Longitudinal ultrasound-based AI model predicts axillary lymph node response to neoadjuvant chemotherapy in breast cancer: a multicenter study.

OBJECTIVES: Developing a deep learning radiomics model from longitudinal breast ultrasound and sonographer's axillary ultrasound diagnosis for predicting axillary lymph node (ALN) response to neoadjuvant chemotherapy (NAC) in breast cancer. METHODS: Breast cancer patients undergoing NAC followed by surgery were recruited from three centers between November 2016 and December 2022. We collected ultrasound images for extracting tumor-derived radiomics and deep learning features, selecting quantitative features through various methods. Two machine learning models based on random forest were developed using pre-NAC and post-NAC features. A support vector machine integrated these data into a fusion model, evaluated via the area under the curve (AUC), decision curve analysis, and calibration curves. We compared the fusion model's performance against sonographer's diagnosis from pre-NAC and post-NAC axillary ultrasonography, referencing histological outcomes from sentinel lymph node biopsy or axillary lymph node dissection. RESULTS: In the validation cohort, the fusion model outperformed both pre-NAC (AUC: 0.899 vs. 0.786, p < 0.001) and post-NAC models (AUC: 0.899 vs. 0.853, p = 0.014), as well as the sonographer's diagnosis of ALN status on pre-NAC and post-NAC axillary ultrasonography (AUC: 0.899 vs. 0.719, p < 0.001). Decision curve analysis revealed patient benefits from the fusion model across threshold probabilities from 0.02 to 0.98. The model also enhanced sonographer's diagnostic ability, increasing accuracy from 71.9% to 79.2%. CONCLUSION: The deep learning radiomics model accurately predicted the ALN response to NAC in breast cancer. Furthermore, the model will assist sonographers to improve their diagnostic ability on ALN status before surgery. CLINICAL RELEVANCE STATEMENT: Our AI model based on pre- and post-neoadjuvant chemotherapy ultrasound can accurately predict axillary lymph node metastasis and assist sonographer's axillary diagnosis. KEY POINTS: Axillary lymph node metastasis status affects the choice of surgical treatment, and currently relies on subjective ultrasound. Our AI model outperformed sonographer's visual diagnosis on axillary ultrasound. Our deep learning radiomics model can improve sonographers' diagnosis and might assist in surgical decision-making.

The impact of vedolizumab therapy on extraintestinal manifestations in patients with inflammatory bowel disease: A systematic review and meta-analysis.

BACKGROUND AND AIM: Extraintestinal manifestations (EIMs) pose a significant threat in inflammatory bowel disease (IBD) patients. Vedolizumab (VDZ) primarily affects the gastrointestinal tract. However, its impact on EIMs remains uncertain. Therefore, we conducted this meta-analysis to examine the effects of VDZ on EIMs during treatment. METHODS: Relevant studies were identified by conducting thorough searches across electronic databases, including PubMed, Ovid Embase, Medline, and Cochrane CENTRAL. Primary outcomes focused on the proportion of patients with resolution for pre-existing EIMs in IBD patients receiving VDZ. Secondary outcomes included the proportion of patients with EIM exacerbations and new onset EIMs during VDZ treatment. RESULTS: Our meta-analysis encompassed 21 studies. The proportion of patients with resolution of pre-existing EIMs in VDZ-treated IBD patients was 39% (150/386; 95% confidence interval [CI] 0.31-0.48). The proportion of patients with EIM exacerbations occurred at a rate of 28% (113/376; 95% CI 0.05-0.50), while new onset EIMs had a rate of 15% (397/2541; 95% CI 0.10-0.20). Subgroup analysis revealed a 40% (136/337) proportion of patients with resolution for articular-related EIMs and a 50% (9/18) rate for erythema nodosum. Exacerbation rates for arthritis/arthralgia, erythema nodosum/pyoderma gangrenosum, and aphthous stomatitis during VDZ use were 28% (102/328), 18% (7/38), and 11% (3/28), respectively. The incidence rate of newly developed EIMs during treatment was 11% (564/4839) for articular-related EIMs, with other EIMs below 2%. CONCLUSION: VDZ demonstrates efficacy in skin-related EIMs like erythema nodosum and joint-related EIMs including arthritis, arthralgia, spondyloarthritis, and peripheral joint diseases. Some joint and skin-related EIMs may experience exacerbation during VDZ therapy.

