CircHAS2 activates CCNE2 to promote cell proliferation and sensitizes the response of colorectal cancer to anlotinib.

BACKGROUND: Tyrosine kinase inhibitors (TKIs) are crucial in the targeted treatment of advanced colorectal cancer (CRC). Anlotinib, a multi-target TKI, has previously been demonstrated to offer therapeutic benefits in previous studies. Circular RNAs (circRNAs) have been implicated in CRC progression and their unique structural stability serves as promising biomarkers. The detailed molecular mechanisms and specific biomarkers related to circRNAs in the era of targeted therapies, however, remain obscure. METHODS: The whole transcriptome RNA sequencing and function experiments were conducted to identify candidate anlotinib-regulated circRNAs, whose mechanism was confirmed by molecular biology experiments. CircHAS2 was profiled in a library of patient-derived CRC organoids (n = 22) and patient-derived CRC tumors in mice. Furthermore, a prospective phase II clinical study of 14 advanced CRC patients with anlotinib-based therapy was commenced to verify drug sensitivity (ClinicalTrials.gov identifier: NCT05262335). RESULTS: Anlotinib inhibits tumor growth in vitro and in vivo by downregulating circHAS2. CircHAS2 modulates CCNE2 activation by acting as a sponge for miR-1244, and binding to USP10 to facilitate p53 nuclear export as well as degradation. In parallel, circHAS2 serves as a potent biomarker predictive of anlotinib sensitivity, both in patient-derived organoids and xenograft models. Moreover, the efficacy of anlotinib inclusion into the treatment regimen yields meaningful clinical responses in patients with high levels of circHAS2. Our findings offer a promising targeted strategy for approximately 52.9% of advanced CRC patients who have high circHAS2 levels. CONCLUSIONS: CircHAS2 promotes cell proliferation via the miR-1244/CCNE2 and USP10/p53/CCNE2 bidirectional axes. Patient-derived organoids and xenograft models are employed to validate the sensitivity to anlotinib. Furthermore, our preliminary Phase II clinical study, involving advanced CRC patients treated with anlotinib, confirmed circHAS2 as a potential sensitivity marker.

Prediction of response to neoadjuvant chemo-immunotherapy in patients with esophageal squamous cell carcinoma by a rapid breath test.

BACKGROUND: Neoadjuvant chemo-immunotherapy combination has shown remarkable advances in the management of esophageal squamous cell carcinoma (ESCC). However, the identification of a reliable biomarker for predicting the response to this chemo-immunotherapy regimen remains elusive. While computed tomography (CT) is widely utilized for response evaluation, its inherent limitations in terms of accuracy are well recognized. Therefore, in this study, we present a novel technique to predict the response of ESCC patients before receiving chemo-immunotherapy by testing volatile organic compounds (VOCs) in exhaled breath. METHODS: This study employed a prospective-specimen-collection, retrospective-blinded-evaluation design. Patients' baseline breath samples were collected and analyzed using high-pressure photon ionization time-of-flight mass spectrometry (HPPI-TOFMS). Subsequently, patients were categorized as responders or non-responders based on the evaluation of therapeutic response using pathology (for patients who underwent surgery) or CT images (for patients who did not receive surgery). RESULTS: A total of 133 patients were included in this study, with 91 responders who achieved either a complete response (CR) or a partial response (PR), and 42 non-responders who had stable disease (SD) or progressive disease (PD). Among 83 participants who underwent both evaluations with CT and pathology, the paired t-test revealed significant differences between the two methods (p < 0.05). For the breath test prediction model using breath test data from all participants, the validation set demonstrated mean area under the curve (AUC) of 0.86 ± 0.06. For 83 patients with pathological reports, the breath test achieved mean AUC of 0.845 ± 0.123. CONCLUSIONS: Since CT has inherent weakness in hollow organ assessment and no other ideal biomarker has been found, our study provided a noninvasive, feasible, and inexpensive tool that could precisely predict ESCC patients' response to neoadjuvant chemo-immunotherapy combination using breath test based on HPPI-TOFMS.

Elucidating the role of exogenous melatonin in mitigating alkaline stress in soybeans across different growth stages: a transcriptomic and metabolomic approach.

