A Randomized Controlled Clinical Trial Investigating the Weaning Process From Mechanical Ventilation in Elderly Patients With Dementia.

BACKGROUND: Limited data is available regarding the weaning techniques employed for mechanical ventilation (MV) in elderly patients with dementia in China. OBJECTIVE: The primary objective of this study is to investigate diverse weaning methods in relation to the prognostic outcomes of elderly patients with dementia undergoing MV in the intensive care unit (ICU). Specifically, we seek to compare the prognosis, likelihood of successful withdrawal from MV, and the length of stay (LOS) in the ICU. METHODS: The study was conducted as a randomized controlled trial, encompassing a group of 169 elderly patients aged ≥ 65 years with dementia who underwent MV. Three distinct weaning methods were used for MV cessation, namely, the tapering parameter, spontaneous breathing trial (SBT), and SmartCare (Dräger, Germany). RESULTS: In the tapering parameter group, the LOS in the ICU was notably prolonged compared to both the SBT and SmartCare groups. However, no statistically significant differences were observed among the groups with respect to demographic characteristics, such as age and sex, as well as factors including the rationale for ICU admission, cause of MV, MV mode, oxygenation index, hemoglobin levels, albumin levels, ejection fraction, sedation and analgesia practices, tracheotomy, duration of MV, successful extubation, successful weaning, incidences of ventilator-associated pneumonia, and overall prognosis. CONCLUSIONS: Both the SBT and SmartCare withdrawal methods demonstrated a reduction in the duration of MV and LOS in the ICU when compared to the tapering parameter method. TRIAL REGISTRATION: Chinese Clinical Trial Registry: ChiCTR1900028449.

A Mitochondria-Targeted Photosensitizer for Combined Pyroptosis and Apoptosis with NIR-II Fluorescence/Photoacoustic Imaging-Guided Phototherapy.

Overcoming tumor apoptosis resistance is a major challenge in enhancing cancer therapy. Pyroptosis, a lytic form of programmed cell death (PCD) involving inflammasomes, Gasdermin family proteins, and cysteine proteases, offers potential in cancer treatment. While photodynamic therapy (PDT) can induce pyroptosis by generating reactive oxygen species (ROS) through the activation of photosensitizers (PSs), many PSs lack specific subcellular targets and are limited to the first near-infrared window, potentially reducing treatment effectiveness. Therefore, developing effective, deep-penetrating, organelle-targeted pyroptosis-mediated phototherapy is essential for cancer treatment strategies. Here, we synthesized four molecules with varying benzene ring numbers in thiopyrylium structures to preliminarily explore their photodynamic properties. The near-infrared-II (NIR-II) PS Z1, with a higher benzene ring count, exhibited superior ROS generation and mitochondria-targeting abilities, and a large Stokes shift. Through nano-precipitation method, Z1 nanoparticles (NPs) also demonstrated high ROS generation (especially type-I ROS) upon 808 nm laser irradiation, leading to efficient mitochondria dysfunction and combined pyroptosis and apoptosis. Moreover, they exhibited exceptional tumor-targeting ability via NIR-II fluorescence imaging (NIR-II FI) and photoacoustic imaging (PAI). Furthermore, Z1 NPs-mediated phototherapy effectively inhibited tumor growth with minimal adverse effects. Our findings offer a promising strategy for cancer therapy, warranting further preclinical investigations in PDT.

The Integration of ANN and FEA and Its Application to Property Prediction of Dual-Performance Turbine Disks.

