To develop a U-net deep learning method for breast tissue segmentation on fat-sat T1-weighted (T1W) MRI using transfer learning (TL) from a model developed for non-fat-sat images. The training ...dataset (
N
= 126) was imaged on a 1.5 T MR scanner, and the independent testing dataset (
N
= 40) was imaged on a 3 T scanner, both using fat-sat T1W pulse sequence. Pre-contrast images acquired in the dynamic-contrast-enhanced (DCE) MRI sequence were used for analysis. All patients had unilateral cancer, and the segmentation was performed using the contralateral normal breast. The ground truth of breast and fibroglandular tissue (FGT) segmentation was generated using a template-based segmentation method with a clustering algorithm. The deep learning segmentation was performed using U-net models trained with and without TL, by using initial values of trainable parameters taken from the previous model for non-fat-sat images. The ground truth of each case was used to evaluate the segmentation performance of the U-net models by calculating the dice similarity coefficient (DSC) and the overall accuracy based on all pixels. Pearson’s correlation was used to evaluate the correlation of breast volume and FGT volume between the U-net prediction output and the ground truth. In the training dataset, the evaluation was performed using tenfold cross-validation, and the mean DSC with and without TL was 0.97 vs. 0.95 for breast and 0.86 vs. 0.80 for FGT. When the final model developed with and without TL from the training dataset was applied to the testing dataset, the mean DSC was 0.89 vs. 0.83 for breast and 0.81 vs. 0.81 for FGT, respectively. Application of TL not only improved the DSC, but also decreased the required training case number. Lastly, there was a high correlation (
R
2
> 0.90) for both the training and testing datasets between the U-net prediction output and ground truth for breast volume and FGT volume. U-net can be applied to perform breast tissue segmentation on fat-sat images, and TL is an efficient strategy to develop a specific model for each different dataset.
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NUK, SBMB, SBNM, UL, UM, UPUK, VSZLJ
Abstract
Objective
Insulin resistance is inversely correlated with the clearance rate of uric acid, which may indicate that improvement in the clearance rate of uric acid could reduce insulin ...resistance. Considering the increased prevalence of diabetes mellitus (DM) in the gout population, this study evaluated the effects of benzbromarone, a uricosuric agent, on the incidence of DM in the gout population.
Methods
We used data from the Taiwan National Health Insurance program. The benzbromarone user cohort included 8678 patients; each patient was age- and sex-matched with one benzbromarone non-user who was randomly selected from the gout population. The Cox proportional hazard regression analysis was conducted to estimate the effects of benzbromarone on the incidence of DM in the gout population.
Results
The incidence of DM was significantly lower in benzbromarone users than in benzbromarone non-users adjusted hazard ratio (HR) = 0.86; 95% CI: 0.79, 0.94. The HR for the incidence of DM was lower in male benzbromarone users (adjusted HR = 0.77; 95% CI: 0.69, 0.86) than in benzbromarone non-users. An analysis of three age groups (<40, 40-59 and ⩾60 years) indicated that the HRs of the age groups of 40-59 years (adjusted HR = 0.86; 95% CI: 0.76, 0.98) and ⩾60 years (adjusted HR = 0.82; 95% CI: 0.71, 0.94) were significantly lower among benzbromarone users than among benzbromarone non-users.
Conclusion
In the gout population, the incidence of DM was lower in benzbromarone users than in benzbromarone non-users.
Abstract
BACKGROUND
Preganglionic cervical root transection (PCRT) is the most severe type of brachial plexus injury. In some cases, surgical procedures must be postponed for ≥3 wk until ...electromyographic confirmation. However, research works have previously shown that treating PCRT after a 3-wk delay fails to result in functional recovery.
OBJECTIVE
To assess whether the immunosuppressive drug sirolimus, by promoting neuroprotection in the acute phase of PCRT, could enable functional recovery in cases of delayed repair.
METHODS
First, rats received a left 6th to 8th cervical root transection, after which half were administered sirolimus for 1 wk. Markers of microglia, astrocytes, neurons, and autophagy were assessed at days 7 and 21. Second, animals with the same injury received nerve grafts, along with acidic fibroblast growth factor and fibrin glue, 3 wk postinjury. Sirolimus was administered to half of them for the first week. Mechanical sensation, grasping power, spinal cord morphology, functional neuron survival, nerve fiber regeneration, and somatosensory-evoked potentials (SSEPs) were assessed 1 and 23 wk postinjury.
