Objective:To investigate the value of radiomics nomogram based on standardized pre-treatment chest enhanced CT in predicting the mutation status of epidermal growth factor receptor (EGFR) for patients with lung adenocarcinoma.Methods:A retrospective analysis was conducted on pre-treatment chest enhanced CT images and clinical data of 262 patients from the affiliated hospital of Jining Medical University with pathologically proven primary lung adenocarcinoma who received EGFR gene testing, including EGFR wild type ( n=122) and mutant type ( n=140). The patients were divided into training group ( n=183) and testing group ( n=79) according to a ratio of 7∶3 by stratified sampling method. Standardized pre-processed the images, delineated the ROI and extracted the radiomics features. Least absolute shrinkage and selection operator (LASSO) algorithm was used to reduce the dimension and select key features. The standardized radiomics model, clinical model and the combined model were established by Logistic Regression (LR) machine learning method. Calculated the Rad-score and drew the nomogram. ROC curve and Delong were used to evaluate and compare the predictive performance of different models. Results:23 standardized enhanced CT radiomics features and 4 clinical features were selected. The predictive performance of standardized radiomics model was better than that of non-standardized radiomics model [area under curve (AUC): 0.863 vs. 0.805, t=2.19, P<0.05]. The AUCs of the combined model and standardized radiomics model were higher than that of the clinical model (training group: 0.885, 0.863 vs. 0.774, t=3.57, 2.17, P<0.05; testing group: 0.873, 0.829 vs. 0.763, t=2.19, 2.02, P<0.05). The radiomics nomogram was built based on Rad-score, age, sex, smoking history and BMI. Conclusions:The combined model and standardized radiomics model could effectively predict the mutation status of EGFR gene in lung adenocarcinoma patients before treatment, providing valuable clinical insights.

Purpose: The poor retention and ambiguous differentiation of stem cells (SCs) within corpus cavernosum (CC) limit the cell application in erectile dysfunction (ED). Herein, the effects and mechanism of microRNA-145 (miR-145) gene modification on modulating the traits and fate of bone marrow-derived mesenchymal stem cells (BMSCs) were investigated. Materials and Methods: The effects of miR-145 on cell apoptosis, proliferation, migration, and differentiation were determined by flow cytometry, cell counting kit-8, transwell assays and myogenic induction. Then, the age-related ED rats were recruited to four groups including phosphate buffer saline, BMSC, vector-BMSC, overexpressed-miR-145-BMSC groups. After cell transplantation, the CC were harvested and prepared to demonstrate the retention and differentiation of BMSCs by immunofluorescent staining. Then, the target of miR-145 was verified by quantitative real-time polymerase chain reaction and immunohistochemical. After that, APTO-253, as an inducer of Krüppel-like factor 4 (KLF4), was introduced for rescue experiments in corpus cavernosum smooth muscle cells (CCSMCs) under the co-culture system. Results: In vitro, miR-145 inhibited the migration and apoptosis of BMSCs and promoted the differentiation of BMSCs into smooth muscle-like cells with stronger contractility. In vivo, the amount of 5-ethynyl-2′-deoxyuridine (EdU)+cells within CC was significantly enhanced and maintained in the miR-145 gene modified BMSC group. The EdU/CD31 co-staning was detected, however, no co-staining of EdU/α-actin was observed. Furthermore, miR-145, which secreted from the gene modified BMSCs, dampened the expression of KLF4. However, the effects of miR-145 on CCSMCs could be rescued by APTO-253. Conclusions Overall, miR-145 modification prolongs the retention of the transplanted BMSCs within the CC, and this effect might be attributed to the modulation of the miR-145/KLF4 axis. Consequently, our findings offer a promising and innovative strategy to enhance the local stem cell-based treatments.

