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The involvement of lymph nodes critically affects patient outcomes in prostate cancer. While traditional risk models use factors like stage and PSA levels, the detection of lymph node involvement through modalities like PET targeting PSMA with 68 Ga radiotracer plays a pivotal role in guiding treatments ranging from prostatectomy to pelvic radiotherapy. This study aims to create a deep learning model to predict lymph node involvement in intermediate to high-risk prostate cancer patients using 68 Ga-PSMA PET/CT imagery, radiomics features, and various clinical parameters. For this study, 68 Ga-PSMA PET/CT scans and corresponding clinical data from 229 prostate cancer patients were retrospectively collected. An artificial intelligence model, integrating PET/CT fusion images, clinical data, and radiomics features, was developed using a slice-wise feature extractor and MNASNet for spatial feature extraction. The model was trained on 181 cases and tested on 48 cases. To assess the model's performance, a reader study was conducted on a balanced subset of the test data with five radiation oncologists. Among the 229 intermediate to high-risk patients with localized prostate cancer evaluated, 67 (30%) had lymph node metastasis, while 162 were non-metastatic. The proposed AI model achieved a mean accuracy of 0.85±0.03 and an F1 score of 0.73±0.03. In the reader study, radiation oncologists' mean evaluations showed lower metrics (accuracy 0.71±0.08, F1 score 0.70±0.07), compared to the AI model's mean accuracy of 0.79±0.02 and F1 score of 0.76±0.02. Our findings demonstrate the potential benefits of the proposed model in the clinical setting, particularly in enhancing decision-making by doctors in scenarios with high variability between readers, such as lymph node metastasis prediction., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

Significant diagnostic variability between and within observers persists in pathology, despite the fact that digital slide images provide the ability to measure and quantify features much more precisely compared to conventional methods. Automated and accurate segmentation of cancerous cell and tissue regions can streamline the diagnostic process, providing insights into the cancer progression, and helping experts decide on the most effective treatment. Here, we evaluate the performance of the proposed PathoSeg model, with an architecture comprising of a modified HRNet encoder and a UNet++ decoder integrated with a CBAM block to utilize attention mechanism for an improved segmentation capability. We demonstrate that PathoSeg outperforms the current state-of-the-art (SOTA) networks in both quantitative and qualitative assessment of instance and semantic segmentation. Notably, we leverage the use of synthetic data generated by PathopixGAN, which effectively addresses the data imbalance problem commonly encountered in histopathology datasets, further improving the performance of PathoSeg. It utilizes spatially adaptive normalization within a generative and discriminative mechanism to synthesize diverse histopathological environments dictated through semantic information passed through pixel-level annotated Ground Truth semantic masks.Besides, we contribute to the research community by providing an in-house dataset that includes semantically segmented masks for breast carcinoma tubules (BCT), micro/macrovesicular steatosis of the liver (MSL), and prostate carcinoma glands (PCG). In the first part of the dataset, we have a total of 14 whole slide images from 13 patients' liver, with fat cell segmented masks, totaling 951 masks of size 512 × 512 pixels. In the second part, it includes 17 whole slide images from 13 patients with prostate carcinoma gland segmentation masks, amounting to 30,000 masks of size 512 × 512 pixels. In the third part, the dataset contains 51 whole slides from 36 patients, with breast carcinoma tubule masks totaling 30,000 masks of size 512 × 512 pixels. To ensure transparency and encourage further research, we will make this dataset publicly available for non-commercial and academic purposes. To facilitate reproducibility and encourage further research, we will also make our code and pre-trained models publicly available at https://github.com/DeepMIALab/PathoSeg., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier B.V. All rights reserved.)

