Adiponectin and Cardiac Hypertrophy in Acromegaly

Background. Adiponectin is an adipocytes-derived hormone which has been shown to possess insulin-sensitizing, antiatherogenic, and anti-inflammatory properties. In acromegaly, the data on adiponectin is contradictory. The relationship between adiponectin levels and cardiac parameters has not been studied.Objectives. The aim of this study was to find out how adiponectin levels were affected in acromegalic patients and the relationship between adiponectin levels and cardiac parameters.Material and Methods. We included 30 subjects (15 male, 15 female), diagnosed with acromegaly and 30 healthy (10 male, 20 female) subjects. Serum glucose, insulin, GH, IGF-1 and adiponectin levels were obtained and the insulin resistance of the subjects was calculated. Echocardiographic studies of the subjects were performed.Results. We determined that adiponectin levels were significantly higher in the acromegalic group than the control group. In the acromegalic group, there was no statistically significant relation between serum adiponectin and growth hormone (GH), or insulin-like growth factor-1 (IGF-1) levels (p = 0.3, p = 0.1). We demonstrated that cardiac function and structure are affected by acromegaly. IVST, PWT, LVMI, E/A ratio, DT, ET, IVRT, VPR, and LVESV values were increased and the results were statistically significant. In the acromegalic group, adiponectin levels were positively related with left ventricle mass index (LVMI) but this correlation was found to be statistically weak (p = 0.03). In our study, there was a positive correlation between VAI and LVM. We also could not find any correlation between VAI and adiponectin levels.Conclusions. Although insulin resistance and high insulin levels occur in active acromegaly patients, adiponectin levels were higher in our study as a consequence of GH lowering therapies. Our study showed that adiponectin levels may be an indicator of the cardiac involvement acromegaly. However, the usage of serum adiponectin levels in acromegalic patients as an indicator of cardiac involvement should be supported with other, wide, multi-centered studies

Density-Guided Label Smoothing for Temporal Localization of Driving Actions

Temporal localization of driving actions plays a crucial role in advanced driver-assistance systems and naturalistic driving studies. However, this is a challenging task due to strict requirements for robustness, reliability and accurate localization. In this work, we focus on improving the overall performance by efficiently utilizing video action recognition networks and adapting these to the problem of action localization. To this end, we first develop a density-guided label smoothing technique based on label probability distributions to facilitate better learning from boundary video-segments that typically include multiple labels. Second, we design a post-processing step to efficiently fuse information from video-segments and multiple camera views into scene-level predictions, which facilitates elimination of false positives. Our methodology yields a competitive performance on the A2 test set of the naturalistic driving action recognition track of the 2022 NVIDIA AI City Challenge with an F1 score of 0.271

Histological changes to the rat mandibular condyle in response to long-term exposure to an extremely low frequency magnetic field

Background: The need for electrical power continues to increase along with the rapidly growing economies of industrialized countries. However, the effects of electrical fields (EFs) on human health remain unclear. Hence, the aim of the present study is to evaluate the histological effects of an extremely low frequency magnetic field (ELF-MF) on the rat mandibular condyle. Methods: Twenty female Sprague–Dawley rats were randomly allocated to one of two groups (n = 10): an untreated control group and an ELF-MF group exposed to a 1.5-mT ELF-MF for 4 h per day for 6 months. After exposure, the left mandibular condyles of all rats were collected for histopathological examinations. Results: The histopathological changes to the ELF-MF group included a non-homogenous appearance and decreased thickness of the hypertrophic layer, irregular appearances of bone marrow cavities, significant deterioration, and delayed calcification and ossification. There were no significant differences in the thicknesses or histomorphometric appearances of the fibrotic, proliferative, and hypertrophic layers of the mandibular condyle of rats between the groups (p = 0.05). Conclusion: Long-term ELF-MF exposure can induce histopathological changes to the mandibular condyle of rats

Detection of Object Throwing Behavior in Surveillance Videos

Anomalous behavior detection is a challenging research area within computer vision. Progress in this area enables automated detection of dangerous behavior using surveillance camera feeds. A dangerous behavior that is often overlooked in other research is the throwing action in traffic flow, which is one of the unique requirements of our Smart City project to enhance public safety. This paper proposes a solution for throwing action detection in surveillance videos using deep learning. At present, datasets for throwing actions are not publicly available. To address the use-case of our Smart City project, we first generate the novel public 'Throwing Action' dataset, consisting of 271 videos of throwing actions performed by traffic participants, such as pedestrians, bicyclists, and car drivers, and 130 normal videos without throwing actions. Second, we compare the performance of different feature extractors for our anomaly detection method on the UCF-Crime and Throwing-Action datasets. The explored feature extractors are the Convolutional 3D (C3D) network, the Inflated 3D ConvNet (I3D) network, and the Multi-Fiber Network (MFNet). Finally, the performance of the anomaly detection algorithm is improved by applying the Adam optimizer instead of Adadelta, and proposing a mean normal loss function that covers the multitude of normal situations in traffic. Both aspects yield better anomaly detection performance. Besides this, the proposed mean normal loss function lowers the false alarm rate on the combined dataset. The experimental results reach an area under the ROC curve of 86.10 for the Throwing-Action dataset, and 80.13 on the combined dataset, respectively