Regulating the microstructure of powder metallurgy (P/M) nickel-based superalloys to achieve superior mechanical properties through heat treatment is a prevalent method in turbine disk design. However, in the case of dual-performance turbine disks, the complexity and non-uniformity of the heat treatment process present substantial challenges. The prediction of yield strength is typically derived from the analysis of microstructures under various heat treatment regimes. This method is time-consuming, expensive, and the accuracy often depends on the precision of microstructural characterization. This study successfully employed a coupled method of Artificial Neural Network (ANN) and finite element analysis (FEA) to reveal the relationship between the heat treatment process and yield strength. The coupled method accurately predicted the location specified and temperature-dependent yield strength based on the heat treatment parameters such as holding temperatures and cooling rates. The root mean square error (RMSE) and mean absolute percentage deviation (MAPD) for the training set are 50.37 and 3.77, respectively, while, for the testing set, they are 50.13 and 3.71, respectively. Furthermore, an integrated model of FEA and ANN is established using a Abaqus user subroutine. The integrated model can predict the yield strength based on temperature calculation results and automatically update material properties of the FEA model during the loading process simulation. This allows for an accurate calculation of the stress-strain state of the turbine disk during actual working conditions, aiding in locating areas of stress concentration, plastic deformation, and other critical regions, and provides a novel reliable reference for the rapid design of the turbine disk.

Spatial distribution of lipophilic shellfish toxins in seawater and sediment in the Bohai Sea and the Yellow Sea, China.

Lipophilic shellfish toxins (LSTs) are widely distributed in marine environments worldwide, potentially threatening marine ecosystem health and aquaculture safety. In this study, two large-scale cruises were conducted in the Bohai Sea and the Yellow Sea, China, in spring and summer 2023 to clarify the composition, concentration, and spatial distribution of LSTs in the water columns and sediments. Results showed that okadaic acid (OA), dinophysistoxin-1 (DTX1) and/or pectenotoxin-2 (PTX2) were detected in 249 seawater samples collected in spring and summer. The concentrations of ∑LSTs in seawater were ranging of ND (not detected) -13.86, 1.60-17.03, 2.73-17.39, and 1.26-30.21 pmol L-1 in the spring surface, intermediate, bottom water columns and summer surface water layers, respectively. The detection rates of LSTs in spring and summer seawater samples were 97% and 100%, respectively. The high concentrations of ∑LSTs were mainly distributed in the north Yellow Sea and the northeast Bohai Sea in spring, and in the northeast Yellow Sea, the waters around Laizhou Bay and Rongcheng Bay in summer. Similarly, only OA, DTX1 and PTX2 were detected in the surface sediments. Overall, the concentration of ∑LSTs in the surface sediments of the northern Yellow Sea was higher than that in other regions. In sediment cores, PTX2 was mainly detected in the upper sediment samples, whereas OA and DTX1 were detected in deeper sediments, and LSTs can persist in the sediments for a long time. Overall, OA, DTX1 and PTX2 were widely distributed in the water column and surface sediments in the Bohai Sea and the Yellow Sea, China. The results of this study contribute to the understanding of spatial distribution of LSTs in seawater and sediment environmental media and provide basic information for health risk assessment of phycotoxins.

Rapid in situ formation of κ-carrageenan-carboxymethyl chitosan-kaolin clay hydrogel films enriched with arbutin for enhanced preservation of cherry tomatoes.

Food waste resulting from perishable fruits and vegetables, coupled with the utilization of non-renewable petroleum-based packaging materials, presents pressing challenges demanding resolution. This study addresses these critical issues through the innovative development of a biodegradable functional plastic wrap. Specifically, the proposed solution involves the creation of a κ-carrageenan/carboxymethyl chitosan/arbutin/kaolin clay composite film. This film, capable of rapid in-situ formation on the surfaces of perishable fruits, adeptly conforms to their distinct shapes. The incorporation of kaolin clay in the composite film plays a pivotal role in mitigating water vapor and oxygen permeability, concurrently bolstering water resistance. Accordingly, tensile strength of the composite film experiences a remarkable enhancement, escalating from 20.60 MPa to 34.71 MPa with the incorporation of kaolin clay. The composite film proves its efficacy by preserving cherry tomatoes for an extended period of 9 days at 28 °C through the deliberate delay of fruit ripening, respiration, dehydration and microbial invasion. Crucially, the economic viability of the raw materials utilized in the film, coupled with the expeditious and straightforward preparation method, underscores the practicality of this innovative approach. This study thus introduces an easy and sustainable method for preserving perishable fruits, offering a cost-effective and efficient alternative to petroleum-based packaging materials.

