Synthesis and Characterizations of Titanium Tungstosilicate and Tungstophosphate Mesoporous Materials

The work reports a development approach for the synthesis of novel multi-components mesoporous materials of titanium tungstate (meso-TiW) titanium tungstosilicate (meso-TiWSi) and tungstophosphate (meso-TiWP) mixed oxides that have high surface area and ordered mesoporous structures at nanometer length scale. Using the solvent evaporation-induced self-assembly (EISA) new oxides of bi- and tri-component of meso-TiW, meso-TiWSi and meso-TiWP oxides with different compositions and porosity were achieved. The physicochemical properties of the mesoporous oxides were characterized by X-ray diffraction, BET surface area analyzer, scanning, and transmission electron microscopes. Subject to the oxide composition, the obtained meso-TiW, meso-TiWSi and meso-TiWP exhibits high surface area, ordered 2D hexagonal mesostructured with order channels extended over a large area. The produced meso-TiW, meso-TiWSi, and meso-TiWP adsorbents exhibit good adsorption efficiency for the removal of Pb(II), Cd(II) and Hg(II) ions from water solution due to the presence of high surface area and accessibility of surface active sites. The adsorption efficiency of these mesoporous oxide reaches up to 95% and is found to be dependent contact time and adsorbents dose. The synthesis strategy is particularly advantageous for the production of new complex (multi-component) inorganic mesoporous materials that might have an application in the field of environmental, catalysis or energy storage and production

Evidence supporting the use of peptides and peptidomimetics as potential SARS-CoV-2 (COVID-19) therapeutics

© 2020 Newlands Press. During a disease outbreak/pandemic situation such as COVID-19, researchers are in a prime position to identify and develop peptide-based therapies, which could be more rapidly and cost-effectively advanced into a clinical setting. One drawback of natural peptide drugs, however, is their proteolytic instability; peptidomimetics can help to overcome this caveat. In this review, we summarize peptide and peptide-based therapeutics that target one main entry pathway of SARS-CoV-2, which involves the host ACE2 receptor and viral spike (S) protein interaction. Furthermore, we discuss the advantages of peptidomimetics and other potential targets that have been studied using peptide-based therapeutics for COVID-19

From Categories to Classifier: Name-Only Continual Learning by Exploring the Web

Continual Learning (CL) often relies on the availability of extensive annotated datasets, an assumption that is unrealistically time-consuming and costly in practice. We explore a novel paradigm termed name-only continual learning where time and cost constraints prohibit manual annotation. In this scenario, learners adapt to new category shifts using only category names without the luxury of annotated training data. Our proposed solution leverages the expansive and ever-evolving internet to query and download uncurated webly-supervised data for image classification. We investigate the reliability of our web data and find them comparable, and in some cases superior, to manually annotated datasets. Additionally, we show that by harnessing the web, we can create support sets that surpass state-of-the-art name-only classification that create support sets using generative models or image retrieval from LAION-5B, achieving up to 25% boost in accuracy. When applied across varied continual learning contexts, our method consistently exhibits a small performance gap in comparison to models trained on manually annotated datasets. We present EvoTrends, a class-incremental dataset made from the web to capture real-world trends, created in just minutes. Overall, this paper underscores the potential of using uncurated webly-supervised data to mitigate the challenges associated with manual data labeling in continual learning

Real-Time Evaluation in Online Continual Learning: A New Hope

Current evaluations of Continual Learning (CL) methods typically assume that there is no constraint on training time and computation. This is an unrealistic assumption for any real-world setting, which motivates us to propose: a practical real-time evaluation of continual learning, in which the stream does not wait for the model to complete training before revealing the next data for predictions. To do this, we evaluate current CL methods with respect to their computational costs. We conduct extensive experiments on CLOC, a large-scale dataset containing 39 million time-stamped images with geolocation labels. We show that a simple baseline outperforms state-of-the-art CL methods under this evaluation, questioning the applicability of existing methods in realistic settings. In addition, we explore various CL components commonly used in the literature, including memory sampling strategies and regularization approaches. We find that all considered methods fail to be competitive against our simple baseline. This surprisingly suggests that the majority of existing CL literature is tailored to a specific class of streams that is not practical. We hope that the evaluation we provide will be the first step towards a paradigm shift to consider the computational cost in the development of online continual learning methods.Comment: Accepted at CVPR'23 as Highlight (Top 2.5%

