Machine learning identifies key metabolic reactions in bacterial growth on different carbon sources.

Carbon source-dependent control of bacterial growth is fundamental to bacterial physiology and survival. However, pinpointing the metabolic steps important for cell growth is challenging due to the complexity of cellular networks. Here, the elastic net model and multilayer perception model that integrated genome-wide gene-deletion data and simulated flux distributions were constructed to identify metabolic reactions beneficial or detrimental to Escherichia coli grown on 30 different carbon sources. Both models outperformed traditional in silico methods by identifying not just essential reactions but also nonessential ones that promote growth. They successfully predicted metabolic reactions beneficial to cell growth, with high convergence between the models. The models revealed that biosynthetic pathways generally promote growth across various carbon sources, whereas the impact of energy-generating pathways varies with the carbon source. Intriguing predictions were experimentally validated for findings beyond experimental training data and the impact of various carbon sources on the glyoxylate shunt, pyruvate dehydrogenase reaction, and redundant purine biosynthesis reactions. These highlight the practical significance and predictive power of the models for understanding and engineering microbial metabolism.

Genome-scale metabolic network model and phenome of solvent-tolerant Pseudomonas putida S12.

BACKGROUND: Pseudomonas putida S12 is a gram-negative bacterium renowned for its high tolerance to organic solvents and metabolic versatility, making it attractive for various applications, including bioremediation and the production of aromatic compounds, bioplastics, biofuels, and value-added compounds. However, a metabolic model of S12 has yet to be developed. RESULTS: In this study, we present a comprehensive and highly curated genome-scale metabolic network model of S12 (iSH1474), containing 1,474 genes, 1,436 unique metabolites, and 2,938 metabolic reactions. The model was constructed by leveraging existing metabolic models and conducting comparative analyses of genomes and phenomes. Approximately 2,000 different phenotypes were measured for S12 and its closely related KT2440 strain under various nutritional and environmental conditions. These phenotypic data, combined with the reported experimental data, were used to refine and validate the reconstruction. Model predictions quantitatively agreed well with in vivo flux measurements and the batch cultivation of S12, which demonstrated that iSH1474 accurately represents the metabolic capabilities of S12. Furthermore, the model was simulated to investigate the maximum theoretical metabolic capacity of S12 growing on toxic organic solvents. CONCLUSIONS: iSH1474 represents a significant advancement in our understanding of the cellular metabolism of P. putida S12. The combined results of metabolic simulation and comparative genome and phenome analyses identified the genetic and metabolic determinants of the characteristic phenotypes of S12. This study could accelerate the development of this versatile organism as an efficient cell factory for various biotechnological applications.

Genome-wide characterization and expression profiling of E2F/DP gene family members in response to abiotic stress in tomato (Solanum lycopersicum L.).

BACKGROUND: E2F/DP (Eukaryotic 2 transcription factor/dimerization partner) family proteins play an essential function in the cell cycle development of higher organisms. E2F/DP family genes have been reported only in a few plant species. However, comprehensive genome-wide characterization analysis of the E2F/DP gene family of Solanum lycopersicum has not been reported so far. RESULTS: This study identified eight nonredundant SlE2F/DP genes that were classified into seven groups in the phylogenetic analysis. All eight genes had a single E2F-TDP domain and few genes had additional domains. Two segmental duplication gene pairs were observed within tomato, in addition to cis-regulatory elements, miRNA target sites and phosphorylation sites which play an important role in plant development and stress response in tomato. To explore the three-dimensional (3D) models and gene ontology (GO) annotations of SlE2F/DP proteins, we pointed to their putative transporter activity and their interaction with several putative ligands. The localization of SlE2F/DP-GFP fused proteins in the nucleus and endoplasmic reticulum suggested that they may act in other biological functions. Expression studies revealed the differential expression pattern of most of the SlE2F/DP genes in various organs. Moreover, the expression of E2F/DP genes against abiotic stress, particularly SlE2F/DP2 and/or SlE2F/DP7, was upregulated in response to heat, salt, cold and ABA treatment. Furthermore, the co-expression analysis of SlE2F/DP genes with multiple metabolic pathways was co-expressed with defence genes, transcription factors and so on, suggested their crucial role in various biological processes. CONCLUSIONS: Overall, our findings provide a way to understand the structure and function of SlE2F/DP genes; it might be helpful to improve fruit development and tolerance against abiotic stress through marker-assisted selection or transgenic approaches.

