245 research outputs found
Fabrication and characterization of crystalline copper nanowires by electrochemical deposition inside anodic alumina template
Copper nanowires were fabricated by electrochemical deposition inside anodic alumina template anodized on aluminum substrate. The morphology, composition and structure of the copper nanowires were characterized by means of scanning electron microscopy (SEM), transmission electron microscopy (TEM), high-resolution transmission electron microscopy (HRTEM), energy-dispersive (EDS) and X-ray diffraction spectroscopy (XRD). The results revealed that copper nanowires were dense, continuous, highly-crystalline and uniform with diameters. The electrical properties of copper nanowires wrer characterized with two-terminal electrical measurements. Different current-voltage (I-V) characteristics of single copper nanowire were observed and possible conductive mechanisms were discussed. The crystalline copper nanowires are promising in application of future nanoelectronic devices and circuits. © 2013 The Author(s)
Cocrystals Mitigate the Effect of pH on Solubility and Dissolution of Basic Drugs
Pharmaceutical cocrystals are emerging as a useful strategy for enhancing solubility, dissolution, and bioavailability for poorly water-soluble drugs. One of the most important properties of cocrystals is their fine-tunable solubility. This property enables cocrystals to increase or decrease solubility. Cocrystal solubility is the result of intricate chemical interactions between cocrystal solution components and conditions such as additives and pH. Without the critical knowledge of cocrystal solution behavior and the underlying solution interactions, studying cocrystals is a trial and error exercise that can be time consuming. This dissertation determines the mechanisms by which the cocrystal solubility is influenced by pH and solubilizing agents and investigates the relationship between cocrystal supersaturation index and conversion kinetics.
The objectives of this work are to (1) determine the effect of pH and solubilizing agents on cocrystal solubility, supersaturation index, and dissolution, (2) derive mathematical equations that describe cocrystal solubility and supersaturation index behavior based on solution equilibria of cocrystal dissociation, component ionization, and component solubilization, (3) investigate the relationship between cocrystal supersaturation index and risk of solution-mediated conversion, and (4) assess the ability of cocrystals to generate and maintain supersaturation.
Three cocrystals (1:1 stochiometric ratio) composed of a basic drug, ketoconazole (KTZ), and acidic coformers, adipic acid (ADP), fumaric acid (FUM), and succinic acid (SUC), were used as model compounds. While KTZ has shown orders of magnitude decreases in solubility and dissolution as pH increases from 1 to 7, the cocrystal solubility increases with respect to drug at pH above pHmax (pHmax range 3.6 to 3.8). Cocrystal solubility advantage (SA), also referred to as the supersaturation index, increased from 1 at pHmax to between 900 and 6000 at pH 6.5. This range of SA translated into cocrystals that sustain supersaturation levels to different extents or not at all. SA values ranged from 5 to 13 (FeSSIF), 13 to 36 (blank FeSSIF), 221 to 1418 (FaSSIF), and 440 to 3118 (blank FaSSIF). Maximum supersaturation with respect to drug and AUC ratio of cocrystal to drug during dissolution showed that cocrystals exhibited superior dissolution behavior over drug in all media except for the cocrystal with the highest SA (3118, KTZ-FUM in blank FaSSIF). Cocrystals showed the highest supersaturation (22 to 30) and AUC ratio (10 to 16) values in FaSSIF. Supersaturation and AUC ratio increased with SA in FaSSIF, and they leveled off at SA between 460 and 1400. The lowest supersaturation (1.5) and AUC ratio (1.6) values were observed in FeSSIF, where cocrystals were fully dissolved and no drug precipitation occurred. pH-shift dissolution studies also showed that the cocrystal Cmax and AUC values exhibited less sensitivity to gastric pH than the drug. KTZ was also observed to undergo liquid-liquid phase separation when high levels of supersaturation (about 150) were generated by rapid pH-shift from 2 to 6.5. These metastable forms exhibited higher solubility compared to the crystalline form, and their formation appeared to delay crystallization. Formation of such metastable phases may increase oral absorption.PHDPharmaceutical SciencesUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttps://deepblue.lib.umich.edu/bitstream/2027.42/140809/1/yitian_1.pd
Case report: successful response to bevacizumab combined with erlotinib for a novel FH gene mutation hereditary leiomyoma and renal cell carcinoma
