A nationwide case-referent study on elevated risks of adenocarcinoma lung cancer by long-term PM2.5 exposure in Taiwan since 1997.

BACKGROUND: The effects of long-term PM2.5 exposures since 1968 on adenocarcinoma lung cancer (AdLC) were not studied before. METHODS: This case-referent study used nationwide cancer registry data since 1997 and air pollution data since 1968 in Taiwan to estimate risks of 30-year PM2.5 exposures on AdLC. Cases were all AdLC, while references were all non-AdLC. Individuals' 30-year PM2.5 exposures were estimated by PM2.5 levels at their residence for 30 years prior their diagnosis dates. We applied multiple logistic regression analyses to estimate PM2.5 exposures on incidence rate ratios (IRRs) between cases and references, adjusting for sex, age, smoking, cancer stage, and EGFR mutation. RESULTS: Elevation in annual ambient PM2.5 concentrations since 1968 were associated with increase in annual age-adjusted AdLC incidence since 1997. AdLC incidences were higher among females, nonsmokers, the elderly aged above 65, cases of stages IIIB to IV, and EGFR mutation. Study subjects' PM2.5 exposures averaged at 33.7±7.4 µg/m3 with 162±130 high PM2.5 pollution days over 30 years. Multiple logistic models showed an increase in 10 µg/m3 of PM2.5 exposures were significantly associated with 1.044 of IRR between all AdLC and all non-AdLC cases during 2011-2020. Our models also showed that females and nonsmokers and adults less than 65 years had higher IRRs than their respective counterparts. Restricted analyses showed similar effects of PM2.5 exposures on IRRs between stage 0-IIIA and IIIB-IV cases and between EGFR+ and EGFR- cases. CONCLUSIONS: Long-term exposures to PM2.5 over 30 years were associated with elevated risks of AdLC against non-AdLC, regardless of gender, age, smoking status, cancer stage, or EGFR mutation.

Combining wireless radar sleep monitoring device with deep machine learning techniques to assess obstructive sleep apnea severity.

STUDY OBJECTIVES: The gold standard for diagnosing obstructive sleep apnea (OSA) is polysomnography (PSG). However, PSG is a time-consuming method with clinical limitations. This study aimed to create a wireless radar framework to screen the likelihood of two levels of OSA severity (i.e., moderate-to-severe and severe OSA) in accordance with clinical practice standards. METHODS: We conducted a prospective, simultaneous study using the wireless radar system and PSG in a Northern Taiwan sleep center, involving 196 patients. The wireless radar sleep monitor, incorporating hybrid models such as deep neural decision trees, estimated the respiratory disturbance index relative to the total sleep time established by PSG (RDIPSG_TST), by analyzing continuous-wave signals indicative of breathing patterns. Analyses were performed to examine the correlation and agreement between the RDIPSG_TST and apnea-hypopnea index (AHI), results obtained through PSG. Cut-off thresholds for RDIPSG_TST were determined using Youden's index, and multiclass classification was performed, after which the results were compared. RESULTS: A strong correlation (ρ = 0.91) and agreement (average difference of 0.59 events/h) between AHI and RDIPSG_TST were identified. In terms of the agreement between the two devices, the average difference between PSG-based AHI and radar-based RDIPSG_TST was 0.59 events/h, while 187 out of 196 cases (95.41%) fell within the 95% confidence interval of differences. A moderate-to-severe OSA model achieved an accuracy of 90.3% (cut-off threshold for RDIPSG_TST: 19.2 events/h). A severe OSA model achieved an accuracy of 92.4% (cut-off threshold for RDIPSG_TST: 28.86 events/h). The mean accuracy of multiclass classification performance using these cut-off thresholds was 83.7%. CONCLUSIONS: The wireless-radar-based sleep monitoring device, with cut-off thresholds, can provide rapid OSA screening with acceptable accuracy, and also alleviate the burden on PSG capacity. However, to independently apply this framework, the function of determining the radar-based total sleep time requires further optimizations and verification in future work.

Risk, Predictive, and Preventive Factors for Noninfectious Ventriculitis and External Ventricular Drain Infection.

