Biodegradable microparticles and in situ forming implants/microparticles containing drugs in different physical states

PLGA drug delivery systems have been widely investigated as carriers for sustained drug release. But incorporating nanosized drugs or excipients into these systems was not been systematically studied until now. This research aimed first to understand the specific properties of PLGA microparticles loaded with nanosized drug when compared to micronized and dissolved drug. Then optimize the manufacturing process and formulation parameters of PLGA drug delivery systems incorporating nanosized drugs. And finally, investigate the possibility of using sugar particles and an optimized manufacturing process to prepare porous PLGA drug delivery systems. Quasi-linear release was obtained by encapsulating 10 % nanosized dexamethasone into PLGA 502H and 503H microparticles. Quick wetting process and homogenous distribution of nanosized drugs inside microparticles helped to form a uniform inner network and thus eliminated the lag phase. Dexamethasone, hydrocortisone and dexamethasone sodium phosphate nanosuspensions (200 – 300 nm) were successfully prepared by wet bead milling in dichloromethane using PLGA as a milling stabilizer, and then encapsulated inside the microparticles. Most microparticles’ encapsulation efficiencies were larger than 80 %. By changing PLGA types, selecting microparticle sizes, varying drug loadings, and using PLGA blends, the release profiles could be modified and a quasi-linear release without a lag phase was obtained. Incorporating nanosized dexamethasone into PLGA in situ forming systems increased systems’ viscosities, which resulted in better physical stability for at least 3 months, a smaller burst release, increased drug release during lag phase and a longer release period, compared to dissolved and micronized dexamethasone. The usage of nanosized/micronized sugar particles as porogen can introduce porosity within PLGA microparticles containing dexamethasone using S/O/W method. The porosity of the microparticles is caused both by the influx of water into the oil droplets and the encapsulation and subsequent dissolution of sugar particles during the manufacturing process. Overall, the introduction of nanosized/micronized sugar particles resulted in porous PLGA microparticles with high encapsulation efficiency. Designed porosity and pore size, as well as modifiable in vitro drug release could be achieved via the selection of appropriate particle size and weight fraction of nanosized/micronized sugar particles. The successful completion of this research can instruct the development of PLGA formulations. Firstly, this work will aid future research in PLGA microparticles in terms of choosing drug particle sizes and dispersion states. Secondly, this study will be helpful in the design and development of PLGA formulations loaded with drug nanocrystals in a simplified process by combining non-aqueous wet bead milling and subsequent microencapsulation. Further, this study presents a newly developed PLGA in situ forming system incorporating nanosized drug. Finally, this research is also an important step toward the development of porous PLGA microparticles using nanosized sugar particles as porogen which can adjust the drug release

SURFACE CROSSING AND ENERGY FLOW IN MANY-DIMENSIONAL QUANTUM SYSTEMS

Vibrational energy flow in molecules, like the dynamics of other many dimensional finite systems, involves quantum transport across a dense network of near resonant states. For molecules in their electronic ground state, the network is ordinarily provided by anharmonic vibrational Fermi resonances. Surface crossing between different electronic states provides another route to chaotic motion and energy redistribution. We show that nonadiabatic coupling between electronic energy surfaces facilitates vibrational energy flow, and conversely, anharmonic vibrational couplings facilitate nonadiabatic electronic state mixing. A generalization of the Logan-Wolynes theory of quantum energy flow in many-dimensional Fermi resonance systems to the two-surface case gives a phase diagram describing the boundary between localized quantum dynamics and global energy flow. We explore these predictions and test them using a model inspired by the problem of electronic excitation energy transfer in the photosynthetic reaction center. Using an explicit numerical solution of the time dependent Schrödinger equation for this ten-dimensional model, we find quite good agreement with the expectations from the approximate analytical theory

