Deep-learning enabled ultrasound based detection of gallbladder cancer in northern India: a prospective diagnostic study.

Background: Gallbladder cancer (GBC) is highly aggressive. Diagnosis of GBC is challenging as benign gallbladder lesions can have similar imaging features. We aim to develop and validate a deep learning (DL) model for the automatic detection of GBC at abdominal ultrasound (US) and compare its diagnostic performance with that of radiologists. Methods: In this prospective study, a multiscale, second-order pooling-based DL classifier model was trained (training and validation cohorts) using the US data of patients with gallbladder lesions acquired between August 2019 and June 2021 at the Postgraduate Institute of Medical Education and research, a tertiary care hospital in North India. The performance of the DL model to detect GBC was evaluated in a temporally independent test cohort (July 2021-September 2022) and was compared with that of two radiologists. Findings: The study included 233 patients in the training set (mean age, 48 ± (2SD) 23 years; 142 women), 59 patients in the validation set (mean age, 51.4 ± 19.2 years; 38 women), and 273 patients in the test set (mean age, 50.4 ± 22.1 years; 177 women). In the test set, the DL model had sensitivity, specificity, and area under the receiver operating characteristic curve (AUC) of 92.3% (95% CI, 88.1-95.6), 74.4% (95% CI, 65.3-79.9), and 0.887 (95% CI, 0.844-0.930), respectively for detecting GBC which was comparable to both the radiologists. The DL-based approach showed high sensitivity (89.8-93%) and AUC (0.810-0.890) for detecting GBC in the presence of stones, contracted gallbladders, lesion size <10 mm, and neck lesions, which was comparable to both the radiologists (p = 0.052-0.738 for sensitivity and p = 0.061-0.745 for AUC). The sensitivity for DL-based detection of mural thickening type of GBC was significantly greater than one of the radiologists (87.8% vs. 72.8%, p = 0.012), despite a reduced specificity. Interpretation: The DL-based approach demonstrated diagnostic performance comparable to experienced radiologists in detecting GBC using US. However, multicentre studies are warranted to explore the potential of DL-based diagnosis of GBC fully. Funding: None.

Experimental kinetics and thermodynamics investigation: Chemically activated carbon-enriched monolithic reduced graphene oxide for efficient CO2 capture.

In this research, we have developed solid MGOs by self-assembled reduction process of GO at 90 °C with different weight ratios of oxalic acid (1:1, 1:0.500, and 1:0.250). The as-synthesized monoliths were carbonized (at 600 °C) and chemically activated with varying proportions of NaOH (1:1, 1:2, and 1:3). This materials offer the CO2 adsorption effect under dynamic conditions, fast mass transfer, easy handling, and outstanding stability throughout the adsorption-desorption cycle. FE-SEM, and HR-TEM analyses confirmed the porous nature and shape of the adsorbents, while XPS examination revealed the presence of distinct functional groups on the surface of the monolith. By increasing the mass ratios (MGO:NaOH) from 1:1 to 1:2, the surface areas increased by approximately 2.6 times, ranging from 520.8 to 753.9 m2 g⁻1 (surface area of the untreated MGO was 289.2 m2 g⁻1). Consequently, this resulted in a notable enhancement of 2.10 mmol g⁻1 in dynamic CO2 capture capacity. The assessment encompassed the evaluation of production yield, selectivity, regenerability, kinetics, equilibrium isotherm, and isosteric temperatures of adsorption (Qst). The decrease in CO2 capture effectiveness with rising adsorption temperature indicated an exothermic and physisorption process. The regenerability of 99.1 % at 100 °C and excellent cyclic stability with efficient CO2 adsorption make this monolithic adsorbent appropriate for post-combustion CO2 capture. The significant Qst lend support to the heterogeneity of the adsorbent's surface, and the pseudo-second-order kinetic model along with the Freundlich isotherm model emerged as the most fitting. Therefore, the current investigation shows that the carbon-enriched adsorbents enhance the CO2 adsorption capacity. It may be used as a low-cost pretreatment method on an industrial scale before carbon capture.

Applications of artificial intelligence in biliary tract cancers.

