MdWER interacts with MdERF109 and MdJAZ2 to mediate methyl jasmonate- and light-induced anthocyanin biosynthesis in apple fruit.

Anthocyanin generation in apples (Malus domestica) and the pigmentation that results from it may be caused by irradiation and through administration of methyl jasmonate (MeJA). However, their regulatory interrelationships associated with fruit coloration are not well defined. To determine whether MdERF109, a transcription factor (TF) involved in light-mediated coloration and anthocyanin biosynthesis, has synergistic effects with other proteins, we performed a yeast two-hybrid assessment and identified another TF, MdWER. MdWER was induced by MeJA treatment, and although overexpression of MdWER alone did not promote anthocyanin accumulation co-overexpression with MdERF109 resulted in significantly increase in anthocyanin biosynthesis. MdWER may form a protein complex with MdERF109 to promote anthocyanin accumulation by enhancing combinations between the proteins and their corresponding genes. In addition, MdWER, as a MeJA responsive protein, interacts with the anthocyanin repressor MdJAZ2. Transient co-expression in apple fruit and protein interaction assays allowed us to conclude that MdERF109 and MdJAZ2 interact with MdWER and take part in the production of anthocyanins upon MeJA treatment and irradiation. Our findings validate a role for the MdERF109-MdWER-MdJAZ2 module in anthocyanin biosynthesis and uncover a novel mechanism for how light and MeJA signals are coordinated anthocyanin biosynthesis in apple fruit.

Phytochrome interacting factor regulates stomatal aperture by coordinating red light and abscisic acid.

Stomata are crucial valves coordinating the fixation of carbon dioxide by photosynthesis and water loss through leaf transpiration. Phytochrome interacting factors (PIFs) are negative regulators of red light responses that belong to the basic helix-loop-helix family of transcription factors. Here, we show that the rice (Oryza sativa) PIF family gene OsPIL15 acts as a negative regulator of stomatal aperture to control transpiration in rice. OsPIL15 reduces stomatal aperture by activating rice ABSCISIC ACID INSENSITIVE 5 (OsABI5), which encodes a critical positive regulator of ABSCISIC ACID (ABA) signaling in rice. Moreover, OsPIL15 interacts with the NIGT1/HRS1/HHO family transcription factor rice HRS1 HOMOLOG 3 (OsHHO3) to possibly enhance the regulation of stomatal aperture. Notably, we discovered that the maize (Zea mays) PIF family genes ZmPIF1 and ZmPIF3, which are homologous to OsPIL15, are also involved in the regulation of stomatal aperture in maize, indicating that PIF-mediated regulation of stomatal aperture may be conserved in the plant lineage. Our findings explain the molecular mechanism by which PIFs play a role in red-light-mediated stomatal opening, and demonstrate that PIFs regulate stomatal aperture by coordinating the red light and ABA signaling pathways.

SNX5-Rab11a protects against cardiac hypertrophy through regulating LRP6 membrane translocation.