Phage tailspike protein coated gold nanoparticles combined with smartphone for rapid bacterial detection and photothermal sterilization.

The integration of recognition and therapeutic functions in multifunctional biosensors is of great importance in guaranteeing food security and reducing the occurrence of foodborne illness caused by foodborne pathogens. In this study, a biosensor utilizing a "sense-and-treat" approach was developed by integrating phage tailspike protein (TSP) with gold nanoparticles (AuNPs@TSP). The synthesized AuNPs@TSP showed strong binding affinity towards Salmonella typhimurium causing color changes and exhibited effective bactericidal activity when exposed to near-infrared (NIR) irradiation. This biosensor facilitated rapid colorimetric detection of S. typhimurium in 50 min, with a LOD (limit of detection) of 2.53 × 103 CFU/mL output on a smartphone APP after analyzing the red-green-blue (RGB) values from color rendering results. Furthermore, the biosensor displayed high selectivity, rapid response time, and broad applicability when tested with real samples. Moreover, the biosensor exhibited a remarkably efficient antibacterial efficacy of 100 % against S. typhimurium under 808 nm light irradiation for 6 min. This study provides a comprehensive investigation into the potential utilization of biosensors for rapid detection and eradication of foodborne pathogens in food industry.

Impact of Duration of Diabetes Mellitus on Long-term Outcome in Type 2 Diabetic Patients With Primary Percutaneous Coronary Intervention After the First Myocardial Infarction.

BACKGROUND: Diabetes mellitus (DM) increases the risk of mortality in patients with acute myocardial infarction (AMI). The impact of the diabetes duration on the long-term outcome of those with percutaneous coronary intervention (PCI) after the first AMI is unclear. In this study, we evaluated the predictive value of diabetes duration in the occurrence of major adverse cardiovascular and cerebrovascular events (MACCEs). METHODS: A total of 394 type 2 DM patients with PCI after the first AMI were enrolled and were divided into two groups by the diabetes duration. A short-DM group with diabetes duration of < 5 years and a long-DM group with a duration of ≥ 5 years. The clinical endpoint was MACCEs. RESULTS: Multivariate Cox regression analysis found that the diabetes duration was independently associated with increased occurrence of MACCEs [HR 1.512, 95% CI: (1.033, 2.215), p = 0.034], along with hypertension, Killip class III or IV, creatinine, multivessel disease, and continuous hypoglycemic therapy. After adjusting for the confounding variables, a nested Cox model showed that diabetes duration was still an independent risk factor of MACCEs [HR 1.963, 95% CI: (1.376, 2.801), p < 0.001]. The Kaplan-Meier survival curve illustrated a significantly high risk of MACCEs (HR 2.045, p < 0.0001) in long-duration DM patients. After propensity score matching, a longer diabetes duration was associated with an increased risk of MACCE occurrence. CONCLUSION: Long-duration diabetes was independently associated with poor clinical outcomes after PCI in patients with their first myocardial infarction, Despite the diabetes duration, continuous hypoglycemic therapy significantly improved long-term clinical outcomes.

FARPA-based tube array coupled with quick DNA extraction enables ultra-fast bedside detection of antibiotic-resistant pathogens.

Rapid and accurate detection of pathogens and antimicrobial-resistant (AMR) genes of the pathogens are crucial for the clinical diagnosis and effective treatment of infectious diseases. However, the time-consuming steps of conventional culture-based methods inhibit the precise and early application of anti-infection therapy. For the prompt treatment of pathogen-infected patients, we have proposed a novel tube array strategy based on our previously reported FARPA (FEN1-aided recombinase polymerase amplification) principle for the ultra-fast detection of antibiotic-resistant pathogens on site. The entire process from "sample to result" can be completed in 25 min by combining quick DNA extraction from a urine sample with FARPA to avoid the usually complicated DNA extraction step. Furthermore, a 36-tube array made from commercial 384-well titre plates was efficiently introduced to perform FARPA in a portable analyser, achieving an increase in the loading sample throughput (from several to several tens), which is quite suitable for the point-of-care testing (POCT) of multiple pathogens and multiple samples. Finally, we tested 92 urine samples to verify the performance of our proposed method. The sensitivities for the detection of E. coli, K. pneumoniae, E. faecium, and E. faecalis were 92.7%, 93.8%, 100% and 88.9%, respectively. The specificities for the detection of the four pathogens were 100%. Consequently, our rapid, low-cost and user-friendly POCT method holds great potential for guiding the rational use of antibiotics and reducing bacterial resistance.