Early Prediction of Mortality for Septic Patients Visiting Emergency Room Based on Explainable Machine Learning: A Real-World Multicenter Study.

BACKGROUND: Worldwide, sepsis is the leading cause of death in hospitals. If mortality rates in patients with sepsis can be predicted early, medical resources can be allocated efficiently. We constructed machine learning (ML) models to predict the mortality of patients with sepsis in a hospital emergency department. METHODS: This study prospectively collected nationwide data from an ongoing multicenter cohort of patients with sepsis identified in the emergency department. Patients were enrolled from 19 hospitals between September 2019 and December 2020. For acquired data from 3,657 survivors and 1,455 deaths, six ML models (logistic regression, support vector machine, random forest, extreme gradient boosting [XGBoost], light gradient boosting machine, and categorical boosting [CatBoost]) were constructed using fivefold cross-validation to predict mortality. Through these models, 44 clinical variables measured on the day of admission were compared with six sequential organ failure assessment (SOFA) components (PaO2/FIO2 [PF], platelets (PLT), bilirubin, cardiovascular, Glasgow Coma Scale score, and creatinine). The confidence interval (CI) was obtained by performing 10,000 repeated measurements via random sampling of the test dataset. All results were explained and interpreted using Shapley's additive explanations (SHAP). RESULTS: Of the 5,112 participants, CatBoost exhibited the highest area under the curve (AUC) of 0.800 (95% CI, 0.756-0.840) using clinical variables. Using the SOFA components for the same patient, XGBoost exhibited the highest AUC of 0.678 (95% CI, 0.626-0.730). As interpreted by SHAP, albumin, lactate, blood urea nitrogen, and international normalization ratio were determined to significantly affect the results. Additionally, PF and PLTs in the SOFA component significantly influenced the prediction results. CONCLUSION: Newly established ML-based models achieved good prediction of mortality in patients with sepsis. Using several clinical variables acquired at the baseline can provide more accurate results for early predictions than using SOFA components. Additionally, the impact of each variable was identified.

A Novel Approach to Clustering Accelerometer Data for Application in Passive Predictions of Changes in Depression Severity.

The treatment of mood disorders, which can become a lifelong process, varies widely in efficacy between individuals. Most options to monitor mood rely on subjective self-reports and clinical visits, which can be burdensome and may not portray an accurate representation of what the individual is experiencing. A passive method to monitor mood could be a useful tool for those with these disorders. Some previously proposed models utilized sensors from smartphones and wearables, such as the accelerometer. This study examined a novel approach of processing accelerometer data collected from smartphones only while participants of the open-science branch of the BiAffect study were typing. The data were modeled by von Mises-Fisher distributions and weighted networks to identify clusters relating to different typing positions unique for each participant. Longitudinal features were derived from the clustered data and used in machine learning models to predict clinically relevant changes in depression from clinical and typing measures. Model accuracy was approximately 95%, with 97% area under the ROC curve (AUC). The accelerometer features outperformed the vast majority of clinical and typing features, which suggested that this new approach to analyzing accelerometer data could contribute towards unobtrusive detection of changes in depression severity without the need for clinical input.

Role of TRPC3 in Right Ventricular Dilatation under Chronic Intermittent Hypoxia in 129/SvEv Mice.

