Vertical Distribution of Nutrients on Transitional Season in Weda Bay, North Maluku

A vertical distribution of nutrient shows an interaction of physical processes, source, and uptake along the water column. These interactions can occur along the water column with different processes in each layer. Water samples from 17 stations were collected for nitrate, phosphate, and silicates concentration analyses during the transitional season in the Weda Bay. During the transitional season, the Weda Bay was characterized by low salinity (33.55-34.10), relatively warm temperature (30.87°C), and the relatively low nutrient concentrations (nitrate=0.03-4.87 µg at/l, phosphate=0.011-0.852 µg at/l, and silicate=0.04-1.21 µg at/l). The present of Western North Pacific Ocean (WNPO) watermass and the influence of Southern Subtropical Lower Water (SSLW) producing high salinity (>35) at the depth of 130-300 m were observed along the Weda Bay. Nutrient geochemical processes in this region were shown by nutrient utilization and regeneration across the water columns. Nutrients utilization was relatively high in the surface layer. Meanwhile, nutrients regeneration and remineralization were more dominant in the thermocline and deeper water layers. Analyses of nutrients showed that nitrate was more dominant than other nutrients with N/P ratio was 3.83-37.99 and N/Si ratio was 0.12-10.98. The effectiveness of silicate (0.25 μg at/l) that was used by phytoplankton found at a depth of 200 m when its concentration decreased at N/P ratio (16:08) close to the Redfield ratio. Due to an uptake, remineralization, and regeneration processes in each layer, a nutrient distribution pattern was formed which the nutrient concentrations decreased in mixed layer and increased in the deeper water

Excipient-mediated alteration in drug bioavailability in the rat depends on the sex of the animal

The pharmaceutical excipient, polyethylene glycol 400 (PEG 400), unexpectedly alters the bioavailability of the BCS class III drug ranitidine in a sex-dependent manner. As ranitidine is a substrate for the efflux transporter P-glycoprotein (P-gp), we hypothesized that the sex-related influence could be due to interactions between PEG 400 and P-gp. In this study, we tested this hypothesis by: i) measuring the influence of PEG 400 on the oral bioavailability of another P-gp substrate (ampicillin) and of a non-P-gp substrate (metformin); and ii) measuring the effect of PEG 400 on drug bioavailability in the presence of a P-gp inhibitor (cyclosporine A) in male and female rats. We found that PEG 400 significantly increased (p<0.05) the bioavailability of ampicillin (the P-gp substrate) in male rats, but not in female ones. In contrast, PEG 400 had no influence on the bioavailability of the non-P-gp substrate, metformin in male or female rats. Inhibition of P-gp by oral pre-treatment with cyclosporine A increased the bioavailability of the P-gp substrates (ampicillin and ranitidine) in males and females (p<0.05), and to a greater extent in males, but had no influence on the bioavailability of metformin in either male or female rats. These results prove the hypothesis that the sex-specific effect of PEG 400 on the bioavailability of certain drugs is due to the interaction of PEG 400 with the efflux transporter P-gp

Advances in powder bed fusion 3D printing in drug delivery and healthcare

Powder bed fusion (PBF) is a 3D printing method that selectively consolidates powders into 3D objects using a power source. PBF has various derivatives; selective laser sintering/melting, direct metal laser sintering, electron beam melting and multi-jet fusion. These technologies provide a multitude of benefits that make them well suited for the fabrication of bespoke drug-laden formulations, devices and implants. This includes their superior printing resolution and speed, and ability to produce objects without the need for secondary supports, enabling them to precisely create complex products. Herein, this review article outlines the unique applications of PBF 3D printing, including the main principles underpinning its technologies and highlighting their novel pharmaceutical and biomedical applications. The challenges and shortcomings are also considered, emphasising on their effects on the 3D printed products, whilst providing a forward-thinking view

3D printing: Principles and pharmaceutical applications of selective laser sintering

Pharmaceutical three-dimensional (3D) printing is a modern fabrication process with the potential to create bespoke drug products of virtually any shape and size from a computer-aided design model. Selective laser sintering (SLS) 3D printing combines the benefits of high printing precision and capability, enabling the manufacture of medicines with unique engineering and functional properties. This article reviews the current state-of-the-art in SLS 3D printing, including the main principles underpinning this technology, and highlights the diverse selection of materials and essential parameters that influence printing. The technical challenges and processing conditions are also considered in the context of their effects on the printed product. Finally, the pharmaceutical applications of SLS 3D printing are covered, providing an emphasis on the advantages the technology offers to drug product manufacturing and personalised medicine

A slippery slope: On the origin, role and physiology of mucus

The mucosa of the gastrointestinal tract, eyes, nose, lungs, cervix and vagina is lined by epithelium interspersed with mucus-secreting goblet cells, all of which contribute to their unique functions. This mucus provides an integral defence to the epithelium against noxious agents and pathogens. However, it can equally act as a barrier to drugs and delivery systems targeting epithelial passive and active transport mechanisms. This review highlights the various mucins expressed at different mucosal surfaces on the human body, and their role in creating a mucoid architecture to protect epithelia with specialized functions. Various factors compromising the barrier properties of mucus have been discussed, with an emphasis on how disease states and microbiota can alter the physical properties of mucus. For instance, Akkermansia muciniphila, a bacterium found in higher levels in the gut of lean individuals induces the production of a thickened gut mucus layer. The aims of this article are to elucidate the different physiological, biochemical and physical properties of bodily mucus, a keen appreciation of which will help circumvent the slippery slope of challenges faced in achieving effective mucosal drug and gene delivery

