Developed metabolomics approach reveals the non-volatile color-contributing metabolites during Keemun congou black tea processing.

While key aroma and taste compounds of Keemun Congou black teas (KCBT) form during aeration and thermal stages, it is still unknown whether these processing stages also produce non-volatile color-contributing metabolites. Through integrating metabolomics with correlation and ridge regression analyses, 190 metabolites were identified as marker compounds that reclassified 15 KCBT samples collected from five processing stages into four groups. Meanwhile, the results of quantification and heatmap analysis showed that the concentrations of theaflavins and theasinensins significantly increased, as catechin decreased, after rolling, while flavonoid aglycones and polyunsaturated fatty acids increased throughout drying. Regression analysis between marker compound levels and total color difference values (∆E) revealed that the major color contributors were 3,5-dicaffeoylquinic acid, glucosyl-dehydrodigallic acid, theacitrin A, kaempferol-O-robinobioside, and (-)-epigallocatechin, with regression coefficients (absolute value) exceeding 4 × 10-2. Overall, the present study confirmed that rolling and drying were the two vital stages responsible for the color formation of KCBT.

The association between serum S100ß levels and prognosis in acute stroke patients after intravenous thrombolysis: a multicenter prospective cohort study.

BACKGROUND: S100ß is a biomarker of astroglial damage, the level of which is significantly increased following brain injury. However, the characteristics of S100ß and its association with prognosis in patients with acute ischemic stroke following intravenous thrombolysis (IVT) remain unclear. METHODS: Patients in this multicenter prospective cohort study were prospectively and consecutively recruited from 16 centers. Serum S100ß levels were measured 24 h after IVT. National Institutes of Health Stroke Scale (NIHSS) and hemorrhagic transformation (HT) were measured simultaneously. NIHSS at 7 days after stroke, final infarct volume, and modified Rankin Scale (mRS) scores at 90 days were also collected. An mRS score ≥ 2 at 90 days was defined as an unfavorable outcome. RESULTS: A total of 1072 patients were included in the analysis. The highest S100ß levels (> 0.20 ng/mL) correlated independently with HT and higher NIHSS at 24 h, higher NIHSS at 7 days, larger final infarct volume, and unfavorable outcome at 3 months. The patients were divided into two groups based on dominant and non-dominant stroke hemispheres. The highest S100ß level was similarly associated with the infarct volume in patients with stroke in either hemisphere (dominant: ß 36.853, 95% confidence interval (CI) 22.659-51.048, P < 0.001; non-dominant: ß 23.645, 95% CI 10.774-36.516, P = 0.007). However, serum S100ß levels at 24 h were more strongly associated with NIHSS scores at 24 h and 3-month unfavorable outcome in patients with dominant hemisphere stroke (NIHSS: ß 3.470, 95% CI 2.392-4.548, P < 0.001; 3-month outcome: odds ratio (OR) 5.436, 95% CI 2.936-10.064, P < 0.001) than in those with non-dominant hemisphere stroke (NIHSS: ß 0.326, 95% CI  - 0.735-1.387, P = 0.547; 3-month outcome: OR 0.882, 95% CI 0.538-1.445, P = 0.619). The association of S100ß levels and HT was not significant in either stroke lateralization group. CONCLUSIONS: Serum S100ß levels 24 h after IVT were independently associated with HT, infarct volume, and prognosis in patients with IVT, which suggests the application value of serum S100ß in judging the degree of disease and predicting prognosis.

The enhancing effects of selenomethionine on harmine in attenuating pathological cardiac hypertrophy via glycolysis metabolism.

Pathological cardiac hypertrophy, a common feature in various cardiovascular diseases, can be more effectively managed through combination therapies using natural compounds. Harmine, a ß-carboline alkaloid found in plants, possesses numerous pharmacological functions, including alleviating cardiac hypertrophy. Similarly, Selenomethionine (SE), a primary organic selenium source, has been shown to mitigate cardiac autophagy and alleviate injury. To explores the therapeutic potential of combining Harmine with SE to treat cardiac hypertrophy. The synergistic effects of SE and harmine against cardiac hypertrophy were assessed in vitro with angiotensin II (AngII)-induced hypertrophy and in vivo using a Myh6R404Q mouse model. Co-administration of SE and harmine significantly reduced hypertrophy-related markers, outperforming monotherapies. Transcriptomic and metabolic profiling revealed substantial alterations in key metabolic and signalling pathways, particularly those involved in energy metabolism. Notably, the combination therapy led to a marked reduction in the activity of key glycolytic enzymes. Importantly, the addition of the glycolysis inhibitor 2-deoxy-D-glucose (2-DG) did not further potentiate these effects, suggesting that the antihypertrophic action is predominantly mediated through glycolytic inhibition. These findings highlight the potential of SE and harmine as a promising combination therapy for the treatment of cardiac hypertrophy.