Biliary tract cancers are malignant neoplasms arising from bile duct epithelial cells. They include cholangiocarcinomas and gallbladder cancer. Gallbladder cancer has a marked geographical preference and is one of the most common cancers in women in northern India. Biliary tract cancers are usually diagnosed at an advanced, unresectable stage. Hence, the prognosis is extremely dismal. The five-year survival rate in advanced gallbladder cancer is < 5%. Hence, early detection and radical surgery are critical to improving biliary tract cancer prognoses. Radiological imaging plays an essential role in diagnosing and managing biliary tract cancers. However, the diagnosis is challenging because the biliary tract is affected by many diseases that may have radiological appearances similar to cancer. Artificial intelligence (AI) can improve radiologists' performance in various tasks. Deep learning (DL)-based approaches are increasingly incorporated into medical imaging to improve diagnostic performance. This paper reviews the AI-based strategies in biliary tract cancers to improve the diagnosis and prognosis.

Biowaste to bioenergy nexus: Fostering sustainability and circular economy.

Existing fossil-based commercial products present a significant threat to the depletion of global natural resources and the conservation of the natural environment. Also, the ongoing generation of waste is giving rise to challenges in waste management. Conventional practices for the management of waste, for instance, incineration and landfilling, emit gases that contribute to global warming. Additionally, the need for energy is escalating rapidly due to the growing populace and industrialization. To address this escalating desire in a sustainable manner, access to clean and renewable sources of energy is imperative for long-term development of mankind. These interrelated challenges can be effectively tackled through the scientific application of biowaste-to-bioenergy technologies. The current article states an overview of the strategies and current status of these technologies, including anaerobic digestion, transesterification, photobiological hydrogen production, and alcoholic fermentation which are utilized to convert diverse biowastes such as agricultural and forest residues, animal waste, and municipal waste into bioenergy forms like bioelectricity, biodiesel, bio alcohol, and biogas. The successful implementation of these technologies requires the collaborative efforts of government, stakeholders, researchers, and scientists to enhance their practicability and widespread adoption.

Enhancing CO2 capture through innovating monolithic graphene oxide frameworks.

The advancement and engineering of novel crystalline materials is facilitated through the utilization of innovative porous crystalline structures, established via KOH-treated monolithic graphene oxide frameworks. These materials exhibit remarkable and versatile characteristics for both functional exploration and applications within the realm of CO2 capture. In this comprehensive study, we have synthesized monolithic reduced graphene oxide-based adsorbents through a meticulous self-assembly process involving different mass ratios of GO/malic acid (MaA) (1:0.250, 1:0.500, and 1:1 by weight). Building upon this foundation, we further modified MGO 0.250 through KOH-treatment by chloroacetic acid method, leading to the creation of MGO 0.250_KOH, which was subjected to CO2 capture assessments. The comprehensive investigation encompassed an array of parameters including morphology, specific surface area, crystal defects, functional group identification, and CO2 capture efficiency. Employing a combination of FT-IR, XRD, Raman, BET, SEM, HR-TEM, and XPS techniques, the study revealed profound insights. Particularly notable was the observation that the MGO 0.250_KOH adsorbent exhibited an exceptional CO2 capture performance, leading to a significant enhancement of the CO2 capture capacity from 1.69 mmol g-1 to 2.35 mmol g-1 at standard conditions of 25 °C and 1 bar pressure. This performance enhancement was concomitant with an augmentation in surface area, elevating from 287.93 to 419.75 m2 g-1 (a nearly 1.5-fold increase compared to MGO 1.000 with a surface area of 287.93 m2 g-1). The monolithic adsorbent demonstrated a commendable production yield of 82.92%, along with an impressive regenerability of 98.80% at 100 °C. Additionally, adsorbent's proficiency in CO2 adsorption, rendering it a promising candidate for post-combustion CO2 capture applications. These findings collectively underscore the capacity adsorbents to significantly amplify CO2 capture capabilities. The viability of employing this strategy as an uncomplicated pre-treatment technique in various industrial sectors is a plausible prospect, given the study's outcomes.

Deep-learning models for differentiation of xanthogranulomatous cholecystitis and gallbladder cancer on ultrasound.