Transfer Learning-Based Hyperspectral Image Classification Using Residual Dense Connection Networks.

The extraction of effective classification features from high-dimensional hyperspectral images, impeded by the scarcity of labeled samples and uneven sample distribution, represents a formidable challenge within hyperspectral image classification. Traditional few-shot learning methods confront the dual dilemma of limited annotated samples and the necessity for deeper, more effective features from complex hyperspectral data, often resulting in suboptimal outcomes. The prohibitive cost of sample annotation further exacerbates the challenge, making it difficult to rely on a scant number of annotated samples for effective feature extraction. Prevailing high-accuracy algorithms require abundant annotated samples and falter in deriving deep, discriminative features from limited data, compromising classification performance for complex substances. This paper advocates for an integration of advanced spectral-spatial feature extraction with meta-transfer learning to address the classification of hyperspectral signals amidst insufficient labeled samples. Initially trained on a source domain dataset with ample labels, the model undergoes transference to a target domain with minimal samples, utilizing dense connection blocks and tree-dimensional convolutional residual connections to enhance feature extraction and maximize spatial and spectral information retrieval. This approach, validated on three diverse hyperspectral datasets-IP, UP, and Salinas-significantly surpasses existing classification algorithms and small-sample techniques in accuracy, demonstrating its applicability to high-dimensional signal classification under label constraints.

Novel kinase 1 regulates CD8+T cells as a potential therapeutic mechanism for idiopathic pulmonary fibrosis.

Idiopathic pulmonary fibrosis (IPF) is a rare, chronic and progressively worsening lung disease that poses a significant threat to patient prognosis, with a mortality rate exceeding that of some common malignancies. Effective methods for early diagnosis and treatment remain for this condition are elusive. In our study, we used the GEO database to access second-generation sequencing data and associated clinical information from IPF patients. By utilizing bioinformatics techniques, we identified crucial disease-related genes and their biological functions, and characterized their expression patterns. Furthermore, we mapped out the immune landscape of IPF, which revealed potential roles for novel kinase 1 and CD8+T cells in disease progression and outcome. These findings can aid the development of new strategies for the clinical diagnosis and treatment of IPF.

GnRH-driven FTO-mediated RNA m6A modification promotes gonadotropin synthesis and secretion.

BACKGROUND: Gonadotropin precisely controls mammalian reproductive activities. Systematic analysis of the mechanisms by which epigenetic modifications regulate the synthesis and secretion of gonadotropin can be useful for more precise regulation of the animal reproductive process. Previous studies have identified many differential m6A modifications in the GnRH-treated adenohypophysis. However, the molecular mechanism by which m6A modification regulates gonadotropin synthesis and secretion remains unclear. RESULTS: Herein, it was found that GnRH can promote gonadotropin synthesis and secretion by promoting the expression of FTO. Highly expressed FTO binds to Foxp2 mRNA in the nucleus, exerting a demethylation function and reducing m6A modification. After Foxp2 mRNA exits the nucleus, the lack of m6A modification prevents YTHDF3 from binding to it, resulting in increased stability and upregulation of Foxp2 mRNA expression, which activates the cAMP/PKA signaling pathway to promote gonadotropin synthesis and secretion. CONCLUSIONS: Overall, the study reveals the molecular mechanism of GnRH regulating the gonadotropin synthesis and secretion through FTO-mediated m6A modification. The results of this study allow systematic interpretation of the regulatory mechanism of gonadotropin synthesis and secretion in the pituitary at the epigenetic level and provide a theoretical basis for the application of reproductive hormones in the regulation of animal artificial reproduction.

