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Abstract Background The burgeoning prevalence of food allergy-related diseases is closely associated with geographical allergen distribution and societal lifestyle paradigms. This study aims to shed light on the distribution patterns of specific IgE (sIgE) and total IgE (tIgE) reactivity to common food allergens in the Southern Chinese populace. Methods Employing an analytical technique spanning two decades, we conducted specific IgE and total IgE on serum samples harvested from patients with food allergy-related pathologies at First Affiliated Hospital of Guangzhou Medical University from 2004 to 2023. This comprehensive examination of eight prototypical food allergens: egg white, milk, wheat, sesame, peanut, soybean, shrimp, and crab. Results Our analysis showed a 100% positivity rate for sIgE and an 86.54% positivity rate for tIgE. Milk had the highest positive response rate, followed by egg white and shrimp. Age-stratified data indicated that milk sensitization peaked in children aged 2 years or younger, while egg white sensitization peaked between 3 and 5 years of age. Sensitization rates for the remaining six allergens increased with age. Additionally, co-sensitization was observed between milk, egg white, crab, and shrimp with other allergens. Conclusion In common allergens of Southern China, egg white, milk, and shrimp ascend as the dominant subjects, underlining their imperative role in food allergy pathogenesis. This landscape-wide allergenic profiling, segregated across age clusters and enhanced by co-sensitization data, augments our power for early diagnosis and strategic intervention in food allergy diseases.

Abstract The prevalence of allergic diseases such as Allergic Rhinitis and Asthma is steadily increasing globally, with pollen allergy being one of the most significant sensitizing factors. However, the cross-reactivity of different pollen allergies remains unclear, posing challenges in the diagnosis and treatment of individuals with multiple sensitivities. In this study, the Component Resolved Diagnosis technique was performed to simultaneously measure the specific IgE concentrations of 52 patients against Art v and its components (Art v 1), Phl p and its components (Phl p 1, Phl p 4, Phl p 5, Phl p 6, Phl p 7, Phl p 12), Bet v and its components (Bet v 1, Bet v 2), Amb a and its component (Amb a 1), and Amb p. Additionally, sIgE inhibition tests were conducted by Art v, Phl p, and Bet v extracts. Among Art v-positive patients, 64.6% showed positivity for Art v 1. In Phl p-positive patients, Phl p 12 had the highest positivity rate (75.0%). Among Bet v-positive patients, 75.6% exhibited positivity for Bet v 2, whereas for Amb a and Amb p-positive patients, 23.7% and 29.0% respectively showed positivity for Amb a 1. The sIgE inhibition assays results revealed that Art v extract had inhibition rates greater than 73.2% against Phl p and its component Phl p 12, as well as Bet v and its component Bet v 2. Simultaneously, Phl p extract showed inhibition rates of 80.70–89.87% against Phl p 12, Bet v and Bet v 2. Bet v extract showed inhibition rates ranging from 21.9 to 59.8% against Phl p and Bet v 2, with a better inhibition rate (76.80%) against Phl p 12. In conclusion, Art v 1 is identified as the principal component of Art v. The profilin proteins of Phl p and Bet v (Phl p 12 and Bet v 2), are implicated as potential cross-reactive elements contributing to polysensitization in patients with respiratory allergies in the Northwest region of China. This cross-reactivity leads to a shared sensitization mechanism among pollen allergens such as Art v, Phl p, and Bet v.

Abstract Background Lung cancer (LC), a paramount global life-threatening condition causing significant mortality, is most commonly characterized by its subtype, lung adenocarcinoma (LUAD). Concomitant with LC, pulmonary fibrosis (PF) and interstitial lung disease (ILD) contribute to an intricate landscape of respiratory diseases. Idiopathic pulmonary fibrosis (IPF) in association with LC has been explored. However, other fibrotic interrelations remain underrepresented, especially for LUAD-PF and LUAD-ILD. Methods We analysed data with statistical analysis from 7,137 healthy individuals, 7,762 LUAD patients, 7,955 ILD patients, and 2,124 complex PF patients collected over ten years. Furthermore, to identify blood indicators related to lung disease and its complications and compare the relationships between different indicators and lung diseases, we successfully applied the naive Bayes model for a biomarker-based prediction of diagnosis and development into complex PF. Results Males predominantly marked their presence in all categories, save for complex PF where females took precedence. Biomarkers, specifically AGR, MLR, NLR, and PLR emerged as pivotal in discerning lung diseases. A machine-learning-driven predictive model underscored the efficacy of these markers in early detection and diagnosis, with NLR exhibiting unparalleled accuracy. Conclusions Our study elucidates the gender disparities in lung diseases and illuminates the profound potential of serum biomarkers, including AGR, MLR, NLR, and PLR in early lung cancer detection. With NLR as a standout, therefore, this study advances the exploration of indicator changes and predictions in patients with pulmonary disease and fibrosis, thereby improving early diagnosis, treatment, survival rate, and patient prognosis.

Abstract Childhood leukemia is a prevalent form of pediatric cancer, with acute lymphoblastic leukemia (ALL) and acute myeloid leukemia (AML) being the primary manifestations. Timely treatment has significantly enhanced survival rates for children with acute leukemia. This study aimed to develop an early and comprehensive predictor for hematologic malignancies in children by analyzing nutritional biomarkers, key leukemia indicators, and granulocytes in their blood. Using a machine learning algorithm and ten indices, the blood samples of 826 children with ALL and 255 children with AML were compared to a control group of 200 healthy children. The study revealed notable differences, including higher indicators in boys compared to girls and significant variations in most biochemical indicators between leukemia patients and healthy children. Employing a random forest model resulted in an area under the curve (AUC) of 0.950 for predicting leukemia subtypes and an AUC of 0.909 for forecasting AML. This research introduces an efficient diagnostic tool for early screening of childhood blood cancers and underscores the potential of artificial intelligence in modern healthcare.

Abstract The upper respiratory tract is the initial site of SARS-CoV-2 infection. Nasal spike-specific secretory immunoglobulin A (sIgA) correlates with protection against Omicron breakthrough infection. We report that intranasal vaccination using human adenovirus serotype 5 (Ad5) vectored Omicron spike in people who previously vaccinated with ancestral vaccine could induce robust neutralizing sIgA in the nasal passage. Nasal sIgA was predominantly present in dimeric and multimeric forms and accounted for nearly 40% of total proteins in nasal mucosal lining fluids (NMLFs). A low-level IgG could also be detected in NMLFs but not IgM, IgD, and IgE. After a complete nasal wash, sIgA in the nasal passage could be replenished rapidly within a few hours. A comparison of purified paired serum IgA, serum IgG, and nasal sIgA from the same individuals showed that sIgA was up to 3-logs more potent than serum antibodies in binding to spikes and in neutralizing Omicron subvariants. Serum IgG and IgA failed to neutralize XBB and BA.2.86, while nasal sIgA retained potent neutralization against these newly emerged variants. Further analysis showed that sIgA was more effective than IgG or IgA in blocking spike-mediated cell-to-cell transmission and protecting hACE2 mice from XBB challenge. Using a sIgA monoclonal antibody as a reference, we estimated that the total nasal sIgA contains about 2.6–3.9% spike-specific sIgA in NMLFs collected approximately one month after intranasal vaccination. Our study provided insights for developing intranasal vaccines that can induce sIgA to build an effective and mutation-resistant first-line immune barrier against constantly emerging variants.

