Chronic obstructive pulmonary disease attributable to air pollution in the South Asian countries: global burden of disease study 1990 - 2019.

This study investigates the burden of COPD attributable to air pollution in South Asia using data from the Global Burden of Disease Study from 1990 to 2019. Method Data for this study were obtained from the Global Burden of Disease Study 2019. The burden was measured in terms of death, disability-adjusted life years (DALYs), and Years of life lost (YLLs). Results Since 1990, several countries in South Asia registered substantial declines in mortality rates attributed to COPD, ranging from -37.47% in Pakistan to -66.25% in Bangladesh. Similar trends were observed for DALYs and YLLs as well, which have potentially contributed to a considerable decrease in mortality rates at the regional level (-43.13%) compared to a 32.59% decline in Low SDI and 56.87% decline globally. Conclusion Despite significant declines since 1990, the burden of COPD attributable to air pollution reductions in the South Asian region's rates remains alarmingly high.

Feasibility of a problem-solving exercise program based on short physical performance battery for older patients with chronic respiratory diseases: A multicenter, pilot clinical trial.

BACKGROUND: This study aimed to assess the feasibility and safety of a problem-solving exercise program based on the items in the short physical performance battery (SPPB) for older patients with chronic respiratory diseases (CRDs) to inform future randomized controlled trials. METHODS: This was a multicenter, prospective, non-randomized feasibility study. Participants with CRD received an enhancement program based on the SPPB decline items (balance, walk, and/or chair stand) for 4 weeks. The feasibility, safety, and efficacy of the problem-solving exercise program in improving the SPPB score, physical function, and step count (measured using a pedometer) were assessed. RESULTS: Overall, 36 patients were enrolled in this study, and adherence to the exercise program was high (100%). No exercise program-related adverse events were observed. The implementation of the exercise program ranged from 70 to 100%. The mean daily step count increased from 2152 ± 1498 steps during the first week to 2899 ± 1865 steps in the last week (p<0.01). Additionally, the SPPB total score increased from 8.9 ± 1.8 points to 10.7 ± 1.3 points at the end of the program (p<0.001). CONCLUSIONS: The problem-solving exercise program based on SPPB is feasible and safe for older patients with CRDs. However, the effectiveness of this exercise program should be validated in large-scale, randomized-controlled trials in the future. TRIAL REGISTRATION: University Hospital Medical Information Network Center (UMIN-CTR) UMIN: approval number: UMIN000048761.

Recent advances in biosensors detecting biomarkers from exhaled breath and saliva for respiratory disease diagnosis.

The global demand for rapid and non-invasive diagnostic methods for respiratory diseases has significantly intensified due to the wide spread of respiratory infectious diseases. Recent advancements in respiratory disease diagnosis through the analysis of exhaled breath and saliva has attracted great attention all over the world. Among various analytical methods, biosensors can offer non-invasive, efficient, and cost-effective diagnostic capabilities, emerging as promising tools in this area. This review intends to provide a comprehensive overview of various biosensors for the detection of respiratory disease related biomarkers in exhaled breath and saliva. Firstly, the characteristics of exhaled breath and saliva, including their generation, composition, and relevant biomarkers are introduced. Subsequently, the design and application of various biosensors for detecting these biomarkers are presented, along with the innovative materials employed as sensitive components. Different types of biosensors are reviewed, including electrochemical, optical, piezoelectric, semiconductor, and other novel biosensors. At last, the challenges, limitations, and future trends of these biosensors are discussed. It is anticipated that biosensors will play a significant role in respiratory disease diagnosis in the future.

Forecasting severe respiratory disease hospitalizations using machine learning algorithms.