Investigating the impact of various sorghum types on the key aroma compounds of Sichuan Xiaoqu Baijiu through application of the sensomics approach.

The aroma of Sichuan Xiaoqu Baijiu (SXB) greatly benefits from the use of sorghum as its primary brewing ingredient. Nevertheless, the impact of different sorghum variety on the primary aroma compounds of SXB has not been thoroughly investigated. Gas chromatography-mass spectrometry (GC-MS) in conjunction with headspace solid phase microextraction (HS-SPME) and liquid-liquid extraction (LLE) were employed in this investigation. Using 5 sorghum varieties as raw materials, five different types of SXB were analysed for their aroma compounds using GC-MS, GC-O, AEDA, aroma recombination, and aroma omission. Key aroma compounds of SXB were successfully identified as ethyl acetate, ethyl 2-methylbutyrate, isoamyl acetate, ethyl hexanoate, ethyl heptanoate, ethyl lactate, ethyl octanoate, ethyl decanoate, phenylethyl acetate, ethyl laurate, ethyl palmitate, isoamyl alcohol, phenylethanol, 1,1-diethoxyethane, 3-hydroxy-2- butanone, furfural, and glacial acetic acid. Glacial acetic acid, ethyl acetate, ethyl lactate, phenylethyl acetate, acetoin, phenylethanol, and ethyl caproate were found to be the seven major aroma compounds that had the biggest impact on the variations of the five SXB aroma properties, according to partial least squares regression (PLS-R) analysis. The collinear network analysis also revealed that the largest positive correlation weight was discovered between the protein and furfural content, tannin content and cereal-like aroma profile while the highest negative correlation weight was found between the moisture and acetoin content. This study is a valuable resource for understanding how raw materials control the directional regulation of the sensory quality of the SXB liquor body.

Wuliangye strong aroma baijiu promotes intestinal homeostasis by improving gut microbiota and regulating intestinal stem cell proliferation and differentiation.

BACKGROUND: Wuliangye strong aroma baijiu (hereafter, Wuliangye baijiu) is a traditional Chinese grain liquor containing short-chain fatty acids, ethyl caproate, ethyl lactate, other trace components, and a large proportion of ethanol. The effects of Wuliangye baijiu on intestinal stem cells and intestinal epithelial development have not been elucidated. Here, the role of Wuliangye baijiu in intestinal epithelial regeneration and gut microbiota modulation was investigated by administering a Lieber-DeCarli chronic ethanol liquid diet in a mouse model to mimic long-term (8 weeks') light/moderate alcohol consumption (1.6 g kg-1 day-1) in healthy human adults. RESULTS: Wuliangye baijiu promoted colonic crypt proliferation in mice. According to immunofluorescence and reverse transcription-quantitative polymerase chain reaction analyses, compared with the ethanol-only treatment, Wuliangye baijiu increased the number of intestinal stem cells and goblet cells and the expression of enteroendocrine cell differentiation markers in the mouse colon. Furthermore, gut microbiota analysis showed an increase in the relative abundance of microbiota related to intestinal homeostasis following Wuliangye baijiu administration. Notably, increased abundance of Bacteroidota, Faecalibaculum, Lachnospiraceae, and Blautia may play an essential role in promoting stem-cell-mediated intestinal epithelial development and maintaining intestinal homeostasis. CONCLUSIONS: In summary, these findings suggest that Wuliangye baijiu can be used to regulate intestinal stem cell proliferation and differentiation in mice and to alter gut microbiota distributions, thereby promoting intestinal homeostasis. This research elucidates the mechanism by which Wuliangye baijiu promotes intestinal health. © 2024 Society of Chemical Industry.

Associations of the Serum KL-6 with Severity and Prognosis in Patients with Acute Exacerbation of Chronic Obstructive Pulmonary Disease.