Patients with obstructive sleep apnea (OSA) exhibit a high prevalence of pulmonary hypertension and right ventricular (RV) hypertrophy. However, the exact molecule responsible for the pathogenesis remains unknown. Given the resistance to RV dilation observed in transient receptor potential canonical 3(Trpc3)-/- mice during a pulmonary hypertension model induced by phenylephrine (PE), we hypothesized that TRPC3 also plays a role in chronic intermittent hypoxia (CIH) conditions, which lead to RV dilation and dysfunction. To test this, we established an OSA mouse model using 8- to 12-week-old 129/SvEv wild-type and Trpc3-/- mice in a customized breeding chamber that simulated sleep and oxygen cycles. Functional parameters of the RV were evaluated through analysis of cardiac cine magnetic resonance images, while histopathological examinations were conducted on cardiomyocytes and pulmonary vessels. Following exposure to 4 weeks of CIH, Trpc3-/- mice exhibited significant RV dysfunction, characterized by decreased ejection fraction, increased end-diastole RV wall thickness, and elevated expression of pathological cardiac markers. In addition, reactive oxygen species (ROS) signaling and the endothelin system were markedly increased solely in the hearts of CIH-exposed Trpc3-/- mice. Notably, no significant differences in pulmonary vessel thickness or the endothelin system were observed in the lungs of wild-type (WT) and Trpc3-/- mice subjected to 4 weeks of CIH. In conclusion, our findings suggest that TRPC3 serves as a regulator of RV resistance in response to pressure from the pulmonary vasculature, as evidenced by the high susceptibility to RV dilation in Trpc3-/- mice without notable changes in pulmonary vasculature under CIH conditions.

Anti-inflammatory Glycocalyx-Mimicking Nanoparticles for Colitis Treatment: Construction and In Vivo Evaluation.

Common medications for treating inflammatory bowel disease (IBD) have limited therapeutic efficacy and severe adverse effects. This underscores the urgent need for novel therapeutic approaches that can effectively target inflamed sites in the gastrointestinal tract upon oral administration, exerting potent therapeutic efficacy while minimizing systemic effects. Here, we report the construction and in vivo therapeutic evaluation of a library of anti-inflammatory glycocalyx-mimicking nanoparticles (designated GlyNPs) in a mouse model of IBD. The anti-inflammatory GlyNP library was created by attaching bilirubin (BR) to a library of glycopolymers composed of random combinations of the five most naturally abundant sugars. Direct in vivo screening of 31 BR-attached anti-inflammatory GlyNPs via oral administration into mice with acute colitis led to identification of a candidate GlyNP capable of targeting macrophages in the inflamed colon and effectively alleviating colitis symptoms. These findings suggest that the BR-attached GlyNP library can be used as a platform to identify anti-inflammatory nanomedicines for various inflammatory diseases.

Active small bowel sparing in intracavitary brachytherapy for cervical cancer.

OBJECTIVE: To propose and evaluate an active method for sparing the small bowel in the treatment field of cervical cancer brachytherapy by prone position procedure. METHODS: The prone position procedure consists of five steps: making bladder empty, prone-positioning a patient on belly board, making the small bowel move to abdomen, filling the bladder with Foley catheter and finally turning the patient into the supine position. The proposed method was applied for the treatment of seven cervical cancer patients. Its effectiveness was evaluated and a correlation between the patient characteristics and the volumetric dose reduction of small bowel was also investigated. Brachytherapy treatment plans were built before and after the proposed method, and their dose-volume histograms were compared for targets and organs-at-risk. In this comparison, all plans were normalized to satisfy the same D90% for high-risk clinical target volume. RESULTS: For the enrolled patients, the average dose of small bowel was significantly reduced from 75.2 ± 4.9 Gy before to 60.2 ± 4.0 Gy after the prone position procedure, while minor dosimetric changes were observed in rectum, sigmoid and bladder. The linear correlation to body mass index, thickness and width of abdominopelvic cavity and bladder volume were 76.2, 69.7, 28.8 and -36.3%, respectively. CONCLUSIONS: The application of prone position procedure could effectively lower the volumetric dose of the small bowel. The dose reduction in the small bowel had a strong correlation with the patient's obesity and abdominal thickness. This means the patients for whom the proposed method would be beneficial can be judiciously selected for safe brachytherapy.

Assessment of a Therapeutic X-ray Radiation Dose Measurement System Based on a Flexible Copper Indium Gallium Selenide Solar Cell.

