Mechanism of intestinal microbiota disturbance promoting the occurrence and development of esophageal squamous cell carcinoma--based on microbiomics and metabolomics.

Esophageal squamous cell carcinoma (ESCC) is a high-risk malignant tumor that has been reported in China. Some studies indicate that gut microbiota disorders can affect the occurrence and development of ESCC, but the underlying mechanism remains unclear. In this study, we aimed to explore the possible underlying mechanisms using microbiomics and metabolomics. Fifty ESCC patients and fifty healthy controls were selected as the study subjects according to sex and age, and fecal samples were collected. 16S rDNA sequencing and LC‒MS were used for microbiomics and nontargeted metabolomics analyses. We found significant differences in the composition of the gut microbiota and metabolites between the ESCC patients and control individuals (P < 0.05). ESCC patients exhibited increased abundances of Fusobacteriaceae and Lactobacillus, increased levels of GibberellinA34 and decreased levels of 12-hydroxydodecanoic acid; these metabolites could be diagnostic and predictive markers of ESCC. An increase in the abundance of Enterobacteriaceae and Lactobacillus significantly reduced the content of L-aspartate and pantothenic acid, which may be involved in the occurrence and development of ESCC by downregulating the expression of proteins in the pantothenate and coenzyme A biosynthesis pathways. An imbalance in the intestinal flora may decrease the number of eosinophils in peripheral blood, resulting in the activation of an inflammatory response and immune dysfunction, leading to ESCC deterioration. We hypothesize that this imbalance in the gut microbiota can cause an imbalance in intestinal metabolites, which can activate carcinogenic metabolic pathways, affect inflammation and immune function, and play a role in the occurrence and development of ESCC.

Hospitalization, case fatality, comorbidities, and isolated pathogens of adult inpatients with pneumonia from 2013 to 2022: a real-world study in Guangzhou, China.

BACKGROUND: In the context of increasing population aging, ongoing drug-resistant pathogens and the COVID-19 epidemic, the changes in the epidemiological and clinical characteristics of patients with pneumonia remain unclear. This study aimed to assess the trends in hospitalization, case fatality, comorbidities, and isolated pathogens of pneumonia-related adult inpatients in Guangzhou during the last decade. METHODS: We retrospectively enrolled hospitalized adults who had doctor-diagnosed pneumonia in the First Affiliated Hospital of Guangzhou Medical University from January 1, 2013 to December 31, 2022. A natural language processing system was applied to automatically extract the clinical data from electronic health records. We evaluated the proportion of pneumonia-related hospitalizations in total hospitalizations, pneumonia-related in-hospital case fatality, comorbidities, and species of isolated pathogens during the last decade. Binary logistic regression analysis was used to assess predictors for patients with prolonged length of stay (LOS). RESULTS: A total of 38,870 cases were finally included in this study, with 70% males, median age of 64 (53, 73) years and median LOS of 7.9 (5.1, 12.8) days. Although the number of pneumonia-related hospitalizations showed an upward trend, the proportion of pneumonia-related hospitalizations decreased from 199.6 per 1000 inpatients in 2013 to 123.4 per 1000 in 2021, and the case fatality decreased from 50.2 per 1000 in 2013 to 23.9 per 1000 in 2022 (all P < 0.05). The most common comorbidities were chronic obstructive pulmonary disease, lung malignancy, cardiovascular diseases and diabetes. The most common pathogens were Pseudomonas aeruginosa, Candida albicans, Acinetobacter baumannii, Stenotrophomonas maltophilia, Klebsiella pneumoniae, and Staphylococcus aureus. Glucocorticoid use during hospitalization (Odd Ratio [OR] = 1.86, 95% Confidence Interval (CI): 1.14-3.06), immunosuppressant use during hospitalization (OR = 1.99, 1.14-3.46), ICU admission (OR = 16.23, 95%CI: 11.25-23.83), receiving mechanical ventilation (OR = 3.58, 95%CI: 2.60-4.97), presence of other underlying diseases (OR = 1.54, 95%CI: 1.15-2.06), and elevated procalcitonin (OR = 1.61, 95%CI: 1.19-2.19) were identified as independent predictors for prolonged LOS. CONCLUSION: The proportion of pneumonia-related hospitalizations and the in-hospital case fatality showed downward trends during the last decade. Pneumonia inpatients were often complicated by chronic underlying diseases and isolated with gram-negative bacteria. ICU admission was a significant predictor for prolonged LOS in pneumonia inpatients.

