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Unraveling the cooperative mechanisms in ultralow copper-loaded WC@NGC for enhanced CO<sub>2</sub> electroreduction to acetic acid
No full textElectrochemical CO2 reduction reaction (eCO2RR) has been explored on tungsten carbide (WC) nanoparticles embedded on N-doped graphitic carbon (NGC), demonstrating excellent activity toward the formation of acetic acid at an extremely lower potential. The activity has been further enhanced by loading ultralow copper sites into the catalyst system, exhibiting 80.02% Faradaic efficiency (FE) toward acetic acid at an applied potential of -0.3 V (vs RHE). Potential-dependent in situ infrared (IR), X-ray photoelectron spectroscopy (XPS), Raman spectroscopy, ex situ extended X-ray absorption fine structure (EXAFS) studies, and computational analysis confirm that synergy between uniformly dispersed Cu atoms and WC lattice plays a crucial role in the formation of acetic acid with high FE at a lower potential. It has been observed that the W atom of WC strongly chemisorbs CO2 with a significant change in the C-O bond length and the O-C-O bond angle, in contrast to weaker adsorption on Cu-based catalyst surfaces. The presence of a Cu site enhances the adsorption of CO2, thereby increasing the possibility of C-C coupling kinetically. Most importantly, hydrogen evolution predominates on the catalyst’s surface at higher applied potentials (-0.5 to -1.1 V vs RHE), elucidating the mechanism underlying enhanced charge transfer between copper and WC, a phenomenon ascertained through in situ IR spectroscopy and ex situ XPS analysis
Lattice charge tuning-driven multi-carbon products from carbon dioxide
No full textMitigating global CO2 concentrations from anthropogenic sources through electrochemical conversion to value-added chemicals is the need of the hour. In this work, the fundamental concept of "Lattice Charge" has been strategically manipulated in materials to selectively produce multi-carbon products from greenhouse CO2 gas. To achieve this, a series of catalysts within a well-known ABX2 family (A = Ag, Cu; B = In, Ga, Fe; X = S, Se) have been explored, which exhibit significant activity toward the electrochemical CO2 reduction reaction (eCO2RR) and results in the formation of higher carbon chemicals including C3 products, acetone, and energy-dense isopropanol (FE = 24.5 ± 2.5%). The Hirshfeld charge analysis technique highlighted the structure-activity correlation and the importance of the optimized lattice charge distribution as a crucial tool to manipulate the eCO2RR product in electrocatalyst designs, and the real-time in situ ATR-FTIR technique probes the crucial intermediate species adsorbed during the CO2 reduction process
Novel Method of Calculation of Magnetic Resonance Imaging Perfusion and Comparison of Single versus Double Barrel Superficial Temporal Artery-Middle Cerebral Artery Bypass for Revascularisation in Moya Moya Disease
No full textObjective
Moyamoya disease (MMD) is characterized by supraclinoid internal carotid artery narrowing causing cerebral parenchyma to starve. Direct and indirect revascularisation techniques are the treatment norm. We provide a clinicoradiological comparison of single and double barrel superficial temporal artery to middle cerebral artery (STA-MCA) bypass for MMD. The perfusion in cerebral hemispheres and vessel density in digital subtraction angiography (DSA) have been evaluated using novel algorithms.
Methods
DSA, arterial spin labeling magnetic resonance imaging methods and Suzuki, Matsushima, Angiographic Outcome Score scales were used to quantify perfusion parameters; modified Rankin Score was used for clinical evaluation. A novel image processing algorithm was designed to perform analysis of arterial spin labeling sequences and compare perfusion. Vessel density was calculated using connected component analysis on thresholded DSA images.
Results
Fifty-four hemispheres with MMD underwent STA-MCA bypass 42(77.8%) single barrel and 12 (22.2%) double barrel. Clinical outcome—modified Rankin Score was significant with P < 0.001 in single barrel and P = 0.001 in double barrel groups. The overall Angiographic Outcome Score showed improvement postoperatively (P = 0.032). Perfusion analysis was performed in 20 hemispheres (13 single barrel; 7 double barrel). MCA territories showed significant improvement in single barrel (2.72%, P = 0.0294) and double barrel groups (12.89%, P = 0.025). Vessel density calculated in MCA territory, showed an overall postoperative improvement (P = 1.75 × 10–8).