Objective: To investigate the diagnostic efficiency and clinical application value of an artificial intelligence-assisted diagnosis model based on a three-dimensional convolutional neural network (3D CNN) on echocardiographic videos of patients with hypertensive heart disease, chronic renal failure (CRF) and hypothyroidism with cardiac involvement. Methods: This study is a retrospective study. The patients with hypertensive heart disease, CRF and hypothyroidism with cardiac involvement, who admitted in Henan Provincial People's Hospital from April 2019 to October 2021, were enrolled. Patients were divided into hypertension group, CRF group, and hypothyroidism group. Additionally, a simple random sampling method was used to select control healthy individuals, who underwent physical examination at the same period. The echocardiographic video data of enrolled participants were analyzed. The video data in each group was divided into a training set and an independent testing set in a ratio of 5 to 1. The temporal and spatial characteristics of videos were extracted using an inflated 3D convolutional network (I3D). The artificial intelligence assisted diagnosis model was trained and tested. There was no case overlapped between the training and validation sets. A model was established according to cases or videos based on video data from 3 different views (single apical four chamber (A4C) view, single parasternal left ventricular long-axis (PLAX) view and all views). The statistical analysis of diagnostic performance was completed to calculate sensitivity, specificity and area under the ROC curve (AUC). The time required for the artificial intelligence and ultrasound physicians to process cases was compared. Results: A total of 730 subjects aged (41.9±12.7) years were enrolled, including 362 males (49.6%), and 17 703 videos were collected. There were 212 cases in the hypertensive group, 210 cases in the CRF group, 105 cases in the hypothyroidism group, and 203 cases in the normal control group. The diagnostic performance of the model predicted by cases based on single PLAX view and all views data was excellent: (1) in the hypertensive group, the sensitivity, specificity and AUC of models based on all views data were 97%, 89% and 0.93, respectively, while those of models based on a single PLAX view were 94%, 95%, and 0.94, respectively; (2) in the CRF group, the sensitivity, specificity and AUC of models based on all views data were 97%, 95% and 0.96, respectively, while those of models based on a single PLAX view were 97%, 89%, and 0.93, respectively; (3) in the hypothyroidism group, the sensitivity, specificity and AUC of models based on all views data were 64%, 100% and 0.82, respectively, while those of models based on a single PLAX view were 82%, 89%, and 0.86, respectively. The time required for the 3D CNN model to measure and analyze the echocardiographic videos of each subject was significantly shorter than that for the ultrasound physicians ((23.96±6.65)s vs. (958.25±266.17)s, P<0.001). Conclusions: The artificial intelligence assisted diagnosis model based on 3D CNN can extract the dynamic temporal and spatial characteristics of echocardiographic videos jointly, and quickly and efficiently identify hypertensive heart disease and cardiac changes caused by CRF and hypothyroidism.
Male ; Humans ; Artificial Intelligence ; Retrospective Studies ; Echocardiography/methods* ; Heart Diseases ; Hypertension ; Hypothyroidism

OBJECTIVE: To screen the prognostic biomarkers of metabolic genes in patients with multiple myeloma (MM), and construct a prognostic model of metabolic genes. METHODS: The histological database related to MM patients was searched. Data from MM patients and healthy controls with complete clinical information were selected for analysis.The second generation sequencing data and clinical information of bone marrow tissue of MM patients and healthy controls were collected from human protein atlas (HPA) and multiple myeloma research foundation (MMRF) databases. The gene set of metabolism-related pathways was extracted from Molecular Signatures Database (MSigDB) by Perl language. The biomarkers related to MM metabolism were screened by difference analysis, univariate Cox risk regression analysis and LASSO regression analysis, and the risk prognostic model and Nomogram were constructed. Risk curve and survival curve were used to verify the grouping effect of the model. Gene set enrichment analysis (GSEA) was used to study the difference of biological pathway enrichment between high risk group and low risk group. Multivariate Cox risk regression analysis was used to verify the independent prognostic ability of risk score. RESULTS: A total of 8 mRNAs which were significantly related to the survival and prognosis of MM patients were obtained (P<0.01). As molecular markers, MM patients could be divided into high-risk group and low-risk group. Survival curve and risk curve showed that the overall survival time of patients in the low-risk group was significantly better than that in the high risk group (P<0.001). GSEA results showed that signal pathways related to basic metabolism, cell differentiation and cell cycle were significantly enriched in the high-risk group, while ribosome and N polysaccharide biosynthesis signaling pathway were more enriched in the low-risk group. Multivariate Cox regression analysis showed that the risk score composed of the eight metabolism-related genes could be used as an independent risk factor for the prognosis of MM patients, and receiver operating characteristic curve (ROC) showed that the molecular signatures of metabolism-related genes had the best predictive effect. CONCLUSION Metabolism-related pathways play an important role in the pathogenesis and prognosis of patients with MM. The clinical significance of the risk assessment model for patients with MM constructed based on eight metabolism-related core genes needs to be confirmed by further clinical studies.
Humans ; Cell Cycle ; Multiple Myeloma/genetics* ; Prognosis ; Risk Factors

Nowadays potential preclinical drugs for the treatment of nonalcoholic steatohepatitis (NASH) have failed to achieve expected therapeutic efficacy because the pathogenic mechanisms are underestimated. Inactive rhomboid protein 2 (IRHOM2), a promising target for treatment of inflammation-related diseases, contributes to deregulated hepatocyte metabolism-associated nonalcoholic steatohepatitis (NASH) progression. However, the molecular mechanism underlying Irhom2 regulation is still not completely understood. In this work, we identify the ubiquitin-specific protease 13 (USP13) as a critical and novel endogenous blocker of IRHOM2, and we also indicate that USP13 is an IRHOM2-interacting protein that catalyzes deubiquitination of Irhom2 in hepatocytes. Hepatocyte-specific loss of the Usp13 disrupts liver metabolic homeostasis, followed by glycometabolic disorder, lipid deposition, increased inflammation, and markedly promotes NASH development. Conversely, transgenic mice with Usp13 overexpression, lentivirus (LV)- or adeno-associated virus (AAV)-driven Usp13 gene therapeutics mitigates NASH in 3 models of rodent. Mechanistically, in response to metabolic stresses, USP13 directly interacts with IRHOM2 and removes its K63-linked ubiquitination induced by ubiquitin-conjugating enzyme E2N (UBC13), a ubiquitin E2 conjugating enzyme, and thus prevents its activation of downstream cascade pathway. USP13 is a potential treatment target for NASH therapy by targeting the Irhom2 signaling pathway.