Combining small airway parameters with conventional parameters obtained during spirometry to diagnose airflow obstruction: A cross-sectional study.

BACKGROUND AND OBJECTIVE: The use of small airway parameters generated by spirometry, namely forced expiratory flow between 25% and 75% of forced vital capacity (FVC) (FEF25%-75%) and forced expiratory flow at 50% and 75% of FVC (FEF50% and FEF75%, respectively), is widely discussed. We evaluated the importance of these spirometric parameters in a large Chinese population. METHODS: We conducted a cross-sectional observational study in which spirometry and bronchodilator responsiveness (BDR) data were collected in a healthcare centre from May 2021 to August 2022 and in a tertiary hospital from January 2017 to March 2022. Discordance was assessed between the classification of test results by the large airway parameters of forced expiratory volume in 1 second (FEV1) and FEV1/FVC ratio and by the small airway parameters of FEF25%-75%, FEF75% and FEF50%. The predictive power of Z-scores of spirometric parameters for airflow limitation and BDR was assessed using receiver operating characteristic curves. RESULTS: Our study included 26,658 people. Among people with a normal FVC (n = 14,688), 3.7%, 4.5% and 3.6% of cases exhibited normal FEV1/FVC ratio but impaired FEF25%-75%, FEF75% and FEF50%, respectively, while 6.8%-7.0% of people exhibited normal FEV1 but impaired FEF25%-75%, FEF75% and FEF50%. Using the Z-scores of combining both large and small airway parameters in spirometry showed the best area under the curve for predicting airflow limitation (0.90; 95% CI 0.87-0.94) and predicting BDR (0.72; 95% CI 0.71-0.73). CONCLUSION: It is important to consider both large and small airway parameters in spirometry to avoid missing a diagnosis of airflow obstruction.

Supervised training models with or without manual lesion delineation outperform clinicians in distinguishing pulmonary cryptococcosis from lung adenocarcinoma on chest CT.

BACKGROUND: The role of artificial intelligence (AI) in the discrimination between pulmonary cryptococcosis (PC) and lung adenocarcinoma (LA) warrants further research. OBJECTIVES: To compare the performances of AI models with clinicians in distinguishing PC from LA on chest CT. METHODS: Patients diagnosed with confirmed PC or LA were retrospectively recruited from three tertiary hospitals in Guangzhou. A deep learning framework was employed to develop two models: an undelineated supervised training (UST) model utilising original CT images, and a delineated supervised training (DST) model utilising CT images with manual lesion annotations provided by physicians. A subset of 20 cases was randomly selected from the entire dataset and reviewed by clinicians through a network questionnaire. The sensitivity, specificity and accuracy of the models and the clinicians were calculated. RESULTS: A total of 395 PC cases and 249 LA cases were included in the final analysis. The internal validation results for the UST model showed a sensitivity of 85.3%, specificity of 81.0%, accuracy of 83.6% and an area under the curve (AUC) of 0.93. Similarly, the DST model exhibited a sensitivity of 88.2%, specificity of 88.1%, accuracy of 88.2% and an AUC of 0.94. The external validation of the two models yielded AUC values of 0.74 and 0.77, respectively. The average sensitivity, specificity and accuracy of 102 clinicians were determined to be 63.1%, 53.7% and 59.3%, respectively. CONCLUSIONS: Both models outperformed the clinicians in distinguishing between PC and LA on chest CT, with the UST model exhibiting comparable performance to the DST model.

