Porous silicon and silica carriers for delivery of peptide therapeutics.

Peptides have gained tremendous popularity as biological therapeutic agents in recent years due to their favourable specificity, diversity of targets, well-established screening methods, ease of production, and lower cost. However, their poor physiological and storage stability, pharmacokinetics, and fast clearance have limited their clinical translation. Novel nanocarrier-based strategies have shown promise in overcoming these issues. In this direction, porous silicon (pSi) and mesoporous silica nanoparticles (MSNs) have been widely explored as potential carriers for the delivery of peptide therapeutics. These materials possess several advantages, including large surface areas, tunable pore sizes, and adjustable pore architectures, which make them attractive carriers for peptide delivery systems. In this review, we cover pSi and MSNs as drug carriers focusing on their use in peptide delivery. The review provides a brief overview of their fabrication, surface modification, and interesting properties that make them ideal peptide drug carriers. The review provides a systematic account of various studies that have utilised these unique porous carriers for peptide delivery describing significant in vitro and in vivo results. We have also provided a critical comparison of the two carriers in terms of their physicochemical properties and short-term and long-term biocompatibility. Lastly, we have concluded the review with our opinion of this field and identified key areas for future research for clinical translation of pSi and MSN-based peptide therapeutic formulations.

Cross-Video Pedestrian Tracking Algorithm with a Coordinate Constraint.

Pedestrian tracking in surveillance videos is crucial and challenging for precise personnel management. Due to the limited coverage of a single video, the integration of multiple surveillance videos is necessary in practical applications. In the realm of pedestrian management using multiple surveillance videos, continuous pedestrian tracking is quite important. However, prevailing cross-video pedestrian matching methods mainly rely on the appearance features of pedestrians, resulting in low matching accuracy and poor tracking robustness. To address these shortcomings, this paper presents a cross-video pedestrian tracking algorithm, which introduces spatial information. The proposed algorithm introduces the coordinate features of pedestrians in different videos and a linear weighting strategy focusing on the overlapping view of the tracking process. The experimental results show that, compared to traditional methods, the method in this paper improves the success rate of target pedestrian matching and enhances the robustness of continuous pedestrian tracking. This study provides a viable reference for pedestrian tracking and crowd management in video applications.

[Action Mechanism of Bacillus on Microalgae During Nitrogen Metabolism in Urban Tailwater].

To improve deep denitrification of black and odorous water and improve the quality of surface water, we studied the characteristics of nitrogen metabolism and denitrification of urban tailwater by microalgae (Z), Bacillus (Y), and Bacillus microalgae (ZY). The results showed that there was a good removal effect of ammonia nitrogen of group Z and group ZY in urban tailwater. The degradation rate of both groups reached 95%. The best effect on the removal of nitrite nitrogen was of group Z in urban tailwater. The combined action of Bacillus and Micrococcus played a relatively strong and stable effect on the conversion of nitrite nitrogen to nitrate nitrogen in the nitrogen cycle reaction. Bacillus could effectively remove nitrate nitrogen and improve the removal efficiency of nitrate nitrogen by microalgae. Best removal effect of nitrate nitrogen was observed in group ZY in urban tailwater, with a degradation rate as high as 99%, in which the nitrate nitrogen was removed almost completely. The Bacteria with high proportions in Z were Chroococcidiopsis_PCC_7203 (24.38%), uncultured_bacterium-g_norank_f_A4b (23.65%), Exiguobacteriu (7.09%), Leptolyngbya_PCC-6306(9.41%), and Bacillus (1.99%). The bacteria with high proportions in ZY were Brevibacillus (22.94%), Clostridium (8.78%), and Bacillus (4.88%), and the proportion of Chroococcidiopsis_PCC_7203 was only 7.84% in ZY, which was considerably lower than that in Z samples. The conclusions were as follows:microalgae could effectively remove ammonia nitrogen in the system. Bacillus and microalgae had very good removal effect of ammonia nitrogen and nitrate nitrogen. During the nitrogen removal of black and odorous water by algae, the Bacillus inhibited the excessive growth of microalgae and prevented eutrophication and black odor in water. This study can provide data support for the deep treatment of urban tail water and prevention of surface water eutrophication.

Unraveling the joint toxicity of transition-metal dichalcogenides and per- and polyfluoroalkyl substances in aqueous mediums by experimentation, machine learning and molecular dynamics.

The environmental fate of transition-metal dichalcogenides (TMDCs) may be further complicated by interacting with existing pollutants, especially per- and polyfluoroalkyl substances (PFAS). However, due to their sheer volume, it is impossible to explore all possible interactions by simply utilizing experimental methods. Herein, we used two model TMDC nanosheets, molybdenum disulfide (MoS2) and tungsten disulfide (WS2), and seven PFAS to explore their interactions and subsequent impacts on model cell lines and zebrafish. Utilizing experimental methods and machine learning approaches, we showed that TMDCs-PFAS interactions can pose unique challenges due to their interaction-specific toxicity niches towards cell lines. Further in vivo experiments, together with molecular dynamics simulation, suggested that TMDCs-PFAS interactions in aqueous environments significantly increased their bioaccumulation in zebrafish towards different target organs, mostly due to the differences in loading PFAS. Such enhanced bioaccumulation increased the oxidative stress in zebrafish liver and intestine, as demonstrated by the increased reactive oxygen species (ROS) level and other enzyme activities, which eventually led to obvious histopathological alterations in the liver and intestine. Our study highlights the importance of exploring interactions between emerging and existing contaminants with state-of-art techniques in aqueous environments and its significance in safeguarding aquatic environment health.