Chicken ovarian follicular atresia: interaction network at organic, cellular, and molecular levels.

Most of follicles undergo a degenerative process called follicular atresia. This process directly affects the egg production of laying hens and is regulated by external and internal factors. External factors primarily include nutrition and environmental factors. In follicular atresia, internal factors are predominantly regulated at 3 levels; organic, cellular and molecular levels. At the organic level, the hypothalamic-pituitary-ovary (HPO) axis plays an essential role in controlling follicular development. At the cellular level, gonadotropins and cytokines, as well as estrogens, bind to their receptors and activate different signaling pathways, thereby suppressing follicular atresia. By contrast, oxidative stress induces follicular atresia by increasing ROS levels. At the molecular level, granulosa cell (GC) apoptosis is not the only factor triggering follicular atresia. Autophagy is also known to give rise to atresia. Epigenetics also plays a pivotal role in regulating gene expression in processes that seem to be related to follicular atresia, such as apoptosis, autophagy, proliferation, and steroidogenesis. Among these processes, the miRNA regulation mechanism is well-studied. The current review focuses on factors that regulate follicular atresia at organic, cellular and molecular levels and evaluates the interaction network among these levels. Additionally, this review summarizes atretic follicle characteristics, in vitro modeling methods, and factors preventing follicular atresia in laying hens.

A modified mechanistic approach for predicting ribbon solid fraction at different roller compaction speeds.

This research investigates the modeling of the pharmaceutical roller compaction process, focusing on the application of the Johanson model and the impact of varying roll speeds from 1 to 15 RPM on predictive accuracy of ribbon solid fraction. The classical Johanson's model was integrated with a dwell time parameter leading to an expression of a floating correction factor as a function of roll speed. Through systematic analysis of the effect of different roll speeds on the solid fraction of ribbons composed of microcrystalline cellulose, lactose, and their blends, corrective adjustment to the Johanson model was found to depend on both roll speed and formulation composition. Interestingly, the correction factor demonstrated excellent correlation with the blend's mechanical properties, namely yield stress (Py) and elastic modulus (E0), representative of the deformability of the powder. Validated by a multicomponent drug formulation with ±0.4-1.3 % differences, the findings underscore the utility of this modified mechanistic approach for precise prediction of ribbon solid fraction when Py or E0 is known for a given blend. Hence, this work advances the field by offering early insights for more accurate and controllable roller compaction operations during late-stage pharmaceutical manufacturing.

Alkyl-Doping Enables Significant Suppression of Conformational Relaxation and Intermolecular Nonradiative Decay for Improved Near-Infrared Fluorescence Imaging.

Despite various efforts to optimize the near-infrared (NIR) performance of perylene diimide (PDI) derivatives for bio-imaging, convenient and efficient strategies to amplify the fluorescence of PDI derivatives in biological environment and the intrinsic mechanism studies are still lacking. Herein, we propose an alkyl-doping strategy to amplify the fluorescence of PDI derivative-based nanoparticles for improved NIR fluorescence imaging. The developed PDI derivative, OPE-PDI, shows much brighter in n-Hexane (HE) compared with that in other organic media, and the excited state dynamics investigation experimentally elucidates the solvent effect-induced suppression of intermolecular energy transfer and intramolecular nonradiative decay as the underlying mechanism for the fluorescence improvement. Theoretical calculations reveal the lowest reorganization energies of OPE-PDI in HE among various solvents, indicating the effectively suppressed conformational relaxation to support the strongest radiative decay. Inspired by this, an alkyl atmosphere mimicking HE is constructed by incorporating the octadecane into OPE-PDI-based nanoparticles, permitting up to 3-fold fluorescence improvement compared with the counterpart nanoparticles. Owing to the merits of high brightness, anti-photobleaching, and low biotoxicity for the optimal nanoparticles, they have been employed for probing and long-term monitoring of tumor. This work highlights a facile strategy for the fluorescence enhancement of PDI derivative-based nanoparticles.

