SATB1, senescence and senescence-related diseases.

Aging leads to an accumulation of cellular mutations and damage, increasing the risk of senescence, apoptosis, and malignant transformation. Cellular senescence, which is pivotal in aging, acts as both a guard against cellular transformation and as a check against cancer progression. It is marked by stable cell cycle arrest, widespread macromolecular changes, a pro-inflammatory profile, and altered gene expression. However, it remains to be determined whether these differing subsets of senescent cells result from unique intrinsic programs or are influenced by their environmental contexts. Multiple transcription regulators and chromatin modifiers contribute to these alterations. Special AT-rich sequence-binding protein 1 (SATB1) stands out as a crucial regulator in this process, orchestrating gene expression by structuring chromatin into loop domains and anchoring DNA elements. This review provides an overview of cellular senescence and delves into the role of SATB1 in senescence-related diseases. It highlights SATB1's potential in developing antiaging and anticancer strategies, potentially contributing to improved quality of life and addressing aging-related diseases.

Identification of prognostic signatures in remnant gastric cancer through an interpretable risk model based on machine learning: a multicenter cohort study.

OBJECTIVE: The purpose of this study was to develop an individual survival prediction model based on multiple machine learning (ML) algorithms to predict survival probability for remnant gastric cancer (RGC). METHODS: Clinicopathologic data of 286 patients with RGC undergoing operation (radical resection and palliative resection) from a multi-institution database were enrolled and analyzed retrospectively. These individuals were split into training (80%) and test cohort (20%) by using random allocation. Nine commonly used ML methods were employed to construct survival prediction models. Algorithm performance was estimated by analyzing accuracy, precision, recall, F1-score, area under the receiver operating characteristic curve (AUC), confusion matrices, five-fold cross-validation, decision curve analysis (DCA), and calibration curve. The best model was selected through appropriate verification and validation and was suitably explained by the SHapley Additive exPlanations (SHAP) approach. RESULTS: Compared with the traditional methods, the RGC survival prediction models employing ML exhibited good performance. Except for the decision tree model, all other models performed well, with a mean ROC AUC above 0.7. The DCA findings suggest that the developed models have the potential to enhance clinical decision-making processes, thereby improving patient outcomes. The calibration curve reveals that all models except the decision tree model displayed commendable predictive performance. Through CatBoost-based modeling and SHAP analysis, the five-year survival probability is significantly influenced by several factors: the lymph node ratio (LNR), T stage, tumor size, resection margins, perineural invasion, and distant metastasis. CONCLUSIONS: This study established predictive models for survival probability at five years in RGC patients based on ML algorithms which showed high accuracy and applicative value.

FURIN suppresses the progression of atherosclerosis by promoting macrophage autophagy.

FURIN, a member of the mammalian proprotein convertases (PCs) family, can promote the proteolytic maturation of proproteins. It has been shown that FURIN plays an important role in the progression of atherosclerosis (AS). Current evidence indicates that autophagy widely participates in atherogenesis. This study aimed to explore whether FURIN could affect atherogenesis via autophagy. The effect of FURIN on autophagy was studied using aortic tissues from aortic dissection patients who had BENTALL surgery, as well as macrophages and ApoE-/- mice. In atherosclerotic plaques of aortic tissues from patients, FURIN expression and autophagy were elevated. In macrophages, FURIN-shRNA and FURIN-overexpression lentivirus were used to intervene in FURIN expression. The results showed that FURIN overexpression accelerated LC3 formation in macrophages during the autophagosome formation phase. Furthermore, FURIN-induced autophagy resulted in lower lipid droplet concentrations in macrophages. The western blot revealed that FURIN regulated autophagy via the AMPK/mTOR/ULK1/PI3KIII signaling pathway. In vivo, FURIN overexpression resulted in increased macrophage LC3 formation in ApoE-/- mice atherosclerotic plaques, confirming that FURIN could inhibit the progression of AS by promoting macrophage autophagy. The present study demonstrated that FURIN suppressed the progression of AS by promoting macrophage autophagy via the AMPK/mTOR/ULK1/PI3KIII signaling pathway, which attenuated atherosclerotic lesion formation. Based on this data, current findings add to our understanding of the complexity of AS.

