Synthetic peripherally-restricted cannabinoid suppresses chemotherapy-induced peripheral neuropathy pain symptoms by CB1 receptor activation.

Chemotherapy-induced peripheral neuropathy (CIPN) is a severe and dose-limiting side effect of cancer treatment that affects millions of cancer survivors throughout the world and current treatment options are extremely limited by their side effects. Cannabinoids are highly effective in suppressing pain symptoms of chemotherapy-induced and other peripheral neuropathies but their widespread use is limited by central nervous system (CNS)-mediated side effects. Here, we tested one compound from a series of recently developed synthetic peripherally restricted cannabinoids (PRCBs) in a rat model of cisplatin-induced peripheral neuropathy. Results show that local or systemic administration of 4-{2-[-(1E)-1[(4-propylnaphthalen-1-yl)methylidene]-1H-inden-3-yl]ethyl}morpholine (PrNMI) dose-dependently suppressed CIPN mechanical and cold allodynia. Orally administered PrNMI also dose-dependently suppressed CIPN allodynia symptoms in both male and female rats without any CNS side effects. Co-administration with selective cannabinoid receptor subtype blockers revealed that PrNMI's anti-allodynic effects are mediated by CB1 receptor (CB1R) activation. Expression of CB2Rs was reduced in dorsal root ganglia from CIPN rats, whereas expression of CB1Rs and various endocannabinoid synthesizing and metabolizing enzymes was unaffected. Daily PrNMI treatment of CIPN rats for two weeks showed a lack of appreciable tolerance to PrNMI's anti-allodynic effects. In an operant task which reflects cerebral processing of pain, PrNMI also dose-dependently suppressed CIPN pain behaviors. Our results demonstrate that PRCBs exemplified by PrNMI may represent a viable option for the treatment of CIPN pain symptoms

Mapping Free Energy Pathways for ATP Hydrolysis in the E. coli ABC Transporter HlyB by the String Method

HlyB functions as an adenosine triphosphate (ATP)-binding cassette (ABC) transporter that enables bacteria to secrete toxins at the expense of ATP hydrolysis. Our previous work, based on potential energy profiles from combined quantum mechanical and molecular mechanical (QM/MM) calculations, has suggested that the highly conserved H-loop His residue H662 in the nucleotide binding domain (NBD) of E. coli HlyB may catalyze the hydrolysis of ATP through proton relay. To further test this hypothesis when entropic contributions are taken into account, we obtained QM/MM minimum free energy paths (MFEPs) for the HlyB reaction, making use of the string method in collective variables. The free energy profiles along the MFEPs confirm the direct participation of H662 in catalysis. The MFEP simulations of HlyB also reveal an intimate coupling between the chemical steps and a local protein conformational change involving the signature-loop residue S607, which may serve a catalytic role similar to an Arg-finger motif in many ATPases and GTPases in stabilizing the phosphoryl-transfer transition state

Advanced Convolutional Neural Network and Long Short-Term Memory Model for Real-Time Spam Detection in Internet of Things Devices

The proliferation of the Internet of Things has seen higher vulnerability to different cyber threats, most notably spam attacks, represents a major risk for device functionality and user privacy. In this study, Authors presents an advanced hybrid deep learning model with the combination of Convolutional Neural Networks and Long Short-Term Memory networks for real-time spam detections on IoT devices. This CNN-LSTM model is designed to deal with the complex and changing IoT environments. This model handles the complexities of spam detection in the sequence data streams common in IoT networks by combining spatial feature extraction offered by CNNs and potential temporal pattern recognition capabilities at which LSTMs excel. One of the fundamental parts of this model lies in its suitability for device strain and limited computational resources. It works well enough that spam can be effectively filtered out, but with a nearly zero processing load on IoT systems. This is important because performance like this will be equivalent to the latency constraints in many real-time applications. Comprehensive testing with real-world datasets shows that this CNN-LSTM model performs better than traditional detection methods, achieving high accuracy and low latency. This move adds to the wider effort of creating more cost-effective, real-time cybersecurity solutions for IoT ecosystems while boosting security and reliability for large-scale IoT deployments

Dual Role of Electron-Accepting Metal-Carboxylate Ligands: Reversible Expansion of Exciton Delocalization and Passivation of Nonradiative Trap-States in Molecule-like CdSe Nanocrystals

