Respiratory Infectious Diseases Research Articles

Alpha-1 antitrypsin inhibits pertussis toxin

Pertussis (whooping cough) is a vaccine-preventable but re-emerging, highly infectious respiratory disease caused by Bordetella pertussis. There are currently no effective treatments for pertussis, complicating care for non-vaccinated individuals, especially newborns. Disease manifestations are predominantly caused by pertussis toxin (PT), a pivotal virulence factor classified as an ADP-ribosylating AB-type protein toxin. In this work, an unbiased approach using peptide libraries, bioassay-guided fractionation and mass spectrometry revealed α1-antitrypsin (α1AT) as a potent PT inhibitor. Biochemistry-, cell culture- and molecular modeling-based in vitro experimentation demonstrated that the α1AT mode of action is based on blocking PT-binding to the host target cell surface. In the infant mouse model of severe pertussis, α1AT expression was reduced upon infection. Further, systemic administration of α1AT significantly reduced B. pertussis-induced leukocytosis, which is a hallmark of infant infection and major risk factor for fatal pertussis. Taken together our data demonstrates that α1AT is a novel PT inhibitor and that further evaluation and development of α1AT as a therapeutic agent for pertussis is warranted. Importantly, purified α1AT is already in use clinically as an intravenous augmentation therapy for those with genetic α1AT deficiency and could be repurposed to clinical management of pertussis.

Educational needs for virtual reality-based simulation training in the nursing care of adult respiratory patients: an explanatory sequential mixed-methods study.

We aimed to ascertain the current state of and needs for virtual reality (VR)-based simulation training in the care of adult respiratory patients. Learning to care for patients with infectious respiratory disease is crucial in nurses' practical education. Thus, studies on the state of VR-based simulation-training are required. We used an explanatory sequential mixed-methods design. The sample included 122 new nurses at two advanced general hospitals and five educators at a nursing college. The educational needs of virtual reality-based simulation education were measured by the tool developed in this study. Research data were collected from August 31 to September 26, 2022. Quantitative data were subjected to a descriptive analysis, while qualitative data were subjected to content analysis. The new nurses in this study had a mean age of 24.51 years and total clinical experience of 11.18 months; 82.8% of the participants had experience in adult respiratory patient care, and 94.3% were aware of the need for this training. In the qualitative data analysis of six new nurses, all participants had experience with simulation training and were aware of its need. Moreover, all participants wanted repeated VR-based simulation training using real clinical cases. Regarding the qualitative data analysis of five nursing college educators, most of them had experience providing and receiving simulation training, and they were aware of its need in caring for respiratory patients. They reported the need for VR learning spaces that reflect the clinical environment, alongside sufficient duration and frequency of learning. Our findings could help develop simulation training programs for nursing students to assist adult respiratory patients. We provide a basis for developing VR-based simulation training for respiratory care by studying the current state of and demand for nurses' VR-based simulation training. The results can contribute to improving the quality of nursing for adult respiratory patients.

Individual Characteristics Associated with Fears and Prevention Behaviors Related to Respiratory Infectious Disease among South Korean Adults Using Complex Sample Design.

This study aimed to identify the relationships among individual characteristics, COVID-19-related fears, and infection-prevention behaviors using data from 228,932 adults (weighted to 43,583,798.71) aged 19 and older who participated in the 2021 Community Health Survey conducted by the Korea Disease Control and Prevention Agency. The complex sample design analysis using SPSS 20.0 revealed the following. Women had statistically significantly higher COVID-19-related fears and a higher level of preventive behaviors compared to men. During the COVID-19 pandemic, the level of physical activity among men was higher than that of women. Compared to the period before COVID-19, the frequency of smoking and drinking decreased for both men and women, with the reduction being more pronounced in men than in women. The high-exercise group had a lower level of COVID-19-related fears. Self-perceived health status was inversely and significantly related to COVID-19-related fears. The low-exercise group had a lower score for self-perceived health status than the high-exercise group. This study demonstrated that maintaining sufficient physical activity positively influences self-perceived health and reduces anxieties related to COVID-19 infection and fatalities. The results highlight the importance of physical activity and the need to identify strategies that effectively maintain regular exercise while adhering to infection-prevention measures during pandemics.

