Objective:To develop an artificial intelligence system using fully convolutional neural networks（FCN）to assist echocardiographers in the quantitative assessment of mitral regurgitation（MR）severity.Methods:From August 2021 to June 2024，echocardiographic images of 441 patients with MR were prospectively collected from Renmin Hospital of Wuhan University and the Central Hospital of Wuhan. After screening，a total of 269 patients（4 917 frames）were included in the study. Of these，3 644 frames（128 patients）of apical four-chamber color Doppler MR flow convergence images from Renmin Hospital of Wuhan University were selected as the training/validation set，while images from 121 patients（813 frames）were used as the internal test set. Additionally，images from 20 patients（460 frames）from the Central Hospital of Wuhan were selected as the external test set. The FCN algorithm was employed to capture features and segment the MR color region on the left atrial side，simultaneously outputting the regurgitant radius（r）for the calculation of the effective regurgitant orifice area and regurgitant volume. The severity of MR was then classified according to the 2017 guidelines of the American Society of Echocardiography. The segmentation and classification performance of the model was evaluated，and the measurement results of the AI system was compared with that of both senior and junior physicians.Results:In the internal test set，the accuracy of r identification for cases classified as Grade Ⅰ to Ⅳ was 0.48，0.81，0.86，and 0.87，respectively. In the external test set，the accuracy of r identification for cases classified as Grade Ⅰ to Ⅳ was 0.60，0.77，0.64，and 0.77，respectively. The average accuracy of MR classification in the internal and external test sets was 0.91 and 0.88，respectively.Conclusions:The FCN model is capable of segmenting the left atrial side regurgitant areas in apical four-chamber heart color Doppler images，aiding physicians in obtaining quantitative assessment parameters for MR，and assisting junior physicians in accurately assessing the severity of MR.

Objective:To develop an artificial intelligence system using fully convolutional neural networks（FCN）to assist echocardiographers in the quantitative assessment of mitral regurgitation（MR）severity.Methods:From August 2021 to June 2024，echocardiographic images of 441 patients with MR were prospectively collected from Renmin Hospital of Wuhan University and the Central Hospital of Wuhan. After screening，a total of 269 patients（4 917 frames）were included in the study. Of these，3 644 frames（128 patients）of apical four-chamber color Doppler MR flow convergence images from Renmin Hospital of Wuhan University were selected as the training/validation set，while images from 121 patients（813 frames）were used as the internal test set. Additionally，images from 20 patients（460 frames）from the Central Hospital of Wuhan were selected as the external test set. The FCN algorithm was employed to capture features and segment the MR color region on the left atrial side，simultaneously outputting the regurgitant radius（r）for the calculation of the effective regurgitant orifice area and regurgitant volume. The severity of MR was then classified according to the 2017 guidelines of the American Society of Echocardiography. The segmentation and classification performance of the model was evaluated，and the measurement results of the AI system was compared with that of both senior and junior physicians.Results:In the internal test set，the accuracy of r identification for cases classified as Grade Ⅰ to Ⅳ was 0.48，0.81，0.86，and 0.87，respectively. In the external test set，the accuracy of r identification for cases classified as Grade Ⅰ to Ⅳ was 0.60，0.77，0.64，and 0.77，respectively. The average accuracy of MR classification in the internal and external test sets was 0.91 and 0.88，respectively.Conclusions:The FCN model is capable of segmenting the left atrial side regurgitant areas in apical four-chamber heart color Doppler images，aiding physicians in obtaining quantitative assessment parameters for MR，and assisting junior physicians in accurately assessing the severity of MR.

To systematically construct a guideline to provide a methodological guide for researchers to develop patient decision aids.

To systematically construct a guideline to provide a methodological guide for researchers to develop patient decision aids.