Background: The main complications seen in patients who have undergone modified radical mastectomy (MRM) are seroma, surgical site infection, hematoma, wound dehiscence, flap necrosis, and nerve damage. While these complications lead to some problems the most feared effect in the early period is that they cause a delay in adjuvant treatment. Incisional Negative Pressure Wound Therapy (iNPWT) decreases wound dehiscence by reducing oedema and tension, especially in the incision line. This study aim to compare recovery times and wound site complications between patients treated with conventional wound dressings and patients treated with iNPWT after MRM., Methods: A retrospective screening was made of the data of 50 patients who underwent MRM because of breast cancer in the General Surgery Clinic of XXX Hospital between 2018 and 2022, and were at high-risk of wound site complications. Two groups were formed as 30 patients applied with iNPWT and 20 patients applied with conventional dressings., Results: The mean age of the 50 female patients was 53.58 years (range, 30-80 years). The most frequently seen complications were seroma (20 patients) and partial flap ischaemia (14 patients). The mean number of iNPWT applications was 1.30 (range, 1-2), and the mean number of days of application was 4.47 (range, 2-9). Postoperative seroma was observed in 8 patients in the iNPWT group and in 12 patients in the conventional dressings group (p = 0.018). Flap ischaemia and the probability of dehiscence was determined at a statistically significantly higher rate in the patients in the conventional dressings groups (p = 0.005, p = 0.021)., Conclusion: The results of this study demonstrated that the use of iNPWT significantly reduced the amount of postoperative drainage, thereby contributing to early drain removal. Furthermore, iNPWT significantly reduced postoperative seroma, flap ischaemia, and flap dehiscence compared to conventional dressings., Competing Interests: Declaration of competing interest The authors have no relevant financial or non-financial interests to disclose., (Copyright © 2024 Asian Surgical Association and Taiwan Society of Coloproctology. Published by Elsevier B.V. All rights reserved.)

Formalin-fixation and paraffin-embedding (FFPE) is a technique for preparing and preserving tissue specimens that has been utilized in histopathology since the late 19th century. This process is further complicated by FFPE preparation steps such as fixation, processing, embedding, microtomy, staining, and coverslipping, which often results in artifacts due to the complex histological and cytological characteristics of a tissue specimen. The term "artifacts" includes, but is not limited to, staining inconsistencies, tissue folds, chattering, pen marks, blurring, air bubbles, and contamination. The presence of artifacts may interfere with pathological diagnosis in disease detection, subtyping, grading, and choice of therapy. In this study, we propose FFPE++, an unpaired image-to-image translation method based on contrastive learning with a mixed channel-spatial attention module and self-regularization loss that drastically corrects the aforementioned artifacts in FFPE tissue sections. Turing tests were performed by 10 board-certified pathologists with more than 10 years of experience. These tests which were performed for ovarian carcinoma, lung adenocarcinoma, lung squamous cell carcinoma, and papillary thyroid carcinoma, demonstrate the clear superiority of the proposed method in many clinical aspects compared with standard FFPE images. Based on the qualitative experiments and feedback from the Turing tests, we believe that FFPE++ can contribute to substantial diagnostic and prognostic accuracy in clinical pathology in the future and can also improve the performance of AI tools in digital pathology. The code and dataset are publicly available at https://github.com/DeepMIALab/FFPEPlus., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 Elsevier B.V. All rights reserved.)

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., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2022 Elsevier B.V. All rights reserved.)

Plastic pollution, which is currently one of the most striking problems of our time, raises concerns about the dispersal of micro and nano-sized plastic particles in ecosystems and their toxic effects on living organisms. This study was designed to reveal the toxic effects of polystyrene nanoplastic (PS NP) exposure on the freshwater macrophyte Lemna minor. In addition, elucidating the interaction of this aquatic plant, which is used extensively in the phytoremediation of water contaminants and wastewater treatment facilities, with nanoplastics will guide the development of remediation techniques. For this purpose, we examined nanoplastic accumulation, oxidative stress markers, photosynthetic efficiency, antioxidant system activity and phytohormonal changes in L. minor leaves subjected to PS NP stress (P-1, 100 mg L -1 ; P-2, 200 mg L -1 PS NP). Our results showed no evidence of PS NP-induced oxidative damage in P-1 group plants, although PS NP accumulation reached 56 µg g -1 in the leaves. Also, no significant changes in chlorophyll a fluorescence parameters were observed in this group, indicating unaffected photosynthetic efficiency. PS NP exposure triggered the antioxidant system in L. minor plants and resulted in a 3- and 4.6-fold increase in superoxide dismutase (SOD) activity in the P-1 and P-2 groups. On the other hand, high-dose PS NP treatment resulted in insufficient antioxidant activity in the P-2 group and increased hydrogen peroxide (H 2 O 2 ) and lipid peroxidation (TBARS contents) by 25 % and 17 % compared to the control plants. Furthermore, PS NP exposure triggered abscisic acid biosynthesis (two-fold in the P-1 and three-fold in the P-2 group), which is also involved in regulating the stress response. In conclusion, L. minor plants tolerated NP accumulation without growth suppression, oxidative stress damage and limitations in photosynthetic capacity and have the potential to be used in remediation studies of NP-contaminated waters., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2022 Elsevier B.V. All rights reserved.)

