p90 ribosomal S6 kinase (RSK1) is an effector of both Ras/MEK/MAPK and PI3K/PDK1 pathways. We present evidence that RSK1 drives p27 phosphorylation at T198 to increase RhoA-p27 binding and cell ...motility. RSK1 activation and p27pT198 both increase in early Gâ. As for many kinase-substrate pairs, cellular RSK1 coprecipitates with p27. siRNA to RSK1 and RSK1 inhibition both rapidly reduce cellular p27pT198. RSK1 overexpression increases p27pT198, p27-cyclin D1-Cdk4 complexes, and p27 stability. Moreover, RSK1 transfectants show mislocalization of p27 to cytoplasm, increased motility, and reduced RhoA-GTP, phospho-cofilin, and actin stress fibers, all of which were reversed by shRNA to p27. Phosphorylation by RSK1 increased p27pT198 binding to RhoA in vitro, whereas p27T157A/T198A bound poorly to RhoA compared with WTp27 in cells. Coprecipitation of cellular p27-RhoA was increased in cells with constitutive PI3K activation and increased in early Gâ. Thus T198 phosphorylation not only stabilizes p27 and mislocalizes p27 to the cytoplasm but also promotes RhoA-p27 interaction and RhoA pathway inhibition. These data link p27 phosphorylation at T198 and cell motility. As for other PI3K effectors, RSK1 phosphorylates p27 at T198. Because RSK1 is also activated by MAPK, the increased cell motility and metastatic potential of cancer cells with PI3K and/or MAPK pathway activation may result in part from RSK1 activation, leading to accumulation of p27T198 in the cytoplasm, p27:RhoA binding, inhibition of RhoA/Rock pathway activation, and loss of actomyosin stability.
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BFBNIB, NMLJ, NUK, PNG, SAZU, UL, UM, UPUK
The effects on cataplexy and daytime sleep of acute and chronic oral administration of CG-3703, a potent TRH analog were assessed in canine narcolepsy. CG-3703 was found to be orally active and to ...reduce cataplexy (0.25 to 16 mg/kg) and sleep (8 and 16 mg/kg) in a dose-dependent manner. Two-week oral administration of CG-3703 (16 mg/kg) significantly reduced cataplexy and daytime sleep. The anticataplectic effects of CG-3703 were not associated with changes in general behavior, heart rate, blood pressure, rectal temperature, blood chemistry and thyroid function. Although drug tolerance for the effects on cataplexy and sleep were observed during the second week of chronic drug administration, therapeutic efficacy on cataplexy was improved with individual dose adjustment (final dose range: 16 to 28 mg/kg, p.o.). These results suggest that TRH analogs could be a promising new form of treatment for human narcolepsy.
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EMUNI, FIS, FZAB, GEOZS, GIS, IJS, IMTLJ, KILJ, KISLJ, MFDPS, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, SBMB, SBNM, UKNU, UL, UM, UPUK, VKSCE, ZAGLJ
Hip fracture risk assessment is an important but challenging task. Quantitative CT-based patient specific finite element analysis (FEA) computes the force (fracture load) to break the proximal femur ...in a particular loading condition. It provides different structural information about the proximal femur that can influence a subject overall fracture risk. To obtain a more robust measure of fracture risk, we used principal component analysis (PCA) to develop a global FEA computed fracture risk index that incorporates the FEA-computed yield and ultimate failure loads and energies to failure in four loading conditions (single-limb stance and impact from a fall onto the posterior, posterolateral, and lateral aspects of the greater trochanter) of 110 hip fracture subjects and 235 age and sex matched control subjects from the AGES-Reykjavik study. We found that the first PC (PC1) of the FE parameters was the only significant predictor of hip fracture. Using a logistic regression model, we determined if prediction performance for hip fracture using PC1 differed from that using FE parameters combined by stratified random resampling with respect to hip fracture status. The results showed that the average of the area under the receive operating characteristic curve (AUC) using PC1 was always higher than that using all FE parameters combined in the male subjects. The AUC of PC1 and AUC of the FE parameters combined were not significantly different than that in the female subjects or in all subjects