BACKGROUND: As a biomarker of alveolar-capillary basement membrane injury, Krebs von den Lungen-6 (KL-6) is involved in the occurrence and development of pulmonary diseases. However, the role of the KL-6 in patients with acute exacerbation of chronic obstructive pulmonary disease (AECOPD) has yet to be elucidated. This prospective study was designed to clarify the associations of the serum KL-6 with the severity and prognosis in patients with AECOPD. METHODS: This study enrolled 199 eligible AECOPD patients. Demographic data and clinical characteristics were recorded. Follow-up was tracked to evaluate acute exacerbation and death. The serum KL-6 concentration was measured via an enzyme-linked immunosorbent assay. RESULTS: Serum KL-6 level at admission was higher in AECOPD patients than in control subjects. The serum KL-6 concentration gradually elevated with increasing severity of AECOPD. Pearson and Spearman analyses revealed that the serum KL-6 concentration was positively correlated with the severity score, monocyte count and concentrations of C-reactive protein, interleukin-6, uric acid, and lactate dehydrogenase in AECOPD patients during hospitalization. A statistical analysis of long-term follow-up data showed that elevated KL-6 level at admission was associated with longer hospital stays, an increased risk of future frequent acute exacerbations, and increased severity of exacerbation in COPD patients. CONCLUSION: Serum KL-6 level at admission is positively correlated with increased disease severity, prolonged hospital stay and increased risk of future acute exacerbations in COPD patients. There are positive dose-response associations of elevated serum KL-6 with severity and poor prognosis in COPD patients. The serum KL-6 concentration could be a novel diagnostic and prognostic biomarker in AECOPD patients.

Comparative Probiogenomics Analysis of Limosilactobacillus fermentum 3872.

Limosilactobacillus fermentum is an important member of the lactic acid bacteria group and holds immense potential for probiotic properties in human health and relevant industries. In this study, a comparative probiogenomic approach was applied to analyze the genome sequence of L. fermentum 3872, which was extracted from a commercially available yogurt sample, along with 20 different publicly available strains. Results indicate that the genome size of the characterized L. fermentum 3892 strain is 2,057,839 bp, with a single- and circular-type chromosome possessing a G + C content of 51.69%. The genome of L. fermentum 3892 strain comprises a total of 2120 open reading frames (ORFs), two genes encoding rRNAs, and 53 genes encoding tRNAs. Upon comparative probiogenomic analysis, two plasmid sequences were detected among the study strains, including one for the L. fermentum 3872 genome, which was found between position 1,288,203 and 1,289,237 with an identity of 80.98. The whole-genome alignment revealed 2223 identical sites and a pairwise identity of 98.9%, indicating a significant difference of 1.1% among genome strains. Comparison of amino acid encoding genes among strains included in this study suggests that the strain 3872 exhibited the highest degree of amino acids present, including glutamine, glutamate, aspartate, asparagine, lysine, threonine, methionine, and cysteine. The comparative antibiotic resistome profiling revealed that strain 3872 exhibited a high resistant capacity only to ciprofloxacin antibiotics as compared to other strains. This study provides a genomic-based evaluation approach for comparative probiotic strain analysis in commercial foods and their significance to human health.

Establishment of a prognosis predictive model for liver cancer based on expression of genes involved in the ubiquitin-proteasome pathway.

BACKGROUND: The ubiquitin-proteasome pathway (UPP) has been proven to play important roles in cancer. AIM: To investigate the prognostic significance of genes involved in the UPP and develop a predictive model for liver cancer based on the expression of these genes. METHODS: In this study, UPP-related E1, E2, E3, deubiquitylating enzyme, and proteasome gene sets were obtained from the Kyoto Encyclopedia of Genes and Genomes (KEGG) database, aiming to screen the prognostic genes using univariate and multivariate regression analysis and develop a prognosis predictive model based on the Cancer Genome Atlas liver cancer cases. RESULTS: Five genes (including autophagy related 10, proteasome 20S subunit alpha 8, proteasome 20S subunit beta 2, ubiquitin specific peptidase 17 like family member 2, and ubiquitin specific peptidase 8) were proven significantly correlated with prognosis and used to develop a prognosis predictive model for liver cancer. Among training, validation, and Gene Expression Omnibus sets, the overall survival differed significantly between the high-risk and low-risk groups. The expression of the five genes was significantly associated with immunocyte infiltration, tumor stage, and postoperative recurrence. A total of 111 differentially expressed genes (DEGs) were identified between the high-risk and low-risk groups and they were enriched in 20 and 5 gene ontology and KEGG pathways. Cell division cycle 20, Kelch repeat and BTB domain containing 11, and DDB1 and CUL4 associated factor 4 like 2 were the DEGs in the E3 gene set that correlated with survival. CONCLUSION: We have constructed a prognosis predictive model in patients with liver cancer, which contains five genes that associate with immunocyte infiltration, tumor stage, and postoperative recurrence.