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., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2021 Elsevier B.V. All rights reserved.)

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)., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2021 Elsevier B.V. All rights reserved.)

Study Objective: Breast cancer is the most common malignancy of women all over the world. In this study, we compared the effects of ultrasound-guided modified pectoral nerve (PECS) block and erector spinae plane (ESP) block on postoperative opioid consumption, pain scores, and intraoperative fentanyl need of patients undergoing unilateral modified radical mastectomy surgery., Design: Single-blinded, prospective, randomized, efficacy study., Setting: Tertiary university hospital, postoperative recovery room and surgical ward., Patients: Forty patients (ASA I-II) were allocated to two groups. After exclusion, 38 patients were included in the final analysis (18 patients in the PECS groups and 20 in the ESP group)., Interventions: Modified pectoral nerve block was performed in the PECS group and erector spinae plane block was performed in the ESP group., Measurements: Postoperative tramadol consumption and pain scores were compared between the groups. Also, intraoperative fentanyl need was measured., Main Results: Postoperative tramadol consumption was 132.78 ± 22.44 mg in PECS group and 196 ± 27.03 mg in ESP group (p = 0.001). NRS scores at the 15th and 30th min were similar between the groups. However, median NRS scores were significantly lower in PECS group at the postoperative 60th min, 120th min, 12th hour and 24th hour (p = 0.024, p = 0.018, p = 0.021 and p = 0.011 respectively). Intraoperative fentanyl need was 75 mg in PECS group and 87.5 mg in ESP group. The difference was not statistically significant (p = 0.263)., Conclusion: Modified PECS block reduced postoperative tramadol consumption and pain scores more effectively than ESP block after radical mastectomy surgery., (Copyright © 2018 Elsevier Inc. All rights reserved.)

Background: West Nile fever is an important zoonotic infection caused by West Nile virus (WNV), a member of the Flaviviridae. Previous serological data from Turkey suggest widespread WNV circulation. This report includes cases of human and equine WNV infections occurring concurrently, and manifesting as central nervous system infections, in two neighboring provinces of Central Anatolia, Turkey. A partial phylogenetic analysis of the causative virus is given for the first time., Methods: The cases were reported in February (horses) and March (human). Symptoms of the disease were similar in the two species, characterized by neurological manifestations suggesting meningoencephalitis. Real-time/nested PCRs and commercial immunoassays and a plaque reduction neutralization assay were employed for the detection of viral RNA and specific antibodies, respectively., Results: WNV RNAs were detected in buffy coat (horses) and cerebrospinal fluid (human) samples. Partial nucleotide sequences of the E-gene coding region revealed that the strains are closely related to viruses of lineage 1, clade 1a. Accompanying equine serosurveillance demonstrated WNV-specific antibodies in 31.6% of the samples., Conclusions: This is the first report of acute WNV infections caused by lineage 1 strains from Turkey, in concordance with previous reports from some European and North African countries., (Copyright © 2013 International Society for Infectious Diseases. Published by Elsevier Ltd. All rights reserved.)

In this study, the ability of surfactant-modified zeolite (SMZ) to remove color from real textile wastewater was investigated. Tests were performed in a fixed-bed column reactor and the surface of natural zeolite was modified with a quaternary amine surfactant hexadecyltrimethylammonium bromide (HTAB). The zeolite bed that was modified at 1 g L(-1) HTAB concentration and HTAB flow rate of 0.015 L min(-1) showed good performance in removing color. Effects of wastewater color intensity, flow rates and bed heights were also studied. Wastewater was diluted several times in the ratios of 25%, 50% and 75% in order to assess the influence of wastewater strength. The breakthrough curves of the original and diluted wastewaters are dispersed due to the fact that breakthrough came late at lower color intensities and saturation of the bed appeared faster at higher color intensities. The column had a 3-cm diameter and four different bed heights of 12.5, 25, 37.5 and 50 cm, which treated 5.25, 19.50, 35.25 and 51 L original textile wastewater, respectively, at the breakthrough time at a flow rate of 0.025 L min(-1). The theoretical service times evaluated from bed depth service time (BDST) approach for different column variables. The calculated and theoretical values of the exchange zone height were found with a difference of 27%. The various design parameters obtained from fixed-bed experimental studies showed good correlation with corresponding theoretical values, under different bed heights. The regeneration of the SMZ was also evaluated using a solution consisting of 30 g L(-1) NaCl and 1.5 g L(-1) NaOH at pH 12 and temperature 30 degrees C. Twice-regenerated SMZ showed the best performance compared with the others while first- and thrice-regenerated perform lower than the original SMZ.