Epidemiological Characteristics and Spatiotemporal Clustering of Pulmonary Tuberculosis Among Students in Southwest China From 2016 to 2022: Analysis of Population-Based Surveillance Data.

Pulmonary tuberculosis (PTB), as a respiratory infectious disease, poses significant risks of covert transmission and dissemination. The high aggregation and close contact among students in Chinese schools exacerbate the transmission risk of PTB outbreaks. This study investigated the epidemiological characteristics, geographic distribution, and spatiotemporal evolution of student PTB in Chongqing, Southwest China, aiming to delineate the incidence risks and clustering patterns of PTB among students. PTB case data from students monitored and reported in the Tuberculosis Information Management System within the China Information System for Disease Control and Prevention were used for this study. Descriptive analyses were conducted to characterize the epidemiological features of student PTB. Spatial trend surface analysis, global and local spatial autocorrelation analyses, and disease rate mapping were performed using ArcGIS 10.3. SaTScan 9.6 software was used to identify spatiotemporal clusters of PTB cases. From 2016 to 2022, a total of 9920 student TB cases were reported in Chongqing, Southwest China, with an average incidence rate of 24.89/100,000. The incidence of student TB showed an initial increase followed by a decline, yet it remained relatively high. High school students (age: 13-18 years; 6649/9920, 67.03%) and college students (age: ≥19 years; 2921/9920, 29.45%) accounted for the majority of student PTB cases. Patient identification primarily relied on passive detection, with a high proportion of delayed diagnosis and positive etiological results. COVID-19 prevention measures have had some impact on reducing incidence levels, but the primary factor appears to be the implementation of screening measures, which facilitated earlier case detection. Global spatial autocorrelation analysis indicated Moran I values of >0 for all years except 2018, ranging from 0.1908 to 0.4645 (all P values were <.05), suggesting strong positive spatial clustering of student PTB cases across Chongqing. Local spatial autocorrelation identified 7 high-high clusters, 13 low-low clusters, 5 high-low clusters, and 4 low-high clusters. High-high clusters were predominantly located in the southeast and northeast parts of Chongqing, consistent with spatial trend surface analysis and spatiotemporal clustering results. Spatiotemporal scan analysis revealed 4 statistically significant spatiotemporal clusters, with the most likely cluster in the southeast (relative risk [RR]=2.87, log likelihood ratio [LLR]=574.29, P<.001) and a secondary cluster in the northeast (RR=1.99, LLR=234.67, P<.001), indicating higher reported student TB cases and elevated risks of epidemic spread within these regions. Future efforts should comprehensively enhance prevention and control measures in high-risk areas of PTB in Chongqing to mitigate the incidence risk among students. Additionally, implementing proactive screening strategies and enhancing screening measures are crucial for early identification of student patients to prevent PTB outbreaks in schools.

Human behavior-based COVID-19 transmission in two dining spaces

Since December 2019, the COVID-19 pandemic has rapidly disseminated globally, posing significant threats to the world. The dining spaces are high-risk indoor environments for the transmission of SARS-CoV-2, posing challenges for intervention and control. This study, based on surveillance videos from two COVID-19 outbreak cases in restaurants, obtained real data on human behaviors of close contact and surface touch. A respiratory infectious disease transmission model was developed, incorporating four transmission routes: short-range airborne, long-range airborne, fomite and large droplet. The results indicate that diners and staff spent 21.9 %−28.7 % and 17.5 %−27.8 % of their time on speaking, respectively, while spending 85.9 %−90.7 % and 83.4 %−87.6 % of their time on surface touching. The primary transmission routes were short-range (contributing 5.8 %−70.9 %) and long-range airborne (contributing 28.4 %−93.0 %), with fomite and large droplet routes contributing less than 12.0 %. Staff-only mask wearing reduced infection risk by 12.8 %−31.8 %. It is recommended that mandatory mask wearing for staff is necessary, while diners should wear masks as much as possible, and that the equivalent ventilation rate of clean fresh air is suggested to 30.0 m3/ (h·person). This study provides a scientific support to make non-pharmaceutical interventions in dinning spaces.

Mapping the Characteristics of Respiratory Infectious Disease Epidemics in China Based on the Baidu Index from November 2022 to January 2023.

