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Background and objectives: Characterization of pediatric coronavirus disease 2019 (COVID-19) is necessary to control the pandemic, as asymptomatic or mildly infected children may act as carriers. To date, there are limited reports describing differences in clinical, laboratory, and radiological characteristics between asymptomatic and symptomatic infection, and between younger and older pediatric patients. The objective of this study is to compare characteristics among: (1) asymptomatic versus symptomatic and (2) less than 10 versus greater or equal to 10 years old pediatric COVID-19 patients. Materials and Methods: We searched for all terms related to pediatric COVID-19 in electronic databases (Embase, Medline, PubMed, and Web of Science) for articles from January 2020. This protocol followed the Preferred Reporting Items for Systematic Reviews and Meta-Analysis guidelines. Results: Eligible study designs included case reports and series, while we excluded comments/letters, reviews, and literature not written in English. Initially, 817 articles were identified. Forty-three articles encompassing 158 confirmed pediatric COVID-19 cases were included in the final analyses. Lymphocytosis and high CRP were associated with symptomatic infection. Abnormal chest CT more accurately detected asymptomatic COVID-19 in older patients than in younger ones, but clinical characteristics were similar between older and younger patients. Conclusions: Chest CT scan findings are untrustworthy in younger children with COVID-19 as compared with clinical findings, or significant differences in findings between asymptomatic to symptomatic children. Further studies evaluating pediatric COVID-19 could contribute to potential therapeutic interventions and preventive strategies to limit spreading.
Subject(s)
Betacoronavirus , Coronavirus Infections/diagnosis , Lung/diagnostic imaging , Pneumonia, Viral/diagnosis , Tomography, X-Ray Computed/methods , Adolescent , COVID-19 , Child , Child, Preschool , Coronavirus Infections/prevention & control , Coronavirus Infections/transmission , Female , Humans , Male , Pandemics/prevention & control , Pneumonia, Viral/prevention & control , Pneumonia, Viral/transmission , SARS-CoV-2ABSTRACT
BACKGROUND: Microbiota and human allergic airway diseases have been proven to be interrelated. Bacteria-derived extracellular vesicle (EV)s are known to play important roles in interbacterial and human-bacteria communications, but their relationship with allergies has not been examined yet. Urine EVs were investigated to determine whether they could be used as biomarkers for monitoring allergic airway diseases in children. METHODS: Subjects were 4 groups of chronic rhinitis (CR), allergic rhinitis (AR), atopic asthma (AS) and healthy controls. Single voided urine samples were collected. Urine EVs were isolated and their DNA was extracted for 16S-rDNA pyrosequencing. RESULTS: A total of 118 children participated in this study; 27, 39, 19, and 33 were in the CR, AR, AS, and control group, respectively. The AR had a significantly high Chao-1 index than that of controls. Principal component analysis revealed dysbiosis in the CR, AR, and AS compared to the controls. One phylum and 19 families and genera were significantly enriched or depleted in the disease groups compared to the controls; the Actinobacteria phylum and the Sphingomonadaceae family were more abundant in the AS and CR, the Comamonadaceae family, the Propionibacteraceae family, Propionibacterium and Enhydrobacter were more enriched in the CR, and the Methylobacteriaceae family and Methylobacterium were more abundant in each disease group, while the Enterobacteriaceae family was depleted in each disease group. CONCLUSIONS: CR, AR, and AS had a distinct composition of urine EVs. Urine EVs could be an indicator for assessing allergic airway diseases in children.
