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Several breast reduction techniques have been introduced, and the reliability of these techniques has been demonstrated in clinical practice. However, it is still controversial how patients should be evaluated radiologically both preoperative and postoperative. This study aims to compare the radiological findings seen following reduction mammoplasty with two different techniques (inferior pedicle and superomedial pedicle), in connection with the surgical steps. Medical records of 141 patients and a total of 278 breasts who underwent breast reduction with the diagnosis of macromastia were retrospectively analyzed. Demographic and operative data such as age, type of pedicle, preoperative and postoperative nipple-areola complex (NAC) position, and NAC transfer distance were recorded. Radiological evaluation was performed by two radiologists experienced in breast imaging by reinterpreting preoperative and postoperative mammography images. The rate of postoperative structural distortion (p < 0.001), thickened areola (p = 0.011), and retroareolar fibrotic band (p < 0.001) were observed to be significantly higher in the superomedial group. The risk of fat necrosis increases as the NAC transfer distance increases and a value of >9.5 cm in the NAC transfer distance can be considered as the cutoff value in terms of fat necrosis development, especially in those using superomedial pedicle technique. Surgical technique-specific benign radiological changes occur following reduction mammoplasty. However, these changes do not significantly affect the Breast imaging, reporting, and data system category. The localization of fat necrosis differs depending on the surgical technique, and the risk of fat necrosis increases as the NAC transfer distance increases, especially in those who have undergone superomedial pedicle breast reduction surgery. [ABSTRACT FROM AUTHOR]

In the last decade, numerous supervised deep learning approaches have been proposed for visual–inertial odometry (VIO) and depth map estimation, which require large amounts of labelled data. To overcome the data limitation, self-supervised learning has emerged as a promising alternative that exploits constraints such as geometric and photometric consistency in the scene. In this study, we present a novel self-supervised deep learning-based VIO and depth map recovery approach (SelfVIO) using adversarial training and self-adaptive visual–inertial sensor fusion. SelfVIO learns the joint estimation of 6 degrees-of-freedom (6-DoF) ego-motion and a depth map of the scene from unlabelled monocular RGB image sequences and inertial measurement unit (IMU) readings. The proposed approach is able to perform VIO without requiring IMU intrinsic parameters and/or extrinsic calibration between IMU and the camera. We provide comprehensive quantitative and qualitative evaluations of the proposed framework and compare its performance with state-of-the-art VIO, VO, and visual simultaneous localization and mapping (VSLAM) approaches on the KITTI, EuRoC and Cityscapes datasets. Detailed comparisons prove that SelfVIO outperforms state-of-the-art VIO approaches in terms of pose estimation and depth recovery, making it a promising approach among existing methods in the literature. [ABSTRACT FROM AUTHOR]

Highlights • The effects of electric vehicle (EV) parking lots and solar power plants (SPPs) are considered in this paper. • The system is analyzed from applicability point of view, investigating the effect of seasonal weather changes. • The SPP power generation is calculated in accordance with solar radiation data of Istanbul, Turkey. • The study consists of the design and calculation of EV parking durations and SPP power generation. • This paper also reviews the key factors for the EV parking lot equipped with SPP. Abstract In this paper, the integration of a solar power plant to an electric vehicle (EV) Parking Lot is analyzed in terms of reduction of power consumption and losses for various scenarios and operating conditions in a distribution system. The parking lot is designed for EVs and is fed by both grid and roof mounted photovoltaic (PV) panels. The energy management system is designed for charging EVs for various scenarios combined with solar radiation data varying during daytime and the seasons. The energy transactions are simulated in accordance with daytime Solar Power Plant (SPP) generation and EV energy response on Electrical Power System Analysis Software (ETAP) environment. EVs based power consumption is calculated by considering the variation of charging sequences of different car brands. The study represents the results for daily change of power consumption for summer and winter conditions along with the reduction of power consumption, reduction of power losses, decreased main feeder ampacity, restoration of voltage level during SPP operation, and comparison of different scenarios and operation sequences. Finally, the effect of the SPP is presented in terms of reducing the peak and continuous power demand of the parking lot for various EV operations. [ABSTRACT FROM AUTHOR]