Abstract Background Monocyte-derived alveolar macrophages (Mo_AMs) are increasingly recognised as potential pathogenic factors for idiopathic pulmonary fibrosis (IPF). While scRNAseq analysis has proven valuable in the transcriptome profiling of Mo_AMs, the integration analysis of multi-omics may provide additional dimensions of understanding of these cellular populations. Methods We performed multi-omics analysis on 116 scRNAseq, 119 bulkseq and five scATACseq lung tissue samples from IPF. We built a large-scale IPF scRNAseq atlas and conducted the Monocle 2/3 as well as the Cellchat to explore the developmental path and intercellular communication on Mo_AMs. We also reported the difference in metabolisms, tissue repair and phagocytosis between Mo_AMs and tissue-resident alveolar macrophages (TRMs). To determine whether Mo_AMs affected pulmonary function, we projected clinical phenotypes (FVC%pred) from the bulkseq dataset onto the scRNAseq atlas. Finally, we used scATATCseq to uncover the upstream regulatory mechanisms and determine key drivers in Mo_AMs. Results We identified three Mo_AMs clusters and the trajectory analysis further validated the origin of these clusters. Moreover, via the Cellchat analysis, the CXCL12/CXCR4 axis was found to be involved in the molecular basis of reciprocal interactions between Mo_AMs and fibroblasts through the activation of the ERK pathway in Mo_AMs. SPP1_RecMacs (RecMacs, recruited macrophages) were higher in the low-FVC group than in the high-FVC group. Specifically, compared with TRMs, the functions of lipid and energetic metabolism as well as tissue repair were higher in Mo_AMs than TRMs. But, TRMs may have higher level of phagocytosis than TRMs. SPIB (PU.1), JUNB, JUND, BACH2, FOSL2, and SMARCC1 showed stronger association with open chromatin of Mo_AMs than TRMs. Significant upregulated expression and deep chromatin accessibility of APOE were observed in both SPP1_RecMacs and TRMs. Conclusion Through trajectory analysis, it was confirmed that SPP1_RecMacs derived from Monocytes. Besides, Mo_AMs may influence FVC% pred and aggravate pulmonary fibrosis through the communication with fibroblasts. Furthermore, distinctive transcriptional regulators between Mo_AMs and TRMs implied that they may depend on different upstream regulatory mechanisms. Overall, this work provides a global overview of how Mo_AMs govern IPF and also helps determine better approaches and intervention therapies.

Abstract Background Our study aims to explore the relationship, shared gene signature, and the underlying mechanisms that connect rheumatoid arthritis (RA) to colorectal cancer (CRC). Methods Mendelian randomization (MR) analysis was conducted to assess the causality between RA and CRC. Summary statistic data-based Mendelian randomization (SMR) leveraging eQTL data was employed to identify the CRC-related causal genes. Integrated analyses of single-cell RNA sequencing and bulk RNA sequencing were employed to comprehensively investigate the shared gene signature and potential mechanisms underlying the pathogenesis of both RA and CRC. Predictive analysis of the shared hub gene in CRC immunotherapy response was performed. Pan-cancer analyses were conducted to explore the potential role of MYO9A in 33 types of human tumors. Results MR analysis suggested that RA might be associated with a slight increased risk of CRC (Odds Ratio = 1.04, 95% Confidence Interval = 1.01–1.07, P = 0.005). SMR analysis combining transcriptome analyses identified MYO9A as a causal gene in CRC and a shared gene signature in both RA and CRC. MYO9A may contribute to tumor suppression, while downregulation of MYO9A may impact CRC tumorigenesis by disrupting epithelial polarity and architecture, resulting in a worse prognosis in CRC. Additionally, MYO9A shows promise as a powerful predictive biomarker for cancer prognosis and immunotherapy response in CRC. Pan-cancer analyses demonstrated MYO9A may have a protective role in the occurrence and progression of various human cancers. Conclusion RA might be associated with a slight increased risk of CRC. MYO9A is a shared gene signature and a potential immune-related therapeutic target for both CRC and RA. Targeting the MYO9A-mediated loss of polarity and epithelial architecture could be a novel therapeutic approach for CRC.

Abstract Near-infrared (NIR) hyperspectral imaging is a powerful technique that enables the capture of three-dimensional (3D) spectra-spatial information within the NIR spectral range, offering a wide array of applications. However, the high cost associated with InGaAs focal plane array (FPA) has impeded the widespread adoption of NIR hyperspectral imaging. Addressing this challenge, in this study, we adopt an alternative approach—single-pixel detection for NIR hyperspectral imaging. Our investigation reveals that single-pixel detection outperforms conventional FPA, delivering a superior signal-to-noise ratio (SNR) for both spectral and imaging reconstruction. To implement this strategy, we leverage self-assembled colloidal quantum dots (CQDs) and a digital micromirror device (DMD) for NIR spectral and spatial information multiplexing, complemented by single-pixel detection for simultaneous spectral and image reconstruction. Our experimental results demonstrate successful NIR hyperspectral imaging with a detection window about 600 nm and an average spectral resolution of 8.6 nm with a pixel resolution of 128 × 128. The resulting spectral and spatial data align well with reference instruments, which validates the effectiveness of our approach. By circumventing the need for expensive and bulky FPA and wavelength selection components, our solution shows promise in advancing affordable and accessible NIR hyperspectral imaging technologies, thereby expanding the range of potential applications.

Abstract Blood is critical for health, supporting key functions like immunity and oxygen transport. While studies have found links between common blood clinical indicators and COVID-19, they cannot provide causal inference due to residual confounding and reverse causality. To identify indicators affecting COVID-19, we analyzed clinical data (n = 2,293, aged 18–65 years) from Guangzhou Medical University’s first affiliated hospital (2022-present), identifying 34 significant indicators differentiating COVID-19 patients from healthy controls. Utilizing bidirectional Mendelian randomization analyses, integrating data from over 2.46 million participants from various large-scale studies, we established causal links for six blood indicators with COVID-19 risk, five of which is consistent with our observational findings. Specifically, elevated Troponin I and Platelet Distribution Width levels are linked with increased COVID-19 susceptibility, whereas higher Hematocrit, Hemoglobin, and Neutrophil counts confer a protective effect. Reverse MR analysis confirmed four blood biomarkers influenced by COVID-19, aligning with our observational data for three of them. Notably, COVID-19 exhibited a positive causal relationship with Troponin I (Tnl) and Serum Amyloid Protein A, while a negative association was observed with Plateletcrit. These findings may help identify high-risk individuals and provide further direction on the management of COVID‐19.

Our research aimed to identify new therapeutic targets for Lung adenocarcinoma (LUAD), a major subtype of non-small cell lung cancer known for its low 5-year survival rate of 22%. By employing a comprehensive methodological approach, we analyzed bulk RNA sequencing data from 513 LUAD and 59 non-tumorous tissues, identifying 2,688 differentially expressed genes. Using Mendelian randomization (MR), we identified 74 genes with strong evidence for a causal effect on risk of LUAD. Survival analysis on these genes revealed significant differences in survival rates for 13 of them. Our pathway enrichment analysis highlighted their roles in immune response and cell communication, deepening our understanding. We also utilized single-cell RNA sequencing (scRNA-seq) to uncover cell type-specific gene expression patterns within LUAD, emphasizing the tumor microenvironment’s heterogeneity. Pseudotime analysis further assisted in assessing the heterogeneity of tumor cell populations. Additionally, protein-protein interaction (PPI) network analysis was conducted to evaluate the potential druggability of these identified genes. The culmination of our efforts led to the identification of five genes (tier 1) with the most compelling evidence, including SECISBP2L, PRCD, SMAD9, C2orf91, and HSD17B13, and eight genes (tier 2) with convincing evidence for their potential as therapeutic targets.

Recent experimental and epidemiological studies underscore the vital interaction between the intestinal microbiota and the lungs, an interplay known as the “gut-lung axis”. The significance of this axis has been further illuminated following the identification of intestinal microbial metabolites, such as short-chain fatty acids (SCFA), as key mediators in setting the tone of the immune system. Through the gut-lung axis, the gut microbiota and its metabolites, or allergens, are directly or indirectly involved in the immunomodulation of pulmonary diseases, thereby increasing susceptibility to allergic airway diseases such as asthma. Asthma is a complex outcome of the interplay between environmental factors and genetic predispositions. The concept of the gut-lung axis may offer new targets for the prevention and treatment of asthma. This review outlines the relationships between asthma and the respiratory microbiome, gut microbiome, and environmental microbiome. It also discusses the current advancements and applications of microbiomics, offering novel perspectives and strategies for the clinical management of chronic respiratory diseases like asthma.

Fine particulate matter (PM2.5) has been extensively implicated in the pathogenesis of neurodevelopmental disorders, but the underlying mechanism remains unclear. Recent studies have revealed that PM2.5 plays a role in regulating iron metabolism and redox homeostasis in the brain, which is closely associated with ferroptosis. In this study, the role and underlying mechanism of ferroptosis in PM2.5-induced neurotoxicity were investigated in mice, primary hippocampal neurons, and HT22 cells. Our findings demonstrated that exposure to PM2.5 could induce abnormal behaviors, neuroinflammation, and neuronal loss in the hippocampus of mice. These effects may be attributed to ferroptosis induced by PM2.5 exposure in hippocampal neurons. RNA-seq analysis revealed that the upregulation of iron metabolism-related protein Heme Oxygenase 1 (HO-1) and the activation of mitophagy might play key roles in PM2.5-induced ferroptosis in HT22 cells. Subsequent in vitro experiments showed that PM2.5 exposure significantly upregulated HO-1 in primary hippocampal neurons and HT22 cells. Moreover, PM2.5 exposure activated mitophagy in HT22 cells, leading to the loss of mitochondrial membrane potential, alterations in the expression of autophagy-related proteins LC3, P62, and mTOR, as well as an increase in mitophagy-related protein PINK1 and PARKIN. As a heme-degradation enzyme, the upregulation of HO-1 promotes the release of excess iron, genetically inhibiting the upregulation of HO-1 in HT22 cells could prevent both PM2.5-induced mitophagy and ferroptosis. Furthermore, pharmacological inhibition of mitophagy in HT22 cells reduced levels of ferrous ions and lipid peroxides, thereby preventing ferroptosis. Collectively, this study demonstrates that HO-1 mediates PM2.5-induced mitophagy-dependent ferroptosis in hippocampal neurons, and inhibiting mitophagy or ferroptosis may be a key therapeutic target to ameliorate neurotoxicity following PM2.5 exposure.