Mechanism of Salvia miltiorrhiza Bunge extract to alleviate Chronic Sleep Deprivation-Induced cognitive dysfunction in rats.

BACKGROUND: Bidirectional communication between the gut microbiota and the brain may play an essential role in the cognitive dysfunction associated with chronic sleep deprivation(CSD). Salvia miltiorrhiza Bunge (Danshen, DS), a famous Chinese medicine and functional tea, is extensively used to protect learning and memory capacities, although the mechanism of action remains unknown. PURPOSE: The purpose of this research was to explore the efficacy and the underlying mechanism of DS in cognitive dysfunction caused by CSD. METHODS: DS chemical composition was analyzed by UPLC-QTOF-MS/MS. Forty rats were randomly assigned to five groups (n = 8): control (CON), model (MOD), low- (1.35 g/kg, DSL), high-dose (2.70 g/kg, DSH) DS group, and Melatonin(100 mg/kg, MT) group. A CSD rat model was established over 21 days. DS's effects and the underlying mechanism were explored using the open-field test(OFT), Morris water-maze(MWM), tissue staining(Hematoxylin and Eosin Staining, Nissl staining, Alcian blue-periodic acid SCHIFF staining, and Immunofluorescence), enzyme-linked immunosorbent assay, Western blot, quantitative real-time polymerase chain reaction(qPCR), and 16S rRNA sequencing. RESULTS: We demonstrated that CSD caused gut dysbiosis and cognitive dysfunction. Furthermore, 16S rRNA sequencing demonstrated that Firmicutes and Proteobacteria were more in fecal samples from model group rats, whereas Bacteroidota and Spirochaetota were less. DS therapy, on the contrary hand, greatly restored the gut microbial community, consequently alleviating cognitive impairment in rats. Further research revealed that DS administration reduced systemic inflammation via lowering intestinal inflammation and barrier disruption. Following that, DS therapy reduced Blood Brain Barrier(BBB) and neuronal damage, further decreasing neuroinflammation in the hippocampus(HP). Mechanistic studies revealed that DS therapy lowered lipopolysaccharide (LPS) levels in the HP, serum, and colon, consequently blocking the TLR4/MyD88/NF-κB signaling pathway and its downstream pro-inflammatory products(IL-1ß, IL-6, TNF-α, iNOS, and COX2) in the HP and colon. CONCLUSION: DS treatment dramatically improved spatial learning and memory impairments in rats with CSD by regulating the composition of the intestinal flora, preserving gut and brain barrier function, and reducing inflammation mediated by the LPS-TLR4 signaling pathway. Our findings provide novel insight into the mechanisms by which DS treats cognitive dysfunction caused by CSD.

Enhanced electrocatalytic removal of bisphenol a by introducing Co/N into precursor formed from phenolic resin waste.

Bisphenol A (BPA) is a typical endocrine disruptor, which can be used as an industrial raw material for the synthesis of polycarbonate and epoxy resins, etc. Recently, BPA has appeared on the list of priority new pollutants for control in various countries and regions. In this study, phenolic resin waste was utilized as a multi-carbon precursor for the electrocatalytic cathode and loaded with cobalt/nitrogen (Co/N) on its surface to form qualitative two-dimensional carbon nano-flakes (Co/NC). The onset potentials, half-wave potentials, and limiting current densities of the nitrogen-doped composite carbon material Co/NC in oxygen saturated 0.5 mol H2SO4 were -0.08 V, -0.61 V, and -0.41 mA cm-2; and those of alkaline conditions were -0.65 V, -2.51 V, and -0.38 mA cm-2, and the corresponding indexes were improved compared with those of blank titanium electrodes, which indicated that the constructed nitrogen-doped composite carbon material Co/NC was superior in oxygen reduction ability. The catalysis by metallic cobalt as well as the N-hybridized active sites significantly improved the efficiency of electrocatalytic degradation of BPA. In the electro-Fenton system, the yield of hydrogen peroxide generated by cathodic reduction of oxygen was 4.012 mg L-1, which effectively promoted the activation of hydroxyl radicals. The removal rate of BPA was above 95% within 180 min. This work provides a new insight for the design and development of novel catalyst to degrade organic pollutants.

