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Factors Impacting Abandonment In Patients With Newly Diagnosed Retinoblastoma In India: Analysis From INPHOG RB-19-01 Study
No full textIntroduction: Treatment abandonment continues to be one of the major causes of treatment-failure for children with newly-diagnosed Retinoblastoma in India. To improve outcomes for retinoblastoma, it is essential that we understand the risk factors for abandonment in our setting and address them systematically. INPHOG RB-19-01, is the first multicentric, collaborative study from India for retinoblastoma. One of the key objectives was to quantify abandonment prospectively and evaluate factors impacting the same. Abandonment was defined as a missed/ delayed scheduled visit for treatment for over four weeks.
Methodology: All centres that treat RB were invited to participate in the study subject to approval from institutional ethics committees. Clinical and epidemiological data was collected with regards to age, gender, laterality, stage, socio-economic status, educational status of parents, distance from treatment centre, family history and whether enucleation was offered and their impact on abandonment assessed. The study was registered with CTRI India (CTRI/2020/09/027846).
Results: A total of 1120 patients were enrolled from 20 centres over 36 months (September 2020-September 2023). The median age at diagnosis was 24 months, M:F:: 1.42:1. Patients were staged as Stages 0, I, II, III, IV in 44.6%, 30.2%, 2.1%, 15%, 8% patients respectively. A total of 82 (7.3%) patients abandoned treatment. Over 50% of these abandoned treatment > 3 months from start of treatment. Abandonment was higher for female patients (p:.018) and those with bilateral (p:0.008)/ extraocular disease (p:0.009). There was inverse correlation with higher distance (<0.05), SES (<0.05) and parental educational status (p:<0.05). There was no correlation with age, family history or enucleation being offered.
Conclusion: The study reports the lowest abandonment to date for retinoblastoma in India. Nevertheless, it continues to be a significant issue. The timing highlights missed opportunities for interventions to prevent abandonment. Enhanced, multipronged efforts are needed to limit abandonment further
3D Segmentation of Whole Lung and Metastatic Lung Nodules Using Adaptive Region Growing and Shape-based Morphology
No full textObjective:
Early diagnosis of primary and metastatic lung nodules is critical for effective therapeutic planning. Manual delineation of lung nodules is not time-efficient and is prone to human error as well as interobserver and intraobserver variability. This study aimed to address the unmet need for an open-source computer-aided detection (CAD) system for 3D segmentation of lung and metastatic lung nodules along with radiomic feature extraction.
Methods:
The proposed adaptive region-growing-based lung nodule segmentation (RGLNS) tool was developed in-house, requiring only manual input to select a seed point within the nodule on computed tomography (CT) images. A total of 230 CT scans from 100 patients with sarcomas were screened. Lung nodules were present in 200 CT scans, which were further analyzed. The accuracy of the lung and nodule segmentation was evaluated qualitatively using a 5-point Likert scale (uninterpretable: 1; poor: 2; fair: 3; good: 4; excellent: 5) and quantitatively using the Dice coefficient and Jaccard index.
Results:
A total of 200 CT scans comprising 12,000 CT slices were analyzed, among which 786 lung nodules were identified. Quantitative lung segmentation accuracies (n=2400 slices) yielded a Dice coefficient of 0.92±0.06 and a Jaccard index of 0.85±0.05. Qualitative scores (n=9600 slices) for lung boundary correction (4.56±1.18) and inclusion of pulmonary vessels (4.75±0.72) were rated as good to excellent. Quantitative nodule segmentation (n=142 nodules) accuracies were as follows: dice coefficient=0.92±0.03, 0.88±0.04, 0.86±0.03, 0.85±0.03, 084±0.04 and Jaccard index=0.84±0.03, 0.81±0.04, 0.78±0.04, 0.78±0.02, 0.76±0.04 for solitary (n=73), juxtapleural (n=32), juxtavascular (n=28), fissure-attached (n=6), and ground-glass (n=6) nodules, respectively. Qualitative scores (n=644 nodules) for nodule-boundary were good to excellent [solitary (n=342): 4.97±0.15; juxtapleural (n=155): 4.45±0.60; juxtavascular (n=127): 4.40±0.65; fissure-attached (n=9): 4.40±0.70; ground-glass (n=11): 4.25±0.75] and for exclusion of pulmonary vessels/pleura from nodules were good [juxtapleural (n=155): 4.10±0.66; juxtavascular (n=127): 4.08±0.64; fissure-attached (n=9): 4.30±0.67].