Ingestible wireless capsule endoscopy is an emerging minimally invasive diagnostic technology for inspection of the GI tract and diagnosis of a wide range of diseases and pathologies. Medical device companies and many research groups have recently made substantial progresses in converting passive capsule endoscopes to active capsule robots, enabling more accurate, precise, and intuitive detection of the location and size of the diseased areas. Since a reliable real time pose estimation functionality is crucial for actively controlled endoscopic capsule robots, in this study, we propose a monocular visual odometry (VO) method for endoscopic capsule robot operations. Our method lies on the application of the deep recurrent convolutional neural networks (RCNNs) for the visual odometry task, where convolutional neural networks (CNNs) and recurrent neural networks (RNNs) are used for the feature extraction and inference of dynamics across the frames, respectively. Detailed analyses and evaluations made on a real pig stomach dataset proves that our system achieves high translational and rotational accuracies for different types of endoscopic capsule robot trajectories. [ABSTRACT FROM AUTHOR]

Ulcerative colitis (UC) belongs to the inflammatory bowel disease (IBD) family, which is mainly caused by inflammation of the tissue in the colon and rectum. The severity of this infection can radically affect the patient's overall well-being. Although there is no definitive treatment for this disease, diagnosis of the severity of the disease through colonoscopy imaging and the use of personalized treatment can prevent progression to more malignant stages. Inter- and intra-observer variability combined with the complex nature of UC infection makes medical assessment cumbersome. Diagnosis and treatment of UC can be made more accurate and robust if disease severity can be determined in a standardized and automated manner. Therefore, the development of a computerized tool that can be integrated into the clinical decision-making process of UC classification is of great importance. In this work, we present an automated UC classification method, UC-NfNet, complemented by a synthetic data generation pipeline aimed at classifying colonoscopy UC images. We show that our model quantitatively outperforms state-of-the-art classification models such as ConViT, Inception-v4, NFNets, ResNets and Swin Transformer. In an independent reader study of five gastroenterologists, the average agreement between the UC-NfNet and individual gastroenterologists was higher than the agreement between individual gastroenterologists. This robust evaluation of the proposed AI system paves the way for clinical trials of AI-assisted UC classification. The code and dataset are publicly available at https://github.com/DeepMIALab/UC-NfNet. [Display omitted] • An ulcerative colitis classification model based on Normalizer-Free Network • A new ulcerative colitis dataset annotated by five expert gastroenterologists • Synthetic data to overcome the problems of imbalance and insufficient data • Interpretable approach to accurately identify morphological features of the severity • Reader study and performance comparison with five board-certified gastroenterologists [ABSTRACT FROM AUTHOR]

Abstract: This study investigated whether or not the anesthetic effect of ketamine in rats is dependent on adrenal gland hormones. The study was performed on two main rat groups, intact and adrenalectomized. Rat were divided into subgroups and given appropriate doses of ketamine, metyrapone or metyrosine. Durations of anesthesia in the groups were then recorded. Endogenous catecholamine levels were measured in samples taken from peripheral blood. This experimental results showed that ketamine did not induce anesthesia in intact rats at doses of 15 or 30mg/kg, and that at 60mg/kg anesthesia was established for only 11min. However, ketamine induced significant anesthesia even at a dose of 30mg/kg in animals in which production of endogenous catecholamine (adrenalin, noradrenalin dopamine) was inhibited with metyrosine at a level of 45–47%. Ketamine at 60mg/kg in animals in which endogenous catecholamine was inhibited at a level of 45–47% established anesthesia for 47.6min. However, ketamine at 30 and 60mg/kg induced longer anesthesia in adrenalectomized rats with higher noradrenalin and dopamine levels but suppressed adrenalin production. Adrenalin plays an important role in the control of duration of ketamine anesthesia, while noradrenalin, dopamine and corticosterone have no such function. If endogenous adrenalin is suppressed, ketamine can even provide sufficient anesthesia at a 2-fold lower dose. This makes it possible for ketamine to be used in lengthy surgical procedures. [Copyright &y& Elsevier]

The aim of this study was to determine the effect of obesity on recurrence time in ovarian cancer. This was a multicenter, retrospective chart review of 370 patients. The median time to recurrence was 15 months in obese and nonobese patients. Obesity does not affect the time to recurrence or progression-free survival in patients with ovarian cancer. Introduction/Background: The objective of this study was to examine whether obesity affects the time to recurrence in primary epithelial ovarian cancer. Patients and Methods: A multicenter retrospective chart review was performed between 2004 and 2009. Three hundred seventy patients were eligible for analysis. Demographic and clinicopathological variables and treatment-related data were collected. Women with a body mass index (BMI) > 30 were categorized as obese. The time to recurrence was quantified in terms of months. Survival analyses were performed using the Kaplan-Meier method and compared using log-rank testing. Results: One hundred thirty (35%) obese patients were compared with 240 (65%) nonobese patients. A recurrence was documented in 125 (47.9%) nonobese patients and 49 (37.7%) obese patients. Time to recurrence between both BMI groups was identical, at 15 months (P = 1.0). The progression-free survival was similar in obese and nonobese subjects (P = .118). Conclusion: Obesity does not affect the recurrence time in patients with primary ovarian cancer. [ABSTRACT FROM AUTHOR]

