chennai, Tamil Nadu, India, 2021

BackgroundIndia experienced the second wave of the COVID-19 pandemic in March 2021, driven by the delta variant. Apprehensions around the usefulness of vaccines against delta variant posed a risk to the vaccination program. Therefore, we estimated the effectiveness of two doses of the ChAdOx1 nCoV-19 (Covishield) vaccine against COVID-19 infection among individuals [≥]45 years in Chennai, India. MethodsA community-based cohort study was conducted from May to September 2021 in a selected geographic area in Chennai, Tamil Nadu. The estimated sample size was 10,232. We enumerated individuals from all eligible households and periodically updated vaccination and COVID-19 infection data. We computed vaccine effectiveness with its 95% confidence interval for two doses of the Covishield vaccine against any COVID-19 infection. ResultsWe enrolled 69,435 individuals, of which 21,793 were above 45 years. Two dose coverage of Covishield in the 18+ and 45+ age group was 18% and 31%, respectively. The overall incidence of COVID-19 infection was 1099 per 100,000 population. The vaccine effectiveness against COVID-19 disease in the [≥]45 age group was 61.3% (95% CI: 43.6 - 73.4) at least two weeks after receiving the second dose of Covishield. Genomic analysis of 74 (28 with two doses, 15 with one dose, and 31 with zero dose) out of the 90 aliquots collected from the 303 COVID-19 positive individuals in the 45+ age group showed delta variants and their sub-lineages. ConclusionWe demonstrated the effectiveness of two doses of the ChAdOx1 vaccine against the delta variant in the general population of Chennai. We recommend similar future studies considering emerging variants and newer vaccines. Two-dose vaccine coverage could be ensured to protect against COVID-19 infection.

MECP2 Mutations in the Rett Syndrome Patients from South India.

Background: Rett syndrome (RTT) is a rare neurological disorder that primarily affects the females. Most cases of RTT are caused by a de novo mutation in the MECP2 gene located on the X chromosome. About 1000 MECP2 mutations have been found to be associated with RTT. Objective: The present study is aimed at the mutation screening of MECP2 gene in the RTT patients belonging to the south Indian state of Kerala. Materials and Methods: In total 22 girls with a clinical suspicion of RTT were recruited for the study. Exons 2, 3, and 4 of MECP2 were amplified and sequenced. Results: MECP2 mutations were observed in 12 patients. While 7 mutations were pathogenic, 4 were benign. All of the mutations were located in exons 3 and 4 of MECP2, spanning the methyl-CpG DNA binding domain (MBD), transcription repression domain (TRD), and C-terminal domain (CTD) domains of the MECP2 protein. Four novel mutations were identified. There were no mutations in the MECP2 gene of 10 patients with a clinical suspicion of RTT. Conclusions: A recommended screening strategy for RTT is to first look for mutations in exons 3 and 4 of MECP2, followed by exons 1 and 2, testing for large deletions in MECP2, and screening for mutations in genes, such as CDKL5 and FOXG1 that are reported to cause a Rett-like phenotype.

Reducing adverse impacts of Amazon hydropower expansion.

Proposed hydropower dams at more than 350 sites throughout the Amazon require strategic evaluation of trade-offs between the numerous ecosystem services provided by Earth's largest and most biodiverse river basin. These services are spatially variable, hence collective impacts of newly built dams depend strongly on their configuration. We use multiobjective optimization to identify portfolios of sites that simultaneously minimize impacts on river flow, river connectivity, sediment transport, fish diversity, and greenhouse gas emissions while achieving energy production goals. We find that uncoordinated, dam-by-dam hydropower expansion has resulted in forgone ecosystem service benefits. Minimizing further damage from hydropower development requires considering diverse environmental impacts across the entire basin, as well as cooperation among Amazonian nations. Our findings offer a transferable model for the evaluation of hydropower expansion in transboundary basins.

Highly efficient functionalized MOF-LIC-1 for extraction of U(VI) and Th(IV) from aqueous solution: experimental and theoretical studies.