Subject(s)
Bacteria/metabolism , Bacteriuria/metabolism , Bacteriuria/microbiology , Extracellular Vesicles/metabolism , Respiratory Hypersensitivity/etiology , Respiratory Hypersensitivity/metabolism , Age Factors , Bacteria/classification , Bacteria/genetics , Child , Child, Preschool , Female , Humans , Immunoglobulin E/blood , Immunoglobulin E/immunology , Male , Phylogeny , RNA, Ribosomal, 16S/genetics , Respiratory Hypersensitivity/diagnosisABSTRACT
Facilities for sensitive populations have increased in Korea; and its indoor air quality (IAQ) was strictly regulated by the Korean government compared to other facilities. However, merely public facilities on certain level of total floor area were lawfully regulated. This study aims to characterize the indoor environment at facilities for sensitive populations in Korea and investigate the effects of legal regulation on IAQ throughout the duration of 1 year. Sixty facilities for sensitive populations were investigated. Particulate matter (PM10), nitrogen dioxide (NO2), carbon dioxide (CO2), carbon monoxide (CO), total bacteria count (TBC), total volatile organic compound (TVOC), formaldehyde (HCHO), radon (Rn), ozone (O3), asbestos, fine particulate matter (PM2.5), and volatile organic compounds (VOCs) were target pollutants. As a result, none of the rooms' concentration of CO, NO2, O3, Rn, asbestos, and VOCs exceeded the Korean Standard of Indoor Air Quality, while some rooms' concentration of other pollutants exceeded the KSIAQ. Statutory facilities had lower indoor pollutant concentrations and exceedance rates due to efficient ventilation system and the lack of kitchen location within the building, as opposed to non-statutory facilities. In addition, the VOCs had significant differences depending on the number of years it took for the building to be constructed. To reduce the indoor pollutants concentrations, efficient ventilation systems should be installed while controlling the main sources of pollutants. In addition, construction and remodeling using eco-friendly materials should be considered. The standards of IAQ for small size facilities should be included in the KSIAQ in the future.
Subject(s)
Air Pollutants , Air Pollution, Indoor , Environmental Monitoring , Humans , Particulate Matter , Republic of Korea , Seoul , Vulnerable PopulationsABSTRACT
The present study investigated the optimum blending condition of protected fat, choline and yeast culture for lowering of rumen temperature. The Box Benken experimental design, a fractional factorial arrangement, and response surface methodology were employed. The optimum blending condition was determined using the rumen simulated in vitro fermentation. An additive formulated on the optimum condition contained 50% of protected fat, 25% of yeast culture, 5% of choline, 7% of organic zinc, 6.5% of cinnamon, and 6.5% of stevioside. The feed additive was supplemented at a rate of 0.1% of diet (orchard grass:concentrate, 3:7) and compared with a control which had no additive. The treatment resulted in lower volatile fatty acid (VFA) concentration and biogas than the control. To investigate the effect of the optimized additive and feed energy levels on rumen and rectal temperatures, four rumen cannulated Hanwoo (Korean native beef breed) steers were in a 4×4 Latin square design. Energy levels were varied to low and high by altering the ratio of forage to concentrate in diet: low energy (6:4) and high energy (4:6). The additive was added at a rate of 0.1% of the diet. The following parameters were measured; feed intake, rumen and rectal temperatures, ruminal pH and VFA concentration. This study was conducted in an environmentally controlled house with temperature set at 30°C and relative humidity levels of 70%. Steers were housed individually in raised crates to facilitate collection of urine and feces. The adaptation period was for 14 days, 2 days for sampling and 7 days for resting the animals. The additive significantly reduced both rumen (p<0.01) and rectal temperatures (p<0.001) without depressed feed intake. There were interactions (p<0.01) between energy level and additive on ruminal temperature. Neither additive nor energy level had an effect on total VFA concentration. The additive however, significantly increased (p<0.01) propionate and subsequently had lower acetate:propionate (A/P) ratios than non-additive supplementation. High concentrate diets had significantly lower pH. Interactions between energy and additive were observed (p<0.01) in ammonia nitrogen production. Supplementation of diets with the additive resulted in lower rumen and rectal temperatures, hence the additive showed promise in alleviating undesirable effects of heat stress in cattle.