BACKGROUND: External ventricular drain (EVD) is used for monitoring intracranial pressure or diverting cerebrospinal fluid. However, confirmation of an infection is not immediate and requires obtaining culture results, often leading to the excessive use of antibiotics. This study aimed to compare noninfectious ventriculitis and EVD infection in terms of the risk factors, predictors, prognosis, and effectiveness of care bundle interventions. METHODS: This retrospective study was conducted at a medical center with 1,006 beds in northern Taiwan between January 2018 and July 2022. Standard EVD insertion protocols and care bundles have been implemented since 2018, along with the initiation of chlorhexidine. RESULTS: In total, 742 EVD cases were identified. Noninfectious ventriculitis typically presents with fever approximately 8 days following EVD placement, whereas EVD infection typically manifests as fever after 20 days. Aneurysmal subarachnoid hemorrhage was strongly associated with the development of noninfectious ventriculitis (adjusted odds ratio [OR] 2.6, 95% confidence interval [CI] 1.5-4.4). Alcoholism (adjusted OR 3.5, 95% CI 1.1-12.3) and arteriovenous malformation (adjusted OR 13.1, 95% CI 2.9-58.2) significantly increased the risk of EVD infection. The EVD infection rate significantly decreased from 3.6% (14 of 446) to 1.0% (3 of 219) (p = 0.03) after the implementation of chlorhexidine gluconate bathing. CONCLUSIONS: Aneurysmal subarachnoid hemorrhage or fever with neuroinflammation within 2 weeks of EVD placement is indicative of a higher likelihood of noninfectious ventriculitis. Conversely, patients with arteriovenous malformation, alcoholism, or fever with neuroinflammation occurring after more than 3 weeks of EVD placement are more likely to necessitate antibiotic treatment for EVD infection. Chlorhexidine gluconate bathing decreases EVD infection.

Prediction value of neutrophil and eosinophil count at risk of COPD exacerbation.

INTRODUCTION: Predicting acute exacerbations (AEs) in chronic obstructive pulmonary disease (COPD) is crucial. This study aimed to identify blood biomarkers for predicting COPD exacerbations by inflammatory phenotypes. MATERIALS AND METHODS: We analyzed blood cell counts and clinical outcomes in 340 COPD patients aged 20-90 years. Patients were categorized into eosinophilic inflammation (EOCOPD) and non-eosinophilic inflammation (N-EOCOPD) groups. Blood cell counts, eosinophil-to-lymphocyte ratio (ELR), neutrophil-to-lymphocyte ratio (NLR) and neutrophil-to-eosinophil ratio (NER) were calculated. Linear and logistic regression models assessed relationships between health outcomes and blood cell counts. RESULTS: EOCOPD patients had distinct characteristics compared to N-EOCOPD patients. Increased neutrophil % and decreased lymphocyte % were associated with reduced pulmonary function, worse quality of life and more exacerbations, but they did not show statistical significance after adjusting by age, sex, BMI, smoking status, FEV1% and patient's medication. Subgroup analysis revealed a 1.372-fold increase in the OR of AE for every 1 unit increase in NLR in EOCOPD patients (p < .05). In N-EOCOPD patients, every 1% increase in blood eosinophil decreased the risk of exacerbation by 59.6%. CONCLUSIONS: Our study indicates that distinct white blood cell profiles in COPD patients, with or without eosinophilic inflammation, can help assess the risk of AE in clinical settings.

Association between air pollutant exposure, body water distribution and sleep disorder indices in individuals with low-arousal-threshold obstructive sleep apnoea.

BACKGROUND: Air pollution may alter body water distribution, it may also be linked to low-arousal-threshold obstructive sleep apnoea (low-ArTH OSA). Here, we explored the mediation effects of air pollution on body water distribution and low-ArTH OSA manifestations. METHODS: In this retrospective study, we obtained sleep centre data from healthy participants and patients with low-ArTH OSA (N=1924) in northern Taiwan. Air pollutant exposure at different time intervals (1, 3, 6 and 12 months) was estimated using the nearest station estimation method, and government air-quality data were also obtained. Regression models were used to assess the associations of estimated exposure, sleep disorder indices and body water distribution with the risk of low-ArTH OSA. Mediation analysis was performed to explore the relationships between air pollution, body water distribution and sleep disorder indices. RESULTS: First, exposure to particulate matter (PM) with a diameter of ≤10 µm (PM10) for 1 and 3 months and exposure to PM with a diameter of ≤2.5 µm (PM2.5) for 3 months were significantly associated with the Apnoea-Hypopnoea Index (AHI), Oxygen Desaturation Index (ODI), Arousal Index (ArI) and intracellular-to-extracellular water ratio (I-E water ratio). Significant associations were observed between the risk of low-ArTH OSA and 1- month exposure to PM10 (OR 1.42, 95% CI 1.09 to 1.84), PM2.5 (OR 1.33, 95% CI 1.02 to 1.74) and ozone (OR 1.27, 95% CI 1.01 to 1.6). I-E water ratio alternation caused by 1-month exposure to PM10 and 3-month exposure to PM2.5 and PM10 had partial mediation effects on AHI and ODI. CONCLUSION: Air pollution can directly increase sleep disorder indices (AHI, ODI and ArI) and alter body water distribution, thus mediating the risk of low-ArTH OSA.

Machine learning approaches for predicting sleep arousal response based on heart rate variability, oxygen saturation, and body profiles.