Study Objective: To determine the impact of the plica mediana dorsalis (PMD) on injected contrast media spread in the epidural space. Design: Prospective interventional study. Setting: Academic medical center. Patients: 30 chronic pain patients ranging in age from37 to 71 years, undergoing epidural steroid injection. Interventions and Measurements: Epidurograms were evaluated for the 1) presence or absence of a PMD and 2) bilateral differential density and the extent of contrast spread on either side of the midline, horizontally and vertically. Results: The PMD(defined as midline radiolucency in epidurograms)was observed in (80%) 24/30 patients based on the epidurograms that were evaluated. Denser contrast spread on one side was found in (79%) 19/ 24 patients who had the PMD and in (33%) 2/6 patients who did not have the PMD (P = 0.03). Horizontal and vertical asymmetrical spread of the contrast was observed in (67%) 16 of 24 patients with the PMD and in (50%) 3 of 6 of patients without the PMD in each direction independently. Conclusion: The difference in density of contrast spread on either side of the midline carries important clinical implications in understanding the pathogenesis of inadequate epidural analgesia and/or unilateral excessive motor weakness or numbness. [ABSTRACT FROM AUTHOR]

Abstract: Objective: To investigate whether thiamine pyrophosphate can prevent infertility developing in rats undergoing unilateral ovariectomy and with ischemia reperfusion induced in the contralateral ovary. Biochemical examinations of the ovaries were also performed. Study design: Rats were divided into two main groups of three subgroups each. An ischemia reperfusion model was established in the first main group, while surgical unilateral ovariectomy was performed in the second. Thiamine pyrophosphate and melatonin were administered to the subgroups. No additional procedure was performed in the control groups. The rats were then left in laboratory environments and their fertility levels were determined. Malondialdehyde, total glutathione and DNA damage products were measured in those rats from which ovarian tissue was collected. Results: The results showed that thiamine pyrophosphate prevented ischemia/reperfusion injury-related infertility, but melatonin did not provide adequate prevention. However, reproduction in healthy animals receiving melatonin began earlier compared to those receiving thiamine pyrophosphate. Melatonin suppressed oxidative stress caused by ischemia/reperfusion in ovarian tissue significantly better than did thiamine pyrophosphate. Conclusions: We think that different mechanisms, in addition to antioxidant activity, are involved in the prevention of reperfusion-associated infertility after ischemia. [Copyright &y& Elsevier]

Abstract: Objective: Epicardial adipose tissue (EAT) is proposed as a cardiovascular risk marker in non-uremic subjects. However, little is known about its role in patients with higher cardiovascular risk profile such as chronic kidney disease. The aim of this study was to investigate the relationship between EAT and several cardiovascular surrogate markers (coronary artery calcification (CAC), arterial stiffness and atherosclerosis) in patients on maintenance hemodialysis. Methods: A total of 191 prevalent hemodialysis patients were enrolled in this cross-sectional study. EAT and CAC scores (CACs) were determined by multi-slice computerized tomography, arterial stiffness by carotid-femoral pulse wave velocity (PWV), and carotid artery intima-media thickness (CA-IMT) by B-mode doppler ultrasonography. Results: Mean age was 59 ± 13 years and time on hemodialysis 75 ± 44 months. Twenty percent of the patients had diabetes. Mean EAT volume was 62.6 ± 26.8 cm3/m2. Mean CA-IMT and PWV values increased across the EAT tertiles. EAT was correlated with age, female gender, body mass index, albumin and lipid parameters. Additionally, CA-IMT and PWV values were positively correlated with EAT. EAT volume was significantly higher in patients with CACs >10 compared to the patients with CACs ≤10. Despite the univariate associations between EAT and cardiovascular surrogate markers, only age, body mass index and total cholesterol levels were associated with EAT in adjusted models. Conclusions: In prevalent hemodialysis patients, EAT is correlated with atherosclerosis, arterial stiffness and the presence of CAC. However, this correlation is not independent of other risk factors. [Copyright &y& Elsevier]