A set of four new functionalized MOFs, namely MOF-LIC-DPPC, MOF-LIC-GA, MOF-LIC-PCA and MOF-LIC-SA, were synthesized via the post-synthetic modification (PSM) strategy using MOF-LIC-1 for efficient extraction of U(VI) and Th(IV) from an aqueous medium. FTIR, powder XRD, TGA and SEM-EDX were employed for characterization of the functionalized MOFs. Sorption studies for U(VI) and Th(IV) were performed by monitoring the pH and contact time. Interestingly, the modified MOF-LIC-SA displayed rapid (∼5 min) and efficient extraction towards U(VI) and Th(IV) from an aqueous medium and modified MOF-LIC-DPPC displayed enhanced thermal stability (600 °C) compared with the parent MOF-LIC-1 (450 °C). These studies revealed that the grafted functionalities on MOF-LIC-1 possess enhanced sorption efficiency towards U(VI) and Th(IV) as well as thermal stability. MOF-LIC-SA exhibited the highest sorption capacity towards U(VI) and Th(IV), viz. 298 mg g-1 (pH 6) and 149 mg g-1 (pH 6), respectively. Leaching, recyclability, and radiation stability studies were also performed using MOF-LIC-1 MOFs. Additionally, we investigated the nature of U(VI) interactions on MOFs by applying density functional theory (DFT). PSM MOFs with various functionalities display high selectivity and efficient extraction of U(VI) and Th(IV) over a wide pH range (2-9) and also exhibit easy recovery of metal ions from MOFs. These studies reveal that U(VI) and Th(IV) can be extracted from aqueous streams in a pH range from 6 to 8 and potential applications of these MOFs include recovery of U(VI) and Th(IV) from mine water, sea water, etc. The studies reported in the present work also have extensive potential applications for environmental concerns as well as in the nuclear industry.

Patients' views on a proposed oral cancer screening technology.

Brush cytology and telemedicine platforms are used with proven benefits in remote diagnosis of malignancies like cervical cancer. In low-resource settings access to the current standard of care, biopsy and histopathology grading of oral lesions, can be unfeasible. Risk-stratifying early malignant and oral potentially-malignant lesions can help instigate therapeutic treatment and improve prognosis. Therefore, a telecytology platform enabling remote connectivity to specialist centres may aid early detection of oral cancer. We outline head and neck (H&N) cancer patients' views on an oral brush cytology investigation.

A machine learning approach to identify barriers in stream networks demonstrates high prevalence of unmapped riverine dams.

Restoring stream ecosystem integrity by removing unused or derelict dams has become a priority for watershed conservation globally. However, efforts to restore connectivity are constrained by the availability of accurate dam inventories which often overlook smaller unmapped riverine dams. Here we develop and test a machine learning approach to identify unmapped dams using a combination of publicly available topographic and geospatial habitat data. Specifically, we trained a random forest classification algorithm to identify unmapped dams using digitally engineered predictor variables and known dam sites for validation. We applied our algorithm to two subbasins in the Hudson River watershed, USA, and quantified connectivity impacts, as well as evaluated a range of predictor sets to examine tradeoffs between classification accuracy and model parameterization effort. The random forest classifier achieved high accuracy in predicting dam sites (true positive rate = 89%, false positive rate = 1.2%) using a subset of variables related to stream slope and presence of upstream lentic habitats. Unmapped dams were prevalent throughout the two test watersheds. In fact, existing dam inventories underestimated the true number of dams by ∼80-94%. Accounting for previously unmapped dams resulted in a 62-90% decrease in dendritic connectivity indices for migratory fishes. Unmapped dams may be pervasive and can dramatically bias stream connectivity information. However, we find that machine learning approaches can provide an accurate and scalable means of identifying unmapped dams that can guide efforts to develop accurate dam inventories, thereby informing and empowering efforts to better manage them.

A Carboniferous synapsid with caniniform teeth and a reappraisal of mandibular size-shape heterodonty in the origin of mammals.