Aculeaquamides B and C, two new paraherquamides from the co-culture of Aspergillus aculeatinus WHUF0198 and Penicillium sp. DM27.

Two new paraherquamides (PHQs) namely aculeaquamides B and C (1 and 2), along with four known PHQs (3-6), were isolated from the co-culture of marine fungus Aspergillus aculeatinus WHUF0198 and mangrove-associated fungus Penicillium sp. DM27. Compound 1 represents the first PHQ derivative featuring an uncommon 7/6/5/5/6/5 hexacyclic system. The structures of the isolated compounds were elucidated based on exhaustive NMR spectroscopy measurement and HRESIMS data. The absolute configurations of new compounds were determined by TDDFT-ECD calculations. Compound 3 demonstrated suppression of AngII-induced cardiac hypertrophy while exhibiting relatively low cardiomyocyte toxicity.

Prognostic Value of Fibrosis-4 in Acute Ischemic Stroke Patients Undergoing Intravenous Thrombolysis.

Purpose: Although recombinant tissue plasminogen activator (rt-PA) treatment is efficient in patients with acute ischemic stroke (AIS), a significant percentage of patients who received rt-PA intravenous thrombolysis (IVT) do not achieve a good prognosis. Therefore, the factors that affect the poor prognosis of patients with IVT are needed. The Fibrosis-4 (FIB-4) index has been used as a liver fibrosis biomarker. We aimed to investigate the relationship between the FIB-4 index and functional outcomes in patients with AIS receiving IVT. Patients and Methods: This study prospectively included consecutive patients with AIS receiving IVT between April 2015 and May 2022. We collected clinical and laboratory data and calculated the FIB-4 index. Clinical outcome was poor functional outcome (mRS ≥3) at 3 months after IVT. Multivariate logistic regression analysis was used to analyze the association between FIB-4 and outcome. We explored the interactive effect of FIB-4 and dyslipidemia on poor outcomes, and subgroup analysis was performed. Furthermore, an individualized prediction model based on the FIB-4 for functional outcome was established in the dyslipidemia group. Results: A total of 1135 patients were included, and 41.50% had poor 3-month outcomes. After adjusted by other variants that P value <0.05 in univariable analysis, FIB-4 was independently associated with poor outcomes (OR=1.420; 95% CI: 1.113-1.812; P=0.004). There was a significant interaction between FIB-4 and dyslipidemia on poor outcome (P=0.036), and the independent association between FIB-4 and poor outcome was maintained in the dyslipidemia subgroup (OR=1.646; 95% CI: 1.228-2.206; P=0.001). Furthermore, in the dyslipidemia group, the FIB-4-based prediction model had good predictive value (the AUC of the training and validation sets were 0.767 and 0.708, respectively), good calibration (P-values for the Hosmer-Lemeshow test >0.05), and clinical usefulness. Conclusion: FIB-4 is an independent risk factor for poor outcomes in IVT patients with dyslipidemia, which can be used as a simple predictor of their prognosis.

Synchronous and efficient removal of carbon, nitrogen, and phosphorus from actual rural sewage by composite wetlands enhanced with functional fillers.

A composite wetland (CECW) was constructed by introducing P-adsorption filler (EPAF) and activated sludge into traditional wetlands for treating actual sewage. The results showed that EPAF improved P removal through physico-chemical adsorption, and it could be stably regenerated after adsorption saturation without potential risks. Meanwhile, zeolite promoted NH4+-N reduction in sewage by cation exchange. In addition, simultaneous biological removal of carbon, nitrogen, and phosphorus was achieved through nitrification, denitrification, anammox, and aerobic P-accumulation processes induced by Nitrobacter, Proteus Hauser, Candidatus Paracaedibacter, and Brevundimonas. Under the coupling of filler interception/adsorption, microbial assimilation/transformation, flocculation, and plant uptake, CECW obtained the removal rates of 93.22 %, 85.75 %, 91.80 %, 95.38 %, 97.07 %, and 78.05 % for turbidity, TN, NH4+-N, TP, PO43--P, and TCOD, which met the Class 1A standard (GB18918-2002). Therefore, the experiment systematically investigated the effects and mechanism of CECW in treating actual sewage, which could provide reference for rural sewage treatment and sludge utilization.

