In order to introduce a cost-effective strategy method for commercial scale dry granulation at the early clinical stage of drug product development, we developed dry granulation process using formulation without API, fitted and optimized the process parameters adopted Design of Experiment (DOE). Then, the process parameters were confirmed using one formulation containing active pharmaceutical ingredient (API). The results showed that the roller pressure had significant effect on particle ratio (retained up to #60 mesh screen), bulk density and tapped density. The roller gap had significant influence on particle ratio and specific energy. The particle ratio was significantly affected by the mill speed (second level). The tabletability of the powder decreased after dry granulation. The effect of magnesium stearate on the tabletability was significant. In the process validation study, the properties of the prepared granules met the requirements for each response studied in the DOE. The prepared tablets showed higher tensile strength, good content uniformity of filled capsules, and the dissolution profiles of which were consistent with that of clinical products. This drug product process development and research strategies could be used as a preliminary experiment for the dry granulation process in the early clinical stage.

OBJECTIVE: Many studies suggested that short-term exposure to fine particulate matter (PM2.5) and coarse particulate matter (PM2.5-10) was linked to elevated risk of cerebrovascular disease. However, little is known about the potentially differential effects of PM2.5 and PM2.5-10 on various types of cerebrovascular disease.
METHODS: We collected individual cerebrovascular death records for all residents in Shanghai, China from 2005 to 2021. Residential daily air pollution data were predicted from a satellite model. The associations between particulate matters (PM) and cerebrovascular mortality were investigated by an individual-level, time-stratified, case-crossover design. The data was analyzed by the conditional logistic regression combined with the distributed lag model with a maximum lag of 7 days. Furthermore, we explored the effect modifications by sex, age and season.
RESULTS: A total of 388,823 cerebrovascular deaths were included. Monotonous increases were observed for mortality of all cerebrovascular diseases except for hemorrhagic stroke. A 10 μg/m3 rise in PM2.5 was related to rises of 1.35% [95% confidence interval (CI): 1.04%, 1.66%] in mortality of all cerebrovascular diseases, 1.84% (95% CI: 1.25%, 2.44%) in ischemic stroke, 1.53% (95% CI: 1.07%, 1.99%) in cerebrovascular sequelae and 1.56% (95% CI: 1.08%, 2.05%) in ischemic stroke sequelae. The excess risk estimates per each 10 μg/m3 rise in PM2.5-10 were 1.47% (95% CI: 1.10%, 1.84%), 1.53% (95% CI: 0.83%, 2.24%), 1.93% (95% CI: 1.38%, 2.49%) and 2.22% (95% CI: 1.64%, 2.81%), respectively. The associations of both pollutants with all cerebrovascular outcomes were robust after controlling for co-pollutants. The associations were greater in females, individuals > 80 years, and during the warm season.
CONCLUSIONS: Short-term exposures to both PM2.5 and PM2.5-10 may independently increase the mortality risk of cerebrovascular diseases, particularly of ischemic stroke and stroke sequelae.

OBJECTIVE: Drug inhalation is generally accepted as the preferred administration method for treating respiratory diseases. To achieve effective inhaled drug delivery for an individual, it is necessary to use an interdisciplinary approach that can cope with inter-individual differences. The paper aims to present an individualised pulmonary drug deposition model based on Computational Fluid and Particle Dynamics simulations within a time frame acceptable for clinical use.
METHODS: We propose a model that can analyse the inhaled drug delivery efficiency based on the patient\'s airway geometry as well as breathing pattern, which has the potential to also serve as a tool for a sub-regional diagnosis of respiratory diseases. The particle properties and size distribution are taken for the case of drug inhalation by using nebulisers, as they are independent of the patient\'s breathing pattern. Finally, the inhaled drug doses that reach the deep airways of different lobe regions of the patient are studied.
RESULTS: The numerical accuracy of the proposed model is verified by comparison with experimental results. The difference in total drug deposition fractions between the simulation and experimental results is smaller than 4.44% and 1.43% for flow rates of 60 l/min and 15 l/min, respectively. A case study involving a COVID-19 patient is conducted to illustrate the potential clinical use of the model. The study analyses the drug deposition fractions in relation to the breathing pattern, aerosol size distribution, and different lobe regions.
CONCLUSIONS: The entire process of the proposed model can be completed within 48 h, allowing an evaluation of the deposition of the inhaled drug in an individual patient\'s lung within a time frame acceptable for clinical use. Achieving a 48-hour time window for a single evaluation of patient-specific drug delivery enables the physician to monitor the patient\'s changing conditions and potentially adjust the drug administration accordingly. Furthermore, we show that the proposed methodology also offers a possibility to be extended to a detection approach for some respiratory diseases.