Machine learning to empower electrohydrodynamic processing

Electrohydrodynamic (EHD) processes are promising healthcare fabrication technologies, as evidenced by the number of commercialised and food-and-drug administration (FDA)-approved products produced by these processes. Their ability to produce both rapidly and precisely nano-sized products provides them with a unique set of qualities that cannot be matched by other fabrication technologies. Consequently, this has stimulated the development of EHD processing to tackle other healthcare challenges. However, as with most technologies, time and resources will be needed to realise fully the potential EHD processes can offer. To address this bottleneck, researchers are adopting machine learning (ML), a subset of artificial intelligence, into their workflow. ML has already made ground-breaking advancements in the healthcare sector, and it is anticipated to do the same in the materials domain. Presently, the application of ML in fabrication technologies lags behind other sectors. To that end, this review showcases the progress made by ML for EHD workflows, demonstrating how the latter can benefit greatly from the former. In addition, we provide an introduction to the ML pipeline, to help encourage the use of ML for other EHD researchers. As discussed, the merger of ML with EHD has the potential to expedite novel discoveries and to automate the EHD workflow

Machine learning predicts electrospray particle size

Electrospraying (ES) is a state-of-the-art processing technique with the promise of achieving key nanotechnology and contemporary manufacturing needs. As a versatile technique, ES can produce particles with different sizes, morphologies, and porosities by tuning a list of experiment parameters. However, this level of precision demands an exhaustive trial-and-error approach, at high costs and heavily relies on processing expertise. The present study demonstrates how machine learning (ML) can expedite the optimization process by accurately predicting particle diameter, for both nano- and micron-sized particles. This was achieved by constructing an informative electrospraying database containing 445 records from the literature, followed by the development of predictive ML models. Feature engineering techniques were explored, where ultimately it was found that solvent physiochemical properties as the molecular representation and data with imputation provided models the highest performance. The top two models were XGBoost and Random Forest (RF), which yielded root-mean-squared errors (RMSE) of 3.91 μm and 6.19 μm evaluated by 5-fold cross-validation (CV), respectively. These models were experimentally validated in-house with different combinations of experiment parameters, where RMSE between the predicted and actual particle size was found to be 1.30 μm for the XGBoost model and 1.62 μm for the RF model. Therefore, it was concluded that data generated by the ES literature, in addition to being both cost- and material-free, can yield high-performing ML models for predicting particle size. The ML models were also consulted to determine the key processing parameters that govern particle size, where it was concluded that the models learnt similar attributes identified by scaling laws

Impact of Peptide Structure on Colonic Stability and Tissue Permeability

Most marketed peptide drugs are administered parenterally due to their inherent gastrointestinal (GI) instability and poor permeability across the GI epithelium. Several molecular design techniques, such as cyclisation and D-amino acid (D-AA) substitution, have been proposed to improve oral peptide drug bioavailability. However, very few of these techniques have been translated to the clinic. In addition, little is known about how synthetic peptide design may improve stability and permeability in the colon, a key site for the treatment of inflammatory bowel disease and colorectal cancer. In this study, we investigated the impact of various cyclisation modifications and D-AA substitutions on the enzymatic stability and colonic tissue permeability of native oxytocin and 11 oxytocin-based peptides. Results showed that the disulfide bond cyclisation present in native oxytocin provided an improved stability in a human colon model compared to a linear oxytocin derivative. Chloroacetyl cyclisation increased native oxytocin stability in the colonic model at 1.5 h by 30.0%, whereas thioether and N-terminal acetylated cyclisations offered no additional protection at 1.5 h. The site and number of D-AA substitutions were found to be critical for stability, with three D-AAs at Tyr, Ile and Leu, improving native oxytocin stability at 1.5 h in both linear and cyclic structures by 58.2% and 79.1%, respectively. Substitution of three D-AAs into native cyclic oxytocin significantly increased peptide permeability across rat colonic tissue; this may be because D-AA substitution favourably altered the peptide’s secondary structure. This study is the first to show how the strategic design of peptide therapeutics could enable their delivery to the colon via the oral route

Nanoencapsulation for Probiotic Delivery

Gut microbiota dynamically participate in diverse physiological activities with direct impact on the host's health. A range of factors associated with the highly complex intestinal flora ecosystem poses challenges in regulating the homeostasis of microbiota. The consumption of live probiotic bacteria, in principle, can address these challenges and confer health benefits. In this context, one of the major problems is ensuring the survival of probiotic cells when faced with physical and chemical assaults during their intake and subsequent gastrointestinal passage to the gut. Advances in the field have focused on improving conventional encapsulation techniques in the microscale to achieve high cell viability, gastric and temperature resistance, and longer shelf lives. However, these microencapsulation approaches are known to have limitations with possible difficulties in clinical translation. In this Perspective, we present a brief overview of the current progress of different probiotic encapsulation methods and highlight the contemporary and emerging single-cell encapsulation strategies using nanocoatings for individual probiotic cells. Finally, we discuss the relative advantages of various nanoencapsulation approaches and the future trend toward developing coated probiotics with advanced features and health benefits