We made the first ever successful effort in India to detect the genetic material of SARS-CoV-2 viruses to understand the capability and application of wastewater-based epidemiology (WBE) surveillance ...in India. Sampling was carried out on 8 and 27 May 2020 at the Old Pirana Waste Water Treatment Plant (WWTP) at Ahmedabad, Gujarat that receives effluent from Civil Hospital treating COVID-19 patients. All three, i.e. ORF1ab, N and S genes of SARS-CoV-2, were found in the influent with no genes detected in effluent collected on 8 and 27 May 2020. Increase in SARS-CoV-2 genetic loading in the wastewater between 8 and 27 May 2020 samples concurred with corresponding increase in the number of active COVID-19 patients in the city. The number of gene copies was comparable to that reported in untreated wastewaters of Australia, China and Turkey and lower than that of the USA, France and Spain. However, temporal changes in SARS-CoV-2 RNA concentrations need to be substantiated further from the perspectives of daily and short-term changes of SARS-CoV-2 in wastewater through long-term monitoring. The study results SARS-CoV-2 will assist concerned authorities and policymakers to formulate and/or upgrade COVID-19 surveillance to have a more explicit picture of the pandemic curve. While infectivity of SARS-CoV-2 through the excreted viral genetic material in the aquatic environment is still being debated, the presence and detection of genes in wastewater systems makes a strong case for the environmental surveillance of the COVID-19 pandemic.
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•First ever report of the presence of gene of SARS-CoV-2 in the wastewater in India.•CT value is explicitly indicative of the increase of COVID-19 patient in the vicinity.•All three i.e. ORF1ab, N and S genes of SARS-CoV-2 were discerned in the influents.•None of three genes were spotted in the effluent collected on 8 and 27 May 2020.•Increase in the SARS-CoV-2 genetic loading concurred with active COVID-19 patient.
Learning meaningful representations of free-hand sketches remains a challenging task given the signal sparsity and the high-level abstraction of sketches. Existing techniques have focused on ...exploiting either the static nature of sketches with convolutional neural networks (CNNs) or the temporal sequential property with recurrent neural networks (RNNs). In this work, we propose a new representation of sketches as multiple sparsely connected graphs. We design a novel graph neural network (GNN), the multigraph transformer (MGT), for learning representations of sketches from multiple graphs, which simultaneously capture global and local geometric stroke structures as well as temporal information. We report extensive numerical experiments on a sketch recognition task to demonstrate the performance of the proposed approach. Particularly, MGT applied on 414k sketches from Google QuickDraw: 1) achieves a small recognition gap to the CNN-based performance upper bound (72.80% versus 74.22%) and infers faster than the CNN competitors and 2) outperforms all RNN-based models by a significant margin. To the best of our knowledge, this is the first work proposing to represent sketches as graphs and apply GNNs for sketch recognition. Code and trained models are available at https://github.com/PengBoXiangShang/multigraph_transformer .
Wastewater-based Epidemiological (WBE) surveillance offers a promising approach to assess the pandemic situation covering pre-symptomatic and asymptomatic cases in highly populated area under limited ...clinical tests. In the present study, we analyzed SARS-CoV-2 RNA in the influent wastewater samples (n = 43) from four wastewater treatment plants (WWTPs) in Gandhinagar, India, during August 7th to September 30th, 2020. A total of 40 samples out of 43 were found positive i.e. having at least two genes of SARS-CoV-2. The average Ct values for S, N, and ORF 1 ab genes were 32.66, 33.03, and 33.95, respectively. Monthly variation depicted a substantial rise in the average copies of N (~120%) and ORF 1 ab (~38%) genes in the month of September as compared to August, while S-gene copies declined by 58% in September 2020. The SARS-CoV-2 genome concentration was higher in the month of September (~924.5 copies/L) than August (~897.5 copies/L), corresponding to a ~2.2-fold rise in the number of confirmed cases during the study period. Further, the percentage change in genome concentration level on a particular date was found in the lead of 1–2 weeks of time with respect to the official confirmed cases registered based on clinical tests on a temporal scale. The results profoundly unravel the potential of WBE surveillance to predict the fluctuation of COVID-19 cases to provide an early warning. Our study explicitly suggests that it is the need of hour that the wastewater surveillance must be included as an integral part of COVID-19 pandemic monitoring which can not only help the water authorities to identify the hotspots within a city but can provide up to 2 weeks of time lead for better tuning the management interventions.