Infectious diseases pose a significant global health and economic burden, underscoring the critical need for precise predictive models. The Baidu index provides enhanced real-time surveillance capabilities that augment traditional systems. Baidu search engine data on the keyword "fever" were extracted from 255 cities in China from November 2022 to January 2023. Onset and peak dates for influenza epidemics were identified by testing various criteria that combined thresholds and consecutive days. The most effective scenario for indicating epidemic commencement involved a 90th percentile threshold exceeded for seven consecutive days, minimizing false starts. Peak detection was optimized using a 7-day moving average, balancing stability and precision. The use of internet search data, such as the Baidu index, significantly improves the timeliness and accuracy of disease surveillance models. This innovative approach supports faster public health interventions and demonstrates its potential for enhancing epidemic monitoring and response efforts.

Assessing the impact of COVID-19 non-pharmaceutical interventions and relaxation policies on Class B respiratory infectious diseases transmission in China

This study investigates the incidence of Class B respiratory infectious diseases (RIDs) in China under the Coronavirus disease 2019 (COVID-19) epidemic and examines variations post-epidemic, following the relaxation of non-pharmaceutical interventions (NPIs). Two-stage evaluation was used in our study. In the first stage evaluation, we established counterfactual models for the pre-COVID-19 period to estimate expected incidences of Class B RIDs without the onset of the epidemic. In the second stage evaluation, we constructed seasonal autoregressive integrated moving average intervention (SARIMA-Intervention) models to evaluate the impact on the Class B RIDs after NPIs aimed at COVID-19 pandemic were relaxed. The counterfactual model in the first stage evaluation suggested average annual increases of 10.015%, 78.019%, 70.439%, and 67.799% for tuberculosis, scarlet fever, measles, and pertussis respectively, had the epidemic not occurred. In the second stage evaluation, the total relative reduction in 2023 of tuberculosis, scarlet fever, measles and pertussis were − 35.209%, − 59.184%, − 4.481%, and − 9.943% respectively. The actual incidence declined significantly in the first stage evaluation. However, the results of the second stage evaluation indicated that a rebound occurred in four Class B RIDs after the relaxation of NPIs; all of these showed a negative total relative reduction rate.

Highly-Efficient Selection of Aptamers for Quantitative Fluorescence Detecting Multiple IAV Subtypes.

Influenza A virus (IAV) can cause infectious respiratory diseases in humans and animals. IAVs mutate rapidly through antigenic drift and shift, resulting in the emergence of numerous IAV subtypes and significant challenges for IAV detection. Therefore, achieving the simultaneous detection of multiple IAVs is crucial. In this work, three specific aptamers targeting the hemagglutination (HA) protein of the influenza A H5N1, H7N9, and H9N2 viruses were screened using a multichannel magnetic microfluidic chip. The aptamers exhibit nanomolar affinity and excellent specificity for the HA protein of H5N1, H7N9, and H9N2 viruses. Furthermore, three specific aptamers were truncated and labeled with different fluorescence markers to realize fluorescence quantitative detection of influenza A H5N1, H7N9, and H9N2 viruses through an aptamer sandwich assay in 1 h. The limit of detection (LOD) of the developed method is 0.38 TCID50/mL for the H5N1 virus, 0.75 TCID50/mL for the H7N9 virus, and 1.14 TCID50/mL for the H9N2 virus. The detection method has excellent specificity, strong anti-interference ability, and good reproducibility. This work provides a sensitive quantitative detection method for the H5N1, H7N9, and H9N2 viruses, enabling quantitative fluorescence detection for multiple IAV subtypes.

New progress in laboratory detection of respiratory infectious diseases in children

Respiratory infectious disease has become ahead of all the children's diseases, with the trend of continuously increasing global incidence, antimicrobial resistance and simultaneous infection with multiple pathogens. Diagnosis of this disease is mainly based on clinical symptoms and pathogenic detection. However, there are some differences in clinical manifestations, progression and prognosis between pediatric patients and adults, which prompting clinical diagnosis mainly depending on clinical laboratory test. Therefore, fast, convenient and accurate methods are urgently needed to clarify the type of infectious pathogen and carry out differentiated treatment, and reduce the burden on families and public health-care systems in schools. This article aims to elaborate the laboratory methods of children's respiratory infectious diseases and explore the opportunities and challenges, which can provide ideas for prevention, early screening and diagnosis, prognosis and treatment monitoring.