BACKGROUNDS: Pathological cardiac hypertrophy is considered one of the independent risk factors for heart failure, with a rather complex pathogenic machinery. Sorting nexins (SNXs), denoting a diverse family of cytoplasmic- and membrane-associated phosphoinositide-binding proteins, act as a pharmacological target against specific cardiovascular diseases including heart failure. Family member SNX5 was reported to play a pivotal role in a variety of biological processes. However, contribution of SNX5 to the development of cardiac hypertrophy, remains unclear. METHODS: Mice underwent transverse aortic constriction (TAC) to induce cardiac hypertrophy and simulate pathological conditions. TAC model was validated using echocardiography and histological staining. Expression of SNX5 was assessed by western blotting. Then, SNX5 was delivered through intravenous administration of an adeno-associated virus serotype 9 carrying cTnT promoter (AAV9-cTnT-SNX5) to achieve SNX5 cardiac-specific overexpression. To assess the impact of SNX5, morphological analysis, echocardiography, histological staining, hypertrophic biomarkers, and cardiomyocyte contraction were evaluated. To unravel potential molecular events associated with SNX5, interactome analysis, fluorescence co-localization, and membrane protein profile were evaluated. RESULTS: Our results revealed significant downregulated protein level of SNX5 in TAC-induced hypertrophic hearts in mice. Interestingly, cardiac-specific overexpression of SNX5 improved cardiac function, with enhanced left ventricular ejection fraction, fraction shortening, as well as reduced cardiac fibrosis. Mechanistically, SNX5 directly bound to Rab11a, increasing membrane accumulation of Rab11a (a Rab GTPase). Afterwards, this intricate molecular interaction upregulated the membrane content of low-density lipoprotein receptor-related protein 6 (LRP6), a key regulator against cardiac hypertrophy. Our comprehensive assessment of siRab11a expression in HL-1 cells revealed its role in antagonism of LRP6 membrane accumulation under SNX5 overexpression. CONCLUSIONS: This study revealed that binding of SNX5 with LRP6 triggers their membrane translocation through Rab11a assisting, defending against cardiac remodeling and cardiac dysfunction under pressure overload. These findings provide new insights into the previously unrecognized role of SNX5 in the progression of cardiac hypertrophy.

Rare variations within the serine/arginine-rich splicing factor PtoRSZ21 modulate stomatal size to determine drought tolerance in Populus.

Rare variants contribute significantly to the 'missing heritability' of quantitative traits. The genome-wide characteristics of rare variants and their roles in environmental adaptation of woody plants remain unexplored. Utilizing genome-wide rare variant association study (RVAS), expression quantitative trait loci (eQTL) mapping, genetic transformation, and molecular experiments, we explored the impact of rare variants on stomatal morphology and drought adaptation in Populus. Through comparative analysis of five world-wide Populus species, we observed the influence of mutational bias and adaptive selection on the distribution of rare variants. RVAS identified 75 candidate genes correlated with stomatal size (SS)/stomatal density (SD), and a rare haplotype in the promoter of serine/arginine-rich splicing factor PtoRSZ21 emerged as the foremost association signal governing SS. As a positive regulator of drought tolerance, PtoRSZ21 can recruit the core splicing factor PtoU1-70K to regulate alternative splicing (AS) of PtoATG2b (autophagy-related 2). The rare haplotype PtoRSZ21hap2 weakens binding affinity to PtoMYB61, consequently affecting PtoRSZ21 expression and SS, ultimately resulting in differential distribution of Populus accessions in arid and humid climates. This study enhances the understanding of regulatory mechanisms that underlie AS induced by rare variants and might provide targets for drought-tolerant varieties breeding in Populus.

A newly developed deep learning-based system for automatic detection and classification of small bowel lesions during double-balloon enteroscopy examination.

BACKGROUND: Double-balloon enteroscopy (DBE) is a standard method for diagnosing and treating small bowel disease. However, DBE may yield false-negative results due to oversight or inexperience. We aim to develop a computer-aided diagnostic (CAD) system for the automatic detection and classification of small bowel abnormalities in DBE. DESIGN AND METHODS: A total of 5201 images were collected from Renmin Hospital of Wuhan University to construct a detection model for localizing lesions during DBE, and 3021 images were collected to construct a classification model for classifying lesions into four classes, protruding lesion, diverticulum, erosion & ulcer and angioectasia. The performance of the two models was evaluated using 1318 normal images and 915 abnormal images and 65 videos from independent patients and then compared with that of 8 endoscopists. The standard answer was the expert consensus. RESULTS: For the image test set, the detection model achieved a sensitivity of 92% (843/915) and an area under the curve (AUC) of 0.947, and the classification model achieved an accuracy of 86%. For the video test set, the accuracy of the system was significantly better than that of the endoscopists (85% vs. 77 ± 6%, p < 0.01). For the video test set, the proposed system was superior to novices and comparable to experts. CONCLUSIONS: We established a real-time CAD system for detecting and classifying small bowel lesions in DBE with favourable performance. ENDOANGEL-DBE has the potential to help endoscopists, especially novices, in clinical practice and may reduce the miss rate of small bowel lesions.