Abstract This study is nationwide multicenter epidemiological research, aimed at investigating the distribution changes and seasonal patterns of various airborne allergens among preschool children with allergic rhinitis (AR) in different regions of China, and analyzing the clinical correlation between sensitization to various airborne allergens and AR symptoms in children. Information on children was collected through standard questionnaires, and total IgE (tIgE) and specific IgE (sIgE) for 11 inhalant allergens were tested. The results showed that dust mites are the primary allergens for preschool AR children (39%). Among pollen allergens, Amb a had the highest positivity rate (8.1%), followed by Art v (7.8%). The sensitization rates for two mites peaked in May (46.9% and 40.6%). Art v peaked in August (21.5%), while Amb a had peaks in May (12.7%) and August (17.8%). The sensitization peaks for various tree pollens mainly occurred in August. In the Eastern monsoon region, the sensitization rate to mites was significantly higher than in the Northwest arid and semi-arid regions; whereas, for pollen allergens, the sensitization rates to Amb a, Pla a, Pin a, Pop d, and Bet v were significantly higher in the Northwest arid and semi-arid regions than in the Eastern monsoon region. The correlation among various tree pollens, specifically between Pla a, Pin r, Pop d, and Bet v was strong (0.63 ~ 0.79), with a cross-overlapping percentage of 53.9%. Children with multiple pollen sensitizations had higher cumulative nasal symptom scores than those negative for pollen (P

Abstract Background The rapid emergence and global dissemination of the Omicron variant of SARS-CoV-2 have posed formidable challenges in public health. This scenario underscores the urgent need for an enhanced understanding of Omicron's pathophysiological mechanisms to guide clinical management and shape public health strategies. Our study is aimed at deciphering the intricate molecular mechanisms underlying Omicron infections, particularly focusing on the identification of specific biomarkers. Methods This investigation employed a robust and systematic approach, initially encompassing 15 Omicron-infected patients and an equal number of healthy controls, followed by a validation cohort of 20 individuals per group. The study's methodological framework included a comprehensive multi-omics analysis that integrated proteomics and metabolomics, augmented by extensive bioinformatics. Proteomic exploration was conducted via an advanced Ultra-High-Performance Liquid Chromatography (UHPLC) system linked with mass spectrometry. Concurrently, metabolomic profiling was executed using an Ultra-Performance Liquid Chromatography (UPLC) system. The bioinformatics component, fundamental to this research, entailed an exhaustive analysis of protein–protein interactions, pathway enrichment, and metabolic network dynamics, utilizing state-of-the-art tools such as the STRING database and Cytoscape software, ensuring a holistic interpretation of the data. Results Our proteomic inquiry identified eight notably dysregulated proteins (THBS1, ACTN1, ACTC1, POTEF, ACTB, TPM4, VCL, ICAM1) in individuals infected with the Omicron variant. These proteins play critical roles in essential physiological processes, especially within the coagulation cascade and hemostatic mechanisms, suggesting their significant involvement in the pathogenesis of Omicron infection. Complementing these proteomic insights, metabolomic analysis discerned 146 differentially expressed metabolites, intricately associated with pivotal metabolic pathways such as tryptophan metabolism, retinol metabolism, and steroid hormone biosynthesis. This comprehensive metabolic profiling sheds light on the systemic implications of Omicron infection, underscoring profound alterations in metabolic equilibrium. Conclusions This study substantially enriches our comprehension of the physiological ramifications induced by the Omicron variant, with a particular emphasis on the pivotal roles of coagulation and platelet pathways in disease pathogenesis. The discovery of these specific biomarkers illuminates their potential as critical targets for diagnostic and therapeutic strategies, providing invaluable insights for the development of tailored treatments and enhancing patient care in the dynamic context of the ongoing pandemic.

Abstract Background Numerous studies have documented significant alterations in the bodily fluids of Chronic Obstructive Pulmonary Disease (COPD) patients. However, existing literature lacks causal inference due to residual confounding and reverse causality. Methods Summary-level data for COPD were obtained from two national biobanks: the UK Biobank, comprising 1,605 cases and 461,328 controls, and FinnGen, with 6,915 cases and 186,723 controls. We also validated our findings using clinical data from 2,690 COPD patients and 3,357 healthy controls from the First Affiliated Hospital of Guangzhou Medical University. A total of 44 bodily fluid biomarkers were selected as candidate risk factors. Mendelian randomization (MR) and meta-analyses were used to evaluate the causal effects of these bodily fluids on COPD and lung function (FEV1/FVC). Results Mendelian randomization (MR) and meta-analyses, by integrating data from the UK Biobank and FinnGen cohort, found that 3 bodily fluids indicators (HDLC, EOS, and TP) were causally associated with the risk of COPD, two (EOS and TP) of which is consistent with our observational findings. Moreover, we noticed EOS and TP were causally associated with the risk of lung function (FEV1/FVC). Conclusions The MR findings and clinical data highlight the independent and significant roles of EOS and TP in the development of COPD and lung function (FEV1/FVC), which might provide a deeper insight into COPD risk factors and supply potential preventative strategies.

IntroductionInfection with SARS-CoV-2 begins in the upper respiratory tract and can trigger the production of mucosal spike-specific secretory IgA (sIgA), which provides protection against reinfection. It has been recognized that individuals with high level of nasal spike-specific IgA have a lower risk of reinfection. However, mucosal spike-specific sIgA wanes over time, and different individuals may have various level of spike-specific sIgA and descending kinetics, leading to individual differences in susceptibility to reinfection. A method for detecting spike-specific sIgA in the nasal passage would be valuable for predicting the risk of reinfection so that people at risk can have better preparedness.MethodsIn this study, we describe the development of a colloidal gold-based immunochromatographic (ICT) strip for detecting SARS-CoV-2 Omicron spike-specific sIgA in nasal mucosal lining fluids (NMLFs).ResultsThe ICT strip was designed to detect 0.125 μg or more spike-specific sIgA in 80 μL of NMLFs collected using a nasal swab. Purified nasal sIgA samples from individuals who recently recovered from an Omicron BA.5 infection were used to demonstrate that this ICT strip can specifically detect spike-specific sIgA. The signal levels positively correlated with neutralizing activities against XBB. Subsequent analysis revealed that people with low or undetectable levels of spike-specific sIgA in the nasal passage were more susceptible to SARS-CoV-2 reinfection.ConclusionsThis nasal spike-specific sIgA ICT strip provides a non-invasive, rapid, and convenient method to assess the risk of reinfection for achieving precision preparedness.