Chemical profile and in-vitro bioactivities of three types of yellow teas processed from different tenderness of young shoots of Huoshanjinjizhong (Camellia sinensis var. sinensis).

In the present study, bud yellow tea (BYT), small-leaf yellow tea (SYT) and large-leaf yellow tea (LYT) were produced from the same local "population" variety Huoshanjinjizhong (Camellia sinensis var. sinensis), and the effects of raw material tenderness on the chemical profile and bioactivities of these teas were investigated. The results showed that 11 crucial compounds were screened by headspace solid-phase microextraction-gas chromatography-mass spectrometry from 64 volatiles in these yellow teas, among which the heterocyclic compounds showed the greatest variations. In addition, 43 key compounds including organic acids, flavan-3-ols, amino acids, saccharides, glycosides and other compounds were screened by liquid chromatography-mass spectrometry from 1781 non-volatile compounds. BYT showed the best α-glucosidase inhibitory activity and antioxidant capacity among the selected yellow teas, which might be contributed by the higher content of galloylated catechins. These findings provided a better understanding of the chemical profile and bioactivities of yellow teas.

Influenza and the gut microbiota: A hidden therapeutic link.

Background: The extensive community of gut microbiota significantly influences various biological functions throughout the body, making its characterization a focal point in biomedicine research. Over the past few decades, studies have revealed a potential link between specific gut bacteria, their associated metabolic pathways, and influenza. Bacterial metabolites can communicate directly or indirectly with organs beyond the gut via the intestinal barrier, thereby impacting the physiological functions of the host. As the microbiota increasingly emerges as a 'gut signature' in influenza, gaining a deeper understanding of its role may offer new insights into its pathophysiological relevance and open avenues for novel therapeutic targets. In this Review, we explore the differences in gut microbiota between healthy individuals and those with influenza, the relationship between gut microbiota metabolites and influenza, and potential strategies for preventing and treating influenza through the regulation of gut microbiota and its metabolites, including fecal microbiota transplantation and microecological preparations. Methods: We utilized PubMed and Web of Science as our search databases, employing keywords such as "influenza," "gut microbiota," "traditional Chinese medicine," "metabolites," "prebiotics," "probiotics," and "machine learning" to retrieve studies examining the potential therapeutic connections between the modulation of gut microbiota and its metabolites in the treatment of influenza. The search encompassed literature from the inception of the databases up to December 2023. Results: Fecal microbiota transplantation (FMT), microbial preparations (probiotics and prebiotics), and traditional Chinese medicine have unique advantages in regulating intestinal microbiota and its metabolites to improve influenza outcomes. The primary mechanism involves increasing beneficial intestinal bacteria such as Bacteroidetes and Bifidobacterium while reducing harmful bacteria such as Proteobacteria. These interventions act directly or indirectly on metabolites such as short-chain fatty acids (SCFAs), amino acids (AAs), bile acids, and monoamines to alleviate lung inflammation, reduce viral load, and exert anti-influenza virus effects. Conclusion: The gut microbiota and its metabolites have direct or indirect therapeutic effects on influenza, presenting broad research potential for providing new directions in influenza research and offering references for clinical prevention and treatment. Future research should focus on identifying key strains, specific metabolites, and immune regulation mechanisms within the gut microbiota to accurately target microbiota interventions and prevent respiratory viral infections such as influenza.

Super-resolution landmark detection networks for medical images.