BACKGROUND: Forecasting models predicting trends in hospitalization rates have the potential to inform hospital management during seasonal epidemics of respiratory diseases and the associated surges caused by acute hospital admissions. Hospital bed requirements for elective surgery could be better planned if it were possible to foresee upcoming peaks in severe respiratory illness admissions. Forecasting models can also guide the use of intervention strategies to decrease the spread of respiratory pathogens and thus prevent local health system overload. In this study, we explore the capability of forecasting models to predict the number of hospital admissions in Auckland, New Zealand, within a three-week time horizon. Furthermore, we evaluate probabilistic forecasts and the impact on model performance when integrating laboratory data describing the circulation of respiratory viruses. METHODS: The dataset used for this exploration results from active hospital surveillance, in which the World Health Organization Severe Acute Respiratory Infection (SARI) case definition was consistently used. This research nurse-led surveillance has been implemented in two public hospitals in Auckland and provides a systematic laboratory testing of SARI patients for nine respiratory viruses, including influenza, respiratory syncytial virus, and rhinovirus. The forecasting strategies used comprise automatic machine learning, one of the most recent generative pre-trained transformers, and established artificial neural network algorithms capable of univariate and multivariate forecasting. RESULTS: We found that machine learning models compute more accurate forecasts in comparison to naïve seasonal models. Furthermore, we analyzed the impact of reducing the temporal resolution of forecasts, which decreased the model error of point forecasts and made probabilistic forecasting more reliable. An additional analysis that used the laboratory data revealed strong season-to-season variations in the incidence of respiratory viruses and how this correlates with total hospitalization cases. These variations could explain why it was not possible to improve forecasts by integrating this data. CONCLUSIONS: Active SARI surveillance and consistent data collection over time enable these data to be used to predict hospital bed utilization. These findings show the potential of machine learning as support for informing systems for proactive hospital management.

Modeling respiratory tract diseases for clinical translation employing conditionally reprogrammed cells.

Preclinical models serve as indispensable tools in translational medicine. Specifically, patient-derived models such as patient-derived xenografts (PDX), induced pluripotent stem cells (iPSC), organoids, and recently developed technique of conditional reprogramming (CR) have been employed to reflect the host characteristics of diseases. CR technology involves co-culturing epithelial cells with irradiated Swiss-3T3-J2 mouse fibroblasts (feeder cells) in the presence of a Rho kinase (ROCK) inhibitor, Y-27632. CR technique facilitates the rapid conversion of both normal and malignant cells into a "reprogrammed stem-like" state, marked by robust in vitro proliferation. This is achieved without reliance on exogenous gene expression or viral transfection, while maintaining the genetic profile of the parental cells. So far, CR technology has been used to study biology of diseases, targeted therapies (precision medicine), regenerative medicine, and noninvasive diagnosis and surveillance. Respiratory diseases, ranking as the third leading cause of global mortality, pose a significant burden to healthcare systems worldwide. Given the substantial mortality and morbidity rates of respiratory diseases, efficient and rapid preclinical models are imperative to accurately recapitulate the diverse spectrum of respiratory conditions. In this article, we discuss the applications and future potential of CR technology in modeling various respiratory tract diseases, including lung cancer, respiratory viral infections (such as influenza and Covid-19 and etc.), asthma, cystic fibrosis, respiratory papillomatosis, and upper aerodigestive track tumors. Furthermore, we discuss the potential utility of CR in personalized medicine, regenerative medicine, and clinical translation.

Liquid-liquid phase separation: a new perspective on respiratory diseases.

Liquid-liquid phase separation (LLPS) is integral to various biological processes, facilitating signal transduction by creating a condensed, membrane-less environment that plays crucial roles in diverse physiological and pathological processes. Recent evidence has underscored the significance of LLPS in human health and disease. However, its implications in respiratory diseases remain poorly understood. This review explores current insights into the mechanisms and biological roles of LLPS, focusing particularly on its relevance to respiratory diseases, aiming to deepen our understanding and propose a new paradigm for studying phase separation in this context.

A Non-natural Peptide Targeting the A-kinase Anchoring Function of PI3Kγ for Therapeutic cAMP Modulation in Pulmonary Cells.