Several detectors have been developed to measure radiation doses during radiotherapy. However, most detectors are not flexible. Consequently, the airgaps between the patient surface and detector could reduce the measurement accuracy. Thus, this study proposes a dose measurement system based on a flexible copper indium gallium selenide (CIGS) solar cell. Our system comprises a customized CIGS solar cell (with a size 10 × 10 cm2 and thickness 0.33 mm), voltage amplifier, data acquisition module, and laptop with in-house software. In the study, the dosimetric characteristics, such as dose linearity, dose rate independence, energy independence, and field size output, of the dose measurement system in therapeutic X-ray radiation were quantified. For dose linearity, the slope of the linear fitted curve and the R-square value were 1.00 and 0.9999, respectively. The differences in the measured signals according to changes in the dose rates and photon energies were <2% and <3%, respectively. The field size output measured using our system exhibited a substantial increase as the field size increased, contrary to that measured using the ion chamber/film. Our findings demonstrate that our system has good dosimetric characteristics as a flexible in vivo dosimeter. Furthermore, the size and shape of the solar cell can be easily customized, which is an advantage over other flexible dosimeters based on an a-Si solar cell.

Direct visualization of single-molecule membrane protein interactions in living cells.

Interactions between membrane proteins are poorly understood despite their importance in cell signaling and drug development. Here, we present a co-immunoimmobilization assay (Co-II) enabling the direct observation of membrane protein interactions in single living cells that overcomes the limitations of currently prevalent proximity-based indirect methods. Using Co-II, we investigated the transient homodimerizations of epidermal growth factor receptor (EGFR) and beta-2 adrenergic receptor (ß2-AR) in living cells, revealing the differential regulation of these receptors' dimerizations by molecular conformations and microenvironment in a plasma membrane. Co-II should provide a simple, rapid, and robust platform for visualizing both weak and strong protein interactions in the plasma membrane of living cells.

Development of a Genome-Scale Metabolic Model and Phenome Analysis of the Probiotic Escherichia coli Strain Nissle 1917.

Escherichia coli Nissle 1917 (EcN) is an intestinal probiotic that is effective for the treatment of intestinal disorders, such as inflammatory bowel disease and ulcerative colitis. EcN is a representative Gram-negative probiotic in biomedical research and is an intensively studied probiotic. However, to date, its genome-wide metabolic network model has not been developed. Here, we developed a comprehensive and highly curated EcN metabolic model, referred to as iDK1463, based on genome comparison and phenome analysis. The model was improved and validated by comparing the simulation results with experimental results from phenotype microarray tests. iDK1463 comprises 1463 genes, 1313 unique metabolites, and 2984 metabolic reactions. Phenome data of EcN were compared with those of Escherichia coli intestinal commensal K-12 MG1655. iDK1463 was simulated to identify the genetic determinants responsible for the observed phenotypic differences between EcN and K-12. Further, the model was simulated for gene essentiality analysis and utilization of nutrient sources under anaerobic growth conditions. These analyses provided insights into the metabolic mechanisms by which EcN colonizes and persists in the gut. iDK1463 will contribute to the system-level understanding of the functional capacity of gut microbes and their interactions with microbiota and human hosts, as well as the development of live microbial therapeutics.

A single amino acid substitution in aromatic hydroxylase (HpaB) of Escherichia coli alters substrate specificity of the structural isomers of hydroxyphenylacetate.