FXR activation remodels hepatic and intestinal transcriptional landscapes in metabolic dysfunction-associated steatohepatitis.

The escalating obesity epidemic and aging population have propelled metabolic dysfunction-associated steatohepatitis (MASH) to the forefront of public health concerns. The activation of FXR shows promise to combat MASH and its detrimental consequences. However, the specific alterations within the MASH-related transcriptional network remain elusive, hindering the development of more precise and effective therapeutic strategies. Through a comprehensive analysis of liver RNA-seq data from human and mouse MASH samples, we identified central perturbations within the MASH-associated transcriptional network, including disrupted cellular metabolism and mitochondrial function, decreased tissue repair capability, and increased inflammation and fibrosis. By employing integrated transcriptome profiling of diverse FXR agonists-treated mice, FXR liver-specific knockout mice, and open-source human datasets, we determined that hepatic FXR activation effectively ameliorated MASH by reversing the dysregulated metabolic and inflammatory networks implicated in MASH pathogenesis. This mitigation encompassed resolving fibrosis and reducing immune infiltration. By understanding the core regulatory network of FXR, which is directly correlated with disease severity and treatment response, we identified approximately one-third of the patients who could potentially benefit from FXR agonist therapy. A similar analysis involving intestinal RNA-seq data from FXR agonists-treated mice and FXR intestine-specific knockout mice revealed that intestinal FXR activation attenuates intestinal inflammation, and has promise in attenuating hepatic inflammation and fibrosis. Collectively, our study uncovers the intricate pathophysiological features of MASH at a transcriptional level and highlights the complex interplay between FXR activation and both MASH progression and regression. These findings contribute to precise drug development, utilization, and efficacy evaluation, ultimately aiming to improve patient outcomes.

Sulfated Polysaccharides with Anticoagulant Potential: A Review Focusing on Structure-Activity Relationship and Action Mechanism.

Thromboembolism is the culprit of cardiovascular diseases, leading to the highest global mortality rate. Anticoagulation emerges as the primary approach for managing thrombotic conditions. Notably, sulfated polysaccharides exhibit favorable anticoagulant efficacy with reduced side effects. This review focuses on the structure-anticoagulant activity relationship of sulfated polysaccharides and the underlying action mechanisms. It is concluded that chlorosulfonicacid-pyridine method serves as the preferred technique to synthesize sulfated polysaccharides. The anticoagulant activity of sulfated polysaccharides is linked to the substitution site of sulfate groups, degree of substitution, molecular weight, main side chain structure, and glycosidic bond conformation. Moreover, sulfated polysaccharides exert anticoagulant activity via various pathways, including the inhibition of blood coagulation factors, activation of antithrombin III and heparin cofactor II, antiplatelet aggregation, and promotion of the fibrinolytic system.

CircHIPK3 contributes to cisplatin resistance in gastric cancer by blocking autophagy-dependent ferroptosis.

Cisplatin is the first-line chemotherapy for gastric cancer (GC). However, its efficacy is dampened by the development of chemoresistance, which leads to poor prognosis in GC patients. Recently, evidence has revealed that circular RNAs (circRNAs) and dysregulation of autophagy-dependent ferroptosis play critical roles in cancer chemoresistance. Herein, for the first time we report that circHIPK3 has a vital role in GC cisplatin resistance. CircHIPK3 regulated cisplatin resistance by targeting autophagy and ferroptosis. In brief, knockdown circHIPK3 decreased GC cell cisplatin resistance by enhancing ferroptosis via the miR-508-3p/Bcl-2/beclin1/SLC7A11 axis. Taken together, our results demonstrate that ferroptosis is a promising strategy to ameliorate cisplatin resistance. Importantly, serum exosomal circHIPK3 could also be a noninvasive indicator to evaluate cisplatin resistance in GC.

Fusobacterium nucleatum-induced exosomal HOTTIP promotes gastric cancer progression through the microRNA-885-3p/EphB2 axis.