BACKGROUND: Soybean (Glycine max), a vital grain and oilseed crop, serves as a primary source of plant protein and oil. Soil salinization poses a significant threat to soybean planting, highlighting the urgency to improve soybean resilience and adaptability to saline stress. Melatonin, recently identified as a key plant growth regulator, plays crucial roles in plant growth, development, and responses to environmental stress. However, the potential of melatonin to mitigate alkali stress in soybeans and the underlying mechanisms remain unclear. RESULTS: This study investigated the effects of exogenous melatonin on the soybean cultivar Zhonghuang 13 under alkaline stress. We employed physiological, biochemical, transcriptomic, and metabolomic analyses throughout both vegetative and pod-filling growth stages. Our findings demonstrate that melatonin significantly counteracts the detrimental effects of alkaline stress on soybean plants, promoting plant growth, photosynthesis, and antioxidant capacity. Transcriptomic analysis during both growth stages under alkaline stress, with and without melatonin treatment, identified 2,834 and 549 differentially expressed genes, respectively. These genes may play a vital role in regulating plant adaptation to abiotic stress. Notably, analysis of phytohormone biosynthesis pathways revealed altered expression of key genes, particularly in the ARF (auxin response factor), AUX/IAA (auxin/indole-3-acetic acid), and GH3 (Gretchen Hagen 3) families, during the early stress response. Metabolomic analysis during the pod-filling stage identified highly expressed metabolites responding to melatonin application, such as uteolin-7-O-(2''-O-rhamnosyl)rutinoside and Hederagenin-3-O-glucuronide-28-O-glucosyl(1,2)glucoside, which helped alleviate the damage caused by alkali stress. Furthermore, we identified 183 differentially expressed transcription factors, potentially playing a critical role in regulating plant adaptation to abiotic stress. Among these, the gene SoyZH13_04G073701 is particularly noteworthy as it regulates the key differentially expressed metabolite, the terpene metabolite Hederagenin-3-O-glucuronide-28-O-glucosyl(1,2)glucoside. WGCNA analysis identified this gene (SoyZH13_04G073701) as a hub gene, positively regulating the crucial differentially expressed metabolite of terpenoids, Hederagenin-3-O-glucuronide-28-O-glucosyl(1,2)glucoside. Our findings provide novel insights into how exogenous melatonin alleviates alkali stress in soybeans at different reproductive stages. CONCLUSIONS: Integrating transcriptomic and metabolomic approaches, our study elucidates the mechanisms by which exogenous melatonin ameliorates the inhibitory effects of alkaline stress on soybean growth and development. This occurs through modulation of biosynthesis pathways for key compounds, including terpenes, flavonoids, and phenolics. Our findings provide initial mechanistic insights into how melatonin mitigates alkaline stress in soybeans, offering a foundation for molecular breeding strategies to enhance salt-alkali tolerance in this crop.

Systemic inflammation influences the prognosis of patients with radically resected non-small cell lung cancer and correlates with the immunosuppressive microenvironment.

The impact of host condition on prognosis of non-small cell lung cancer (NSCLC) and the interaction between host and NSCLC remain unclear. This study investigated the association between systemic inflammation and prognosis and characteristics of radically resected NSCLC. This study consisted of a cohort study and an exploratory study of institutional prospective databases. All participants underwent video-assisted thoracoscopic lobectomy as the primary treatment. Systemic inflammation was assessed before surgery using the advanced lung cancer inflammation index and the systemic inflammation response index. Next-generation sequencing and multiplex immunofluorescence analysis were conducted to delineate tumor characteristics. In the cohort study including 1507 participants, high inflammation was associated with poor disease-free survival and overall survival before and after propensity score matching and in multivariable analysis. Systemic inflammation showed good prognostic value for stage IA-IB NSCLC, and the prognostic value diminished with upstaging of NSCLC. In the exploratory study including 217 adenocarcinomas, tumor microenvironment of high inflammation group showed a greater abundance of PDL1+ tumor cells and immune cells, which were independent from driver gene mutations and clinicopathological characteristics. Spatial analysis demonstrated a higher frequency of immune-suppressed cellular neighborhood, increased avoidance between immune cells and PDL1- tumor cells and compromised immune killing and presentation in tumor microenvironment of high inflammation group. Systemic inflammation showed limited association with genomic mutations. Systemic inflammation may influence the prognosis of NSCLC at both the systematic level and the local immune response. The correlation between high inflammation and immunosuppressive microenvironment indicates a novel thread for anticancer treatment.