Craniomaxillofacial (CMF) and nasal landmark detection are fundamental components in computer-assisted surgery. Medical landmark detection method includes regression-based and heatmap-based methods, and heatmap-based methods are among the main methodology branches. The method relies on high-resolution (HR) features containing more location information to reduce the network error caused by sub-pixel location. Previous studies extracted HR patches around each landmark from downsampling images via object detection and subsequently input them into the network to obtain HR features. Complex multistage tasks affect accuracy. The network error caused by downsampling and upsampling operations during training, which interpolates low-resolution features to generate HR features or predicted heatmap, is still significant. We propose standard super-resolution landmark detection networks (SRLD-Net) and super-resolution UNet (SR-UNet) to reduce network error effectively. SRLD-Net used Pyramid pooling block, Pyramid fusion block and super-resolution fusion block to combine global prior knowledge and multi-scale local features, similarly, SR-UNet adopts Pyramid pooling block and super-resolution block. They can obviously improve representation learning ability of our proposed methods. Then the super-resolution upsampling layer is utilized to generate detail predicted heatmap. Our proposed networks were compared to state-of-the-art methods using the craniomaxillofacial, nasal, and mandibular molar datasets, demonstrating better performance. The mean errors of 18 CMF, 6 nasal and 14 mandibular landmarks are 1.39 ± 1.04, 1.31 ± 1.09, 2.01 ± 4.33 mm. These results indicate that the super-resolution methods have great potential in medical landmark detection tasks. This paper provides two effective heatmap-based landmark detection networks and the code is released in https://github.com/Runshi-Zhang/SRLD-Net.

Increased peripheral leukocyte aggravates brain injury and leads to poor outcome in stroke patients receiving intravenous thrombolysis: A study based on clinical evidence.

Whether the dynamic development of peripheral inflammation aggravates brain injury and leads to poor outcome in stroke patients receiving intravenous thrombolysis (IVT), remains unclear and warrants further study. In this study, total of 1034 patients with acute ischemic stroke who underwent IVT were enrolled. Serum leukocyte variation (whether increase from baseline to 24 h after IVT), National Institutes of Health Stroke Scale (NIHSS), infarct volume, early neurologic deterioration (END), the unfavorable outcome at 3-month (modified Rankin Scale [mRS] score ≥3) and mortality were recorded. Serum brain injury biomarkers, including Glial fibrillary acidic protein (GFAP), ubiquitin c-terminal hydrolase L1 (UCH-L1), S100ß, neuron-specific enolase (NSE), were measured to reflect the extent of brain injury. We found that patients with increased serum leukocytes had elevated brain injury biomarkers (GFAP, UCH-L1, and S100ß), larger infarct volume, higher 24 h NIHSS, higher proportion of END, unfavorable outcome and mortality. Furthermore, an increase in serum leukocytes was independently associated with infarct volume, 24 h NIHSS, END, and unfavorable outcome at 3 months, and serum UCH-L1, S100ß, and NSE levels. These results suggest that an increase in serum leukocytes indicates severe brain injury and may be used to predict the outcome of patients with ischemic stroke who undergo IVT.

[Mechanism of Xuanbai Chengqi Decoction in treating acute lung injury based on network pharmacology and experimental verification].

This study aims to investigate the mechanism of Xuanbai Chengqi Decoction in treating acute lung injury(ALI) based on network pharmacology and animal experiments. The potential targets and signaling pathways of Xuanbai Chengqi Decoction in regulating ALI were predicted by network pharmacology. The rat model of ALI was constructed and administrated with different doses of Xuanbai Chengqi Decoction. The pathological changes in the lung tissue of rats were observed by hematoxylin-eosin(HE) staining. The levels of interleukin-6(IL-6), interleukin-1ß(IL-1ß), and tumor necrosis factor-α(TNF-α) in the peripheral blood were measured by enzyme-linked immunosorbent assay(ELISA). The mRNA and protein levels of factors in the phosphatidylinositol 3-kinase(PI3K)/protein kinase B(Akt)/mammalian target of rapamycin(mTOR) signaling pathway were determined by quantitative real-time PCR(qPCR) and Western blot, respectively. A total of 52 compounds from Xuanbai Chengqi Decoction were predicted to be involved in the treatment of ALI, including ß-sitosterol, emodin, stigmasterol, glabridin, and aloe-emodin, which corresponded to 112 targets,and 4 723 targets of ALI were predicted. The compounds and ALI shared 94 common targets. The key targets included TNF, IL-1ß,prostaglandin-endoperoxide synthase 2(PTGS2), and tumor protein 53(TP53). Lipids and atherosclerosis, p53 signaling pathway,IL-17 signaling pathway, and PI3K/Akt signaling pathway were mainly involved in the treatment. Animal experiments showed that compared with the model group, Xuanbai Chengqi Decoction alleviated the pathological changes in the lung tissue, lowered the serum levels of IL-6, IL-1ß, and TNF-α, down-regulated the mRNA and protein levels of PI3K, Akt, and mTOR, and reduced the p-PI3K/PI3K, p-Akt/Akt, and p-mTOR/mTOR ratios in ALI rats. The results showed that Xuanbai Chengqi Decoction exerted its therapeutic effects on ALI via multiple components, targets, and pathways. Meanwhile, Xuanbai Chengqi Decoction may reduce the inflammation and attenuate the lung injuries of ALI rats by inhibiting the PI3K/Akt/mTOR signaling pathway.