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BACKGROUND: This study aimed to systematically review case reports documenting rare adverse events in patients with small cell lung cancer (SCLC) following the administration of immune checkpoint inhibitors (ICIs). METHODS: A systematic literature review was conducted to identify case reports detailing previously unreported adverse drug reactions to ICIs in patients with SCLC. The scope of the literature reviewed was restricted to case studies on SCLC published up to 31 December 2023. RESULTS: We analyzed twenty-four studies on ICI use for patients with SCLC. There were six reports on atezolizumab, four on durvalumab, and three on adverse events from monotherapy with nivolumab. Reports involving combination treatments were the most frequent, with a total of six, predominantly involving using nivolumab in combination with ipilimumab. Additionally, there was one report each on using pembrolizumab, nofazinilimab, sintilimab, tislelizumab, and toripalimab. We collected detailed information on the clinical course, including patient and disease characteristics, symptoms, treatment for each adverse event, and recovery status. Among the patients included in the case reports, 21 out of 24 (87.5%) had extensive-stage SCLC when initiating ICI therapy, with only 1 patient diagnosed with limited-stage SCLC. Respiratory system adverse events were most common, with seven cases, followed by neurological, endocrinological, and gastroenterological events. Three case reports documented adverse events across multiple systems in a single patient. In most cases, patients showed symptom improvement; however, four studies reported cases where patients either expired without symptom improvement or experienced sequelae. CONCLUSIONS: Efforts to develop reliable biomarkers for predicting irAEs continue, with ongoing research to enhance predictive precision. Immunotherapy presents diverse and unpredictable adverse events, underscoring the need for advanced diagnostic tools and a multidisciplinary approach to improve patient management.
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The effect of conjugated linoleic acid (CLA) feeding on growth performance and fatty acid profiles in thigh meat of broiler chicken was investigated using meta-analysis with a total of 9 studies. Overall effects were calculated by standardized mean differences between treatment (CLA fed) and control using Hedges's adjusted g from fixed and random effect models. Meta-regression was conducted to evaluate the effect of CLA levels. Subgroups in the same study were designated according to used levels of CLA, CP levels or substituted oils in diets. The effects on final body weight, weight gain, feed intake and feed conversion ratio were investigated as growth parameters. Total saturated and unsaturated fatty acid concentrations and C16:0, C18:0, C18:2 and C18:3 concentrations in thigh meat of broiler chicken were used as fatty acid profile parameters. The overall effect of CLA feeding on final weight was negative and it was only significant in fixed effect model (p<0.01). Significantly lower weight gain, feed intake and higher feed conversion ratio compared to control were found (p<0.05). CLA feeding on the overall increased total saturated fatty acid concentration in broilers compared to the control diet (p<0.01). Total unsaturated fatty acid concentration was significantly decreased by CLA feeding (p<0.01). As for individual fatty acid profiles, C16:0, C18:0 and C18:3 were increased and C18:2 was significantly decreased by CLA feeding (p<0.01). In conclusion, CLA was proved not to be beneficial for improving growth performance, whereas it might be supposed that CLA is effective modulating n-6/n-3 fatty acids ratio in thigh meat. However, the economical compensation of the loss from suppressed growth performance and increased saturated fatty acids with the benefit from enhanced n-6/n-3 ratio should be investigated in further studies in order to propose an appropriate use of dietary CLA in the broiler industry.
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The incidence of breast cancer (BC) is increasing in South Korea, and diet is closely related to the high prevalence of BC. The microbiome directly reflects eating habits. In this study, a diagnostic algorithm was developed by analyzing the microbiome patterns of BC. Blood samples were collected from 96 patients with BC and 192 healthy controls. Bacterial extracellular vesicles (EVs) were collected from each blood sample, and next-generation sequencing (NGS) of bacterial EVs was performed. Microbiome analysis of patients with BC and healthy controls identified significantly higher bacterial abundances using EVs in each group and confirmed the receiver operating characteristic (ROC) curves. Using this algorithm, animal experiments were performed to determine which foods affect EV composition. Compared to BC and healthy controls, statistically significant bacterial EVs were selected from both groups, and a receiver operating characteristic (ROC) curve was drawn with a sensitivity of 96.4%, specificity of 100%, and accuracy of 99.6% based on the machine learning method. This algorithm is expected to be applicable to medical practice, such as in health checkup centers. In addition, the results obtained from animal experiments are expected to select and apply foods that have a positive effect on patients with BC.
