Regulation of 3β-Hydroxysteroid Dehydrogenase Activity in Rat Testis under Hyperprolactinemia and Excessive 17β-Estradiol

The effects of hyperprolactinemia on the activity of 3β-hydroxysteroid dehydrogenase (3β-HSD) in rat testis were studied during excessive 17β-estradiol (E2) administration. Without E2 treatment, 3β-HSD activity did not change significantly in moderate hyperprolactinemic rats (756 ± 179 ng/ml). However, this enzyme activity was significantly decreased in marked hyperprolactinemic rats (3612 ± 1090 ng/ml) compared to that in control rats (45.4 ± 6.2 ng/ml). Under the excessive E2 administration, this enzyme activity was insignificantly decreased in slight hyperprolactinemic rats (218 ± 42 ng/ml1 and inhibited in moderate hyperprolactinemic rats (566 ± 77 ng/ml) as refer to control level. It may be concluded that inhibition of 3β-HSD activity in testis due to the excess administration of estrogen is promoted by the transplantation of MtT/F84 which produces prolactin at the limited level

Effect of Hyperprolactinemia Induced by Prolactinoma (MtT/F84) on the Accessory Sexual Organs of Male Rat

A new transplantable prolactinoma, designated MtT/F84 has been serially passaged in female F344 rats. Persistently high levels of serum prolactin could be achieved in male F344 rats by MtT/F84 inoculating under the skin. This investigation deals with the effects of hyperprolactinemia upon the accessory sexual organs of male rats during puberty. The weights and the concentrations of dihydrotestosterone (DHT) in the dorsal prostate increased significantly in rats with moderate hyperprolactinemia (756 ± 179 ng/ml), but they in rats with marked hyperprolactinemia (3612 ± 1089 ng/ml) were similar t.o those of control rats. In contrast, serum testosterone levels (0.52 ± 0/17 ng/ml) in those of hyperprolactinemic rats were significantly decreased compared to that of controls (1.11± 0.13 ng/ml). These results suggested that the growth-promoting effect of prolactin on the rat prostate mediated through the action of androgen varied according to the degree of hyperprolactinemia

Pearlite Stabilisation by Copper on Ductile Cast Iron

Abstract. In ductile cast irons with copper, cementite stability was investigated against an annealing heat treatment used to obtain a fully ferritic matrix. Copper controls cast-iron mechanical properties, but its role in the matrix microstructure formation remains unclear. Some reports suggest the copper layer around graphite or cementite. They can be barrier to carbon diffusion at eutectoid reaction, however it is difficult to understand the mechanism of pearlite stability by copper. To confirm the existence of the barrier and effect of copper addtion, ten 9-mm-thick spheroidal graphite cast iron castings were prepared with different copper contents of 0.16 wt% -0.69 wt%. The samples' as-cast microstructures included spheroidal graphite, ledeburite, and pearlite. The pearlite fraction degreases to about 10% by heat treatment for ordinary ductile irons without intentional copper addition. The samples' copper content and the pearlite fraction after heat treatment are not linearly related. The retained pearlite increased suddenly with increased copper content greater than 0.4 wt%. However, even the sample with the highest copper content showed no precipitation of a copper solid solution around graphite nodule or cementite

Pearlite Stabilisation by Copper on Ductile Cast Iron

Abstract. In ductile cast irons with copper, cementite stability was investigated against an annealing heat treatment used to obtain a fully ferritic matrix. Copper controls cast-iron mechanical properties, but its role in the matrix microstructure formation remains unclear. Some reports suggest the copper layer around graphite or cementite. They can be barrier to carbon diffusion at eutectoid reaction, however it is difficult to understand the mechanism of pearlite stability by copper. To confirm the existence of the barrier and effect of copper addtion, ten 9-mm-thick spheroidal graphite cast iron castings were prepared with different copper contents of 0.16 wt% -0.69 wt%. The samples' as-cast microstructures included spheroidal graphite, ledeburite, and pearlite. The pearlite fraction degreases to about 10% by heat treatment for ordinary ductile irons without intentional copper addition. The samples' copper content and the pearlite fraction after heat treatment are not linearly related. The retained pearlite increased suddenly with increased copper content greater than 0.4 wt%. However, even the sample with the highest copper content showed no precipitation of a copper solid solution around graphite nodule or cementite

Peritumoral radiomics features on preoperative thin-slice CT images can predict the spread through air spaces of lung adenocarcinoma