BackgroundSepsis is a major contributor to global morbidity and mortality, affecting millions each year. Notwithstanding the decline in sepsis incidence and mortality over decades, gender disparities in sepsis outcomes persist, with research suggesting higher mortality rates in males.MethodsThis retrospective study aims to delineate gender-specific clinical biomarker profiles impacting sepsis progression and mortality by examining sepsis cases and related clinical data from the past three years. Propensity score matching was used to select age-matched healthy controls for comparison.ResultsAmong 265 sepsis patients, a significantly higher proportion were male (60.8%, P

Abstract Research has shown that the concentration and composition of biological samples may change after long-term ultra-low temperature storage. Consequently, this study examined the effect of ultra-low temperature storage on serum sIgE detection by comparing sIgE concentrations at various durations from the time of sample storage to subsequent testing. We selected 40 serum samples from the Guangzhou Medical University Affiliated First Hospital Biobank, which had been tested for house dust mites, dog hair, tobacco mold, cockroaches, and cow milk allergen sIgE. Samples were categorized by storage duration: 14 samples stored for 10 years, 12 for 5 years, and 14 for 3 years. They were also classified by sIgE positive levels: 15 samples at levels 1–2, 15 at levels 3–4, and 10 at levels 5–6. The allergen sIgE of these samples was retested using the same technology. Regardless of the type of allergen or the level of positivity, the majority of sIgE concentrations measured at the time of storage were higher than the current measurements, but the difference was not statistically significant. The correlation between the sIgE results at the time of storage and the current results was high for samples stored for 10 years (rs = 0.991, P

Abstract Interstitial lung diseases (ILDs), also known as diffuse lung diseases, pose a significant challenge to the respiratory health of individuals worldwide. Among these conditions, idiopathic pulmonary fibrosis (IPF) is one of the most prevalent, contributing substantially to morbidity and mortality. However, IPF is characterized by high heterogeneity, presenting a substantial obstacle to clinical program development and scientific research due to significant variations in disease progression, treatment response, and prognosis. Recent advances in metabolomics have enabled the identification of specific biochemical pathways and disease biomarkers, offering a beacon of hope for patients afflicted with various diseases. Remarkably, metabolomics has made significant strides in ILDs, particularly in IPF. Metabonomics, a branch of life science, provides an in‐depth analysis of metabolic pathways and the specific biological molecular composition of omics, obtained primarily from biological samples such as serum, plasma, pleural effusion, bronchoalveolar lavage fluid, lung surgical biopsy samples, urine, feces, sputum, and cerebrospinal fluid. In this review, we aim to provide a comprehensive overview of the application of metabolomics in ILDs, with a particular focus on IPF. By summarizing the current state of research in this field, we hope to shed light on the latest advances, challenges, and opportunities that metabolomics can provide in managing ILDs.

Abstract This study aims to reduce the cost of allergen testing for Guangzhou, China by limiting the number of allergens for which patients are tested, and provide a testing panel to improve diagnostic and therapeutic efficiency. This retrospective study of real-world data from 2012 to 2019 included 39,570 patients with suspected allergies in Guangzhou, southern China. All the patients were tested for one or more of the following allergens serum specific immunoglobulin E (sIgE): Dermatophagoides pteronyssinus, Dermatophagoides farinae, cat dander, dog dander, Artemisia vulgaris, Aspergillus fumigatus, Alternaria alternata, Blattella germanica, egg whites, milk, wheat, peanuts, soybeans, Cancer pagurus, and Penaeus monodon by PhadiaCAP 1000. Totally, only the positive rates of allergens sIgE in D. farinae, D. pteronyssinus, milk, egg whites, B. germanica, C. pagurus, A. alternata, and P. monodon were > 10%, the other allergens were between 4–7%. Moreover, among the allergic diseases, dust mites exhibited the overall highest positive rate, followed by milk and B. germanica. In children, milk was the main allergen, whereas in adults, mites, cockroaches, shrimp, and crab allergens had higher positive rates. The optimal scale analysis shows that the multiple sensitization classification of patients can be divided into three categories: I D. farinae and D. pteronyssinus; II. C. pagurus, P. monodon, and B. germanica; III. Milk and egg whites. Generally, a panel including 4 allergens can detect > 90% of the potential allergy in this local population. In Guangzhou, southern China, D. farinae, milk, B. germanica, and A. alternata as a panel screening allergy for suspected allergic patients was suggested base on this study.

Summary: During the persistent COVID-19 pandemic, the swift progression of acute myocarditis has emerged as a profound concern due to its augmented mortality, underscoring the urgency of prompt diagnosis. This study analyzed blood samples from 5,230 COVID-19 individuals, identifying key blood and myocardial markers that illuminate the relationship between COVID-19 severity and myocarditis. A predictive model, applying Bayesian and random forest methodologies, was constructed for myocarditis' early identification, unveiling a balanced gender distribution in myocarditis cases contrary to a male predominance in COVID-19 occurrences. Particularly, older men exhibited heightened vulnerability to severe COVID-19 strains. The analysis revealed myocarditis was notably prevalent in younger demographics, and two subvariants COVID-19 progression paths were identified, characterized by symptom intensity and specific blood indicators. The enhanced myocardial marker model displayed remarkable diagnostic accuracy, advocating its valuable application in future myocarditis detection and treatment strategies amidst the COVID-19 crisis.

BackgroundRecent studies have demonstrated the relevance of circulating factors in the occurrence and development of colorectal cancer (CRC); however, the causal relationship remains unclear.MethodsSummary-level data for CRC were obtained from the UK Biobank (5,657 cases and 372,016 controls), FinnGen cohort (3,022 cases and 215,770 controls), and BioBank Japan Project (BBJ, 7,062 cases and 195,745 controls). Thirty-two peripheral markers with consistent definitions were collected from the three biobanks. Mendelian randomization (MR) was used to evaluate the causal effect of circulating factors on CRC. The effects from the three consortiums were combined using trans-ancestry meta-analysis methods.ResultsOur analysis provided compelling evidence for the causal association of higher genetically predicted eosinophil cell count (EOS, odds ratio [OR], 0.8639; 95% confidence interval [CI] 0.7922-0.9421) and red cell distribution width (RDW, OR, 0.9981; 95% CI, 0.9972-0.9989) levels with a decreased risk of CRC. Additionally, we found suggestive evidence indicating that higher levels of total cholesterol (TC, OR, 1.0022; 95% CI, 1.0002-1.0042) may increase the risk of CRC. Conversely, higher levels of platelet count (PLT, OR, 0.9984; 95% CI, 0.9972-0.9996), total protein (TP, OR, 0.9445; 95% CI, 0.9037-0.9872), and C-reactive protein (CRP, OR, 0.9991; 95% CI, 0.9983-0.9999) may confer a protective effect against CRC. Moreover, we identified six ancestry-specific causal factors, indicating the necessity of considering patients' ancestry backgrounds before formulating prevention strategies.ConclusionsMR findings support the independent causal roles of circulating factors in CRC, which might provide a deeper insight into early detection of CRC and supply potential preventative strategies.

Background: Body mass index (BMI) is known to affect the outcomes of spirometry indices. However, its association with spirometry indices in COPD and asthma is less studied. We aimed to explore the impact of BMI on these patients.Methods: Patients with COPD or asthma who completed bronchodilator tests (BDTs) between 2017 and 2021 were reviewed. Spirometry indices were compared among patients with COPD or asthma that were subclassified as underweight (BMI< 18.5 kg/m2), normal weight (≥18.5 to < 25), overweight (≥ 25 to < 30), and obesity (≥ 30). Results.Results: Analysis was conducted on 3891 COPD patients (age:66.5 ± 7.8 years) and 1208 asthma patients (age:59.7 ± 7.5 years). COPD patients classified as underweight demonstrated significantly lower values of pre-and post FEV1 (L, %), pre-and post FVC (L, %), and pre- and post-FEV1/FVC (all p < 0.05). In contrast, COPD patients who were overweight or obese exhibited higher values for pre-and post FEV1 (L, %), and pre and post FEV1/FVC (all p < 0.05). Within the cohort of asthma patients, those underweight had lower pre-and post FEV1 (L, %), pre and post FVC (L, %), pre and post FEV1/FVC %. Obese asthma patients displayed higher pre and post FEV1/FVC (all p < 0.05).Conclusion: Significant BMI category differences in spirometry indices can be seen in patients with COPD or asthma. Both underweight and obesity could affect the diagnosis and severity of these diseases. Recognizing these effects is essential to better management and diagnosis of these patients.

AbstractPurpose Few risk-forecasting models of allergic rhinitis (AR) exist that may aid AR pre-exposure prophylaxis (PrEP) in clinical practice. Therefore, this study aimed to develop and validate an effective clinical model for identifying candidates for AR PrEP using a routine medical questionnaire.Methods This study was conducted in 10 Chinese provinces with 13 medical centers (n = 877) between 2019 and 2021. Clinical characteristics and exposure history were collected via face-to-face interviews. Well-trained physicians diagnosed patients with AR based on skin prick test results and clinical performance. The least absolute shrinkage and selection operator model was used to identify potential risk factors for AR, and the logistic regression model was used to construct the risk-forecasting model. Predictive power and model reliability were assessed using area under the receiver operating characteristic curve and calibration curves, respectively.Results This study diagnosed 625 patients with AR who had positive responses to at least one indoor or outdoor allergen and 460 to at least one outdoor pollen allergen. Two nomograms were established to identify two types of AR with various sensitization patterns. Both models had an area under curve of approximately 0.7 in the development and internal validation datasets. Additionally, our findings found good agreement for the calibration curves of both models.Conclusion Early identification of candidates for AR PrEP using routine medical information may improve the deployment of limited resources and effective health management. Our models showed good performance in predicting AR; therefore, they can serve as potential automatic screening tools to identify AR PrEP candidates.