H 1-antihistamines are widely used in the treatment of various allergic diseases, but there are still many challenges in the safe and rational use of H 1-antihistamines in pediatrics, and there is a lack of guidance on the prescription review of H 1-antihistamines for children.In this paper, suggestions are put forward from the indications, dosage, route of administration, pathophysiological characteristics of children with individual difference and drug interactions, so as to provide reference for clinicians and pharmacists.

Aim To compare the effects of different methods on the preparation of ovariectomized mouse models. Methods The bilateral ovaries of mouse were completely removed by desmurgia and diathermocoagulation respectively. The effects of desmurgia and diathermocoagulation methods on ovariectomized mouse models were compared by detecting vaginal smears, organ indexes , biochemical indexes, Micro-CT was used to detect the mor-phological changes in femur tissue, and HE staining was used to observe the pathological changes in femur, uterus, thymus and spleen. Results Compared with the control group, the estrous cycle of mouse was disordered by desmurgia and diathermocoagulation, the indexes of uterus, spleen and thymus were reduced, the levels of BGP, BALP and E

The fundamental purpose of tissue-engineered skin development is to restore the skin barrier function of patients with severe skin injury, and this kind of product has become an ideal substitute for skin transplantation in clinic at present. With the development of three-dimensional bioprinting technology, the three-dimensional skin models constructed with complex structures such as skin appendages are also becoming increasingly mature. The stable three-dimensional skin model is widely used in skin physiological and pathological research, cosmetic safety and efficacy evaluation, and alternating animal experiments. In this paper, we introduced the three-dimensional bioprinting technology in categories, summarized the types of bio-inks commonly used for skin model construction, reviewed the recent advances of three-dimensional bioprinting technology applied in the field of skin tissue engineering, and explored and prospected the future directions of its research development and application fields.

Objective: This article aims to observe the changes in long noncoding RNA (lncRNA) expression profiles in rat hearts after ozone sub-chronic exposure. To provide scientific data to explore the role and mechanism of differentially expressed lncRNA in damaged hearts caused by ozone sub-chronic exposure. Methods: Eighteen Wistar rats were randomly divided into filtered air and ozone exposure groups, with nine rats in each group. The rats in filtered air group were exposed to filtered air, while the rats in ozone exposure group were exposed to ozone at 0.5 ppm(0.980 mg/m³)for 90 days at a frequency of 6 hours per day. After ozone exposure, cardiac tissues were collected and the total RNA was extracted. The expression level of lncRNA in the hearts of two groups was detected by microarray and qRT-PCR method and the potential functions of the differentially expressed lncRNA were analyzed by bioinformatics. Results: Compared with the filtered air group, lncRNA's expression profile was significantly altered in the rat hearts of ozone exposure group. A total of 167 lncRNA were up-regulated significantly and 64 lncRNA were down-regulated significantly. GO analysis indicated that the up-regulated lncRNA might involve in the process of regulating growth and development, and the down-regulated lncRNA might participate in nutrient catabolic. KEGG results showed that the up-regulated lncRNA might be involved in regulating the PI3K-Akt signaling pathway. The down-regulated lncRNA might regulate the metabolic processes of various vitamins and main energy-supplying substances. Conclusion: Ozone sub-chronic exposure can cause changes in the expression profile of lncRNA in rat hearts, which may regulate the effects of ozone sub-chronic exposure on the heart through the metabolism of energy and nutrients.
Animals ; Computational Biology ; Ozone/adverse effects* ; Phosphatidylinositol 3-Kinases ; RNA, Long Noncoding/genetics* ; Rats ; Rats, Wistar

Recent advancement in natural language processing (NLP) and medical imaging empowers the wide applicability of deep learning models. These developments have increased not only data understanding, but also knowledge of state-of-the-art architectures and their real-world potentials. Medical imaging researchers have recognized the limitations of only targeting images, as well as the importance of integrating multimodal inputs into medical image analysis. The lack of comprehensive surveys of the current literature, however, impedes the progress of this domain. Existing research perspectives, as well as the architectures, tasks, datasets, and performance measures examined in the present literature, are reviewed in this work, and we also provide a brief description of possible future directions in the field, aiming to provide researchers and healthcare professionals with a detailed summary of existing academic research and to provide rational insights to facilitate future research.
Humans ; Natural Language Processing ; Surveys and Questionnaires