A-kinase anchoring proteins (AKAPs) are key orchestrators of cyclic AMP (cAMP) signaling that act by recruiting protein kinase A (PKA) in proximity of its substrates and regulators to specific subcellular compartments. Modulation of AKAPs function offers the opportunity to achieve compartment-restricted modulation of the cAMP/PKA axis, paving the way to new targeted treatments. For instance, blocking the AKAP activity of PI3Kγ improves lung function by inducing cAMP-mediated bronchorelaxation, ion transport and anti-inflammatory responses. Here, we report the generation of a non-natural peptide, DRI-Pep #20, optimized to disrupt the AKAP function of PI3Kγ. DRI-Pep #20 mimicked the native interaction between the N-terminal domain of PI3Kγ and PKA, demonstrating nanomolar affinity for PKA, high resistance to protease degradation and high permeability to the pulmonary mucus barrier. DRI-Pep #20 triggered cAMP elevation both in vivo in the airway tract of mice upon intratracheal administration, and in vitro in bronchial epithelial cells of cystic fibrosis (CF) patients. In CF cells, DRI-Pep #20 rescued the defective function of the cAMP-operated channel cystic fibrosis conductance regulator (CFTR), by boosting the efficacy of approved CFTR modulators. Overall, this study unveils DRI-Pep #20 as a potent PI3Kγ/PKA disruptor for achieving therapeutic cAMP elevation in chronic respiratory disorders.

Exploring the relationship between sarcopenia and 11 respiratory diseases: a comprehensive mendelian randomization analysis.

BACKGROUND: Sarcopenia (SP) is an aging-related loss of muscle mass and function, affecting the respiratory system. However, the causality of the association between sarcopenia on lung diseases remains elusive. METHODS: The bidirectional univariate Mendelian randomization (UVMR), multivariate MR (MVMR) analysis, and mediation MR were utilized to systematically investigate the genetic causal relationship of SP and 11 respiratory diseases. Independent genomic variants related to sarcopenia or respiratory diseases were identified as instrumental variables (IVs), and the summary level data of genome-wide associated studies (GWAS) were obtained from the UK biobank and FinnGen. MVMR analysis was conducted to explore the mediation effects of body mass index (BMI), Alcohol Use Disorders Identification Test (AUDIT), smoking, education attainment (EA), physical activity, and Type 2 Diabetes Mellitus (T2DM). RESULTS: Forward UVMR analysis based on the primary method revealed that pneumoconiosis was associated with a higher risk of appendicular lean mass (ALM) (OR = 1.01, p = 0.03), and BMI (10.65%), smoking (10.65%), and physical activity (17.70%) had a mediating role in the effect of pneumoconiosis on ALM. In reverse MR analysis, we found that genetically predicted ALM was significantly associated with an increased risk of pulmonary embolism (PE) (OR = 1.24, p = 7.21E-05). Chronic obstructive pulmonary disease (COPD) (OR = 0.98, p = 0.002) and sarcoidosis (OR = 1.01, p = 0.004) were identified to increase the loss of left-hand grip strength (HGS). Conversely, the increase in left- HGS presented a protective effect on chronic bronchitis (CB) (OR = 0.35, p = 0.03), (OR = 0.80, p = 0.02), and asthma (OR = 0.78, p = 0.04). Similarly, the loss of the right-HGS elevated the risk of low respiratory tract infection (LRTI) (OR = 0.97, p = 0.02) and bronchiectasis (OR = 1.01, p = 0.03), which is also an independent protective factor for LRTI and asthma. In the aspects of low HGS, the risk of LRTI was increased after MVMR analysis, and the risk of sarcoidosis and pneumoconiosis was elevated in the reverse analysis. Lastly, asthma was found to be related to the loss of the usual walking pace, and the reverse MR analysis suggested a causal relationship between the usual walking pace and LRTI (OR = 0.32, p = 2.79 × 10-5), asthma (OR = 0.24, p = 2.09 × 10-6), COPD (OR = 0.22, p = 6.64 × 10-4), and PE(OR = 0.35, p = 0.03). CONCLUSIONS: This data-driven MR analysis revealed SP was bidirectional causally associated with lung diseases, providing genetic evidence for further mechanistic and clinical studies to understand the crosstalk between SP and lung diseases.

Survey on the Traditional Use of Medicinal Herbs in Haiti: A Study on Knowledge, Practices, and Efficacy Prevention.

