Transition metal complexes of tetracyclines

Forty-one transition metals were studied to observe their complexing properties with the tetracyclines. Four metals were found to form sufficiently strong complexes with the tetracyclines to provide a basis for a rapid, reliable method of assaying the potency of the tetracycline products used in medicine today. Microbiological methods take twenty hours to perform; spectrophotometric methods may be completed within one hour. Twenty-eight of the transition metals showed evidence of complex formation with the tetracyclines; not all of these complexes were found to be suitable for the spectrophotometric assay of the tetracyclines, however. The ligand-metal ratios of some of the transition metal-tetracycline complexes were determined under specified conditions using Job's method. In the concentration range for ligand and metal (3 x 10⁻⁵ M), the 1 : 1 complexes appeared to predominate. Attempts were made to identify the binding sites of the metal ions on the tetracycline molecules, using infra-red spectrophotometry, but the results were inconclusive. The stability constant of one of the transition metal-tetracycline complexes was determined by a potentiometric method. Using this method, the result for the titanium-tetracycline complex was β₁= 3,4 x 10¹⁵ M⁻¹

Housing as a Platform for Improving Education Outcomes Among Low-Income Children

Reviews research on how housing stability, affordability, quality, and location affect low-income children's safety, physical and mental health, and frequency of school changes, which in turn affect attendance, behavior, test scores, and graduation rates

Mixed metal nanoparticle assembly and the effect on surface enhanced raman scattering

Here we report the assembly of mixed metal nanoparticles using an oligonucleotide-templated approach. Substitution of one of the gold nanoparticle probes with an analagous silver probe to produce a hetero-metal duplex permitted surface enhanced Raman scattering of the dye label, exploiting the improved surface enhancement properties of silver nanoparticles whilst maintaining the surface chemistry benefits of gold nanoaprticle

Being a Feminist Community During a Pandemic: Our Editors’ Welcome

Volume 4, the pandemic issue of The Seneca Falls Dialogues Journal, features a selection of participants from our 2020 gathering who have transformed their conference offerings into articles for posterity, ones that aim to keep the dialogue going and widen the sphere of feminist inquiry

The Seneca Falls Dialogues Journal, v. 4, 2021 (complete issue)

Table of Contents Being a Feminist Community During a Pandemic: Our Editors’ Welcome by Jill Swiencicki, Lisa Cunningham, & Mary E. Graham Creating Seneca Falls Dialogues Journal by Deborah Uman & Barbara LeSavoy Disrupters: Three Women of Color Tell Their Stories by Dulce María Gray, Denise A. Harrison, & Yuko Kurahashi Contemporary Black Women’s Voting Rights Activism: Some Historical Perspective by Alison Parker, Valeria Sinclair-Chapman, & Naomi R. Williams Shapeshifting Power: Indigenous Teachings of Trickster Consciousness and Relational Accountability for Building Communities of Care by Ionah M. Elaine Scully Influencing Public Opinion: Public Relations and the Arrest of Susan B. Anthony by Arien Rozelle #THEMTOO: Two NFL Team Options for Not Exploiting Women Cheerleaders by Melanie Kelly, Colby A. Murphy, & Mary E. Graham Feminist Attitudes, Behaviors, and Culture Shaping Women’s Center Practice by Angela Clark-Taylor, Emily Creamer, Barbara LeSavoy, & Catherine Cerull

Inflammatory (B) symptoms are independent predictors of myelosuppression from chemotherapy in Non-Hodgkin Lymphoma (NHL) patients – analysis of data from a British National Lymphoma Investigation phase III trial comparing CHOP to PMitCEBO

<p>Abstract</p> <p>Background</p> <p>Toxicity from chemotherapy is highly variable, unpredictable and results in substantial morbidity and increased healthcare costs. New predictors of toxicity are required to improve the safety and efficacy of chemotherapy. Inflammatory or B symptoms in lymphoma are associated with elevated plasma inflammatory markers and predict worse treatment response and survival. Recent data suggest that systemic inflammation results in reduced hepatic drug metabolism and increased toxicity from chemotherapy. We investigated whether B symptoms were associated with greater toxicity in patients treated for non-Hodgkin lymphoma (NHL).</p> <p>Methods</p> <p>The British National Lymphoma Investigation compared two chemotherapy regimens in older patients with aggressive NHL. Approximately 50% of patients had B symptoms. Demographic and toxicity data on 664 patients were analysed to identify predictors of toxicity by multivariate analysis, with particular reference to B symptoms.</p> <p>Results</p> <p>Using univariate analyses, severe (grades 3–4) leucopenia, anaemia, thrombocytopenia, nausea and vomiting and diarrhoea occurred more frequently in patients with B symptoms. The associations between B symptoms and severe leucopenia (OR 1.7, p = 0.005) and anaemia (OR 2.3, p = 0.025) persisted after adjustment for other prognostic factors in multivariate analyses. The use of granulocyte colony stimulating factor reduced neutropenia in patients with both A and B symptoms.</p> <p>Conclusion</p> <p>For the first time and in a large NHL cohort we have shown that inflammatory symptoms are independent predictors for myelosuppression from chemotherapy. These data will enable improved prognostication for toxicity and provide individualisation of therapy in NHL and other tumours. These findings also create the potential for strategies used prior to chemotherapy aimed at reducing systemic inflammation in order to improve drug metabolism and reduce treatment-related toxicity.</p> <p>Trial registration number</p> <p>ISRCTN98741793</p

Privacy-preserving synthetic location data in the real world

Sharing sensitive data is vital in enabling many modern data analysis and machine learning tasks. However, current methods for data release are insufficiently accurate or granular to provide meaningful utility, and they carry a high risk of deanonymization or membership inference attacks. In this paper, we propose a differentially private synthetic data generation solution with a focus on the compelling domain of location data. We present two methods with high practical utility for generating synthetic location data from real locations, both of which protect the existence and true location of each individual in the original dataset. Our first, partitioning-based approach introduces a novel method for privately generating point data using kernel density estimation, in addition to employing private adaptations of classic statistical techniques, such as clustering, for private partitioning. Our second, network-based approach incorporates public geographic information, such as the road network of a city, to constrain the bounds of synthetic data points and hence improve the accuracy of the synthetic data. Both methods satisfy the requirements of differential privacy, while also enabling accurate generation of synthetic data that aims to preserve the distribution of the real locations. We conduct experiments using three large-scale location datasets to show that the proposed solutions generate synthetic location data with high utility and strong similarity to the real datasets. We highlight some practical applications for our work by applying our synthetic data to a range of location analytics queries, and we demonstrate that our synthetic data produces near-identical answers to the same queries compared to when real data is used. Our results show that the proposed approaches are practical solutions for sharing and analyzing sensitive location data privately