Objective: Obstructive sleep apnea is a global health concern, and several tools have been developed to screen its severity. However, most tools focus on respiratory events instead of sleep arousal, which can also affect sleep efficiency. This study employed easy-to-measure parameters-namely heart rate variability, oxygen saturation, and body profiles-to predict arousal occurrence. Methods: Body profiles and polysomnography recordings were collected from 659 patients. Continuous heart rate variability and oximetry measurements were performed and then labeled based on the presence of sleep arousal. The dataset, comprising five body profiles, mean heart rate, six heart rate variability, and five oximetry variables, was then split into 80% training/validation and 20% testing datasets. Eight machine learning approaches were employed. The model with the highest accuracy, area under the receiver operating characteristic curve, and area under the precision recall curve values in the training/validation dataset was applied to the testing dataset and to determine feature importance. Results: InceptionTime, which exhibited superior performance in predicting sleep arousal in the training dataset, was used to classify the testing dataset and explore feature importance. In the testing dataset, InceptionTime achieved an accuracy of 76.21%, an area under the receiver operating characteristic curve of 84.33%, and an area under the precision recall curve of 86.28%. The standard deviations of time intervals between successive normal heartbeats and the square roots of the means of the squares of successive differences between normal heartbeats were predominant predictors of arousal occurrence. Conclusions: The established models can be considered for screening sleep arousal occurrence or integrated in wearable devices for home-based sleep examination.

Associations between air pollution, intracellular-to-extracellular water distribution, and obstructive sleep apnea manifestations.

Background: Exposure to air pollution may be a risk factor for obstructive sleep apnea (OSA) because air pollution may alter body water distribution and aggravate OSA manifestations. Objectives: This study aimed to investigate the mediating effects of air pollution on the exacerbation of OSA severity through body water distribution. Methods: This retrospective study analyzed body composition and polysomnographic data collected from a sleep center in Northern Taiwan. Air pollution exposure was estimated using an adjusted nearest method, registered residential addresses, and data from the databases of government air quality motioning stations. Next, regression models were employed to determine the associations between estimated air pollution exposure levels (exposure for 1, 3, 6, and 12 months), OSA manifestations (sleep-disordered breathing indices and respiratory event duration), and body fluid parameters (total body water and body water distribution). The association between air pollution and OSA risk was determined. Results: Significant associations between OSA manifestations and short-term (1 month) exposure to PM2.5 and PM10 were identified. Similarly, significant associations were identified among total body water and body water distribution (intracellular-to-extracellular body water distribution), short-term (1 month) exposure to PM2.5 and PM10, and medium-term (3 months) exposure to PM10. Body water distribution might be a mediator that aggravates OSA manifestations, and short-term exposure to PM2.5 and PM10 may be a risk factor for OSA. Conclusion: Because exposure to PM2.5 and PM10 may be a risk factor for OSA that exacerbates OSA manifestations and exposure to particulate pollutants may affect OSA manifestations or alter body water distribution to affect OSA manifestations, mitigating exposure to particulate pollutants may improve OSA manifestations and reduce the risk of OSA. Furthermore, this study elucidated the potential mechanisms underlying the relationship between air pollution, body fluid parameters, and OSA severity.

Therapeutic hypothermia in patients after cardiac arrest: A systematic review and meta-analysis of randomized controlled trials.

OBJECTIVE: Targeted temperature management (TTM) with therapeutic hypothermia (TH) has been used to improve neurological outcomes in patients after cardiac arrest; however, several trials have reported conflicting results regarding its effectiveness. This systematic review and meta-analysis assessed whether TH was associated with better survival and neurological outcomes after cardiac arrest. METHOD: We searched online databases for relevant studies published before May 2023. Randomized controlled trials (RCTs) comparing TH and normothermia in post-cardiac-arrest patients were selected. Neurological outcomes and all-cause mortality were assessed as the primary and secondary outcomes, respectively. A subgroup analysis according to initial electrocardiography (ECG) rhythm was performed. RESULT: Nine RCTs (4058 patients) were included. The neurological prognosis was significantly better in patients with an initial shockable rhythm after cardiac arrest (RR = 0.87, 95% confidence interval [CI] = 0.76-0.99, P = 0.04), especially in those with earlier TH initiation (<120 min) and prolonged TH duration (≥24 h). However, the mortality rate after TH was not lower than that after normothermia (RR = 0.91, 95% CI = 0.79-1.05). In patients with an initial nonshockable rhythm, TH did not provide significantly more neurological or survival benefits (RR = 0.98, 95% CI = 0.93-1.03 and RR = 1.00, 95% CI = 0.95-1.05, respectively). CONCLUSION: Current evidence with a moderate level of certainty suggests that TH has potential neurological benefits for patients with an initial shockable rhythm after cardiac arrest, especially in those with faster TH initiation and longer TH maintenance.

Association of Low Arousal Threshold Obstructive Sleep Apnea Manifestations with Body Fat and Water Distribution.