The use of medicinal herbs is highly developed in Haiti. However, there is a significant lack of knowledge in the literature on medicinal plants and their uses. The objective of this study was to determine the knowledge and practices of Haitian families for the prevention/treatment of COVID-19, influenza, and respiratory diseases, as well as the mode of preparation and administration of the plants. Individuals were interviewed using the TRAMIL questionnaire as the information holder. The data obtained were analyzed by calculating 5 indices (relative frequency of citation, use value, the family use value, informant consensus factor, and fidelity level). The study surveyed 120 Haitians and collected 75 plants from 43 botanical families. The botanical family most used for all these preventions and remedies is the Lamiaceae. The highest ranked species with a relative frequency of citation value > 0.3. Infusion, decoction, and in the form of punch are the methods used for the remedies. The study found that the use of herbal remedies is still prevalent in the study area, and many of the commonly used plants have been scientifically validated. However, some plants, such as Samyda rosea Sims, lack sufficient research and are recommended for further investigation.

Sex and disease regulate major histocompatibility complex class I expression in human lung epithelial cells.

Major histocompatibility complex class I (MHC I) molecules present peptides to CD8+ T-cells for immunosurveillance of infection and cancer. Recent studies indicate lineage-specific heterogeneity in MHC I expression. While respiratory diseases rank among the leading causes of mortality, studies in mice have shown that lung epithelial cells (LECs) express the lowest levels of MHC I in the lung. This study aims to answer three questions: (i) Do human LECs express low levels of MHC I? (ii) Is LEC MHC I expression modulated in chronic respiratory diseases? (iii) Which factors regulate MHC I levels in human LECs? We analyzed human LECs from parenchymal explants using single-cell RNA sequencing and immunostaining. We confirmed low constitutive MHC I expression in human LECs, with significant upregulation in chronic respiratory diseases. We observed a sexual dimorphism, with males having higher MHC I levels under steady-state conditions, likely due to differential redox balance. Our study unveils the complex interplay between MHC I expression, sex, and respiratory disease. Since MHC I upregulation contributes to the development of immunopathologies in other models, we propose that it may have a similar impact on chronic lung disease.

Estimating the generation time for influenza transmission using household data in the United States.

The generation time, representing the interval between infections in primary and secondary cases, is essential for understanding and predicting the transmission dynamics of seasonal influenza, including the real-time effective reproduction number (Rt). However, comprehensive generation time estimates for seasonal influenza, especially post the 2009 influenza pandemic, are lacking. We estimated the generation time utilizing data from a 7-site case-ascertained household study in the United States over two influenza seasons, 2021/2022 and 2022/2023. More than 200 individuals who tested positive for influenza and their household contacts were enrolled within 7 days of the first illness in the household. All participants were prospectively followed for 10 days completing daily symptom diaries and collecting nasal swabs, which were tested for influenza via RT-PCR. We analyzed these data by modifying a previously published Bayesian data augmentation approach that imputes infection times of cases to obtain both intrinsic (assuming no susceptible depletion) and realized (observed within household) generation times. We assessed the robustness of the generation time estimate by varying the incubation period, and generated estimates of the proportion of transmission before symptomatic onset, infectious period, and latent period. We estimated a mean intrinsic generation time of 3.2 (95% credible interval, CrI: 2.9-3.6) days, with a realized household generation time of 2.8 (95% CrI: 2.7-3.0) days. The generation time exhibited limited sensitivity to incubation period variation. Estimates of the proportion of transmission that occurred before symptom onset, the infectious period, and the latent period were sensitive to variation in incubation periods. Our study contributes to the ongoing efforts to refine estimates of the generation time for influenza. Our estimates, derived from recent data following the COVID-19 pandemic, are consistent with previous pre-pandemic estimates, and will be incorporated into real-time Rt estimation efforts.

Association between serum 25-hydroxyvitamin D and asthma: Evidence from the National Health and Nutrition Examination Survey (NHANES) 2011-2018.