Threats to Terrestrial Plants from Emerging Nanoplastics.

Nanoplastics are ubiquitous in ecosystems and impact planetary health. However, our current understanding on the impacts of nanoplastics upon terrestrial plants is fragmented. The lack of systematic approaches to evaluating these impacts limits our ability to generalize from existing studies and perpetuates regulatory barriers. Here, we undertook a meta-analysis to quantify the overall strength of nanoplastic impacts upon terrestrial plants and developed a machine learning approach to predict adverse impacts and identify contributing features. We show that adverse impacts are primarily associated with toxicity metrics, followed by plant species, nanoplastic mass concentration and size, and exposure time and medium. These results highlight that the threats of nanoplastics depend on a diversity of reactions across molecular to ecosystem scales. These reactions are rooted in both the spatial and functional complexities of nanoplastics and, as such, are specific to both the plastic characteristics and environmental conditions. These findings demonstrate the utility of interrogating the diversity of toxicity data in the literature to update both risk assessments and evidence-based policy actions.

Linking electron ionization mass spectra of organic chemicals to toxicity endpoints through machine learning and experimentation.

Quantitative structure-activity relationship (QSAR) modeling has been widely used to predict the potential harm of chemicals, in which the prediction heavily relies on the accurate annotation of chemical structures. However, it is difficult to determine the accurate structure of an unknown compound in many cases, such as in complex water environments. Here, we solved the above problem by linking electron ionization mass spectra (EI-MS) of organic chemicals to toxicity endpoints through various machine learning methods. The proposed method was verified by predicting 50% growth inhibition of Tetrahymena pyriformis (T. pyriformis) and liver toxicity. The optimal model performance obtained an R2 > 0.7 or balanced accuracy > 0.72 for both the training set and test set. External experimentation further verified the application potential of our proposed method in the toxicity prediction of unknown chemicals. Feature importance analysis allowed us to identify critical spectral features that were responsible for chemical-induced toxicity. Our approach has the potential for toxicity prediction in such fields that it is difficult to determine accurate chemical structures.

Comprehensive Interrogation on Acetylcholinesterase Inhibition by Ionic Liquids Using Machine Learning and Molecular Modeling.

Quantitative structure-activity relationship (QSAR) modeling can be used to predict the toxicity of ionic liquids (ILs), but most QSAR models have been constructed by arbitrarily selecting one machine learning method and ignored the overall interactions between ILs and biological systems, such as proteins. In order to obtain more reliable and interpretable QSAR models and reveal the related molecular mechanism, we performed a systematic analysis of acetylcholinesterase (AChE) inhibition by 153 ILs using machine learning and molecular modeling. Our results showed that more reliable and stable QSAR models (R2 > 0.85 for both cross-validation and external validation) were obtained by combining the results from multiple machine learning approaches. In addition, molecular docking results revealed that the cations and organic anions of ILs bound to specific amino acid residues of AChE through noncovalent interactions such as π interactions and hydrogen bonds. The calculation results of binding free energy showed that an electrostatic interaction (ΔEele < -285 kJ/mol) was the main driving force for the binding of ILs to AChE. The overall findings from this investigation demonstrate that a systematic approach is much more convincing. Future research in this direction will help design the next generation of biosafe ILs.

Engagement in video and audio narratives: contrasting self-report and physiological measures.

Stories play a fundamental role in human culture. They provide a mechanism for sharing cultural identity, imparting knowledge, revealing beliefs, reinforcing social bonds and providing entertainment that is central to all human societies. Here we investigated the extent to which the delivery medium of a story (audio or visual) affected self-reported and physiologically measured engagement with the narrative. Although participants self-reported greater involvement for watching video relative to listening to auditory scenes, stronger physiological responses were recorded for auditory stories. Sensors placed at their wrists showed higher and more variable heart rates, greater electrodermal activity, and even higher body temperatures. We interpret these findings as evidence that the stories were more cognitively and emotionally engaging at a physiological level when presented in an auditory format. This may be because listening to a story, rather than watching a video, is a more active process of co-creation, and that this imaginative process in the listener's mind is detectable on the skin at their wrist.

[Research & development and evaluation of oral films].

Oral film is a new type of oral preparation. Due to portability, simple preparation process and good clinical compliance, oral films have become the focus of novel drug delivery system in recent years. Meanwhile, oral films have been gradually used in the development of Chinese medicine preparations. According to the application and approval situation of different types of oral films both at home and abroad in recent years, their research and development status was analyzed, including the basic concept, formulation, manufacturing process and quality control, as well as related progress and development prospects of oral films applied in traditional Chinese medicine. Some suggestions on the technical evaluation of oral films were put forward by considering specific requirements from regulatory agencies. This paper could provide some references for the development and evaluation of oral films. Due to the complexity of the drug substances and the particularity of the drug product, the development and application of oral films in traditional Chinese medicine are still faced with opportunity and challenges.