Circular RNA P4HB promotes glycolysis and tumor progression by binding with PKM2 in lung adenocarcinoma.

BACKGROUND: Emerging evidence indicates that circular RNAs (circRNAs) play vital roles in tumor progression, including lung adenocarcinomas (LUAD). However, the mechanisms by which circRNAs promote the progression of LUAD still require further investigation. METHODS: Quantitative real-time PCR was performed to detect the expression of circP4HB in LUAD tissues and cells. Then, Kaplan-Meier analysis was used to determine the prognostic value of circP4HB expression. We employed RNA pull-down, RNA immunoprecipitation, mass spectrometry, cells fraction, glucose consumption, lactate production, pyruvate kinase M2 (PKM2) activity, and macrophage polarization assays to uncover the underlying mechanisms of circP4HB in LUAD. RESULTS: We found that circP4HB is upregulated in LUAD tissues and correlated with advanced TNM stages and lymph node metastasis. LUAD patients with high circP4HB expression had poor prognoses. Functionally, circP4HB promoted LUAD progression in vivo and in vitro. Upregulated circP4HB increased glucose consumption, lactate production and accelerated aerobic glycolysis in LUAD cells. Mechanically, circP4HB mainly accumulated in the cytoplasm of LUAD cells and bound with PKM2 and subsequently upregulating PKM2 enzymatic activity by increasing its tetramer formation. Additionally, circP4HB promoted M2 macrophage phenotype shift via targeting PKM2. Finally, rescue assays further confirmed that circP4HB could promote LUAD cell progression through its interaction with PKM2. CONCLUSION: These results demonstrate that circP4HB could promote LUAD progression, indicating circP4HB might be a potential therapeutic target of LUAD.

A Multiple-Center Nomogram to Predict Pneumonectomy Complication Risk for Non-Small Cell Lung Cancer Patients.

OBJECTIVE: This study aimed to construct a nomogram to quantitatively predict pneumonectomy complication risks for non-small cell lung cancer (NSCLC) patients. METHODS: Data from 1052 NSCLC patients who underwent pneumonectomy were retrospectively retrieved from the databases of three thoracic centers. Multivariable logistic regression was used to investigate postoperative morbidity predictors. Clinical parameters and operative features were analyzed using univariable and multivariable logistic regression analyses, and a nomogram to predict the risk of postoperative complications was constructed using bootstrap resampling. A receiver operating characteristic (ROC) curve was used to estimate the discrimination power for the nomogram. RESULTS: A total of 212 patients (20.2%) had major complications. After regression analysis, forced expiratory volume in 1 s, Charlson Comorbidity Index score, male sex, and right-sided pneumonectomy were identified and entered into the nomogram. The nomogram showed a robust discrimination, with an area under the ROC curve of 0.753 (95% confidence interval 0.604-0.818). The calibration curves for the probability of postoperative complications showed optimal agreement between the nomogram and the actual probability. CONCLUSIONS: Based on preoperative data, we developed a nomogram for predicting complication risks after pneumonectomy. This model may be helpful for thoracic surgeons in selecting appropriate patients for adopting prophylactic measures after surgery.

The distribution and structural fingerprints of metals from particulate matters (PM) deposited in human lungs.

This work investigated the distribution and chemical fingerprints of 24 metals in particulate matter (PM) deposited in nonoccupational human lungs. Metals in the pulmonary PM can be grouped by the mean concentration as > 5 × 103 µg/g (Al/Fe/Ca/Mg/Zn), 1-5 × 103 µg/g (Ti/Ba/Pb/Mn), 0.2-1 × 103 µg/g (Cu/Cr/As/V) and < 100 µg/g (Ni/Sn/Cd/Sb). Three parameters (LFL, LR, EFP) were defined to predict different metal leaching behaviors. The leaching factor (LFL) of metals was 10-60 for Pb/Sb/Cd/Co/Cu and decreased to 1-2 for Ni/Cr/Mg/Al/Fe. Metals showed a divergent extent of lung retention (LR), including high retention (LR>10, Al/Cd/Cr/Ba/Ni/Ti/Sn/V/Sb), moderate retention (2 

GmCCD4 controls carotenoid content in soybeans.