BACKGROUND AND OBJECTIVE: Asthma is a heterogeneous respiratory disease characterized by airway hyper-responsiveness and reversible airflow blockage. There is ongoing debate about the impact of vitamin D on asthma. This research is focused on investigating the correlation between serum levels of 25-hydroxyvitamin D and asthma. METHODS: This cross-sectional study comprised 22,708 eligible participants. Data on asthma and serum 25-hydroxyvitamin D levels from the National Health and Nutrition Examination Survey (NHANES) 2011-2018 were analyzed. Serum 25-hydroxyvitamin D levels were the main factor, with the presence of asthma as the outcome variable. Weighted logistic regression was utilized to investigate the relationship between serum levels of 25-hydroxyvitamin D and asthma, while accounting for factors such as age, gender, race, length of time in US, annual family income, education level, high-density lipoprotein, low-density lipoprotein, triglycerides, and cholesterol. RESULTS: Upon adjusting all variables in model III, epi-25-hydroxyvitamin D3 displayed a negative correlation with current asthma at the lower quartile Q1 (0.784, [0.697 to 0.922]), Q2 (0.841, [0.729 to 0.946]), Q3 (0.396, [0.240 to 0.653]) when compared to the highest quartile Q4 level. However, no significant difference was observed between asthma and 25-hydroxyvitamin D2, as well as 25-hydroxyvitamin D3. CONCLUSIONS: In the U.S. population, elevated levels of epi-25-hydroxyvitamin D3 are correlated with an increased risk of developing existing asthma. However, it is important to interpret this finding carefully given the constraints of cross-sectional studies.

The association between prenatal pyrethroids exposure and children's health - current research.

Exposure to pyrethroids, a widely used agricultural, forestry, and household insecticide, is a major public health concern due to its potential health effects on children. The aim of this review was to summarize the current knowledge of the effects of prenatal exposure to pyrethroids on the course and outcome of pregnancy, health status, and neurobehavioural development of children. A systematic and comprehensive search of the PubMed, Web of Science, and Scopus databases was conducted during January-February 2024. The review included original articles published in peerreviewed English-language journals since 2015. Based on keywords, 198 studies were identified and screened for eligibility. Ultimately, the review analyzed 25 articles including 16 that assessed the effects of prenatal exposure to pyrethroids on children's neurobehavioural development, 3 studies that assessed the effects on the course and outcome of pregnancy, and further 3 focused on respiratory disease. In addition, 1 study analyzed the development of obesity and 2 studies examined the effects on children's growth, weight and body composition in early childhood. In conclusion, there is considerable uncertainty about the adverse effects of prenatal exposure to pyrethroids on children's health. The strongest evidence has been reported for neurobehavioural development although results are also inconsistent. Further research is needed to understand the mechanisms of action and health effects of pyrethroids in susceptible populations. Int J Occup Med Environ Health. 2024;37(4).

Causal Relationships Between Emotional Instability and Respiratory Diseases: A Mendelian Randomization Analysis.

Background: In the past few years, there has been a growing fascination with the connection between mental well-being and respiratory conditions. However, the causal relationship between personality traits and respiratory diseases remains largely unknown. This study aimed to investigate the link between genetically predicted emotional instability and eight respiratory conditions using a two-sample Mendelian randomization (MR) analysis. Methods: In a GWAS dataset from the UK Biobank, SNPs linked to emotional instability were discovered among 204,412 participants of European descent. Genetic information for lung cancer, pulmonary fibrosis, pneumonia, and bronchiectasis was obtained from the European Bioinformatics Institute (EBI). While data for chronic obstructive pulmonary disease (COPD), pulmonary embolism, chronic cough, and asthma was collected from the UK BioBank. An MR study was carried out to investigate how specific single nucleotide polymorphisms (SNPs) impact the likelihood of developing the eight respiratory conditions listed. Our main approach for the initial screening was the utilization of inverse variance weighting (IVW). Multiplicity was assessed using the MR-Egger regression test, while heterogeneity was evaluated with Cochran's Q test. To ensure the reliability of the findings, a leave-one-out analysis was conducted. Results: IVW found evidence that emotional instability had a significant causal effect on the increased risk of COPD (OR = 1.009; 95% CI = 1.001-1.017; P = 0.022), pneumonia (OR = 1.648; 95% CI = 1.036-2.622; P = 0.035), chronic cough (OR = 1.077; 95% CI = 1.013-1.145; P = 0.017) and increased risk of asthma (OR = 1.073; 95% CI = 1.026-1.123; P = 0.002) had a significant causal relationship. This association remained strong in the case of potential confounders, including smoking. Additionally, the instrumental variable weighted method in this study did not find any indication of a causal link between emotional instability and lung cancer, pulmonary embolism, pulmonary fibrosis, and bronchiectasis (all P > 0.05). Conclusion: The research discovered a link between emotional instability and a higher likelihood of developing COPD, pneumonia, chronic cough, and asthma. This study also found that emotional instability was not causally associated with lung cancer, pulmonary embolism, pulmonary fibrosis, and bronchiectasis.