Recent studies have reported that Fusobacterium nucleatum (Fn) is associated with gastric cancer (GC). Cancer-derived exosomes contain key regulatory noncoding RNAs and are a crucial medium of intercellular communication. However, the function and regulatory mechanism of exosomes (Fn-GCEx) secreted from Fn-infected GC cells remains unclear. In this study, Fn-GCEx enhanced the proliferation, migration, and invasion capacity of GC cells in vitro, as well as tumor growth and metastasis in vivo. HOTTIP was also upregulated in GC cells treated with Fn-GCEx. Moreover, knockdown of HOTTIP weakened the effects of Fn-GCEx in recipient GC cells. Mechanistically, HOTTIP promoted EphB2 expression by sponging microRNA (miR)-885-3p, thus activating the PI3K/AKT pathway in Fn-GCEx treated GC cells. Overall, Fn infection induced the upregulation of exosomal HOTTIP from GC cells that subsequently promoted GC progression through the miR-885-3p/EphB2/PI3K/AKT axis. Herein, we identify a potential molecular pathway and therapeutic target for GC.

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.).

Uncoupling of the center-to-periphery arterial stiffness gradient and pulse pressure amplification in viral pneumonia infection.

OBJECTIVES: Arterial stiffness is a common manifestation of viral pneumonia infections, including COVID-19. Nevertheless, the relationship between the center-to-periphery arterial stiffness gradient and pulse pressure amplification (PPA) in infectious diseases remains unclear. This study aimed to investigate this relationship utilizing arterial pressure volume index (API) and arterial velocity pulse index (AVI) ratio. METHODS: API/AVI and PPA were measured in 219 participants with COVID-19 and 374 normal participants. Multiple linear regression was used to assess the association of API/AVI and PPA, and restricted cubic spline was used to investigate the non-linear relationship between API/AVI and PPA. Receiver operating characteristic curve (ROC) analysis was used to evaluate the effects of API/AVI in identifying COVID-19 infection and severe stage. RESULTS: There was a significant J-shaped relationship between API/AVI and PPA in COVID-19 group, while a M-shaped relationship was observed in normal group. API/AVI decreased rapidly as PPA decreased until API/AVI decreased slowly at PPA of 1.07, and then API/AVI decreased slowly again at PPA of 0.78. ROC results showed that API/AVI demonstrated excellent accuracy in identifying COVID-19 infection (AUC = 0.781) and a high specificity (84.88%) in identifying severe stage. CONCLUSIONS: There was a J-shaped association between the API/AVI and PPA in viral infected patients, while a M-shaped relationship in the normal participants. API/AVI is better for identifying infected and uninfected patients, with a high specificity in identifying those in severe stages of the disease. The attenuation or reversal of API/AVI may be associated with the loss of PPA coupling.

Increased arterial pressure volume index and cardiovascular risk score in China.

BACKGROUND AND OBJECTIVE: The new non-invasive arterial stiffness indices, arterial pressure volume index (API) is explored as a novel marker of residual stress in the wall of the peripheral muscular arteries at zero-stress state in clinical settings. The present study aimed to study the association of API with cardiovascular disease (CVD) risk in China (China-PAR). METHODS: According to China-PAR score, participants were divided into three groups: low risk (< 5%), medium risk (5-9.9%), and high risk (≥ 10.0%). API ≥ 31 was defined as high API, and the incidences of high API were compared. Logistic regression models were used to analyze the risk factors of high API and high risk China-PAR categories. The association between China-PAR and API was analyzed by restrictive cubic spline. RESULTS: The study included 4311 participants. After adjustments for confounding factors, high API was independent factor associated with high risk China-PAR categories, and the probability of high API was 1.366 times higher than that in normal API subjects. While, the independent factors associated with high API were BMI, blood pressure and heart rate. Furthermore, API had a significant U-shaped association with China-PAR. CVD risk was lowest with API of 19 units, the fastest increase at 26 units and the flattest starting point at 59 units. CONCLUSION: API, an indicator of arterial stiffness and residual stress, had a U-shaped association with China-PAR score and might play an important role in predicting CVD risk in Chinese natural populations.

Gender and age disparities in small-to-medium arterial stiffness among the Chinese population.