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•Study unravels the early warning potential of wastewater based surveillance of COVID-19.•Adequate SARS-CoV-2 RNA were detected despite of limited reported case in the vicinity.•Up to 2 weeks of lead is possible from a regular wastewater based COVID-19 surveillance.•SARS-CoV-2 RNA was higher in September than August in response to a ~2.2-fold rise in COVID-19 active cases.
For the first time, we present, i) an account of decay in the genetic material loading of SARS-CoV-2 during Upflow Anaerobic Sludge Blanket (UASB) treatment of wastewater, and ii) comparative ...evaluation of polyethylene glycol (PEG), and ultrafiltration as virus concentration methods from wastewater for the quantification of SARS-CoV-2 genes. The objectives were achieved through tracking of SARS-CoV-2 genetic loadings i.e. ORF1ab, N and S protein genes on 8th and 27th May 2020 along the wastewater treatment plant (106000 m3 million liters per day) equipped with UASB system in Ahmedabad, India. PEG method performed better in removing materials inhibiting RT-qPCR for SARS-CoV-2 gene detection from the samples, as evident from constant and lower CT values of control (MS2). Using the PEG method, we found a reduction >1.3 log10 reduction in SARS-CoV-2 RNA abundance during UASB treatment, and the RNA was not detected at all in the final effluent. The study implies that i) conventional wastewater treatment systems is effective in SARS-CoV-2 RNA removal, and ii) UASB system significantly reduces SARS-CoV-2 genetic loadings. Finally, PEG method is recommended for better sensitivity and inhibition removal during SARS-CoV-2 RNA quantification in wastewater.
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•First report of the decay of SARS-CoV-2 gene during UASB treatment•Polyethylene glycol method had superior inhibition removal than filtration method.•The viral genetic loading reduction during UASB treatment was more than 1.3 log10.•Higher RNA loading in the influent on 27th May 2020 translated into higher reduction.
Knowledge distillation (KD) is a learning paradigm for boosting resource-efficient graph neural networks (GNNs) using more expressive yet cumbersome teacher models. Past work on distillation for GNNs ...proposed the local structure preserving (LSP) loss, which matches local structural relationships defined over edges across the student and teacher's node embeddings. This article studies whether preserving the global topology of how the teacher embeds graph data can be a more effective distillation objective for GNNs, as real-world graphs often contain latent interactions and noisy edges. We propose graph contrastive representation distillation (G-CRD), which uses contrastive learning to implicitly preserve global topology by aligning the student node embeddings to those of the teacher in a shared representation space. Additionally, we introduce an expanded set of benchmarks on large-scale real-world datasets where the performance gap between teacher and student GNNs is non-negligible. Experiments across four datasets and 14 heterogeneous GNN architectures show that G-CRD consistently boosts the performance and robustness of lightweight GNNs, outperforming LSP (and a global structure preserving (GSP) variant of LSP) as well as baselines from 2-D computer vision. An analysis of the representational similarity among teacher and student embedding spaces reveals that G-CRD balances preserving local and global relationships, while structure preserving approaches are best at preserving one or the other.
The use of nanoparticles as biomaterials in dentistry Bapat, Ranjeet A.; Joshi, Chaitanya P.; Bapat, Prachi ...
Drug discovery today,
January 2019, 2019-Jan, 2019-01-00, 20190101, Volume:
24, Issue:
1
Journal Article
Peer reviewed
•Nanoparticle (NP) applications have become useful in endodontics, periodontics, oral surgery and dental imaging.•NPs have been widely used in dentistry due to its antimicrobial action on controlling ...of oral biofilm.•Use of polymeric and metallic NPs into dental biomaterials improves its mechanical, physical & biological properties.
Maintenance of oral health is a major challenge in dentistry. Different materials have been used to treat various dental diseases, although treatment success is limited by features of the biomaterials used. To overcome these limitations, materials incorporated with nanoparticles (NPs) can be used in dental applications including endodontics, periodontics, tissue engineering, oral surgery, and imaging. The unique properties of NPs, including their surface:volume ratio, antibacterial action, physical, mechanical, and biological characteristics, and unique particle size have rendered them effective vehicles for dental applications. In this review, we provide insights into the various applications of NPs in dentistry, including their benefits, limitations, properties, actions and future potential.