Obstructive sleep apnea (OSA) with a low arousal threshold (low-ArTH) phenotype can cause minor respiratory events that exacerbate sleep fragmentation. Although anthropometric features may affect the risk of low-ArTH OSA, the associations and underlying mechanisms require further investigation. This study investigated the relationships of body fat and water distribution with polysomnography parameters by using data from a sleep center database. The derived data were classified as those for low-ArTH in accordance with criteria that considered oximetry and the frequency and type fraction of respiratory events and analyzed using mean comparison and regression approaches. The low-ArTH group members (n = 1850) were significantly older and had a higher visceral fat level, body fat percentage, trunk-to-limb fat ratio, and extracellular-to-intracellular (E-I) water ratio compared with the non-OSA group members (n = 368). Significant associations of body fat percentage (odds ratio [OR]: 1.58, 95% confident interval [CI]: 1.08 to 2.3, p < 0.05), trunk-to-limb fat ratio (OR: 1.22, 95% CI: 1.04 to 1.43, p < 0.05), and E-I water ratio (OR: 1.32, 95% CI: 1.08 to 1.62, p < 0.01) with the risk of low-ArTH OSA were noted after adjustments for sex, age, and body mass index. These observations suggest that increased truncal adiposity and extracellular water are associated with a higher risk of low-ArTH OSA.

Impact of lifetime air pollution exposure patterns on the risk of chronic disease.

Long-term exposure to air pollution can lead to cardiovascular disease, metabolic syndrome, and chronic respiratory disease. However, from a lifetime perspective, the critical period of air pollution exposure in terms of health risk is unknown. This study aimed to evaluate the impact of air pollution exposure at different life stages. The study participants were recruited from community centers in Northern Taiwan between October 2018 and April 2021. Their annual averages for fine particulate matter (PM2.5) exposure were derived from a national visibility database. Lifetime PM2.5 exposures were determined using residential address information and were separated into three stages (<20, 20-40, and >40 years). We employed exponentially weighted moving averages, applying different weights to the aforementioned life stages to simulate various weighting distribution patterns. Regression models were implemented to examine associations between weighting distributions and disease risk. We applied a random forest model to compare the relative importance of the three exposure life stages. We also compared model performance by evaluating the accuracy and F1 scores (the harmonic mean of precision and recall) of late-stage (>40 years) and lifetime exposure models. Models with 89% weighting on late-stage exposure showed significant associations between PM2.5 exposure and metabolic syndrome, hypertension, diabetes, and cardiovascular disease, but not gout or osteoarthritis. Lifetime exposure models showed higher precision, accuracy, and F1 scores for metabolic syndrome, hypertension, diabetes, and cardiovascular disease, whereas late-stage models showed lower performance metrics for these outcomes. We conclude that exposure to high-level PM2.5 after 40 years of age may increase the risk of metabolic syndrome, hypertension, diabetes, and cardiovascular disease. However, models considering lifetime exposure showed higher precision, accuracy, and F1 scores and lower equal error rates than models incorporating only late-stage exposures. Future studies regarding long-term air pollution modelling are required considering lifelong exposure pattern. .1.

Machine learning model for aberrant driving behaviour prediction using heart rate variability: a pilot study involving highway bus drivers.

Objectives. Current approaches via physiological features detecting aberrant driving behaviour (ADB), including speeding, abrupt steering, hard braking and aggressive acceleration, are developing. This study proposes using machine learning approaches incorporating heart rate variability (HRV) parameters to predict ADB occurrence. Methods. Naturalistic driving data of 10 highway bus drivers in Taiwan from their daily routes were collected for 4 consecutive days. Their driving behaviours and physiological data during a driving task were determined using a navigation mobile application and heart rate watch. Participants' self-reported data on sleep, driving-related experience, open-source data on weather and the traffic congestion level were obtained. Five machine learning models - logistic regression, random forest, naive Bayes, support vector machine and gated recurrent unit (GRU) - were employed to predict ADBs. Results. Most drivers with ADB had low sleep efficiency (≤80%), with significantly higher scores in driver behaviour questionnaire subcategories of lapses and errors and in the Karolinska sleepiness scale than those without ADBs. Moreover, HRV parameters were significantly different between baseline and pre-ADB event measurements. GRU had the highest accuracy (81.16-84.22%). Conclusions. Sleep deficit may be related to the increased fatigue level and ADB occurrence predicted from HRV-based models among bus drivers.

Association of air pollution exposure with exercise-induced oxygen desaturation in COPD.