Effect of artificial intelligence on novice-performed colonoscopy: a multicenter randomized controlled tandem study.

BACKGROUND AND AIMS: The efficacy and safety of colonoscopy performed by artificial intelligence (AI)-assisted novices remain unknown. The aim of this study was to compare the lesion detection capability of novices, AI-assisted novices, and experts. METHODS: This multicenter, randomized, noninferiority tandem study was conducted across 3 hospitals in China from May 1, 2022, to November 11, 2022. Eligible patients were randomized into 1 of 3 groups: the CN group (control novice group, withdrawal performed by a novice independently), the AN group (AI-assisted novice group, withdrawal performed by a novice with AI assistance), or the CE group (control expert group, withdrawal performed by an expert independently). Participants underwent a repeat colonoscopy conducted by an AI-assisted expert to evaluate the lesion miss rate and ensure lesion detection. The primary outcome was the adenoma miss rate (AMR). RESULTS: A total of 685 eligible patients were analyzed: 229 in the CN group, 227 in the AN group, and 229 in the CE group. Both AMR and polyp miss rate were lower in the AN group than in the CN group (18.82% vs 43.69% [P < .001] and 21.23% vs 35.38% [P < .001], respectively). The noninferiority margin was met between the AN and CE groups of both AMR and polyp miss rate (18.82% vs 26.97% [P = .202] and 21.23% vs 24.10% [P < .249]). CONCLUSIONS: AI-assisted colonoscopy lowered the AMR of novices, making them noninferior to experts. The withdrawal technique of new endoscopists can be enhanced by AI-assisted colonoscopy. (Clinical trial registration number: NCT05323279.).

Validation of Artificial Intelligence-based Bowel Preparation Assessment in Screening Colonoscopy.

BACKGROUND AND AIMS: Accurate bowel preparation assessment is essential for determining colonoscopy screening intervals. Patients with suboptimal bowel preparation are at a high risk of missing >5mm adenomas, and should undergo an early repeat colonoscopy. In this study, we employed artificial intelligence (AI) to evaluate bowel preparation and validated the ability of the system in accurately identifying patients who are at high risk of missing >5mm adenoma due to inadequate bowel preparation. PATIENTS AND METHODS: This prospective, single-center, observational study was conducted at the Eighth Affiliated Hospital, Sun Yat-sen University from October 8, 2021, to November 9, 2022. Eligible patients underwent screening colonoscopy were consecutively enrolled. The AI assessed bowel preparation using e-Boston Bowel Preparation Scale (BBPS) while endoscopists evaluated using BBPS. If both BBPS and e-BBPS deemed preparation adequate, the patient immediately underwent a second colonoscopy, otherwise the patient underwent bowel re-cleansing before the second colonoscopy. RESULTS: Among the 393 patients, 72 ＞5mm adenomas were detected, while 27 ＞5mm adenomas were missed. In unqualified-AI patients, the >5mm AMR was significantly higher than in qualified-AI patients (35.71% vs 13.19%, p=0.0056, OR 0.2734, 95% CI 0.1139, 0.6565), as were the AMR (50.89% vs 20.79%, p<0.001, OR 0.2532, 95% CI 0.1583, 0.4052) and >5mm PMR (35.82% vs 19.48%, p=0.0152, OR 0.4335, 95% CI 0.2288, 0.8213). CONCLUSIONS: This study confirmed that patients classified as inadequate by AI showed unacceptable >5mm AMR, provided key evidence for implementing AI in guiding the bowel re-cleansing, potentially standardizing the future colonoscopy screening; ClincialTrials.gov, NCT05145712.

Combination of retagliptin and henagliflozin as add-on therapy to metformin in patients with type 2 diabetes inadequately controlled with metformin: A multicentre, randomized, double-blind, active-controlled, phase 3 trial.