BACKGROUND: The radiological differentiation of xanthogranulomatous cholecystitis (XGC) and gallbladder cancer (GBC) is challenging yet critical. We aimed at utilizing the deep learning (DL)-based approach for differentiating XGC and GBC on ultrasound (US). METHODS: This single-center study comprised consecutive patients with XGC and GBC from a prospectively acquired database who underwent pre-operative US evaluation of the gallbladder lesions. The performance of state-of-the-art (SOTA) DL models (GBCNet-convolutional neural network [CNN] and RadFormer, transformer) for XGC vs. GBC classification in US images was tested and compared with popular DL models and a radiologist. RESULTS: Twenty-five patients with XGC (mean age, 57 ± 12.3, 17 females) and 55 patients with GBC (mean age, 54.6 ± 11.9, 38 females) were included. The performance of GBCNet and RadFormer was comparable (sensitivity 89.1% vs. 87.3%, p = 0.738; specificity 72% vs. 84%, p = 0.563; and AUC 0.744 vs. 0.751, p = 0.514). The AUCs of DenseNet-121, vision transformer (ViT) and data-efficient image transformer (DeiT) were significantly smaller than of GBCNet (p = 0.015, 0.046, 0.013, respectively) and RadFormer (p = 0.012, 0.027, 0.007, respectively). The radiologist labeled US images of 24 (30%) patients non-diagnostic. In the remaining patients, the sensitivity, specificity and AUC for GBC detection were 92.7%, 35.7% and 0.642, respectively. The specificity of the radiologist was significantly lower than of GBCNet and RadFormer (p = 0.001). CONCLUSION: SOTA DL models have a better performance than radiologists in differentiating XGC and GBC on the US.

Upcycling Waste: Citrus limon Peel-Derived Carbon Quantum Dots for Sensitive Detection of Tetracycline in the Nanomolar Range.

In this work, a sustainable method was developed for the production of water-soluble carbon quantum dots employing a green approach. The synthetic protocol was employed using the microwave pyrolysis technique, while lemon peel served as a carbon precursor. Fabrication of highly fluorescent lemon-peel-derived CQDs (LP-CQDs) having inherent nitrogen functionality was validated by X-ray photoelectron spectroscopy, FTIR, X-ray diffraction, Raman spectroscopic analysis, and TEM techniques. The average particle size of fabricated LP-CQDs was 4.46 nm. LP-CQDs yielded a remarkable quantum yield of 49.5%, which displayed excellent salinity, photostability, storage time, conditions, and pH stability. LP-CQDs displayed encouraging results for tetracycline (TC) detection using a PL turn-off approach. The sensitivity of LP-CQDs toward TC was seen in a nanomolar range having a detection limit of 50.4 nM. Method validation was comprehensively studied to ensure the precision of the nanosensor. A complete analysis of different photophysical parameters of LP-CQDs was performed with TC to gain a deeper understanding of the sensing mechanism. Fabricated LP-CQDs showed fluorescence quenching toward TC, elucidated by the inner filter effect (IFE) mechanism. The synthesized nanoprobe demonstrated a lesser detection limit with a broad linear range, enabling facile, cheap, environmentally friendly, and fast detection of TC. Practicality of the detection method was assessed through analysis of real samples, resulting in satisfactory recovery percentage and relative standard deviation with respect to the developed probes. Furthermore, LP-CQDs were used as fluorescent inks and to fabricate paper-based fluorescent strips. This study lays the door for the sensing platform of LP-CQDs toward detection of TC, which may impact the potential role of environmental sustainability.

Photophysical Study of Heteroatom-Doped Carbon Dots-MnO2-Based Nanosensor: Selective Detection of Glutathione in the Nanomolar Level.