Comprehensive appraisal of lung function in young COPD patients: a single center observational study.

PURPOSE: The present study aimed to investigate the clinical characteristics and lung function impairment in young people diagnosed with chronic obstructive pulmonary disease (COPD). PATIENTS AND METHODS: We retrospectively enrolled patients with COPD who underwent symptom assessment and comprehensive pulmonary function tests at the First Affiliated Hospital of Guangzhou Medical University between August 2017 and March 2022. The patients were categorized into two groups based on age: a young COPD group (aged 20-50 years) and an old COPD group (aged > 50 years). RESULTS: A total of 1282 patients with COPD were included in the study, with 76 young COPD patients and 1206 old COPD patients. Young COPD patients exhibited a higher likelihood of being asymptomatic, lower rates of smoking, and a lower smoking index compared to old COPD patients. Although young COPD patients had higher median post-bronchodilator forced expiratory volume in 1 s (post-BD FEV1) (1.4 vs.1.2 L, P = 0.019), diffusing capacity of the lung for carbon monoxide (DLCO) (7.2 vs. 4.6, P<0.001), and a lower median residual volume to total lung capacity ratio (RV/TLC) compared to their older counterparts, there were no differences observed in severity distribution by GOLD categories or the proportion of lung hyperinflation (RV/TLC%pred > 120%) between two groups. Surprisingly, the prevalence of reduced DLCO was found to be 71.1% in young COPD, although lower than in old COPD (85.2%). CONCLUSION: Young COPD showed fewer respiratory symptoms, yet displayed a similar severity distribution by GOLD categories. Furthermore, a majority of them demonstrated lung hyperinflation and reduced DLCO. These results underscore the importance of a comprehensive assessment of lung function in young COPD patients.

Association between mixed metal exposure and stroke risk in Shanxi Province: a case-control study.

BACKGROUND: Stroke is the second leading cause of death for all human beings and poses a serious threat to human health. Environmental exposure to a mixture of metals may be associated with the occurrence and development of stroke, but the evidence in the Chinese population is not yet conclusive. OBJECTIVES: This study evaluated the association between stroke risk and 13 metals METHODS: Metal concentrations in whole blood samples from 100 stroke cases and 100 controls were measured by ICP-MS. The cumulative impact of mixed metal on stroke risk was investigated by using three statistical models, BKMR, WQS and QGC. RESULTS: The case group had higher concentrations of Mg, Mn, Zn, Se, Sn, and Pb than the control group (p<0.05). BKMR model indicated a correlation between the risk of stroke and exposure to mixed metals. WQS model showed that Mg (27.2 %), Se (25.1 %) and Sn (14.8 %) were positively correlated with stroke risk (OR=1.53; 95 %Cl: 1.03-2.37, p=0.013). The QGC model showed that Mg (49.2 %) was positively correlated with stroke risk, while Ti (31.7 %) was negatively correlated with stroke risk. CONCLUSIONS: Mg may be the largest contributor to the cumulative effect of mixed metal exposure on stroke risk, and the interaction between metals requires more attention. These findings could provide scientific basis for effectively preventing stroke by managing metals in the environment.

Establishment and application of reference equations for FEF50 and FEF75 in the Chinese population.