FH-deficient Renal Cell Carcinoma (FH-deficient RCC) are inherited tumors caused by mutations in the fumarate hydratase (FH) gene, which plays a role in the tricarboxylic acid cycle. These mutations often result in aggressive forms of renal cell carcinoma (RCC) and other tumors. Here, we present a case of FH-deficient RCC in a 43-year-old woman with a history of uterine fibroids. She exhibited a new heterozygous mutation in exon six of the FH gene (c.799_803del, c.781_796del). The patient had multiple bone metastases and small subcutaneous nodules in various areas such as the shoulders, back, and buttocks. Biopsy of a subcutaneous nodule on the right side revealed positive expression of 2-succinate-cysteine (2SC), and FH staining indicated FH expression deletion. The patient underwent treatment with a combination of erlotinib and bevacizumab, which resulted in significant efficacy with moderate side effects. This treatment combination may be recommended as a standard regimen. This case underscores the importance of genetic testing in patients with advanced renal cancer to enhance diagnostic accuracy. Furthermore, it provides insights into potential treatment approaches for FH-deficient RCC
GP-NAS-ensemble: a model for NAS Performance Prediction
It is of great significance to estimate the performance of a given model
architecture without training in the application of Neural Architecture Search
(NAS) as it may take a lot of time to evaluate the performance of an
architecture. In this paper, a novel NAS framework called GP-NAS-ensemble is
proposed to predict the performance of a neural network architecture with a
small training dataset. We make several improvements on the GP-NAS model to
make it share the advantage of ensemble learning methods. Our method ranks
second in the CVPR2022 second lightweight NAS challenge performance prediction
track
Optimal use of Charge Information for the HL-LHC Pixel Detector Readout
The pixel detectors for the High Luminosity upgrades of the ATLAS and CMS
detectors will preserve digitized charge information in spite of extremely high
hit rates. Both circuit physical size and output bandwidth will limit the
number of bits to which charge can be digitized and stored. We therefore study
the effect of the number of bits used for digitization and storage on single
and multi-particle cluster resolution, efficiency, classification, and particle
identification. We show how performance degrades as fewer bits are used to
digitize and to store charge. We find that with limited charge information (4
bits), one can achieve near optimal performance on a variety of tasks.Comment: 27 pages, 20 figure
Gender Bias in Large Language Models across Multiple Languages
With the growing deployment of large language models (LLMs) across various
applications, assessing the influence of gender biases embedded in LLMs becomes
crucial. The topic of gender bias within the realm of natural language
processing (NLP) has gained considerable focus, particularly in the context of
English. Nonetheless, the investigation of gender bias in languages other than
English is still relatively under-explored and insufficiently analyzed. In this
work, We examine gender bias in LLMs-generated outputs for different languages.
We use three measurements: 1) gender bias in selecting descriptive words given
the gender-related context. 2) gender bias in selecting gender-related pronouns
(she/he) given the descriptive words. 3) gender bias in the topics of
LLM-generated dialogues. We investigate the outputs of the GPT series of LLMs
in various languages using our three measurement methods. Our findings revealed
significant gender biases across all the languages we examined.Comment: 20 pages, 27 tables, 7 figures, submitted to ACL202
Automated Vessel Segmentation Using Infinite Perimeter Active Contour Model with Hybrid Region Information with Application to Retinal Images
Automated detection of blood vessel structures is becoming of crucial interest for better management of vascular disease. In this paper, we propose a new infinite active contour model that uses hybrid region information of the image to approach this problem. More specifically, an infinite perimeter regularizer, provided by using L 2 Lebesgue measure of the γ-neighborhood of boundaries, allows for better detection of small oscillatory (branching) structures than the traditional models based on the length of a feature's boundaries (i.e., H 1 Hausdorff measure). Moreover, for better general segmentation performance, the proposed model takes the advantage of using different types of region information, such as the combination of intensity information and local phase based enhancement map. The local phase based enhancement map is used for its superiority in preserving vessel edges while the given image intensity information will guarantee a correct feature's segmentation. We evaluate the performance of the proposed model by applying it to three public retinal image datasets (two datasets of color fundus photography and one fluorescein angiography dataset). The proposed model outperforms its competitors when compared with other widely used unsupervised and supervised methods. For example, the sensitivity (0.742), specificity (0.982) and accuracy (0.954) achieved on the DRIVE dataset are very close to those of the second observer's annotations
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