The spread through air spaces (STAS) is recognized as a negative prognostic factor in patients with early-stage lung adenocarcinoma. The present study aimed to develop a machine learning model for the prediction of STAS using peritumoral radiomics features extracted from preoperative CT imaging. A total of 339 patients who underwent lobectomy or limited resection for lung adenocarcinoma were included. The patients were randomly divided (3:2) into training and test cohorts. Two prediction models were created using the training cohort: a conventional model based on the tumor consolidation/tumor (C/T) ratio and a machine learning model based on peritumoral radiomics features. The areas under the curve for the two models in the testing cohort were 0.70 and 0.76, respectively ( = 0.045). The cumulative incidence of recurrence (CIR) was significantly higher in the STAS high-risk group when using the radiomics model than that in the low-risk group (44% vs. 4% at 5 years;  = 0.002) in patients who underwent limited resection in the testing cohort. In contrast, the 5-year CIR was not significantly different among patients who underwent lobectomy (17% vs. 11%;  = 0.469). In conclusion, the machine learning model for STAS prediction based on peritumoral radiomics features performed better than the C/T ratio model

Feasibility of Dedicated Breast Positron Emission Tomography Image Denoising Using a Residual Neural Network

Objective(s): This study aimed to create a deep learning (DL)-based denoising model using a residual neural network (Res-Net) trained to reduce noise in ring-type dedicated breast positron emission tomography (dbPET) images acquired in about half the emission time, and to evaluate the feasibility and the effectiveness of the model in terms of its noise reduction performance and preservation of quantitative values compared to conventional post-image filtering techniques.Methods: Low-count (LC) and full-count (FC) PET images with acquisition durations of 3 and 7 minutes, respectively, were reconstructed. A Res-Net was trained to create a noise reduction model using fifteen patients’ data. The inputs to the network were LC images and its outputs were denoised PET (LC + DL) images, which should resemble FC images. To evaluate the LC + DL images, Gaussian and non-local mean (NLM) filters were applied to the LC images (LC + Gaussian and LC + NLM, respectively). To create reference images, a Gaussian filter was applied to the FC images (FC + Gaussian). The usefulness of our denoising model was objectively and visually evaluated using test data set of thirteen patients. The coefficient of variation (CV) of background fibroglandular tissue or fat tissue were measured to evaluate the performance of the noise reduction. The SUVmax and SUVpeak of lesions were also measured. The agreement of the SUV measurements was evaluated by Bland–Altman plots.Results: The CV of background fibroglandular tissue in the LC + DL images was significantly lower (9.10 2.76) than the CVs in the LC (13.60  3.66) and LC + Gaussian images (11.51  3.56). No significant difference was observed in both SUVmax and SUVpeak of lesions between LC + DL and reference images. For the visual assessment, the smoothness rating for the LC + DL images was significantly better than that for the other images except for the reference images.Conclusion: Our model reduced the noise in dbPET images acquired in about half the emission time while preserving quantitative values of lesions. This study demonstrates that machine learning is feasible and potentially performs better than conventional post-image filtering in dbPET denoising

Neuroimaging at 7 Tesla: a pictorial narrative review

Neuroimaging using the 7-Tesla (7T) human magnetic resonance (MR) system is rapidly gaining popularity after being approved for clinical use in the European Union and the USA. This trend is the same for functional MR imaging (MRI). The primary advantages of 7T over lower magnetic fields are its higher signal-to-noise and contrast-to-noise ratios, which provide high-resolution acquisitions and better contrast, making it easier to detect lesions and structural changes in brain disorders. Another advantage is the capability to measure a greater number of neurochemicals by virtue of the increased spectral resolution. Many structural and functional studies using 7T have been conducted to visualize details in the white matter and layers of the cortex and hippocampus, the subnucleus or regions of the putamen, the globus pallidus, thalamus and substantia nigra, and in small structures, such as the subthalamic nucleus, habenula, perforating arteries, and the perivascular space, that are difficult to observe at lower magnetic field strengths. The target disorders for 7T neuroimaging range from tumoral diseases to vascular, neurodegenerative, and psychiatric disorders, including Alzheimer’s disease, Parkinson’s disease, multiple sclerosis, epilepsy, major depressive disorder, and schizophrenia. MR spectroscopy has also been used for research because of its increased chemical shift that separates overlapping peaks and resolves neurochemicals more effectively at 7T than a lower magnetic field. This paper presents a narrative review of these topics and an illustrative presentation of images obtained at 7T. We expect 7T neuroimaging to provide a new imaging biomarker of various brain disorders

Denoising approach with deep learning-based reconstruction for neuromelanin-sensitive MRI: image quality and diagnostic performance