Cancer-associated fibroblasts promote the progression and chemoresistance of HCC by inducing IGF-1.

Crosstalk between cancer-associated fibroblasts (CAFs) and tumour cells plays a critical role in multiple cancers, including hepatocellular carcinoma (HCC). CAFs contribute to tumorigenesis by secreting growth factors, modifying the extracellular matrix, supporting angiogenesis, and suppressing antitumor immune responses. However, effect and mechanism of CAF-mediated promotion of hepatocellular carcinoma cells are still unclear. In study, we demonstrated CAFs promoted the proliferation and inhibited the apoptosis of HCC cells by secreting interleukin-6 (IL-6), which induced autocrine insulin-like growth factor-1 (IGF-1) in HCC. IGF-1 promoted the progression and chemoresistance of HCC. IGF-1 receptor (IGF-1R) inhibitor NT157 abrogated the effect of CAF-derived IL-6 and autocrine IGF-1 on HCC. Mechanistic studies revealed that NT157 decreased IL-6-induced IGF-1 expression by inhibiting STAT3 phosphorylation and led to IRS-1 degradation, which mediated the proliferation of tumour by activating AKT signalling in ERK-dependent manner. Inhibition of IGF-1R also enhanced the therapeutic effect of sorafenib on HCC, especially chemoresistant tumours. STATEMENT OF SIGNIFICANCE: Our study showed IL-6-IGF-1 axis played crucial roles in the crosstalk between HCC and CAFs, providing NT157 inhibited of STAT3 and IGF-1R as a new targeted therapy in combination with sorafenib.

Salinomycin, a potent inhibitor of XOD and URAT1, ameliorates hyperuricemic nephropathy by activating NRF2, modulating the gut microbiota, and promoting SCFA production.

Long-term hyperuricemia can induce kidney damage, clinically referred to as hyperuricemic nephropathy (HN), which is characterized by renal fibrosis, inflammation, and oxidative stress. However, currently used uric acid-lowering drugs are not capable of protecting the kidneys from damage. Therefore, uric acid-lowering drugs that can also protect the kidneys are urgently needed. In this study, we first discovered that salinomycin, an antibiotic, can regulate uric acid homeostasis and ameliorate kidney damage in mice with HN. Mechanistically, salinomycin inhibited serum and hepatic xanthine oxidase (XOD) activities and downregulated renal urate transporter 1 (URAT1) expression and transport activity, thus exerting uric acid-lowering effects in mice with HN. Furthermore, we found that salinomycin promoted p-NRF2 Ser40 expression, resulting in increased nuclear translocation of NRF2 and activation of NRF2. More importantly, salinomycin affected the gut microbiota and promoted the generation of short-chain fatty acids (SCFAs) in mice with HN. In conclusion, our results revealed that salinomycin maintains uric acid homeostasis and alleviates kidney injury in mice with HN by multiple mechanisms, suggesting that salinomycin might be a desirable candidate for HN treatment in the clinic.

Novel Pink Pigments Produced by Thermal Interaction of Theaflavins, Theanine, and Glucose: Color Formation, Isolation, and Structural Characterization.

A color-deepening effect of theaflavins on the theanine-glucose thermal reaction model was revealed. Generated chromogenic intermediates in the initial stage and an accelerated browning rate through the promoted degradation of theanine-glucose Amadori rearrangement product in the intermediate and final stages are responsible for the color-deepening effect. Four pink-to-red theaflavin-theanine intermediates were verified as theaflavinies referencing the nuclear magnetic resonance and liquid chromatography-mass spectrometry information on theaflavins and l-theanine, including one accurately identified as theaflavinie 4. Theaflavinie 4 showed two maximum absorption peaks at 401 and 506 nm with parallel intensities, which resulted in a significant dichromic color change from pale pink to orange and red. Theaflavinies also could undergo further thermal reactions to yield brown polymers under higher temperatures (130 and 140 °C). This research provided new insight into realizing thermally formed polymers during black tea processing, which may be formed by oxidation products and amino acids or proteins through non-enzymatic thermal reactions.