To better understand the mechanisms regulating plant carotenoid metabolism in staple crop, we report the map-based cloning and functional characterization of the Glycine max carotenoid cleavage dioxygenase 4 (GmCCD4) gene, which encodes a carotenoid cleavage dioxygenase enzyme involved in metabolizing carotenoids into volatile ß-ionone. Loss of GmCCD4 protein function in four Glycine max increased carotenoid content (gmicc) mutants resulted in yellow flowers due to excessive accumulation of carotenoids in flower petals. The carotenoid contents also increase three times in gmicc1 seeds. A genome-wide association study indicated that the GmCCD4 locus was one major locus associated with carotenoid content in natural population. Further analysis indicated that the haplotype-1 of GmCCD4 gene was positively associated with higher carotenoid levels in soybean cultivars and accumulated more ß-carotene in engineered E. coli with ectopic expression of different GmCCD4 haplotypes. These observations uncovered that GmCCD4 was a negative regulator of carotenoid content in soybean, and its various haplotypes provide useful resources for future soybean breeding practice.

Fringe projection profilometry by conducting deep learning from its digital twin.

High-accuracy and high-speed three-dimensional (3D) fringe projection profilometry (FPP) has been widely applied in many fields. Recently, researchers discovered that deep learning can significantly improve fringe analysis. However, deep learning requires numerous objects to be scanned for training data. In this paper, we propose to build the digital twin of an FPP system and perform virtual scanning using computer graphics, which can significantly save cost and labor. The proposed method extracts 3D geometry directly from a single-shot fringe image, and real-world experiments have demonstrated the success of the virtually trained model. Our virtual scanning method can automatically generate 7,200 fringe images and 800 corresponding 3D scenes within 1.5 hours.

Video-Assisted Thoracoscopic Surgery for Pulmonary Sequestrations: Series of 35 Consecutive Patients in a Single Center.

OBJECTIVE: The aim of this report is to summarize the experience of completely video-assisted thoracoscopic surgery (VATS) for pulmonary sequestration in a single center and to evaluate the long-term outcome in a larger series of patients. METHODS: The data of 35 pulmonary sequestrations who received completely VATS consecutively in Peking University People's Hospital between January 2008 and November 2017 were retrospectively reviewed. Twenty-three females and twelve males with an average of 38 years old were included. RESULTS: A total of 28 (80%) patients had preoperative symptoms; leading symptoms were recurrent infections (22), fever (11), hemoptysis (11), chest pain (9), and shortness of breath (4). Twenty-nine (82.9%) patients were intralobar pulmonary sequestration (22 in the left lower lobe, 6 in the right lower lobe, and 1 in the left upper lobe) and six (17.1%) patients were extralobar pulmonary sequestration. All the patients underwent VATS excision successfully, 26 underwent lobectomy, 2 underwent wedge resection, 1 underwent occlusion of the aberrant artery, and 6 underwent mass resection in all of those with extralobar pulmonary sequestration. The median surgery time and estimated blood loss was 150 (75-300) minutes and 50 (10-600) mL, respectively. There was no mortality. Only one patient suffered postoperative complication (recurrent laryngeal nerve injury). During the median follow-up period of 57 months, none of the patients presented recurrence. CONCLUSIONS: Completely VATS was a safe and effective mini-invasive procedure for pulmonary sequestration in an experienced team. Its long-term outcome was remarkable.

Timely ICU Outcome Prediction Utilizing Stochastic Signal Analysis and Machine Learning Techniques with Readily Available Vital Sign Data.

The ICU is a specialized hospital department that offers critical care to patients at high risk. The massive burden of ICU-requiring care requires accurate and timely ICU outcome predictions for alleviating the economic and healthcare burdens imposed by critical care needs. Existing research faces challenges such as feature extraction difficulties, low accuracy, and resource-intensive features. Some studies have explored deep learning models that utilize raw clinical inputs. However, these models are considered non-interpretable black boxes, which prevents their wide application. The objective of the study is to develop a new method using stochastic signal analysis and machine learning techniques to effectively extract features with strong predictive power from ICU patients' real-time time series of vital signs for accurate and timely ICU outcome prediction. The results show the proposed method extracted meaningful features and outperforms baseline methods, including APACHE IV (AUC = 0.750), deep learning-based models (AUC = 0.732, 0.712, 0.698, 0.722), and statistical feature classification methods (AUC = 0.765) by a large margin (AUC = 0.869). The proposed method has clinical, management, and administrative implications since it enables healthcare professionals to identify deviations from prognostications timely and accurately and, therefore, to conduct proper interventions.

