Effects of Carob (Ceratonia siliqua) on Sperm Quality, Testicular Structure, Testosterone Level and Oxidative Stress in Busulfan-Induced Infertile Mice

Background: Ceratonia silique has antioxidant activities that may inactivate toxic factors and influence sperm quality. To the best of the authors’ knowledge, there is no available data on the effects of carob on male fertility. Hence, the purpose of this study was to investigate the effects of carob on sperm quality, testicular structure, and level of testosterone hormone in busulfan-induced infertile mice. Methods: Sixty-four adult male mice were randomly divided into 8 groups (control, sham, busulfan and carobs 1 to 5). The busulfan group was injected a single dose of 10 mg/kg busulfan intraperitoneally. Carobs 1 to 5 groups received intraperitoneal doses of 800, 400, 200, 100 and 50 mg/kg of carob extract plus a single dose of 10 mg/kg busulfan for 35 days. The sperm analysis, morphometric study, testosterone levels and oxidative stress determination were done on the 35th day of the experiment. Results: The lowest percentage of sperm parameters was related to the busulfan group and the highest was related to the carobs 1 and 2 groups. The seminal vesicles index of the carob 1 group showed a significant increase as compared to the busulfan group (p < 0.001). A significant increase was observed in the mean value of germinal epithelium thickness, as well as thiol and catalase levels in carobs 1 and 2 groups as compared to the busulfan group (p < 0.001). There was a significant increase in the mean level of testosterone in the carob groups as compared to the busulfan group (p < 0.001). Also, there was a significant decrease in the mean value of malondialdehyde level in the carobs 1 and 2 groups p < 0.001) and a significant increase in the mean value of superoxide dismutase enzyme in the carob groups as compared to the busulfan group (p < 0.001). Conclusion: Administration of 800 mg/kg of carob extract for 35 days improved sperm quality, biochemical parameters, thickness of germinal epithelium and testosterone levels in infertile mice induced by busulfan

Chemical compositions of the essential oil and calculation the biophysicochemical coefficients of the components of Hymenocrater longiflorus Benth. of Iran

From: Erik Lindner <[email protected]> Date: 14.07.2003 Subject: Projekt: Zeitungsausschnittarchiv "Broschek-Archiv" ------------------------------------------------------------------------ Unternehmensarchiv der Axel Springer AG, Hamburg 14.07.2003 Sehr geehrte Damen und Herren, im Unternehmensarchiv der Axel Springer AG haben wir gerade einen Bestand besonderer Art erschlossen: Vom Haus Broschek, dem Verlag des "Hamburger Fremdenblattes", hat unser Verlagshaus Anfang der 50er Jahre das Zeitungsausschnittsarch...</erik

The association between melasma and iron profile: a case-control study

Background — Melasma is a chronic acquired localized hypermelanosis, causing aesthetic problem for women and impairing their quality of life. Evidence has suggested that hyperpigmentation can occur as a result of iron deficiency anemia and vitamin B12 deficiency. Aim — We aimed to evaluate the serum parameters of iron profile in melasma patients. Material and Methods — This case-control study investigated 51 adult non pregnant women with melasma, compared with 51 controls, from patients referred to the Hospital, Tehran, Iran, 2017–2018. Melasma was diagnosed clinically according to the melasma area and severity index (MASI) score was calculated and recorded by the physician. The groups were compared in terms of vitamin B12, folate, serum iron, hemoglobin (Hb), mean corpuscular volume (MCV), total iron binding capacity (TIBC), and ferritin. Results — The mean and standard deviation of the women’s age was 36.89±8.88 years, significantly higher in the group of patients with melasma. Comparing the serum parameters between the groups indicated no statistically significant difference in terms of mean levels of ferritin, Hb, MCV, iron, vitamin B12, TIBC, and folate. The women in melasma group had a higher frequency in below normal range of ferritin and serum iron compared to the control group. None of the serum parameters were correlated with MASI. Conclusion — The higher frequency of below normal range of ferritin and serum iron levels in women with melasma compared to the control group showed a possible association between these serum parameters and melasma

Effects of LI-4 and SP-6 Acupuncture on Labor Pain, Cortisol Level and Duration of Labor

AbstractNowadays, acupuncture is widely used to manage pain, and childbirth is a condition requiring appropriate pain management interventions. The efficacy of acupuncture in the management of labor pain has recently been studied, but the results are not satisfactory and conflicts exist. In this study, we investigated the effects of acupuncture on labor pain, serum cortisol level, and duration of labor. We conducted a randomized, single-blind, controlled trial that included 63 nulliparous women: 32 in the study group and 31 in the control group. Acupuncture was performed at the SP-6 and the LI-4 points in the study group, and sham acupuncture was performed at the same points in the control group. Pain scores and serum cortisol levels were measured before and after the intervention. Changes in these measures and in the duration of labor were compared between the groups. No significant variations in pain scores or serum cortisol levels were observed between the two control groups. However, the duration of labor was significantly lower (p < 0.001) in the group receiving real acupuncture. Our results show that acupuncture is significantly associated with a decreased duration of labor, even though it was no better than a placebo for the treatment of labor pain