Physico-chemical properties of some polymer blended task specific novel S-(+)-2-3-dihydroxy-N, N, N-tributyl-propanaminiumtriflate and 1-(2-propoxy)- 3-methylimdazolium-borohydride room temperature ionic liquids

Two novel chiral ionic liquids S-(+)-2-3-dihydroxy-N, N, N-tributyl-propanaminiumtriflate and 1-(2-propoxy)-3-methylimdazolium-borohydride have been prepared using conventional metathesis reaction. These ionic liquids have been subjected to solution cast method followed by ultrasonication to obtain the corresponding ionic liquid gel polymer electrolytes with poly (vinylidene fluoride-co-hexafluoropropene) (PVDF-HFP), free-standing, rubbery, dimensionally stable films with a high degree of transparency have been obtained. Thermo-gravimetric analysis confirms that the intermediate solvent, acetone used for mixing PVDF-HFP polymer with ionic liquid is completely evaporated after gelation and drying process. Further thermal properties have been analyzed by differential scanning calorimetry. Scanning electron microscopy micrographs show the different surface morphology of the gel electrolytes according to nature of the ionic liquid. The structural information has been extracted by X-ray diffraction. The ionic conductivities of both polymer-ionic liquid blends are in the order of 10-3 to 10-5 S cm-1. Electrochemical stability window of these polymer electrolytes ranges from 4.0 to 5.0 V. Various physicochemical properties and fast ion conduction in the gel polymer membranes show their promising characteristics as electrolytes in different ionic devices

Facial mimicry and metacognitive judgments in emotion recognition are distinctly modulated by social anxiety and autistic traits

Action Contro

Prognosis related to treatment plan in patients with biliary tract cancer: A nationwide database study

BackgroundBiliary tract cancer (BTC) is a malignancy characterized by a low 5-year survival rate (<20 %). Clinical aspects such as tumor resectability, Eastern Cooperative Oncology Group performance status score (ECOG-PS), and molecular profiling are used to determine the treatment for these patients. Diagnosis and treatment are typically established by a multidisciplinary team (MDT). However, standardized practices for BTC are lacking, and there is a need to assess the impact of current MDT treatment decisions on BTC outcomes. The purpose of this study was to investigate the role of the treatment plan proposed by the first MDT conference on survival in patients with BTC, and to identify risk factors for poor survival in this population.MethodThis nationwide, multicenter, retrospective cohort study examined data from the Danish Liver Cancer Group (2013–2020) with confirmed BTC diagnoses. Multiple imputation was used to handle missing data. Survival and variable-survival rate relationships were analyzed using the Kaplan-Meier estimator, and the Cox regression model, respectively.ResultsEligible BTC-confirmed cases: n=1923. The overall median survival was 7.7 months (95 % CI: 7.1–8.5), with a 5-year survival rate of 16.3 %. Patients over 70 years of age, with ECOG-PS 3 or 4, non-operable cases, and with unresectable tumors had lower survival rates. Surgery as the first therapeutic option showed the highest median survival (33.1 months, 95 % CI: 27.2–41.6; p < 0.0001). Multivariable analysis showed that poor ECOG-PS, palliative and neoadjuvant chemotherapy, stereotactic radiotherapy, and best supportive care significantly increased mortality risk in patients with BTC (p=0.05).ConclusionAmong the therapeutic options prescribed by the MDT for patients with BTC, surgery offered the best survival rates, likely due to patient-related prognostic factors. High ECOG-PS was linked to an increased mortality risk regardless of age, highlighting the importance of this criterion in treatment decisions

Evaluation of the impact of cardiac implantable electronic devices on cine MRI for real-time adaptive cardiac radioablation on a 1.5 T MR-linac