Study on the differential diagnosis of benign and malignant breast lesions using a deep learning model based on multimodal images.

OBJECTIVE: To establish a multimodal model for distinguishing benign and malignant breast lesions. MATERIALS AND METHODS: Clinical data, mammography, and MRI images (including T2WI, diffusion-weighted images (DWI), apparent diffusion coefficient (ADC), and DCE-MRI images) of 132 benign and breast cancer patients were analyzed retrospectively. The region of interest (ROI) in each image was marked and segmented using MATLAB software. The mammography, T2WI, DWI, ADC, and DCE-MRI models based on the ResNet34 network were trained. Using an integrated learning method, the five models were used as a basic model, and voting methods were used to construct a multimodal model. The dataset was divided into a training set and a prediction set. The accuracy, sensitivity, specificity, positive predictive value, and negative predictive value of the model were calculated. The diagnostic efficacy of each model was analyzed using a receiver operating characteristic curve (ROC) and an area under the curve (AUC). The diagnostic value was determined by the DeLong test with statistically significant differences set at P < 0.05. RESULTS: We evaluated the ability of the model to classify benign and malignant tumors using the test set. The AUC values of the multimodal model, mammography model, T2WI model, DWI model, ADC model and DCE-MRI model were 0.943, 0.645, 0.595, 0.905, 0.900, and 0.865, respectively. The diagnostic ability of the multimodal model was significantly higher compared with that of the mammography and T2WI models. However, compared with the DWI, ADC, and DCE-MRI models, there was no significant difference in the diagnostic ability of these models. CONCLUSION: Our deep learning model based on multimodal image training has practical value for the diagnosis of benign and malignant breast lesions.

Epigenetic regulation of H3K27me3 in laying hens with fatty liver hemorrhagic syndrome induced by high-energy and low-protein diets.

BACKGROUND: Fatty liver hemorrhagic syndrome (FLHS) in the modern poultry industry is primarily caused by nutrition. Despite encouraging progress on FLHS, the mechanism through which nutrition influences susceptibility to FLHS is still lacking in terms of epigenetics. RESULTS: In this study, we analyzed the genome-wide patterns of trimethylated lysine residue 27 of histone H3 (H3K27me3) enrichment by chromatin immunoprecipitation-sequencing (ChIP-seq), and examined its association with transcriptomes in healthy and FLHS hens. The study results indicated that H3K27me3 levels were increased in the FLHS hens on a genome-wide scale. Additionally, H3K27me3 was found to occupy the entire gene and the distant intergenic region, which may function as silencer-like regulatory elements. The analysis of transcription factor (TF) motifs in hypermethylated peaks has demonstrated that 23 TFs are involved in the regulation of liver metabolism and development. Transcriptomic analysis indicated that differentially expressed genes (DEGs) were enriched in fatty acid metabolism, amino acid, and carbohydrate metabolism. The hub gene identified from PPI network is fatty acid synthase (FASN). Combined ChIP-seq and transcriptome analysis revealed that the increased H3K27me3 and down-regulated genes have significant enrichment in the ECM-receptor interaction, tight junction, cell adhesion molecules, adherens junction, and TGF-beta signaling pathways. CONCLUSIONS: Overall, the trimethylation modification of H3K27 has been shown to have significant regulatory function in FLHS, mediating the expression of crucial genes associated with the ECM-receptor interaction pathway. This highlights the epigenetic mechanisms of H3K27me3 and provides insights into exploring core regulatory targets and nutritional regulation strategies in FLHS.

Experimental and Numerical Simulation Research on Controllable Shock Wave-Induced Shale Fracturing under Repeated Action.