Deep representation learning from electronic medical records identifies distinct symptom based subtypes and progression patterns for COVID-19 prognosis.

OBJECTIVE: Symptoms are significant kind of phenotypes for managing and controlling of the burst of acute infectious diseases, such as COVID-19. Although patterns of symptom clusters and time series have been considered the high potential prediction factors for the prognosis of patients, the elaborated subtypes and their progression patterns based on symptom phenotypes related to the prognosis of COVID-19 patients still need be detected. This study aims to investigate patient subtypes and their progression patterns with distinct features of outcome and prognosis. METHODS: This study included a total of 14,139 longitudinal electronic medical records (EMRs) obtained from four hospitals in Hubei Province, China, involving 2,683 individuals in the early stage of COVID-19 pandemic. A deep representation learning model was developed to help acquire the symptom profiles of patients. K-means clustering algorithm is used to divide them into distinct subtypes. Subsequently, symptom progression patterns were identified by considering the subtypes associated with patients upon admission and discharge. Furthermore, we used Fisher's test to identify significant clinical entities for each subtype. RESULTS: Three distinct patient subtypes exhibiting specific symptoms and prognosis have been identified. Particularly, Subtype 0 includes 44.2% of the whole and is characterized by poor appetite, fatigue and sleep disorders; Subtype 1 includes 25.6% cases and is characterized by confusion, cough with bloody sputum, encopresis and urinary incontinence; Subtype 2 includes 30.2% cases and is characterized by dry cough and rhinorrhea. These three subtypes demonstrate significant disparities in prognosis, with the mortality rates of 4.72%, 8.59%, and 0.25% respectively. Furthermore, symptom cluster progression patterns showed that patients with Subtype 0 who manifest dark yellow urine, chest pain, etc. in the admission stage exhibit an elevated risk of transforming into the more severe subtypes with poor outcome, whereas those presenting with nausea and vomiting tend to incline towards entering the milder subtype. CONCLUSION: This study has proposed a clinical meaningful approach by utilizing the deep representation learning and real-world EMR data containing symptom phenotypes to identify the COVID-19 subtypes and their progression patterns. The results would be potentially useful to help improve the precise stratification and management of acute infectious diseases.

Multimodal Distillation Pre-training Model for Ultrasound Dynamic Images Annotation.

With the development of medical technology, ultrasonography has become an important diagnostic method in doctors' clinical work. However, compared with the static medical image processing work such as CT, MRI, etc., which has more research bases, ultrasonography is a dynamic medical image similar to video, which is captured and generated by a real-time moving probe, so how to deal with the video data in the medical field and cross modal extraction of the textual semantics in the medical video is a difficult problem that needs to be researched. For this reason, this paper proposes a pre-training model of multimodal distillation and fusion coding for processing the semantic relationship between ultrasound dynamic Images and text. Firstly, by designing the fusion encoder, the visual geometric features of tissues and organs in ultrasound dynamic images, the overall visual appearance descriptive features and the named entity linguistic features are fused to form a unified visual-linguistic feature, so that the model obtains richer visual, linguistic cues aggregation and alignment ability. Then, the pre-training model is augmented by multimodal knowledge distillation to improve the learning ability of the model. The final experimental results on multiple datasets show that the multimodal distillation pre-training model generally improves the fusion ability of various types of features in ultrasound dynamic images, and realizes the automated and accurate annotation of ultrasound dynamic images.

Gut bacterial type III secretion systems aggravate colitis in mice and serve as biomarkers of Crohn's disease.