BACKGROUND: There is a link between exposure to air pollution and the increased prevalence of chronic obstructive pulmonary disease (COPD) and declining pulmonary function, but the association with O2 desaturation during exercise in COPD patients with emphysema is unclear. Our aims were to estimate the prevalence of O2 desaturation during exercise in patients with COPD, and determine the association of exposure to air pollution with exercise-induced desaturation (EID), the degree of emphysema, and dynamic hyperinflation (DH). METHODS: We assessed the effects of 10-year prior to the HRCT assessment and 7 days prior to the six-minute walking test exposure to particulate matter with an aerodynamic diameter of < 10 µm (PM10) or of < 2.5 µM (PM2.5), nitrogen dioxide (NO2), and ozone (O3) in patients with emphysema in this retrospective cohort study. EID was defined as a nadir standard pulse oximetry (SpO2) level of < 90% or a delta (△)SpO2 level of ≥ 4%. Ambient air pollutant (PM2.5, PM10, O3, and NO2) data were obtained from Taiwan Environmental Protection Administration (EPA) air-monitoring stations, usually within 10 km to each participant's home address. RESULTS: We recruited 141 subjects with emphysema. 41.1% of patients with emphysema exhibited EID, and patients with EID had more dyspnea, worse lung function, more severe emphysema, more frequent acute exacerbations, managed a shorter walking distance, had DH, and greater long-term exposure to air pollution than those without EID. We observed that levels of 10-year concentrations of PM10, PM2.5, and NO2 were significantly associated with EID, PM10 and PM2.5 were associated with the severity of emphysema, and associated with DH in patients with emphysema. In contrast, short-term exposure did not have any effect on patients. CONCLUSION: Long-term exposure to ambient PM10, PM2.5 and NO2, but not O3, was associated with EID.

lnc-IL7R Expression Reflects Physiological Pulmonary Function and Its Aberration Is a Putative Indicator of COPD.

Despite rapidly evolving pathobiological mechanistic demystification, coupled with advances in diagnostic and therapeutic modalities, chronic obstructive pulmonary disease (COPD) remains a major healthcare and clinical challenge, globally. Further compounded by the dearth of available curative anti-COPD therapy, it is posited that this challenge may not be dissociated from the current lack of actionable COPD pathognomonic molecular biomarkers. There is accruing evidence of the involvement of protracted 'smoldering' inflammation, repeated lung injury, and accelerated lung aging in enhanced predisposition to or progression of COPD. The relatively novel uncharacterized human long noncoding RNA lnc-IL7R (otherwise called LOC100506406) is increasingly designated a negative modulator of inflammation and regulator of cellular stress responses; however, its role in pulmonary physiology and COPD pathogenesis remains largely unclear and underexplored. Our previous work suggested that upregulated lnc-IL7R expression attenuates inflammation following the activation of the toll-like receptor (TLR)-dependent innate immune system, and that the upregulated lnc-IL7R is anti-correlated with concomitant high PM2.5, PM10, and SO2 levels, which is pathognomonic for exacerbated/aggravated COPD in Taiwan. In the present study, our quantitative analysis of lnc-IL7R expression in our COPD cohort (n = 125) showed that the lnc-IL7R level was significantly correlated with physiological pulmonary function and exhibited COPD-based stratification implications (area under the curve, AUC = 0.86, p < 0.001). We found that the lnc-IL7R level correctly identified patients with COPD (sensitivity = 0.83, specificity = 0.83), precisely discriminated those without emphysematous phenotype (sensitivity = 0.48, specificity = 0.89), and its differential expression reflected disease course based on its correlation with the COPD GOLD stage (r = −0.59, p < 0.001), %LAA-950insp (r = −0.30, p = 0.002), total LAA (r = −0.35, p < 0.001), FEV1(%) (r = 0.52, p < 0.001), FVC (%) (r = 0.45, p < 0.001), and post-bronchodilator FEV1/FVC (r = 0.41, p < 0.001). Consistent with other data, our bioinformatics-aided dose−response plot showed that the probability of COPD decreased as lnc-IL7R expression increased, thus, corroborating our posited anti-COPD therapeutic potential of lnc-IL7R. In conclusion, reduced lnc-IL7R expression not only is associated with inflammation in the airway epithelial cells but is indicative of impaired pulmonary function, pathognomonic of COPD, and predictive of an exacerbated/ aggravated COPD phenotype. These data provide new mechanistic insights into the ailing lung and COPD progression, as well as suggest a novel actionable molecular factor that may be exploited as an efficacious therapeutic strategy in patients with COPD.

Lnc-IL7R alleviates PM2.5-mediated cellular senescence and apoptosis through EZH2 recruitment in chronic obstructive pulmonary disease.