BACKGROUND AND AIMS: Arterial pressure-volume index (API) is a non-invasive tool for assessing small-to-medium-sized arterial stiffness. This study aimed to investigate the potential age- and sex-related differences in the API and explore the practical implications of such differences. METHODS AND RESULTS: The study analysed 7620 subjects for whom API measurements were available. Linear regression and restrictive cubic spline models were used to investigate the associations between potential risk conditions and the API. Additionally, this study employed a backward stepwise regression method to identify the independent factors associated with a high API. Middle-aged to older women had higher API values and a higher prevalence of high API than men in the same age group. However, the opposite was observed among younger individuals, with women having lower API values than men. This study also identified a J-shaped relationship between API and age, where API values began to increase at a certain age and rapidly increased after that. In women, the API started to increase at 31 years of age and rapidly increased after 54 years of age. In men, the API started to increase at 38 years of age, followed by a rapid increase after 53 years of age. CONCLUSION: This study's observation of a significant age-sex interaction in small-to-medium-sized arterial stiffening offers a valuable explanation for cardiovascular disease risk and provides important parameters for using API measurements to evaluate such risk.

Quality of life in patients with cervical cancer between the Han nationality and ethnic minorities in the Yunnan Province of China.

BACKGROUND: Cervical cancer is the fourth most diagnosed cancer and the leading cause of cancer death, and it still poses a crippling threat to women's health. China launched the National Cervical Cancer Screening Program for Rural Women in 2009, and an increasing number of cervical cancer patients have been detected. Health-related quality of life is not only the end point of cancer research but is also related to socioeconomic and clinical factors and has received an increasing amount of attention. In light of the characteristics of the Yunnan nationality, we conducted cross-sectional research to assess and explore the health-related quality of life in both Han and ethnic minority patients. METHODS: A cross-sectional study was conducted from January 2020 to May 2021 at the Third Affiliated Hospital of Kunming University/Yunnan Cancer Hospital. Patients, including 100 Han patients and 100 ethnic minorities, were interviewed using the FACT-Cx questionnaire within 3 months of receiving treatment. RESULTS: Patients of Han ethnicity and ethnic minorities were comparable in both sociodemographic and clinical features. The total FACT-Cx scores were 139.38 ± 9.83 and 134.39 ± 13.63 in Han and ethnic minority patients, respectively (P < 0.05). Significant differences were shown in physical well-being, emotional well-being and the FACT-Cx subscale between the Han and ethnic minority groups. Independent predictors of the FACT-Cx scale were ethnicity, educational level, participation in the National Cervical Cancer Screening Program for Rural Areas (NCCSPRA) and clinical stage. CONCLUSIONS: The results of our study imply that the HRQOL of Han patients is better than that of ethnic minority patients. Thus, clinicians and related health workers should pay more attention to the HRQOL of cervical cancer patients, especially for ethnic minority patients, and provide psychosocial interventions as much as possible to improve their HRQOL. Policies should also aim to strengthen health education regarding cervical cancer and expand the coverage of the NCCSPRA among those who are ethnic minorities, are older and have low educational levels.

Comparison of 30-day planned and unplanned readmissions in a tertiary teaching hospital in China.

PURPOSE: The purpose of this study was to analyze and compare the clinical characteristics of patients with 30-day planned and unplanned readmissions and to identify patients at high risk for unplanned readmissions. This will facilitate a better understanding of these readmissions and improve and optimize resource utilization for this patient population. METHODS: A retrospective cohort descriptive study was conducted at the West China Hospital (WCH), Sichuan University from January 1, 2015, to December 31, 2020. Discharged patients (≥ 18 years old) were divided into unplanned readmission and planned readmission groups according to 30-day readmission status. Demographic and related information was collected for each patient. Logistic regression analysis was used to assess the association between unplanned patient characteristics and the risk of readmission. RESULTS: We identified 1,118,437 patients from 1,242,496 discharged patients, including 74,494 (6.7%) 30-day planned readmissions and 9,895 (0.9%) unplanned readmissions. The most common diseases of planned readmissions were antineoplastic chemotherapy (62,756/177,749; 35.3%), radiotherapy sessions for malignancy (919/8,229; 11.2%), and systemic lupus erythematosus (607/4,620; 13.1%). The most common diseases of unplanned readmissions were antineoplastic chemotherapy (2038/177,747; 1.1%), age-related cataract (1061/21,255; 5.0%), and unspecified disorder of refraction (544/5,134; 10.6%). There were statistically significant differences between planned and unplanned readmissions in terms of patient sex, marital status, age, length of initial stay, the time between discharge, ICU stay, surgery, and health insurance. CONCLUSION: Accurate information on 30-day planned and unplanned readmissions facilitates effective planning of healthcare resource allocation. Identifying risk factors for 30-day unplanned readmissions can help develop interventions to reduce readmission rates.