Heterodonty is a hallmark of early mammal evolution that originated among the non-mammalian therapsids by the Middle Permian. Nonetheless, the early evolution of heterodonty in basal synapsids is poorly understood, especially in the mandibular dentition. Here, we describe a new synapsid, Shashajaia bermani gen. et sp. nov., based on a well-preserved dentary and jaw fragments from the Carboniferous-Permian Halgaito Formation of southern Utah. Shashajaia shares with some sphenacodontids enlarged (canine-like) anterior dentary teeth, a dorsoventrally deep symphysis and low-crowned, subthecodont postcanines having festooned plicidentine. A phylogenetic analysis of 20 taxa and 154 characters places Shashajaia near the evolutionary divergence of Sphenacodontidae and Therapsida (Sphenacodontoidea). To investigate the ecomorphological context of Palaeozoic sphenacodontoid dentitions, we performed a principal component analysis based on two-dimensional geometric morphometrics of the mandibular dentition in 65 synapsids. Results emphasize the increasing terrestrialization of predator-prey interactions as a driver of synapsid heterodonty; enhanced raptorial biting (puncture/gripping) aided prey capture, but this behaviour was probably an evolutionary antecedent to more complex processing (shearing/tearing) of larger herbivore prey by the late Early to Middle Permian. The record of Shashajaia supports the notion that the predatory feeding ecology of sphenacodontoids emerged in palaeotropical western Pangea by late Carboniferous times.

Declining diversity of wild-caught species puts dietary nutrient supplies at risk.

Although biodiversity loss adversely influences a variety of ecosystem functions, how declining wild food diversity affects nutrient supplies for people is poorly understood. Here, we analyze the impact of declining biodiversity on nutrients supplied by fish using detailed information from the Peruvian Amazon, where inland fisheries provide a critical source of nutrition for many of the region's 800,000 people. We found that the impacts of biodiversity loss on nutrient supplies depended on compensation, trophic dynamics, and functional diversity. When small sedentary species compensated for declines in large migratory species, fatty acid supplies increased, while zinc and iron supplies decreased. In contrast, the probability of failing to maintain supplies or nutrient supply risk increased when species were nutritionally unique. Our results show that trait-based regulations and public health polices need to consider biodiversity's vital role in sustaining nutritional benefits for over 2 billion people dependent on wild foods across the globe.

Trajectories of Systolic Blood Pressure in Children: Risk Factors and Cardiometabolic Correlates.

OBJECTIVE: To identify systolic blood pressure (SBP) percentile trajectories in children and to describe the early-life risk factors and cardiometabolic correlates of those trajectories. STUDY DESIGN: Using age-, sex-, and height-specific SBP percentiles based on the American Academy of Pediatrics reference, we examined SBP trajectories using latent class mixed models from ages 3 to 8 years (n = 844) from the Growing Up in Singapore Towards healthy Outcomes-study, a Singaporean mother-offspring cohort study. We analyzed associations between SBP trajectories and early-life risk factors using multinomial logistic regression and differences across trajectories in cardiometabolic outcomes using multiple linear regression. RESULTS: Children were classified into 1 of 4 SBP percentile trajectories: "low increasing" (15%), "high stable" (47%), "high decreasing" (20%), and "low stable" (18%). Maternal hypertension during early pregnancy was a predictor of the "high stable" and "low increasing" SBP trajectories. Rapid child weight gain in the first 2 years of life was only associated with the "high stable" trajectory. Compared with children in the "low stable" trajectory, children in the "high stable" SBP trajectory had greater body mass index z scores, sum of skinfold thicknesses, waist circumference from ages 3 to 8 years, and abdominal adipose tissue (milliliters) at 4.5 years (adjusted mean difference [95% CI]: superficial and deep subcutaneous abdominal adipose tissue: 115.2 [48.1-182.3] and 85.5 [35.2-135.8]). Their fat mass (kilograms) (1.3 [0.6-2.0]), triglyceride levels (mmol/L) (0.10 [0.02-0.18]), and homeostasis model assessment of insulin resistance (0.28 [0.11 0.46]) at age 6 years were also greater but not their arterial thickness and stiffness. CONCLUSIONS: Reducing maternal blood pressure during pregnancy and infant weight gain in the first 2 years of life might help to prevent the development of high SBP.