Conclusion
Double barrel STA-MCA bypass clinically as well as radiologically improves perfusion in the ACA as well as MCA territories in MMD. The novel image processing algorithm is an accurate, objective tool to evaluate perfusion in magnetic resonance images and vessel density in DSA images of MMD
Imaging and MR Spectroscopy in Papillary Craniopharyngioma
No full textSellar-suprasellar masses exhibit a diverse range of differential diagnoses and it is feasible to establish a preliminary diagnosis before surgery by evaluating conventional CT scans and contrast-enhanced MRI results. Nevertheless, certain cases may present with inconclusive findings, making it challenging to anticipate the underlying tissue composition accurately through imaging alone. Researchers have explored the application of Proton MR spectroscopy in analyzing suprasellar tumors, and their investigations have revealed that it can complement traditional MRI by enhancing the accuracy of preoperative diagnoses. In this context, we report three biopsy-proven cases of suprasellar papillary craniopharyngioma where the MRS spectra derived from the solid component exhibited noticeable lipid peaks alongside reduced levels of choline and NAA. These findings played a pivotal role in facilitating the correct preoperative identification of papillary craniopharyngioma
Temporal variability in air temperature lapse rates across the glacierised terrain of the Chandra basin, western Himalaya
No full textThe air temperature lapse rate (TLR) is one of the essential parameters for glacio-hydrological studies. However, TLR estimations are limited in the glacierised regions of Himalaya due to a scarcity of long-term observations. Therefore, a dense in-situ monitoring network over a high Himalayan region is needed to estimate the TLR accurately. Here, in-situ air temperature data is obtained from Automatic Weather Stations (AWS) installed over the Chandra basin, western Himalaya, from October 2020 to September 2022. This data is used to estimate the TLR by regressing the air temperature with the corresponding elevations. We estimated the mean annual TLR of 3.8 ± 0.3 °C km-1 for the entire Chandra basin, significantly less than the standard environmental lapse rate (6.5 °C km-1). We found substantial seasonal variability in each TLR time series. The maximum TLR is 5.8 ± 0.2 °C km-1 during the summer, and the minimum is -1.6 ± 0.1 °C km-1 during winter, comparing all the meteorological stations. Further, we observe strong diurnal fluctuations of TLR, which has maximum and minimum values during 10:00 to 18:00 hrs and 20:00 to 09:00 hrs, respectively. The study highlights that the temporal variability of TLR is site-specific and strongly correlated with wind speed, relative humidity, and radiation fluxes. Furthermore, a temperature-index model is used to assess the implications of TLR by estimating glacier mass balance. This study highlights the importance of considering observed TLR to accurately model surface mass balance over the glacierised Himalayan region
Forest carbon stock-based bioeconomy: Mixed models improve accuracy of tree biomass estimates
No full textTree biomass and carbon stock continue to be the most important contributors to a forest-based bioeconomy. Accurate estimation of tree biomass and carbon stock therefore is crucial for planning a sustainable bioeconomy based on sustained forest bioresource production and harvest. Precise carbon accounting is also of fundamental importance for a green carbon market as well as for an improved model of quantitative global carbon cycle. However, estimating biomass and carbon at a large spatial scale without causing significant environmental disruption has been posing a methodological challenge necessitating to evolve a robust yet accurate estimation method. Although forest-specific generalized allometric models are the most widely used method to estimate forest tree biomass and carbon stock, these either under- or over-estimate the values, particularly in mixed-species forests. To address this challenge, we employed mixed equations that included species-specific models or available models for a sister species that provided a more conservative estimate of stand-level tree biomass and carbon compared to the generalized equations. We gathered primary data on tree girth and height at the stand level from sub-tropical and temperate forests of Tawang river basin, Arunachal Pradesh, India for validation. We compiled 32 equations comprising 27 species-specific and 5 forest-specific generalized models from a global dataset of allometric models. The outputs from the mixed models were comparable with the results of the harvest studies conducted by other researchers in similar forest types validating the efficacy of mixed models at a landscape scale