Subject(s)
Microbiota , Neoplasms , Humans , Biomarkers, Tumor/analysis , ROC Curve , Bacteria , Microbiota/geneticsABSTRACT
Over several decades, the disease pattern of intractable disease has changed from acute infection to chronic disease accompanied by immune and metabolic dysfunction. In addition, scientific evidence has shown that humans are holobionts; of the DNA in humans, 1% is derived from the human genome, and 99% is derived from microbial genomes (the microbiome). Extracellular vesicles (EVs) are lipid bilayer-delimited nanoparticles and key messengers in cell-to-cell communication. Many publications indicate that microbial EVs are both positively and negatively involved in the pathogenesis of various intractable diseases, including inflammatory diseases, metabolic disorders, and cancers. Microbial EVs in feces, blood, and urine show significant differences in their profiles between patients with a particular disease and healthy subjects, demonstrating the potential of microbial EVs as biomarkers for disease diagnosis, especially for assessing disease risk. Furthermore, microbial EV therapy offers a variety of advantages over live biotherapeutics and human cell EV (or exosome) therapy for the treatment of intractable diseases. In summary, microbial EVs are a new tool in medicine, and microbial EV technology might provide us with innovative diagnostic and therapeutic solutions in precision medicine.
Subject(s)
Exosomes , Extracellular Vesicles , Microbiota , Cell Communication , Exosomes/metabolism , Extracellular Vesicles/metabolism , Humans , Precision MedicineABSTRACT
Although mounting evidence suggests that the microbiome has a tremendous influence on intractable disease, the relationship between circulating microbial extracellular vesicles (EVs) and respiratory disease remains unexplored. Here, we developed predictive diagnostic models for COPD, asthma, and lung cancer by applying machine learning to microbial EV metagenomes isolated from patient serum and coded by their accumulated taxonomic hierarchy. All models demonstrated high predictive strength with mean AUC values ranging from 0.93 to 0.99 with various important features at the genus and phylum levels. Application of the clinical models in mice showed that various foods reduced high-fat diet-associated asthma and lung cancer risk, while COPD was minimally affected. In conclusion, this study offers a novel methodology for respiratory disease prediction and highlights the utility of serum microbial EVs as data-rich features for noninvasive diagnosis.
Subject(s)
Asthma , Extracellular Vesicles , Lung Neoplasms , Pulmonary Disease, Chronic Obstructive , Algorithms , Animals , Asthma/diagnosis , Asthma/etiology , Lung Neoplasms/etiology , Machine Learning , Mice , Risk AssessmentABSTRACT
Inflammatory bowel diseases (IBD), including Crohn's disease and ulcerative colitis, are chronic immune-mediated intestinal inflammatory disorders associated with microbial dysbiosis at multiple sites, particularly the gut. Anti-tumor necrosis factor-α (TNF-α) agents are important treatments for IBD. We investigated whether microbiome changes at multiple sites can predict the effectiveness of such treatment in IBD. Stool, saliva, serum, and urine biosamples were collected from 19 IBD patients before (V1) and 3 months after (V2) anti-TNF-α treatment, and 19 healthy subjects (control). Microbiota analysis was performed using extracellular vesicles (EVs; all four sample types) and next-generation sequencing (NGS; stool and saliva). The stool, using NGS analysis, was the only sample type in which α-diversity differed significantly between the IBD and control groups at V1 and V2. Relative to non-responders, responders to anti-TNF-α treatment had significantly higher levels of Firmicutes (phylum), Clostridia (class), and Ruminococcaceae (family) in V1 stool, and Prevotella in V1 saliva. Non-responders had significantly higher V2 serum and urine levels of Lachnospiraceae than responders. Finally, Acidovorax caeni was detected in all V1 sample types in responders, but was not detected in non-responders. Microbiome changes at multiple sites may predict the effectiveness of anti-TNF-α treatment in IBD, warranting further research.