Particulate contaminants, such as microplastics (1 μm to 5 mm) and nanoplastics (<1 μm), are disseminated in many terrestrial environments. However, it is still unclear how particles\' properties drive their mobility through soils and aquifers due to (i) poor environmental relevance of the model particles that are studied (e.g., spherical and monodisperse) and (ii) the use of packed bed experiments which do not allow a direct observation of deposition dynamics. Using transparent 2D porous media, this study analyzes deposition dynamics of rough polystyrene fragments with irregular shapes and with a size continuum (≈10 nm to 5 μm). Using in situ and ex situ measurements, particle deposition as a function of size was monitored over time under repulsive conditions. In the absence of natural organic matter (NOM), micrometric particles rapidly deposit and promote the physical interception of smaller nanoparticles by creating local porous roughness or obstacles. In the presence of NOM, differences according to particle size were no longer observed, and all fragments were more prone to being re-entrained, thereby limiting the growth of deposits. This work demonstrates the importance of pore surface roughness and porosity of the pore surface for the deposition of colloidal particles, such as microplastics and nanoplastics, under repulsive conditions.

Encapsulating enzymes in metal-organic frameworks is a common practice to improve enzyme stability against harsh conditions. However, the synthesis of enzyme@MOFs has been primarily limited to small-scale laboratory settings, hampering their industrial applications. Spray drying is a scalable and cost-effective technology, which has been frequently used in industry for large-scale productions. Despite these advantages, its potential for encapsulating enzymes in MOFs remains largely unexplored, due to challenges such as nozzle clogging from MOF particle formation, utilization of toxic organic solvents, controlled release of encapsulated enzymes, and high temperatures that could compromise enzyme activity. Herein, we present a novel approach for preparing phytase@MIL-88 A using solvent-free spray drying. This involves atomizing two MOF precursor solutions separately using a three-fluid nozzle, with enzyme release controlled by manipulating defects within the MOFs. The physicochemical properties of the spray dried particles are characterized using X-ray diffraction, Fourier-transform infrared spectroscopy, and scanning electron microscopy. Leveraging the efficiency and scalability of spray drying in industrial production, this scalable encapsulation technique holds considerable promise for broad industrial applications.

BACKGROUND: The connections between fine particulate matter (PM2.5) and coarse particulate matter (PM2.5-10) and daily mortality of viral pneumonia and bacterial pneumonia were unclear.
OBJECTIVE: To distinguish the connections between PM2.5 and PM2.5-10 and daily mortality due to viral pneumonia and bacterial pneumonia.
METHODS: Using a comprehensive national death registry encompassing all areas of mainland China, we conducted a case-crossover investigation from 2013 to 2019 at an individual level. Residential daily particle concentrations were evaluated using satellite-based models with a spatial resolution of 1 km. To analyze the data, we employed the conditional logistic regression model in conjunction with polynomial distributed lag models.
RESULTS: We included 221,507 pneumonia deaths in China. Every interquartile range (IQR) elevation in concentrations of PM2.5 (lag 0-2 d, 37.6 μg/m3) was associated with higher magnitude of mortality for viral pneumonia (3.03%) than bacterial pneumonia (2.14%), whereas the difference was not significant (p-value for difference = 0.38). An IQR increase in concentrations of PM2.5-10 (lag 0-2 d, 28.4 μg/m3) was also linked to higher magnitude of mortality from viral pneumonia (3.06%) compared to bacterial pneumonia (2.31%), whereas the difference was not significant (p-value for difference = 0.52). After controlling for gaseous pollutants, their effects were all stable; however, with mutual adjustment, the associations of PM2.5 remained, and those of PM2.5-10 were no longer statistically significant. Greater magnitude of associations was noted in individuals aged 75 years and above, as well as during the cold season.
CONCLUSIONS: This nationwide study presents compelling evidence that both PM2.5 and PM2.5-10 exposures could increase pneumonia mortality of viral and bacterial causes, highlighting the more robust effects of PM2.5 and somewhat higher sensitivity of viral pneumonia.

