Palladium(II)-Catalysed Aminocarbonylation of Terminal Alkynes for the Synthesis of 2-Ynamides: Addressing the Challenges of Solvents and Gas Mixtures

2‐Ynamides can be synthesised through Pd(II) catalysed oxidative carbonylation, utilising low catalyst loadings. A variety of alkynes and amines can be used to afford 2‐ynamides in high yields, whilst overcoming the drawbacks associated with previous oxidative methods, which rely on dangerous solvents and gas mixtures. The use of [NBu(4)]I allows the utilisation of the industrially recommended solvent ethyl acetate. O(2) can be used as the terminal oxidant, and the catalyst can operate under safer conditions with low O(2) concentrations

Application of a single-objective, hybrid genetic algorithm approach to pharmacokinetic model building.

A limitation in traditional stepwise population pharmacokinetic model building is the difficulty in handling interactions between model components. To address this issue, a method was previously introduced which couples NONMEM parameter estimation and model fitness evaluation to a single-objective, hybrid genetic algorithm for global optimization of the model structure. In this study, the generalizability of this approach for pharmacokinetic model building is evaluated by comparing (1) correct and spurious covariate relationships in a simulated dataset resulting from automated stepwise covariate modeling, Lasso methods, and single-objective hybrid genetic algorithm approaches to covariate identification and (2) information criteria values, model structures, convergence, and model parameter values resulting from manual stepwise versus single-objective, hybrid genetic algorithm approaches to model building for seven compounds. Both manual stepwise and single-objective, hybrid genetic algorithm approaches to model building were applied, blinded to the results of the other approach, for selection of the compartment structure as well as inclusion and model form of inter-individual and inter-occasion variability, residual error, and covariates from a common set of model options. For the simulated dataset, stepwise covariate modeling identified three of four true covariates and two spurious covariates; Lasso identified two of four true and 0 spurious covariates; and the single-objective, hybrid genetic algorithm identified three of four true covariates and one spurious covariate. For the clinical datasets, the Akaike information criterion was a median of 22.3 points lower (range of 470.5 point decrease to 0.1 point decrease) for the best single-objective hybrid genetic-algorithm candidate model versus the final manual stepwise model: the Akaike information criterion was lower by greater than 10 points for four compounds and differed by less than 10 points for three compounds. The root mean squared error and absolute mean prediction error of the best single-objective hybrid genetic algorithm candidates were a median of 0.2 points higher (range of 38.9 point decrease to 27.3 point increase) and 0.02 points lower (range of 0.98 point decrease to 0.74 point increase), respectively, than that of the final stepwise models. In addition, the best single-objective, hybrid genetic algorithm candidate models had successful convergence and covariance steps for each compound, used the same compartment structure as the manual stepwise approach for 6 of 7 (86 %) compounds, and identified 54 % (7 of 13) of covariates included by the manual stepwise approach and 16 covariate relationships not included by manual stepwise models. The model parameter values between the final manual stepwise and best single-objective, hybrid genetic algorithm models differed by a median of 26.7 % (q₁ = 4.9 % and q₃ = 57.1 %). Finally, the single-objective, hybrid genetic algorithm approach was able to identify models capable of estimating absorption rate parameters for four compounds that the manual stepwise approach did not identify. The single-objective, hybrid genetic algorithm represents a general pharmacokinetic model building methodology whose ability to rapidly search the feasible solution space leads to nearly equivalent or superior model fits to pharmacokinetic data

Accuracy of In Vivo Multimodal Optical Imaging for Detection of Oral Neoplasia

If detected early, oral cancer is eminently curable. However, survival rates for oral cancer patients remain low, largely due to late-stage diagnosis and subsequent difficulty of treatment. To improve cliniciansﾒ ability to detect early disease and to treat advanced cancers, we developed a multimodal optical imaging system (MMIS) to evaluate tissue in situ, at macroscopic and microscopic scales. The MMIS was used to measure 100 anatomic sites in 30 patients, correctly classifying 98% of pathologically confirmed normal tissue sites, and 95% of sites graded as moderate dysplasia, severe dysplasia, or cancer. When used alone, MMIS classification accuracy was 35% for sites determined by pathology as mild dysplasia. However, MMIS measurements correlated with expression of candidate molecular markers in 87% of sites with mild dysplasia. These findings support the ability of noninvasive multimodal optical imaging to accurately identify neoplastic tissue and premalignant lesions. This in turn may have considerable impact on detection and treatment of patients with oral cancer and other epithelial malignancies

Spatially-selective in situ magnetometry of ultracold atomic clouds

We demonstrate novel implementations of high-precision optical magnetometers which allow for spatially-selective and spatially-resolved in situ measurements using cold atomic clouds. These are realised by using shaped dispersive probe beams combined with spatially-resolved balanced homodyne detection. Two magnetometer sequences are discussed: a vectorial magnetometer, which yields sensitivities two orders of magnitude better compared to a previous realisation and a Larmor magnetometer capable of measuring absolute magnetic fields. We characterise the dependence of single-shot precision on the size of the analysed region for the vectorial magnetometer and provide a lower bound for the measurement precision of magnetic field gradients for the Larmor magnetometer. Finally, we give an outlook on how dynamic trapping potentials combined with selective probing can be used to realise enhanced quantum simulations in quantum gas microscopes

A Fiber-Optic Fluorescence Microscope Using a Consumer-Grade Digital Camera for In Vivo Cellular Imaging