Subject(s)
Colitis, Ulcerative , Gastrointestinal Microbiome , Inflammatory Bowel Diseases , Clostridiales , Dysbiosis , Humans , Inflammatory Bowel Diseases/drug therapy , Saliva , Tumor Necrosis Factor Inhibitors , Tumor Necrosis Factor-alphaABSTRACT
There is increasing evidence supporting the association between gut microbiome composition and mood disorders; however, studies on the circulating microbiome are scarce. This study aimed to analyze the association of the serum microbial DNA composition with depressive and anxiety symptoms in patients with mood disorders. The sera of 69 patients with mood disorders, aged from 19 to 60, were analyzed. Bacterial DNA was isolated from extracellular membrane vesicles and, subsequently, amplified and quantified with specific primers for the V3-V4 hypervariable region of the 16S rDNA gene. Sequence reads were clustered into Operational Taxonomic Units and classified using the SILVA database. There were no significant associations between alpha diversity measures and the total Hamilton depression rating scale (HAM-D) or Beck anxiety inventory (BAI) scores. Only the weighted UniFrac distance was associated with the total HAM-D score (F = 1.57, p = 0.045). The Bacteroidaceae family and Bacteroides genus were negatively associated with the total HAM-D score (ß = - 0.016, p < 0.001, q = 0.08 and ß = - 0.016, p < 0.001, q = 0.15, respectively). The Desulfovibrionaceae family and Clostridiales Family XIII were positively associated with the total BAI score (ß = 1.8 × 10-3, p < 0.001, q = 0.04 and ß = 1.3 × 10-3, p < 0.001, q = 0.24, respectively). Further studies with larger sample sizes and longitudinal designs are warranted.
Subject(s)
Anxiety , Cell-Free Nucleic Acids/blood , DNA, Bacterial , Depression , Mood Disorders/blood , Mood Disorders/psychology , Adult , DNA Barcoding, Taxonomic , Female , Humans , Male , Middle Aged , Mood Disorders/diagnosis , Mood Disorders/etiology , RNA, Ribosomal, 16S , Symptom Assessment , Young AdultABSTRACT
BACKGROUND: : The microbiome is important in the development and progression of breast cancer. This study investigated the effects of microbiome derived from Klebsiella on endocrine therapy of breast cancer using MCF7 cells. The bacterial extracellular vesicles (EVs) that affect endocrine therapy were established through experiments focused on tamoxifen efficacy. METHODS: : The microbiomes of breast cancer patients and healthy controls were analyzed using next-generation sequencing. Among microbiome, Klebsiella was selected as the experimental material for the effect on endocrine therapy in MCF7 cells. MCF7 cells were incubated with tamoxifen in the absence/presence of bacterial EVs derived from Klebsiella pneumoniae and analyzed by quantitative real-time polymerase chain reaction and Western blot. RESULTS: : Microbiome derived from Klebsiella is abundant in breast cancer patients especially luminal A subtype compared to healthy controls. The addition of EVs derived from K pneumoniae enhances the anti-hormonal effects of tamoxifen in MCF7 cells. The increased efficacy of tamoxifen is mediated via Cyclin E2 and p-ERK. CONCLUSION: : Based on experiments, the EVs derived from K pneumoniae are important in hormone therapy on MCF7 cells. This result provides new insight into breast cancer mechanisms and hormone therapy using Klebsiella found in the microbiome.