Environmental RNA (eRNA) analysis is conventionally expected to infer physiological information about organisms within their ecosystems, whereas environmental DNA (eDNA) analysis only infers their presence and abundance. Despite the promise of eRNA application, basic research on eRNA characteristics and dynamics is limited. The present study conducted aquarium experiments using zebrafish (Danio rerio) to estimate the particle size distribution (PSD) of eRNA in order to better understand the persistence state of eRNA particles. Rearing water samples were sequentially filtered using different pore-size filters, and the resulting size-fractioned mitochondrial cytochrome b (CytB) eDNA and eRNA data were modeled with the Weibull complementary cumulative distribution function (CCDF) to estimate the parameters characterizing the PSDs. It was revealed that the scale parameter (α) was significantly higher (i.e., the mean particle size was larger) for eRNA than eDNA, while the shape parameter (β) was not significantly different between them. This result supports the hypothesis that most eRNA particles are likely in a protected, intra-cellular state, which mitigates eRNA degradation in water. Moreover, these findings also imply the heterogeneous dispersion of eRNA relative to eDNA and suggest an efficient method of eRNA collection using a larger pore-size filter. Further studies on the characteristics and dynamics of eRNA particles should be pursued in the future.

Spices are usually ground for applications and the resulting particle size of the powders is an important product attribute in view of the release of flavour. However, inhomogeneity of the original material may lead to variations in the physicochemical characteristics of the particles. This variation and its linkage to particle size may be examined by particular imaging techniques. This study aimed to explore the potential of Fluorescence Lifetime Imaging Microscopy (FLIM) to characterize spice powders according to particle size variations and correlation with their pigment contents to reveal the chemical information contained within the FLIM data. Ginger powder was used as a representative powder model. The FLIM profiles of the individual samples and populations revealed that FLIM coupled with the phasor approach has the capacity to characterize spice powder according to particle size. Meanwhile, Principal Component Analysis of pre-processed FLIM data revealed clustering of particle size groups. Further correlation analysis between the pigment compound contents and FLIM data of the ginger powders indicated that FLIM reflected chemical information of ginger powder and was able to visualize endogenous fluorophores. The current study revealed the potential of FLIM to characterize ginger powder particles. This approach may be extrapolated to other spice powder products. The new knowledge is a step further in paving the way for the application of innovative techniques, already prevalent in other domains, to food quality and authentication.

Titanium dioxide (TiO2) is used primarily as an opacifier in solid dosage forms and is present in the majority of tablet and capsule dosage forms on the market. The IQ* TiO2 Working Group has previously shown that titanium dioxide has unique properties which are necessary for its function in these formulations and noted that, as the potential replacements lack the semi-conductor properties, high refractive index and whiteness of E171, it might be hard to replicate these properties with alternative materials. In this paper we detail the results of readiness surveys and practical assessments that have been conducted with alternative materials by IQ member companies. A range of technical challenges and regulatory hurdles were identified which mean that, in the short term, it may be difficult to replace titanium dioxide with the currently available alternative materials while readily achieving the same drug product quality attributes, especially for some of the marketed formulations that titanium dioxide is currently used for. We note the higher technical complexity, due to the variability, color fading and identified scale up risk, of E171 free film coatings and the likely impact on development costs and timelines. We also highlight several regulatory hurdles that would have to be overcome if a titanium dioxide replacement was required for some markets but was not mandated by others.

Twin-screw wet granulation is an emerging continuous manufacturing technology for solid oral dosage forms. This technology has been successfully employed for the commercial manufacture of immediate-released tablets. However, the higher polymer content in extended-release (ER) formulations may present challenges in developing and operating within a desired design space. The work described here used a systematic approach for defining the optimum design space by understanding the effects of the screw design, operating parameters, and their interactions on the critical characteristics of granules and ER tablets. The impacts of screw speed, powder feeding rate, and the number of kneading (KEs) and sizing elements on granules and tablets characteristics were investigated by employing a definitive screening design. A semi-mechanistic model was used to calculate the residence time distribution parameters and validated using the tracers. The results showed that an increase in screw speed decreased the mean residence time of the material within the barrel, while an increase in the powder feeding rate or number of KEs did the opposite and increased the barrel residence time. Screw design and operating parameters affected the flow and bulk characteristics of granules. The screw speed was the most significant factor impacting the tablet\'s breaking strength. The dissolution profiles revealed that granule characteristics mainly influenced the early phase of drug release. This study demonstrated that a simultaneous optimization of both operating and screw design parameters was beneficial in producing ER granules and tablets of desired performance characteristics while mitigating any failure risks, such as swelling during processing.