BACKGROUND: A broad range of aromatic compounds can be degraded by enteric bacteria, and hydroxyphenylacetic acid (HPA) degrading bacteria are the most widespread. Majority of Escherichia coli strains can use both the structural isomers of HPA, 3HPA and 4HPA, as the sole carbon source, which are catabolized by the same pathway whose associated enzymes are encoded by hpa gene cluster. Previously, we observed that E. coli B REL606 grew only on 4HPA, while E. coli B BL21(DE3) grew on 3HPA as well as 4HPA. RESULTS: In this study, we report that a single amino acid in 4-hydroxyphenylacetate 3-hydroxylase (HpaB) of E. coli determines the substrate specificity of HPA isomers. Alignment of protein sequences encoded in hpa gene clusters of BL21(DE3) and REL606 showed that there was a difference of only one amino acid (position 379 in HpaB) between the two, viz., Arg in BL21(DE3) and Cys in REL606. REL606 cells expressing HpaB having Arg379 could grow on 3HPA, whereas those expressing HpaB with Gly379 or Ser379 could not. Structural analysis suggested that the amino acid residue at position 379 of HpaB is located not in the active site, but in the vicinity of the 4HPA binding site, and that it plays an important role in mediating the entrance and stable binding of substrates to the active site. CONCLUSIONS: The arginine residue at position 379 of HpaB is critical for 3HPA recognition. Information regarding the effect of amino acid residues on the substrate specificity of structural isomers can facilitate in designing hydoxylases with high catalytic efficiency and versatility.

Feasibility study of shutter scan acquisition for region of interest (ROI) digital tomosynthesis.

Dose reduction techniques have been studied in medical imaging. We propose shutter scan acquisition for region of interest (ROI) imaging to reduce the patient exposure dose received from a digital tomosynthesis system. A prototype chest digital tomosynthesis (CDT) system (LISTEM, Wonju, Korea) and the LUNGMAN phantom (Kyoto Kagaku, Japan) with lung nodules 8, 10, and 12 mm in size were used for this study. A total of 41 projections with shutter scan acquisition consisted of 21 truncated projections and 20 non-truncated projections. For comparison, 41 projections using conventional full view scan acquisition were also acquired. Truncated projections obtained by shutter scan acquisition were corrected by proposed image processing procedure to remove the truncation artifacts. The image quality was evaluated using the contrast to noise ratio (CNR), coefficient of variation (COV), and figure of merit (FOM). We measured the dose area product (DAP) value to verify the dose reduction using shutter scan acquisition. The ROI of the reconstructed image from shutter scan acquisition showed enhanced contrast. The results showed that CNR values of 8 and 12 mm lung nodules increased by 6.38% and 21.21%, respectively, and the CNR value of 10 mm lung nodule decreased by 3.63%. COV values of the lung nodules were lower in a shutter scan image than in a full view scan image. FOM values of 8, 10, and 12 mm lung nodules increased by 3.06, 2.25, and 2.33 times, respectively. This study compared the proposed shutter scan and conventional full view scan acquisition. In conclusion, using a shutter scan acquisition method resulted in enhanced contrast images within the ROI and higher FOM values. The patient exposure dose of the proposed shutter scan acquisition method can be reduced by limiting the field of view (FOV) to focus on the ROI.

Analysis of Interactions between the Epidermal Growth Factor Receptor and Soluble Ligands on the Basis of Single-Molecule Diffusivity in the Membrane of Living Cells.

We present a single-molecule diffusional-mobility-shift assay (smDIMSA) for analyzing the interactions between membrane and water-soluble proteins in the crowded membrane of living cells. We found that ligand-receptor interactions decreased the diffusional mobility of ErbB receptors and ß-adrenergic receptors, as determined by single-particle tracking with super-resolution microscopy. The shift in diffusional mobility was sensitive to the size of the water-soluble binders that ranged from a few tens of kilodaltons to several hundred kilodaltons. This technique was used to quantitatively analyze the dissociation constant and the cooperativity of antibody interactions with the epidermal growth factor receptor and its mutants. smDIMSA enables the quantitative investigation of previously undetected ligand-receptor interactions in the intact membrane of living cells on the basis of the diffusivity of single-molecule membrane proteins without ligand labeling.

Proteomic analysis of hypoxia-induced U373MG glioma secretome reveals novel hypoxia-dependent migration factors.