Background: Reference equations for forced expiratory flow at 50% and 75% of forced vital capacity (FVC) (FEF50 and FEF75) in the Chinese population are lacking. It is of great importance to establish equations covering most age groups and to study their applicability in clinical practice. Methods: Using the lambda-mu-sigma (LMS) method, reference equations for FEF50 and FEF75 were constructed based on pulmonary function data from healthy subjects collected from January 2007 to June 2010 at 24 centers throughout China. Differences between the established equations and extraneous equations were compared using standardized means (Z values) and percentage errors (PE). The proportion of small airway dysfunction (SAD) defined by the present equations was calculated. The Fisher precision probability test and the Mann-Whitney test were used to analyze the magnitude of changes in small and large airway indices after bronchodilator inhalation in patients with suspected asthma and chronic obstructive pulmonary disease (COPD). Results: Reference equations for FEF50 and FEF75 were established based on data from 7,115 healthy individuals (aged 4 to 80 years, 50.9% female, height between 95 and 190 cm). The present equations (all Z values were -0.0 and PE ranged from 2.0% to 4.2%) showed advantages over the European Community for Steel and Coal (ECSC) equations in 1993 (with Z values ranging from -0.7 to -0.2 and PE ranged from -23.4% to -4.5%). A total of 4,356 patients with suspected asthma (51.1% female; a mean age of 45.4 years) and 6,558 patients with suspected COPD (10.1% female; a mean age of 65.0 years) were included. The present equations defined 95.7% and 99.9% of SAD in these patients. After bronchodilator inhalation, greater mean improvement rates in small airway indices were observed both in patients with suspected asthma [mean ± standard deviation (SD) =48%±47%] and in patients with suspected COPD (mean ± SD =20%±30%) (P<0.05). Conclusions: The reference equations for FEF50 and FEF75 established in this study should be considered for use in China. Further studies are needed to validate their value in the diagnosis of some chronic respiratory diseases.

Effect of YuPingFeng granules on clinical symptoms of stable COPD: study protocol for a multicenter, double-blind, and randomized controlled trial.

BACKGROUND: Reducing current clinical symptoms and the risks of future exacerbations is the main goal of stable COPD management. Traditional Chinese medicine has unique advantages in chronic disease management. YuPingFeng (YPF), as a classical prescription, has been proven to reduce the risk of exacerbations, but there is a lack of high-quality evidence for the assessment of clinical symptoms and quality of life, particularly for the assessment of treatment response of microecology and immunity. METHODS/DESIGN: This is a prospective, multicentre, randomized, double-blind, placebo-controlled clinical trial. A total of 316 eligible subjects with moderate to severe COPD will be randomized 1:1 to receive YPF or placebo. Participants will receive either YPF or a placebo at 5 g three times daily for 52 weeks. The primary outcome will be the change in the COPD Assessment Test (CAT) score after 52 weeks of treatment. Secondary outcomes will include changes in the St George's Respiratory Questionnaire (SGRQ) score and clinical symptom score, among others. Outcomes will be measured at each visit. The study will continue for 52 weeks and will include six visits to each subject (at day 0 and weeks 4,12,24,36 and 52). In the event of exacerbations, subjects will be required to go back to the hospital once on the first day of exacerbation or when their condition permits. DISCUSSION: This trial will provide research methods to evaluate the clinical efficacy, safety, and the possible mechanism of YPF in the treatment of stable moderate-to-severe COPD patients. In addition, we hope to provide more possibilities for TCM to participate in the management of stable COPD. TRIAL REGISTRATION: The trial was registered at the Chinese Clinical Trials Registry on 3 June 2022 (ChiCTR2200060476; date recorded: 3/6/2022, https://www.chictr.org.cn/ ).

Unraveling the independent role of METTL3 in m6A modification and tumor progression in esophageal squamous cell carcinoma.