Detection of SARS-CoV-2 using machine learning-enabled paper-assisted ratiometric fluorescent sensors based on target-induced magnetic DNAzyme.

The development of an advanced analytical platform with regard to SARS-CoV-2 is crucial for public health. Herein, we present a machine learning platform based on paper-assisted ratiometric fluorescent sensors for highly sensitive detection of the SARS-CoV-2 RdRp gene. The assay involves target-induced rolling circle amplification to generate magnetic DNAzyme, which is then detectable using the paper-assisted ratiometric fluorescent sensor. This sensor detects the SARS-CoV-2 RdRp gene with a visible-fluorescence color response. Moreover, leveraging different fluorescence responses, the ResNet algorithm of machine learning assists in accurately identifying fluorescence images and differentiating the concentration of the SARS-CoV-2 RdRp gene with over 99% recognition accuracy. The machine learning platform exhibits exceptional sensitivity and color responsiveness, achieving a limit of detection of 30 fM for the SARS-CoV-2 RdRp gene. The integration of intelligent artificial vision with the paper-assisted ratiometric fluorescent sensor presents a novel approach for the on-site detection of COVID-19 and holds potential for broader use in disease diagnostics in the future.

Alleviating Recombinant Tissue Plasminogen Activator-induced Hemorrhagic Transformation in Ischemic Stroke via Targeted Delivery of a Ferroptosis Inhibitor.

Intravenous thrombolysis with recombinant tissue plasminogen activator (rtPA) is the primary treatment for ischemic stroke. However, rtPA treatment can substantially increase blood-brain barrier (BBB) permeability and susceptibility to hemorrhagic transformation. Herein, the mechanism underlying the side effects of rtPA treatment is investigated and demonstrated that ferroptosis plays an important role. The ferroptosis inhibitor, liproxstatin-1 (Lip) is proposed to alleviate the side effects. A well-designed macrocyclic carrier, glucose-modified azocalix[4]arene (GluAC4A), is prepared to deliver Lip to the ischemic site. GluAC4A bound tightly to Lip and markedly improved its solubility. Glucose, modified at the upper rim of GluAC4A, imparts BBB targeting to the drug delivery system owing to the presence of glucose transporter 1 on the BBB surface. The responsiveness of GluAC4A to hypoxia due to the presence of azo groups enabled the targeted release of Lip at the ischemic site. GluAC4A successfully improved drug accumulation in the brain, and Lip@GluAC4A significantly reduced ferroptosis, BBB leakage, and neurological deficits induced by rtPA in vivo. These findings deepen the understanding of the side effects of rtPA treatment and provide a novel strategy for their effective mitigation, which is of great significance for the treatment and prognosis of patients with ischemic stroke.

Effects of a rainwater harvesting system on the soil water, heat and growth of apricot in rain-fed orchards on the Loess Plateau.

Rainwater is the main water source in arid and semiarid areas of the Loess Plateau, where rainfall is generally insufficient, ineffective and underutilized during the growing season. Thus, improving rainwater utilization efficiency is essential for sustainable agricultural development. A new system composed of rainwater harvesting, an infiltrator bucket with multiple holes and mulching (RHM), was designed to maintain soil moisture at a proper level in rain-fed orchards in arid and semiarid areas of the Loess Region of China. However, there is a lack of clarity on the effectiveness of RHM. In this study, changes in the soil environment and the growth and physiology of apricot trees were monitored via two treatments: (1) Rain-harvesting irrigation system (RHM) treatment and (2) traditional orchard treatment (CK) as a baseline. The results showed that (1) RHM could effectively improve soil water storage at depths of 0-45 cm and at a horizontal distance of 40 cm from the trunk. For the 1.4 mm light rain event, the soil water content increased by 6.3-12%, and for the two moderate rains, the soil water content increased by 12-25%. The change in the soil relative water content predicted by the LSTM model is consistent with the overall trend of the measured value and gradually decreases, and the prediction accuracy is high, with an error of 0.65. (2) The average soil temperatures at 5 cm, 20 cm and 40 cm under RHM were 17.0% (2.4 °C), 13.6% (1.9 °C) and 7.5% (1 °C) greater than those under CK, respectively. (3) Compared with the control treatment, RHM improved the growth and WUEL of apricot trees. The results highlighted the efficiency of the RHM system in enhancing the soil environment and regulating the growth and physiology of apricot trees, which has greater popularization value in arid and semiarid areas.