Development and validation of an artificial intelligence-based system for predicting colorectal cancer invasion depth using multi-modal data.

OBJECTIVES: Accurate endoscopic optical prediction of the depth of cancer invasion is critical for guiding an optimal treatment approach of large sessile colorectal polyps but was hindered by insufficient endoscopists expertise and inter-observer variability. We aimed to construct a clinically applicable artificial intelligence (AI) system for the identification of presence of cancer invasion in large sessile colorectal polyps. METHODS: A deep learning-based colorectal cancer invasion calculation (CCIC) system was constructed. Multi-modal data including clinical information, white light (WL) and image-enhanced endoscopy (IEE) were included for training. The system was trained using 339 lesions and tested on 198 lesions across three hospitals. Man-machine contest, reader study and video validation were further conducted to evaluate the performance of CCIC. RESULTS: The overall accuracy of CCIC system using image and video validation was 90.4% and 89.7%, respectively. In comparison with 14 endoscopists, the accuracy of CCIC was comparable with expert endoscopists but superior to all the participating senior and junior endoscopists in both image and video validation set. With CCIC augmentation, the average accuracy of junior endoscopists improved significantly from 75.4% to 85.3% (P = 0.002). CONCLUSIONS: This deep learning-based CCIC system may play an important role in predicting the depth of cancer invasion in colorectal polyps, thus determining treatment strategies for these large sessile colorectal polyps.

Identification of in vivo metabolites of Citri Sarcodactylis Fructus by UHPLC-Q/Orbitrap HRMS.

INTRODUCTION: Citri Sarcodactylis Fructus has the effects of relieving cough, removing phlegm, and reducing asthma, but little is known about the metabolic and distribution of its chemical constituents in vivo. Therefore, it is necessary to study the metabolism of Citri Sarcodactylis Fructus in vivo. OBJECTIVE: We aimed to (1) analyze the distribution of prototype compounds and metabolites of the chemical constituents of Citri Sarcodactylis Fructus in rat and (2) infer the metabolites and metabolic pathways of the chemical constituents. MATERIALS AND METHODS: A C18 column (3 × 100 mm, 2.6 µm) was used. The mobile phase was water containing 0.1% formic acid (eluent A) and acetonitrile containing 0.1% formic acid (eluent B) at a discharge rate of 0.3 mL/min. Mass spectra of biological samples were collected in electrospray ionization (ESI) positive ion mode in the m/z 100-1500 scan range. The obtained biological samples were then subjected to chemical analysis, including plasma, urine, feces, and heart, liver, spleen, lungs, kidneys, stomach, and small intestine tissues. Prototype compounds and metabolites were identified. RESULTS: In all, 40 prototype compounds and 78 metabolites, including 26 phase I metabolites and 52 phase II metabolites, were identified using UHPLC-Q/Orbitrap HRMS. Eight possible metabolic pathways (reduction, hydrolysis, dehydration, methylation, hydroxylation, sulfation, glucuronidation, and demethylation) were proposed. The prototype compounds were predominantly distributed in lung tissues. The metabolites were mainly distributed in plasma and kidney tissues. CONCLUSION: We systematically investigated the metabolites of Citri Sarcodactylis Fructus in vivo. We suggest metabolic pathways that might be relevant for further metabolic studies and screening of active ingredients of Citrus Sarcodactylis Fructus in vivo.