Intratumor microbiome-derived butyrate promotes lung cancer metastasis.

Most recurrences of lung cancer (LC) occur within 3 years after surgery, but the underlying mechanism remains unclear. Here, we collect LC tissues with shorter (<3 years, recurrence group) and longer (>3 years, non-recurrence group) recurrence-free survival. By using 16S sequencing, we find that intratumor microbiome diversity is lower in the recurrence group and butyrate-producing bacteria are enriched in the recurrence group. The intratumor microbiome signature and circulating microbiome DNA can accurately predict LC recurrence. We prove that intratumor injection of butyrate-producing bacteria Roseburia can promote subcutaneous tumor growth. Mechanistically, bacteria-derived butyrate promotes LC metastasis by increasing expression of H19 in tumor cells through inhibiting HDAC2 and increasing H3K27 acetylation at the H19 promoter and inducing M2 macrophage polarization. Depletion of macrophages partially abolishes the metastasis-promoting effect of butyrate. Our results provide evidence for the cross-talk between the intratumor microbiome and LC metastasis and suggest the potential prognostic and therapeutic value of the intratumor microbiome.

Multi-omics analysis reveals NNMT as a master metabolic regulator of metastasis in esophageal squamous cell carcinoma.

Metabolic reprogramming has been observed in cancer metastasis, whereas metabolic changes required for malignant cells during lymph node metastasis of esophageal squamous cell carcinoma (ESCC) are still poorly understood. Here, we performed single-cell RNA sequencing (scRNA-seq) of paired ESCC tumor tissues and lymph nodes to uncover the reprogramming of tumor microenvironment (TME) and metabolic pathways. By integrating analyses of scRNA-seq data with metabolomics of ESCC tumor tissues and plasma samples, we found nicotinate and nicotinamide metabolism pathway was dysregulated in ESCC patients with lymph node metastasis (LN+), exhibiting as significantly increased 1-methylnicotinamide (MNA) in both tumors and plasma. Further data indicated high expression of N-methyltransferase (NNMT), which converts active methyl groups from the universal methyl donor, S-adenosylmethionine (SAM), to stable MNA, contributed to the increased MNA in LN+ ESCC. NNMT promotes epithelial-mesenchymal transition (EMT) and metastasis of ESCC in vitro and in vivo by inhibiting E-cadherin expression. Mechanically, high NNMT expression consumed too much active methyl group and decreased H3K4me3 modification at E-cadherin promoter and inhibited m6A modification of E-cadherin mRNA, therefore inhibiting E-cadherin expression at both transcriptional and post-transcriptional level. Finally, a detection method of lymph node metastasis was build based on the dysregulated metabolites, which showed good performance among ESCC patients. For lymph node metastasis of ESCC, this work supports NNMT is a master regulator of the cross-talk between cellular metabolism and epigenetic modifications, which may be a therapeutic target.

Using Foliation Leaves to Extract Reeb Graphs on Surfaces.

For Reeb graph extraction on surfaces, existing methods always use the isolines of a function defined on the surface to detect the surface components and the neighboring relationships between them. Since such detection is unstable, it is still a challenge for the extracted Reeb graphs to stably and concisely encode the topological information of the surface. In this article, we address this challenge by using foliation leaves to extract Reeb graphs. In particular, we employ a method for generating measured harmonic foliations by defining loops for foliation initialization and diffusing leaves from loops over the surface. We demonstrate that when the loops are determined, the neighboring relationships between the leaves from different loops are fixed. Thus, we can use loops to represent surface components for robustly detecting the interrelationships between surface components. As a result, we are able to extract stable and concise Reeb graphs. We developed novel measures for loop determination and improved foliation generation, and our method allows the user to manually prescribe loops for generating Reeb graphs with desired structures. Therefore, the potential of Reeb graphs for representing surfaces is enhanced, including conveniently representing the symmetries of the surface and ignoring topological noise. This is verified by our experimental results which indicate that our Reeb graphs are compact and expressive, promoting shape analysis.

Physiological responses and transcriptome analysis of soybean under gradual water deficit.