Abstract Background Astigmatic mites contain potent allergens that can trigger IgE‐mediated immune responses, leading to allergic diseases such as asthma, allergic rhinitis and atopic dermatitis. In house dust mites Dermatophagoides pteronyssinus and Dermatophagoides farinae, group 1 allergens (Der p 1 and Der f 1), characterized as papain‐like cysteine proteases, have been defined as the major allergens that have high prevalence and potency. Previous studies of mite group 1 allergens mainly focused on identification, comparison of sequence and structure, as well as the investigation of cross‐reactivity. To achieve a comprehensive view of mite group 1 allergens, we performed a comparative genomic analysis of all the cysteine proteases in six astigmatic mite species to elucidate the evolutionary relationships of group 1 allergens. Methods Based on the high‐quality and annotated genomes, all the cysteine proteases in six astigmatic mite species were identified by sequence homology search. The phylogenetic relationships, gene synteny and expression levels were revealed by bioinformatic tools. The allergenicity of recombinant cysteine proteases was evaluated by enzyme‐linked immunosorbent assay. Results Tandem duplication was revealed as the major feature of cysteine protease gene evolution in astigmatic mites. The high IgE‐binding capacity and the significant expression level of the cysteine protease DP_007902.01 suggested its potential as a novel group 1 allergen of D. pteronyssinus. In addition, gene decay events were identified in the skin‐burrowing parasitic mite Sarcoptes scabiei. Conclusion This comprehensive analysis provided insights into the evolution of cysteine proteases, as well as the component‐resolved diagnosis of mite allergies.

Abstract Background Immune dysfunction and oxidative stress caused by severe pneumonia can lead to multiple organ dysfunction and even death, causing a significant impact on health and the economy. Currently, great progress has been made in the diagnosis and treatment of this disease, but the mortality rate remains high (approximately 50%). Therefore, there is still potential for further exploration of the immune response mechanisms against severe pneumonia. Objective This study analyzed the difference in serum metabolic profiles between patients with severe pneumonia and health individuals through metabolomics, aiming to uncover the correlation between the Tryptophan‐Kynurenine pathway and the severity of severe pneumonia, as well as N‐3/N‐6 polyunsaturated fatty acids (PUFAs). Methods In this study, 44 patients with severe pneumonia and 37 health controls were selected. According to the changes in the disease symptoms within the 7 days of admission, the patients were divided into aggravation (n = 22) and remission (n = 22) groups. Targeted metabolomics techniques were performed to quantify serum metabolites and analyze changes between groups. Results Metabolomics analysis showed that serum kynurenine and kynurenine/tryptophan (K/T) were significantly increased and tryptophan was significantly decreased in patients with severe pneumonia; HETE and HEPE in lipids increased significantly, while eicosapentaenoic acid (EPA), docosapentaenoic acid (DPA), docosahexaenoic acid (DHA), α‐linolenic acid (linolenic acid, α‐LNA), arachidonic acid (ARA), Dihomo‐γ‐linolenic acid (DGLA), and 13(s)‐hydroperoxylinoleic acid (HPODE) decreased significantly. Additionally, the longitudinal comparison revealed that Linolenic acid, DPA, and Tryptophan increased significantly in the remission group, while and kynurenine and K/T decreased significantly. In the aggravation group, Kynurenine and K/T increased significantly, while ARA, 8(S)‐hydroxyeicosatetraenoic acid (HETE), 11(S)‐HETE, and Tryptophan decreased significantly. The correlation analysis matrix demonstrated that Tryptophan was positively correlated with DGLA, 12(S)‐hydroxyeicosapentaenoic acid (HEPE), ARA, EPA, α‐LNA, DHA, and DPA. Kynurenine was positively correlated with 8(S)‐HETE and negatively correlated with DHA. Additionally, K/T was negatively correlated with DGLA, ARA, EPA, α‐LNA, DHA, and DPA. Conclusion This study revealed that during severe pneumonia, the Tryptophan‐Kynurenine pathway was activated and was positively correlated with the disease progression. On the other hand, the activation of the Tryptophan‐Kynurenine pathway was negatively correlated with N‐3/N‐6 PUFAs.

The detection of allergen-specific IgE antibodies is an important biomarker for the diagnosis and treatment monitoring of allergic diseases. And the pre-analytical phase is an important part of the overall quality of the laboratory. In this study, 44 patients with allergic diseases (including 23 patients with allergic rhinitis, 12 patients with allergic rhinitis and asthma, and 9 patients with allergic dermatitis) were included in the outpatient center of the Department of Allergy, the First Affiliated Hospital of Guangzhou Medical University. We mixed the serums of the above 44 patients (approximately 0.8 ml of serum volume per patient) into a large volume of serum pool (about 35 ml in total) and divided into 26 parts. And 26 serum samples were stored at 4 different temperatures for 90 days to observe the stability of sIgE antibodies to 16 allergens in serum. The results show that serum sIgE antibody titers in patients with allergic diseases show significant stability during 90 days of storage, even at room temperature. Good stability even after up to 10 freeze-thaw cycles under low temperature storage conditions.

Objectives: Rabies is an acute lethal infectious disease caused by a lyssavirus infection. In 2018, the World Health Organization proposed a global strategic plan to end human rabies deaths by 2030. However, systematic studies on the global rabies disease burden and epidemiological trends are scarce. Methods: We extracted the disease burden and epidemiological data of rabies worldwide in the preceding 30 years from the Global Burden of Disease Study 2019 and performed a comprehensive analysis. Results: In 2019, the incident cases of rabies worldwide were 14,075.51 (95% uncertainty interval: 6124.33-21,618.11), and the number of deaths was 13,743.44 (95% uncertainty interval: 6019.13-17,938.53), both of which were lower than that in 1990. With the improvement of the sociodemographic index, the incident cases, the number of deaths, age-standardized incidence rate, age-standardized incidence death rate, and disability-adjusted life years of rabies all showed downward trends. Adolescents and adults aged

Purpose The relationship between childhood blood eosinophils and subtypes of allergic diseases remains understudied. This study aimed to examine the associations between childhood blood eosinophils and subtypes of asthma, rhinitis and dermatitis, as well as the modifying effect of age.Methods We obtained concurrent blood cell counts and serum Immunoglobulin E (IgE) test results in 5026 children (0–13, years) from First Affiliated Hospital of Guangzhou Medical University from 2014 to 2019. Generalized additive models with multivariable adjustments were utilized to model the exposure-response relationship between eosinophils and allergic symptoms. The robustness of the association was assessed in two age categories (

In vaccinees who were infected with SARS-CoV in 2003, we observed greater antibody responses against spike and nucleoprotein of both SARS-CoV-2 and SARS-CoV after a single dosage of inactivated SARS-CoV-2 vaccine. After receiving the second vaccination, antibodies against RBD of SARS-CoV-2 Wuhan, Beta, Delta, and recently emerged Omicron are significantly higher in SARS-CoV experienced vaccinees than in SARS-CoV naïve vaccinees. Neutralizing activities measured by authentic viruses and pseudoviruses of SARS-CoV, SARS-CoV-2 Wuhan, Beta, and Delta are greater in SARS-CoV experienced vaccinees. In contrast, only weak neutralizing activities against SARS-CoV-2 and variants were detected in SARS-CoV naïve vaccinees. By 6 months after the second vaccination, neutralizing activities were maintained at a relatively higher level in SARS-CoV experienced vaccinees but were undetectable in SARS-CoV naïve vaccinees. These findings suggested a great possibility of developing a universal vaccine by heterologous vaccination using spike antigens from different SARS-related coronaviruses.