An interpretable DIC risk prediction model based on convolutional neural networks with time series data.

Disseminated intravascular coagulation (DIC) is a complex, life-threatening syndrome associated with the end-stage of different coagulation disorders. Early prediction of the risk of DIC development is an urgent clinical need to reduce adverse outcomes. However, effective approaches and models to identify early DIC are still lacking. In this study, a novel interpretable deep learning based time series is used to predict the risk of DIC. The study cohort included ICU patients from a 4300-bed academic hospital between January 1, 2019, and January 1, 2022. Experimental results show that our model achieves excellent performance (AUC: 0.986, Accuracy: 95.7%, and F1:0.935). Gradient-weighted Class Activation Mapping (Grad-CAM) was used to explain how predictive models identified patients with DIC. The decision basis of the model was displayed in the form of a heat map. The model can be used to identify high-risk patients with DIC early, which will help in the early intervention of DIC patients and improve the treatment effect.

A deep learning-based system for real-time image reporting during esophagogastroduodenoscopy: a multicenter study.

BACKGROUND AND STUDY AIMS: Endoscopic reports are essential for the diagnosis and follow-up of gastrointestinal diseases. This study aimed to construct an intelligent system for automatic photo documentation during esophagogastroduodenoscopy (EGD) and test its utility in clinical practice. PATIENTS AND METHODS: Seven convolutional neural networks trained and tested using 210,198 images were integrated to construct the endoscopic automatic image reporting system (EAIRS). We tested its performance through man-machine comparison at three levels: internal, external, and prospective test. Between May 2021 and June 2021, patients undergoing EGD at Renmin Hospital of Wuhan University were recruited. The primary outcomes were accuracy for capturing anatomical landmarks, completeness for capturing anatomical landmarks, and detected lesions. RESULTS: The EAIRS outperformed endoscopists in retrospective internal and external test. A total of 161 consecutive patients were enrolled in the prospective test. The EAIRS achieved an accuracy of 95.2% in capturing anatomical landmarks in the prospective test. It also achieved higher completeness on capturing anatomical landmarks compared with endoscopists: (93.1% vs. 88.8%), and was comparable to endoscopists on capturing detected lesions: (99.0% vs. 98.0%). CONCLUSIONS: The EAIRS can generate qualified image reports and could be a powerful tool for generating endoscopic reports in clinical practice.

Randomised controlled trial of WISENSE, a real-time quality improving system for monitoring blind spots during esophagogastroduodenoscopy.

OBJECTIVE: Esophagogastroduodenoscopy (EGD) is the pivotal procedure in the diagnosis of upper gastrointestinal lesions. However, there are significant variations in EGD performance among endoscopists, impairing the discovery rate of gastric cancers and precursor lesions. The aim of this study was to construct a real-time quality improving system, WISENSE, to monitor blind spots, time the procedure and automatically generate photodocumentation during EGD and thus raise the quality of everyday endoscopy. DESIGN: WISENSE system was developed using the methods of deep convolutional neural networks and deep reinforcement learning. Patients referred because of health examination, symptoms, surveillance were recruited from Renmin hospital of Wuhan University. Enrolled patients were randomly assigned to groups that underwent EGD with or without the assistance of WISENSE. The primary end point was to ascertain if there was a difference in the rate of blind spots between WISENSE-assisted group and the control group. RESULTS: WISENSE monitored blind spots with an accuracy of 90.40% in real EGD videos. A total of 324 patients were recruited and randomised. 153 and 150 patients were analysed in the WISENSE and control group, respectively. Blind spot rate was lower in WISENSE group compared with the control (5.86% vs 22.46%, p<0.001), and the mean difference was -15.39% (95% CI -19.23 to -11.54). There was no significant adverse event. CONCLUSIONS: WISENSE significantly reduced blind spot rate of EGD procedure and could be used to improve the quality of everyday endoscopy. TRIAL REGISTRATION NUMBER: ChiCTR1800014809; Results.