Association between P M 10 and respiratory diseases admission in peninsula Malaysia during haze.

Numerous studies have been conducted in other countries on the health effects of exposure to particulate matter with a diameter of 10 microns or less P M 10 , but little research has been conducted in Malaysia, particularly during the haze season. This study intends to investigate how exposure of P M 10 influenced hospital admissions for respiratory diseases during the haze period in peninsula Malaysia and it was further stratified by age group, gender and respiratory diseases categories. The study includes data from all patients with respiratory diseases in 92 government hospitals, as well as P M 10 concentration and meteorological data from 92 monitoring stations in Peninsula Malaysia starting from 1st January 2000 to 31st December 2019. A quasi-poison time series regression with distributed lag nonlinear model (DLNM) was employed in this study to examine the relationship between exposure of P M 10 and hospital admissions for respiratory diseases during the haze period. Haze period for this study has been defined from June to September each year. According to the findings of this study, P M 10 was positively associated with hospitalisation of respiratory disease within 30 lag days under various lag patterns, with lag 25 showing the strongest association (RR = 1.001742, CI 1.001029,1.002456). Using median as a reference, it was discovered that females were more likely than males to be hospitalized for P M 10 exposure. Working age group will be the most affected by the increase in P M 10 exposure with a significant cumulative RR from lag 010 to lag 030. The study found that P M 10 had a significant influence on respiratory hospitalisation in peninsula Malaysia, particularly for lung diseases caused by external agents(CD5). Therefore, it is important to implement effective intervention measures to control P M 10 and reduce the burden of respiratory disease admissions.

The epidemiology of critical respiratory diseases in ex-premature infants in Vietnam: A prospective single-center study.

INTRODUCTION: This study aimed to describe the epidemiology and etiologies of critical respiratory diseases of ex-premature infants (EPIs) admitted to the Pediatric Intensive Care unit (PICU). METHODS: Infants ≤2 years old with acute respiratory illnesses admitted to PICU of Vietnam National Children's Hospital from November 2019 to April 2021 were enrolled and followed up to hospital discharge. We compared respiratory pathogens, outcomes, and PICU resources utilized between EPIs and term infants. Among EPIs, we described clinical characteristics and evaluated the association between associated factors and mortality. RESULTS: Among 1183 patients, aged ≤2 years were admitted for critical respiratory illnesses, 202 (17.1%) were EPIs. Respiratory viruses were detected in 53.5% and 38.2% among EPIs and term infants, respectively. Compared to term infants, a higher proportion of EPIs required mechanical ventilation (MV) (85.6 vs. 66.5%, p < .005) and vasopressor support (37.6 vs. 10.7%%, p < .005). EPIs had a higher median PICU length of stay (11.0 [IQR: 7; 22] vs. 6.0 days [IQR: 3; 11], p = .09), hospital length of stay (21.5 [IQR: 13; 40] vs. 10.0 days [IQR: 5; 18], p < .005) and case fatality rate (31.3% vs. 22.6%) compared to term infants. Among EPIs, PIM-3 score (adjusted odds ratio [aOR]: 1.51; 95% confidence interval [CI]: 1.30-1.75) and PELOD-2 score at admission (aOR: 1.41; 95% CI: 1.08-1.85) were associated with mortality. CONCLUSIONS: EPIs with critical respiratory illnesses constituted a significant population in the PICU, required more PICU support, and had worse clinical outcomes compared to term infants.