AIM: This study assessed the efficacy and safety of co-administering retagliptin and henagliflozin versus individual agents at corresponding doses in patients with type 2 diabetes mellitus who were inadequately controlled with metformin. METHODS: This multicentre, phase 3 trial consisted of a 24-week, randomized, double-blind, active-controlled period. Patients with glycated haemoglobin (HbA1c) levels between 7.5% and 10.5% were randomized to receive once-daily retagliptin 100 mg (R100; n = 155), henagliflozin 5 mg (H5; n = 156), henagliflozin 10 mg (H10; n = 156), co-administered R100/H5 (n = 155), or R100/H10 (n = 156). The primary endpoint was the change in HbA1c from baseline to week 24. RESULTS: Based on the primary estimand, the least squares mean reductions in HbA1c at week 24 were significantly greater in the R100/H5 (-1.51%) and R100/H10 (-1.54%) groups compared with those receiving the corresponding doses of individual agents (-0.98% for R100, -0.86% for H5 and -0.95% for H10, respectively; p < .0001 for all pairwise comparisons). Achievement of HbA1c <7.0% at week 24 was observed in 27.1% of patients in the R100 group, 21.2% in the H5 group, 24.4% in the H10 group, 57.4% in the R100/H5 group and 56.4% in the R100/H10 group. Reductions in fasting plasma glucose and 2-h postprandial glucose were also more pronounced in the co-administration groups compared with the individual agents at corresponding doses. Decreases in body weight and systolic blood pressure were greater in the groups containing henagliflozin than in the R100 group. The incidence rates of adverse events were similar across all treatment groups, with no reported episodes of severe hypoglycaemia. CONCLUSIONS: For patients with type 2 diabetes mellitus inadequately controlled by metformin monotherapy, the co-administration of retagliptin and henagliflozin yielded more effective glycaemic control through 24 weeks compared with the individual agents at their corresponding doses.

PLD2 deletion ameliorates sepsis-induced cardiomyopathy by suppressing cardiomyocyte pyroptosis via the NLRP3/caspase 1/GSDMD pathway.

OBJECTIVE: Sepsis-induced cardiomyopathy (SICM) is a life-threatening complication. Phospholipase D2 (PLD2) is crucial in mediating inflammatory reactions and is associated with the prognosis of patients with sepsis. Whether PLD2 is involved in the pathophysiology of SICM remains unknown. This study aimed to investigate the effect of PLD2 knockout on SICM and to explore potential mechanisms. METHODS: The SICM model was established using cecal ligation and puncture in wild-type and PLD2-knockout mice and lipopolysaccharide (LPS)-induced H9C2 cardiomyocytes. Transfection with PLD2-shRNA lentivirus and a PLD2 overexpression plasmid were used to interfere with PLD2 expression in H9C2 cells. Cardiac pathological alterations, cardiac function, markers of myocardial injury, and inflammatory factors were used to evaluate the SICM model. The expression of pyroptosis-related proteins (NLRP3, cleaved caspase 1, and GSDMD-N) was assessed using western blotting, immunofluorescence, and immunohistochemistry. RESULTS: SICM mice had myocardial tissue damage, increased inflammatory response, and impaired heart function, accompanied by elevated PLD2 expression. PLD2 deletion improved cardiac histological changes, mitigated cTNI production, and enhanced the survival of the SICM mice. Compared with controls, PLD2-knockdown H9C2 exhibits a decrease in inflammatory markers and lactate dehydrogenase production, and scanning electron microscopy results suggest that pyroptosis may be involved. The overexpression of PLD2 increased the expression of NLRP3 in cardiomyocytes. In addition, PLD2 deletion decreased the expression of pyroptosis-related proteins in SICM mice and LPS-induced H9C2 cells. CONCLUSION: PLD2 deletion is involved in SICM pathogenesis and is associated with the inhibition of the myocardial inflammatory response and pyroptosis through the NLRP3/caspase 1/GSDMD pathway.

Current status of quality control in screening esophagogastroduodenoscopy and the emerging role of artificial intelligence.