Conclusions:
The proposed semiautomated CAD system, RGLNS, requiring minimal manual input, demonstrated robust, and promising segmentation results for the whole lung and various types of metastatic lung nodules
High-fidelity QND readout and measurement back-action in a tantalum-based high-coherence fluxonium qubit
No full textImplementing a precise measurement of the quantum state of a qubit is critical for building a practical quantum processor, as it plays an important role in state initialization and quantum error correction. While the transmon qubit has been the most commonly used design in small- to medium-scale processors, the fluxonium qubit is emerging as a strong alternative with the potential for high-fidelity gate operation as a result of the high anharmonicity and high coherence achievable due to its unique design. Here, we explore the measurement characteristics of a tantalum-based high-coherence fluxonium qubit and demonstrate single-shot measurement fidelity (assignment fidelity) of 96.2% ± 0.5% and 97.8% ± 0.4% without and with the use of a Josephson parametric amplifier, respectively. We study the back-action of the measurement photons on the qubit and measure a QND fidelity of 99.0% ± 0.3%. We find that the measurement fidelity and the QND nature are limited by state-mixing errors, and our results suggest that a careful study of measurement-induced transitions in the fluxonium is needed to further optimize the readout performance
Possibilities for enhanced electron-phonon interactions and high- <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"><mml:msub><mml:mi>T</mml:mi><mml:mi>c</mml:mi></mml:msub></mml:math> superconductivity in engineered bimetallic nanostructured superlattices
No full textWe explore theoretically the properties of engineered bimetallic nanostructured superlattices where an array of nanoclusters of a simple (single band) metal are embedded periodically inside another simple metal with a different work function. The exploration is done using a simplified tight-binding model with Coulomb interactions included, and also density functional theory. Taking arrays of Ag clusters of fixed sizes and configurations (when unrelaxed) embedded periodically in a Au matrix as an example, we show that a significant enhancement of electron-phonon interactions ensues, implying possibilities for high superconductivity. The enhancement stems from a strong coupling, via Coulomb interactions, between the dipolar charge distribution that forms at the Au-Ag interfaces and the breathing and other modes of vibration of the light Ag atoms caged inside the heavier Au matrix. The interface dipoles form because of the interplay between the mismatch of the local potential seen by the conduction electrons localized in Wannier orbitals at the Ag and Au sites (the Ag sites being slightly repulsive relative to the Au sites) and the (long-range) Coulomb repulsion between electrons occupying these Wannier orbitals. We also discuss the DC transport in such systems
Improving Streamflow Prediction Using Multiple Hydrological Models and Machine Learning Methods
No full textStreamflow prediction is crucial for flood monitoring and early warning, which often hampered by bias and uncertainties arising from nonlinear processes, model parameterization, and errors in meteorological forecast. We examined the utility of multiple hydrological models (VIC, H08, CWatM, Noah-MP, and CLM) and machine learning (ML) methods to improve streamflow simulations and prediction. The hydrological models (HMs) were forced with observed meteorological data from the India Meteorological Department (IMD) and meteorological forecast from the Global Ensemble Forecast System (GEFS) to simulate flood peaks and flood inundation areas. We used Multiple Linear Regression, Random Forest (RF), Extreme Gradient Boosting (XGB), and Long Short-Term Memory (LSTM) for the post-processing of simulated streamflow from HMs. Considering the influence of dams is crucial for the effectiveness of HMs and ML methods for improving streamflow simulations and predictions. In addition, ML-based multi-model ensemble streamflow from HMs performs better than individual models, highlighting the need for multi-model-based streamflow forecast systems. The post-processing of streamflow simulated by the hydrological models using ML significantly improved overall streamflow simulations, with limited improvement in high-flow conditions. The combination of physics-based hydrological models, observed climate data, and ML methods improve streamflow predictions for flood magnitude, timing, and inundated area, which can be valuable for developing flood early warning systems in India
Migrant Laborers in India Face Increased Heat Stress Driven by Climate Warming and ENSO Variability
No full textMigrant laborers typically work long hours at physically demanding tasks without air conditioning, and they account for a considerable fraction of India's population—a share that is increasing with urban growth. However, changes in heat stress and labor capacity in major urban centers that attract rural-to-urban work migrants remain unexplored. Moreover, it remains unclear how the increased heat stress and reduced labor capacity under the warming climate will alter the most preferred workplaces for migrant laborers in India. Here, we use station-based observations, reanalysis data, and climate model projections to reconstruct trends and variability in heat stress metrics, including wet-bulb temperature for indoor exposure and wet-bulb globe temperature for outdoor exposure based on migrant data from the 2011 Census. We show that during 1980–2021, most rural-to-urban migration hotspots in north, east, and southern India witnessed a significant (p < 0.05) rise in Tw, indicating elevated indoor heat stress. Over that interval, outdoor heat stress has considerably increased and led to a ∼10% decline in labor capacity in these hotspots. A substantial rise in the indoor and outdoor heat stress exposure of migrants and a reduction in their physical labor capacity is projected with each additional degree of global warming. El Niño-Southern Oscillation variability can also significantly enhance these effects. Effective mitigation and adaptation options are needed to reduce the risks migrant workers face due to increasing indoor and outdoor heat stress in India
Power-law rheology on mass transport of neutral solute induced by mixed electroosmotic flow through rough microtube with porous wall.