Heteroatom doping on carbon dots (Cdots) has been developed as an efficient approach to modify its optical and electronic properties. The four different types of heteroatom-doped Cdots (undoped Cdots (u-Cdots, nitrogen-doped Cdots (N-Cdots), sulfur-doped Cdots (Cdots), nitrogen, sulfur codoped Cdots (N, S-Cdots)) have been synthesized through a simple heat treatment of 5 min. Among four different heteroatoms doped nanosensors, N, S-Cdots with MnO2 nanospheres (Mn NS) showed one of the best fluorescents "on-off-on" nanosensors for selective sensing of glutathione (GSH) and cell imaging. N, S-Cdots showed a high fluorescence quantum yield, good photostability, ionic strength, and pH stability. N, S-Cdots with Mn NS demonstrated extremely high fluorescence quenching efficiency and the maximum fluorescence recovery rate after adding GSH to the produced solution. The photophysical study of N, S-Cdots-Mn NS used as a sensor confirms the inner filter effect (IFE) quenching mechanism between them. The developed sensor has an 80 nM limit of detection (LOD) for GSH. The heteroatom-doped framework of Cdots plays a significant role in the sensitive detection of GSH. N, S-Cdots-Mn NS have good permeability, biocompatibility, and low toxicity, due to which it was used in the intracellular imaging of GSH in living cells. The prepared sensor is rapid, economical, less toxic, and highly applicable in diagnosing diseases.

Unleashing the power of solar light: WO3 nanorods decorated onto BiVO4 dendrites for tetracycline detoxification and water splitting.

The coupling of different oxide materials in a nanohybrid enables the customization of their optical and charge transport properties, leading to improved interfacial charge segregation and migration. In this study, BiVO4/WO3 (BVW), a sunlight-driven photocatalyst with distinct mole ratios was synthesized via a facile hydrothermal approach. The resultant catalyst exhibits a nanorods shape morphology decorated onto dendrite-like matrix and is studied for photocatalytic elimination of tetracycline (TC) and photoelectrocatalytic (PEC) H2 production. The effect of illumination time, solution pH, photocatalyst concentration, and mole ratios of BiVO4 to WO3 on the photocatalytic abatement of TC were tested sequentially as effective operating factors. Under optimal condition, 3:1 BiVO4:WO3 (31BVW) nanohybrid demonstrated a maximum degradation efficacy of 96.2% (rate constant ~0.0241 min-1), which is much better than its individual components and commercial TiO2-P25 (50.9%). The resultant by-products of TC decomposition were analyzed using GC-MS to explain the degradation mechanism. Moreover, as a photoanode, 31BVW showed a high photocurrent density of 0.64 mA/cm2 at 1.23 V vs RHE and a steady photocurrent for ~6 h under chronoamperometry study at1.23 V vs RHE. However, bare BiVO4 and WO3 exhibited the photocurrent density of 0.001 mA/cm2, and 0.015 mA/cm2, respectively at 1.23 V vs RHE. The Mott-Schottky analysis of 31BVW confirms their n-type behavior, with a calculated flat band potential of -0.067 V. The hydrogen production rate was theoretically calculated as 4.56 mmolcm-2 s-1 from chronoamperometric measurements. The photocatalyst's efficacy in TC degradation was further established via its reusability upto 7 cycles. Post degradation characterization of catalyst confirms its stability in lieu of practical usage. Comparative studies with existing literature revealed the superiority of reported photocatalysts in both applications. Overall, the binary BVW photocatalyst shows great potential for removing detrimental contaminants as well as H2 production via PEC water splitting due to efficient charge separation, reduced recombination, high surface area, and widen absorption window of the nanohybrid.

Sunlight active cellulose/g-C3N4/TiO2nano-photocatalyst for simultaneous degradation of methylene blue dye and atenolol drug in real wastewater.

The paper critically addresses two contemporary environmental challenges, the water crisis and the unrestricted discharge of organic pollutants in waterways together. An eco-friendly method was used to fabricate a cellulose/g-C3N4/TiO2photocatalytic composite that displayed a remarkable degradation of methylene blue dye and atenolol drug under natural sunlight. Introducing graphitic carbon nitride (g-C3N4) onto pristine TiO2improved hybrid material's photonic efficacy and enhanced interfacial charge separation. Furthermore, immobilizing TiO2/g-C3N4on a semi-interpenetrating cellulose matrix promoted photocatalyst recovery and its reuse, ensuring practical affordability. Under optimized conditions, the nano-photocatalyst exhibited ∼95% degradation of both contaminants within two hours while retaining ∼55% activity after ten cycles demonstrating a promising photostability. The nano-photocatalyst caused 66% and 57% reduction in COD and TOC values in industrial wastewater containing these pollutants. The photocatalysis was fitted to various models to elucidate the degradation kinetics, while LC-MS results suggested the mineralization pathway of dye majorly via ring opening demethylation. >98% disinfection was achieved againstE. coli(104-105CFU·ml-1) contaminated water. This study thus paves multifaceted strategies to treat wastewater contaminants at environmental levels employing nano-photocatalysis.