This paper reports large bathochromic shifts of up to 260 meV in both the excitonic absorption and emission peaks of oleylamine (OLA)-passivated molecule-like (CdSe)34 nanocrystals caused by postsynthetic treatment with the electron accepting Cd(O2CPh)2 complex at room temperature. These shifts are found to be reversible upon removal of Cd(O2CPh)2 by N,N,N′,N′-tetramethylethylene-1,2-diamine. 1H NMR and FTIR characterizations of the nanocrystals demonstrate that the OLA remained attached to the surface of the nanocrystals during the reversible removal of Cd(O2CPh)2. On the basis of surface ligand characterization, X-ray powder diffraction measurements, and additional control experiments, we propose that these peak red shifts are a consequence of the delocalization of confined exciton wave functions into the interfacial electronic states that are formed from interaction of the LUMO of the nanocrystals and the LUMO of Cd(O2CPh)2, as opposed to originating from a change in size or reorganization of the inorganic core. Furthermore, attachment of Cd(O2CPh)2 to the OLA-passivated (CdSe)34 nanocrystal surface increases the photoluminescence quantum yield from 5% to an unprecedentedly high 70% and causes a 3-fold increase of the photoluminescence lifetime, which are attributed to a combination of passivation of nonradiative surface trap states and relaxation of exciton confinement. Taken together, our work demonstrates the unique aspects of surface ligand chemistry in controlling the excitonic absorption and emission properties of ultrasmall (CdSe)34 nanocrystals, which could expedite their potential applications in solid-state device fabrication

Ultrahigh-temperature microwave annealing of Al⁺- and P⁺-implanted 4H-SiC

In this work, an ultrafast solid-state microwaveannealing has been performed, in the temperature range of 1700–2120°C on Al⁺- and P⁺-implanted 4H-SiC. The solid-state microwave system used in this study is capable of raising the SiC sample temperatures to extremely high values, at heating rates of ∼600°C∕s. The samples were annealed for 5–60s in a pure nitrogen ambient. Atomic force microscopy performed on the annealed samples indicated a smooth surface with a rms roughness of 1.4nm for 5×5μm² scans even for microwaveannealing at 2050°C for 30s. Auger sputter profiling revealed a <7nm thick surface layer composed primarily of silicon, oxygen, and nitrogen for the samples annealed in N₂, at annealing temperatures up to 2100°C. X-ray photoelectron spectroscopy revealed that this surface layer is mainly composed of silicon oxide and silicon nitride. Secondary ion mass spectrometry depth profiling confirmed almost no dopant in diffusion after microwaveannealing at 2100°C for 15s. However, a sublimation of ∼100nm of the surface SiC layer was observed for 15sannealing at 2100°C. Rutherford backscattering spectra revealed a lattice damage-free SiC material after microwaveannealing at 2050°C for 15s, with scattering yields near the virgin SiC material. Van der Pauw–Hall measurements have revealed sheet resistance values as low as 2.4kΩ∕□ for Al⁺-implanted material annealed at 2100°C for 15s and 14Ω∕□ for the P+-implanted material annealed at 1950°C for 30s. The highest electron and hole mobilities measured in this work were 100 and 6.8cm2/Vs, respectively, for the P⁺- and Al⁺-implanted materials.The GMU work is supported by Army Research Of- fice Dr. Prater under Grant No. W911NF-04-1-0428 and a subcontract from LT Technologies under NSF SBIR Grant No. 0539321