Background: Stereotactic arrhythmia radioablation (STAR) is a novel treatment approach for refractory ventricular tachycardia (VT). The risk of treatment-induced toxicity and geographic miss can be reduced with online MRI-guidance on an MR-linac. However, most VT patients carry cardiac implantable electronic devices (CIED), which compromise MR images. Purpose: Robust MR-linac imaging sequences are required for cardiac visualization and accurate motion monitoring in presence of a CIED during MRI-guided STAR. We optimized two clinically available cine sequences for cardiorespiratory motion estimation in presence of a CIED on a 1.5 T MR-linac. The image quality, motion estimation accuracy, and geometric fidelity using these cine sequences were evaluated. Methods: Clinically available 2D balanced steady-state free precession (bSSFP, voxel size = 3.0 (Formula presented.) 3.0 (Formula presented.) 10 mm3, Tscan = 96 ms, bandwidth (BW) = 1884 Hz/px) and (Formula presented.) -spoiled gradient echo ((Formula presented.) -GRE, voxel size = 4.0 (Formula presented.) 4.0 (Formula presented.) 10 mm3, Tscan = 97 ms, BW = 500 Hz/px) sequences were adjusted for real-time cardiac visualization and cardiorespiratory motion estimation on a 1.5 T Unity MR-linac (Elekta AB, Stockholm, Sweden), while complying with safety guidelines for MRI in presence of CIEDs (specific absorption rate (Formula presented.) 2 W/kg and (Formula presented.) 80 mT/s). Cine acquisitions were performed in five healthy volunteers, with and without an implantable cardioverter– defibrillator (ICD) placed on the clavicle, and a VT patient. Generalized divergence-curl (GDC) deformable image registration (DIR) was used for automated landmark motion estimation in the left ventricle (LV). Gaussian processes (GP), a machine-learning technique, was trained using GDC landmarks and deployed for real-time cardiorespiratory motion prediction. (Formula presented.) -mapping was performed to assess geometric image fidelity in the presence of CIEDs. Results: CIEDs introduced banding artifacts partially obscuring cardiac structures in bSSFP acquisitions. In contrast, the (Formula presented.) -GRE was more robust to CIED-induced artifacts at the expense of a lower signal-to-noise ratio. In presence of an ICD, image-based cardiorespiratory motion estimation was possible for 85% (100%) of the volunteers using the bSSFP ((Formula presented.) -GRE) sequence. The in-plane 2D root-mean-squared deviation (RMSD) range between GDC-derived landmarks and manual annotations using the bSSFP (T1-GRE) sequence was 3.1–3.3 (3.3–4.1) mm without ICD and 4.6–4.6 (3.2–3.3) mm with ICD. Without ICD, the RMSD between the GP-predictions and GDC-derived landmarks ranged between 0.9 and 2.2 mm (1.3–3.0 mm) for the bSSFP (T1-GRE) sequence. With ICD, the RMSD between the GP-predictions and GDC-derived landmarks ranged between 1.3 and 2.2 mm (1.2–3.2 mm) using the bSSFP (T1-GRE) sequence resulting in an RMSD-increase of 42%–143% (bSSFP) and −61%–142% (T1-GRE). Lead-induced spatial distortions ranged between −0.2 and 0.2 mm (−0.7–1.2 mm) using the bSSFP ((Formula presented.) -GRE) sequence. The 98th percentile range of the spatial distortions in the gross target volume of the patient was between 0.0 and 0.4 mm (0.0–1.8 mm) when using bSSFP ((Formula presented.) -GRE). Conclusions: Tailored bSSFP and (Formula presented.) -GRE sequences can facilitate real-time cardiorespiratory estimation using GP trained with GDC-derived landmarks in the majority of landmark locations in the LV despite the presence of CIEDs. The need for high temporal resolution noticeably reduced achievable spatial resolution of the cine MRIs. However, the effect of the CIED-induced artifacts is device, patient and sequence dependent and requires specific assessment per case

Respiratory navigator-guided multi-slice free-breathing cardiac T1 mapping on a magnetic resonance-guided linear accelerator

BACKGROUND AND PURPOSE: Image-guided cardiac radioablation on a magnetic resonance-guided linear accelerator (MR-linac) is emerging as a non-invasive treatment alternative for patients with cardiac arrhythmia. Precise target identification is required for such treatments. However, owing to concerns with the use of gadolinium-based contrast agents during treatment with high-energy radiation, non-contrast alternatives must be considered. Native T1 mapping is a promising technique to delineate myocardial scar which can serve as a surrogate for the treatment target. Further, the likely presence of an implantable cardioverter defibrillator (ICD) in arrhythmia patients necessitates approaches that are robust to metal-related artefacts. MATERIALS AND METHODS: We implemented an electrocardiogram (ECG)-triggered free-breathing cardiac T1 mapping approach on an MR-linac, making use of a respiratory navigator to account for respiratory motion. The technique was validated in a motion phantom and tested in healthy volunteers. We also compared the use of different readout schemes to evaluate performance in the presence of an ICD. RESULTS: The free-breathing cardiac T1 mapping approach agreed within 5% compared with ground truth T1 in a motion phantom. In healthy volunteers, an average difference in T1 of -3.5% was seen between the free-breathing and breath-hold approaches, but T1 quantification was impacted by data discarded by the respiratory navigator. Compared to balanced SSFP, the spoiled gradient echo readout was much less susceptible to artefacts caused by an ICD, but the lower signal adversely affected T1 quantification. CONCLUSIONS: Free-breathing cardiac T1 mapping is feasible on an MR-linac. Further optimisation is required to reduce scan times and improve accuracy