Revolutionizing the Role of Solar Light Responsive BiVO4/BiOBr Heterojunction Photocatalyst for the Photocatalytic Deterioration of Tetracycline and Photoelectrocatalytic Water Splitting.

In this study, a series of BiVO4/BiOBr composites with varying mole ratios were successfully synthesized using a hydrothermal method. The in-situ synthesis strategy facilitated the formation of a close interfacial contact between BiVO4 and BiOBr at the depletion zone, resulting in improved charge segregation, migration, reduced charge recombination, enhanced solar light absorption capacity, promoting narrow band gap, and large surface area. This study investigates the influence of different mole ratios of BiVO4 and BiOBr in a BiVO4/BiOBr nanocomposite on the photocatalytic degradation of tetracycline (TC), a pharmaceutical pollutant, and photoelectrocatalytic water splitting (PEC) under solar light irradiation. Maximum decomposition efficiency of ~90.4% (with a rate constant of 0.0159 min-1) for TC was achieved with 0.5 g/L of 3:1 BiVO4: BiOBr (31BVBI) photocatalyst within 140 min. The degraded compounds resulting from the TC abatement were analyzed using GC-MS. Furthermore, TC standards exhibited 78.2% and 87.7% removal of chemical oxygen demand (COD) and total organic carbon (TOC), respectively, while TC tablets showed 64.6% COD removal and 73.8% TOC removal. The PEC water splitting experiments demonstrated that the 31BVBI photoanode achieved the highest photocurrent density of approximately 0.2198 mA/cm2 at 1.23 V vs. RHE, resulting in the generation of approximately 1.864 mmolcm-2 s-1 of hydrogen, while remaining stable for 21,600 s. The stability of the photocatalyst was confirmed by post-degradation characterizations, which revealed intact crystalline planes, shape, and surface area. Comparisons with existing physicochemical methods used in industries indicate that the reported photocatalyst possesses strong surface catalytic properties and has the potential for application in industrial wastewater treatment and hydrogen generation, offering an advantageous alternative to costly and time-consuming processes.

2D g-C3N4 nanosheets functionalized with nickel-doped ZrO2 nanoparticles for synergistic photodegradation of toxic chemical pollutants.

The photocatalytic removal of toxic chemical pollutants from wastewater has garnered significant attention in recent times owing to its notable removal efficiency, cost-effectiveness, and eco-friendly characteristics. Nonetheless, this catalytic process necessitates augmented charge separation and distinctive interface properties to facilitate catalytic reactions for water treatment applications. Therefore, in the current study, novel g-C3N4/Ni-doped ZrO2 heterostructured hybrid catalysts have been synthesized via a hydrothermal approach. Microscopic studies reveal that ZrO2 nanospheres were distributed on the layered-like 2D structure of g-C3N4 nanosheets. Electrochemical impedance spectroscopy (EIS), X-ray photoelectron spectroscopy (XPS), UV-Vis diffuse reflectance spectroscopy (UV-DRS), and photoluminescence (PL) characterizations were employed to investigate the impact of bandgap, electron-hole recombination, charge transfer, and interface properties on the catalytic performance of g-C3N4/ZrO2 hybrids. XRD analysis confirmed that the Ni-ions do not disturb the host lattice crystal structure and heterostructure development between g-C3N4 and doped ZrO2 sample. Structurally, Ni-doped nanoparticles were found to be equally superficially dispersed on g-C3N4 sheets. Optical analysis results suggest that the hybrid catalyst possesses a narrow bandgap of 2.56 eV. The synthesized photocatalyst degraded rhodamine B (RhB) and tetracycline (TC) with ∼92% and ∼89% degradation efficiency, respectively. Heterostructured hybrid catalysts showed superior degradation rate constants than other catalysts. This might be attributed to the sufficient separation of electron-hole due to the development of a heterojunction. The radical scavenging experiments suggested that O2●- and ●OH radicals contributed substantially to the dye elimination activity of the composite. Therefore, the synthesized novel nanohybrid catalysts in this study present an efficient and straightforward synthesis method for the efficient removal of toxins from wastewater under visible light irradiation.