METTL3 and METTL14 are traditionally posited to assemble the m6A methyltransferase complex in a stoichiometric 1:1 ratio, modulating mRNA fate via m6A modifications. Nevertheless, recent investigations reveal inconsistent expression levels and prognostic significance of METTL3 and METTL14 across various tumor types, challenging their consistent functional engagement in neoplastic contexts. A pan-cancer analysis leveraging The Cancer Genome Atlas (TCGA) data has identified pronounced disparities in the expression patterns, functional roles, and correlations with tumor burden between METTL3 and METTL14, particularly in esophageal squamous cell carcinoma (ESCC). Knockdown experiments of METTL3 in EC109 cells markedly suppress cell proliferation both in vitro and in vivo, whereas METTL14 knockdown shows a comparatively muted effect on proliferation and does not significantly alter METTL3 protein levels. mRNA sequencing indicates that METTL3 singularly governs the expression of 1615 genes, with only 776 genes co-regulated with METTL14. Additionally, immunofluorescence co-localization studies suggest discrepancies in cellular localization between METTL3 and METTL14. High-performance liquid chromatography-mass spectrometry (HPLC-MS) analyses demonstrate that METTL3 uniquely associates with the Nop56p-linked pre-rRNA complex and mRNA splicing machinery, independent of METTL14. Preliminary bioinformatics and multi-omics investigations reveal that METTL3's autonomous role in modulating tumor cell proliferation and its involvement in mRNA splicing are potentially pivotal molecular mechanisms. Our study lays both experimental and theoretical groundwork for a deeper understanding of the m6A methyltransferase complex and the development of targeted tumor therapies focusing on METTL3.

Mendelian randomization analysis identifies druggable genes and drugs repurposing for chronic obstructive pulmonary disease.

Background: Chronic obstructive pulmonary disease (COPD) is a prevalent condition that significantly impacts public health. Unfortunately, there are few effective treatment options available. Mendelian randomization (MR) has been utilized to repurpose existing drugs and identify new therapeutic targets. The objective of this study is to identify novel therapeutic targets for COPD. Methods: Cis-expression quantitative trait loci (cis-eQTL) were extracted for 4,317 identified druggable genes from genomics and proteomics data of whole blood (eQTLGen) and lung tissue (GTEx Consortium). Genome-wide association studies (GWAS) data for doctor-diagnosed COPD, spirometry-defined COPD (Forced Expiratory Volume in one second [FEV1]/Forced Vital Capacity [FVC] <0.7), and FEV1 were obtained from the cohort of FinnGen, UK Biobank and SpiroMeta consortium. We employed Summary-data-based Mendelian Randomization (SMR), HEIDI test, and colocalization analysis to assess the causal effects of druggable gene expression on COPD and lung function. The reliability of these druggable genes was confirmed by eQTL two-sample MR and protein quantitative trait loci (pQTL) SMR, respectively. The potential effects of druggable genes were assessed through the phenome-wide association study (PheWAS). Information on drug repurposing for COPD was collected from multiple databases. Results: A total of 31 potential druggable genes associated with doctor-diagnosed COPD, spirometry-defined COPD, and FEV1 were identified through SMR, HEIDI test, and colocalization analysis. Among them, 22 genes (e.g., MMP15, PSMA4, ERBB3, and LMCD1) were further confirmed by eQTL two-sample MR and protein SMR analyses. Gene-level PheWAS revealed that ERBB3 expression might reduce inflammation, while GP9 and MRC2 were associated with other traits. The drugs Montelukast (targeting the MMP15 gene) and MARIZOMIB (targeting the PSMA4 gene) may reduce the risk of spirometry-defined COPD. Additionally, an existing small molecule inhibitor of the APH1A gene has the potential to increase FEV1. Conclusions: Our findings identified 22 potential drug targets for COPD and lung function. Prioritizing clinical trials that target these identified druggable genes with existing drugs or novel medications will be beneficial for the development of COPD treatments.

Assessing the effectiveness of inhalation therapy in patients with chronic airway diseases: A new digital measurement.