No full textIn this work, the mass transport properties of a neutral solute in a rough microtube with a porous wall under the combined influence of both pressure and electric fields for non-Newtonian power-law fluids are examined. This investigation explores the effect of various microtube roughness patterns, such as sinusoidal, triangular, and rectangular, as well as different flow behavior indices, on solute mass transport behavior. The Poisson–Boltzmann equation, Cauchy momentum equation, and species conservation equation were solved computationally for different roughness profiles to assess the distribution of electric potential, velocity, and concentration fields. Higher relative roughness amplitude (δ = 0.1) and roughness wavenumber (λ = 12) reduced the average cross-sectional velocity by 31% for the dilatant solution, leading to improved permeation. The influence of roughness parameters (δ and λ) and the flow behavior index (n) on solute permeation mass flux was quantified. For the dilatant case, solute mass flux was enhanced by employing rectangular, sinusoidal, and triangular roughness profiles compared to the smooth porous wall by 19%, 9%, and 8% for assisting flow and 16%, 13%, and 11% for opposing flow. In fact, the highest mass flux effectiveness (ξ) for solute delivery was observed for the dilatant fluid with rectangular roughness in assisting flow. It is anticipated that the results of this study will provide valuable insights for the design of specialized drug delivery systems using microfluidic channels and contribute to a better understanding of nutrient transport in physiological systems
An overview of leather processing industry.
No full textLeather processing is one of the oldest and largest industry leading to significant employment generation. It involves a series of unit operations, involving mostly various inorganic chemicals. Every step generates huge amount of wastewater, typically characterized by high total dissolved and suspended solids, high chemical and biological oxygen demand. This chapter outlines the processing steps involved in a leather industry and characteristics of the wastewater emerging from each operating step. The chapter would also provide the possible outlines of treatment technologies to be adopted for the treatment of tannery wastewater keeping in view the sustainability of the adopted technologies addressing the concepts of zero liquid discharge and circular economy
Dynamical signature of the onset of sol-gel phase transition in aqueous solutions of hydrophobically modified poly(acrylic acid)-based copolymers.
No full textSol-gel transition-driven relaxation dynamics of aqueous solutions of rationally designed polyacrylic acid (PAA)-based copolymers with hydrophobic modifications were explored by employing time-resolved fluorescence and MHz–GHz dielectric relaxation (DR) measurements. This sol-gel transition driven dynamics was monitored over an incubation period of 30 days, as these systems were found to undergo gelation after a few weeks. The designed PAA-based homo (P0), hydrophobically modified (∼4%) copolymers (P4, P6), and their coumarin 343 (C343) attached analogous copolymers (P4′, P6′) were synthesized by reversible addition–fragmentation chain transfer polymerization and characterized by 1H NMR spectroscopy and size exclusion chromatography (SEC). Dynamic light scattering experiments of aqueous copolymer solutions showed a gradual increment of hydrodynamic diameter (Dh) up to ∼4000 nm, and the onset of sol-gel transition was estimated by locating the intersection of two distinct slopes produced by the plots of average Dh as a function of incubation time. The sol-gel transition for these copolymer solutions (aqueous) was clearly demonstrated by the progressive slowing down of DR times and the rotational fluorescence anisotropy times tracked over the entire incubation period. Interestingly, the onset time for the sol-gel transition was found to be insensitive to the chemical binding of the fluorescent probe to these polymers. A comparison between the steady state UV–VIS absorption and fluorescence spectral characteristics of aqueous solutions of these copolymers with chemically bound and externally added C343 suggested that the sol-gel transition involved polymer aggregation. This study may be useful for designing supramolecular polymer gels for biomedical applications
Reactivity ratio study for the cationic copolymerization of vinyl ethers with 2,3-dihydrofuran.
No full textTo understand the monomer distribution in the copolymers from the cationic copolymerization of vinyl ethers (VEs) with 2,3-dihydrofuran (DHF), the reactivity ratios of VEs (rVE) and DHF (rDHF) were determined. The copolymer compositions were calculated from 1H NMR spectroscopy, which were used to determine the reactivity ratios from the extended Kelen-Tüdós (extended K-T) method at high monomer conversion. Furthermore, the effect of solvent (hexane and toluene), temperature (0, −20, and −40 °C), Lewis acid (SnCl4 and TiCl4) and alkyl groups in VE monomers (iso-butyl vinyl ether (iBVE), propyl vinyl ether (PVE), and n-butyl vinyl ether (nBVE)) were studied in detail on the reactivity ratios of monomers during the cationic copolymerization of VEs with DHF. The two monomers in every case were randomly placed along the copolymer chain. This article demonstrates the scope of copolymer synthesis of VEs with DHF and their microstructure analysis