Evaluation Of Raftlin And 8-Iso Prostaglandin Levels On The Clinical Severity Of Cases With Covid-19 In Turkey : A Cross-Sectional Study

COVID-19 is an infectious respiratory disease caused by the severe acute respiratory syndrome Coronavirus 2 (SARS-CoV-2). Raftlin is a large lipid raft protein found in cell membranes and plays a crucial role in inducing autoimmune and vascular inflammatory responses. Although there have been few studies on 8-iso-prostaglandin F2α (8-iso-PGF2α) as a marker of oxidative stress in COVID-19, the levels of raftlin in the disease have not been previously investigated. The objective of our study was to evaluate the levels of Raftlin and 8-iso-prostaglandin F2α (8-iso-PGF2α) in COVID patients. We analyzed clinical findings from three groups: healthy controls, patients with a mild course of COVID, and patients with a severe course of COVID. We measured the levels of Raftlin and 8-iso-PGF2α in serum samples using ELISA. Our results showed that the levels of Raftlin and 8-iso-PGF2α were higher in patients with severe COVID compared to the control and mild course groups. Furthermore, a significant positive correlation was found between Raftlin and 8-iso-PGF2α in the severe COVID group. Raftlin was identified as a potentially important biomarker in COVID-19 patients. This study is valuable as it is the first to investigate changes in Raftlin and 8-iso-PGF2α levels in COVID-19 disease.

Critical measures for the prevention and control of respiratory infectious diseases in the workplace: a South African facilities management perspective

PurposeThis study aims to comprehensively examine the respiratory infection prevention and control measures used in South African workplaces, particularly in the context of facilities management (FM), during the 2020–2022 pandemic.Design/methodology/approachThe present research involved pre-crafted semi-structured interviews conducted by University of the Witwatersrand students with FM heads in Johannesburg, South Africa. Recurrent themes were generated using NVIVO software and analysed using frequencies, word counts and word clouds.FindingsThis study identified 119 measures and placed these into two broad categories. Twelve critical measures were found. These measures were further validated by five FM experts, separate from FM heads, who cross-referenced them with WHO guidelines, enhancing the credibility of the findings. Subsequently, challenges with implementing these measures were explored.Practical implicationsThe findings have direct relevance to the work of FM professionals, as they suggest that applying timely and comprehensive infection prevention and control measures can help employees to safely continue to work or return to the workplace during any future epidemic outbreaks.Originality/valueThus far, limited studies have explored critical measures used to prevent and control COVID-19 in the workplaces of developing countries during the 2020–2022 pandemic.

Study on the impact of meteorological factors on influenza in different periods and prediction based on artificial intelligence RF-Bi-LSTM algorithm: to compare the COVID-19 period with the non-COVID-19 period

ObjectiveAt different times, public health faces various challenges and the degree of intervention measures varies. The research on the impact and prediction of meteorology factors on influenza is increasing gradually, however, there is currently no evidence on whether its research results are affected by different periods. This study aims to provide limited evidence to reveal this issue.MethodsDaily data on influencing factors and influenza in Xiamen were divided into three parts: overall period (phase AB), non-COVID-19 epidemic period (phase A), and COVID-19 epidemic period (phase B). The association between influencing factors and influenza was analysed using generalized additive models (GAMs). The excess risk (ER) was used to represent the percentage change in influenza as the interquartile interval (IQR) of meteorology factors increases. The 7-day average daily influenza cases were predicted using the combination of bi-directional long short memory (Bi-LSTM) and random forest (RF) through multi-step rolling input of the daily multifactor values of the previous 7-day.ResultsIn periods A and AB, air temperature below 22 °C was a risk factor for influenza. However, in phase B, temperature showed a U-shaped effect on it. Relative humidity had a more significant cumulative effect on influenza in phase AB than in phase A (peak: accumulate 14d, AB: ER = 281.54, 95% CI = 245.47 ~ 321.37; A: ER = 120.48, 95% CI = 100.37 ~ 142.60). Compared to other age groups, children aged 4–12 were more affected by pressure, precipitation, sunshine, and day light, while those aged ≥ 13 were more affected by the accumulation of humidity over multiple days. The accuracy of predicting influenza was highest in phase A and lowest in phase B.ConclusionsThe varying degrees of intervention measures adopted during different phases led to significant differences in the impact of meteorology factors on influenza and in the influenza prediction. In association studies of respiratory infectious diseases, especially influenza, and environmental factors, it is advisable to exclude periods with more external interventions to reduce interference with environmental factors and influenza related research, or to refine the model to accommodate the alterations brought about by intervention measures. In addition, the RF-Bi-LSTM model has good predictive performance for influenza.