Photoelectrochemical performance of strontium titanium oxynitride photo-activated with cobalt phosphate nanoparticles for oxidation of alkaline water

Photoelectrochemical (PEC) solar water splitting is favourable for transforming solar energy into sustainable hydrogen fuel using semiconductor electrodes. Perovskite-type oxynitrides are attractive photocatalysts for this application due to their visible light absorption features and stability. Herein, strontium titanium oxynitride (STON) containing anion vacancies of SrTi(O,N)3−δ was prepared via solid phase synthesis and assembled as a photoelectrode by electrophoretic deposition, and their morphological and optical properties and PEC performance for alkaline water oxidation are investigated. Further, cobalt-phosphate (CoPi)-based co-catalyst was photo-deposited over the surface of the STON electrode to boost the PEC efficiency. A photocurrent density of ~138 μA/cm at 1.25 V versus RHE was achieved for CoPi/STON electrodes in presence of a sulfite hole scavenger which is approximately a four-fold enhancement compared to the pristine electrode. The observed PEC enrichment is mainly due to the improved kinetics of oxygen evolution because of the CoPi co-catalyst and the reduced surface recombination of the photogenerated carriers. Moreover, the CoPi modification over perovskite-type oxynitrides provides a new dimension for developing efficient and highly stable photoanodes in solar-assisted water-splitting reactions

Cetuximab and anemia prevention in head and neck cancer patients undergoing radiotherapy

BACKGROUND: Epidermal growth factor receptor (EGFR) activation is associated with increased production of interleukin 6 (IL6), which is intensified by radiotherapy (RT) induced inflammatory response. Elevated IL6 levels intensifies RT-induced anemia by upregulating hepcidin causing functional iron deficiency. Cetuximab, an EGFR inhibitor, has been associated with lower rates of anemia for locally advanced head and neck squamous cell carcinoma (HNSCC). We hypothesized that concomitant cetuximab could prevent RT-induced anemia. METHODS: We queried our institutional head and neck cancers database for non-metastatic HNSCC cases that received RT with concomitant cetuximab or RT-only between 2006 and 2018. Cetuximab was administered for some high-risk cases medically unfit for platinum agents per multidisciplinary team evaluation. We only included patients who had at least one complete blood count in the 4 months preceding and after RT. We compared the prevalence of anemia (defined as hemoglobin (Hb) below 12 g/dL in females and 13 g/dL in males) and mean Hb levels at baseline and after RT. Improvement of anemia/Hb (resolution of baseline anemia and/or an increase of baseline Hb ≥1 g/dL after RT), and overall survival (OS) in relation to anemia/Hb dynamics were also compared. RESULTS: A total of 171 patients were identified equally distributed between cetuximab-plus-RT and RT-only groups. The cetuximab-plus-RT group had more locally-advanced stage, oropharyngeal and high grade tumors (p \u3c 0.001 for all). Baseline anemia/Hb were similar, however anemia after RT conclusion was higher in the cetuximab-plus-RT vs RT-only (63.5% vs. 44.2%; p = 0.017), with a mean Hb of 11.98 g/dL vs. 12.9 g/dL; p = 0.003, for both respectively. This contributed to significantly worse anemia/Hb improvement for cetuximab-plus-RT (18.8% vs. 37.2%; p = 0.007). This effect was maintained after adjusting for other factors in multivariate analysis. The prevalence of iron, vitamin-B12 and folate deficiencies; and chronic kidney disease, was non-different. Baseline anemia was associated with worse OS (p = 0.0052) for the whole study cohort. Nevertheless, improvement of anemia/Hb was only marginally associated with better OS (p = 0.068). CONCLUSIONS: In contrast to previous studies, cetuximab was not associated with lower rates of anemia after RT for nonmetastatic HNSCC patients compared to RT-alone. Dedicated prospective studies are needed to elucidate the effect of cetuximab on RT-induced anemia

Structure and electrochemical activity of nickel aluminium fluoride nanosheets during urea electro-oxidation in an alkaline solution