Orange Pomace-Derived Fluorescent Carbon Quantum Dots: Detection of Dual Analytes in the Nanomolar Range.

Green-emissive carbon quantum dots (CQDs) with exclusive chemosensing aspects were synthesized from orange pomace as a biomass-based precursor via a facile microwave method without using any chemicals. The synthesis of highly fluorescent CQDs with inherent nitrogen was confirmed through X-ray diffraction, X-ray photoelectron, Fourier transform infrared, Raman, and transmission electron microscopic techniques. The average size of the synthesized CQDs was found to be 7.5 nm. These fabricated CQDs displayed excellent photostability, water solubility, and outstanding fluorescent quantum yield, i.e., 54.26%. The synthesized CQDs showed promising results for the detection of Cr6+ ions and 4-nitrophenol (4-NP). The sensitivity of CQDs toward Cr6+ and 4-NP was found up to the nanomolar range with the limit of detection values of 59.6 and 14 nM, respectively. Several analytical performances were thoroughly studied for high precision of dual analytes of the proposed nanosensor. Various photophysical parameters of CQDs (quenching efficiency, binding constant, etc.) were analyzed in the presence of dual analytes to gain more insights into the sensing mechanism. The synthesized CQDs exhibited fluorescence quenching toward incrementing the quencher concentration, which was rationalized by the inner filter effect through time-correlated single-photon counting measurements. The CQDs fabricated in the current work exhibited a lower detection limit and a wide linear range through the simple, eco-friendly, and rapid detection of Cr6+ and 4-NP ions. To evaluate the feasibility of the detection approach, real sample analysis was conducted, demonstrating satisfactory recovery rates and relative standard deviations toward the developed probes. This research paves the way for developing CQDs with superior characteristics utilizing orange pomace (biowaste precursor).

Novel MoS2/C3N5 composites with extended spectral response towards highly efficient photocatalytic abatement of hazardous pollutants.

Carbon nitride materials are one of the potential candidates for photocatalytic application. The present work demonstrates the fabrication of C3N5 catalyst from a simple, low-cost, and easily available nitrogen-containing precursor, melamine. The facile and microwave mediated method was used to prepare novel MoS2/C3N5 composites (referred to as MC) with varying weight ratios (1:1, 1:3, and 3:1). This work provided a novel strategy to improve photocatalytic activity and accordingly fabricated a potential material for effective removal of organic contaminants from water. XRD and FT-IR results affirms the cryatalinity and successful formation of the composites. The elemental composition/distribution was analysed via EDS and color mapping. The elemental oxidation state and successful charge migration in hetrostructure was confirmed by XPS findings. The catalyst's surface morphology indicates tiny MoS2 nanopetals dispersed throughout C3N5 sheets, while BET studies revealed its high surface area (34.7 m2/g). The MC catalysts were highly active in visiblelight, with an energy band gap value of 2.01 eV and a lowered recombination of charges. Because of the strong synergistic relationship (2.19) in the hybrid, excellent activity for methylene blue (MB) dye (88.9%; 0.0157 min-1) and fipronil (FIP) photodegradation (85.3%; 0.0175 min-1) with MC (3:1) catalyst under visible-light irradiation was obtained. Investigations were carried out on the effect of catalyst quantity, pH, and effectual illumination area on photoactivity. Post-photocatalytic assessment verified the high re-useable character of the catalyst with a high degradation (63% (5 mg/L MB) and 54% (600 mg/L FIP)) after five cycles. The trapping investigations demonstrated that superoxide radicals and holes were intimately enrolled in the degradation activity. Remarkable removal rates of COD (68.4%) and TOC (53.1%) demonstrate excellent photocatalytic removal of practical wastewater even without any preliminary processes. The new study, when paired with previous research, demonstrates the real-world perspective of these novel MC composites for the elimination of refractory contaminants.

Novel g-C3N4/BiVO4 heterostructured nanohybrids for high efficiency photocatalytic degradation of toxic chemical pollutants.