Low permeability is a key geological factor constraining the development of shale gas, and reservoir modification to improve its permeability is a prerequisite. Controlled shock wave fracturing can induce the formation of complex fractures in reservoirs and is expected to become an important means of reservoir modification. However, the mechanism of controlled shock wave fracturing in shale and the geological engineering control factors are unclear. Therefore, this article reveals the mechanism and effect of shock wave modification through small-scale experiments and large-scale numerical simulations. Results show that as the impact number increases, a significant increase in large fractures and fracture connectivity within the shale samples is observed, while the correlation between the geometric parameters of the fractures and the number of impacts is weak. High-energy input in the model will cause a larger range of damage to the rock, accompanied by a smaller attenuation index, indicating that the speed of energy attenuation plays a decisive role in rock damage. The influence of crustal stress is greater than the speed of energy attenuation, and higher crustal stress will inhibit the formation of fractures. A moderate increase in the number of controllable shock waves is beneficial for the fracturing effect; however, further increasing the loading number of controllable shock waves will weaken the strengthening effect of the fracturing effect.

Machine learning modeling for ultrasonic quality attribute assessment of pharmaceutical tablets for continuous manufacturing and real-time release testing.

In in-process quality monitoring for Continuous Manufacturing (CM) and Critical Quality Attributes (CQA) assessment for Real-time Release (RTR) testing, ultrasonic characterization is a critical technology for its direct, non-invasive, rapid, and cost-effective nature. In quality evaluation with ultrasound, relating a pharmaceutical tablet's ultrasonic response to its defect state and quality parameters is essential. However, ultrasonic CQA characterization requires a robust mathematical model, which cannot be obtained with traditional first principles-based modeling approaches. Machine Learning (ML) using experimental data is emerging as a critical analytical tool for overcoming such modeling challenges. In this work, a novel Deep Neural Network-based ML-driven Non-Destructive Evaluation (ML-NDE) modeling framework is developed, and its effectiveness for extracting and predicting three CQAs, namely defect states, compression force levels, and amounts of disintegrant, is demonstrated. Using a robotic tablet handling experimental rig, each attribute's distinct waveform dataset was acquired and utilized for training, validating, and testing the respective ML models. This study details an advanced algorithmic quality assessment framework for pharmaceutical CM in which automated RTR testing is expected to be critical in developing cost-effective in-process real-time monitoring systems. The presented ML-NDE approach has demonstrated its effectiveness through evaluations with separate (unused) test datasets.

Customized Intranasal Hydrogel Delivering Methylene Blue Ameliorates Cognitive Dysfunction against Alzheimer's Disease.

The accumulation of hyperphosphorylated tau protein aggregates is a key pathogenic event in Alzheimer's disease (AD) and induces mitochondrial dysfunction and reactive oxygen species overproduction. However, the treatment of AD remains challenging owning to the hindrance caused by the blood-brain barrier (BBB) and the complex pathology of AD. Nasal delivery represents an effective means of circumventing the BBB and delivering drugs to the brain. In this study, black phosphorus (BP) is used as a drug carrier, as well as an antioxidant, and loaded with a tau aggregation inhibitor, methylene blue (MB), to obtain BP-MB. For intranasal (IN) delivery, a thermosensitive hydrogel is fabricated by cross-linking carboxymethyl chitosan and aldehyde Pluronic F127 (F127-CHO) micelles. The BP-MB nanocomposite is incorporated into the hydrogel to obtain BP-MB@Gel. BP-MB@Gel could be injected intranasally, providing high nasal mucosal retention and controlled drug release. After IN administration, BP-MB is continuously released and delivered to the brain, exerting synergistic therapeutic effects by suppressing tau neuropathology, restoring mitochondrial function, and alleviating neuroinflammation, thus inducing cognitive improvements in mouse models of AD. These findings highlight a potential strategy for brain-targeted drug delivery in the management of the complex pathologies of AD.

The unique salt bridge network in GlacPETase: a key to its stability.