An electrocatalyst of potassium nickel aluminium hexafluoride (KNiAlF6) nanosheets has been prepared using solid-phase synthesis at 900 °C. X-ray diffraction, scanning electron microscopy, and conductivity studies confirmed the formation of KNiAlF6 nanosheets having a cubic defect pyrochlore structure with an average thickness of 60–70 nm and conductivity of 1.297 × 103 S m−1. The electrochemical catalytic activity of the KNiAlF6 nanosheets was investigated for urea oxidation in alkaline solution. The results show that the KNiAlF6 nanosheets exhibit a mass activity of ∼395 mA cm−2 mg−1 at 1.65 V vs. HRE, a reaction activation energy of 4.02 kJ mol−1, Tafel slope of 22 mV dec−1 and an oxidation onset potential of ∼1.35 V vs. HRE which is a significant enhancement for urea oxidation when compared with both bulk Ni(OH)2 and nickel hydroxide-based catalysts published in the literature. Chronoamperometry and impedance analysis of the KNiAlF6 nanosheets reveal lower charge transfer resistance and long-term stability during the prolonged urea electro-oxidation process, particularly at 60 °C. After an extended urea electrolysis process, the structure and morphology of the KNiAlF6 nanosheets were significantly changed due to partial transformation to Ni(OH)2 but the electrochemical activity was sustained. The enhanced electrochemical surface area and the replacement of nickel in the lattice by aluminium make KNiAlF6 nanosheets highly active electrocatalysts for urea oxidation in alkaline solution

Bayesian calibration, validation and uncertainty quantification for predictive modelling of tumour growth: a tutorial

In this work we present a pedagogical tumour growth example, in which we apply calibration and validation techniques to an uncertain, Gompertzian model of tumour spheroid growth. The key contribution of this article is the discussion and application of these methods (that are not commonly employed in the field of cancer modelling) in the context of a simple model, whose deterministic analogue is widely known within the community. In the course of the example we calibrate the model against experimental data that is subject to measurement errors, and then validate the resulting uncertain model predictions. We then analyse the sensitivity of the model predictions to the underlying measurement model. Finally, we propose an elementary learning approach for tuning a threshold parameter in the validation procedure in order to maximize predictive accuracy of our validated model

Approaches in biotechnological applications of natural polymers

Natural polymers, such as gums and mucilage, are biocompatible, cheap, easily available and non-toxic materials of native origin. These polymers are increasingly preferred over synthetic materials for industrial applications due to their intrinsic properties, as well as they are considered alternative sources of raw materials since they present characteristics of sustainability, biodegradability and biosafety. As definition, gums and mucilages are polysaccharides or complex carbohydrates consisting of one or more monosaccharides or their derivatives linked in bewildering variety of linkages and structures. Natural gums are considered polysaccharides naturally occurring in varieties of plant seeds and exudates, tree or shrub exudates, seaweed extracts, fungi, bacteria, and animal sources. Water-soluble gums, also known as hydrocolloids, are considered exudates and are pathological products; therefore, they do not form a part of cell wall. On the other hand, mucilages are part of cell and physiological products. It is important to highlight that gums represent the largest amounts of polymer materials derived from plants. Gums have enormously large and broad applications in both food and non-food industries, being commonly used as thickening, binding, emulsifying, suspending, stabilizing agents and matrices for drug release in pharmaceutical and cosmetic industries. In the food industry, their gelling properties and the ability to mold edible films and coatings are extensively studied. The use of gums depends on the intrinsic properties that they provide, often at costs below those of synthetic polymers. For upgrading the value of gums, they are being processed into various forms, including the most recent nanomaterials, for various biotechnological applications. Thus, the main natural polymers including galactomannans, cellulose, chitin, agar, carrageenan, alginate, cashew gum, pectin and starch, in addition to the current researches about them are reviewed in this article.. }To the Conselho Nacional de Desenvolvimento Cientfíico e Tecnológico (CNPq) for fellowships (LCBBC and MGCC) and the Coordenação de Aperfeiçoamento de Pessoal de Nvíel Superior (CAPES) (PBSA). This study was supported by the Portuguese Foundation for Science and Technology (FCT) under the scope of the strategic funding of UID/BIO/04469/2013 unit, the Project RECI/BBB-EBI/0179/2012 (FCOMP-01-0124-FEDER-027462) and COMPETE 2020 (POCI-01-0145-FEDER-006684) (JAT)