Decentralized collaborative multi-institutional PET attenuation and scatter correction using federated deep learning

Purpose: Attenuation correction and scatter compensation (AC/SC) are two main steps toward quantitative PET imaging, which remain challenging in PET-only and PET/MRI systems. These can be effectively tackled via deep learning (DL) methods. However, trustworthy, and generalizable DL models commonly require well-curated, heterogeneous, and large datasets from multiple clinical centers. At the same time, owing to legal/ethical issues and privacy concerns, forming a large collective, centralized dataset poses significant challenges. In this work, we aimed to develop a DL-based model in a multicenter setting without direct sharing of data using federated learning (FL) for AC/SC of PET images. Methods: Non-attenuation/scatter corrected and CT-based attenuation/scatter corrected (CT-ASC) 18F-FDG PET images of 300 patients were enrolled in this study. The dataset consisted of 6 different centers, each with 50 patients, with scanner, image acquisition, and reconstruction protocols varying across the centers. CT-based ASC PET images served as the standard reference. All images were reviewed to include high-quality and artifact-free PET images. Both corrected and uncorrected PET images were converted to standardized uptake values (SUVs). We used a modified nested U-Net utilizing residual U-block in a U-shape architecture. We evaluated two FL models, namely sequential (FL-SQ) and parallel (FL-PL) and compared their performance with the baseline centralized (CZ) learning model wherein the data were pooled to one server, as well as center-based (CB) models where for each center the model was built and evaluated separately. Data from each center were divided to contribute to training (30 patients), validation (10 patients), and test sets (10 patients). Final evaluations and reports were performed on 60 patients (10 patients from each center). Results: In terms of percent SUV absolute relative error (ARE%), both FL-SQ (CI:12.21-14.81%) and FL-PL (CI:11.82-13.84%) models demonstrated excellent agreement with the centralized framework (CI:10.32-12.00%), while FL-based algorithms improved model performance by over 11% compared to CB training strategy (CI: 22.34-26.10%). Furthermore, the Mann-Whitney test between different strategies revealed no significant differences between CZ and FL-based algorithms (p-value &gt; 0.05) in center-categorized mode. At the same time, a significant difference was observed between the different training approaches on the overall dataset (p-value &lt; 0.05). In addition, voxel-wise comparison, with respect to reference CT-ASC, exhibited similar performance for images predicted by CZ (R2 = 0.94), FL-SQ (R2 = 0.93), and FL-PL (R2 = 0.92), while CB model achieved a far lower coefficient of determination (R2 = 0.74). Despite the strong correlations between CZ and FL-based methods compared to reference CT-ASC, a slight underestimation of predicted voxel values was observed. Conclusion: Deep learning-based models provide promising results toward quantitative PET image reconstruction. Specifically, we developed two FL models and compared their performance with center-based and centralized models. The proposed FL-based models achieved higher performance compared to center-based models, comparable with centralized models. Our work provided strong empirical evidence that the FL framework [...]</p

Decentralized Distributed Multi-institutional PET Image Segmentation Using a Federated Deep Learning Framework

Purpose: The generalizability and trustworthiness of deep learning (DL)-based algorithms depend on the size and heterogeneity of training datasets. However, because of patient privacy concerns and ethical and legal issues, sharing medical images between different centers is restricted. Our objective is to build a federated DL-based framework for PET image segmentation utilizing a multicentric dataset and to compare its performance with the centralized DL approach. Methods: PET images from 405 head and neck cancer patients from 9 different centers formed the basis of this study. All tumors were segmented manually. PET images converted to SUV maps were resampled to isotropic voxels (3 × 3 × 3 mm3) and then normalized. PET image subvolumes (12 × 12 × 12 cm3) consisting of whole tumors and background were analyzed. Data from each center were divided into train/validation (80% of patients) and test sets (20% of patients). The modified R2U-Net was used as core DL model. A parallel federated DL model was developed and compared with the centralized approach where the data sets are pooled to one server. Segmentation metrics, including Dice similarity and Jaccard coefficients, percent relative errors (RE%) of SUVpeak, SUVmean, SUVmedian, SUVmax, metabolic tumor volume, and total lesion glycolysis were computed and compared with manual delineations. Results: The performance of the centralized versus federated DL methods was nearly identical for segmentation metrics: Dice (0.84 ± 0.06 vs 0.84 ± 0.05) and Jaccard (0.73 ± 0.08 vs 0.73 ± 0.07). For quantitative PET parameters, we obtained comparable RE% for SUVmean (6.43% ± 4.72% vs 6.61% ± 5.42%), metabolic tumor volume (12.2% ± 16.2% vs 12.1% ± 15.89%), and total lesion glycolysis (6.93% ± 9.6% vs 7.07% ± 9.85%) and negligible RE% for SUVmax and SUVpeak. No significant differences in performance (P &gt; 0.05) between the 2 frameworks (centralized vs federated) were observed. Conclusion: The developed federated DL model achieved comparable quantitative performance with respect to the centralized DL model. Federated DL models could provide robust and generalizable segmentation, while addressing patient privacy and legal and ethical issues in clinical data sharing.</p