Type 2 diabetes mellitus is a complex disorder encompassing multiple metabolic defects. We report results from an autosomal genome scan for type 2 diabetes–related quantitative traits in 580 Finnish ...families ascertained for an affected sibling pair and analyzed by the variance components-based quantitative-trait locus (QTL) linkage approach. We analyzed diabetic and nondiabetic subjects separately, because of the possible impact of disease on the traits of interest. In diabetic individuals, our strongest results were observed on chromosomes 3 (fasting C-peptide/glucose: maximum LOD score MLS = 3.13 at 53.0 cM) and 13 (body-mass index: MLS = 3.28 at 5.0 cM). In nondiabetic individuals, the strongest results were observed on chromosomes 10 (acute insulin response: MLS = 3.11 at 21.0 cM), 13 (2-h insulin: MLS = 2.86 at 65.5 cM), and 17 (fasting insulin/glucose ratio: MLS = 3.20 at 9.0 cM). In several cases, there was evidence for overlapping signals between diabetic and nondiabetic individuals; therefore we performed joint analyses. In these joint analyses, we observed strong signals for chromosomes 3 (body-mass index: MLS = 3.43 at 59.5 cM), 17 (empirical insulin-resistance index: MLS = 3.61 at 0.0 cM), and 19 (empirical insulin-resistance index: MLS = 2.80 at 74.5 cM). Integrating genome-scan results from the companion article by Ghosh et al., we identify several regions that may harbor susceptibility genes for type 2 diabetes in the Finnish population.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
Patients' expectations can influence antibiotic prescription by primary healthcare physicians. We assessed knowledge, attitude and practices towards antibiotic use for upper respiratory tract ...infections (URTIs), and whether knowledge is associated with increased expectations for antibiotics among patients visiting primary healthcare services in Singapore.
Data was collected through a cross-sectional interviewer-assisted survey of patients aged ≥21 years waiting to see primary healthcare practitioners for one or more symptoms suggestive of URTI (cough, sore throat, runny nose or blocked nose) for 7 days or less, covering the demographics, presenting symptoms, knowledge, attitudes, beliefs and practices of URTI and associated antibiotic use. Univariate and multivariate logistic regression was used to assess independent factors associated with patients' expectations for antibiotics.
Nine hundred fourteen out of 987 eligible patients consulting 35 doctors were recruited from 24 private sector primary care clinics in Singapore. A third (307/907) expected antibiotics, of which a substantial proportion would ask the doctor for antibiotics (121/304, 40 %) and/or see another doctor (31/304, 10 %) if antibiotics were not prescribed. The majority agreed "antibiotics are effective against viruses" (715/914, 78 %) and that "antibiotics cure URTI faster" (594/912, 65 %). Inappropriate antibiotic practices include "keeping antibiotics stock at home" (125/913, 12 %), "taking leftover antibiotics" (114/913, 14 %) and giving antibiotics to family members (62/913, 7 %). On multivariate regression, the following factors were independently associated with wanting antibiotics (odds ratio; 95 % confidence interval): Malay ethnicity (1.67; 1.00-2.79), living in private housing (1.69; 1.13-2.51), presence of sore throat (1.50; 1.07-2.10) or fever (1.46; 1.01-2.12), perception that illness is serious (1.70; 1.27-2.27), belief that antibiotics cure URTI faster (5.35; 3.76-7.62) and not knowing URTI resolves on its own (2.18; 1.08-2.06), while post-secondary education (0.67; 0.48-0.94) was inversely associated. Those with lower educational levels were significantly more likely to have multiple misconceptions about antibiotics.
Majority of patients seeking primary health care in Singapore are misinformed about the role of antibiotics in URTI. Agreeing with the statement that antibiotics cure URTI faster was most strongly associated with wanting antibiotics. Those with higher educational levels were less likely to want antibiotics, while those with lower educational levels more likely to have incorrect knowledge.