Subject(s)
Antineoplastic Agents, Hormonal/pharmacology , Biological Products/pharmacology , Breast Neoplasms/drug therapy , Extracellular Vesicles/metabolism , Gastrointestinal Microbiome , Antineoplastic Agents, Hormonal/therapeutic use , Biological Products/therapeutic use , Breast Neoplasms/pathology , Cell Survival/drug effects , Drug Screening Assays, Antitumor , Drug Synergism , Female , Humans , Klebsiella pneumoniae/cytology , Klebsiella pneumoniae/metabolism , MCF-7 Cells , Tamoxifen/pharmacology , Tamoxifen/therapeutic use , Urine/cytologyABSTRACT
BACKGROUND: Severe alcoholic hepatitis (AH) is the most aggressive form of alcohol-related liver disease with high mortality. The microbiome is an emerging therapeutic target in alcohol-related liver disease. AIMS: To investigate the microbiome composition in patients with severe AH, and to determine microbiome recovery after rifaximin treatment in gut bacteria and bacteria derived-extracellular vesicles. METHODS: We enrolled 24 patients with severe AH and 24 healthy controls. Additional faecal samples were collected after 4 weeks in 8 patients with severe AH who completed rifaximin treatment. Treatment response was defined based on Lille score model after 7 days of treatment. Metagenomic profiling was performed using 16S ribosomal RNA amplicon sequencing. RESULTS: Faecal microbiomes of patients with severe AH had lower alpha diversity and higher beta diversity than those of healthy controls in both gut bacteria and extracellular vesicles. Bacilli, Lactobacillales and Veillonella were significantly increased in the gut bacteria of patients with severe AH, and Veillonella, Veillonella parvula group and Lactobacillales were significantly increased in the extracellular vesicles of patients with severe AH. Eubacterium_g23, Oscillibacter and Clostridiales decreased in the gut bacteria of patients with severe AH, and Eubacterium_g23, Oscillibacter and Christensenellaceae decreased in the extracellular vesicles of patients with severe AH. After rifaximin treatment, 17 taxa in the gut bacteria and 23 taxa in extracellular vesicles were significantly restored in patients with severe AH. In common, Veillonella and Veillonella parvula group increased in patients with severe AH and decreased after rifaximin treatment, and Prevotella and Prevotellaceae decreased in patients with severe AH and increased after rifaximin treatment. Treatment non-responders showed a significantly lower abundance of Prevotella at baseline than did treatment responders. CONCLUSION: Dysbiosis was confirmed in severe AH but was alleviated by rifaximin treatment. Taxa associated with severe AH can be candidate biomarkers or therapeutic targets.
Subject(s)
Gastrointestinal Microbiome , Hepatitis, Alcoholic , Microbiota , Biomarkers , Dysbiosis , Hepatitis, Alcoholic/diagnosis , Hepatitis, Alcoholic/drug therapy , Humans , VeillonellaABSTRACT
The human microbiota comprises trillions of microbes, and the relationship between cancer and microbiota is very complex. The impact of fecal microbiota alterations on colorectal cancer (CRC) pathogenesis is emerging. This study analyzed changes in the microbial composition in CRC subjects with both fecal microbiota and gut microbe-derived extracellular vesicles (EVs). From August 2017 to August 2018, 70 CRC patients and 158 control subjects were enrolled in the study. Metagenomic profiling of fecal microbiota and gut microbe-derived EVs in stool was performed using 16S ribosomal DNA sequencing. Relative abundance, evenness, and diversity in both the gut microbiota and gut microbe-derived EVs were analyzed. Additionally, microbial composition changes according to the stage and location of CRC were analyzed. Microbial composition was significantly changed in CRC subjects compared to control subjects, with evenness and diversity significantly lower in the fecal microbiota of CRC subjects. Gut microbe-derived EVs of stool demonstrated significant differences in the microbial composition, evenness, and diversity in CRC subjects compared to the control subjects. Additionally, microbial composition, evenness, and diversity significantly changed in late CRC subjects compared to early CRC subjects with both fecal microbiota and gut microbe-derived EVs. Alistipes-derived EVs could be novel biomarkers for diagnosing CRC and predicting CRC stages. Ruminococcus 2-derived EVs significantly decreased in distal CRC subjects than in proximal CRC subjects. Gut microbe-derived EVs in CRC had a distinct microbial composition compared to the controls. Profiling of microbe-derived EVs may offer a novel biomarker for detecting and predicting CRC prognosis.