• Indocyanine green (ICG) dye is a contrast agent that fluoresces under near-infrared camera systems. • The features of indocyanine green-based photodiagnosis were researched. • Fluorescent property of ICG provides surgeons the ability to define tissues borders, functions and viability. • ICG fluorescence angiography technique has been used to reduce the incidance of postoperative hypoparathyroidism in endocrine surgery procedures. • The use of ICG fluorescence angiography with transoral endoscopic parathyroidectomy vestibular approach could be a method to increase operative success and cosmesis. Indocyanine green fluorescence (ICG) angiography has been used for many purposes including as part of a focused parathyroidectomy technique. Concomitant fluorescence of thyroid tissue may cause challenges defining parathyroid tissue during surgery, since ICG is not a selective fluorescent agent. On the other hand, cosmesis is still a big problem for patients due to the visible neck scars produced by the standard surgical technique. In this study, we described a novel technique to solve both these handicaps. Seven patients who underwent ICG fluorescence angiography-guided transoral endoscopic thyroidectomy and parathyroidectomy vestibular approach between February 2018 and July 2019 were included. Serum parathyroid hormone (PTH) levels were measured intraoperatively and on postoperative day 1. Fluorescent images were confirmed with intraoperative quick-PTH levels. All operations were done successfully without conversion to open surgery. Intense and isolated parathyroid fluorescent images were achieved in all operations. All patients had a 50 % decrease between the baseline and final quick-PTH levels and the final quick-PTH levels were in the normal range in all. One of 7 patients had epistaxis due to nasotracheal intubation. One of 7 patients had seroma on post-operative day 5. None of patients had mental nerve injury, permanent hypocalcemia and temporary or permanent recurrent laryngeal nerve injury. ICG-guided transoral endoscopic thyroid and parathyroid surgery can be used in select patients to increase operative success in focused parathyroidectomy with excellent cosmetic outcome also noted. [ABSTRACT FROM AUTHOR]

Mental health problems are currently diversifying, increasing the possibility of suicide. Exposure to psychological maltreatment is one of the factors that increases suicidal cognitions. In addition, psychological flexibility and meaning-centered approaches may be effective in coping with suicidal cognitions. A hypothesized model was tested to examine the relationships among psychological maltreatment, suicidal cognitions, psychological flexibility, and meaning-centered coping. Data were collected from a sample of 652 participants. Mediation and moderation analyses were conducted to examine the mediating and moderating role of psychological flexibility and meaning-centered coping in the relationship between childhood psychological maltreatment and suicide cognitions among Turkish adults. The results of the study indicated significant negative and positive relationships between psychological maltreatment, suicide cognitions, psychological flexibility, and meaning-centered coping. The findings suggest that psychological flexibility and meaning-centered coping have a serial mediating effect on the relationship between psychological maltreatment and suicide cognitions. Furthermore, according to the study results, psychological flexibility plays a moderating role both between psychological maltreatment and suicidal cognitions and between meaning-centered coping and suicidal cognitions. The study suggests that psychological maltreatment can be considered as a risk factor and meaning-centered coping and psychological flexibility as protective factors in suicide prevention studies. [ABSTRACT FROM AUTHOR]

Abstract: Aim: Diabetes is associated with abnormalities in lipid profile and increased oxidative stress. Statins are preferred agents in diabetic patients due to their antioxidant and LDL-C lowering effects. This study is designed to compare the effects of atorvastatin and rosuvastatin on low density lipoprotein cholesterol (LDL-C), lipid hydroperoxide (LOOH), total oxidant status (TOS) and total antioxidant capacity (TAC) in diabetic patients with hyperlipidemia. Materials and methods: Sixty two patients who have type 2 diabetes mellitus with serum LDL levels more than 100mg/dL were randomly assigned to receive atorvastatin 20mg (n =31) or rosuvastatin 10mg (n =31). Blood tests were performed at the beginning of the study and after three months. Results: There were no statistically significant differences in the pre- and after treatment levels of the LDL-C between groups. TAC values were increased in both groups and statistically significant in the former group (p =0.007). There was no diferrence between the change percentages ((after treatment TAC−pretreatment TAC)/pretreatment level) of TAC between two treatment groups. The effects of two drugs on the other oxidative parameters were not significantly different. Conclusion: Both atorvastatin and rosuvastatin may be helpful in reducing increased oxidative stress in diabetic patients with hyperlipidemia. [Copyright &y& Elsevier]