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DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Despite advancements in medical care, hip fractures impose a significant
burden on individuals and healthcare systems. This paper focuses on the
prediction of hip fracture risk in older and ...middle-aged adults, where falls
and compromised bone quality are predominant factors. We propose a novel staged
model that combines advanced imaging and clinical data to improve predictive
performance. By using CNNs to extract features from hip DXA images, along with
clinical variables, shape measurements, and texture features, our method
provides a comprehensive framework for assessing fracture risk. A staged
machine learning-based model was developed using two ensemble models: Ensemble
1 (clinical variables only) and Ensemble 2 (clinical variables and DXA imaging
features). This staged approach used uncertainty quantification from Ensemble 1
to decide if DXA features are necessary for further prediction. Ensemble 2
exhibited the highest performance, achieving an AUC of 0.9541, an accuracy of
0.9195, a sensitivity of 0.8078, and a specificity of 0.9427. The staged model
also performed well, with an AUC of 0.8486, an accuracy of 0.8611, a
sensitivity of 0.5578, and a specificity of 0.9249, outperforming Ensemble 1,
which had an AUC of 0.5549, an accuracy of 0.7239, a sensitivity of 0.1956, and
a specificity of 0.8343. Furthermore, the staged model suggested that 54.49% of
patients did not require DXA scanning. It effectively balanced accuracy and
specificity, offering a robust solution when DXA data acquisition is not always
feasible. Statistical tests confirmed significant differences between the
models, highlighting the advantages of the advanced modeling strategies. Our
staged approach could identify individuals at risk with a high accuracy but
reduce the unnecessary DXA scanning. It has great promise to guide
interventions to prevent hip fractures with reduced cost and radiation.
Automated chemical synthesis carries great promises of safety, efficiency and reproducibility for both research and industry laboratories. Current approaches are based on specifically-designed ...automation systems, which present two major drawbacks: (i) existing apparatus must be modified to be integrated into the automation systems; (ii) such systems are not flexible and would require substantial re-design to handle new reactions or procedures. In this paper, we propose a system based on a robot arm which, by mimicking the motions of human chemists, is able to perform complex chemical reactions without any modifications to the existing setup used by humans. The system is capable of precise liquid handling, mixing, filtering, and is flexible: new skills and procedures could be added with minimum effort. We show that the robot is able to perform a Michael reaction, reaching a yield of 34%, which is comparable to that obtained by a junior chemist (undergraduate student in Chemistry).
The aim of this paper is to design a deep learning-based model to predict proximal femoral strength using multi-view information fusion. Method: We developed new models using multi-view variational ...autoencoder (MVAE) for feature representation learning and a product of expert (PoE) model for multi-view information fusion. We applied the proposed models to an in-house Louisiana Osteoporosis Study (LOS) cohort with 931 male subjects, including 345 African Americans and 586 Caucasians. With an analytical solution of the product of Gaussian distribution, we adopted variational inference to train the designed MVAE-PoE model to perform common latent feature extraction. We performed genome-wide association studies (GWAS) to select 256 genetic variants with the lowest p-values for each proximal femoral strength and integrated whole genome sequence (WGS) features and DXA-derived imaging features to predict proximal femoral strength. Results: The best prediction model for fall fracture load was acquired by integrating WGS features and DXA-derived imaging features. The designed models achieved the mean absolute percentage error of 18.04%, 6.84% and 7.95% for predicting proximal femoral fracture loads using linear models of fall loading, nonlinear models of fall loading, and nonlinear models of stance loading, respectively. Compared to existing multi-view information fusion methods, the proposed MVAE-PoE achieved the best performance. Conclusion: The proposed models are capable of predicting proximal femoral strength using WGS features and DXA-derived imaging features. Though this tool is not a substitute for FEA using QCT images, it would make improved assessment of hip fracture risk more widely available while avoiding the increased radiation dosage and clinical costs from QCT.
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