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IoT-based monitoring devices can transmit real-time and long-term thermal environment data, enabling innovative conversion for the evaluation and management of the indoor thermal environment. However, long-term indoor thermal measurements using IoT-based devices to investigate health effects have rarely been conducted. Using apartments in Seoul as a case study, we conducted long-term monitoring of thermal environmental using IoT-based real-time wireless sensors. We measured the temperature, relative humidity (RH), and CO2 in the kitchen, living room, and bedrooms of each household over one year. In addition, in one of the houses, velocity and globe temperatures were measured for multiple summer and autumn seasons. Results of our present study indicated that outdoor temperature is an important influencing factor of indoor thermal environment and indoor RH is a good indicator of residents' lifestyle. Our findings highlighted the need for temperature management in summer, RH management in winter, and kitchen thermal environment management during summer and tropical nights. This study suggested that IoT devices are a potential approach for evaluating personal exposure to indoor thermal environmental risks. In addition, long-term monitoring and analysis is an efficient approach for analyzing complex indoor thermal environments and is a viable method for application in healthcare.
Subject(s)
Air Pollution, Indoor , Data Science , Air Pollution, Indoor/analysis , Environmental Monitoring , Housing , Humans , Humidity , Republic of Korea , Seasons , Seoul , TemperatureABSTRACT
As electronic devices and mainboards become smaller, the need for thermal conductive materials having excellent internal heat dissipation is increasing. In this study, nano thermal grease was prepared by mixing in copper nanopowder, which is used as a heat transfer medium in thermal grease, which is a kind of thermal conductive material, with silicon oil. In addition, copper powder was mixed with graphene and alumina, respectively, and the thermal conductivity performance was compared. As a result, the thermal conductivity improved by 4.5 W/m·k over the silicon base, and the upward trend of thermal conductivity increased steadily up to 15 vol. %, and the increasing trend decreased after 20 vol. %. In addition, the increased rate of thermal conductivity from 0 to 5 vol. % and 10 to 15 vol. % was the largest.
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The relationship between ambient particulate matter exposure and health has been well established. Ultrafine particles (UFP) with a diameter of 100 nm or less are known to increase pulmonary disease risk. Biological factors in dust containing UFP can cause severe inflammatory reactions. Pulmonary diseases develop primarily as a result of chronic inflammation caused by immune dysfunction. Thus, this review focuses on the adverse pulmonary effects of biological UFP, principally lipopolysaccharide (LPS), and bacterial extracellular vesicles (EVs), in indoor dust and the pathophysiological mechanisms involved in the development of chronic pulmonary diseases. The impact of LPS-induced pulmonary inflammation is based primarily on the amount of inhaled LPS. When relatively low levels of LPS are inhaled, a cascade of immune responses leads to Th2 cell induction, and IL-5 and IL-13 released by Th2 cells contributes to asthma development. Conversely, exposure to high levels of LPS induces a Th17 cell response, leading to increased production of IL-17, which is associated with asthma, COPD, and lung cancer incidence. Responses to bacterial EV exposure can similarly be broadly divided based on whether one of two mechanisms, either intracellular or extracellular, is activated, which depends on the type of the parent cell. Extracellular bacteria-derived EVs can cause neutrophilic inflammation via Th17 cell induction, which is associated with asthma, emphysema, COPD, and lung cancer. On the other hand, intracellular bacteria-derived EVs lead to mononuclear inflammation via Th1 cell induction, which increases the risk of emphysema. In conclusion, future measures should focus on the overall reduction of LPS sources in addition to the improvement of the balance of inhaled bacterial EVs in the indoor environment to minimize pulmonary disease risk.