Esophagogastroduodenoscopy (EGD) screening is being implemented in countries with a high incidence of upper gastrointestinal (UGI) cancer. High-quality EGD screening ensures the yield of early diagnosis and prevents suffering from advanced UGI cancer and minimal operational-related discomfort. However, performance varied dramatically among endoscopists, and quality control for EGD screening remains suboptimal. Guidelines have recommended potential measures for endoscopy quality improvement and research has been conducted for evidence. Moreover, artificial intelligence offers a promising solution for computer-aided diagnosis and quality control during EGD examinations. In this review, we summarized the key points for quality assurance in EGD screening based on current guidelines and evidence. We also outline the latest evidence, limitations, and future prospects of the emerging role of artificial intelligence in EGD quality control, aiming to provide a foundation for improving the quality of EGD screening.

Highly Efficient Visible-Blind Ultraviolet Photodetector Based on Scalably Produced Titanium Dioxide Nanowire Arrays.

Here, we report a novel, feasible, and cost-effective method for the preparation of one-dimensional TiO2 nanowire arrays using a super-aligned carbon nanotube film as a template. Pure-anatase-phase TiO2 nanowires were scalably prepared in a suspended manner, and a high-performance ultraviolet (UV) photodetector was realized on a flexible substrate. The large surface area and one-dimensional nanostructure of the TiO2 nanowire array led to a high detectivity (1.35 × 1016 Jones) and an ultrahigh photo gain (2.6 × 104), respectively. A high photoresponsivity of 7.7 × 103 A/W was achieved under 7 µW/cm2 UV (λ = 365 nm) illumination at a 10 V bias voltage, which is much higher than those of commercial UV photodetectors. Additionally, by taking advantage of its anisotropic geometry, we found the TiO2 nanowire array showed polarized photodetection. The concept of using nanomaterial systems shows the potential for realization of nanostructured photodetectors for practical applications.

Strong In-Plane Optoelectronic Anisotropy and Polarization Sensitivity in Low-Symmetry 2D Violet Phosphorus.

Anisotropic optoelectronics based on low-symmetry two-dimensional (2D) materials hold immense potential for enabling multidimensional visual perception with improved miniaturization and integration capabilities, which has attracted extensive interest in optical communication, high-gain photoswitching circuits, and polarization imaging fields. However, the reported in-plane anisotropic photocurrent and polarized dichroic ratios are limited, hindering the achievement of high-performance anisotropic optoelectronics. In this study, we introduce novel low-symmetry violet phosphorus (VP) with a unique tubular cross-linked structure into this realm, and the corresponding anisotropic optical and optoelectronic properties are investigated both experimentally and theoretically for the first time. Remarkably, our prepared VP-based van der Waals phototransistor exhibits significant optoelectronic anisotropies with a giant in-plane anisotropic photocurrent ratio exceeding 10 and a comparable polarized dichroic ratio of 2.16, which is superior to those of most reported 2D counterparts. Our findings establish VP as an exceptional candidate for anisotropic optoelectronics, paving the way for future multifunctional applications.

Detection of Severe Murine Typhus by Nanopore Targeted Sequencing, China.

We report a case of murine typhus in China caused by Rickettsia typhi and diagnosed by nanopore targeted sequencing of a bronchoalveolar lavage fluid sample. This case highlights that nanopore targeted sequencing can effectively detect clinically unexplained infections and be especially useful for detecting infections in patients without typical signs and symptoms.

A Review of Phosphorus Structures as CO2 Reduction Photocatalysts.

Effective photocatalytic carbon dioxide (CO2 ) reduction into high-value-added chemicals is promising to mitigate current energy crisis and global warming issues. Finding effective photocatalysts is crucial for photocatalytic CO2 reduction. Currently, metal-based semiconductors for photocatalytic CO2 reduction have been well reviewed, while review of nonmetal-based semiconductors is almost limited to carbon nitrides. Phosphorus is a promising nonmetal photocatalysts with various allotropes and tunable band gaps, which has been demonstrated to be promising non-metallic photocatalysts. However, no systematic review about phosphorus structures for photocatalytic CO2 reduction reactions has been reported. Herein, the progresses of phosphorus structures as photocatalysts for CO2 reduction are reviewed. The fundamentals of photocatalytic CO2 reduction, corresponding properties of phosphorus allotropes, photocatalysts with phosphorus doping or phosphorus-containing ligands, research progress of phosphorus allotropes as photocatalysts for CO2 reduction have been reviewed in this paper. The future research and perspective of phosphorus structures for photocatalytic CO2 reduction are also presented.