RESULTS
Sirolimus was shown to attenuate microglial and astrocytic proliferation and enhance neuronal autophagy and survival; only rats treated with sirolimus underwent significant sensory and motor function recovery. In addition, rats who achieved functional recovery were shown to have abundant nerve fibers and neurons in the dorsal root entry zone, dorsal root ganglion, and ventral horn, as well as to have SSEPs reappearance.
CONCLUSION
Sirolimus-induced neuroprotection in the acute stage of PCRT enables functional recovery, even if surgical repair is performed after a 3-wk delay.
Considerable effort has focused on the development of selective protein farnesyl transferase (FTase) and protein geranylgeranyl transferase (GGTase) inhibitors as cancer chemotherapeutics. Here, we ...report a new strategy for anticancer therapeutic agents involving inhibition of farnesyl diphosphate synthase (FPPS) and geranylgeranyl diphosphate synthase (GGPPS), the two enzymes upstream of FTase and GGTase, by lipophilic bisphosphonates. Due to dual site targeting and decreased polarity, the compounds have activities far greater than do current bisphosphonate drugs in inhibiting tumor cell growth and invasiveness, both in vitro and in vivo. We explore how these compounds inhibit cell growth and how cell activity can be predicted based on enzyme inhibition data, and using X-ray diffraction, solid state NMR, and isothermal titration calorimetry, we show how these compounds bind to FPPS and/or GGPPS.
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IJS, KILJ, NUK, PNG, UL, UM
Mammalian target of rapamycin (mTOR) inhibitors, such as sirolimus and its derivative, everolimus, are potent immunosuppressive and antiproliferative drugs. Inflammatory diseases are characterized by ...immunological dysfunction, and monocyte recruitment underlies the mechanism of cell damage. Chemokines attract inflammatory cells to sites of inflammation. Interleukin-8 (IL-8/CXCL8); the monocyte chemoattractant protein-1 (MCP-1/CCL2); the regulated on activation, normal T cell expressed, presumably secreted protein (RANTES/CCL5); the macrophage inflammatory protein (MIP)-1α (CCL3); and MIP-1β (CCL4) are involved in the pathogenesis of inflammation. However, whether mTOR inhibitors moderate the production of chemokines in monocytes remains unclear.
A human monocyte cell line, THP-1, and primary monocytes obtained from human volunteers, were stimulated using lipopolysaccharide (LPS), and then treated with sirolimus. The expression of the MCP-1, RANTES, IL-8, MIP-1α, MIP-1β, and TNF-α proteins was measured using enzyme-linked immunosorbent assays, and intracellular signalling was examined using western blotting.
Sirolimus significantly suppressed the LPS-induced expression of MCP-1, IL-8, RANTES, MIP-1α, and MIP-1β in the THP-1 cells and human primary monocytes. The mitogen-activated protein kinase (MAPK) inhibitors that were examined suppressed the LPS-induced expression of MCP-1, IL-8, RANTES, MIP-1α, and MIP-1β. In addition, sirolimus suppressed the LPS-induced phosphorylation of p38 and p65 in the THP-1 and human primary monocytes.
Sirolimus downregulates the expression of chemokines in monocytes, including MCP-1, RANTES, IL-8, MIP-1α, and MIP-1β, by inhibiting the NF-κB-p65 and MAPK-p38 signalling pathways.
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DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
The management of the coexistence of heart disease and kidney disease is increasingly challenging for clinicians. Chronic kidney disease (CKD) is not only a prevalent comorbidity of patients with ...heart failure but has also been identified as a noteworthy risk factor for all-cause mortality and poor clinical outcomes. Digoxin is one of the commonest treatments for heart disease. There are few trials investigating the role of digoxin in patients with cardiorenal syndrome (CRS). This study aims to examine the association between digoxin usage and clinical outcomes in patients with CRS in a nationwide cohort.
We conducted a population-based study that included 705 digoxin users with CRS; each patient was age, sex, comorbidities, and medications matched with three non-users who were randomly selected from the CRS population. Cox proportional hazards regression analysis was conducted to estimate the effects of digoxin on the incidence of all-cause mortality, congestive heart failure (CHF) hospitalization, coronary artery disease (CAD) hospitalization, and end-stage renal disease (ESRD).
