Gamma-ray Bursts, Classified Physically

From Galactic binary sources, to extragalactic magnetized neutron stars, to long-duration GRBs without associated supernovae, the types of sources we now believe capable of producing bursts of gamma-rays continues to grow apace. With this emergent diversity comes the recognition that the traditional (and newly formulated) high-energy observables used for identifying sub-classes does not provide an adequate one-to-one mapping to progenitors. The popular classification of some > 100 sec duration GRBs as ``short bursts'' is not only an unpalatable retronym and syntactically oxymoronic but highlights the difficultly of using what was once a purely phenomenological classification to encode our understanding of the physics that gives rise to the events. Here we propose a physically based classification scheme designed to coexist with the phenomenological system already in place and argue for its utility and necessity.Comment: 6 pages, 3 figures. Slightly expanded version of solicited paper to be published in the Proceedings of ''Gamma Ray Bursts 2007,'' Santa Fe, New Mexico, November 5-9. Edited by E. E. Fenimore, M. Galassi, D. Palme

Taking Gene Therapy into the Clinic

Gene therapy represents a promising novel treatment strategy for colorectal cancer. Preclinical data has been encouraging and several clinical trials are underway. Many phase 1 trials have proven the safety of the reagents but have yet to demonstrate significant therapeutic benefit. Ongoing efforts are being made to improve the efficiency of gene delivery and accuracy of gene targeting with the aim of enhancing antitumor potency. It is envisaged that gene therapy will be used in combination with other therapies including surgery, chemotherapy, and radiotherapy to facilitate the improvements in cancer treatments in the future

Solvation entropy, enthalpy and free energy prediction using a multi-task deep learning functional in 1D-RISM

Simultaneous calculation of entropies, enthalpies and free energies has been a long-standing challenge in computational chemistry, partly because of the difficulty in obtaining estimates of all three properties from a single consistent simulation methodology. This has been particularly true for methods from the Integral Equation Theory of Molecular Liquids such as the Reference Interaction Site Model which have traditionally given large errors in solvation thermodynamics. Recently, we presented pyRISM-CNN, a combination of the 1 Dimensional Reference Interaction Site Model (1D-RISM) solver, pyRISM, with a deep learning based free energy functional, as a method of predicting solvation free energy (SFE). With this approach, a 40-fold improvement in prediction accuracy was delivered for a multi-solvent, multi-temperature dataset when compared to the standard 1D-RISM theory [Fowles et al., Digital Discovery, 2023, 2, 177–188]. Here, we report three further developments to the pyRISM-CNN methodology. Firstly, solvation free energies have been introduced for organic molecular ions in methanol or water solvent systems at 298 K, with errors below 4 kcal mol−1 obtained without the need for corrections or additional descriptors. Secondly, the number of solvents in the training data has been expanded from carbon tetrachloride, water and chloroform to now also include methanol. For neutral solutes, prediction errors nearing or below 1 kcal mol−1 are obtained for each organic solvent system at 298 K and water solvent systems at 273–373 K. Lastly, pyRISM-CNN was successfully applied to the simultaneous prediction of solvation enthalpy, entropy and free energy through a multi-task learning approach, with errors of 1.04, 0.98 and 0.47 kcal mol−1, respectively, for water solvent systems at 298 K

Alemtuzumab improves neurological functional systems in treatment-naive relapsing-remitting multiple sclerosis patients.

BACKGROUND: Individual functional system scores (FSS) of the Expanded Disability Status Scale (EDSS) play a central role in determining the overall EDSS score in patients with early-stage multiple sclerosis (MS). Alemtuzumab treatment improves preexisting disability for many patients; however, it is unknown whether improvement is specific to certain functional systems. OBJECTIVE: We assessed the effect of alemtuzumab on individual FSS of the EDSS. METHODS: CAMMS223 was a 36-month, rater-blinded, phase 2 trial; treatment-naive patients with active relapsing-remitting MS, EDSS ≤3, and symptom onset within 3 years were randomized to annual courses of alemtuzumab or subcutaneous interferon beta-1a (SC IFNB-1a) 44 μg three times weekly. RESULTS: Alemtuzumab-treated patients had improved outcomes versus SC IFNB-1a patients on most FSS at Month 36; the greatest effect occurred for sensory, pyramidal, and cerebellar FSS. Among patients who experienced 6-month sustained accumulation of disability, clinical worsening occurred most frequently in the brainstem and sensory systems. For patients with 6-month sustained reduction in preexisting disability, pyramidal and sensory systems contributed most frequently to clinical improvement. CONCLUSIONS: Alemtuzumab demonstrated a broad treatment effect in improving preexisting disability. These findings may influence treatment decisions in patients with early, active relapsing-remitting MS displaying neurological deficits. ClinicalTrials.gov Identifier NCT00050778.Funding was provided by Sanofi Genzyme and Bayer Healthcare Pharmaceuticals. The authors would like to thank Marco Rizzo and Isabel Firmino for reviewing and providing input on the manuscript; Isabel Firmino is an employee of Sanofi Genzyme; Marco Rizzo was an employee of Sanofi Genzyme at the time the work was conducted. Data analysis was carried out by Linda Kasten, PROMETRIKA, LLC, Cambridge, MA, USA, which was supported by Sanofi Genzyme. Editorial support for this manuscript was provided by Fiona Nitsche, PhD, and Susan M Kaup, PhD, which was funded by Sanofi Genzyme. Fiona Nitsche is an employee of Evidence Scientific Solutions; Susan M Kaup was an employee of Evidence Scientific Solutions at the time the work was conducted.This is the final version of the article. It first appeared from Elsevier via http://dx.doi.org/10.1016/j.jns.2016.02.02