The extensive accumulation of polyethylene terephthalate (PET) has become a critical environmental issue. PET hydrolases can break down PET into its building blocks. Recently, we identified a glacial PET hydrolase GlacPETase sharing less than 31% amino acid identity with any known PET hydrolases. In this study, the crystal structure of GlacPETase was determined at 1.8 Å resolution, revealing unique structural features including a distinctive N-terminal disulfide bond and a specific salt bridge network. Site-directed mutagenesis demonstrated that the disruption of the N-terminal disulfide bond did not reduce GlacPETase's thermostability or its catalytic activity on PET. However, mutations in the salt bridges resulted in changes in melting temperature ranging from -8°C to +2°C and the activity on PET ranging from 17.5% to 145.5% compared to the wild type. Molecular dynamics simulations revealed that these salt bridges stabilized the GlacPETase's structure by maintaining their surrounding structure. Phylogenetic analysis indicated that GlacPETase represented a distinct branch within PET hydrolases-like proteins, with the salt bridges and disulfide bonds in this branch being relatively conserved. This research contributed to the improvement of our comprehension of the structural mechanisms that dictate the thermostability of PET hydrolases, highlighting the diverse characteristics and adaptability observed within PET hydrolases.IMPORTANCEThe pervasive problem of polyethylene terephthalate (PET) pollution in various terrestrial and marine environments is widely acknowledged and continues to escalate. PET hydrolases, such as GlacPETase in this study, offered a solution for breaking down PET. Its unique origin and less than 31% identity with any known PET hydrolases have driven us to resolve its structure. Here, we report the correlation between its unique structure and biochemical properties, focusing on an N-terminal disulfide bond and specific salt bridges. Through site-directed mutagenesis experiments and molecular dynamics simulations, the roles of the N-terminal disulfide bond and salt bridges were elucidated in GlacPETase. This research enhanced our understanding of the role of salt bridges in the thermostability of PET hydrolases, providing a valuable reference for the future engineering of PET hydrolases.

Interplay of Drug-Polymer Interactions and Release Performance for HPMCAS-Based Amorphous Solid Dispersions.

The interplay between drug and polymer chemistry and its impact on drug release from an amorphous solid dispersion (ASD) is a relatively underexplored area. Herein, the release rates of several drugs of diverse chemistry from hydroxypropyl methylcellulose acetate succinate (HPMCAS)-based ASDs were explored using surface area normalized dissolution. The tendency of the drug to form an insoluble complex with HPMCAS was determined through coprecipitation experiments. The role of pH and the extent of drug ionization were probed to evaluate the role of electrostatic interactions in complex formation. Relationships between the extent of complexation and the drug release rate from an ASD were observed, whereby the drugs could be divided into two groups. Drugs with a low extent of insoluble complex formation with HPMCAS tended to be neutral or anionic and showed reasonable release at pH 6.8 even at higher drug loadings. Cationic drugs formed insoluble complexes with HPMCAS and showed poor release when formulated as an ASD. Thus, and somewhat counterintuitively, a weakly basic drug showed a reduced release rate from an ASD at a bulk solution pH where it was ionized, relative to when unionized. The opposite trend was observed in the absence of polymer for the neat amorphous drug. In conclusion, electrostatic interactions between HPMCAS and lipophilic cationic drugs led to insoluble complex formation, which in turn resulted in ASDs with poor release performance.

AlmA involved in the long-chain n-alkane degradation pathway in Acinetobacter baylyi ADP1 is a Baeyer-Villiger monooxygenase.