BACKGROUND: Mesenteric adipose tissue (mAT) hyperplasia, known as creeping fat, is a pathologic characteristic of Crohn's disease (CD). In our previously reported cohort, we observed that Achromobacter pulmonis was the most abundant and prevalent bacteria cultivated from creeping fat. METHODS: A whole genomic sequencing and identification of T3SS orthologs of mAT-derived A. pulmonis were used. A functional type III secretion system (T3SS) mediated the pathogenic potential of A. pulmonis in vitro and in mouse colitis model. Furthermore, a T3SS Finder pipeline was introduced to evaluate gut bacterial T3SS orthologs in the feces of CD patients, ulcerative colitis and colorectal cancer patients. FINDINGS: Here, we reveal that mAT-derived A. pulmonis possesses a functional T3SS, aggravates colitis in mice via T3SS, and exhibits T3SS-dependent cytotoxicity via a caspase-independent mechanism in macrophages and epithelial cells, which demonstrated the pathogenic potential of the T3SS-harboring A. pulmonis. Metagenomic analyses demonstrate an increased abundance of Achromobacter in the fecal of Crohn's disease patients compared to healthy controls. A comprehensive comparison of total microbial vT3SS abundance in various intestine diseases demonstrated that the specific enrichment of vT3SS genes was shown in fecal samples of CD, neither ulcerative colitis nor colorectal cancer patients, and ten T3SS gene-based biomarkers for CD were discovered and validated in a newly recruited CD cohort. Furthermore, treatment with exclusive enteral nutrition (EEN), an intervention that improves CD patient symptomatology, was found associated with a significant reduction in the prevalence of T3SS genes in fecal samples. INTERPRETATION: These findings highlight the pathogenic significance of T3SSs in the context of CD and identify specific T3SS genes that could potentially function as biomarkers for diagnosing and monitoring the clinical status of CD patients. FUNDING: This work is supported by the National Key Research and Development Program of China (2020YFA0907800), the China Postdoctoral Science Foundation (2023M744089), the National Natural Science Foundation of China (32000096), the Shenzhen Science and Technology Programs (KQTD20200820145822023, RCIC20231211085944057, and ZDSYS20220606100803007), National Key Clinical Discipline, Guangdong Provincial Clinical Research Center for Digestive Diseases (2020B1111170004), Qingfeng Scientific Research Fund of the China Crohn's & Colitis Foundation (CCCF) (CCCF-QF-2022B71-1), and the Sixth Affiliated Hospital, Sun Yat-sen University Clinical Research 1010 Program 1010CG(2023)-08. These funding provided well support for this research work, which involved data collection, analysis, interpretation, patient recruitment and so on.

Unraveling anti-aging mystery of green tea in C. elegans: Chemical truth and multiple mechanisms.

Tea drinking impacts aging and aging-related diseases. However, knowledge of anti-aging molecules other than the major catechins in complex tea extracts remains limited. Here we used Caenorhabditis elegans to analyze the longevity effects of tea extracts and constituents comprehensively. We found that the hot water extract of green tea prolonged lifespan and heathspan. Further, the MeOH fraction prolonged lifespan significantly longer than other fractions. Correlation analysis between mass spectroscopic data and anti-aging activity suggests that ester-type catechins (ETCs) are the major anti-aging components, including 4 common ETCs, 6 phenylpropanoid-substituted ester-type catechins (PSECs), 5 cinnamoylated catechins (CCs), 7 ester-type flavoalkaloids (ETFs), and 4 cinnamoylated flavoalkaloids (CFs). CFs (200 µM) are the strongest anti-aging ETCs (with the longest 73% lifespan extension). Green tea hot water extracts and ETCs improved healthspan by enhancing stress resistance and reducing ROS accumulation. The mechanistic study suggests that they work by multiple pathways. Moreover, ETCs modulated gut microbial homeostasis, increased the content of short-chain fatty acids, and reduced fat content. Altogether, our study provides new evidence for the anti-aging benefits of green tea and insights into a deep understanding of the chemical truth and multi-target mechanism.

[Identification of the binding proteins of organic acid metabolites by matrix thermal shift assay].