Modulating the Function of GeAs/ReS2 van der Waals Heterojunction with its Potential Application for Short-Wave Infrared and Polarization-Sensitive Photodetection.

Van der Waals heterojunction (vdWs) of 2D materials with integrated or extended superior characteristics, opening up new opportunities in functional electronic and optoelectric device applications. Exploring methods to achieve multifunctional vdWs heterojunction devices is one of the most promising prospects in this area. Herein, a diverse function of forward rectifying diode, Zener tunneling diode, and backward rectifying diodes are realized in GeAs/ReS2 heterojunction by modulating the doping level of GeAs. The tunneling diode presents an interesting trend forward negative differential resistance (NDR) behavior which may facilitate the application of multi-value logic. More importantly, the GeAs/ReS2 forward rectifying diode exhibits highly sensitive photodetection in the wide-spectrum range up to 1550 nm corresponding to a short-wave infrared (SWIR) region. In addition, as two strong anisotropic 2D materials of GeAs and ReS2 , the heterojunction exhibits strong polarization-sensitive photodetection behavior with a dichroic photocurrent ratio of 1.7. This work provides an effective strategy to achieve multifunctional 2D vdW heterojunction devices and develops more possibilities to broaden their functionalities and applications.

Effect of a deep learning-based automatic upper GI endoscopic reporting system: a randomized crossover study (with video).

BACKGROUND AND AIMS: EGD is essential for GI disorders, and reports are pivotal to facilitating postprocedure diagnosis and treatment. Manual report generation lacks sufficient quality and is labor intensive. We reported and validated an artificial intelligence-based endoscopy automatic reporting system (AI-EARS). METHODS: The AI-EARS was designed for automatic report generation, including real-time image capturing, diagnosis, and textual description. It was developed using multicenter datasets from 8 hospitals in China, including 252,111 images for training, 62,706 images, and 950 videos for testing. Twelve endoscopists and 44 endoscopy procedures were consecutively enrolled to evaluate the effect of the AI-EARS in a multireader, multicase, crossover study. The precision and completeness of the reports were compared between endoscopists using the AI-EARS and conventional reporting systems. RESULTS: In video validation, the AI-EARS achieved completeness of 98.59% and 99.69% for esophageal and gastric abnormality records, respectively, accuracies of 87.99% and 88.85% for esophageal and gastric lesion location records, and 73.14% and 85.24% for diagnosis. Compared with the conventional reporting systems, the AI-EARS achieved greater completeness (79.03% vs 51.86%, P < .001) and accuracy (64.47% vs 42.81%, P < .001) of the textual description and completeness of the photo-documents of landmarks (92.23% vs 73.69%, P < .001). The mean reporting time for an individual lesion was significantly reduced (80.13 ± 16.12 seconds vs 46.47 ± 11.68 seconds, P < .001) after the AI-EARS assistance. CONCLUSIONS: The AI-EARS showed its efficacy in improving the accuracy and completeness of EGD reports. It might facilitate the generation of complete endoscopy reports and postendoscopy patient management. (Clinical trial registration number: NCT05479253.).

Synergistic Antibacterial Surface with Liquid Repellency and Enhanced Photothermal Bactericidal Activity.