Many Acinetobacter species can grow on n-alkanes of varying lengths (≤C40). AlmA, a unique flavoprotein in these Acinetobacter strains, is the only enzyme proven to be required for the degradation of long-chain (LC) n-alkanes, including C32 and C36 alkanes. Although it is commonly presumed to be a terminal hydroxylase, its role in n-alkane degradation remains elusive. In this study, we conducted physiological, biochemical, and bioinformatics analyses of AlmA to determine its role in n-alkane degradation by Acinetobacter baylyi ADP1. Consistent with previous reports, gene deletion analysis showed that almA was vital for the degradation of LC n-alkanes (C26-C36). Additionally, enzymatic analysis revealed that AlmA catalyzed the conversion of aliphatic 2-ketones (C10-C16) to their corresponding esters, but it did not conduct n-alkane hydroxylation under the same conditions, thus suggesting that AlmA in strain ADP1 possesses Baeyer-Villiger monooxygenase (BVMO) activity. These results were further confirmed by bioinformatics analysis, which revealed that AlmA was closer to functionally identified BVMOs than to hydroxylases. Altogether, the results of our study suggest that LC n-alkane degradation by strain ADP1 possibly follows a novel subterminal oxidation pathway that is distinct from the terminal oxidation pathway followed for short-chain n-alkane degradation. Furthermore, our findings suggest that AlmA catalyzes the third reaction in the LC n-alkane degradation pathway.IMPORTANCEMany microbial studies on n-alkane degradation are focused on the genes involved in short-chain n-alkane (≤C16) degradation; however, reports on the genes involved in long-chain (LC) n-alkane (>C20) degradation are limited. Thus far, only AlmA has been reported to be involved in LC n-alkane degradation by Acinetobacter spp.; however, its role in the n-alkane degradation pathway remains elusive. In this study, we conducted a detailed characterization of AlmA in A. baylyi ADP1 and found that AlmA exhibits Baeyer-Villiger monooxygenase activity, thus indicating the presence of a novel LC n-alkane biodegradation mechanism in strain ADP1.

Size Modulation of Conjugated Polymer Nanoparticles for Improved NIR-II Fluorescence Imaging and Photothermal Therapy.

Near-infrared-II fluorescence imaging (NIR-II FI) has become a powerful imaging technique for disease diagnosis owing to its superiorities, including high sensitivity, high spatial resolution, deep imaging depth, and low background interference. Despite the widespread application of conjugated polymer nanoparticles (CPNs) for NIR-II FI, most of the developed CPNs have quite low NIR-II fluorescence quantum yields based on the energy gap law, which makes high-sensitivity and high-resolution imaging toward deep lesions still a huge challenge. This work proposes a nanoengineering strategy to modulate the size of CPNs aimed at optimizing their NIR-II fluorescence performance for improved NIR-II phototheranostics. By adjusting the initial concentration of the synthesized conjugated polymer, a series of CPNs with different particle sizes are successfully prepared via a nanoprecipitation approach. Results show that the NIR-II fluorescence brightness of CPNs gradually amplifies with decreasing particle size, and the optimal CPNs, NP0.2, demonstrate up to a 2.05-fold fluorescence enhancement compared with the counterpart nanoparticles. With the merits of reliable biocompatibility, high photostability, and efficient light-heat conversion, the optimal NP0.2 has been successfully employed for NIR-II FI-guided photothermal therapy both in vitro and in vivo. Our work highlights an effective strategy of nanoengineering to improve the NIR-II performance of CPNs, advancing the development of NIR-II FI in life sciences.

Responses of the intestinal microbiota to exposure of okadaic acid in marine medaka Oryzias melastigma.

It is still limited that how the microalgal toxin okadaic acid (OA) affects the intestinal microbiota in marine fishes. In the present study, adult marine medaka Oryzias melastigma was exposed to the environmentally relevant concentration of OA (5 µg/L) for 10 days, and then recovered in fresh seawater for 10-days depuration. Analysis of taxonomic composition and diversity of the intestinal microbiota, as well as function prediction analysis and histology observation were carried out in this study. Functional prediction analysis indicated that OA potentially affected the development of colorectal cancer, protein and carbohydrate digestion and absorption functions, and development of neurodegenerative diseases like Parkinson's disease, which may be associated with changes in Proteobacteria and Firmicutes in marine medaka. Significant increases of C-reactive protein (CRP) and inducible nitric oxide synthase (iNOS) levels, as well as the changes of histology of intestinal tissue demonstrated that an intestinal inflammation was induced by OA exposure in marine medaka. This study showed that the environmental concentrations of OA could harm to the intestinal microbiota thus threatening the health of marine medaka, which hints that the chemical ecology of microalgal toxins should be paid attention to in future studies.