Investigation of Metabolic and Inflammatory Disorder in the Aging FGF21 Knockout Mouse.

Aging is a physiological condition accomplished with persistent low-grade inflammation and metabolic disorders. FGF21 has been reported to act as a potent longevity determinant, involving inflammatory response and energy metabolism. In this study, we engineered aging FGF21 knockout mice of 36-40 weeks and observed that FGF21 deficiency manifests a spontaneous inflammatory response of lung and abnormal accumulation of lipids in liver. On one hand, inflamed state in lungs and increased circulating inflammatory cytokines were found in FGF21 knockout mice of 36-40 weeks. To evaluate the ability of FGF21 to suppress inflammation, a subsequent study found that FGF21 knockout aggravated LPS-induced pulmonary exudation and inflammatory infiltration in mice, while exogenous administration of FGF21 reversed these malignant phenotypes by enhancing microvascular endothelial junction. On the other hand, FGF21 knockout induces fatty liver in aging mice, characterized by excessive accumulation of triglycerides within hepatocytes. Further quantitative metabolomics and lipidomics analysis revealed perturbed metabolic profile in liver lacking FGF21, including disrupted glucose and lipids metabolism, glycerophospholipid metabolism, and amino acid metabolism. Taken together, this investigation reveals the protective role of FGF21 during aging by weakening the inflammatory response and balancing energy metabolism.

A fresh perspective on dissociation mechanism of cellulose in DMAc/LiCl system based on Li bond theory.

In this case, various characterization technologies have been employed to probe dissociation mechanism of cellulose in N,N-dimethylacetamide/lithium chloride (DMAc/LiCl) system. These results indicate that coordination of DMAc ligands to the Li+-Cl- ion pair results in the formation of a series of Lix(DMAc)yClz (x = 1, 2; y = 1, 2, 3, 4; z = 1, 2) complexes. Analysis of interaction between DMAc ligand and Li center indicate that Li bond plays a major role for the formation of these Lix(DMAc)yClz complexes. And the saturation and directionality of Li bond in these Lix(DMAc)yClz complexes are found to be a tetrahedral structure. The hydrogen bonds between two cellulose chains could be broken at the nonreduced end of cellulose molecule via combined effects of basicity of Cl- ion and steric hindrance of [Li (DMAc)4]+ unit. The unique feature of Li bond in Lix(DMAc)yClz complexes is a key factor in determination of the dissociation mechanism.

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.

Circulating microbiome DNA as biomarkers for early diagnosis and recurrence of lung cancer.

Lung cancer mortality is exacerbated by late-stage diagnosis. Emerging evidence indicates the potential clinical significance of distinct microbial signatures as diagnostic and prognostic biomarkers across various cancers. However, circulating microbiome DNA (cmDNA) profiles are underexplored in lung cancer (LC). Here, whole-genome sequencing is performed on plasma of LC patients and healthy controls (HCs). Differentially enriched microbial species are identified between LC and HC. A diagnostic model is developed, which has a high sensitivity of 87.7% and achieves an AUC of 93.2% in the independent validation dataset. Crucially, this model demonstrates the capability to detect early-stage LC, achieving a sensitivity of 86.5% for stage I and 87.1% for tumors <1 cm. In addition, we construct a cmDNA model for recurrence, which precisely predicts LC recurrence after surgery. Overall, this study highlights the significant alterations of cmDNA profiles in LC, indicating its potential as biomarkers for early diagnosis and recurrence.