Abstract Background This cross‐sectional study aimed to identify latent sensitization profiles of asthma patients in mainland China, unveiling the association between regional differences and sensitization patterns. Methods 1056 asthma participants from 10 medical centers divided into eastern and western cohorts were clustered into four individual sensitization patterns, respectively, by using an unsupervised statistical modeling method, latent class analysis (LCA), based on the levels of 12 aeroallergens specific IgE reactivities. Moreover, differences in clinical characteristics and environmental exposures were compared in different sensitization patterns. Results Four distinct sensitization patterns in the two cohorts were defined as follows, respectively. Eastern cohort: Class 1: “High weed pollen and house dust mites (HDMs) sensitization” (8.87%), Class 2: “HDMs dominated sensitization” (38.38%), Class 3: “High HDMs and animal dander sensitization” (6.95%), Class 4: “Low/no aeroallergen sensitization” (45.80%). Western cohort: Class 1: “High weed pollen sensitization” (26.14%), Class 2: “High multi‐pollen sensitization” (15.02%), Class 3: “HDMs‐dominated sensitization” (10.33%), Class 4: “Low/no aeroallergen sensitization” (48.51%). Of note, the significant statistical difference in age, asthma control test score (ACT) and comorbidities were observed within or between different sensitization patterns. Exposure factors in different sensitization patterns were pointed out. Conclusions Asthmatic patients with distinct sensitization patterns were clustered and identified through the LCA method, disclosing the relationship between sensitization profiles of multiple aeroallergens and geographical differences, providing novel insights and potential strategies for atopic disease monitoring, management and prevention in clinical practice.

BackgroundRecently emerged reports indicated that patients with coronavirus disease 2019 (COVID-19) might experience novo genitourinary symptoms after discharge. Nevertheless, the causal associations and underlying mechanisms remain largely unclear.MethodsGenome-wide association study (GWAS) statistics for COVID-19 and 28 genitourinary symptoms with consistent definitions were collected from the COVID‐19 Host Genetic Initiative, FinnGen, and UK Biobanks. Mendelian randomization (MR) analyses were applied to explore the causal effects of COVID-19 on genitourinary symptoms by selecting single-nucleotide polymorphisms as instrumental variables. Meta-analyses were conducted to evaluate the combined causal effect. Molecular pathways connecting COVID-19 and its associated disorders were evaluated by weighted gene co-expression network analysis (WGCNA) and enrichment analyses to extract insights into the potential mechanisms underlying the connection.ResultsThe MR and meta-analyses indicated that COVID-19 was causally associated with increased risk for calculus of the lower urinary tract (LUTC, OR: 1.2984 per doubling in odds of COVID‐19, 95% CI: 1.0752–1.5680, p = 0.007) and sexual dysfunction (SD, OR: 1.0931, 95% CI: 1.0292–1.1610, p = 0.004). Intriguingly, COVID-19 might exert a slight causal protective effect on the progression of urinary tract infections (UTIs) and bladder cancer (BLCA). These results were robust to sensitivity analyses. Bioinformatic analyses indicated that the inflammatory-immune response module may mediate the links between COVID‐19 and its associated disorders at the molecular level.ConclusionsIn response to post-COVID-19 symptoms, we recommend that COVID-19 patients should strengthen the prevention of LUTC and the monitoring of sexual function. Meanwhile, the positive effects of COVID-19 on UTIs and BLCA should attach equal importance.

Background: No comprehensive multicenter study of sensitization patterns among patients with allergic rhinitis (AR) to various common pollen allergens was available nationwide, and risks factors of pollen-induced allergic rhinitis (PiAR) in mainland China was unclear. This study aimed to fill this gap. Methods: A multicenter study was performed on 736 AR patients aged below 18 from four regions of mainland China. Patients completed a standardized questionnaire asking for the environmental risk factors and AR severity, and undertook skin prick tests (SPT) with 14 common pollen allergens. Findings: Among the 736 patients, 341 patients (46.33%) suffered at least one positive pollen allergen sensitization. The positive rate of pollen allergens was significantly higher in the high-age group (Damato et al., 2007; Wang et al., 2018; Luo et al., 2016; Demoly et al., 2011; Sampson and Albergo, 1984; Li et al., 2009; Luo et al., 2021; Ziska and Beggs, 2011; Melén et al., 2020; Jensen-Jarolim, 2017; Rönmark et al., 2017; Ge et al., 2017) [6-17] than the low-age group ( ≤ 5), while no significant difference was found between the sexes. The sensitizations to pollen allergens varied widely among four geographical areas. The positive rate was higher in north China and west China than in east China, and south China had the lowest positive rate. The region of residence, ages, ethnic minorities, history of pollen exposure, the material of living room floor and material of pillow were statistically significant risks of PiAR. Interpretation: This study provides new insights into the pollen allergens sensitization characteristics in AR and the factors affecting PiAR in mainland China.

Background: The prevalence of allergic diseases has increased significantly in China over the last few decades, and there have been very few reports of allergic diseases in certain occupational specialties, with almost no reports among sanitation workers. Objective: Our objective was to investigate the prevalence of allergic diseases and the prevalence of common allergen sensitization in the population engaged in sanitation, and to try to answer the connection between urban garbage waste exposure and the development of allergic diseases. Methods: We conducted a cross-sectional survey of people working in sanitation-related jobs in Liwan District, Guangzhou, China. A total of 893 people completed the questionnaire for this study, and 500 of them were further screened and tested for allergens specific IgE and IgG4. Combining the questionnaire and test results, we investigated the incidence of allergy disorders and patterns of sensitization to allergens in this community, and evaluated the presence of occupational-related risk factors in this particular population. Results: Of the 893 sanitation workers, 166 (18.59%) self-reported allergic diseases, predominantly suffering from allergic rhinitis (AR) (n = 98, 10.97%), followed by drug allergy (n = 31, 3.47%), atopic dermatitis (n = 27, 3.02%), food allergy (n = 21, 2.35%), and asthma (n = 9, 1.00%), in that order. In addition to dust mites (32.20%), which had the highest sensitization rate, the subject population had relatively high sensitization rates to ragweed (7.00%) and moulds mixture (8.20%) when compared with the rates of sensitization to moulds and ragweed in the general population; the top 3 sIgG4 positivity rates were egg (50.00%), milk (10.20%), and soybean (9.40%). The prevalence of self-reported AR was higher in office managers (the control group) than in cleaning staff (the exposed group), but there was no difference in sIgE positivity for serum allergens between the 2 groups. The chance of having AR may increase with management positions (crude OR 2.20, 95% CI 1.38–3.50), P = 0.001). Conclusion: This is the first study to investigate the prevalence of allergy illnesses in the sanitation workforce in mainland China. We identified a community of real sanitation workers with high ragweed and mycobacterial sensitization rates. Urban cleaning may be protective factor against AR at the symptom level, but the serological results did not show this to be the case.

COVID-19 pandemic is a global public health emergency. Despite extensive research, there are still few effective treatment options available today. Neutralizing-antibody-based treatments offer a broad range of applications, including the prevention and treatment of acute infectious diseases. Hundreds of SARS-CoV-2 neutralizing antibody studies are currently underway around the world, with some already in clinical applications. The development of SARS-CoV-2 neutralizing antibody opens up a new therapeutic option for COVID-19. We intend to review our current knowledge about antibodies targeting various regions (i.e., RBD regions, non-RBD regions, host cell targets, and cross-neutralizing antibodies), as well as the current scientific evidence for neutralizing-antibody-based treatments based on convalescent plasma therapy, intravenous immunoglobulin, monoclonal antibodies, and recombinant drugs. The functional evaluation of antibodies (i.e., in vitro or in vivo assays) is also discussed. Finally, some current issues in the field of neutralizing-antibody-based therapies are highlighted.

Abstract Background Smoking is believed as one of the major risk factors resulting in a variety of non-communicable diseases, such as lung cancer and chronic respiratory diseases (CRDs). However, the global burden of CRDs attributed to smoking has not been systematically studied, particularly across different temporal and spatial scales. Methods We conducted a systematic analysis of the Global Burden of CRDs and related risk factors using data from the Global Burden of Disease Study 2019. Incidence, death, risk factors, and other parameters such as estimated annual percentage change have been analyzed. We also compared various risk factors across regions, countries, and genders. Results Globally, the incidence of CRDs and deaths cases have increased in the last 30 years, while the corresponding age-standardized incidence rate (ASIR) and death rate (ASDR) have declined. Smoking was the leading risk factor for the death of CRDs all over the world. However, in low and low-middle Socio-demographic Index (SDI) areas, particulate matter pollution was the main risk factor leading to death from CRDs, while smoking was ranked first among the major risk factors in areas with middle, middle-high, or high SDI. Globally, gender differences in morbidity and mortality from CRDs were observed. Males had slightly more cases and ASIR of chronic respiratory diseases than females over the last 30 years. However, the mortality cases and ASDR in males were significantly higher than that of females. Furthermore, the ASDR of all major risk factors, specially smoking, was higher in men than in women. Conclusions CRDs were still major threats human health. The current study highlights the dominating roles of smoking for death risks resulting from CRDs, followed by PM pollution. Therefore, tobacco control and improving air quality are key to reducing deaths from CRDs.