Novel heterostructured hybrid catalysts are essential for the efficient photocatalytic removal of organic pollutants from wastewater generated by the pharmaceutical and textile industries. In this study, novel g-C3N4/BiVO4 nanohybrid catalysts were prepared using a solvothermal technique, and examined their structural and optical properties using different characterizations. The X-ray diffraction analysis confirmed the monoclinic crystal phase of BiVO4. Field emission scanning electron microscopy (FESEM) images revealed that g-C3N4 sheets anchored on the surface of BiVO4 nanospheres. X-ray photoelectron spectroscopy (XPS) analysis confirmed the oxidation states of g-C3N4/BiVO4 composite sample. UV-Vis DRS spectroscopy analysis revealed that the composite (2.08 eV) sample had a reduced bandgap compared to other samples. The photocatalytic properties of the prepared samples were tested in the presence of organic methylene blue (MB) and antibiotic tetracycline (TC) pollutants under visible light illumination. The hybrid composite catalyst exhibited enhanced photocatalytic degradation efficiency of MB (88%) and TC (89%) pollutants at elevated rate constants of 0.0128 and 0.01174 min-1, respectively. The improved catalytic performance of the composite catalyst is due to the heterojunctions between g-C3N4 and BiVO4 that successfully reduced the rate of charge carrier recombination in the catalyst system. Scavenger experiments revealed that O2●- and h+ radicals played a main role in the degradation of the chemical pollutants. The developed g-C3N4/BiVO4 heterostructured catalyst is a suitable candidate for removing contaminants from industrial wastewater because of its facile fabrication and exceptional photocatalytic activity under visible light irradiation.

RadFormer: Transformers with global-local attention for interpretable and accurate Gallbladder Cancer detection.

We propose a novel deep neural network architecture to learn interpretable representation for medical image analysis. Our architecture generates a global attention for region of interest, and then learns bag of words style deep feature embeddings with local attention. The global, and local feature maps are combined using a contemporary transformer architecture for highly accurate Gallbladder Cancer (GBC) detection from Ultrasound (USG) images. Our experiments indicate that the detection accuracy of our model beats even human radiologists, and advocates its use as the second reader for GBC diagnosis. Bag of words embeddings allow our model to be probed for generating interpretable explanations for GBC detection consistent with the ones reported in medical literature. We show that the proposed model not only helps understand decisions of neural network models but also aids in discovery of new visual features relevant to the diagnosis of GBC. Source-code is available at https://github.com/sbasu276/RadFormer.

Rice Husk-Derived Carbon Quantum Dots-Based Dual-Mode Nanoprobe for Selective and Sensitive Detection of Fe3+ and Fluoroquinolones.

Herein, eco-friendly, water-soluble, and fluorescent carbon quantum dots (CQDs) with an average size of 8.3 nm were synthesized from rice husk (RH) using the hydrothermal method, and the CQDs were labeled as rice husk CQDs (RH-CQDs). The composition and surface functionalities were studied using X-ray photoelectron spectroscopy, Fourier transform infrared spectroscopy, and Raman spectroscopy. A study on the impact of pH and irradiation time on fluorescence affirmed the stability of RH-CQDs. The as-synthesized nanosensor has high selectivity and sensitivity for Fe3+ ions. Several photophysical studies were performed to investigate the interaction between RH-CQDs and Fe3+. Using the time-correlated single-photon technique, it is determined that the average lifetime value of RH-CQDs significantly decreases in the presence of Fe3+, which supports a dynamic quenching mechanism. The developed sensor exhibited excellent sensitivity with a detection limit in the nanomolar range (149 nM) with a wide linear range of 0-1300 nM for Fe3+ ions. The prepared nanosensor was also used to detect Fe3+ in a tablet supplement with high recoveries. Moreover, the RH-CQD nanoprobe was used to detect other analytes (fluoroquinolones) using the fluorescence enhancement technique. It showed high selectivity and sensitivity toward ofloxacin (OFX) and ciprofloxacin (CPX). The detection limits calculated were 150 nM and 127 nM with a linearity range of 50-1150 nM for OFX and CPX, respectively. The enhancement of the average lifetime value and quantum yield in the presence of OFX and CPX favors the increased fluorescence property of RH-CQDs through hydrogen bonding and charge transfer. In this work, the integration of two different mechanisms (fluorescence quenching and fluorescence enhancement) was followed to construct a single sensing platform for accurate quantification of dual-mode nanosensors for the detection of metal ions and fluoroquinolones by the excited-state electron transfer and hydrogen bonding mechanism, respectively. This strategy also stimulates the detection of more than one analyte.