The presence of microorganisms on biomedical devices and food packaging surfaces poses an important threat to human health. Superhydrophobic surfaces, a powerful tool to combat pathogenic bacterial adhesion, are threatened by their poor robustness. As a supplement, photothermal bactericidal surfaces may be expected to kill adhered bacteria. Using copper mesh as a mask, we prepared a superhydrophobic surface with a homogeneous conical array. The surface shows synergistic antibacterial properties, including a superhydrophobic character against bacterial adhesion and photothermal bactericidal activity. As a result of the excellent liquid repellency, the surface could highly repel the adherence of bacteria after immersing in a bacterial suspension for 10 s (95%) and 1 h (57%). Photothermal graphene can easily eliminate most adhered bacteria during the subsequent treatment of near-infrared (NIR) radiation. After a self-cleaning wash, the deactivated bacteria were easily rinsed off the surface. Furthermore, this antibacterial surface exhibited an approximately 99.9% resisted bacterial adhesion rate regardless of planar and various uneven surfaces. The results offer promising advancement of an antibacterial surface combining both adhesion resistance and photothermal bactericidal activity in fighting microbial infections.

Technological innovations or advancement in detecting frozen and thawed meat quality: A review.

Frozen storage is one of the main storage methods for meat products. Freezing and thawing processes are important factors affecting the quality of stored foods. Deterioration of texture, denaturation of protein, decline of water holding capacity etc. are among the major quality issues during freezing that must be addressed. A number of advanced technologies are now available to detect the quality changes that can occur during freezing and/or thawing. This paper presents an overview of the techniques commonly used for the detection of meat product quality; these include: advanced microscopy, molecular sensory science and technology, nuclear magnetic resonance, hyperspectral technology, near infrared spectroscopy, Raman spectroscopy etc. These direct and indirect measurement techniques can characterize the quality of meat product from many different angles. The objective of this review is to provide an in-depth understanding of possible quality changes in meat products during freezing and thawing cycle so as to improve the quality of frozen and thawed meat products in industrial practice.

Evaluate prognostic accuracy of SOFA component score for mortality among adults with sepsis by machine learning method.

INTRODUCTION: Sepsis has the characteristics of high incidence, high mortality of ICU patients. Early assessment of disease severity and risk stratification of death in patients with sepsis, and further targeted intervention are very important. The purpose of this study was to develop machine learning models based on sequential organ failure assessment (SOFA) components to early predict in-hospital mortality in ICU patients with sepsis and evaluate model performance. METHODS: Patients admitted to ICU with sepsis diagnosis were extracted from MIMIC-IV database for retrospective analysis, and were randomly divided into training set and test set in accordance with 2:1. Six variables were included in this study, all of which were from the scores of 6 organ systems in SOFA score. The machine learning model was trained in the training set and evaluated in the validation set. Six machine learning methods including linear regression analysis, least absolute shrinkage and selection operator (LASSO), Logistic regression analysis (LR), Gaussian Naive Bayes (GNB) and support vector machines (SVM) were used to construct the death risk prediction models, and the accuracy, area under the receiver operating characteristic curve (AUROC), Decision Curve Analysis (DCA) and K-fold cross-validation were used to evaluate the prediction performance of developed models. RESULT: A total of 23,889 patients with sepsis were enrolled, of whom 3659 died in hospital. Three feature variables including renal system score, central nervous system score and cardio vascular system score were used to establish prediction models. The accuracy of the LR, GNB, SVM were 0.851, 0.844 and 0.862, respectively, which were better than linear regression analysis (0.123) and LASSO (0.130). The AUROCs of LR, GNB and SVM were 0.76, 0.76 and 0.67, respectively. K-fold cross validation showed that the average AUROCs of LR, GNB and SVM were 0.757 ± 0.005, 0.762 ± 0.006, 0.630 ± 0.013, respectively. For the probability threshold of 5-50%, LY and GNB models both showed positive net benefits. CONCLUSION: The two machine learning-based models (LR and GNB models) based on SOFA components can be used to predict in-hospital mortality of septic patients admitted to ICU.

Bioremediation of environmental organic pollutants by Pseudomonas aeruginosa: Mechanisms, methods and challenges.