BACKGROUND: Long-term exposure to PM2.5 (particulate matter with an aerodynamic diameter of ≤ 2.5 µm) is associated with pulmonary injury and emphysema in patients with chronic obstructive pulmonary disease (COPD). We investigated mechanisms through which the long noncoding RNA lnc-IL7R contributes to cellular damage by inducing oxidative stress in COPD patients exposed to PM2.5. METHODS: Associations of serum lnc-IL7R levels with lung function, emphysema, and previous PM2.5 exposure in COPD patients were analyzed. Reactive oxygen species and lnc-IL7R levels were measured in PM2.5-treated cells. The levels of lnc-IL7R and cellular senescence-associated genes, namely p16INK4a and p21CIP1/WAF1, were determined through lung tissue section staining. The effects of p16INK4a or p21CIP1/WAF1 regulation were examined by performing lnc-IL7R overexpression and knockdown assays. The functions of lnc-IL7R-mediated cell proliferation, cell cycle, senescence, colony formation, and apoptosis were examined in cells treated with PM2.5. Chromatin immunoprecipitation assays were conducted to investigate the epigenetic regulation of p21CIP1/WAF1. RESULTS: Lnc-IL7R levels decreased in COPD patients and were negatively correlated with emphysema or PM2.5 exposure. Lnc-IL7R levels were upregulated in normal lung epithelial cells but not in COPD cells exposed to PM2.5. Lower lnc-IL7R expression in PM2.5-treated cells induced p16INK4a and p21CIP1/WAF1 expression by increasing oxidative stress. Higher lnc-IL7R expression protected against cellular senescence and apoptosis, whereas lower lnc-IL7R expression augmented injury in PM2.5-treated cells. Lnc-IL7R and the enhancer of zeste homolog 2 (EZH2) synergistically suppressed p21CIP1/WAF1 expression through epigenetic modulation. CONCLUSION: Lnc-IL7R attenuates PM2.5-mediated p21CIP1/WAF1 expression through EZH2 recruitment, and its dysfunction may augment cellular injury in COPD.

Associations of the distance-saturation product and low-attenuation area percentage in pulmonary computed tomography with acute exacerbation in patients with chronic obstructive pulmonary disease.

Background: Chronic obstructive pulmonary disease (COPD) has high global health concerns, and previous research proposed various indicators to predict mortality, such as the distance-saturation product (DSP), derived from the 6-min walk test (6MWT), and the low-attenuation area percentage (LAA%) in pulmonary computed tomographic images. However, the feasibility of using these indicators to evaluate the stability of COPD still remains to be investigated. Associations of the DSP and LAA% with other COPD-related clinical parameters are also unknown. This study, thus, aimed to explore these associations. Methods: This retrospective study enrolled 111 patients with COPD from northern Taiwan. Individuals' data we collected included results of a pulmonary function test (PFT), 6MWT, life quality survey [i.e., the modified Medical Research Council (mMRC) scale and COPD assessment test (CAT)], history of acute exacerbation of COPD (AECOPD), and LAA%. Next, the DSP was derived by the distance walked and the lowest oxygen saturation recorded during the 6MWT. In addition, the DSP and clinical phenotype grouping based on clinically significant outcomes by previous study approaches were employed for further investigation (i.e., DSP of 290 m%, LAA% of 20%, and AECOPD frequency of ≥1). Mean comparisons and linear and logistic regression models were utilized to explore associations among the assessed variables. Results: The low-DSP group (<290 m%) had significantly higher values for the mMRC, CAT, AECOPD frequency, and LAA% at different lung volume scales (total, right, and left), whereas it had lower values of the PFT and 6MWT parameters compared to the high-DSP group. Significant associations (with high odds ratios) were observed of the mMRC, CAT, AECOPD frequency, and PFT with low- and high-DSP groupings. Next, the risk of having AECOPD was associated with the mMRC, CAT, DSP, and LAA% (for the total, right, and left lungs). Conclusion: A lower value of the DSP was related to a greater worsening of symptoms, more-frequent exacerbations, poorer pulmonary function, and more-severe emphysema (higher LAA%). These readily determined parameters, including the DSP and LAA%, can serve as indicators for assessing the COPD clinical course and may can serve as a guide to corresponding treatments.

3-Nitrobenzanthrone promotes malignant transformation in human lung epithelial cells through the epiregulin-signaling pathway.

Exposure to environmental and occupational contaminants leads to lung cancer. 3-Nitrobenzanthrone (3-nitro-7H-benz[de]anthracen-7-one, 3-NBA) is a potential carcinogen in ambient air or diesel particulate matter. Studies have revealed that short-term exposure to 3-NBA induces cell death, reactive oxygen species activation, and DNA adduct formation and damage. However, details of the mechanism by which chronic exposure to 3-NBA influences lung carcinogenesis remain largely unknown. In this study, human lung epithelial BEAS-2B cells were continuously exposed to 0-10-µM 3-NBA for 6 months. NanoString analysis was conducted to evaluate gene expression in the cells, revealing that 3-NBA-mediated transformation results in a distinct gene expression signature including carbon cancer metabolism, metastasis, and angiogenesis. Alterations in tumor-promoting genes such as EREG (epiregulin), SOX9, E-cadherin, TWIST, and IL-6 were involved in epithelial cell aggressiveness. Kaplan-Meier plotter analyses indicated that increased EREG and IL-6 expressions in early-stage lung cancer cells are correlated with poor survival. In vivo xenografts on 3-NBA-transformed cells exhibited prominent tumor formation and metastasis. EREG knockout cells exposed to 3-NBA for a short period exhibited high apoptosis and low colony formation. By contrast, overexpression of EREG in 3-NBA-transformed cells markedly activated the PI3K/AKT and MEK/ERK signaling pathways, resulting in tumorigenicity. Furthermore, elevated IL-6 and EREG expressions synergistically led to STAT3 signaling activation, resulting in clonogenic cell survival and migration. Taken together, chronic exposure of human lung epithelial cells to 3-NBA leads to malignant transformation, in which the EREG signaling pathway plays a pivotal mediating role. • Short-term exposure of lung epithelial cells to 3-NBA can lead to ROS production and cell apoptosis. • Long-term chronic exposure to 3-NBA upregulates the levels of tumor-promoting genes such as EREG and IL-6. • Increased EREG expression in 3-NBA-transformed cells markedly contributes to tumorigenesis through PI3K/AKT and MEK/ERK activation and synergistically enhances the IL-6/STAT3 signaling pathway, which promotes tumorigenicity.