Efficacy of Remote Health Monitoring in Reducing Hospital Readmissions Among High-Risk Postdischarge Patients: Prospective Cohort Study.

BACKGROUND: Patients with respiratory or cardiovascular diseases often experience higher rates of hospital readmission due to compromised heart-lung function and significant clinical symptoms. Effective measures such as discharge planning, case management, home telemonitoring follow-up, and patient education can significantly mitigate hospital readmissions. OBJECTIVE: This study aimed to determine the efficacy of home telemonitoring follow-up in reducing hospital readmissions, emergency department (ED) visits, and total hospital days for high-risk postdischarge patients. METHODS: This prospective cohort study was conducted between July and October 2021. High-risk patients were screened for eligibility and enrolled in the study. The intervention involved implementing home digital monitoring to track patient health metrics after discharge, with the aim of reducing hospital readmissions and ED visits. High-risk patients or their primary caregivers received education on using communication measurement tools and recording and uploading data. Before discharge, patients were familiarized with these tools, which they continued to use for 4 weeks after discharge. A project manager monitored the daily uploaded health data, while a weekly video appointment with the program coordinator monitored the heart and breathing sounds of the patients, tracked health status changes, and gathered relevant data. Care guidance and medical advice were provided based on symptoms and physiological signals. The primary outcomes of this study were the number of hospital readmissions and ED visits within 3 and 6 months after intervention. The secondary outcomes included the total number of hospital days and patient adherence to the home monitoring protocol. RESULTS: Among 41 eligible patients, 93% (n=38) were male, and 46% (n=19) were aged 41-60 years, while 46% (n=19) were aged 60 years or older. The study revealed that home digital monitoring significantly reduced hospitalizations, ED visits, and total hospital stay days at 3 and 6 months after intervention. At 3 months after intervention, average hospitalizations decreased from 0.45 (SD 0.09) to 0.19 (SD 0.09; P=.03), and average ED visits decreased from 0.48 (SD 0.09) to 0.06 (SD 0.04; P<.001). Average hospital days decreased from 6.61 (SD 2.25) to 1.94 (SD 1.15; P=.08). At 6 months after intervention, average hospitalizations decreased from 0.55 (SD 0.11) to 0.23 (SD 0.09; P=.01), and average ED visits decreased from 0.55 (SD 0.11) to 0.23 (SD 0.09; P=.02). Average hospital days decreased from 7.48 (SD 2.32) to 6.03 (SD 3.12; P=.73). CONCLUSIONS: By integrating home telemonitoring with regular follow-up, our research demonstrates a viable approach to reducing hospital readmissions and ED visits, ultimately improving patient outcomes and reducing health care costs. The practical application of telemonitoring in a real-world setting showcases its potential as a scalable solution for chronic disease management.

Impact of Hypoxia on Neutrophil Degranulation and Inflammatory Response in Alpha-1 Antitrypsin Deficiency Patients.

BACKGROUND: Alpha-1 antitrypsin deficiency (AATD) is an inflammatory disorder where neutrophils play a key role. Excessive neutrophil activation leads to local hypoxia and tissue damage. Most research on neutrophil function has been conducted under atmospheric conditions (21% O2), which may not represent physiological or pathological conditions. This study aimed to determine the effects of hypoxia on neutrophil degranulation and cytokine production in AATD patients. METHODS: Neutrophils isolated from 54 AATD patients (31 MZ; 8 SZ; 15 ZZ) and 7 controls (MM) were exposed to hypoxia (1% O2) for 4 h. Neutrophil degranulation was assessed by measuring elastase (NE), myeloperoxidase (MPO), lactoferrin, and matrix metalloproteinase-9 (MMP-9) levels using immunoassay-based methods. Pro-inflammatory (IL-8, IL-1 beta, IL-6, and TNF-alpha) and anti-inflammatory (IL-4 and IL-10) cytokine levels were assessed by a Luminex-based method. RESULTS: Our results indicate a significantly increased release of NE (p = 0.015), MPO (p = 0.042), lactoferrin (p = 0.015), and MMP-9 (p = 0.001) compared to controls. Pro-inflammatory cytokines show a significant rise in IL-8 (p = 0.019), a trend towards increased IL-1 beta (p = 0.3196), no change in IL-6 (p = 0.7329), and reduced TNF-alpha (p = 0.006). Anti-inflammatory cytokines show increased IL-4 (p = 0.057) and decreased IL-10 (p = 0.05703). CONCLUSIONS: Increased neutrophil degranulation and inflammatory phenotype are observed in AATD neutrophils under physiological hypoxia.