Cost-effective strategies for the long-term management of diabetes mellitus

Diabetes mellitus (DM) is a significant public health problem that afflicted approximately 29.1 million Americans in 2012 (CDC, 2014). The estimated cost of diabetes in the United States in 2012 was $245 billion, including$176 billion in direct medical costs and $69 billion in reduced productivity (ADA, 2013a). To reach a diagnosis of DM, a clinician generally relies on fasting plasma glucose (FPG), the oral glucose tolerance test (OGTT), and/or the Hemoglobin A1c (HbA1c) test (ADA, 2013b). Current noninsulin antidiabetic medications include sulfonylureas, GLP-1 analogues, DPP-4 inhibitors, biguanides, thiazolidinediones, and SGLT2 inhibitors (Kaiser & Oetjen, 2014). Insulin therapies include basal (long-acting insulin analogues), biphasic (premixed insulin analogues), prandial (short-acting insulin analogues), and basal bolus (a combination of long-acting and short-acting insulin analogues) (Esposito et al., 2012). The aim of this study is to review the existing literature on the cost effectiveness of diabetes interventions to develop a standardized protocol for early type 2 diabetes care that can be delivered through primary care providers. The substantial cost effectiveness of preventative measures, including ad campaigns and outreach programs, has already been established (Mendis & Chestnov, 2013). Screening for impaired glucose tolerance early and implementing lifestyle and pharmacological changes at an early stage are also considered cost effective approaches for the long-term management of diabetes mellitus (Gillies et al., 2008). This study utilizes six cost effectiveness analyses on both clinical and non-clinical interventions to determine a standardized protocol for screening, diagnosing, and treating DM. Noninsulin antidiabetic drugs accounted for 78.4% of the 154.4 million prescriptions for antidiabetic drugs filled in 2012 (Hampp et al., 2014). Approximately half of the noninsulin antidiabetic drugs filled in 2012 was for metformin, whereas roughly a quarter of the same category was for sulfonylureas (Hampp et al., 2014). In decreasing order, long-acting human analog insulin and fast-acting human analog insulin were the most popular insulin variants in the insulin antidiabetic drug market (Hampp et al., 2014). Of the noninsulin antidiabetic drugs, the highest proportion of diabetic patients who achieved the HbA1C target of <7% were those taking sustained release exenatide (a GLP-1 analog) (63.2%) (Esposito et al., 2012). Of the insulin varieties, the highest proportion of diabetic patients who achieved the HbA1C target of <7% were those using basal bolus insulin (50.2%) (Esposito et al., 2012). While there are some concerns about the ability of diabetic patients with chronic kidney disease to clear metformin via renal excretion, extensive clinical experience supports its use in diabetic patients with mild to moderate renal impairment (Inzucchi et al., 2014). From the cost effectiveness studies, lifestyle modification (i.e., changes in diet and exercise) beginning at any age was determined to be a cost-effective approach in preventing and treating DM and may be cost saving for adults between the age of 25 to 44 (Herman et al., 2005). Screening for DM beginning at age 45 and repeating every three years if negative provides the best balance of effectiveness and cost effectiveness (Kahn et al., 2010). As a first-line clinical intervention, metformin was established to be cost-effective as well in treating DM (but less so compared to lifestyle modification) (Herman et al., 2005). Bariatric surgery for diabetics with a BMI greater than or equal to 35 kg/m2 has also been established as cost effective (Hoerger et al., 2010). Next, in considering the ideal frequency of clinical consultations, diabetics with a stable condition (assessed as HbA1c ≤7.5%, blood pressure ≤145 mmHg, and total cholesterol ≤201 mg/dL) can safely be seen by a primary care provider every six months compared to every three months with no noticeable decline in long-term health outcomes (Wermeling et al., 2014). For cases of T2D that cannot be simply controlled with metformin, sulfonylurea has shown that it is overall more cost-effective and effective as a second-line therapy when compared to DPP-4 inhibitors and GLP-1 analogs (Zhang et al., 2014). Cost effectiveness analysis of the long-acting analogue insulin detemir across different countries reveals substantially different cost effectiveness for the medication in terms of both nominal and purchasing power terms (Home et al., 2014). The results of these studies were parsed to establish a long-term clinical protocol for primary care providers in screening, diagnosing, and treating type 2 diabetes. Future studies should focus on integrating cost effectiveness and comparative effectiveness research in implementing even more nuanced clinical decisions through a structured protocol. The cost effectiveness of existing and new interventions--both clinical and non-clinical in nature--will also need to be continuously assessed to ensure that the measurements incorporate the most accurate set of assumptions on costs and effectiveness

Digital Model-Based Engineering: Expectations, Prerequisites, and Challenges of Infusion

Digital model-based engineering (DMbE) is the use of digital artifacts, digital environments, and digital tools in the performance of engineering functions. DMbE is intended to allow an organization to progress from documentation-based engineering methods to digital methods that may provide greater flexibility, agility, and efficiency. The term 'DMbE' was developed as part of an effort by the Model-Based Systems Engineering (MBSE) Infusion Task team to identify what government organizations might expect in the course of moving to or infusing MBSE into their organizations. The Task team was established by the Interagency Working Group on Engineering Complex Systems, an informal collaboration among government systems engineering organizations. This Technical Memorandum (TM) discusses the work of the MBSE Infusion Task team to date. The Task team identified prerequisites, expectations, initial challenges, and recommendations for areas of study to pursue, as well as examples of efforts already in progress. The team identified the following five expectations associated with DMbE infusion, discussed further in this TM: (1) Informed decision making through increased transparency, and greater insight. (2) Enhanced communication. (3) Increased understanding for greater flexibility/adaptability in design. (4) Increased confidence that the capability will perform as expected. (5) Increased efficiency. The team identified the following seven challenges an organization might encounter when looking to infuse DMbE: (1) Assessing value added to the organization. Not all DMbE practices will be applicable to every situation in every organization, and not all implementations will have positive results. (2) Overcoming organizational and cultural hurdles. (3) Adopting contractual practices and technical data management. (4) Redefining configuration management. The DMbE environment changes the range of configuration information to be managed to include performance and design models, database objects, as well as more traditional book-form objects and formats. (5) Developing information technology (IT) infrastructure. Approaches to implementing critical, enabling IT infrastructure capabilities must be flexible, reconfigurable, and updatable. (6) Ensuring security of the single source of truth (7) Potential overreliance on quantitative data over qualitative data. Executable/ computational models and simulations generally incorporate and generate quantitative vice qualitative data. The Task team also developed several recommendations for government, academia, and industry, as discussed in this TM. The Task team recommends continuing beyond this initial work to further develop the means of implementing DMbE and to look for opportunities to collaborate and share best practices