Subject(s)
Lung/drug effects , Particulate Matter/adverse effects , Pneumonia/chemically induced , Pulmonary Emphysema/chemically induced , Animals , Bacteria , Dust , Humans , Th1 Cells/drug effects , Th17 Cells/drug effectsABSTRACT
The human microbiome has been recently associated with human health and disease. Brain tumors (BTs) are a particularly difficult condition to directly link to the microbiome, as microorganisms cannot generally cross the blood-brain barrier (BBB). However, some nanosized extracellular vesicles (EVs) released from microorganisms can cross the BBB and enter the brain. Therefore, we conducted metagenomic analysis of microbial EVs in both serum (152 BT patients and 198 healthy controls (HC)) and brain tissue (5 BT patients and 5 HC) samples based on the V3-V4 regions of 16S rDNA. We then developed diagnostic models through logistic regression and machine learning algorithms using serum EV metagenomic data to assess the ability of various dietary supplements to reduce BT risk in vivo. Models incorporating the stepwise method and the linear discriminant analysis effect size (LEfSe) method yielded 12 and 29 significant genera as potential biomarkers, respectively. Models using the selected biomarkers yielded areas under the curves (AUCs) >0.93, and the model using machine learning resulted in an AUC of 0.99. In addition, Dialister and [Eubacterium] rectale were significantly lower in both blood and tissue samples of BT patients than in those of HCs. In vivo tests showed that BT risk was decreased through the addition of sorghum, brown rice oil, and garlic but conversely increased by the addition of bellflower and pear. In conclusion, serum EV metagenomics shows promise as a rich data source for highly accurate detection of BT risk, and several foods have potential for mitigating BT risk.
Subject(s)
Brain Neoplasms/diagnosis , Brain Neoplasms/metabolism , Extracellular Vesicles/metabolism , Extracellular Vesicles/microbiology , Microbiota , Aged , Animals , Biomarkers, Tumor , Case-Control Studies , Computational Biology , Diet , Female , Humans , Machine Learning , Male , Metagenome , Metagenomics/methods , Mice , Middle Aged , ROC CurveABSTRACT
Different patterns of bacterial communities have been reported in the airways and gastrointestinal tract of asthmatics when compared to healthy controls. However, the blood microbiome of asthmatics is yet to be investigated. Therefore, we aimed to determine whether a distinct serum microbiome is observed in asthmatics by metagenomic analysis of serum extracellular vesicles (EVs). We obtained serum from 190 adults with asthma and 260 healthy controls, from which EVs were isolated and analyzed. The bacterial composition of asthmatics was significantly different from that of healthy controls. Chao 1 index was significantly higher in the asthma group, while Shannon and Simpson indices were higher in the control group. At the phylum level, Bacteroidetes was more abundant in asthmatics, while Actinobacter, Verrucomicrobia, and Cyanobacteria were more abundant in healthy controls. At the genus level, 24 bacterial genera showed differences in relative abundance between asthmatics and controls, with linear discriminant analysis scores greater than 3. Further, in a diagnostic model based on these differences, a high predictive value with a sensitivity of 0.92 and a specificity of 0.93 was observed. In conclusion, we demonstrated distinct blood microbiome in asthma indicating the role of microbiome as a potential diagnostic marker of asthma.
Subject(s)
Asthma/diagnosis , Bacteria/genetics , DNA, Bacterial/blood , Extracellular Vesicles/microbiology , Metagenome , Microbiota/genetics , Asthma/blood , Asthma/microbiology , Bacteria/classification , Bacteria/isolation & purification , Case-Control Studies , DNA, Bacterial/genetics , Female , Humans , Male , Middle AgedABSTRACT
We aimed to develop a diagnostic model identifying ovarian cancer (OC) from benign ovarian tumors using metagenomic data from serum microbe-derived extracellular vesicles (EVs). We obtained serum samples from 166 patients with pathologically confirmed OC and 76 patients with benign ovarian tumors. For model construction and validation, samples were randomly divided into training and test sets in the ratio 2:1. Isolation of microbial EVs from serum samples of the patients and 16S rDNA amplicon sequencing were carried out. Metagenomic and clinicopathologic data-based OC diagnostic models were constructed in the training set and then validated in the test set. There were significant differences in the metagenomic profiles between the OC and benign ovarian tumor groups; specifically, genus Acinetobacter was significantly more abundant in the OC group. More importantly, Acinetobacter was the only common genus identified by seven different statistical analysis methods. Among the various metagenomic and clinicopathologic data-based OC diagnostic models, the model consisting of age, serum CA-125 levels, and relative abundance of Acinetobacter showed the best diagnostic performance with the area under the receiver operating characteristic curve of 0.898 and 0.846 in the training and test sets, respectively. Thus, our findings establish a metagenomic analysis of serum microbe-derived EVs as a potential tool for the diagnosis of OC.