The development of the chemical industry has led to a boom in daily consumption and convenience, but has also led to the release of large amounts of organic pollutants, such as petroleum hydrocarbons, plastics, pesticides, and dyes. These pollutants are often recalcitrant to degradation in the environment, whereby the most problematic compounds may even lead to carcinogenesis, teratogenesis and mutagenesis in animals and humans after accumulation in the food chain. Microbial degradation of organic pollutants is efficient and environmentally friendly, which is why it is considered an ideal method. Numerous studies have shown that Pseudomonas aeruginosa is a powerful platform for the remediation of environmental pollution with organic chemicals due to its diverse metabolic networks and its ability to secrete biosurfactants to make hydrophobic substrates more bioavailable, thereby facilitating degradation. In this paper, the mechanisms and methods of the bioremediation of environmental organic pollutants (EOPs) by P. aeruginosa are reviewed. The challenges of current studies are highlighted, and new strategies for future research are prospected. Metabolic pathways and critical enzymes must be further deciphered, which is significant for the construction of a bioremediation platform based on this powerful organism.

Tracheal microbiome and metabolome profiling in iatrogenic subglottic tracheal stenosis.

BACKGROUND: To study the role of microecology and metabolism in iatrogenic tracheal injury and cicatricial stenosis, we investigated the tracheal microbiome and metabolome in patients with tracheal stenosis after endotracheal intubation. METHODS: We collected 16 protected specimen brush (PSB) and 8 broncho-alveolar lavage (BAL) samples from 8 iatrogenic subglottic tracheal stenosis patients, including 8 PSB samples from tracheal scar sites, 8 PSB samples from scar-free sites and 8 BAL samples, by lavaging the subsegmental bronchi of the right-middle lobe. Metagenomic sequencing was performed to characterize the microbiome profiling of 16 PSB and 8 BAL samples. Untargeted metabolomics was performed in 6 PSB samples (3 from tracheal scar PSB and 3 from tracheal scar-free PSB) using high-performance liquid chromatography‒mass spectrometry (LC‒MS). RESULTS: At the species level, the top four bacterial species were Neisseria subflava, Streptococcus oralis, Capnocytophaga gingivals, and Haemophilus aegyptius. The alpha and beta diversity among tracheal scar PSB, scar-free PSB and BAL samples were compared, and no significant differences were found. Untargeted metabolomics was performed in 6 PSB samples using LC‒MS, and only one statistically significant metabolite, carnitine, was identified. Pathway enrichment analysis of carnitine revealed significant enrichment in fatty acid oxidation. CONCLUSION: Our study found that carnitine levels in tracheal scar tissue were significantly lower than those in scar-free tissue, which might be a new target for the prevention and treatment of iatrogenic tracheal stenosis in the future.

Natural product drupacine acting on a novel herbicidal target shikimate dehydrogenase.

Natural products are one of the important sources for the creation of new pesticides. Drupacine ((1R,11S,12S,13R,15S)-13-methoxy-5,7,21-trioxa-19-azahexacyclo[11.7.1.02,10.04,8.011,15.015,19]henicosa-2,4(8),9-trien-12-ol), isolated from Cephalotaxus sinensis (Chinese plum-yew), is a potent herbicidal compound containing an oxo-bridged oxygen bond structure. However, its molecular target still remains unknown. In this study, the targets of drupacine in Amaranthus retroflexus were identified by combining drug affinity responsive target stability (DARTS), cellular thermal shift assay coupled with mass spectrometry (CETSA MS), RNA-seq transcriptomic, and TMT proteomic analyses. Fifty-one and sixty-eight main binding proteins were identified by DARTS and CETSA MS, respectively, including nine co-existing binding proteins. In drupacine-treated A. retroflexus seedlings we identified 1389 up-regulated genes and 442 down-regulated genes, 34 up-regulated proteins, and 194 down-regulated proteins, respectively. Combining the symptoms and the biochemical profiles, Profilin, Shikimate dehydrogenase (SkDH), and Zeta-carotene desaturase were predicted to be the drupacine potential target proteins. At the same time, drupacine was found to bind SkDH stronger by molecular docking, and its inhibition on ArSkDH increased with the treatment concentration increase. Our results suggest that the molecular target of drupacine is SkDH, a new herbicide target, which lay a foundation for the rational design of herbicides based on new targets from natural products and enrich the target resources for developing green herbicides.