Determinants of Pulmonary Emphysema Severity in Taiwanese Patients with Chronic Obstructive Pulmonary Disease: An Integrated Epigenomic and Air Pollutant Analysis.

BACKGROUND: Chronic obstructive pulmonary disease (COPD) continues to pose a therapeutic challenge. This may be connected with its nosological heterogeneity, broad symptomatology spectrum, varying disease course, and therapy response. The last three decades has been characterized by increased understanding of the pathobiology of COPD, with associated advances in diagnostic and therapeutic modalities; however, the identification of pathognomonic biomarkers that determine disease severity, affect disease course, predict clinical outcome, and inform therapeutic strategy remains a work in progress. OBJECTIVES: Hypothesizing that a multi-variable model rather than single variable model may be more pathognomonic of COPD emphysema (COPD-E), the present study explored for disease-associated determinants of disease severity, and treatment success in Taiwanese patients with COPD-E. METHODS: The present single-center, prospective, non-randomized study enrolled 125 patients with COPD and 43 healthy subjects between March 2015 and February 2021. Adopting a multimodal approach, including bioinformatics-aided analyses and geospatial modeling, we performed an integrated analysis of selected epigenetic, clinicopathological, geospatial, and air pollutant variables, coupled with correlative analyses of time-phased changes in pulmonary function indices and COPD-E severity. RESULTS: Our COPD cohort consisted of 10 non-, 57 current-, and 58 ex-smokers (median age = 69 ± 7.76 years). Based on the percentages of low attenuation area below - 950 Hounsfield units (%LAA-950insp), 36 had mild or no emphysema (%LAA-950insp < 6), 22 were moderate emphysema cases (6 ≤ %LAA-950insp < 14), and 9 presented with severe emphysema (%LAA-950insp ≥ 14). We found that BMI, lnc-IL7R, PM2.5, PM10, and SO2 were differentially associated with disease severity, and are highly-specific predictors of COPD progression. Per geospatial levels, areas with high BMI and lnc-IL7R but low PM2.5, PM10, and SO2 were associated with fewer and ameliorated COPD cases, while high PM2.5, PM10, and SO2 but low BMI and lnc-IL7R characterized places with more COPD cases and indicated exacerbation. The prediction pentad effectively differentiates patients with mild/no COPD from moderate/severe COPD cases, (mean AUC = 0.714) and exhibited very high stratification precision (mean AUC = 0.939). CONCLUSION: Combined BMI, lnc-IL7R, PM2.5, PM10, and SO2 levels are optimal classifiers for accurate patient stratification and management triage for COPD in Taiwan. Low BMI, and lnc-IL7R, with concomitant high PM2.5, PM10, and SO2 levels is pathognomonic of exacerbated/aggravated COPD in Taiwan.

Impact of Comorbidities on Beneficial Effect of Lactated Ringers vs. Saline in Sepsis Patients.

Background: Lactated Ringers reduced mortality more than saline in sepsis patients but increased mortality more than saline in traumatic brain injury patients. Method: This prospective cohort study was conducted in a medical intensive care unit (ICU) in central Taiwan. We applied standard sepsis evaluation protocol and identified heart, lung, liver, kidney, and endocrine comorbidities. We also evaluated resuscitation response with central venous pressure, central venous oxygen saturation, and serum lactate level simultaneously. Propensity-score matching and Cox regression were used to estimate mortality. The competing risk model compared the lengths of hospital stays with the subdistribution hazard ratio (SHR). Results: Overall, 938 patients were included in the analysis. The lactated Ringers group had a lower mortality rate (adjusted hazard ratio, 0.59; 95% CI 0.43-0.81) and shorter lengths of hospital stay (SHR, 1.39; 95% C.I. 1.15-1.67) than the saline group; the differences were greater in patients with chronic pulmonary disease and small and non-significant in those with chronic kidney disease, moderate to severe liver disease and cerebral vascular disease. The resuscitation efficacy was the same between fluid types, but serum lactate levels were significantly higher in the lactated Ringers group than in the saline group (0.12 mg/dl/h; 95% C.I.: 0.03, 0.21), especially in chronic liver disease patients. Compared to the saline group, the lactated Ringers group achieved target glucose level earlier in both diabetes and non-diabetes patients. Conclusion: Lactate Ringer's solution provides greater benefits to patients with chronic pulmonary disease than to those with chronic kidney disease, or with moderate to severe liver disease. Comorbidities are important in choosing resuscitation fluid types.