BACKGROUND: This study aimed to evaluate the effectiveness of inhalation therapy in patients with chronic airway diseases via the use of a new multiparametric inhalation assessment device. METHODS: A multiparametric inhalation evaluation device (PF810, UBREATH, Zhejiang, China) that could simulate common inhalation devices with 6 different levels (0-V) of resistance was used in this study. The device was considered suitable if the three parameters of peak inspiratory flow rate (PIFR), effective inspiratory time (EIT), and breath-hold time (BHT) after inspiration met the minimum requirements. RESULTS: A total of 4,559 tests were performed. The qualification rates of 0-V resistance gear from low to high were 3.38 % (I), 8.42 % (0), 15.31 % (II), 16.71 % (III), 20.27 % (IV), and 46.91 % (V). The COPD patients in the 3 experimental groups had the lowest percentages of isolates classified as resistant 0, III, and V, which were 5.65 %, 11.93 %, and 40.43 %, respectively. The lowest percentage was 39.67 % (V) for insufficient EIT and 18.40 % (V) for BHT less than 5 s after inspiration. The results of 149 subjects who had used the inhalation device showed that the VIE and EIT at 0 levels were significantly greater than those before training (Z= -5.651, -5.646, P < 0.001). The VIE and EIT at I-III and V significantly increased after training (all P < 0.05). CONCLUSIONS: Patients using portable inhaler devices do not always inhale with adequate flow patterns. The multiparametric inhalation assessment device may be useful in outpatient settings.

Prevalence, Medicaid use and mortality risk of low FEV1 in adults aged 20-35 years old in the USA: evidence from a population-based retrospective cohort study.

BACKGROUND: The prevalence, Medicaid use and mortality risk associated with low forced expiratory volume in 1 s (FEV1) among young adults aged 20-35 years are not well understood, despite its potential implications for the development of chronic pulmonary disease and overall prognosis. METHODS: A retrospective cohort study was conducted among young adults aged 20-35 years old, using data from the National Health and Nutrition Examination Survey, National Death Index and Centers for Medicare & Medicaid Services. Participants were categorised into a low FEV1 group (pre-bronchodilator FEV1%pred <80%) and a normal FEV1 group (FEV1%pred ≥80%). Weighted logistic regression analysis was employed to identify the risk factors associated with low FEV1, while Cox proportional hazard models were used to calculate the hazard ratio (HR) for Medicaid use and the all-cause mortality between the two groups. RESULTS: A total of 5346 participants aged 20-35 were included in the study, with 329 in the low FEV1 group and 5017 in the normal group. The weighted prevalence of low FEV1 among young adults was 7.1% (95% CI 6.0 to 8.2). Low body mass index (OR=3.06, 95% CI 1.79 to 5.24), doctor-diagnosed asthma (OR=2.25, 1.28 to 3.93), and wheezing or whistling (OR=1.57, 1.06 to 2.33) were identified as independent risk factors for low FEV1. Over a 15-year follow-up, individuals in the low FEV1 group exhibited a higher likelihood of Medicaid use compared with those in the normal group (HR=1.73, 1.07 to 2.79). However, there was no statistically significant increase in the risk of all-cause mortality over a 30-year follow-up period (HR=1.48, 1.00 to 2.19). CONCLUSIONS: A considerable portion of young adults demonstrated low FEV1 levels, a characteristic that was associated with a higher risk of Medicaid use over a long-term follow-up, yet not linked to an augmented risk of all-cause mortality.

Forest carbon stocks increase with higher dominance of ectomycorrhizal trees in high latitude forests.

Understanding the mechanisms controlling forest carbon accumulation is crucial for predicting and mitigating future climate change. Yet, it remains unclear whether the dominance of ectomycorrhizal (EcM) trees influences the carbon accumulation of entire forests. In this study, we analyzed forest inventory data from over 4000 forest plots across Northeast China. We find that EcM tree dominance consistently exerts a positive effect on tree, soil, and forest carbon stocks. Moreover, we observe that these positive effects are more pronounced during unfavorable climate conditions, at lower tree species richness, and during early successional stages. This underscores the potential of increasing the dominance of native EcM tree species not only to enhance carbon stocks but also to bolster resilience against climate change in high-latitude forests. Here we show that forest managers can make informed decisions to optimize carbon accumulation by considering various factors such as mycorrhizal types, climate, successional stages, and species richness.