A Phase Diagram For Energy Flow-limited Reactivity

\begin{wrapfigure}{r}{0pt} \includegraphics[scale=0.15]{Figure1.eps} \end{wrapfigure} Intramolecular vibrational redistributionis often assumed in Rice–Ramsperger–Kassel–Marcus and other rate calculations. In contrast, experimental spectroscopy, computational results, and models based on Anderson localization have shown that ergodicity is achieved rather slowly during molecular energy flow and the statistical assumption might easily fail due to quantum localization. Here, we develop a simple model for the interplay of IVR and energy transfer and simulate the model with near-exact quantum dynamics for 10-degree of freedom system. We find that there is a rather sharp “phase transition” as a function of molecular anharmonicity “a” between a region of facile energy transfer and a region limited by IVR with incomplete accessibility of the state space. The very narrow transition range of the order parameter "a" happens to lie right in the middle of the range expected for molecular vibrations, thus demonstrating that reactive energy transfer dynamics occurs not far from the localization boundary,with implications for controllability of reactions. This work is publised on JCP: doi: 10.1063/5.004366

Quantum Scrambling In Molecules

\begin{wrapfigure}{I}{0pt} \includegraphics[scale=0.3]{Fig1.eps} \end{wrapfigure} In quantum systems, out of time order correlators (OTOCs) can be used to probe the sensitivity of the dynamics to perturbing the Hamiltonian or changing the initial conditions ordinarily associated with classical chaos or its quantum analog. The vibrations of polyatomic molecules are known to undergo a transition from regular dynamics at low energy to facile energy flow at sufficiently high energy. Molecules therefore represent ideal quantum systems to study the transition to chaos in many-body systems of moderate size (here 6 to 36 degrees of freedom). By computing quantum OTOCs and their classical counterparts we quantify how information becomes ‘scrambled’ quantum mechanically in molecular systems

CNN or ViT? Revisiting Vision Transformers Through the Lens of Convolution

The success of Vision Transformer (ViT) has been widely reported on a wide range of image recognition tasks. The merit of ViT over CNN has been largely attributed to large training datasets or auxiliary pre-training. Without pre-training, the performance of ViT on small datasets is limited because the global self-attention has limited capacity in local modeling. Towards boosting ViT on small datasets without pre-training, this work improves its local modeling by applying a weight mask on the original self-attention matrix. A straightforward way to locally adapt the self-attention matrix can be realized by an element-wise learnable weight mask (ELM), for which our preliminary results show promising results. However, the element-wise simple learnable weight mask not only induces a non-trivial additional parameter overhead but also increases the optimization complexity. To this end, this work proposes a novel Gaussian mixture mask (GMM) in which one mask only has two learnable parameters and it can be conveniently used in any ViT variants whose attention mechanism allows the use of masks. Experimental results on multiple small datasets demonstrate that the effectiveness of our proposed Gaussian mask for boosting ViTs for free (almost zero additional parameter or computation cost). Our code will be publicly available at \href{https://github.com/CatworldLee/Gaussian-Mixture-Mask-Attention}{https://github.com/CatworldLee/Gaussian-Mixture-Mask-Attention}

Dexamethasone-releasing PLGA films containing sucrose particles as porogens

The objective of this study was to investigate the use of sucrose particles as a porogen for preparing porous poly (lactide-co-glycolide) (PLGA) films containing dexamethasone by solvent casting technique to modulate PLGA degradation and drug release. Increasing the sucrose content up to 30 % decreased PLGA degradation and extended the drug release duration, a further increase to more than 60 % shortened the release duration. Sucrose created cavities and increased the internal pore surface area for the exchange of degraded acidic oligomers and monomers. This process decreased the autocatalysis within the PLGA matrix, resulting in slower drug release at lower sucrose content. At higher sucrose content, the interconnectivity of the PLGA matrix increased, accelerating the drug release of the entrapped drug. Decreasing the particle size of sucrose has a similar impact on PLGA degradation and drug release as increasing sucrose content. Smaller sucrose particles formed more cavities and a larger overall acidic exchange surface areas. Only 20 % nanosized sucrose resulted in a quasi-linear release profile with interconnected sucrose particles, while 60 % micronized or 100 % non-micronized sucrose particles were necessary to achieve the same effect. In conclusion, modifying the content and particle size of sucrose effectively altered PLGA degradation and drug release, with nanosized sucrose being the most effective porogen. The data obtained with PLGA films could be potentially applied to other PLGA drug delivery systems such as microparticles or implants