High-grade gliomas are one of the most common brain tumors and notorious for poor prognosis due to their malignant nature. Gliomas have an extensive area of hypoxia, which is critical for glioma progression by inducing aggressiveness and activating the angiogenesis process in the tumor microenvironment. To resolve the factors responsible for the highly malignant nature of gliomas, we comprehensively profiled the U373MG glioma cell secretome-exosome and soluble fraction under hypoxic and normoxic conditions. A total of 239 proteins were identified from the exosome and soluble fractions. Vascular endothelial growth factor, stanniocalcin 1 (STC1) and stanniocalcin 2, and insulin-like growth factor binding protein 3 and 6, enriched in the soluble fraction, and lysyl oxidase homolog 2 enriched in the exosomal fraction were identified as upregulated proteins by hypoxia based on a label-free quantitative analysis. STCs and insulin-like growth factor binding proteins, which were identified as secretory proteins under hypoxic conditions, were highly correlated with glioma grade in human patients by microarray analysis. An in vitro scratch wound assay revealed that STC1 and 2 have important functions in the induction of cell migration in a hypoxia-dependent manner, suggesting that they are hypoxia-dependent migration factors.

SiSe2 for Superior Sulfide Solid Electrolytes and Li-Ion Batteries.

Among the various existing layered compounds, silicon diselenide (SiSe2) possesses diverse chemical and physical properties, owing to its large interlayer spacing and interesting atomic arrangements. Despite the unique properties of layered SiSe2, it has not yet been used in energy applications. Herein, we introduce the synthesis of layered SiSe2 through a facile solid-state synthetic route and demonstrate its versatility as a sulfide solid electrolyte (SE) additive for all-solid-state batteries (ASSBs) and as an anode material for Li-ion batteries (LIBs). Li-argyrodites with various compositions substituted with SiSe2 are synthesized and evaluated as sulfide SEs for ASSBs. SiSe2-substituted Li-argyrodites exhibit high ionic conductivities, low activation energies, and high air stabilities. In addition, when using a sulfide SE, the ASSB full cell exhibits a high discharge/charge capacity of 202/169 mAh g-1 with a high initial Coulombic efficiency (ICE) of 83.7% and stable capacity retention at 1C after 100 cycles. Furthermore, the Li-storage properties of SiSe2 as an anode material for LIBs are evaluated, and its Li-pathway mechanism is explored by using various cutting-edge ex situ analytical tools. Moreover, the SiSe2 nanocomposite anode exhibits a high Li- insertion/extraction capacity of 950/775 mAh g-1, a high ICE of 81.6%, a fast rate capability, and stable capacity retention after 300 cycles. Accordingly, layered SiSe2 and its versatile applications as a sulfide SE additive for ASSBs and an anode material for LIBs are promising candidates in energy storage applications as well as myriad other applications.

Noninvasive ROS imaging and drug delivery monitoring in the tumor microenvironment.

Reactive oxygen species (ROS) that are overproduced in certain tumors can be considered an indicator of oxidative stress levels in the tissue. Here, we report a magnetic resonance imaging (MRI)-based probe capable of detecting ROS levels in the tumor microenvironment (TME) using ROS-responsive manganese ion (Mn2+)-chelated, biotinylated bilirubin nanoparticles (Mn@bt-BRNPs). These nanoparticles are disrupted in the presence of ROS, resulting in the release of free Mn2+, which induces T1-weighted MRI signal enhancement. Mn@BRNPs show more rapid and greater MRI signal enhancement in high ROS-producing A549 lung carcinoma cells compared with low ROS-producing DU145 prostate cancer cells. A pseudo three-compartment model devised for the ROS-reactive MRI probe enables mapping of the distribution and concentration of ROS within the tumor. Furthermore, doxorubicin-loaded, cancer-targeting ligand biotin-conjugated Dox/Mn@bt-BRNPs show considerable accumulation in A549 tumors and also effectively inhibit tumor growth without causing body weight loss, suggesting their usefulness as a new theranostic agent. Collectively, these findings suggest that Mn@bt-BRNPs could be used as an imaging probe capable of detecting ROS levels and monitoring drug delivery in the TME with potential applicability to other inflammatory diseases.

Longitudinal Magnetic Resonance Imaging with ROS-Responsive Bilirubin Nanoparticles Enables Monitoring of Nonalcoholic Steatohepatitis Progression to Cirrhosis.