Soybean is an important food and oil crop widely cultivated globally. However, water deficit can seriously affect the yield and quality of soybeans. In order to ensure the stability and increase of soybean yield and improve agricultural water use efficiency (WUE), research on improving drought tolerance and the efficiency of water utilization of soybeans under drought stress has become particularly important. This study utilized the drought-tolerant variety Heinong 44 (HN44) and the drought-sensitive variety Suinong 14 (SN14) to analyze physiological responses and transcriptome changes during the gradual water deficit at the early seed-filling stage. The results indicated that under drought conditions, HN44 had smaller stomata, higher stomatal density, and lower stomatal conductance (Gs) and transpiration rate as compared to SN14. Additionally, HN44 had a higher abscisic acid (ABA) content and faster changes in stomatal morphology and Gs to maintain a dynamic balance between net photosynthetic rate (Pn) and Gs. Additionally, drought-tolerant variety HN44 had high instantaneous WUE under water deficit. Further, HN44 retained a high level of superoxide dismutase (SOD) activity and proline content, mitigating malondialdehyde (MDA) accumulation and drought-induced damage. Comprehensive analysis of transcriptome data revealed that HN44 had fewer differentially expressed genes (DEGs) under light drought stress, reacting insensitivity to water deficit. At the initial stage of drought stress, both varieties had a large number of upregulated DEGs to cope with the drought stress. Under severe drought stress, HN44 had fewer downregulated genes enriched in the photosynthesis pathway than SN14, while it had more upregulated genes enriched in the ABA-mediated signaling and glutathione metabolism pathways than SN14. During gradual water deficit, HN44 demonstrated better drought-tolerant physiological characteristics and water use efficiency than SN14 through key DEGs such as GmbZIP4, LOC100810474, and LOC100819313 in the major pathways. Key transcription factors were screened and identified, providing further clarity on the molecular regulatory pathways responsible for the physiological differences in drought tolerance among these varieties. This study deepened the understanding of the drought resistance mechanisms in soybeans, providing valuable references for drought-resistant soybean breeding.

Nodulation number tempers the relative importance of stochastic processes in the assembly of soybean root-associated communities.

Identifying the ecological forces that structure root-associated microbial communities is an essential step toward more sustainable agriculture. Legumes are widely utilized as model plants to study selective forces and their functioning in plant-microbial interactions owing to their ability to establish mutualism with rhizobia. Root nodules act as symbiotic organs to optimize the cost-benefit balance in this mutualistic relationship by modulating the number of nodules. However, it is not known whether the number of nodules is related to the structure of root-associated bacterial communities. Here, the root-associated bacterial communities of soybean grown in native soil by means of soybean cultivars with super- or normal nodulation were investigated across four developmental stages. We compared ecological processes between communities and found decreased relative importance of neutral processes for super-nodulating soybean, although the overall structures resembled those of normal-nodulating soybean. We identified the generalist core bacterial populations in each root-associated compartment, that are shared across root-associated niches, and persist through developmental stages. Within core bacterial species, the relative abundances of bacterial species in the rhizosphere microbiome were linked to host-plant functional traits and can be used to predict these traits from microbes using machine learning algorithms. These findings broaden the comprehensive understanding of the ecological forces and associations of microbiotas in various root-associated compartments and provide novel insights to integrate beneficial plant microbiomes into agricultural production to enhance plant performance.

Optimization of bronchoalveolar lavage fluid volume for untargeted lipidomic method and application in influenza A virus infection.

Bronchoalveolar lavage (BAL) has been widely applied for the diagnosis of pulmonary diseases in clinical as it was recognized as a minimally invasive, well-tolerated and easily performed procedure. Lipid analysis of BAL fluid is a comprehensive strategy to observe lipid phenotypes, explore potential biomarkers, and elucidate the biological mechanisms of respiratory diseases. However, the highly diverse concentration of lipids in BAL fluid due to the deviation between the retrieved and injected aliquot volumes during lavage raised a challenge in obtaining high-quality lipidomic data. Here, this study aims to investigate what volume of BAL fluid is suitable for lipidomic analysis. Specifically, the BAL fluid harvested from H1N1 infected mice and controls was concentrated to varying degrees by freeze-drying technique before preparation for lipidomic analysis. The optimal concentration multiple of BAL fluid was approved by comparing the coverage and quality of identified lipids, as well as the number of differentially expressed lipids in the H1N1 infection model. Sixty-two differential lipids were identified respectively in the positive and negative modes when the BAL fluid was condensed five times, and they were classified into glycerolipids, phospholipids and fatty acids. This study focuses on the alterations of phospholipids, since they are the main constituents of pulmonary surfactants. Several phospholipids significantly accumulated in the BAL fluid of H1N1-infected mice, while most of them contained omega-3 polyunsaturated fatty acids, indicating disrupted inflammatory homeostasis in lungs. This study recommends freeze-drying/reconstitution prior to lipid extraction from BAL fluid for lipidomic analysis, as this procedure increased the richness and abundance of lipids.