• To mitigate the paucity of endoscopy data with time-synchronized 6 DoF ground truth pose, and high precision topographical information obtained from multiple ex-vivo organs and phantom colon, we have created a comprehensive EndoSLAM dataset recorded using multiple endoscopic cameras. • EndoSLAM dataset is available as an opensource and convenient to use for depth, pose estimation, simultaneous localization and mapping (SLAM), 3D map reconstruction and domain adaptation tasks. • We have also propounded Endo-SfMLearner as a spatial attention based monocular depth and pose estimation algorithm which is specifically optimized via hybrid loss function to deal with the problems in endoscopy images such as frequently changing enlightenment conditions and scale inconsistency between consecutive frames. Experimental analysis shows the applicability of Endo-SfMLearner on endoscopy images compared to the state-of-the-art methods.(Zhou, Brown, Snavely, Lowe, 2017) [Display omitted] Deep learning techniques hold promise to develop dense topography reconstruction and pose estimation methods for endoscopic videos. However, currently available datasets do not support effective quantitative benchmarking. In this paper, we introduce a comprehensive endoscopic SLAM dataset consisting of 3D point cloud data for six porcine organs, capsule and standard endoscopy recordings, synthetically generated data as well as clinically in use conventional endoscope recording of the phantom colon with computed tomography(CT) scan ground truth. A Panda robotic arm, two commercially available capsule endoscopes, three conventional endoscopes with different camera properties, two high precision 3D scanners, and a CT scanner were employed to collect data from eight ex-vivo porcine gastrointestinal (GI)-tract organs and a silicone colon phantom model. In total, 35 sub-datasets are provided with 6D pose ground truth for the ex-vivo part: 18 sub-datasets for colon, 12 sub-datasets for stomach, and 5 sub-datasets for small intestine, while four of these contain polyp-mimicking elevations carried out by an expert gastroenterologist. To verify the applicability of this data for use with real clinical systems, we recorded a video sequence with a state-of-the-art colonoscope from a full representation silicon colon phantom. Synthetic capsule endoscopy frames from stomach, colon, and small intestine with both depth and pose annotations are included to facilitate the study of simulation-to-real transfer learning algorithms. Additionally, we propound Endo-SfMLearner, an unsupervised monocular depth and pose estimation method that combines residual networks with a spatial attention module in order to dictate the network to focus on distinguishable and highly textured tissue regions. The proposed approach makes use of a brightness-aware photometric loss to improve the robustness under fast frame-to-frame illumination changes that are commonly seen in endoscopic videos. To exemplify the use-case of the EndoSLAM dataset, the performance of Endo-SfMLearner is extensively compared with the state-of-the-art: SC-SfMLearner, Monodepth2, and SfMLearner. The codes and the link for the dataset are publicly available at https://github.com/CapsuleEndoscope/EndoSLAM. A video demonstrating the experimental setup and procedure is accessible as Supplementary Video 1. [ABSTRACT FROM AUTHOR]

• To mitigate the paucity of capsule endoscopy data with ground truth depth, pose and topographical information we develop VR-Caps, a virtual capsule endoscopy simulation environment that uses advanced rendering techniques. • VR-Caps can generate fully-labeled and realistic synthetic data that is consistent with the topology and texture of real organs for control, navigation and machine vision related tasks. • Experimental analysis shows the applicability of VR-Caps for five different computational and quantitative endoscopy tasks and its adaptation to real endoscopy data. • VR-Caps is available as an open source easy to use tool for computational and quantitative endoscopy researchers. [Display omitted] Current capsule endoscopes and next-generation robotic capsules for diagnosis and treatment of gastrointestinal diseases are complex cyber-physical platforms that must orchestrate complex software and hardware functions. The desired tasks for these systems include visual localization, depth estimation, 3D mapping, disease detection and segmentation, automated navigation, active control, path realization and optional therapeutic modules such as targeted drug delivery and biopsy sampling. Data-driven algorithms promise to enable many advanced functionalities for capsule endoscopes, but real-world data is challenging to obtain. Physically-realistic simulations providing synthetic data have emerged as a solution to the development of data-driven algorithms. In this work, we present a comprehensive simulation platform for capsule endoscopy operations and introduce VR-Caps, a virtual active capsule environment that simulates a range of normal and abnormal tissue conditions (e.g., inflated, dry, wet etc.) and varied organ types, capsule endoscope designs (e.g., mono, stereo, dual and 360 ∘ camera), and the type, number, strength, and placement of internal and external magnetic sources that enable active locomotion. VR-Caps makes it possible to both independently or jointly develop, optimize, and test medical imaging and analysis software for the current and next-generation endoscopic capsule systems. To validate this approach, we train state-of-the-art deep neural networks to accomplish various medical image analysis tasks using simulated data from VR-Caps and evaluate the performance of these models on real medical data. Results demonstrate the usefulness and effectiveness of the proposed virtual platform in developing algorithms that quantify fractional coverage, camera trajectory, 3D map reconstruction, and disease classification. All of the code, pre-trained weights and created 3D organ models of the virtual environment with detailed instructions how to setup and use the environment are made publicly available at https://github.com/CapsuleEndoscope/VirtualCapsuleEndoscopy and a video demonstration can be seen in the supplementary videos (Video-I). [ABSTRACT FROM AUTHOR]