BACKGROUND: Early detection is an essential component of cancer management. Unfortunately, visual examination can often be unreliable, and many settings lack the financial capital and infrastructure to operate PET, CT, and MRI systems. Moreover, the infrastructure and expense associated with surgical biopsy and microscopy are a challenge to establishing cancer screening/early detection programs in low-resource settings. Improvements in performance and declining costs have led to the availability of optoelectronic components, which can be used to develop low-cost diagnostic imaging devices for use at the point-of-care. Here, we demonstrate a fiber-optic fluorescence microscope using a consumer-grade camera for in vivo cellular imaging. METHODS: The fiber-optic fluorescence microscope includes an LED light, an objective lens, a fiber-optic bundle, and a consumer-grade digital camera. The system was used to image an oral cancer cell line labeled with 0.01% proflavine. A human tissue specimen was imaged following surgical resection, enabling dysplastic and cancerous regions to be evaluated. The oral mucosa of a healthy human subject was imaged in vivo, following topical application of 0.01% proflavine. FINDINGS: The fiber-optic microscope resolved individual nuclei in all specimens and tissues imaged. This capability allowed qualitative and quantitative differences between normal and precancerous or cancerous tissues to be identified. The optical efficiency of the system permitted imaging of the human oral mucosa in real time. CONCLUSION: Our results indicate this device as a useful tool to assist in the identification of early neoplastic changes in epithelial tissues. This portable, inexpensive unit may be particularly appropriate for use at the point-of-care in low-resource settings

Carbohydrate scaffolds as glycosyltransferase inhibitors with in vivo antibacterial activity

The rapid rise of multi-drug-resistant bacteria is a global healthcare crisis, and new antibiotics are urgently required, especially those with modes of action that have low-resistance potential. One promising lead is the liposaccharide antibiotic moenomycin that inhibits bacterial glycosyltransferases, which are essential for peptidoglycan polymerization, while displaying a low rate of resistance. Unfortunately, the lipophilicity of moenomycin leads to unfavourable pharmacokinetic properties that render it unsuitable for systemic administration. In this study, we show that using moenomycin and other glycosyltransferase inhibitors as templates, we were able to synthesize compound libraries based on novel pyranose scaffold chemistry, with moenomycin-like activity, but with improved drug-like properties. The novel compounds exhibit in vitro inhibition comparable to moenomycin, with low toxicity and good efficacy in several in vivo models of infection. This approach based on non-planar carbohydrate scaffolds provides a new opportunity to develop new antibiotics with low propensity for resistance induction

Continuous-flow transfer hydrogenation of benzonitrile using formate as a safe and sustainable source of hydrogen †

The continuous catalytic transfer hydrogenation of benzonitrile to benzylamine is demonstrated using a palladium on carbon catalyst with triethylammonium formate as reducing agent. Solvent choice was critical in overcoming rapid catalyst deactivation. A 15-fold increase in catalyst productivity was observed in flow compared to batch, which was achieved using an ethanol–water solvent in combination with intermittent catalyst regeneration by washing with water

Interactions among oscillatory pathways in NF-kappa B signaling

<p>Abstract</p> <p>Background</p> <p>Sustained stimulation with tumour necrosis factor alpha (TNF-alpha) induces substantial oscillations—observed at both the single cell and population levels—in the nuclear factor kappa B (NF-kappa B) system. Although the mechanism has not yet been elucidated fully, a core system has been identified consisting of a negative feedback loop involving NF-kappa B (RelA:p50 hetero-dimer) and its inhibitor I-kappa B-alpha. Many authors have suggested that this core oscillator should couple to other oscillatory pathways.</p> <p>Results</p> <p>First we analyse single-cell data from experiments in which the NF-kappa B system is forced by short trains of strong pulses of TNF-alpha. Power spectra of the ratio of nuclear-to-cytoplasmic concentration of NF-kappa B suggest that the cells' responses are entrained by the pulsing frequency. Using a recent model of the NF-kappa B system due to Caroline Horton, we carried out extensive numerical simulations to analyze the response frequencies induced by trains of pulses of TNF-alpha stimulation having a wide range of frequencies and amplitudes. These studies suggest that for sufficiently weak stimulation, various nonlinear resonances should be observable. To explore further the possibility of probing alternative feedback mechanisms, we also coupled the model to sinusoidal signals with a wide range of strengths and frequencies. Our results show that, at least in simulation, frequencies other than those of the forcing and the main NF-kappa B oscillator can be excited via sub- and superharmonic resonance, producing quasiperiodic and even chaotic dynamics.</p> <p>Conclusions</p> <p>Our numerical results suggest that the entrainment phenomena observed in pulse-stimulated experiments is a consequence of the high intensity of the stimulation. Computational studies based on current models suggest that resonant interactions between periodic pulsatile forcing and the system's natural frequencies may become evident for sufficiently weak stimulation. Further simulations suggest that the nonlinearities of the NF-kappa B feedback oscillator mean that even sinusoidally modulated forcing can induce a rich variety of nonlinear interactions.</p

Loss of neuronal network resilience precedes seizures and determines the ictogenic nature of interictal synaptic perturbations

The mechanisms of seizure emergence, and the role of brief interictal epileptiform discharges (IEDs) in seizure generation are two of the most important unresolved issues in modern epilepsy research. Our study shows that the transition to seizure is not a sudden phenomenon,but a slow process characterized by the progressive loss of neuronal network resilience. From a dynamical perspective, the slow transition is governed by the principles of critical slowing, a robust natural phenomenon observable in systems characterized by transitions between dynamical regimes. In epilepsy, this process is modulated by the synchronous synaptic input from IEDs. IEDs are external perturbations that produce phasic changes in the slow transition process and exert opposing effects on the dynamics of a seizure-generating network, causing either anti-seizure or pro-seizure effects. We show that the multifaceted nature of IEDs is defined by the dynamical state of the network at the moment of the discharge occurrence