Taguchi method was applied as an experimental design to determine optimum conditions for color removal from textile dyebath house effluents in a zeolite fixed bed reactor. After the parameters were determined to treat real textile wastewater, adsorption experiments were carried out. The breakthrough curves for adsorption studies were constructed under different conditions by plotting the normalized effluent color intensity (C/C(0)) versus time (min) or bed volumes (BV). The chosen experimental parameters and their ranges are: HTAB concentration (C(htab)), 1-7.5 gL(-1); HTAB feeding flowrate (Q(htab)), 0.015-0.075 L min(-1); textile wastewater flowrate (Q(dye)), 0.025-0.050 L min(-1) and zeolite bed height (H(bed)), 25-50 cm, respectively. Mixed orthogonal array L(16) (4(2)x2(2)) for experimental plan and the larger the better response category were selected to determine the optimum conditions. The optimum conditions were found to be as follows: HTAB concentration (C(htab))=1g L(-1), HTAB feeding flowrate (Q(htab))=0.015 L min(-1), textile wastewater flowrate (Q(dye))=0.025 L min(-1) and bed height (H(bed))=50 cm. Under these conditions, the treated wastewater volume reached a maximum while the bed volumes (BV) were about 217. While HTAB concentration, gL(-1) (A); zeolite bed height, cm (D) and wastewater flowrate, L min(-1) (C) were found to be significant parameters, respectively, whereas, HTAB flowrate, L min(-1) (B) was found to be an insignificant parameter.

Removal of ammonium ion (NH(4)(+)) from leachate from Odayeri sanitary landfill, located in the European part of Istanbul, was examined using Gördes (Turkish) clinoptilolite. The effects of pH, flow rate, ammonium concentration and competitive cations on the removal efficiency were investigated in both batch and column studies. Thomas model were used to analyze the breakthrough data. Nonlinear least square method was applied for fitting the column data. The competitive effect was observed more effective in lower ammonium concentration and higher cation concentrations. Conditioning and regeneration using NaCl improved removal efficiency of ammonium from leachate.

Ammonium ion exchange from aqueous solution using clinoptilolite zeolite was investigated at laboratory scale. Batch experimental studies were conducted to evaluate the effect of various parameters such as pH, zeolite dosage, contact time, initial ammonium concentration and temperature. Freundlich and Langmuir isotherm models and pseudo-second-order model were fitted to experimental data. Linear and non-linear regression methods were compared to determine the best fitting of isotherm and kinetic model to experimental data. The rate limiting mechanism of ammonium uptake by zeolite was determined as chemical exchange. Non-linear regression has better performance for analyzing experimental data and Freundlich model was better than Langmuir to represent equilibrium data.

A study on ion exchange kinetics and equilibrium isotherms of ammonium ion on natural Turkish clinoptilolite (zeolite) was conducted using a batch experiment technique. The effects of relevant parameters, such as temperature, contact time and initial ammonium (NH(4)(+)) concentration were examined, respectively. The pseudo first-order, pseudo second-order kinetic models and intraparticle diffusion model were used to describe the kinetic data. The pseudo second-order kinetic model provided excellent kinetic data fitting (R(2)>0.990) and intraparticle diffusion effects ammonium uptake. The Langmuir and Freundlich models were applied to describe the equilibrium isotherms for ammonium uptake and the Langmuir model agrees very well with experimental data. Thermodynamic parameters such as change in free energy (DeltaG(0)), enthalpy (DeltaH(0)) and entropy (DeltaS(0)) were also determined. An examination of the thermodynamic parameters shows that the exchange of ammonium ion by clinoptilolite is a process occurring spontaneously and physical in nature at ambient conditions (25 degrees C). The process is also found to be exothermic. The results indicate that there is a significant potential for the natural Turkish clinoptilolite as an adsorbent material for ammonium removal from aqueous solutions.