Abstract The newly identified Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) has resulted in a global health emergency (COVID-19) because of its rapid spread and high mortality. Since the virus epidemic, many pathogenic mechanisms have been revealed, and virus-related vaccines have been successfully developed and applied in clinical practice. However, the pandemic is still developing, and new mutations are still emerging. Virus pathogenicity is closely related to the immune status of the host. As innate immunity is the body’s first defense against viruses, understanding the inhibitory effect of SARS-CoV-2 on innate immunity is of great significance for determining the target of antiviral intervention. This review summarizes the molecular mechanism by which SARS-CoV-2 escapes the host immune system, including suppressing innate immune production and blocking adaptive immune priming. Here, on the one hand, we devoted ourselves to summarizing the combined action of innate immune cells, cytokines, and chemokines to fine-tune the outcome of SARS-CoV-2 infection and the related immunopathogenesis. On the other hand, we focused on the effects of the SARS-CoV-2 on innate immunity, including enhancing viral adhesion, increasing the rate of virus invasion, inhibiting the transcription and translation of immune-related mRNA, increasing cellular mRNA degradation, and inhibiting protein transmembrane transport. This review on the underlying mechanism should provide theoretical support for developing future molecular targeted drugs against SARS-CoV-2. Nevertheless, SARS-CoV-2 is a completely new virus, and people’s understanding of it is in the process of rapid growth, and various new studies are also being carried out. Although we strive to make our review as inclusive as possible, there may still be incompleteness.

Abstract House dust mites (HDM) are one of the important factors of airway allergic diseases, HDM allergens can be detected in the human gut mucosa, which induces local inflammation and increases intestinal epithelial permeability. This study tests a hypothesis that HDM contribute to the development of OVA (ovalbumin)-induced intestinal allergy. The serum levels of IgE against HDM in patients with food allergy were detected with UniCAP100 (Pharmacia, Uppsala, Sweden); a mouse model of food allergy was developed with OVA and HDM as the specific antigens. Compared to healthy controls, patients with food allergy have higher levels of serum HDM-specific IgE. Compared to food allergy alone groups, the levels of HDM-specific IgE in patients with food allergy and asthma or allergic rhinitis were significantly higher. In mouse models, we found that HDM/OVA induced allergy-like symptoms, lower body temperature, and lower body weight. The levels of IgE, IgG1, mMCP-1 (mouse mast cell protease-1), IL-4 and IL-5 in the HDM and HDM + CT (cholera toxin) groups were higher than the control groups, and the levels of IgE, IgG1, IL-4 and IL-5 in the HDM, OVA and HDM + OVA groups were higher than the control groups. The pathological changes of intestinal tissues in the HDM and HDM + CT/the HDM, OVA and HDM + OVA groups were more severe, more eosinophil infiltration than the control groups. Moreover, exposure to HDM induced intestinal barrier dysfunction, and facilitated the development of intestinal allergy in mice. In conclusion, HDM exposure enhances immune responses to OVA-induced food allergy.

Abstract. Objective:. The coronavirus disease 2019 (COVID-19) epidemic resulting from severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has still spread globally. The occurrence of the Delta variant, which is more infectious and spreads faster than earlier forms of the virus that causes COVID-19, makes infection prevention more challenging. Therefore, this study aimed to gain a comprehensive insight into the transmission routes of SARS-CoV-2 for curbing the propagation of SARS-CoV-2 in human populations. Methods:. We studied a prospective cohort of 576 patients admitted consecutively to the First Affiliated Hospital of Guangzhou Medical University from January 21 to June 8, 2020. These patients were chosen based on their similar clinical phenotypes or imaging findings. There were 21 (3.6%) laboratory-confirmed COVID-19 patients (16 severe and 5 mild cases) and 555 non-COVID-19 patients. The antibody response and routes and duration of viral shedding were systematically evaluated in serial clinical specimens. Moreover, SARS-CoV-2 RNA was also detected in a mouth rinse, urine, and tear samples. This study was approved by the Medical Ethical Committee of The First Affiliated Hospital of Guangzhou Medical University (approval No. 2020-77). Results:. SARS-CoV-2 mainly existed in sputum, nasal and throat swabs, and feces samples. Virus latency was longer in sputum and feces samples than in nasopharyngeal samples. IgG antibody response in respiratory samples was related to disease severity. Although droplets and aerosols are the major transmission routes for COVID-19, covert routes of transmission from asymptomatic patients, contaminated surfaces, and wastewater are also of interest. Conclusion:. Our findings provide a solid foundation for developing prophylactic measures against SARS-CoV-2.

The COVID-19 pandemic has highlighted the urgent need for accurate, rapid, and cost-effective diagnostic methods to identify and track the disease. Traditional diagnostic methods, such as PCR and serological assays, have limitations in terms of sensitivity, specificity, and timeliness. To investigate the potential of using protein–peptide hybrid microarray (PPHM) technology to track the dynamic changes of antibodies in the serum of COVID-19 patients and evaluate the prognosis of patients over time. A discovery cohort of 20 patients with COVID-19 was assembled, and PPHM technology was used to track the dynamic changes of antibodies in the serum of these patients. The results were analyzed to classify the patients into different disease severity groups, and to predict the disease progression and prognosis of the patients. PPHM technology was found to be highly effective in detecting the dynamic changes of antibodies in the serum of COVID-19 patients. Four polypeptide antibodies were found to be particularly useful for reflecting the actual status of the patient’s recovery process and for accurately predicting the disease progression and prognosis of the patients. The findings of this study emphasize the multi-dimensional space of peptides to analyze the high-volume signals in the serum samples of COVID-19 patients and monitor the prognosis of patients over time. PPHM technology has the potential to be a powerful tool for tracking the dynamic changes of antibodies in the serum of COVID-19 patients and for improving the diagnosis and prognosis of the disease.

ObjectiveVaccination is effective tool for preventing and controlling SARS-CoV-2 infections, and inactivated vaccines are the most widely used type of vaccine. In order to identify antibody-binding peptide epitopes that can distinguish between individuals who have been vaccinated and those who have been infected, this study aimed to compare the immune responses of vaccinated and infected individuals.MethodsSARS-CoV-2 peptide microarrays were used to assess the differences between 44 volunteers inoculated with the inactivated virus vaccine BBIBP-CorV and 61 patients who were infected with SARS-CoV-2. Clustered heatmaps were used to identify differences between the two groups in antibody responses to peptides such as M1, N24, S15, S64, S82, S104, and S115. Receiver operating characteristic curve analysis was used to determine whether a combined diagnosis with S15, S64, and S104 could effectively distinguish infected patients from vaccinated individuals.ResultsOur findings showed that the specific antibody responses against S15, S64, and S104 peptides were stronger in vaccinators than in infected persons, while responses to M1, N24, S82, and S115 were weaker in asymptomatic patients than in symptomatic patients. Additionally, two peptides (N24 and S115) were found to correlate with the levels of neutralizing antibodies.ConclusionOur results suggest that antibody profiles specific to SARS-CoV-2 can be used to distinguish between vaccinated individuals and those who are infected. The combined diagnosis with S15, S64, and S104 was found to be more effective in distinguishing infected patients from those who have been vaccinated than the diagnosis using individual peptides. Moreover, the specific antibody responses against the N24 and S115 peptides were found to be consistent with the changing trend of neutralizing antibodies.

Background. SARS-CoV-2 induces apoptosis and amplifies the immune response by continuously stressing the endoplasmic reticulum (ER) after invading cells. This study aimed to establish a protein-metabolic pathway associated with ER dysfunction based on the invasion mechanism of SARS-CoV-2. Methods. This study included 17 healthy people and 46 COVID-19 patients, including 38 mild patients and 8 severe patients. Proteomics and metabolomics were measured in the patient plasma collected at admission and one week after admission. The patients were further divided into the aggravation and remission groups based on disease progression within one week of admission. Results. Cross-sectional comparison showed that endoplasmic reticulum molecular chaperone-binding immunoglobulin protein (ERC-BiP), angiotensinogen (AGT), ceramide acid (Cer), and C-reactive protein (CRP) levels were significantly increased in COVID-19 patients, while the sphingomyelin (SM) level was significantly decreased P

IntroductionLung cancer is a serious global health concern, and its subtypes are closely linked to lifestyle and dietary habits. Recent research has suggested that malnutrition, over-nutrition, electrolytes, and granulocytes have an effect on the development of cancer. This study investigated the impact of combining patient nutritional indicators, electrolytes, and granulocytes as comprehensive predictors for lung cancer treatment outcomes, and applied a machine learning algorithm to predict lung cancer.Methods6,336 blood samples were collected from lung cancer patients classified as lung squamous cell carcinoma (LUSC), lung adenocarcinoma (LUAD), and small cell lung cancer (SCLC). 2,191 healthy individuals were used as controls to compare the differences in nutritional indicators, electrolytes and granulocytes among different subtypes of lung cancer, respectively.ResultsOur results demonstrated significant differences between men and women in healthy people and NSCLC, but no significant difference between men and women in SCLC patients. The relationship between indicators is basically that the range of indicators for cancer patients is wider, including healthy population indicators. In the process of predicting lung cancer through nutritional indicators by machine learning, the AUC of the random forest model was as high as 93.5%, with a sensitivity of 75.9% and specificity of 96.5%.DiscussionThis study supports the feasibility and accuracy of nutritional indicators in predicting lung cancer through the random forest model. The successful implementation of this novel prediction method could guide clinicians in providing both effective diagnostics and treatment of lung cancers.