BACKGROUND: Pneumonia-like primary pulmonary lymphoma (PPL) was commonly misdiagnosed as infectious pneumonia, leading to delayed treatment. The purpose of this study was to establish a computed tomography (CT)-based radiomics model to differentiate pneumonia-like PPL from infectious pneumonia. METHODS: In this retrospective study, 79 patients with pneumonia-like PPL and 176 patients with infectious pneumonia from 12 medical centers were enrolled. Patients from center 1 to center 7 were assigned to the training or validation cohort, and the remaining patients from other centers were used as the external test cohort. Radiomics features were extracted from CT images. A three-step procedure was applied for radiomics feature selection and radiomics signature building, including the inter- and intra-class correlation coefficients (ICCs), a one-way analysis of variance (ANOVA), and least absolute shrinkage and selection operator (LASSO). Univariate and multivariate analyses were used to identify the significant clinicoradiological variables and construct a clinical factor model. Two radiologists reviewed the CT images for the external test set. Performance of the radiomics model, clinical factor model, and each radiologist were assessed by receiver operating characteristic, and area under the curve (AUC) was compared. RESULTS: A total of 144 patients (44 with pneumonia-like PPL and 100 infectious pneumonia) were in the training cohort, 38 patients (12 with pneumonia-like PPL and 26 infectious pneumonia) were in the validation cohort, and 73 patients (23 with pneumonia-like PPL and 50 infectious pneumonia) were in the external test cohort. Twenty-three radiomics features were selected to build the radiomics model, which yielded AUCs of 0.95 (95% confidence interval [CI]: 0.94-0.99), 0.93 (95% CI: 0.85-0.98), and 0.94 (95% CI: 0.87-0.99) in the training, validation, and external test cohort, respectively. The AUCs for the two readers and clinical factor model were 0.74 (95% CI: 0.63-0.83), 0.72 (95% CI: 0.62-0.82), and 0.73 (95% CI: 0.62-0.84) in the external test cohort, respectively. The radiomics model outperformed both the readers' interpretation and clinical factor model ( P <0.05). CONCLUSIONS The CT-based radiomics model may provide an effective and non-invasive tool to differentiate pneumonia-like PPL from infectious pneumonia, which might provide assistance for clinicians in tailoring precise therapy.
Humans ; Retrospective Studies ; Pneumonia/diagnostic imaging* ; Analysis of Variance ; Tomography, X-Ray Computed ; Lymphoma/diagnostic imaging*

Blunt bowel injury (BBI) is relatively rare but life-threatening when delayed in surgical repair or anastomosis. Providing enteral nutrition (EN) in BBI patients with open abdomen after damage control surgery is challenging, especially for those with discontinuity of the bowel. Here, we report a 47-year-old male driver who was involved in a motor vehicle collision and developed ascites on post-trauma day 3. Emergency exploratory laparotomy at a local hospital revealed a complete rupture of the jejunum and then primary anastomosis was performed. Postoperatively, the patient was transferred to our trauma center for septic shock and hyperbilirubinemia. Following salvage resuscitation, damage control laparotomy with open abdomen was performed for abdominal sepsis, and a temporary double enterostomy (TDE) was created where the anastomosis was ruptured. Given the TDE and high risk of malnutrition, multiple portions EN were performed, including a proximal portion EN support through a nasogastric tube and a distal portion EN via a jejunal feeding tube. Besides, chyme delivered from the proximal portion of TDE was injected into the distal portion of TDE via a jejunal feeding tube. Hyperbilirubinemia was alleviated with the increase in chyme reinfusion. After 6 months of home EN and chyme reinfusion, the patient finally underwent TDE reversal and abdominal wall reconstruction and was discharged with a regular diet. For BBI patients with postoperative hyperbilirubinemia who underwent open abdomen, the combination of multiple portions EN and chyme reinfusion may be a feasible and safe option.
Male ; Humans ; Middle Aged ; Enteral Nutrition ; Intestines/surgery* ; Intestinal Diseases ; Abdomen/surgery* ; Anastomosis, Surgical ; Abdominal Injuries/surgery*

Jasminum pentaneurum Hand.-Mazz is widely used in Yao areas,but there are few reports on its composition,pharmacological effects,and quality markers(Q-markers)both domestically and internationally.On the basis of previous research,this article is based on the"Five Principles"of Q-marker research,predicting and analyzing the Q-marker of Jasminum pentaneurum Hand.-Mazz from aspects such as resource distribution,composition,traditional efficacy,plant phylogeny,and component specificity,providing a basis for further in-depth research.

Both natural ginsenoside F2 and unnatural ginsenoside 3β,20S-Di-O-Glc-DM were reported to exhibit anti-tumor activity. Traditional approaches for producing them rely on direct extraction from Panax ginseng, enzymatic catalysis or chemical synthesis, all of which result in low yield and high cost. Metabolic engineering of microbes has been recognized as a green and sustainable biotechnology to produce natural and unnatural products. Hence we engineered the complete biosynthetic pathways of F2 and 3β,20S-Di-O-Glc-DM in Saccharomyces cerevisiae via the CRISPR/Cas9 system. The titers of F2 and 3β,20S-Di-O-Glc-DM were increased from 1.2 to 21.0 mg/L and from 82.0 to 346.1 mg/L at shake flask level, respectively, by multistep metabolic engineering strategies. Additionally, pharmacological evaluation showed that both F2 and 3β,20S-Di-O-Glc-DM exhibited anti-pancreatic cancer activity and the activity of 3β,20S-Di-O-Glc-DM was even better. Furthermore, the titer of 3β,20S-Di-O-Glc-DM reached 2.6 g/L by fed-batch fermentation in a 3 L bioreactor. To our knowledge, this is the first report on demonstrating the anti-pancreatic cancer activity of F2 and 3β,20S-Di-O-Glc-DM, and achieving their de novo biosynthesis by the engineered yeasts. Our work presents an alternative approach to produce F2 and 3β,20S-Di-O-Glc-DM from renewable biomass, which lays a foundation for drug research and development.