Roadway Lighting's Impact on Altering Soybean Growth: Volume 1

The impact of roadway lighting on soybean plant growth and development was measured in situ at seven locations in the state of Illinois. The plant data collection included periodic height, reproductive-stage, and Normalized Difference Vegetation Index (NDVI), as well as plant moisture content and dried seed weight after harvest. The periodic measurements were made at the same locations over time to determine delays in plant development. The impact of roadway lighting trespass was significant and measurable above thresholds of both horizontal and vertical illuminance as well as a combination of the two. A specification was drafted to minimize the impact of roadway lighting trespass on the soybean, and countermeasures were recommended to control the impact of lighting on the soybean.IDOT-R27-172Ope

Accurately predicting solvation free energy in aqueous and organic solvents beyond 298 K by combining deep learning and the 1D reference interaction site model

We report a method to predict the absolute solvation free energy (SFE) of small organic and druglike molecules in water, carbon tetrachloride and chloroform solvents beyond 298 K by combining the 1 Dimensional Reference Interaction Site Model (1D-RISM) and deep learning. RISM is a statistical mechanics based method for modelling molecular solutions that is computationally inexpensive but is too inaccurate for routine SFE calculations in its common form. By replacing the 1D-RISM SFE functional with a 1D convolutional neural network (CNN) trained on RISM correlation functions, we show that predictions approaching chemical accuracy can be obtained for aqueous and non-aqueous solvents at a wide-range of temperatures. This method builds upon the previously reported RISM-MOL-INF procedure which applied RISM to accurately characterise solvation and desolvation processes through solute–solvent correlation functions [Palmer et al., Mol. Pharm., 2015, 12, 3420–3432]. Unlike RISM-MOL-INF however, the newly developed pyRISM-CNN model applied here is capable of rapidly modelling these processes in several different solvents and at a wide-range of temperatures. The pyRISM-CNN functional reduces the predictive error by up to 40-fold as compared to the standard 1D-RISM theory. Prediction errors below 1 kcal mol−1 are obtained for organic solutes in carbon tetrachloride or chloroform solvent systems at 298 K and water solvent systems at 273–373 K. pyRISM-CNN has been implemented in our in-house 1D-RISM solver (pyRISM), which is made freely available as open-source software

Differential dopamine function in fibromyalgia

Approximately 30% of Americans suffer from chronic pain disorders, such as fibromyalgia (FM), which can cause debilitating pain. Many pain-killing drugs prescribed for chronic pain disorders are highly addictive, have limited clinical efficacy, and do not treat the cognitive symptoms reported by many patients. The neurobiological substrates of chronic pain are largely unknown, but evidence points to altered dopaminergic transmission in aberrant pain perception. We sought to characterize the dopamine (DA) system in individuals with FM. Positron emission tomography (PET) with [18F]fallypride (FAL) was used to assess changes in DA during a working memory challenge relative to a baseline task, and to test for associations between baseline D2/D3 availability and experimental pain measures. Twelve female subjects with FM and eleven female controls completed study procedures. Subjects received one FAL PET scan while performing a “2-back” task, and one while performing a “0-back” (attentional control, “baseline”) task. FM subjects had lower baseline FAL binding potential (BP) in several cortical regions relative to controls, including anterior cingulate cortex. In FM subjects, self-reported spontaneous pain negatively correlated with FAL BP in the left orbitofrontal cortex and parahippocampal gyrus. Baseline BP was significantly negatively correlated with experimental pain sensitivity and tolerance in both FM and CON subjects, although spatial patterns of these associations differed between groups. The data suggest that abnormal DA function may be associated with differential processing of pain perception in FM. Further studies are needed to explore the functional significance of DA in nociception and cognitive processing in chronic pain

Combinations of Griffithsin with Other Carbohydrate-Binding Agents Demonstrate Superior Activity Against HIV Type 1, HIV Type 2, and Selected Carbohydrate-Binding Agent-Resistant HIV Type 1 Strains

Abstract Carbohydrate-binding agents (CBAs) are potential HIV microbicidal agents with a high genetic barrier to resistance. We wanted to evaluate whether two mannose-specific CBAs, recognizing multiple and often distinct glycan structures on the HIV envelope gp120, can interact synergistically against HIV-1, HIV-2, and HIV-1 strains that were selected for resistance against particular CBAs [i.e., 2G12 mAb and microvirin (MVN)]. Paired CBA/CBA combinations mainly showed synergistic activity against both wild-type HIV-1 and HIV-2 but also 2G12 mAb- and MVN-resistant HIV-1 strains as based on the median effect principle with combination indices (CIs) ranging between 0.29 and 0.97. Upon combination, an increase in antiviral potency of griffithsin (GRFT) up to ?12-fold (against HIV-1), ?8-fold (against HIV-2), and ?6-fold (against CBA-resistant HIV-1) was observed. In contrast, HHA/GNA combinations showed additive activity against wild-type HIV-1 and HIV-2 strains, but remarkable synergy with HHA and GNA was observed against 2G12 mAb- and MVN-resistant HIV-1 strains (CI, 0.64 and 0.49, respectively). Overall, combinations of GRFT and other CBAs showed synergistic activity against HIV-1, HIV-2, and even against certain CBA-resistant HIV-1 strains. The CBAs tested appear to have distinct binding patterns on the gp120 envelope and therefore do not necessarily compete with each other's glycan binding sites on gp120. As a result, there might be no steric hindrance between two different CBAs in their competition for glycan binding (except for the HHA/GNA combination). These data are encouraging for the use of paired CBA combinations in topical microbicide applications (e.g., creams, gels, or intravaginal rings) to prevent HIV transmission.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/98459/1/aid%2E2012%2E0026.pd