Despite the vital importance of monitoring the progression of nonalcoholic fatty liver disease (NAFLD) and its progressive form, nonalcoholic steatohepatitis (NASH), an efficient imaging modality that is readily available at hospitals is currently lacking. Here, a new magnetic-resonance-imaging (MRI)-based imaging modality is presented that allows for efficient and longitudinal monitoring of NAFLD and NASH progression. The imaging modality uses manganese-ion (Mn2+)-chelated bilirubin nanoparticles (Mn@BRNPs) as a reactive-oxygen-species (ROS)-responsive MRI imaging probe. Longitudinal T1-weighted MR imaging of NASH model mice is performed after injecting Mn@BRNPs intravenously. The MR signal enhancement in the liver relative to muscle gradually increases up to 8 weeks of NASH progression, but decreases significantly as NASH progresses to the cirrhosis-like stage at weeks 10 and 12. A new dual input pseudo-three-compartment model is developed to provide information on NASH stage with a single MRI scan. It is also demonstrated that the ROS-responsive Mn@BRNPs can be used to monitor the efficacy of potential anti-NASH drugs with conventional MRI. The findings suggest that the ROS-responsive Mn@BRNPs have the potential to serve as an efficient MRI contrast for monitoring NASH progression and its transition to the cirrhosis-like stage.

A chitosan/alginate coated nano-liposome to improve intestinal absorption of curcumin for oral administration.

Attempts to improve low absorption and rapid metabolic conversion of curcumin were made by developing curcumin-loaded bilayer nanoliposomes coated with chitosan and alginate for intestinal-specific drug delivery. A curcumin-loaded nano-liposome was prepared with optimized formulations with phosphatidylcholine, curcumin, chitosan, and alginate. The particle size of the optimized formulation was approximately 400 nm, and the encapsulation efficiency was more than 99%. In the in vitro release study, curcumin release from the curcumin-loaded nanoliposome with double layers of chitosan/alginate (CNL-CH/AL) was suppressed in the simulated gastric fluid (SGF, pH 1.2) and enhanced in the simulated intestinal fluid (SIF, pH 6.8). In the in vivo pharmacokinetic study in rats, the CNL-CH/AL-treated group showed a prolonged absorption pattern of curcumin and the area under the plasma concentration-time curve from 0 to 24 h (AUC0-24) was improved 109-fold compared to the control group treated with a curcumin solution without a nanocarrier.

Facemask acne attenuation through modulation of indirect microbiome interactions.

During the COVID-19 pandemic, facemasks played a pivotal role in preventing person-person droplet transmission of viral particles. However, prolonged facemask wearing causes skin irritations colloquially referred to as 'maskne' (mask + acne), which manifests as acne and contact dermatitis and is mostly caused by pathogenic skin microbes. Previous studies revealed that the putative causal microbes were anaerobic bacteria, but the pathogenesis of facemask-associated skin conditions remains poorly defined. We therefore characterized the role of the facemask-associated skin microbiota in the development of maskne using culture-dependent and -independent methodologies. Metagenomic analysis revealed that the majority of the facemask microbiota were anaerobic bacteria that originated from the skin rather than saliva. Previous work demonstrated direct interaction between pathogenic bacteria and antagonistic strains in the microbiome. We expanded this analysis to include indirect interaction between pathogenic bacteria and other indigenous bacteria classified as either 'pathogen helper (PH)' or 'pathogen inhibitor (PIn)' strains. In vitro screening of bacteria isolated from facemasks identified both strains that antagonized and promoted pathogen growth. These data were validated using a mouse skin infection model, where we observed attenuation of symptoms following pathogen infection. Moreover, the inhibitor of pathogen helper (IPH) strain, which did not directly attenuate pathogen growth in vitro and in vivo, functioned to suppress symptom development and pathogen growth indirectly through PH inhibitory antibacterial products such as phenyl lactic acid. Taken together, our study is the first to define a mechanism by which indirect microbiota interactions under facemasks can control symptoms of maskne by suppressing a skin pathogen.