Glycyrrizae Radix et Rhizoma has high medicinal value and is widely used in compatibility. It is used most frequently in the compatibility of Chinese medicine prescriptions，and is known as ''Guolao''（national medicine） and "master of all medicines". The characteristic active ingredients are mainly liquitin，glycyrrizic acid，glycyrrizin，and licochalcone. In different compatibilities，based on traditional and modern pharmacological theories，the corresponding effect of Glycyrrizae Radix et Rhizoma are brought into play through different mechanisms. Based on the traditional pharmacology of Glycyrrizae Radix et Rhizoma for tonifying spleen，replenishing Qi，clearing heat，removing toxin，dispelling phlegm，relieving cough and pain，and harmonizing various medicines，this paper used herbal authentication to analyze its compatibility application and mechanism. It was found that Glycyrrizae Radix et Rhizoma played corresponding effect in compatibilities through "tonification"，"harmonization"，and "regulation". For example，Glycyrrizae Radix et Rhizoma was combined with tonics including Ginseng Radix et Rhizoma and Atractylodis Macrocephalae Rhizoma to tonify the five Zang-organs through its strong tonifying effect，combined with Paeoniae Radix Alba and Aconiti Lateralis Radix Praeparata to relieve emergencies and pains through harmonizing medicine power and properties，and combined with Rhei Radix et Rhizoma and Natrii Sulfas to reduce medicine intensity through regulating medicine properties and body characteristics. The application law and mechanism of the modern pharmacological compatibility of Glycyrrizae Radix et Rhizoma were analyzed by data mining and network pharmacology. It was found that the modern clinical formula was often compatible with Glycyrrizae Radix et Rhizoma for anti-inflammation，cardiovascular and cerebrovascular protection，anti-virus，and anti-tumor，Ephedrae Herba and Scutellariae Radix for anti-inflammation，Bambusae Caulis in Taenias，Salviae Miltiorrhizae Radix et Rhizoma，and Aurantii Fructus Immaturus for cardiovascular and cerebrovascular protection，and Ophiopogonis Radix and Chuanxiong Rhizoma for nerves protection. Meanwhile，the important targets of the characteristic ingredients were protein kinase B1 （Akt1），interleukin-6 （IL-6），tumor necrosis factor （TNF），and epidermal growth factor receptor （EGFR）. The important characteristic pathways such as tyrosine kinase inhibitor resistance pathway and cyclic guanosine monophosphate （cGMP）/protein kinase G （PKG） signal pathway played the role of cardiovascular and cerebrovascular protection，and proteoglycan pathway in cancer played a neuroprotective role. This study is expected to provide references for the rational compatibility and application of Glycyrrizae Radix et Rhizoma，as well as the compatibility application of Chinese medicine prescriptions.

Objective:To meet the individualized needs of residents in standardized residency training of cardiac intervention specialty for cardiac ultrasound teaching, to construct a bionic 3D printing model of ultrasound source, and to discuss its application value in ultrasound teaching and simulation exercises.Methods:Sixty residents majored in cardiovascular medicine receiving standardized residency training of ultrasound in ultrasound imaging department of Renmin Hospital of Wuhan University were randomized into experimental group and control group in average. The experimental group adopted ultrasound bionic 3D printing heart model combined with problem-based learning (PBL) teaching method, and the control group adopted traditional multimedia PPT combined with PBL teaching method. At the end of teaching activities, theoretical examination, operation assessment and questionnaire survey were conducted to evaluate and compare the teaching effect between the two groups. SPSS 21.0 software was performed for t test. Results:The theoretical examination scores of the experimental group and the control group were (81.4±8.2) points and (74.8±9.4) points, respectively, P=0.002, and the operation assessment scores were (89.1±5.6) points and (71.5±8.8) points, respectively, P<0.001. The questionnaire survey showed that the experimental group had better feedbacks than the control group in the aspects of mastery of heart anatomy knowledge, learning experience, learning interest, learning efficiency, understanding of interventional heart disease, clinical skills of interventional operation and overall satisfaction (all P<0.05). Conclusions:Ultrasound bionic 3D printing combined with PBL teaching method can help strengthen the mastery of cardiac anatomy knowledge, promote the learning experience of cardiac ultrasound and improve the skills of interventional operation. The teaching effect is significant and the students' satisfaction is high.