[Purpose]Neuromelanin-sensitive MRI (NM-MRI) has proven useful for diagnosing Parkinson’s disease (PD) by showing reduced signals in the substantia nigra (SN) and locus coeruleus (LC), but requires a long scan time. The aim of this study was to assess the image quality and diagnostic performance of NM-MRI with a shortened scan time using a denoising approach with deep learning-based reconstruction (dDLR).[Materials and methods]We enrolled 22 healthy volunteers, 22 non-PD patients and 22 patients with PD who underwentNM-MRI, and performed manual ROI-based analysis. Signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) in ten healthy volunteers were compared among images with a number of excitations (NEX) of 1 (NEX1), NEX1 images with dDLR (NEX1+dDLR) and 5-NEX images (NEX5). Acquisition times for NEX1 and NEX5 were 3 min 12 s and 15 min 58 s, respectively. Diagnostic performances using the contrast ratio (CR) of the SN (CR_SN) and LC (CR_LC) and those by visual assessment for diferentiating PD from non-PD were also compared between NEX1 and NEX1+dDLR.[Results]Image quality analyses revealed that SNRs and CNRs of the SN and LC in NEX1+dDLR were signifcantly higherthan in NEX1, and comparable to those in NEX5. In diagnostic performance analysis, areas under the receiver operating characteristic curve (AUC) using CR_SN and CR_LC of NEX1+dDLR were 0.87 and 0.75, respectively, which had no signifcant diference with those of NEX1. Visual assessment showed improvement of diagnostic performance by applying dDLR.[Conclusion]Image quality for NEX1+dDLR was comparable to that of NEX5. dDLR has the potential to reduce scan time of NM-MRI without degrading image quality. Both 1-NEX NM-MRI with and without dDLR showed high AUCs for diagnosing PD by CR. The results of visual assessment suggest advantages of dDLR. Further tuning of dDLR would be expected to provide clinical merits in diagnosing PD

Daptomycin-related Musculoskeletal Adverse Events and Statin Use

Background. There is a growing concern about the association between the combined use of daptomycin (DAP) and statins and the occurrence of musculoskeletal adverse events (MAEs), but this remains controversial. This study aimed to clarify the association between statin use and DAP-related MAEs. Methods. We used a mixed approach that combines 2 methodologies. First, we conducted a meta-analysis to examine the effects of statin use on DAP-related MAEs. Second, we conducted a disproportionality analysis using the US Food and Drug Administration Adverse Events Reporting System (FAERS) to further confirm the results of the meta-analysis and to examine the effect of each type of statin on DAP-related MAEs in a large population. Results. In the meta-analysis, statin use significantly increased the incidence of DAP-related rhabdomyolysis (odds ratio [OR]: 3.83; 95% confidence interval [CI]: 1.43–10.26) but not DAP-related myopathy (OR: 1.72; 95% CI: .95–3.12). In the disproportionality analysis using the FAERS, the use of statin significantly increased the reporting OR (ROR) for DAP-related myopathy (ROR: 5.69; 95% CI: 4.31–7.51) and rhabdomyolysis (ROR: 5.77; 95% CI: 4.33–7.68). Atorvastatin, rosuvastatin, and simvastatin all increased the incidence of DAP-related myopathy and rhabdomyolysis. Conclusion. The mixed approach combining a meta-analysis and disproportionality analysis showed that statin use was associated with the occurrence of DAP-related rhabdomyolysis. The appropriate use of statins and DAP should be performed with careful consideration of its safety

Clarithromycin expands CD11b+Gr-1+ MDSC-like cells

Macrolides are used to treat various inflammatory diseases owing to their immunomodulatory properties; however, little is known about their precise mechanism of action. In this study, we investigated the functional significance of the expansion of myeloid-derived suppressor cell (MDSC)-like CD11b+Gr-1+ cells in response to the macrolide antibiotic clarithromycin (CAM) in mouse models of shock and post-influenza pneumococcal pneumonia as well as in humans. Intraperitoneal administration of CAM markedly expanded splenic and lung CD11b+Gr-1+ cell populations in naïve mice. Notably, CAM pretreatment enhanced survival in a mouse model of lipopolysaccharide (LPS)-induced shock. In addition, adoptive transfer of CAM-treated CD11b+Gr-1+ cells protected mice against LPS-induced lethality via increased IL-10 expression. CAM also improved survival in post-influenza, CAM-resistant pneumococcal pneumonia, with improved lung pathology as well as decreased interferon (IFN)-γ and increased IL-10 levels. Adoptive transfer of CAM-treated CD11b+Gr-1+ cells protected mice from post-influenza pneumococcal pneumonia. Further analysis revealed that the CAM-induced CD11b+Gr-1+ cell expansion was dependent on STAT3-mediated Bv8 production and may be facilitated by the presence of gut commensal microbiota. Lastly, an analysis of peripheral blood obtained from healthy volunteers following oral CAM administration showed a trend toward the expansion of human MDSC-like cells (Lineage−HLA-DR−CD11b+CD33+) with increased arginase 1 mRNA expression. Thus, CAM promoted the expansion of a unique population of immunosuppressive CD11b+Gr-1+ cells essential for the immunomodulatory properties of macrolides