Versatile Carbon Nanofiber-Based Sensors.

Carbon nanofibers (CNFs) display colossal potential in different fields like energy, catalysis, biomedicine, sensing, and environmental science. CNFs have revealed extensive uses in various sensing platforms due to their distinctive structure, properties, function, and accessible surface functionalization capabilities. This review presents insight into various fabrication methods for CNFs like electrospinning, chemical vapor deposition, and template methods with merits and demerits of each technique. Also, we give a brief overview of CNF functionalization. Their unique physical and chemical properties make them promising candidates for the sensor applications. This review offers detailed discussion of sensing applications (strain sensor, biosensor, small molecule detection, food preservative detection, toxicity biomarker detection, and gas sensor). Various sensing applications of CNF like human motion monitoring and energy storage and conversion are discussed in brief. The challenges and obstacles associated with CNFs for futuristic applications are discussed. This review will be helpful for readers to understand the different fabrication methods and explore various applications of the versatile CNFs.

Visible-light-induced photocatalytic response of easily recoverable Mn2O3/SiO2 monolith in centimeter-scale towards degradation of ofloxacin: Performance evaluation and product analysis.

Monolithic-photocatalysts being easily recoverable are a suitable alternative to powdered materials for pollutant treatment. This study was conducted to prepare Mn2O3/SiO2 monoliths by wet-impregnating Mn(NO3)2․4H2O in SiO2 monoliths. The crystallinity of oxide was affirmed via XRD analyses, whereas EDS and elemental-mapping, and XPS studies revealed the constituent elements and their oxidation states. FESEM images confirmed porous morphology, while BET-analysis confirmed its mesoporous nature (∼8.44 nm) and enormous surface area (∼241 m2/g). The DRS and PL studies disclosed that Mn2O3/SiO2 monoliths consisted of narrow band-gap of ∼2.14 eV and had suitable electron/hole separation. The photocatalytic effectiveness of the monolith had been checked by degrading model dye methylene blue (MB) and antibiotic ofloxacin (OF). The influence of various reaction parameters for degradation, i.e., monolith dose, solution-pH, illumination-area, scavengers, etc., was noted. At optimal reaction conditions, outstanding competence was achieved for MB (95.23%; 0.0225 min-1) and decent results were obtained for OF-degradation (73.2%; 0.0096 min-1). The recyclable nature of the catalyst (∼12.7%-reduction in effectiveness after 10 successive cycles) was vindicated by several characterization studies after reusability. The O2•-radicals participated majorly in the degradation reaction. The reaction intermediates plus products, generated after the degradation of had been identified via LC/MS study. The mineralization extent of the OF and MB was also gauged through TOC analyses. The photocatalytic treatment of raw textile wastewater manifested ∼57.8% COD and 53% TOC-removal. This study emphasizes the competence of Mn2O3/SiO2 monoliths for the photocatalytic abatement of refractory organic contaminants.

Two-dimensional ultrathin metal-based nanosheets for photocatalytic CO2 conversion to solar fuels.

Artificially simulated photosynthesis has created substantial curiosity as the majority of efforts in this arena have been aimed to upsurge solar fuel efficiencies for commercialization. The layered inorganic 2D nanosheets offer considerably higher tunability of their chemical surface, physicochemical properties and catalytic activity. Despites the intrinsic advantages of such metal-based materials viz., metal oxides, transition metal dichalcogenides, metal oxyhalides, metal organic frameworks, layered double hydroxide, MXene's, boron nitride, black phosphorous and perovskites, studies on such systems are limited for applications in photocatalytic CO2 reduction. The role of metal-based layers for CO2 conversion and new strategies such as surface modifications, defect generation and heterojunctions to optimize their functionalities are discussed in this review. Research prospects and technical challenges for future developments of layered 2D metal-based nanomaterials are critically discussed.