Microbial Diversity and Flavor Regularity of Soy Milk Fermented Using Kombucha.

Plant-based milk is considered a healthy and environmentally sustainable option. However, due to the low protein content of most plant-based milk and the difficulty of gaining flavor acceptance by consumers, its production scale is usually limited. Soy milk is a kind of food with comprehensive nutrition and high protein content. In addition, kombucha is naturally fermented by acetic acid bacteria (AAB), yeast, lactic acid bacteria (LAB), and other microorganisms, and the microorganisms in its system can improve the flavor characteristics of food. In the present study, LAB (commercially purchased) and kombucha were used as fermenting agents for soybean, which was used as a raw material to produce soy milk. A variety of characterization methods were used to study the relationship between the microbial composition and flavor regularity of soy milk produced with different proportions of fermenting agents and different fermentation times. In soy milk produced at 32 °C with a mass ratio of LAB to kombucha of 1:1 and a fermentation time of 42 h, the concentrations of LAB, yeast, and acetic acid bacteria in the milk were optimal at 7.48, 6.68, and 6.83 log CFU/mL, respectively. In fermented soy milk produced with kombucha and LAB, the dominant bacterial genera were Lactobacillus (41.58%) and Acetobacter (42.39%), while the dominant fungal genera were Zygosaccharomyces (38.89%) and Saccharomyces (35.86%). After 42 h, the content of hexanol in the fermentation system of kombucha and LAB decreased from 30.16% to 8.74%, while flavor substances such as 2,5-dimethylbenzaldehyde and linalool were produced. Soy milk fermented with kombucha offers the opportunity to explore the mechanisms associated with flavor formation in multi-strain co-fermentation systems and to develop commercial plant-based fermentation products.

Chemical fingerprints and implicated cancer risks of Polycyclic aromatic hydrocarbons (PAHs) from fine particulate matter deposited in human lungs.

Exposure to fine particles (PM2.5) and associated PAHs are frequently linked with lung cancer, which makes the understanding of their occurrence and health risk in human lungs urgently important. Using the ultrasonic treatment and sequencing centrifugation (USC) extraction method coupled with gas chromatography-tandem mass spectrometry (GC - MS/MS) analysis, we revealed the molecular fingerprints of PM-accumulated PAHs in human lungs from a cohort of 68 patients with lung cancer in a typical air-polluted region, China. Sixteen priority PAHs can be grouped by concentrations as âˆ¼ 1 × 104 ng/g (ANT/BkF/ACE/DBA/BgP/PHN/PYR), 2-5 × 103 ng/g (BaP/FLE/NaP/BbF), and âˆ¼ 1 × 103 ng/g (IND/Acy/CHR/FLT/BaA). The sum concentration of 16 PAHs was approximately equaled to 13% of those in atmospheric PM2.5, suggesting significant pulmonary leaching of PAHs deposited in lungs. Low- and high-molecular weight PAHs accounted for âˆ¼ 41.8% and âˆ¼ 45.1% of the total PAHs, respectively, which indicated that atmospheric PM2.5, tobacco and cooking smoke were likely to be important sources of pulmonary PAHs. The evident increasing concentrations of NaP and FLE in pulmonary PM were significantly correlated with smoking history among smokers. The implicated carcinogenic potency of PM-accumulated PAHs among the participants aged 70-80 was 17 times that among participants aged 40-50 on the basis of BaP equivalent concentration (BaPeq) evaluation. The particulate enrichment factor (EFP), the PAH content in pulmonary PM relative to the bulk lung tissue, was equaled to 54 âˆ¼ 835 and averaged at 436. The high value of EFP suggested that PAHs were essentially accumulated in pulmonary PM and exhibited a pattern of "hotspot" distribution in the lungs, which would likely increase the risk of monoclonal tumorigenesis. The chemical characteristics of PM-accumulated PAHs in human lungs together with their implicated lung cancer risks could provide significant information for understanding health effects of particulate pollution in the human body.