Objective: To investigate the possible pathogenesis and report the postoperative results of the late tricuspid regurgitation (TR) after left cardiac valve replacement. Methods: 56 patients developed severe TR after left cardiac valve replacement, including 10 patients with normal prosthesis valve function (group A) and 46 patients with prosthesis valve dysfunction (group B). Four patients underwent mitral valve replacement (MVR) and 6 patients underwent mitral and aortic valve replacement (DVR) in group A. In group B, 36 patients received MVR, 4 aortic valve replacement (AVR) and 6 DVR. Ten patients underwent tricuspid De Vega annuloplasty and 46 patients' tricuspid valves were normal during the initial operation. The surgical treatment of tricuspid valve included tricuspid valve replacement (TVR) in 9 and tricuspid valve plasty (TVP) in 47 at the second operation. Results: Two patients died postoperatively with hospital mortality of 3.6%. The 54 survivors were followed up from 6 to 132 months, mean 79.4 months. The heart function improved significantly in 8 after TVR and 40 after TVP. However, echocardiography showed moderate TR in 5 and severe TR in 1 patient after TVP and medical treatment was needed. Conclusion: The sustained pulmonary hypertension, irreversible right heart impairment, resumption of left ventricular function and sustained atrial fibrillation may be responsible for the development of late TR after left cardiac valve replacement. TVR may achieve a reliable result for severe functional TR and rheumatic tricuspid valve lesion. In some patients with TVP during the follow up, the TR might become more serious.

The serotonergic system in vertebrates and invertebrates has been a focus for over 50 years and will likely continue in the future. Recently, genomic analysis and discovery of alternative splicing and differential expression in tissues have increased the knowledge of serotonin (5-HT) receptor types. Comparative studies can provide useful insights to the wide variety of mechanistic actions of 5-HT responsible for behaviors regulated or modified by 5-HT. To determine cellular responses and influences on neural systems as well as the efferent control of behaviors by the motor units, preparations amenable to detailed studies of synapses are beneficial as working models. The invertebrate neuromuscular junctions (NMJs) offer some unique advantages for such investigations; action of 5-HT at crustacean NMJs has been widely studied, and leech and Aplysia continue to be key organisms. However, there are few studies in insects likely due to the focus in modulation within the CNS and lack of evidence of substantial action of 5-HT at the Drosophila NMJs. There are only a few reports in gastropods and annelids as well as other invertebrates. In this review we highlight some of the key findings of 5-HT actions and receptor types associated at NMJs in a variety of invertebrate preparations in hopes that future studies will build on this knowledge base.
Alternative Splicing ; Aplysia ; Drosophila ; Gastropoda ; Insects ; Invertebrates ; Knowledge Bases ; Neuromuscular Junction ; Serotonin ; Synapses ; Synaptic Transmission ; Vertebrates

OBJECTIVETo investigate the mechanisms by which hypertension occurs in D(3) dopamine receptor null mice (D(3)-/-).

METHODSSeveral parameters, including blood pressure, renal sodium excretion, D(3) receptor protein and mRNA expression, plasma renin activity, norepinephrine concentration and AT(1) receptor expression were checked in D(3)-/- mice and their littermate wild type mice (D(3)+/+). Moreover, the vasorelaxant effect of D(3) receptor stimulation was measured with ex-vivo mesenteric artery isolated from Wistar-Kyoto rats.

RESULTSBlood pressure was higher in D(3)-/- mice compared with that in D(3)+/+ mice, salt-loading had no effect on blood pressure in both groups, at the last period, sodium excretion was lower in D(3)-/- mice as compared with D(3)+/+ mice, renal renin activity and AT(1) receptor expression were higher in D(3) -/- [corrected] mice than in D(3) +/+ [corrected] mice. In contrast, no difference of renal norepinephrine was found in two groups. When using angiotensin II subtype-1 receptor antagonist, the systolic blood pressure declined for a longer duration in mutant mice than in wild-type mice. Vaso-relaxation was found in ex-vivo isolated mesenteric artery when D(3) receptor was stimulated.

CONCLUSIONSElevation of blood pressure in D(3)-/- mice might be related with impaired renal sodium excretion and vaso-relaxation in resistance artery.

Animals ; Hypertension ; genetics ; physiopathology ; Kidney ; Mesenteric Arteries ; physiopathology ; Mice ; Mice, Inbred BALB C ; Mice, Knockout ; Rats ; Receptors, Dopamine D3 ; genetics

Objective: To develop a machine learning (ML) pipeline based on radiomics to predict Coronavirus Disease 2019 (COVID-19) severity and the future deterioration to critical illness using CT and clinical variables. Materials and Methods: Clinical data were collected from 981 patients from a multi-institutional international cohort with real-time polymerase chain reaction-confirmed COVID-19. Radiomics features were extracted from chest CT of the patients. The data of the cohort were randomly divided into training, validation, and test sets using a 7:1:2 ratio. A ML pipeline consisting of a model to predict severity and time-to-event model to predict progression to critical illness were trained on radiomics features and clinical variables. The receiver operating characteristic area under the curve (ROC-AUC), concordance index (C-index), and time-dependent ROC-AUC were calculated to determine model performance, which was compared with consensus CT severity scores obtained by visual interpretation by radiologists. Results: Among 981 patients with confirmed COVID-19, 274 patients developed critical illness. Radiomics features and clinical variables resulted in the best performance for the prediction of disease severity with a highest test ROC-AUC of 0.76 compared with 0.70 (0.76 vs. 0.70, p = 0.023) for visual CT severity score and clinical variables. The progression prediction model achieved a test C-index of 0.868 when it was based on the combination of CT radiomics and clinical variables compared with 0.767 when based on CT radiomics features alone (p < 0.001), 0.847 when based on clinical variables alone (p = 0.110), and 0.860 when based on the combination of visual CT severity scores and clinical variables (p = 0.549). Furthermore, the model based on the combination of CT radiomics and clinical variables achieved time-dependent ROC-AUCs of 0.897, 0.933, and 0.927 for the prediction of progression risks at 3, 5 and 7 days, respectively. Conclusion CT radiomics features combined with clinical variables were predictive of COVID-19 severity and progression to critical illness with fairly high accuracy.