Air pollution, dysbiosis and diseases: pneumonia, asthma, COPD, lung cancer and irritable bowel syndrome.

With substantial effects on human health, air pollution has become a major global concern. Air pollution has been linked to numerous gastrointestinal and respiratory diseases with increasing mortalities. The gut and respiratory dysbiosis brought about by air pollution has recently received much attention. This review attempts to provide an overview of the types of air pollutants, their sources, their impact on the respiratory and gut dysbiotic patterns and their correlation with five major diseases including pneumonia, asthma, COPD, lung cancer and irritable bowel syndrome. Deeper insights into the links between pollutants, dysbiosis and disease may pave the way for novel diagnostic biomarkers for prognosis and early detection of these diseases, as well as ways to ease the disease burden.

Air pollution has become a major environmental concern because it can harm human health. Generally, air pollution is either classified as indoor or outdoor. Air pollutants are released from factories, automobiles, preparation of construction materials, agricultural practices, poultry and animal farming and even domestic tasks such as cooking. Air pollution can cause various illnesses of the gastrointestinal tract and lungs. These include cystic fibrosis, pneumonia, asthma, lung cancer, COPD and irritable bowel syndrome. These diseases are linked to disruptions of the community of bacteria in the lungs and gastrointestinal tract. This review looks at the impact of air pollution on microbial communities and associated diseases.

Epidemiology and risk factors for adult gliomas died by respiratory diseases during the COVID-19 pandemic: a population-based study.

BACKGROUND: The research on epidemiology of gliomas died of respiratory diseases (RDs) is very scarce. The study aimed to explore the epidemiology and risk factors for adult gliomas death from respiratory diseases during the COVID-19 pandemic. METHODS: Adult gliomas patients (age ≥ 18 years) diagnosed between 2020 and 2021 were selected from the Surveillance, Epidemiology, and End Results (SEER) database. Propensity score matching analysis was used to reduce confounding bias between gliomas died of respiratory diseases and died of gliomas directly. The Cox proportional hazards regression model and Kaplan-Meier (K-M) survival curves were used for survival analyses in the matched groups. Logistic regression analyses were conducted to identify risk factors for dying of respiratory diseases in the entire population. RESULTS: Among 9315 eligible adult gliomas enrolled in the study, 39.4% died from gliomas, 1.0% from respiratory diseases, and 61.4% survived. Gliomas who died from respiratory diseases had a trend towards a higher risk of death (HR = 1.35, P = 0.031). Surgery did not increase the all-cause mortality risk (HR = 0.86, P = 0.327). The K-M survival curves suggested a worse prognosis for dying from respiratory diseases. Those who died from RDs had a shortened median survival (median 3 months) compared with those who died from gliomas directly (median 5 months). Multivariable logistic regression models indicated that those aged ≥ 65 years, with median household income < 75,000$/year, and not receiving surgery had a higher risk of dying from RDs. CONCLUSIONS: RDs have become a crucial cause of death for gliomas. Those with advanced age and lower median household income have a higher risk of dying from respiratory diseases. Surgical treatment has been found to be safe for glioma patients and has been shown to reduce the risk of glioma patients dying from respiratory diseases. The study provides valuable insights for the perioperative management of gliomas patients in the post-pandemic era.