Exploring Varicella Vaccine Coverage and Influencing Factors in Rural and Pastoral Children of Qinghai Province: A Cross-Sectional Catch-Up Vaccination Study

&amp;lt;i&amp;gt;Background: &amp;lt;/i&amp;gt;Varicella is a respiratory infectious disease caused by varicella-zoster virus (VZV) infection. Varicella vaccine has been shown to be highly effective in preventing varicella disease, however it is not included in Qinghai Province’s local immunization planning program and must be paid for by families. Its use in local areas is options instead of compulsory, so high coverage is difficult to guarantee. Starting in October 2021, one dose of live attenuated varicella vaccine was recommended at lest for 3-17-year-old children in Qinghai. In 2022, it was conducted that an investigation of varicella vaccine coverage and factors influencing coverage among children in rural rural and pastoral areas to determine the impact of this VarV catch-up policy. &amp;lt;i&amp;gt;Objective: &amp;lt;/i&amp;gt; To explore varicella vaccine coverage and factors influencing caverage among 3-17-year-old children in rural and pastoral areas of Qinghai province. &amp;lt;i&amp;gt;Methods:&amp;lt;/i&amp;gt; A stratified cluster sampling method was used to select children aged 3-17 years from kindergartens and primary /secondary schools in rural and pastoral areas of Qinghai province for a questionnaire-based survey of their guardians. Coverage levels of one and two doses of VarV (VarV&amp;lt;sub&amp;gt;1&amp;lt;/sub&amp;gt; and VarV&amp;lt;sub&amp;gt;2&amp;lt;/sub&amp;gt;) before and after a catch-up vaccination activity initiated in October 2021, and identified factors influenceing VarV&amp;lt;sub&amp;gt;1&amp;lt;/sub&amp;gt; coverage. &amp;lt;i&amp;gt;Results:&amp;lt;/i&amp;gt; VarV&amp;lt;sub&amp;gt;1&amp;lt;/sub&amp;gt; and VarV&amp;lt;sub&amp;gt;2 &amp;lt;/sub&amp;gt;coverage levels after the catch-up activity were 79.06% (676/855) and 43.79% (363/829), respectively, and increased by 34.38 and 24.13 percentage points compared with before the catch-up activity. Multivariate logistic regression showed that VarV&amp;lt;sub&amp;gt;1 &amp;lt;/sub&amp;gt;coverage was higher in rural areas than in pastoral areas (OR=4.63, 95%&amp;lt;I&amp;gt;CI&amp;lt;/I&amp;gt;: 2.91-7.39), and higher among children whose guardians scored 4-6 or 7-10 points on knowledge about varicella and VarV than among children whose guardians scored 0-3 points (OR=8.61, 95%&amp;lt;I&amp;gt;CI&amp;lt;/I&amp;gt;: 4.73-15.69, OR=2.86, 95%&amp;lt;I&amp;gt;CI&amp;lt;/I&amp;gt;: 1.69-4.84). the main reasons for non-vaccination were guardians’ lack of understanding of VarV (48.6%, 87 children), guardians’ unawarness of the need for VarV vaccination (43.6%, 78 children), and unavailability of VarV at vaccination centers (31.3%, 56 children). &amp;lt;i&amp;gt;Conclusions: &amp;lt;/i&amp;gt;The catch-up activity significantly increased VarV coverage among children in the surveyed areas. It should been strengthened that health education on knowledge about varicella and VarV among guardians of children in Qinghai, especially in pastoral areas, to promote VarV vaccination of age-eligible children.