The all-cause mortality rate was significantly higher in digoxin users than in non-users (adjusted hazard ratio aHR = 1.26; 95% confidence interval CI = 1.09-1.46,
=
). In a subgroup analysis, there was significantly high mortality in the
defined daily dose (DDD) subgroup of digoxin users (aHR = 1.49; 95% CI = 1.23-1.82,
<
). Thus, the
was
. With digoxin prescription, the CHF hospitalization was significantly higher subdistribution HR (sHR) = 1.17; 95% CI = 1.05-1.30,
=
, especially in the >
subgroup (sHR = 1.19; 95% CI = 1.01-1.41,
=
=
). The digoxin usage lowered the coronary artery disease (CAD) hospitalization in the >
subgroup (sHR = 0.79; 95% CI = 0.63-0.99,
=
). In renal function progression, more patients with CRS entered ESRD with digoxin usage (sHR = 1.34; 95% CI = 1.16-1.54,
<
). There was a significantly greater incidence of ESRD in the <
and
-
subgroups of digoxin users (sHR = 1.32; 95% CI = 1.06-1.66,
=
; sHR = 1.44; 95% CI = 1.18-1.75;
<
).
Digoxin should be prescribed with caution to patients with CRS.
Computer-aided methods have been widely applied to diagnose lesions on breast magnetic resonance imaging (MRI). The first step was to identify abnormal areas. A deep learning Mask Regional ...Convolutional Neural Network (R-CNN) was implemented to search the entire set of images and detect suspicious lesions.
Two DCE-MRI datasets were used, 241 patients acquired using non-fat-sat sequence for training, and 98 patients acquired using fat-sat sequence for testing. All patients have confirmed unilateral mass cancers. The tumor was segmented using fuzzy c-means clustering algorithm to serve as the ground truth. Mask R-CNN was implemented with ResNet-101 as the backbone. The neural network output the bounding boxes and the segmented tumor for evaluation using the Dice Similarity Coefficient (DSC). The detection performance, and the trade-off between sensitivity and specificity, was analyzed using free response receiver operating characteristic.
When the precontrast and subtraction image of both breasts were used as input, the false positive from the heart and normal parenchymal enhancements could be minimized. The training set had 1469 positive slices (containing lesion) and 9135 negative slices. In 10-fold cross-validation, the mean accuracy = 0.86 and DSC = 0.82. The testing dataset had 1568 positive and 7264 negative slices, with accuracy = 0.75 and DSC = 0.79. When the obtained per-slice results were combined, 240 of 241 (99.5%) lesions in the training and 98 of 98 (100%) lesions in the testing datasets were identified.
Deep learning using Mask R-CNN provided a feasible method to search breast MRI, localize, and segment lesions. This may be integrated with other artificial intelligence algorithms to develop a fully automatic breast MRI diagnostic system.
Abstract C-reactive protein (CRP) and corrected QT (QTc) interval are predictors of cardiovascular disease. Whether CRP is associated with QTc interval and QT prolongation is unknown in hypertensive ...patients. We recruited hypertensive patients from a cardiovascular clinic in a tertiary medical center in Taiwan. All received standard 12-lead electrocardiogram examination. QT prolongation was defined as QTc interval ≥440 ms in men or ≥450 ms in women. High-sensitive CRP kits were used for the measurement of the CRP levels. A total of 466 consecutive patients were finally enrolled. Mean age was 60.6 ± 12.0 years. CRP level was correlated with QTc interval ( p < 0.001) and presence of QT prolongation ( p = 0.014). Multivariate regression analysis showed that CRP level ( p = 0.001), age ( p = 0.004), sex ( p < 0.001), height ( p = 0.001), low-density lipoprotein ( p = 0.041), and QRS interval ( p < 0.001) were associated with QTc interval. Furthermore, CRP level odds ratio (OR) = 1.203, 95% confidence interval (CI) = 1.027–1.410, p = 0.022, age (OR = 1.040, 95% CI = 1.010–1.071, p = 0.009), waist (OR = 1.033, 95% CI = 1.000–1.066, p = 0.047), triglyceride (OR = 0.993, 95% CI = 0.987–0.999, p = 0.021) and QRS interval (OR = 1.046, 95% CI = 1.028–1.065, p < 0.001) independently predicted the presence of QT prolongation. Because CRP is an independent predictor of QTc interval and presence of QT prolongation, it could be considered in the risk assessment for hypertensive patients.
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FZAB, GEOZS, GIS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, SBMB, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
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