Microtubule-Targeting NAP Peptide-Ru(II)-polypyridyl Conjugate As a Bimodal Therapeutic Agent for Triple Negative Breast Carcinoma
No full textTriple-negative breast cancer (TNBC) poses significant treatment challenges due to its high metastasis, heterogeneity, and poor biomarker expression. The N-terminus of an octapeptide NAPVSIPQ (NAP) was covalently coupled to a carboxylic acid derivative of Ru(2,2'-bipy) 3+2 (Rubpy) to synthesize an N-stapled short peptide-Rubpy conjugate (Ru-NAP). This photosensitizer (PS) was utilized to treat TNBC through microtubule (MT) targeted chemotherapy and photodynamic therapy (PDT). Ru-NAP formed more elaborate molecular aggregates with fibrillar morphology as compared to NAP. A much higher binding affinity of Ru-NAP over NAP toward β-tubulin (KRU-NAP: (6.8 ± 0.55) × 106 M-1; KNAP: (8.2 ± 1.1) × 104 M-1) was observed due to stronger electrostatic interactions between the MT with an average linear charge density of ∼85 e/nm and the cationic Rubpy part of Ru-NAP. This was also supported by docking, simulation, and appropriate imaging studies. Ru-NAP promoted serum stability, specific binding of NAP to the E-site of the βIII-tubulin followed by the disruption of the MT network, and effective singlet oxygen generation in TNBC cells (MDA-MB-231), causing cell cycle arrest in the G2/M phase and triggering apoptosis. Remarkably, MDA-MB-231 cells were more sensitive to Ru-NAP compared to noncancerous human embryonic kidney (HEK293 cells) when exposed to light (LightIC50RU-NAP [HEK293]: 17.2 ± 2.5 μM, compared to LightIC50 RU-NAP [MDA-MB-231]: 32.5 ± 7.8 nM, DarkIC50RU-NAP [HEK293]: > 80 μM, compared to DarkIC50RU-NAP [MDA-MB-231]: 2.9 ± 0.5 μM). Ru-NAP also effectively inhibited tumor growth in MDA-MB-231 xenograft models in nude mice. Our findings provide strong evidence that Ru-NAP has a potential therapeutic role in TNBC treatment
Flash Drought Intensification due to Enhanced Land–Atmospheric Coupling in India
No full textLand–atmospheric feedback influences the occurrence and severity of flash droughts. However, the observed and projected changes in flash droughts and associated land–atmospheric coupling have not been examined over India. Moreover, the causes of the rapid depletion of soil moisture during flash droughts are not well known. We identify major flash droughts and associated soil moisture–vapor pressure deficit (SM–VPD) coupling in India using ERA5 and simulations from global climate models (CMIP6-GCMs). The summer monsoon season (June–September) witnesses more than 60% of the flash drought events and a relatively higher rate of flash drought development. The flash drought frequency has mainly decreased during India’s observed climate (1980–2019), which is projected to decline further in the future warming climate. On the other hand, the flash drought development rate has significantly increased during the observed period, which is projected to enhance further under the warming climate. SM–VPD coupling during the flash drought onset-development phase is considerably higher (threefold to fivefold) than during the normal condition (in the absence of flash drought). The high (low) SM–VPD coupling explains the faster (slower) flash drought development rate in the observed and future warming climate. The strength of SM–VPD coupling has increased in the recent period and is projected to increase further in the future warming climate. The increased SM–VPD coupling can intensify future flash droughts in India, especially during the summer monsoon season, with considerable implications for agriculture, water resources, and ecosystems.