Intelligent generation method of infection risk map and management system in hospital waiting room for respiratory infectious diseases

Respiratory infectious diseases, such as seasonal influenza, pose significant risks to public health safety through airborne transmission. This study aims to explore methods for controlling airborne infection risk in waiting rooms, a hotspot for cross-infection. A database of 990 samples was established by integrating the results of computational fluid dynamics and social force model simulations into the Wells-Riley equation. We introduced two indicators, Pr (Particle Removal Efficiency) and Hr (High-risk Area Ratio), to evaluate the cleanliness performance of waiting room spaces. Additionally, the Sci (Space Cleanliness Index) was proposed as a criterion for evaluating architectural designs and fine-tuning fresh air system operational parameters. We also unveiled the mapping relationship between spatial morphology parameters and ventilation design parameters in relation to the cleanliness performance of waiting rooms. An infection-risk prediction proxy model was established based on machine learning methods, suitable for rapid prediction of spatial infection risks in waiting rooms and optimization of fresh air system operational parameters. The findings can be applied to the selection of hospital design schemes and the optimization of ventilation operational control strategies, aiding in strengthening infectious disease control and reducing the public health safety risks of cross-infection from respiratory infections during peak seasons in hospitals.

Theoretical Investigations of a point mutation affecting H5 Hemagglutinin’s receptor binding preference

The avian influenza A H5N1 virus is a subtype of influenza A virus (IAV) that causes a highly infectious and severe respiratory illness in birds and poses significant economic losses in poultry farming. To infect host cell, the virus uses its surface glycoprotein named Hemagglutinin (HA) to recognize and to interact with the host cell receptor containing either α2,6- (SAα2,6 Gal) or α2,3-linked Sialic Acid (SAα2,3 Gal). The H5N1 virus has not yet acquired the capability for efficient human-to-human transmission. However, studies have demonstrated that even a single amino acid substitution in the HA can switch its glycan receptor preference from the avian-type SAα2,3 Gal to the human-type SAα2,6 Gal. The present study aims to explain the underlying mechanism of a mutation (D94N) on the H5 HA that causes the protein to change its glycan receptor-binding preference using molecular dynamics (MD) simulations. Our results reveal that the mutation alters the electrostatic interactions pattern near the HA receptor binding pocket, leading to a reduced stability for the HA-avian-type SAα2,3 Gal complex. On the other hand, the detrimental effect of the mutation D94N is not observed in the HA-human-type SAα2,6 Gal complex due to the glycan's capability to switch its topology.

Yinqin Qingfei granules alleviate Mycoplasma pneumoniae pneumonia via inhibiting NLRP3 inflammasome-mediated macrophage pyroptosis.

Mycoplasma pneumoniae pneumonia (MPP) is a prevalent respiratory infectious disease in children. Given the increasing resistance of M. pneumoniae (MP) to macrolide antibiotics, the identification of new therapeutic agents is critical. Yinqin Qingfei granules (YQQFG), a Chinese patent medicine formulated specifically for pediatric MPP, lacks a clear explanation of its mechanism. The primary components of YQQFG were identified using LC-MS/MS. In vitro, RAW264.7 cells infected with MP underwent morphological examination via scanning electron microscopy. Drug-containing serum was prepared, and its intervention concentration was determined using the CCK-8 assay. The active components of YQQFG were molecularly docked with NLRP3 protein using Autodock Vina software. A RAW264.7 cell line overexpressing NLRP3 was created using lentivirus to pinpoint the target of YQQFG. In vivo, MPP model mice were established via nasal instillation of MP. Lung damage was assessed by lung index and H&E staining. Pyroptosis-associated protein levels in cells and lung tissue were measured by western blot, while interleukin (IL)-1β and IL-18 levels in cell supernatants and mouse serum were quantified using ELISA. Immunofluorescence double staining of lung tissue sections was conducted to assess the correlation between NLRP3 protein expression and macrophages. The expression of the community-acquired respiratory distress syndrome toxin (CARDS TX) was evaluated by qPCR. 25 effective components with favorable oral bioavailability were identified in YQQFG. Both in vitro and in vivo studies demonstrated that YQQFG substantially reduced the expression of the NLRP3/Caspase-1/GSDMD pathway, decreasing the release of IL-1β and IL-18, and inhibited MP exotoxin. Molecular docking indicated strong affinity between most YQQFG components and NLRP3 protein. Lentivirus transfection and immunofluorescence double staining confirmed that YQQFG significantly suppressed NLRP3 expression in macrophages, outperforming azithromycin (AZM). The combination of YQQFG and AZM yielded the optimal therapeutic effect for MPP. YQQFG mitigates inflammatory responses by suppressing NLRP3 inflammasome-mediated macrophage pyroptosis, thereby ameliorating MP-induced acute lung injury. YQQFG serves as an effective adjunct and alternative medication for pediatric MPP treatment.