The aim of this study is to demonstrate the potential of Cr(VI) generation during jigging operation applied for ferrochrome recovery from slag. The Cr(VI) concentrations of water contacted with ferrochromium slag (W/FS=10) in a closed cycle after 50 batches were found as 0.61 mg/l. Also, reduction of Cr(VI) to Cr(III) and a subsequent precipitation of Cr(III) by using ferrochrome slag (FS) in a model solution has been aimed. The effects of amount of acid, contact time, FS dosage, initial Cr(VI) concentration and temperature on the Cr(VI) reduction have been studied through the batch runs. The amount of acid has been found to be the most effective parameter affecting the Cr(VI) reduction. A 10 g/l FS dosage and 3.5 ml/l H2SO4 (5M) are sufficient to reduce all Cr(VI) in the model solution containing 10mg/l Cr(VI) and for contact time of 60 min at 25 degrees C. In reduced solutions, precipitation of metal ions has been studied by using extra FS. A 60 g/l dosage of fresh FS can precipitate all Cr(III) and Fe ions in the reduced solution. Thus, it has been demonstrated that the treatment of jigging water stream to be generated in a ferrochrome plant containing Cr(VI) can be accomplished by using ferrochromium slag and sulphuric acid. Also, it has been determined that solid residues of the process are environmentally stable by applying TCLP test.

The graft survival rates of sensitized kidney recipients have been shown to be lower than non-sensitized patients. Therefore, panel reactive antibody (PRA) and cross-match determination is accepted as mandatory screening for renal transplantation candidates. Our recent previous study has shown that simvastatin had a significant immunosuppressive effect in PRA-positive and/or crossmatch-positive patients. We present the pre and post-transplantation follow-up outcomes of simvastatin treatment in the highly sensitized dialysis patients. Thirty patients were followed for a mean period of 26 months. The PRA and flow cytometric measurements were performed at monthly intervals. Ten patients underwent successful kidney transplantation (eight living-related and two cadaveric). None of the patients developed hyperacute or acute rejection, and there was no graft loss during 19.8+/-6.2 months of post-transplantation follow-up. Of the 18 patients who stayed on dialysis throughout the study with PRA positivity, six were lost to follow-up and three spontaneously stopped taking the simvastatin. In the latter three cases, the PRA levels rose significantly after the drug was discontinued. Eight of the remaining nine PRA-positive patients showed significant drops in mean PRA level over the study period, and entered the range considered acceptable for transplantation. Only one patient showed persistently high PRA levels throughout the study. In one patient, the drug had to be discontinued due to acute toxic hepatitis. In conclusion, the results indicate that continuous simvastatin therapy effective in immunized and highly sensitized dialysis patients. Meanwhile, it has beneficial effect on 1-year graft survival in sensitized renal transplantation group.

Pre- and post-renal transplantation panel reactive antibody (PRA) screening is associated with increased incidence of hyperacute or acute graft rejection and graft loss. This study was designed to find any relationship PRA sensitization and associated human leukocyte antigen (HLA)-specific antibodies in Turkish renal transplant candidates. We included 340 patients who were in the renal transplantation waiting list in the study. We determined PRA sensitization ratio and the associated anti-HLA IgG antibody distribution of the patient group. The PRA testing was currently performed and levels above 30% were accepted to be positive. The PRA class I positivity was determined in 24 (7%) and class II in 34 (10%) of the patients. The most frequent HLA antibodies for class I were B56, A2, A34, A1, A23, A24 and B61; and for class II were DR11, DR14, DQ7, DR10, DQ5, DR1 and DR7, respectively. From these, the increase of the numbers of anti-HLA class II antibodies was significantly correlated with the increase of PRA sensitization ratio. In conclusion, the identification of the associated HLA-specific antibodies and correlation with the Turkish population HLA antigen distribution will identify the high-risk patients who are candidates for transplantation.

Background: There are few reports describing chromosomal abnormalities in transsexuals. In rare cases, transsexualism and sexual chromosomal multiplicity coexist. Six cases of male-to-female transsexuals with 47,XYY chromosomal pattern have been previously reported. We have not encountered any female transsexual cases with 47,XXX karyotype in the literature., Methods: A 21-year-old female patient came to our outpatient department with depressive symptoms and suicidal thoughts. On psychiatric interview, she reported that she had feelings of discomfort with her gender identity and had desired to be male since her childhood. Then, we performed cytogenetic investigation using blood culture and G chromosome banding., Results: Histology and DNA histograms of the patient revealed a chromosomal pattern of 47,XXX., Conclusions: We conclude that sexual chromosomal abnormalities in some transsexuals may cause a vulnerability to development of a gender identity disorder.