Significance Statement
This study aims to understand better the role of land–atmospheric coupling in explaining flash drought characteristics (frequency and development rate) in India. Strong land–atmospheric (SM–VPD) feedback might influence the regional weather patterns during flash drought, which often negatively impacts humans and the ecosystem. We explain the causes and drivers of increasing (decreasing) flash drought development rate (frequency) in India. The long-term change in SM–VPD coupling drives the frequency of flash drought, whereas an anomalous instantaneous change in coupling controls the flash drought development rate. More intense flash droughts contributed by the increased land–atmospheric coupling are projected in the future. Predicting the SM–VPD coupling metric can facilitate more time for preparedness, resulting in minimizing the flash drought impacts
Summer Monsoon Drying Accelerates India's Groundwater Depletion Under Climate Change
No full textGroundwater in north India remains a vital food and water security resource for more than one billion people. Both summer monsoon drying, and winter warming pose considerable challenges for rapidly declining groundwater. However, their impacts on irrigation water demands and groundwater storage under the observed and projected future climate remain unexplored. Using in situ observations, satellite data, and a hydrological model that considers the role of irrigation and groundwater pumping, we show that summer monsoon drying and winter warming accelerate groundwater depletion in north India during the observed climate, which will continue in the projected future climate. Summer monsoon precipitation has significantly (P-value = 0.04) declined (∼8%) while winters have become warmer in north India during 1951–2021. Both satellite (GRACE/GRACE-FO) and hydrological model-based estimates show a rapid groundwater depletion (∼1.5 cm/year) in north India with a net loss of 450 km3 of groundwater during 2002–2021. The summer monsoon drying followed by winter warming cause a substantial reduction in groundwater storage due to reduced groundwater recharge and enhanced pumping to meet irrigation demands. Summer monsoon drying and winter warming will continue to affect groundwater storage in north India in the future. For instance, summer monsoon drying (10%–15% deficit for near-far periods) followed by substantial winter warming (1–4°C) in the future will further accelerate groundwater depletion by increasing (6%–20%) irrigation water demands and reducing groundwater recharge (6%–12%). Groundwater sustainability measures including reducing groundwater abstraction and enhancing the groundwater recharge during the summer monsoon seasons are needed to ensure future agricultural production
MCL-079 survival prediction models (AIIMS mantle cell lymphoma overall survival [AMOS] score and AIIMS mantle cell lymphoma event-free survival [AMES] score) for patients with mantle cell lymphoma from Indian population
No full textContext:
Mantle cell lymphoma (MCL) in Southeast Asia specifically among Indian population presents in advanced stage with bulky disease, significant extranodal involvement, and poor ECOG PS. Indigenous survival prediction models for this part of the world are lacking.
Objective:
Development of prediction models for overall survival (OS) and event-free survival (EFS) in Indian MCL patients.
Design, Setting and Study Participants
We analyzed ambispective clinical data of 90 MCL patients treated January 2013-December 2023 at Dr. B.R. Ambedkar Institute Rotary Cancer Hospital, All India Institute of Medical Sciences (AIIMS), New Delhi, India.
Outcome Measures:
Statistical analysis performed using STATA 13.0. Clinical and laboratory correlates of OS and EFS with P<.2 in univariate logistic regression analysis were included in multivariate analysis. Predictive models (AMOS and AMES scores) were developed using coefficients of variables from regression models. Receiver operating characteristic (ROC) curve analysis was used to set optimal cutoff for both models. Performance of cutoffs was reported using sensitivity, specificity. P<.05 defined statistical significance.
Results:
In multivariate analysis; age >60 years (a), presence of B symptoms (b), ECOG PS ≥2 (c), splenomegaly (d), LDH ≥ULN (e), and nonuse of rituximab maintenance (f) were significantly associated with no OS and no EFS at 1 year; male sex (g) was associated with no OS at 1 year. Each variable (a-g) was dichotomized to have a score of 0 (if variables were as mentioned above) or 1. AMOS score calculated as 18.9(a) + 20.4(b) + 10.0(c) + 11.1(d) + 19.4(e) + 33.3(f) + 14.9(g). AMES score calculated as 17.8(a) + 14.9(b) + 10.0(c) + 15.0(d) + 13.8(e) + 21.1(f). Mean (±SD) AMOS score 59.8 (±28.3); optimal cutoff at 48.8. AMOS score ≥48.8 had sensitivity, specificity of 86.0%, 81.0%, respectively, to predict OS at 1 year. Mean (±SD) AMES score 46.8 (±22.6); optimal cutoff at 42.2. AMES score ≥42.2 had sensitivity, specificity of 75.0%, 85.0%, respectively, to predict EFS at 1 year. Area under ROC (AUROC) for AMOS and AMES models were 0.86 and 0.91, respectively.
Conclusions:
AMOS and AMES scores are indigenous models with high predictive capacity for OS and EFS, respectively, in patients of MCL from this part of the world. This exemplifies their utility to predict survival outcome in MCL patients