Nanoplatform Based Intranasal Vaccines: Current Progress and Clinical Challenges.

Multiple vaccine platforms have been employed to develop the nasal SARS-CoV-2 vaccines in preclinical studies, and the dominating pipelines are viral vectored as protein-based vaccines. Among them, several viral vectored-based vaccines have entered clinical development. Nevertheless, some unsatisfactory results were reported in these clinical studies. In the face of such urgent situations, it is imperative to rapidly develop the next-generation intranasal COVID-19 vaccine utilizing other technologies. Nanobased intranasal vaccines have emerged as an approach against respiratory infectious diseases. Harnessing the power of nanotechnology, these vaccines offer a noninvasive yet potent defense against pathogens, including the threat of COVID-19. The improvements made in vaccine mucosal delivery technologies based on nanoparticles, such as lipid nanoparticles, polymeric nanoparticles, inorganic nanoparticles etc., not only provide stability and controlled release but also enhance mucosal adhesion, effectively overcoming the limitations of conventional vaccines. Hence, in this review, we overview the evaluation of intranasal vaccine and highlight the current barriers. Next, the modern delivery systems based on nanoplatforms are summarized. The challenges in clinical application of nanoplatform based intranasal vaccine are finally discussed.

Design and Analysis of a Contact Piezo Microphone for Recording Tracheal Breathing Sounds.

Analysis of tracheal breathing sounds (TBS) is a significant area of study in medical diagnostics and monitoring for respiratory diseases and obstructive sleep apnea (OSA). Recorded at the suprasternal notch, TBS can provide detailed insights into the respiratory system's functioning and health. This method has been particularly useful for non-invasive assessments and is used in various clinical settings, such as OSA, asthma, respiratory infectious diseases, lung function, and detection during either wakefulness or sleep. One of the challenges and limitations of TBS recording is the background noise, including speech sound, movement, and even non-tracheal breathing sounds propagating in the air. The breathing sounds captured from the nose or mouth can interfere with the tracheal breathing sounds, making it difficult to isolate the sounds necessary for accurate diagnostics. In this study, two surface microphones are proposed to accurately record TBS acquired solely from the trachea. The frequency response of each microphone is compared with a reference microphone. Additionally, this study evaluates the tracheal and lung breathing sounds of six participants recorded using the proposed microphones versus a commercial omnidirectional microphone, both in environments with and without background white noise. The proposed microphones demonstrated reduced susceptibility to background noise particularly in the frequency ranges (1800-2199) Hz and (2200-2599) Hz with maximum deviation of 2 dB and 2.1 dB, respectively, compared to 9 dB observed in the commercial microphone. The findings of this study have potential implications for improving the accuracy and reliability of respiratory diagnostics in clinical practice.

Future projections: the interplay of smoking, infectious respiratory diseases, and vaccination for public health insights.

Future projections: the interplay of smoking, infectious respiratory diseases, and vaccination for public health insights.

Development of a personalized mask design method using three-dimensional scan data

Purpose This study aims to develop a novel design method to make personalized masks for the effective prevention of pandemic respiratory infectious disease.Design/methodology/approachThe changes in facial shape during speaking were analyzed using a three-dimensional (3D) scanning technique. In total, 13 anthropometric items were measured, and mask patterns were generated using a parametric pattern design method. Three sizing methods were proposed to reflect not only static but also dynamic body dimensions on the mask patterns.FindingsA significant increase or decrease was observed in 10 out of 13 measurement items. Based on this, four items were selected to be used in the mask pattern design. The nose and cheek areas of a mask were fixed to protect the respiratory tract against viruses. The lower jaw area was deformed to improve the fit.Social implicationsThis study is expected to provide fundamental data to understand the changes in facial shape during movement. In addition, it is expected that the development of individualized personal protective equipment with movement adaptability will facilitate an effective response to various pandemic respiratory diseases.Originality/valueIn order to develop a personal protective equipment (PPE) that has a good fit and can protect against pandemic respiratory infectious diseases, morphological analysis was attempted using 3D facial data. It would be possible to design various products and equipment to be worn on the face by using the method proposed in this study.