Organic acid metabolites exhibit acidic properties. These metabolites serve as intermediates in major carbon metabolic pathways and are involved in several biochemical pathways, including the tricarboxylic acid (TCA) cycle and glycolysis. They also regulate cellular activity and play crucial roles in epigenetics, tumorigenesis, and cellular signal transduction. Knowledge of the binding proteins of organic acid metabolites is crucial for understanding their biological functions. However, identifying the binding proteins of these metabolites has long been a challenging task owing to the transient and weak nature of their interactions. Moreover, traditional methods are unsuitable for the structural modification of the ligands of organic acid metabolites because these metabolites have simple and similar structures. Even minor structural modifications can significantly affect protein interactions. Thermal proteome profiling (TPP) provides a promising avenue for identifying binding proteins without the need for structural modifications. This approach has been successfully applied to the identification of the binding proteins of several metabolites. In this study, we investigated the binding proteins of two TCA cycle intermediates, i.e., succinate and fumarate, and lactate, an end-product of glycolysis, using the matrix thermal shift assay (mTSA) technique. This technique involves combining single-temperature (52 ℃) TPP and dose-response curve analysis to identify ligand-binding proteins with high levels of confidence and determine the binding affinity between ligands and proteins. To this end, HeLa cells were lysed, followed by protein desalting to remove endogenous metabolites from the cell lysates. The desalted cell lysates were treated with fumarate or succinate at final concentrations of 0.004, 0.04, 0.4, and 2 mmol/L in the experimental groups or 2 mmol/L sodium chloride in the control group. Considering that the cellular concentration of lactate can be as high as 2-30 mmol/L, we then applied lactate at final concentrations of 0.2, 1, 5, 10, and 25 mmol/L in the experimental groups or 25 mmol/L sodium chloride in the control group. Using high-sensitivity mass spectrometry coupled with data-independent acquisition (DIA) quantification, we quantified 5870, 5744, and 5816 proteins in succinate, fumarate, and lactate mTSA experiments, respectively. By setting stringent cut-off values (i.e., significance of changes in protein thermal stability (p-value)<0.001 and quality of the dose-response curve fitting (square of Pearson's correlation coefficient, R2)>0.95), multiple binding proteins for these organic acid metabolites from background proteins were confidently determined. Several known binding proteins were identified, notably fumarate hydratase (FH) as a binding protein for fumarate, and α-ketoglutarate-dependent dioxygenase (FTO) as a binding protein for both fumarate and succinate. Additionally, the affinity data for the interactions between these metabolites and their binding proteins were obtained, which closely matched those reported in the literature. Interestingly, ornithine aminotransferase (OAT), which is involved in amino acid biosynthesis, and 3-mercaptopyruvate sulfurtransferase (MPST), which acts as an antioxidant in cells, were identified as lactate-binding proteins. Subsequently, an orthogonal assay technique developed in our laboratory, the solvent-induced precipitation (SIP) technique, was used to validate the mTSA results. SIP identified OAT as the top target candidate, validating the mTSA-based finding that OAT is a novel lactate-binding protein. Although MPST was not identified as a lactate-binding protein by SIP, statistical analysis of MPST in the mTSA experiments with 10 or 25 mmol/L lactate revealed that MPST is a lactate-binding protein with a high level of confidence. Peptide-level empirical Bayes t-tests combined with Fisher's exact test also supported the conclusion that MPST is a lactate-binding protein. Lactate is structurally similar to pyruvate, the known binding protein of MPST. Therefore, assuming that lactate could potentially occupy the binding site of pyruvate on MPST. Overall, the novel binding proteins identified for lactate suggest their potential involvement in amino acid synthesis and redox balance regulation.

LC-MS and GC-MS based metabolomics analysis revealed the impact of tea trichomes on the chemical and flavor characteristics of white tea.

To explore the influence of tea trichomes on the quality of white tea, liquid chromatography quadrupole time-of-flight mass spectrometry (LC-Q-TOF-MS), and headspace solid phase microextraction gas chromatography-mass spectrometry (HS-SPME-GC-MS) were used to identify non-volatile and volatile compounds white tea without trichomes (WTwt) and pure trichomes (PT). It was found that the bitter and astringent compounds, caffeine (CAF), epigallocatechin gallate (EGCG), epicatechin gallate (ECG) and flavonol glycosides, were mainly enriched in the WTwt, with 16.3-fold, 47.1-fold and 28.7-fold decrease in CAF and EGCG and ECG, respectively, and the content of these compounds in PT were lower than the taste thresholds. In PT, kaempferol-3-O-(p-coumaroyl)-glucoside and kaempferol-3-O-(di-p-coumaroyl)-glucoside were non-volatile marker compounds, and decanal was significant aroma contributor with rOAV = 250.86. Moreover, the compounds in trichomes mainly contributed to the fruity and floral aroma of white tea, among which benzyl alcohol, (E)-geranylacetone, decanal, dodecanal and 6-methyl-5-hepten-2-one were the crucial aroma components, which were 2.1, 1.7, 1.8, 1.4 and 2.2 times as much as the WTwt in the PT, respectively. In conclusion, trichomes can improve the quality of white tea by reducing the bitterness and astringency, increasing the umami, as well as enhancing the fruity and floral aromas.