This review explores the benefits of incorporating various types of nanoparticle into dental biomaterials and their applications in different fields of dentistry.
Breastfeeding undoubtedly provides important benefits to the mother-infant dyad and should be encouraged. Mastitis, one of the common but major cause of premature weaning among lactating women, is an ...inflammation of connective tissue within the mammary gland. This study reports the influence of mastitis on human milk microbiota by utilizing 16 S rRNA gene sequencing approach. We sampled and sequenced microbiome from 50 human milk samples, including 16 subacute mastitis (SAM), 16 acute mastitis (AM) and 18 healthy-controls. Compared to controls, SAM and AM microbiota were quite distinct and drastically reduced. Genera including, Aeromonas, Staphylococcus, Ralstonia, Klebsiella, Serratia, Enterococcus and Pseudomonas were significantly enriched in SAM and AM samples, while Acinetobacter, Ruminococcus, Clostridium, Faecalibacterium and Eubacterium were consistently depleted. Further analysis of our samples revealed positive aerotolerant odds ratio, indicating dramatic depletion of obligate anaerobes and enrichment of aerotolerant bacteria during the course of mastitis. In addition, predicted functional metagenomics identified several gene pathways related to bacterial proliferation and colonization (e.g. two-component system, bacterial secretion system and motility proteins) in SAM and AM samples. In conclusion, our study confirmed previous hypothesis that mastitis women have lower microbial diversity, increased abundance of opportunistic pathogens and depletion of commensal obligate anaerobes.
Neurological diseases and disorders (NDDs) present a significant societal burden and currently available drug- and biological-based therapeutic strategies have proven inadequate to alleviate it. Gene ...therapy is a suitable alternative to treat NDDs compared to conventional systems since it can be tailored to specifically alter select gene expression, reverse disease phenotype and restore normal function. The scope of gene therapy has broadened over the years with the advent of RNA interference and genome editing technologies. Consequently, encouraging results from central nervous system (CNS)-targeted gene delivery studies have led to their transition from preclinical to clinical trials. As we shift to an exciting gene therapy era, a retrospective of available literature on CNS-associated gene delivery is in order. This review is timely in this regard, since it analyzes key challenges and major findings from the last two decades and evaluates future prospects of brain gene delivery. We emphasize major areas consisting of physiological and pharmacological challenges in gene therapy, function-based selection of a ideal cellular target(s), available therapy modalities, and diversity of viral vectors and nanoparticles as vehicle systems. Further, we present plausible answers to key questions such as strategies to circumvent low blood-brain barrier permeability and most suitable CNS cell types for targeting. We compare and contrast pros and cons of the tested viral vectors in the context of delivery systems used in past and current clinical trials. Gene vector design challenges are also evaluated in the context of cell-specific promoters. Key challenges and findings reported for recent gene therapy clinical trials, assessing viral vectors and nanoparticles are discussed from the perspective of bench to bedside gene therapy translation. We conclude this review by tying together gene delivery challenges, available vehicle systems and comprehensive analyses of neuropathogenesis to outline future prospects of CNS-targeted gene therapies.
Dual-comb spectroscopy is a powerful technique for real-time, broadband optical sampling of molecular spectra, which requires no moving components. Recent developments with microresonator-based ...platforms have enabled frequency combs at the chip scale. However, the need to precisely match the resonance wavelengths of distinct high quality-factor microcavities has hindered the development of on-chip dual combs. We report the simultaneous generation of two microresonator combs on the same chip from a single laser, drastically reducing experimental complexity. We demonstrate broadband optical spectra spanning 51 THz and low-noise operation of both combs by deterministically tuning into soliton mode-locked states using integrated microheaters, resulting in narrow (<10 kHz) microwave beat notes. We further use one comb as a reference to probe the formation dynamics of the other comb, thus introducing a technique to investigate comb evolution without auxiliary lasers or microwave oscillators. We demonstrate high signal-to-noise ratio absorption spectroscopy spanning 170 nm using the dual-comb source over a 20-μs acquisition time. Our device paves the way for compact and robust spectrometers at nanosecond time scales enabled by large beat-note spacings (>1 GHz).
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