Due to the molecular heterogeneity, most bladder cancer (BLCA) patients show no pathological responses to immunotherapy and chemotherapy yet suffer from their toxicity. This study identified and validated three distinct and stable molecular clusters of BLCA in cross-platform databases based on personalized immune and inflammatory characteristics. H&E-stained histopathology images confirmed the distinct infiltration of immune and inflammatory cells among clusters. Cluster-A was characterized by a favorable prognosis and low immune and inflammatory infiltration but showed the highest abundance of prognosis-related favorable immune cell and inflammatory activity. Cluster-B featured the worst prognosis and high immune infiltration, but numerous unfavorable immune cells exist. Cluster-C had a favorable prognosis and the highest immune and inflammatory infiltration. Based on machine learning, a highly precise predictive model (immune and inflammatory responses signature, IIRS), including FN1, IL10, MYC, CD247, and TLR2, was developed and validated to identify the high IIRS-score group that had a poor prognosis and advanced clinical characteristics. Compared to other published models, IIRS showed the highest AUC in 5 years of overall survival (OS) and a favorable predictive value in predicting 1- and 3- year OS. Moreover, IIRS showed an excellent performance in predicting immunotherapy and chemotherapy’s response. According to immunohistochemistry and qRT-PCR, IIRS genes were differentially expressed between tumor tissues with corresponding normal or adjacent tissues. Finally, immunohistochemical and H&E-stained analyses were performed on the bladder tissues of 13 BLCA patients to further demonstrate that the IIRS score is a valid substitute for IIR patterns and can contribute to identifying patients with poor clinical and histopathology characteristics. In conclusion, we established a novel IIRS depicting an IIR pattern that could independently predict OS and acts as a highly precise predictive biomarker for advanced clinical characters and the responses to immunotherapy and chemotherapy.

Background: The global pandemic of COVID-19 is caused by the rapidly evolving severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). The clinical presentation of SARS-CoV-2 Omicron variant infection varies from asymptomatic to severe disease with diverse symptoms. However, the underlying mechanisms responsible for these symptoms remain incompletely understood. Methods: Transcriptome datasets from peripheral blood mononuclear cells (PBMCs) of COVID-19 patients infected with the Omicron variant and healthy volunteers were obtained from public databases. A comprehensive bioinformatics analysis was performed to identify hub genes associated with the Omicron variant. Hub genes were validated using quantitative RT-qPCR and clinical data. DSigDB database predicted potential therapeutic agents. Results: Seven hub genes (IFI44, IFI44L, MX1, OAS3, USP18, IFI27, and ISG15) were potential biomarkers for Omicron infection’s symptomatic diagnosis and treatment. Type I interferon-related hub genes regulated Omicron-induced symptoms, which is supported by independent datasets and RT-qPCR validation. Immune cell analysis showed elevated monocytes and reduced lymphocytes in COVID-19 patients, which is consistent with retrospective clinical data. Additionally, ten potential therapeutic agents were screened for COVID-19 treatment, targeting the hub genes. Conclusions: This study provides insights into the mechanisms underlying type I interferon-related pathways in the development and recovery of COVID-19 symptoms during Omicron infection. Seven hub genes were identified as promising biological biomarkers for diagnosing and treating Omicron infection. The identified biomarkers and potential therapeutic agent offer valuable implications for Omicron’s clinical manifestations and treatment strategies.

Currently, breast cancer (BRCA) has become the most common cancer in the world, whose pathological mechanism is complex. Among its subtypes, triple-negative breast cancer (TNBC) has the worst prognosis. With the increasing number of diagnosed TNBC patients, the urgent need of novel biomarkers is also rising. Cyclin-dependent kinase inhibitor 2A (CDKN2A) has recently emerged as a key regulator associated with ferroptosis and cuproptosis (FAC) and has exhibited a significant effect on BRCA, but its detailed mechanism remains elusive. Herein, we conducted the first converge comprehensive landscape analysis of FAC-related gene CDKN2A in BRCA and disclosed its prognostic value in BRCA. Then, an unsupervised cluster analysis based on CDKN2A-correlated genes unveiled three subtypes, namely cold-immune subtype, IFN-γ activated subtype and FTL-dominant subtype. Subsequent analyses depicting hallmarks of tumor microenvironment (TME) among three subtypes suggested strong association between TNBC and CDKN2A. Given the fact that the most clinically heterogeneous TNBC always displayed the most severe outcomes and lacked relevant drug targets, we further explored the potential of immunotherapy for TNBC by interfering CDKN2A and constructed the CDKN2A-derived prognostic model for TNBC patients by Lasso-Cox. The 21-gene–based prognostic model showed high accuracy and was verified in external independent validation cohort. Moreover, we proposed three drugs for TNBC patients based on our model via targeting epidermal growth factor receptor. In summary, our study indicated the potential of CDKN2A as a pioneering prognostic predictor for TNBC and provided a rationale of immunotherapy for TNBC, and offered fresh perspectives and orientations for cancer treatment via inducing ferroptosis and cuproptosis to develop novel anti-cancer treatment strategies.

Background: The impact of deaths and disability-adjusted life years (DALYs) caused by air pollution in China has not been well elucidated. We aimed to analyze the association of air pollution with deaths and DALYs in the Chinese population.Methods: We extracted data on burden due to deaths and disability-adjusted life years attributed to air pollution in the previous 30 years in China from the Global Burden of Disease (GBD) study 2019 and performed a comprehensive analysis and summary.Results: 1.85 (95% UI: 1.57–2.17) million Chinese people lost their lives as a result of air pollution in 2019, a slight decrease from 1990. In 2019, the disability-adjusted life years (DALYs) caused by air pollution in China was 42.51 (95% UI: 36.34–49.48) million, a 30.2% decrease from 1990. From 1990 to 2019, both age-standardized death rate (ASDR) and age-standardized DALYs due to air pollution in China showed a significant year-on-year downward trend. Air pollution–related deaths and DALYs occurred mostly in people over the age of 50 years. Stroke, ischemic heart disease, and chronic obstructive pulmonary disease were attributed the maximum death burden due to air pollution in China in 2019.Conclusion: Over the past 30 years, air pollution has brought a heavy disease burden to China, and in the future, joint efforts are required to improve the air quality.

Levels of neutralizing antibodies (NAb) after vaccine against coronavirus disease 2019 (COVID-19) can be detected using a variety of methods. A critical challenge is how to apply simple and accurate methods to assess vaccine effect. In a population inoculated with three doses of the inactivated Sinopharm/BBIBP vaccine, we assessed the performance of chemiluminescent immunoassay (CLIA) in its implementation to detect severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) specific antibodies, as well as the antibody kinetics of healthcare workers throughout the course of vaccination. The antibody levels of NAb, the receptor-binding-domain (RBD) antibodies and IgG peaked one month after the second and remained at a relatively high level for over three months after the booster injection, while IgM and IgA levels remained consistently low throughout the course of vaccination. The production of high-level neutralizing antibodies is more likely when the inoculation interval between the first two doses is within the range of one to two months, and that between the first and booster dose is within 230 days. CLIA showed excellent consistency and correlation between NAb, RBD, and IgG antibodies with the cytopathic effect (CPE) conventional virus neutralization test (VNT). Receiver operating characteristic (ROC) analysis revealed that the optimal cut-off levels of NAb, RBD and IgG were 61.77 AU/ml, 37.86 AU/ml and 4.64 AU/ml, with sensitivity of 0.833, 0.796 and 0.944, and specificity of 0.768, 0.750 and 0.625, respectively, which can be utilized as reliable indicators of COVID-19 vaccination immunity detection.