Objective: To develop a machine learning (ML) pipeline based on radiomics to predict Coronavirus Disease 2019 (COVID-19) severity and the future deterioration to critical illness using CT and clinical variables. Materials and Methods: Clinical data were collected from 981 patients from a multi-institutional international cohort with real-time polymerase chain reaction-confirmed COVID-19. Radiomics features were extracted from chest CT of the patients. The data of the cohort were randomly divided into training, validation, and test sets using a 7:1:2 ratio. A ML pipeline consisting of a model to predict severity and time-to-event model to predict progression to critical illness were trained on radiomics features and clinical variables. The receiver operating characteristic area under the curve (ROC-AUC), concordance index (C-index), and time-dependent ROC-AUC were calculated to determine model performance, which was compared with consensus CT severity scores obtained by visual interpretation by radiologists. Results: Among 981 patients with confirmed COVID-19, 274 patients developed critical illness. Radiomics features and clinical variables resulted in the best performance for the prediction of disease severity with a highest test ROC-AUC of 0.76 compared with 0.70 (0.76 vs. 0.70, p = 0.023) for visual CT severity score and clinical variables. The progression prediction model achieved a test C-index of 0.868 when it was based on the combination of CT radiomics and clinical variables compared with 0.767 when based on CT radiomics features alone (p < 0.001), 0.847 when based on clinical variables alone (p = 0.110), and 0.860 when based on the combination of visual CT severity scores and clinical variables (p = 0.549). Furthermore, the model based on the combination of CT radiomics and clinical variables achieved time-dependent ROC-AUCs of 0.897, 0.933, and 0.927 for the prediction of progression risks at 3, 5 and 7 days, respectively. Conclusion CT radiomics features combined with clinical variables were predictive of COVID-19 severity and progression to critical illness with fairly high accuracy.

Catalytic Domain ; Enzyme Inhibitors ; metabolism ; pharmacology ; Influenza A Virus, H1N1 Subtype ; enzymology ; Models, Molecular ; Mutation ; Neuraminidase ; antagonists & inhibitors ; chemistry ; genetics ; metabolism ; Protein Binding

Background: and Purpose Recent studies suggested an increased incidence of cerebral venous thrombosis (CVT) during the coronavirus disease 2019 (COVID-19) pandemic. We evaluated the volume of CVT hospitalization and in-hospital mortality during the 1st year of the COVID-19 pandemic compared to the preceding year. Methods: We conducted a cross-sectional retrospective study of 171 stroke centers from 49 countries. We recorded COVID-19 admission volumes, CVT hospitalization, and CVT in-hospital mortality from January 1, 2019, to May 31, 2021. CVT diagnoses were identified by International Classification of Disease-10 (ICD-10) codes or stroke databases. We additionally sought to compare the same metrics in the first 5 months of 2021 compared to the corresponding months in 2019 and 2020 (ClinicalTrials.gov Identifier: NCT04934020). Results: There were 2,313 CVT admissions across the 1-year pre-pandemic (2019) and pandemic year (2020); no differences in CVT volume or CVT mortality were observed. During the first 5 months of 2021, there was an increase in CVT volumes compared to 2019 (27.5%; 95% confidence interval [CI], 24.2 to 32.0; P<0.0001) and 2020 (41.4%; 95% CI, 37.0 to 46.0; P<0.0001). A COVID-19 diagnosis was present in 7.6% (132/1,738) of CVT hospitalizations. CVT was present in 0.04% (103/292,080) of COVID-19 hospitalizations. During the first pandemic year, CVT mortality was higher in patients who were COVID positive compared to COVID negative patients (8/53 [15.0%] vs. 41/910 [4.5%], P=0.004). There was an increase in CVT mortality during the first 5 months of pandemic years 2020 and 2021 compared to the first 5 months of the pre-pandemic year 2019 (2019 vs. 2020: 2.26% vs. 4.74%, P=0.05; 2019 vs. 2021: 2.26% vs. 4.99%, P=0.03). In the first 5 months of 2021, there were 26 cases of vaccine-induced immune thrombotic thrombocytopenia (VITT), resulting in six deaths. Conclusions During the 1st year of the COVID-19 pandemic, CVT hospitalization volume and CVT in-hospital mortality did not change compared to the prior year. COVID-19 diagnosis was associated with higher CVT in-hospital mortality. During the first 5 months of 2021, there was an increase in CVT hospitalization volume and increase in CVT-related mortality, partially attributable to VITT.