Suppressor of variegation 3-9 homologue 1 impairment and neutrophil-skewed systemic inflammation are associated with comorbidities in COPD.

BACKGROUND: Systemic manifestations and comorbidities are characteristics of chronic obstructive pulmonary disease (COPD) and are probably due to systemic inflammation. The histone methyltransferase SUV39H1 controls the Th1/Th2 balance. We previously reported that reduced SUV39H1 expression contributed to abnormal inflammation in COPD. Here, we aimed to determine whether impaired SUV39H1 expression in COPD patients associated with neutrophilic/eosinophilic inflammation responses and comorbidities. METHODS: A total of 213 COPD patients and 13 healthy controls were recruited from the Shuang Ho Hospital, Taipei Medical University. SUV39H1 levels in peripheral blood mononuclear cells (PBMCs) from 13 healthy and 30 COPD participants were measured by immunoblotting. We classified the patients into two groups based on low (fold change, FC < 0.5) and high SUV39H1 expression (FC ≥ 0.5) compared to normal controls. Clinical outcomes including neutrophil or eosinophil counts associated with SUV39H1-related inflammation were evaluated by Chi square analyses or Mann-Whitney U test. The correlations between the percentage of neutrophils and number of COPD comorbidities or Charlson Comorbidity Index (CCI) scores were performed by Spearman's rank analysis. RESULTS: Low SUV39H1 expression group had high neutrophil counts relative to high SUV39H1expression group. In the COPD cohort, the high comorbidity group (≥ 2 comorbidities) had higher counts of whole white blood cell (WBC) and neutrophil, and lower proportion of eosinophil and eosinophil/neutrophil, as compared with low comorbidity group (0 and 1 comorbidities). The quantity of neutrophils was associated with COPD comorbidities (Spearman's r = 0.388, p < 0.001), but not with CCI scores. We also found that the high comorbidity group had more exacerbations per year compared with low comorbidity group (1.5 vs. 0.9 average exacerbations, p = 0.005). However, there were no significant differences between groups with these non-frequent (0-1 exacerbation) and frequent exacerbations per year (> 1 exacerbation) in numbers of WBC and proportion of neutrophils, eosinophils or eosinophil/neutrophil. Finally, patients with high comorbidities had lower SUV39H1 levels in their PBMCs than did those with low comorbidities. CONCLUSION: Blood neutrophil counts are associated with comorbidities in COPD patients. Impaired SUV39H1 expression in PBMCs from COPD patients are correlated with neutrophilic inflammation and comorbidities.

Combination therapies with thiazolidinediones are associated with a lower risk of acute exacerbations in new-onset COPD patients with advanced diabetic mellitus: a cohort-based case-control study.

BACKGROUND: The effects of oral antihyperglycaemic drugs (OADs) for type 2 diabetes mellitus (T2DM) on the outcomes of co-existing chronic obstructive pulmonary disease (COPD) patients are not well studied. We examined the association of combinational OADs and the risk of acute exacerbations of COPD (AECOPD) in T2DM patients with co-existing COPD. METHODS: A cohort-based case-control study was conducted using data from the National Health Insurance Research Database of Taiwan. Among new-onset COPD-T2DM patients, 65,370 were prescribed metformin and 2nd-line OADs before the date of COPD onset. Each AECOPD case was matched to 4 randomly selected controls according to the propensity score estimated by the patient's baseline characteristics. Conditional logistic regression analysis was performed to estimate the association between AECOPD risk and OAD use. RESULTS: Among COPD-T2DM patients, 3355 AECOPD cases and 13,420 matched controls were selected. Of the patients treated with a double combination of oral OADs (n = 12,916), those treated with sulfonylurea (SU) and thiazolidinediones (TZD) had a lower AECOPD risk than the patients who received metformin (MET) and SU, with an adjusted odds ratio (OR) of 0.69 (95% confidence interval [CI] 0.51-0.94, P = 0.02). Of the patients with a triple combination of oral OADs (n = 3859), we found that those treated with MET, SU and TZD had a lower risk of AECOPD (adjusted OR 0.81 (0.68-0.96, P = 0.01) than a combination of MET, SU and α-glucosidase inhibitors (AGIs) regardless of the level of COPD complexity. CONCLUSION: Combination therapies with TZD were associated with a reduced risk of AECOPD in advanced T2DM patients with co-existing COPD.